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1. Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes

Author

Aniket Mishra, Tomáš Paus, Alexa S. Beiser, Sudha Seshadri, Ami Tsuchida, Christophe Tzourio, Hieab H.H. Adams, Stéphanie Debette, Fabrice Crivello, Bernard Mazoyer, Charles DeCarli, Quentin Le Grand, Joshua C. Bis, Melissa Macalli, Alexandre Laurent, Aicha Soumare, Baljeet Singh, Evan Fletcher, Muralidharan Sargurupremraj, Jean Shin, Claudia L. Satizabal, Mark Lathrop, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Clinical Genetics, and Radiology & Nuclear Medicine

Subjects
Aging, Epidemiology, Caudate nucleus, Disease, Neurodegenerative, 0302 clinical medicine, 80 and over, 2.1 Biological and endogenous factors, Aetiology, Young adult, Aged, 80 and over, 0303 health sciences, Putamen, Brain, Organ Size, Genomics, Magnetic Resonance Imaging, Neurological, Mental health, Adult, 1.1 Normal biological development and functioning, Cognitive Neuroscience, Longevity, Life course approach, Biology, Genetic correlation, Article, 03 medical and health sciences, Neuroimaging, Underpinning research, Genetics, medicine, Humans, Dementia, Radiology, Nuclear Medicine and imaging, Biological Psychiatry, Aged, 030304 developmental biology, Genetic association, Prevention, Human Genome, Neurosciences, medicine.disease, Subcortical volumes, Lifecourse approach, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Neurology (clinical), Neuroscience, 030217 neurology & neurosurgery
Abstract

Background Subcortical brain structures play a key role in pathological processes of age-related neurodegenerative disorders. Mounting evidence also suggests that early-life factors may have an impact on the development of common late-life neurological diseases, including genetic factors that can influence both brain maturation and neurodegeneration. Methods Using large population-based brain imaging datasets across the lifespan (N 40,628) we aimed to: (i) estimate the heritability of subcortical volumes in young ( 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ), middle (35-65), and older age (65+), and their genetic correlation across age groups; (ii) identify whether genetic loci associated with subcortical volumes in older persons also show associations in early adulthood, and explore underlying genes using transcriptome-wide association studies; (iii) explore their association with neurological phenotypes. Results Heritability of subcortical volumes consistently decreased with increasing age. Genetic risk scores for smaller caudate nucleus, putamen and hippocampus volume in older adults were associated with smaller volumes in young adults. Individually, ten loci associated with subcortical volumes in older adults also showed associations in young adults. Within these loci, transcriptome-wide association studies showed that expression of several genes in brain tissues (especially MYLK2 and TUFM) was associated with subcortical volumes in both age-groups. One risk variant for smaller caudate nucleus volume (TUFM locus) was associated with lower cognitive performance. Genetically-predicted Alzheimer’s disease was associated with smaller subcortical volumes in middle and older age. Conclusions Our findings provide novel insights into the genetic determinants of subcortical volumes across the lifespan. More studies are needed to decipher the underlying biology and clinical impact.

Published
2022

2. Neural correlates of orbital telorism

Author

Meike W. Vernooij, Maria J. Knol, Mikolaj A. Pawlak, M. Arfan Ikram, Tavia E. Evans, Hieab H.H. Adams, Clinical Genetics, Epidemiology, and Radiology & Nuclear Medicine

Subjects
medicine.medical_specialty, Brain development, Cognitive Neuroscience, Population, Experimental and Cognitive Psychology, Neuropsychological Tests, Grey matter, Biology, Audiology, Fluid intelligence, Cognition, Hypotelorism, medicine, Humans, Purdue Pegboard Test, Gray Matter, Hypertelorism, education, education.field_of_study, Neural correlates of consciousness, medicine.diagnostic_test, Anomaly (natural sciences), Brain, Magnetic resonance imaging, medicine.disease, Magnetic Resonance Imaging, Frontal Lobe, Neuropsychology and Physiological Psychology, medicine.anatomical_structure, medicine.symptom, Psychology
Abstract

Orbital telorism, the interocular distance, is a clinically informative and in extremes is considered a minor physical anomaly. While its extremes, hypo- and hypertelorism, have been linked to disorders often related to cognitive ability, little is known about the neural correlates of normal variation of telorism within the general population. We derived measures of orbital telorism from cranial magnetic resonance imaging (MRI) by calculating the distance between the eyeball center of gravity in two population-based datasets (N=5,653, N=29,824, Mean age 64.66, 63.75 years). This measure was found to be related grey matter tissue density within numerous regions of the brain, including, but surprisingly not limited to, the frontal regions, in both positive and negative directions. Additionally, telorism was related to several cognitive functions, such as Perdue Pegboard test (Beta, P-value, (CI95%) −0.02, 1.63×10-7(−0.03;-0.01)) and fluid intelligence (0.02, 4.75×10-06(0.01:0.02)), with some relationships driven by individuals with a smaller orbital telorism. This is reflective of the higher prevalence of hypo-telorism in developmental disorders, specifically those that accompany lower cognitive lower functioning. This study suggests, despite previous links only made in clinical extremes, that orbital telorism holds some relation to structural brain development and cognitive function in the general population. This relationship is likely driven by shared developmental periods.

Published
2021

3. GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

Author

Arno van Hilten, Manfred Kayser, Gennady V. Roshchupkin, Wiro J. Niessen, Hieab H.H. Adams, Caroline C W Klaver, Steven A. Kushner, M. Arfan Ikram, Radiology & Nuclear Medicine, Psychiatry, Genetic Identification, Epidemiology, Clinical Genetics, and Ophthalmology

Subjects
Population genetics, Epidemiology, Computer science, QH301-705.5, Schizophrenia (object-oriented programming), Medicine (miscellaneous), Computational biology, Article, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], General Biochemistry, Genetics and Molecular Biology, Population genomics, Novel gene, Deep Learning, SDG 3 - Good Health and Well-being, Machine learning, Humans, Biology (General), Artificial neural network, business.industry, Deep learning, Genetic data, Phenotype, Genetic architecture, Neural Networks, Computer, Artificial intelligence, General Agricultural and Biological Sciences, business, Software
Abstract

Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically plausible connections. We applied the framework to seventeen phenotypes and found well-replicated genes such as HERC2 and OCA2 for hair and eye color, and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases., van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases.

Published
2021

4. Genetic architecture of orbital telorism

Author

Hieab H.H. Adams, Edith Hofer, M. Arfan Ikram, Lukas Pirpamer, Natalie Terzikhan, Meike W. Vernooij, Tavia E. Evans, Caroline C W Klaver, Sander Lamballais, Ziyi Xiong, Reinhold Schmidt, Mikolaj A Pawlak, Maria J. Knol, Manfred Kayser, Epidemiology, Clinical Genetics, Genetic Identification, Ophthalmology, and Radiology & Nuclear Medicine

Subjects
Intraclass correlation, Population, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], 03 medical and health sciences, 0302 clinical medicine, Hypotelorism, Genetics, medicine, Humans, Hypertelorism, education, Molecular Biology, Genetics (clinical), 030304 developmental biology, Genetic association, 0303 health sciences, education.field_of_study, Reproducibility of Results, General Medicine, Heritability, medicine.disease, Genetic architecture, Genetic Loci, Evolutionary biology, medicine.symptom, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Contains fulltext : 251528.pdf (Publisher’s version ) (Open Access) The interocular distance, or orbital telorism, is a distinctive craniofacial trait that also serves as a clinically informative measure. While its extremes, hypo- and hypertelorism, have been linked to monogenic disorders and are often syndromic, little is known about the genetic determinants of interocular distance within the general population. We derived orbital telorism measures from cranial magnetic resonance imaging by calculating the distance between the eyeballs' centre of gravity, which showed a good reproducibility with an intraclass correlation coefficient of 0.991 (95% confidence interval 0.985-0.994). Heritability estimates were 76% (standard error = 12%) with a family-based method (N = 364) and 39% (standard error = 2.4%) with a single nucleotide polymorphism-based method (N = 34 130) and were unaffected by adjustment for height (model II) and intracranial volume (model III) or head width (model IV). Genome-wide association studies in 34 130 European individuals identified 56 significantly associated genomic loci (P

Published
2022

5. Association of Serum Neurofilament Light Chain Concentration and MRI Findings in Older Adults: The Cardiovascular Health Study

Author

Alison E. Fohner, Traci M. Bartz, Russell P. Tracy, Hieab H.H. Adams, Joshua C. Bis, Luc Djousse, Claudia L. Satizabal, Oscar L. Lopez, Sudha Seshadri, Kenneth J. Mukamal, Lewis H. Kuller, Bruce M. Psaty, W.T. Longstreth, and Clinical Genetics

Subjects
Male, Neurofilament Proteins, Skull, Intermediate Filaments, Humans, Female, Longitudinal Studies, Neurology (clinical), Magnetic Resonance Imaging, White Matter, Biomarkers, Research Article, Aged
Abstract

Background and ObjectivesNeurofilament light chain (NfL) in blood is a sensitive but nonspecific marker of brain injury. This study sought to evaluate associations between NfL concentration and MRI findings of vascular brain injury in older adults.MethodsA longitudinal cohort study included 2 cranial MRI scans performed about 5 years apart and assessed for white matter hyperintensities (WMH) and infarcts. About 1 year before their second MRI, 1,362 participants (median age 77 years, 61.4% women) without a history of TIA or stroke had measurement of 4 biomarkers: NfL, total tau, glial fibrillary acidic protein (GFAP), and ubiquitin carboxyl-terminal hydrolase L1. Most (n = 1,279) also had the first MRI scan, and some (n = 633) had quantitative measurements of hippocampal and WMH. In primary analyses, we assessed associations of NfL with a 10-point white matter grade (WMG) and prevalent infarcts on second MRI and with worsening WMG and incident infarct comparing the 2 scans. A p value ResultsIn fully adjusted models, log2(NfL) concentration was associated with WMG (β = 0.27; p = 2.3 × 10−4) and worsening WMG (relative risk [RR] 1.24; p = 0.0022), but less strongly with prevalent brain infarcts (RR 1.18; p = 0.013) and not with incident brain infarcts (RR 1.18; p = 0.18). Associations were also present with WMH volume (β = 2,242.9, p = 0.0036). For the other 3 biomarkers, the associations for log2 (GFAP) concentration with WMG and worsening WMG were significant.DiscussionAmong older adults without a history of stroke, higher serum NfL concentration was associated with covert MRI findings of vascular brain injury, especially the burden of WMH and its worsening. Whether these results offer opportunities for the use of NfL as a noninvasive biomarker of WMH or to control vascular risk factors remains to be determined.

Published
2022

6. Migraine Genetic Variants Influence Cerebral Blood Flow

Author

Ke-xin Wen, Meike W. Vernooij, Daniel Bos, M. Kamran Ikram, M. Arfan Ikram, Maria J. Knol, Hieab H.H. Adams, Elizabeth Loehrer, Epidemiology, Radiology & Nuclear Medicine, Neurology, and Clinical Genetics

Subjects
Male, medicine.medical_specialty, Migraine Disorders, Population, Hemodynamics, perfusion imaging, brain imaging, Research Submissions, Cohort Studies, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Internal medicine, medicine.artery, Basilar artery, Medicine, Humans, genetics, Genetic Predisposition to Disease, 030212 general & internal medicine, education, Genetic Association Studies, Genetic association, Aged, Netherlands, education.field_of_study, business.industry, Genetic Variation, Blood flow, Middle Aged, medicine.disease, regional blood flow, Magnetic Resonance Imaging, Research Submission, Carotid Arteries, Neurology, Cerebral blood flow, Migraine, Basilar Artery, Cerebrovascular Circulation, Cardiology, Female, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract

textabstractObjective: To investigate the association of migraine genetic variants with cerebral blood flow (CBF). Background: Migraine is a common disorder with many genetic and non-genetic factors affecting its occurrence. The exact pathophysiological mechanisms underlying the disease remain unclear, but are known to involve hemodynamic and vascular disruptions. Recent genome-wide association studies have identified 44 genetic variants in 38 genetic loci that affect the risk of migraine, which provide the opportunity to further disentangle these mechanisms. Methods: We included 4665 participants of the population-based Rotterdam Study (mean age 65.0 ± 10.9 years, 55.6% women). Cross-sectional area (mm2), flow velocity (mm/s), and blood flow (mL/min) were measured in both carotids and the basilar artery using 2-dimensional phase-contrast magnetic resonance imaging. We analyzed 43 previously identified migraine variants separately and calculated a genetic risk score (GRS). To assess the association with CBF, we used linear regression models adjusted for age, sex, and total brain volume. Hierarchical clustering was performed based on the associations with CBF measures and tissue enrichment. Results: The rs67338227 risk allele was associated with higher flow velocity and smaller cross-sectional area in the carotids (Pminimum = 3.7 × 10−8). Other variants were related to CBF with opposite directions of effect, but not significantly after multiple testing adjustments (P

Published
2020

7. Gray Matter Age Prediction as a Biomarker for Risk of Dementia

Author

Gennady V. Roshchupkin, Meike W. Vernooij, Aleksei Tiulpin, M. Arfan Ikram, Hieab H.H. Adams, Marleen de Bruijne, Maria J. Knol, Johnny Wang, Florian Dubost, Wiro J. Niessen, Medical Informatics, Epidemiology, and Radiology & Nuclear Medicine

Subjects
Male, Risk, Oncology, medicine.medical_specialty, Logistic regression, Hippocampus, Rotterdam Study, Internal medicine, medicine, Humans, Dementia, Longitudinal Studies, Gray Matter, Aged, Proportional Hazards Models, Multidisciplinary, business.industry, Proportional hazards model, Hazard ratio, Odds ratio, Biological Sciences, Amygdala, medicine.disease, Magnetic Resonance Imaging, White Matter, Hyperintensity, Biomarker (medicine), Female, business, Biomarkers
Abstract

The gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as a biomarker for early-stage neurodegeneration. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link. We aimed to investigate the utility of such a gap as a risk biomarker for incident dementia using a deep learning approach for predicting brain age based on MRI-derived gray matter (GM). We built a convolutional neural network (CNN) model to predict brain age trained on 3,688 dementia-free participants of the Rotterdam Study (mean age 66 ± 11 y, 55% women). Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for age, sex, intracranial volume, GM volume, hippocampal volume, white matter hyperintensities, years of education, and APOE ε4 allele carriership. Additionally, we computed the attention maps, which shows which regions are important for age prediction. Logistic regression and Cox proportional hazard models showed that the age gap was significantly related to incident dementia (odds ratio [OR] = 1.11 and 95% confidence intervals [CI] = 1.05–1.16; hazard ratio [HR] = 1.11, and 95% CI = 1.06–1.15, respectively). Attention maps indicated that GM density around the amygdala and hippocampi primarily drove the age estimation. We showed that the gap between predicted and chronological brain age is a biomarker, complimentary to those that are known, associated with risk of dementia, and could possibly be used for early-stage dementia risk screening.

Published
2019

8. A functional variant in the miR‐142 promoter modulating its expression and conferring risk of Alzheimer disease

Author

Wenshi Wang, Saverio Bellusci, Stefan J. Erkeland, Bas Lendemeijer, Steven A. Kushner, Shashini T. Munshi, Kerstin Goth, Femke M.S. de Vrij, M. Arfan Ikram, Buyun Ma, Mohsen Ghanbari, Wilfred F. J. van IJcken, Denise E. Slump, Hieab H.H. Adams, Sakshi Bansal, Mirjam C G N van den Hout, Qiuwei Pan, Epidemiology, Psychiatry, Gastroenterology & Hepatology, Clinical Genetics, Radiology & Nuclear Medicine, Cell biology, and Immunology

Subjects
RNA, Untranslated, Induced Pluripotent Stem Cells, Locus (genetics), Biology, Hippocampus, Models, Biological, Polymorphism, Single Nucleotide, Cell Line, PICALM, Mice, 03 medical and health sciences, Neural Stem Cells, Alzheimer Disease, microRNA, Genetics, medicine, Animals, Humans, Genetic Predisposition to Disease, Promoter Regions, Genetic, Gene, Alleles, Genetic Association Studies, Genetics (clinical), Derepression, 030304 developmental biology, Mice, Knockout, Regulation of gene expression, 0303 health sciences, 030305 genetics & heredity, Chromosome Mapping, Computational Biology, Genetic Variation, medicine.disease, Disease Models, Animal, MicroRNAs, Gene Expression Regulation, Knockout mouse, RNA Interference, Alzheimer's disease, Genome-Wide Association Study
Abstract

Noncoding RNAs have been widely recognized as essential mediators of gene regulation. However, in contrast to protein-coding genes, much less is known about the influence of noncoding RNAs on human diseases. Here we examined the association of genetic variants located in primary microRNA sequences and long noncoding RNAs (lncRNAs) with Alzheimer disease (AD) by leveraging data from the largest genome-wide association meta-analysis of late-onset AD. Variants annotated to 5 miRNAs and 10 lncRNAs (in seven distinct loci) exceeded the Bonferroni-corrected significance threshold (p G) at the 17q22 locus annotated to two noncoding RNAs (MIR142 and BZRAP1-AS) was significantly associated with a reduced risk of AD and fulfilled predefined criteria for being a functional variant. Our functional genomic analyses revealed that rs2526377 affects the promoter activity and decreases the expression of miR-142. Moreover, differential expression analysis by RNA-Seq in human iPSC-derived neural progenitor cells and the hippocampus of miR-142 knockout mice demonstrated multiple target genes of miR-142 in the brain that are likely to be involved in the inflammatory and neurodegenerative manifestations of AD. These include TGFBR1 and PICALM, of which their derepression in the brain due to reduced expression levels of miR-142-3p may reduce the risk of AD.

Published
2019

9. 3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI

Author

Florian Dubost, M. Arfan Ikram, Hieab H.H. Adams, Marleen de Bruijne, Gerda Bortsova, Wiro J. Niessen, Meike W. Vernooij, Medical Informatics, Radiology & Nuclear Medicine, Epidemiology, and Neurology

Subjects
FOS: Computer and information sciences, Male, Computer science, Intraclass correlation, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Health Informatics, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Imaging, Three-Dimensional, Region of interest, Margin (machine learning), Image Interpretation, Computer-Assisted, Humans, Radiology, Nuclear Medicine and imaging, Aged, Aged, 80 and over, Radiological and Ultrasound Technology, Artificial neural network, business.industry, Deep learning, Reproducibility of Results, Pattern recognition, Middle Aged, Computer Graphics and Computer-Aided Design, Magnetic Resonance Imaging, Object detection, Regression, Random forest, Cerebral Small Vessel Diseases, Female, Computer Vision and Pattern Recognition, Artificial intelligence, Neural Networks, Computer, business, Glymphatic System, 030217 neurology & neurosurgery, Algorithms
Abstract

Enlarged perivascular spaces (EPVS) in the brain are an emerging imaging marker for cerebral small vessel disease, and have been shown to be related to increased risk of various neurological diseases, including stroke and dementia. Automatic quantification of EPVS would greatly help to advance research into its etiology and its potential as a risk indicator of disease. We propose a convolutional network regression method to quantify the extent of EPVS in the basal ganglia from 3D brain MRI. We first segment the basal ganglia and subsequently apply a 3D convolutional regression network designed for small object detection within this region of interest. The network takes an image as input, and outputs a quantification score of EPVS. The network has significantly more convolution operations than pooling ones and no final activation, allowing it to span the space of real numbers. We validated our approach using a dataset of 2000 brain MRI scans scored visually. Experiments with varying sizes of training and test sets showed that a good performance can be achieved with a training set of only 200 scans. With a training set of 1000 scans, the intraclass correlation coefficient (ICC) between our scoring method and the expert's visual score was 0.74. Our method outperforms by a large margin - more than 0.10 - four more conventional automated approaches based on intensities, scale-invariant feature transform, and random forest. We show that the network learns the structures of interest and investigate the influence of hyper-parameters on the performance. We also evaluate the reproducibility of our network using a set of 60 subjects scanned twice (scan-rescan reproducibility). On this set our network achieves an ICC of 0.93, while the intrarater agreement reaches 0.80. Furthermore, the automatic EPVS scoring correlates similarly to age as visual scoring.

Published
2019

10. Mapping the multicausality of Alzheimer’s disease through group model building

Author

Martin Dresler, Alfons G. Hoekstra, Etiënne A. J. A. Rouwette, Rick Quax, Edo Richard, Marcel G. M. Olde Rikkert, Marcel M. Verbeek, Inge M. C. M. de Kok, Isabelle F. van der Velpen, Eddy A. van der Zee, Ondine van de Rest, Jeroen F. Uleman, Dick H. J. Thijssen, Hieab H.H. Adams, Ben Schmand, René J. F. Melis, Jeroen de Bresser, Radiology & Nuclear Medicine, Epidemiology, Clinical Genetics, Public Health, Van der Zee lab, Computational Science Lab (IVI, FNWI), Psychology Other Research (FMG), and FMG

Subjects
0301 basic medicine, Aging, Alzheimer`s disease Donders Center for Medical Neuroscience [Radboudumc 1], Systems thinking, Process (engineering), Causal loop diagram, Vascular damage Radboud Institute for Health Sciences [Radboudumc 16], Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], Disease, Scientific literature, Healthcare improvement science Radboud Institute for Health Sciences [Radboudumc 18], 03 medical and health sciences, 0302 clinical medicine, Alzheimer Disease, Risk Factors, Group model building, 130 000 Cognitive Neurology & Memory, Humans, Centrality, Cognitive Dysfunction, Cognitive decline, VLAG, Complexity, Alzheimer's disease, Disorders of movement Donders Center for Medical Neuroscience [Radboudumc 3], R1, Nutritional Biology, 030104 developmental biology, Multicausal, RC0321, Original Article, Geriatrics and Gerontology, Psychology, Psychosocial, Alzheimer’s disease, 030217 neurology & neurosurgery, Cognitive psychology
Abstract

Alzheimer’s disease (AD) is a complex, multicausal disorder involving several spatiotemporal scales and scientific domains. While many studies focus on specific parts of this system, the complexity of AD is rarely studied as a whole. In this work, we apply systems thinking to map out known causal mechanisms and risk factors ranging from intracellular to psychosocial scales in sporadic AD. We report on the first systemic causal loop diagram (CLD) for AD, which is the result of an interdisciplinary group model building (GMB) process. The GMB was based on the input of experts from multiple domains and all proposed mechanisms were supported by scientific literature. The CLD elucidates interaction and feedback mechanisms that contribute to cognitive decline from midlife onward as described by the experts. As an immediate outcome, we observed several non-trivial reinforcing feedback loops involving factors at multiple spatial scales, which are rarely considered within the same theoretical framework. We also observed high centrality for modifiable risk factors such as social relationships and physical activity, which suggests they may be promising leverage points for interventions. This illustrates how a CLD from an interdisciplinary GMB process may lead to novel insights into complex disorders. Furthermore, the CLD is the first step in the development of a computational model for simulating the effects of risk factors on AD. Electronic supplementary material The online version of this article (10.1007/s11357-020-00228-7) contains supplementary material, which is available to authorized users.

Published
2021

11. Circulating metabolites are associated with brain atrophy and white matter hyperintensities

Author

Frederik Barkhof, Thomas Hankemeier, Philip Scheltens, Aad van der Lugt, Cornelia M. van Duijn, Carel F.W. Peeters, Francisca A. de Leeuw, M. Arfan Ikram, Dina Vojinovic, Najaf Amin, Hieab H.H. Adams, Charlotte E. Teunissen, Daniel Bos, Shahzad Ahmad, Meike W. Vernooij, Betty M. Tijms, Wiesje M. van der Flier, Maartje I. Kester, Hata Karamujić-Čomić, Neurology, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Neuroscience - Brain Imaging, Epidemiology and Data Science, Radiology and nuclear medicine, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Neuroinfection & -inflammation, Laboratory Medicine, APH - Methodology, APH - Personalized Medicine, Epidemiology, Clinical Genetics, and Radiology & Nuclear Medicine

Subjects
Blood Glucose, Male, magnetic resonance imaging (MRI), Epidemiology, Hippocampus, chemistry.chemical_compound, 0302 clinical medicine, High-density lipoprotein, 030212 general & internal medicine, HDL particle, glucose, medicine.diagnostic_test, Health Policy, Brain, Alzheimer's disease, Middle Aged, Magnetic Resonance Imaging, White Matter, Hippocampal atrophy, 3. Good health, Psychiatry and Mental health, Female, medicine.medical_specialty, Intervention trials, lipids, 03 medical and health sciences, Cellular and Molecular Neuroscience, Atrophy, SDG 3 - Good Health and Well-being, Developmental Neuroscience, Alzheimer Disease, Internal medicine, medicine, Humans, Aged, Featured Articles, business.industry, Cholesterol, cholesterol, Magnetic resonance imaging, Featured Article, medicine.disease, Hyperintensity, Endocrinology, chemistry, Neurology (clinical), Geriatrics and Gerontology, business, metabolism, 030217 neurology & neurosurgery
Abstract

Introduction: Our aim was to study whether systemic metabolites are associated with magnetic resonance imaging (MRI) measures of brain and hippocampal atrophy and white matter hyperintensities (WMH). Methods: We studied associations of 143 plasma-based metabolites with MRI measures of brain and hippocampal atrophy and WMH in three independent cohorts (n = 3962). We meta-analyzed the results of linear regression analyses to determine the association of metabolites with MRI measures. Results: Higher glucose levels and lower levels of three small high density lipoprotein (HDL) particles were associated with brain atrophy. Higher glucose levels were associated with WMH. Discussion: Glucose levels were associated with brain atrophy and WMH, and small HDL particle levels were associated with brain atrophy. Circulating metabolites may aid in developing future intervention trials.

Published
2021
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12. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Author

Kai-How Farh, Caleb Webber, Albert Hofman, George McMahon, Nicholas G. Martin, Paul M. Ridker, Lynn Cherkas, Mart Kals, Dorret I. Boomsma, George Davey Smith, Verneri Anttila, Tune H. Pers, Bertram Müller-Myhsok, Ville Artto, Benjamin M. Neale, Ester Cuenca-León, Anine H. Stam, Christopher Sivert Nielsen, Hieab H.H. Adams, Guntram Borck, Andres Metspalu, Maria Gudlaug Hrafnsdottir, Martin Dichgans, Reedik Mägi, Hailiang Huang, Daniel I. Chasman, Elizabeth Loehrer, John-Anker Zwart, Thomas Meitinger, Markus Färkkilä, Cornelia M. van Duijn, Arn M. J. M. van den Maagdenberg, Evie Stergiakouli, Johan G. Eriksson, Kauko Heikkilä, Hreinn Stefansson, Nicholas A. Furlotte, Minna Männikkö, Nicholas Eriksson, Jaakko Kaprio, David P. Strachan, Juho Wedenoja, Zameel M. Cader, Scott G. Gordon, Brenda W.J.H. Penninx, Linda M. Pedersen, Olli T. Raitakari, Phil Lee, André G. Uitterlinden, Ann-Louise Esserlind, Tobias Kurth, Arpo Aromaa, Priit Palta, Jes Olesen, Audun Stubhaug, Antti-Pekka Sarin, Andres Ingason, Stefan Schreiber, Salli Vepsäläinen, Hartmut Göbel, Kalle Pärn, Jouke-Jan Hottenga, Kari Stefansson, Bendik S. Winsvold, Markku Koiranen, Tim D. Spector, Evelin Mihailov, Mikko Muona, Marjo-Riitta Järvelin, Cynthia Sandor, Anne Francke Christensen, Lude Franke, Grant W. Montgomery, Tobias Freilinger, Caroline Ran, Thomas Werge, Maija Wessman, David A. Hinds, Lannie Ligthart, Terho Lehtimäki, Lili Milani, Mari A. Kaunisto, Lydia Quaye, Andrea Carmine Belin, Eija Hamalainen, M. Arfan Ikram, Veikko Salomaa, Mark J. Daly, Dale R. Nyholt, Pamela A. F. Madden, Andrew C. Heath, Tõnu Esko, Rainer Malik, Gisela M. Terwindt, Mitja I. Kurki, Aarno Palotie, Thomas Hansen, Padhraig Gormley, Michel D. Ferrari, Susan M. Ring, Julie E. Buring, Christian Kubisch, Mikko Kallela, Andrea Byrnes, Stacy Steinberg, Jie Huang, Markus Schürks, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Stem Cell Aging Leukemia and Lymphoma (SALL), Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, EMGO - Mental health, Internal Medicine, Epidemiology, Neurology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, Biological Psychology, and Complex Trait Genetics

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), SMOOTH-MUSCLE-CELLS, Medizin, Genome-wide association study, Disease, Bioinformatics, Genome-wide association studies, 0302 clinical medicine, Familial hemiplegic migraine, GENE-EXPRESSION, Genetics, Genetics & Heredity, FAMILIAL HEMIPLEGIC MIGRAINE, International Headache Genetics Consortium, SINGLE-NUCLEOTIDE POLYMORPHISMS, 11 Medical And Health Sciences, Genomics, SDG 10 - Reduced Inequalities, 3. Good health, Migranya, Cortical spreading depression, SPREADING DEPRESSION, Life Sciences & Biomedicine, Gens, Genetic Markers, Migraine Disorders, Locus (genetics), Single-nucleotide polymorphism, Biology, GENOTYPE IMPUTATION, Polymorphism, Single Nucleotide, 03 medical and health sciences, medicine, SYSTEMATIC ANALYSIS, Humans, Genetic Predisposition to Disease, Vascular Diseases, GENOME-WIDE ASSOCIATION, Migraine, Science & Technology, Case-control study, Muscle, Smooth, 06 Biological Sciences, medicine.disease, 030104 developmental biology, Genes, MYOCARDIAL-INFARCTION, Genetic Loci, Case-Control Studies, RECEPTOR-RELATED PROTEIN-1, 030217 neurology & neurosurgery, Developmental Biology, Genome-Wide Association Study
Abstract

Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association ( GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms ( SNPs) significantly associated with migraine risk ( P

Published
2020

13. Stroke

Author

Paul M. Thompson, Joshua C. Bis, Julian N. Trollor, Siggi Siggurdsson, Leonie Lampe, Piyush Gampawar, Myriam Fornage, Neda Jahanshad, Dina Vojinovic, Jiyang Jiang, Christophe Tzourio, Helena Schmidt, Shuo Li, Ian J. Deary, Lewis C. Becker, Karen A. Mather, Najaf Amin, Rui Xia, Bernard Mazoyer, Arno Villringer, Albert V. Smith, Henry Brodaty, Jeroen van der Grond, Vilmundur Gudnason, Rainer Malik, Christine Fennema-Notestine, Brian G. Kral, Asta Håberg, Clinton B. Wright, David C. Liewald, Sudha Seshadri, Claudia L. Satizabal, Bruce M. Psaty, Ralph L. Sacco, Reinhold Schmidt, Lisa R. Yanek, Mark Jenkinson, Qiong Yang, Jose R. Romero, Fidel Alfaro-Almagro, Philippe Amouyel, Margaret J. Wright, William T. Longstreth, Muralidharan Sargurupremraj, Mark E. Bastin, John B.J. Kwok, M. Arfan Ikram, David J. Stott, Nicole Dueker, Lukas Pirpamer, Perminder S. Sachdev, Stéphanie Debette, Edith Hofer, Ludovica Griffanti, Alexa S. Beiser, Nicola J. Armstrong, Stephen M. Smith, Lloyd T. Elliott, Wei Wen, J. Wouter Jukema, William S. Kremen, Markus Scholz, Anbupalam Thalamuthu, Peter R. Schofield, Clifford R. Jack, Stella Trompet, Gennady V. Roshchupkin, Matthias L. Schroeter, Joanna M. Wardlaw, Thomas H. Mosley, Michelle Luciano, Lenore J. Launer, Meike W. Vernooij, Maria J. Knol, Pauline Maillard, Charles DeCarli, Jonathan Marchini, Rebecca F. Gottesman, Paul A. Nyquist, Martin Dichgans, Zoe Morris, Cornelia M. van Duijn, David Ames, Veronica A. Witte, Hieab H.H. Adams, Mark A. Logue, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epidemiology, and Clinical Genetics

Subjects
Male, Aging, Cardiorespiratory Medicine and Haematology, 0302 clinical medicine, pathology [Brain], pathology [White Matter], 2.1 Biological and endogenous factors, risk factors, Aetiology, genetics [Genetic Predisposition to Disease], 0303 health sciences, neuroimaging, Middle Aged, White Matter, Cerebral Small Vessel Diseases, Stroke, medicine.anatomical_structure, VINTAGE, Neurological, Deep white matter hyperintensities, Female, diagnostic imaging [Cerebral Small Vessel Diseases], Cardiology and Cardiovascular Medicine, Cartography, white matter, Biotechnology, brain, Clinical Sciences, Article, diagnostic imaging [White Matter], White matter, 03 medical and health sciences, Clinical Research, Genetic variation, Genetics, Acquired Cognitive Impairment, medicine, Humans, Genetic Predisposition to Disease, ddc:610, HEALTHY, diagnostic imaging [Brain], 030304 developmental biology, Aged, Advanced and Specialized Nursing, Neurology & Neurosurgery, genome-wide association study, business.industry, Prevention, Human Genome, Neurosciences, Brain Disorders, Clinical neurology, Periventricular white matter hyperintensities, genetics [Cerebral Small Vessel Diseases], pathology [Cerebral Small Vessel Diseases], Dementia, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Neurology (clinical), business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Background and Purpose: Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. Methods: Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. Results: In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 ( NBEAL ), 10q23.1 ( TSPAN14/FAM231A ), and 10q24.33 ( SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 ( NOS3 ) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. Conclusions: Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

Published
2020

14. Global and regional development of the human cerebral cortex: Molecular architecture and occupational aptitudes

Author

M. Arfan Ikram, Lukas Pirpamer, Daniel E. Vosberg, Edith Hofer, David Ames, Sandra van der Auwera-Palitschka, Zdenka Pausova, Xueqiu Jian, Henry Brodaty, André M. M. Sousa, Linda Ding, Tavia E. Evans, William S. Kremen, Jean Shin, Steven Tilley, Fabrice Crivello, Christophe Tzourio, Karen A. Mather, Peter R. Schofield, Joanna M. Wardlaw, Joshua C. Bis, Tomáš Paus, Bernard Mazoyer, Myriam Fornage, Thomas H. Mosley, Natalie Terzikhan, Nathan A. Gillespie, Hans J. Grabe, Michelle Luciano, Mathew A. Harris, Nenad Sestan, Wei Wen, Sherif Karama, Reinhold Schmidt, Shaojie Ma, Katharina Wittfeld, Lindsay B. Lewis, Arno Villringer, Hieab H.H. Adams, Sudha Seshadri, Neda Jahanshad, Jiyang Jiang, Sophie Maingault, Yasaman Saba, Qiong Yang, Frauke Beyer, Stéphanie Debette, Nicola J. Armstrong, Markus Scholz, Carol E. Franz, Margaret J. Wright, Shuo Li, Rebecca F. Gottesman, Aniket Mishra, Perminder S. Sachdev, Yash Patel, John B.J. Kwok, Anbupalam Thalamuthu, Helena Schmidt, Amaia Carrion-Castillo, Robin Bülow, Mark E. Bastin, Markus Loeffler, Ian E. Deary, Stefan Frenzel, Julian N. Trollor, Gennady V. Roshchupkin, A. Veronica Witte, Epidemiology, Medical Informatics, Radiology & Nuclear Medicine, Neurology, the ENIGMA Consortium, for the neuroCHARGE Working Group, and the neuroCHARGE Working Group

Subjects
rho GTP-Binding Proteins, Male, Aptitude, Genome-wide association study, brain development, cortical surface area, 0302 clinical medicine, Form perception, Intracranial volume, genetics [RNA-Binding Proteins], genetics [Form Perception], Visual Cortex, media_common, Cerebral Cortex, Aged, 80 and over, 0303 health sciences, Principal Component Analysis, Career Choice, Microfilament Proteins, genomeide association study, RNA-Binding Proteins, Gene Expression Regulation, Developmental, Cognition, growth & development [Visual Cortex], Middle Aged, medicine.anatomical_structure, VINTAGE, Cerebral cortex, growth & development [Cerebral Cortex], Original Article, Female, Adult, endocrine system, Adolescent, Cognitive Neuroscience, media_common.quotation_subject, tau Proteins, Biology, occupational aptitude, 03 medical and health sciences, Cellular and Molecular Neuroscience, Young Adult, Regional development, medicine, Humans, ddc:610, 030304 developmental biology, Genetic association, Aged, physiology [Aptitude], genome-wide association study, 9. Industry and infrastructure, cortical thickness, Brain Cortical Thickness, Form Perception, genetics [tau Proteins], genetics [rho GTP-Binding Proteins], genetics [Microfilament Proteins], Transcriptome, Neuroscience, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade—albeit in a very limited manner—to behaviors as complex as the choice of one’s occupation.

Published
2020

15. Polygenic Multiple Sclerosis Risk and Population-Based Childhood Brain Imaging

Author

Philip R. Jansen, R Q Hintzen, Tonya White, Meike W. Vernooij, Hieab H.H. Adams, Maria J. Knol, Vincent W. V. Jaddoe, Ryan L. Muetzel, Rinze F. Neuteboom, C. Louk de Mol, Human Genetics, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Neurology, Child and Adolescent Psychiatry / Psychology, Radiology & Nuclear Medicine, Epidemiology, Clinical Genetics, Erasmus MC other, Pediatrics, Human genetics, APH - Aging & Later Life, and APH - Mental Health

Subjects
0301 basic medicine, Oncology, Male, medicine.medical_specialty, Multifactorial Inheritance, Multiple Sclerosis, Genotype, Population, Neuroimaging, White matter, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Fractional anisotropy, medicine, Genetic predisposition, Humans, Genetic Predisposition to Disease, Brain/pathology, education, Child, Research Articles, education.field_of_study, business.industry, Multiple sclerosis, Genetic Predisposition to Disease/genetics, Brain, medicine.disease, Magnetic Resonance Imaging, 030104 developmental biology, medicine.anatomical_structure, Neurology, Multiple Sclerosis/genetics, Generation R, Female, Neurology (clinical), business, 030217 neurology & neurosurgery, Diffusion MRI, Research Article
Abstract

Objective: Multiple sclerosis (MS) is a neurological disease with a substantial genetic component and immune-mediated neurodegeneration. Patients with MS show structural brain differences relative to individuals without MS, including smaller regional volumes and alterations in white matter (WM) microstructure. Whether genetic risk for MS is associated with brain structure during early neurodevelopment remains unclear. In this study, we explore the association between MS polygenic risk scores (PRS) and brain imaging outcomes from a large, population-based pediatric sample to gain insight into the underlying neurobiology of MS. Methods: We included 8- to 12-year-old genotyped participants from the Generation R Study in whom T1-weighted volumetric (n = 1,136) and/or diffusion tensor imaging (n = 1,088) had been collected. PRS for MS were calculated based on a large genome-wide association study of MS (n = 41,505) and were regressed on regional volumes, global and tract-specific fractional anisotropy (FA), and global mean diffusivity using linear regression. Results: No associations were observed for the regional volumes. We observed a positive association between the MS PRS and global FA (β = 0.098, standard error [SE] = 0.030, p = 1.08 × 10 −3). Tract-specific analyses showed higher FA and lower radial diffusivity in several tracts. We replicated our findings in an independent sample of children (n = 186) who were scanned in an earlier phase (global FA; β = 0.189, SE = 0.072, p = 9.40 × 10 −3). Interpretation: This is the first study to show that greater genetic predisposition for MS is associated with higher global brain WM FA at an early age in the general population. Our results suggest a preadolescent time window within neurodevelopment in which MS risk variants act upon the brain. ANN NEUROL 2020;87:774–787.

Published
2020

16. Association of CD14 with incident dementia and markers of brain aging and injury

Author

Hieab H.H. Adams, Russell P. Tracy, Sudha Seshadri, Alexa S. Beiser, Jayandra J. Himali, Matthew P. Pase, Charles DeCarli, Alexander P. Reiner, Claudia L. Satizabal, Hugo J. Aparicio, Emer R. McGrath, Myriam Fornage, Joshua C. Bis, Daniel Levy, Bruce M. Psaty, Oscar L. Lopez, W. T. Longstreth, and Epidemiology

Subjects
Male, medicine.medical_specialty, Aging, Clinical Sciences, Lipopolysaccharide Receptors, Neurodegenerative, Cardiovascular, Alzheimer's Disease, Article, Framingham Heart Study, Atrophy, Clinical Research, Internal medicine, medicine, 80 and over, Acquired Cognitive Impairment, Dementia, Humans, Cognitive Dysfunction, Longitudinal Studies, Cognitive decline, Aged, Aged, 80 and over, Neurology & Neurosurgery, business.industry, Incidence (epidemiology), Incidence, Neurosciences, Brain, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Cognition, Middle Aged, medicine.disease, Confidence interval, Brain Disorders, Endophenotype, Neurological, Female, Cognitive Sciences, Neurology (clinical), business, Biomarkers
Abstract

ObjectiveTo test the hypothesis that the inflammatory marker plasma soluble CD14 (sCD14) associates with incident dementia and related endophenotypes in 2 community-based cohorts.MethodsOur samples included the prospective community-based Framingham Heart Study (FHS) and Cardiovascular Health Study (CHS) cohorts. Plasma sCD14 was measured at baseline and related to the incidence of dementia, domains of cognitive function, and MRI-defined brain volumes. Follow-up for dementia occurred over a mean of 10 years (SD 4) in the FHS and a mean of 6 years (SD 3) in the CHS.ResultsWe studied 1,588 participants from the FHS (mean age 69 ± 6 years, 47% male, 131 incident events) and 3,129 participants from the CHS (mean age 72 ± 5 years, 41% male, 724 incident events) for the risk of incident dementia. Meta-analysis across the 2 cohorts showed that each SD unit increase in sCD14 was associated with a 12% increase in the risk of incident dementia (95% confidence interval 1.03–1.23; p = 0.01) following adjustments for age, sex, APOE ε4 status, and vascular risk factors. Higher levels of sCD14 were associated with various cognitive and MRI markers of accelerated brain aging in both cohorts and with a greater progression of brain atrophy and a decline in executive function in the FHS.ConclusionsCD14 is an inflammatory marker related to brain atrophy, cognitive decline, and incident dementia.

Published
2020

17. Corticosteroids and Regional Variations in Thickness of the Human Cerebral Cortex across the Lifespan

Author

Leon French, Nadine Parker, Bernard Mazoyer, Anders M. Fjell, Henry Völzke, Reinhold Schmidt, Ian J. Deary, Perminder S. Sachdev, Aniket Mishra, Jean Shin, Kristine B. Walhovd, Norbert Hosten, Katharina Wittfeld, Qiong Yang, Gunter Schumann, Stéphanie Debette, Sudha Seshadri, Tomáš Paus, Claudia L. Satizabal, Simon R. Cox, Maria J. Knol, Hans J. Grabe, Jiyang Jiang, Hieab H.H. Adams, Henry Brodaty, Helena Schmidt, Stefan Frenzel, Zdenka Pausova, Giovanni Abrahão Salum, Wei Wen, Didac Vidal-Piñeiro, Mohammad Arfan Ikram, Epidemiology, Radiology & Nuclear Medicine, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Rotman Research Institute at the Baycrest Centre (RRI), Centre for Healthy Brain Ageing, University of New South Wales [Sydney] (UNSW), Groupe d'imagerie neurofonctionnelle (GIN), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Metacohorts Consortium, Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Institute for Community Medicine, Universität Greifswald - University of Greifswald, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), and University of Washington [Seattle]

Subjects
Male, Aging, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Gene Expression, 0302 clinical medicine, Glucocorticoid receptor, metabolism [Receptors, Mineralocorticoid], Gene expression, Child, metabolism [Receptors, Glucocorticoid], Aged, 80 and over, Cerebral Cortex, 0303 health sciences, Microglia, Human brain, Middle Aged, physiology [Aging], medicine.anatomical_structure, VINTAGE, Cerebral cortex, Child, Preschool, anatomy & histology [Cerebral Cortex], Corticosteroid, Female, Original Article, Glucocorticoid, medicine.drug, Adult, medicine.medical_specialty, Adolescent, medicine.drug_class, Cognitive Neuroscience, Biology, 03 medical and health sciences, Cellular and Molecular Neuroscience, Young Adult, Receptors, Glucocorticoid, Internal medicine, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], medicine, Humans, ddc:610, Gene, 030304 developmental biology, Aged, metabolism [Cerebral Cortex], Endocrinology, Receptors, Mineralocorticoid, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 030217 neurology & neurosurgery
Abstract

Exposures to life stressors accumulate across the lifespan, with possible impact on brain health. Little is known, however, about the mechanisms mediating age-related changes in brain structure. We use a lifespan sample of participants (n = 21 251; 4–97 years) to investigate the relationship between the thickness of cerebral cortex and the expression of the glucocorticoid- and the mineralocorticoid-receptor genes (NR3C1 and NR3C2, respectively), obtained from the Allen Human Brain Atlas. In all participants, cortical thickness correlated negatively with the expression of both NR3C1 and NR3C2 across 34 cortical regions. The magnitude of this correlation varied across the lifespan. From childhood through early adulthood, the profile similarity (between NR3C1/NR3C2 expression and thickness) increased with age. Conversely, both profile similarities decreased with age in late life. These variations do not reflect age-related changes in NR3C1 and NR3C2 expression, as observed in 5 databases of gene expression in the human cerebral cortex (502 donors). Based on the co-expression of NR3C1 (and NR3C2) with genes specific to neural cell types, we determine the potential involvement of microglia, astrocytes, and CA1 pyramidal cells in mediating the relationship between corticosteroid exposure and cortical thickness. Therefore, corticosteroids may influence brain structure to a variable degree throughout life.

Published
2020

18. Subregional volumes of the hippocampus in relation to cognitive function and risk of dementia

Author

M. Kamran Ikram, Meike W. Vernooij, Tavia E. Evans, Hieab H.H. Adams, Michael O'Sullivan, Frank J. Wolters, Aad van der Lugt, M. Arfan Ikram, Silvan Licher, Epidemiology, Radiology & Nuclear Medicine, and Neurology

Subjects
Male, 0301 basic medicine, medicine.medical_specialty, Cognitive Neuroscience, Population, Prodromal Symptoms, Neuroimaging, Hippocampal formation, Audiology, Hippocampus, Executive Function, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Image Processing, Computer-Assisted, Humans, Medicine, Dementia, Cognitive Dysfunction, education, Aged, education.field_of_study, business.industry, Hazard ratio, Subiculum, Cognition, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Cognitive test, 030104 developmental biology, nervous system, Neurology, Female, business, 030217 neurology & neurosurgery, Follow-Up Studies
Abstract

Background Total hippocampal volume has been consistently linked to cognitive function and dementia. Yet, given its complex and parcellated internal structure, the role of subregions of the hippocampus in cognition and risk of dementia remains relatively underexplored. We studied subregions of the hippocampus in a large population-based cohort to further understand their role in cognitive impairment and dementia risk. Methods We studied 5035 dementia- and stroke-free persons from the Rotterdam Study, aged over 45 years. All participants underwent magnetic resonance imaging (1.5 T) between 2005 and 2015. Automatic segmentation of the hippocampus and 12 of its subregions was performed using the FreeSurfer software (version 6.0). A cognitive test battery was performed, and participants were followed up for the development of dementia until 2015. Associations of hippocampal subregion volumes with cognition and incident dementia were examined using linear and Cox regression models, respectively. All analyses were adjusted for age, sex, education, and total hippocampal volume. Results Mean age was 64.3 years (SD 10.6) with 56% women. Smaller volumes of the hippocampal fimbria, presubiculum and subiculum showed the strongest associations with poor performance on several cognitive domains, including executive function but not memory. During a mean follow-up of 5.5 years, 76 persons developed dementia. Smaller subiculum volume was associated with risk of dementia adjusted for total volume (hazard ratio per SD decrease in volume: 1.75, 95% confidence interval 1.35; 2.26). Conclusions In a community-dwelling non-demented population, we describe patterns of association between hippocampal subregions with cognition and risk of dementia. Specifically, the subiculum was associated with both poorer cognition and higher risk of dementia.

Published
2018

19. Brain Volumes and Longitudinal Cognitive Change: A Population-based Study

Author

Wiro J. Niessen, Hieab H.H. Adams, Henning Tiemeier, Saira Saeed Mirza, Aad van der Lugt, Albert Hofman, Deepti Vibha, Meike W. Vernooij, Kameshwar Prasad, Mohammad Arfan Ikram, Epidemiology, Radiology & Nuclear Medicine, Child and Adolescent Psychiatry / Psychology, and Medical Informatics

Subjects
Male, 0301 basic medicine, medicine.medical_specialty, Population, Neuropsychological Tests, Audiology, Cohort Studies, White matter, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, medicine, Humans, Cognitive Dysfunction, Longitudinal Studies, Cognitive decline, education, Netherlands, education.field_of_study, medicine.diagnostic_test, business.industry, Brain, Magnetic resonance imaging, Cognition, Middle Aged, Magnetic Resonance Imaging, White Matter, Hyperintensity, Psychiatry and Mental health, Clinical Psychology, 030104 developmental biology, medicine.anatomical_structure, Population Surveillance, Brain size, Female, Geriatrics and Gerontology, business, Gerontology, 030217 neurology & neurosurgery
Abstract

Objective: To investigate the association of brain volumes, white matter lesion (WML) volumes, and lacunes, with cognitive decline in a population-based cohort of nondemented persons. Methods: Within the Rotterdam Study, 3624 participants underwent brain magnetic resonance imaging. Cognition was evaluated at baseline (2005 to 2009) and at the follow-up visit (2011 to 2013). We used a test battery that tapped into domains of executive function, information processing speed, motor speed, and memory. The volumetric measures assessed were total brain volume, lobar (gray matter and white matter) volumes, and hippocampal volumes. We also studied the association of WML volumes and lacunes with cognitive decline using linear regression models. Results: Total brain volume was associated with decline in global cognition, information processing, and motor speed (P

Published
2018

20. Enlarged perivascular spaces and cognition A meta-analysis of 5 population-based studies

Author

Henry Völzke, Edith Hofer, Hieab H.H. Adams, Norbert Hosten, Saima Hilal, Christopher Chen, Chuen Seng Tan, Meike W. Vernooij, Mohamad Habes, M. Arfan Ikram, Hans J. Grabe, Jill Abrigo, Narayanaswamy Venketasubramanian, Reinhold Schmidt, Vincent Mok, M. Kamran Ikram, Epidemiology, Radiology & Nuclear Medicine, and Neurology

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Population, Brain Edema, diagnostic imaging [Brain Edema], Neuropsychological Tests, diagnostic imaging [Cognition Disorders], Article, Community Health Planning, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Internal medicine, Centrum semiovale, medicine, Dementia, Humans, pathology [Cerebral Arteries], ddc:610, Cognitive decline, education, Aged, education.field_of_study, business.industry, complications [Brain Edema], etiology [Cognition Disorders], Cerebral Arteries, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Confidence interval, 030104 developmental biology, Study of Health in Pomerania, Meta-analysis, Female, Neurology (clinical), Cognition Disorders, business, 030217 neurology & neurosurgery
Abstract

ObjectiveTo investigate the association of enlarged perivascular spaces (ePVS) with cognition in elderly without dementia.MethodsWe included 5 studies from the Uniform Neuro-Imaging of Virchow-Robin Space Enlargement (UNIVRSE) consortium, namely the Austrian Stroke Prevention Family Study, Study of Health in Pomerania, Rotterdam Study, Epidemiology of Dementia in Singapore study, and Risk Index for Subclinical Brain Lesions in Hong Kong study. ePVS were counted in 4 regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) with harmonized rating across studies. Mini-Mental State Examination (MMSE) and general fluid cognitive ability factor (G-factor) were used to assess cognitive function. For each study, a linear regression model was performed to estimate the effect of ePVS on MMSE and G-factor. Estimates were pooled across studies with the use of inverse variance meta-analysis with fixed- or random-effect models when appropriate.ResultsThe final sample size consisted of 3,575 persons (age range 63.4–73.2 years, 50.6% women). Total ePVS counts were not significantly associated with MMSE score (mean difference per ePVS score increase 0.001, 95% confidence interval [CI] −0.007 to 0.008, p = 0.885) or G-factor (mean difference per ePVS score increase 0.002, 95% CI −0.001 to 0.006, p = 0.148) in age-, sex-, and education-adjusted models. Adjustments for cardiovascular risk factors and MRI markers did not change the results. Repeating the analyses with region-specific ePVS rendered similar results.ConclusionsIn this study, we found that ePVS counts were not associated with cognitive dysfunction in the general population. Future studies with longitudinal designs are warranted to examine whether ePVS contribute to cognitive decline.

Published
2018

21. Disentangling the biological pathways involved in early features of Alzheimer's disease in the Rotterdam Study

Author

Emily Baker, M. Arfan Ikram, Peter Holmans, Christian Bannister, Meike W. Vernooij, Sven J. van der Lee, Cornelia M. van Duijn, Shahzad Ahmad, Julie Williams, Hieab H.H. Adams, Valentina Escott-Price, Alfredo Ramirez, Dina Vojinovic, Najaf Amin, Rebecca Sims, Epidemiology, Radiology & Nuclear Medicine, and Neurology

Subjects
Male, 0301 basic medicine, Apolipoprotein E, Epidemiology, Disease, Bioinformatics, Hippocampus, Clathrin, Biological pathway, 03 medical and health sciences, Cellular and Molecular Neuroscience, Rotterdam Study, 0302 clinical medicine, Developmental Neuroscience, Alzheimer Disease, Risk Factors, Humans, Medicine, Cognitive Dysfunction, Prospective Studies, Aged, Netherlands, Aged, 80 and over, Framingham Risk Score, biology, business.industry, Health Policy, Brain, Middle Aged, Magnetic Resonance Imaging, White Matter, Endocytosis, Hyperintensity, Psychiatry and Mental health, 030104 developmental biology, Brain size, biology.protein, Female, Neurology (clinical), Geriatrics and Gerontology, business, 030217 neurology & neurosurgery
Abstract

Introduction: Exploring the role of Alzheimer's disease (AD) implicated pathways in the predementia phase may provide new insight for preventive and clinical trials targeting disease specific pathways. Methods: We constructed weighted Genetic risk scores, first based on 20 genome-wide significant AD risk variants and second clustering these variants within pathways. Risk scores were investigated for their association with AD, mild cognitive impairment, and brain magnetic resonance imaging phenotypes including white matter lesions, hippocampal volume, and brain volume. Results: The risk score capturing endocytosis pathway was significantly associated with mild cognitive impairment (P = 1.44 × 10−4). Immune response (P =.016) and clathrin/AP2 adaptor complex pathway (P = 3.55 × 10−3) excluding apolipoprotein E also showed modest association with white matter lesions but did not sustain Bonferroni correction (P = 9.09 × 10−4). Discussion: Our study suggests that the clinical spectrum of early AD pathology is explained by different biological pathways, in particular, the endocytosis, clathrin/AP2 adaptor complex, and immune response pathways, that are independent of apolipoprotein E (APOE).

Published
2018

22. Heritability and genome-wide associations studies of cerebral blood flow in the general population

Author

Oscar H. Franco, Gennady V. Roshchupkin, Albert V. Smith, Hieab H.H. Adams, Vilmundur Gudnason, Lenore J. Launer, Hazel I. Zonneveld, Meike W. Vernooij, André G. Uitterlinden, Cornelia M. van Duijn, Sigurdur Sigurdsson, M. Arfan Ikram, Epidemiology, Neurology, Radiology & Nuclear Medicine, and Internal Medicine

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Pathology, Population, Genome-wide association study, Biology, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine.artery, medicine, Basilar artery, Humans, education, Genetic association, Aged, Aged, 80 and over, education.field_of_study, medicine.diagnostic_test, Brain, Magnetic resonance imaging, Heritability, Middle Aged, medicine.disease, Magnetic Resonance Imaging, 030104 developmental biology, Cross-Sectional Studies, Neurology, Migraine, Cerebral blood flow, Cerebrovascular Circulation, Cardiology, Female, Neurology (clinical), Cardiology and Cardiovascular Medicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Cerebral blood flow is an important process for brain functioning and its dysregulation is implicated in multiple neurological disorders. While environmental risk factors have been identified, it remains unclear to what extent the flow is regulated by genetics. Here we performed heritability and genome-wide association analyses of cerebral blood flow in a population-based cohort study. We included 4472 persons free of cortical infarcts who underwent genotyping and phase-contrast magnetic resonance flow imaging (mean age 64.8 ± 10.8 years). The flow rate, cross-sectional area of the vessel, and flow velocity through the vessel were measured in the basilar artery and bilateral carotids. We found that the flow rate of the basilar artery is most heritable (h2 (SE) = 24.1 (9.8), p-value = 0.0056), and this increased over age. The association studies revealed two significant loci for the right carotid artery area (rs12546630, p-value = 2.0 × 10−8) and velocity (rs2971609, p-value = 1.4 × 10−8), with the latter showing a concordant effect in an independent sample (N = 1350, p-value = 0.057, meta-analyzed p-value = 2.5 × 10−9). These loci were also associated with other cerebral blood flow parameters below genome-wide significance, and rs2971609 lies in a known migraine locus. These findings establish that cerebral blood flow is under genetic control with potential relevance for neurological diseases.

Published
2018

23. Genetic susceptibility to multiple sclerosis: Brain structure and cognitive function in the general population

Author

Albert Hofman, Wiro J. Niessen, André G. Uitterlinden, Meike W. Vernooij, Gennady V. Roshchupkin, R Q Hintzen, Mohammad Arfan Ikram, Cornelia M. van Duijn, Hieab H.H. Adams, Epidemiology, Neurology, Radiology & Nuclear Medicine, Medical Informatics, and Internal Medicine

Subjects
Male, 0301 basic medicine, Multiple Sclerosis, Population, Bioinformatics, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, medicine, Genetic predisposition, Humans, Cognitive Dysfunction, Genetic Predisposition to Disease, education, Aged, Netherlands, education.field_of_study, Framingham Risk Score, medicine.diagnostic_test, Multiple sclerosis, Magnetic resonance imaging, Cognition, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Cognitive test, 030104 developmental biology, Neurology, Female, Neurology (clinical), Psychology, Neuroscience, 030217 neurology & neurosurgery
Abstract

Background: Multiple sclerosis (MS) affects brain structure and cognitive function and has a heritable component. Over a 100 common genetic risk variants have been identified, but most carriers do not develop MS. For other neurodegenerative diseases, risk variants have effects outside patient populations, but this remains uninvestigated for MS. Objectives: To study the effect of MS-associated genetic variants on brain structure and cognitive function in the general population. Methods: We studied middle-aged and elderly individuals (mean age = 65.7 years) from the population-based Rotterdam Study. We determined 107 MS variants and additionally created a risk score combining all variants. Magnetic resonance imaging ( N = 4710) was performed to obtain measures of brain macrostructure, white matter microstructure, and gray matter voxel-based morphometry. A cognitive test battery ( N = 7556) was used to test a variety of cognitive domains. Results: The MS risk score was associated with smaller gray matter volume over the whole brain (βstandardized = −0.016; p = 0.044), but region-specific analyses did not survive multiple testing correction. Similarly, no significant associations with brain structure were observed for individual variants. For cognition, rs2283792 was significantly associated with poorer memory (β = −0.064; p = 3.4 × 10−5). Conclusion: Increased genetic susceptibility to MS may affect brain structure and cognition in persons without disease, pointing to a “hidden burden” of MS.

Published
2017

24. A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer's disease

Author

Towfique Raj, Sven J. van der Lee, Julie Williams, Anna A. Pimenova, Benjamin Grenier-Boley, Laura Ibanez, Annette L. Fitzpatrick, Jorge L. Del-Aguila, Benjamin P. Fairfax, Gerard D. Schellenberg, Edoardo Marcora, Anita L. DeStefano, Sarah Bertelsen, Hieab H.H. Adams, Manav Kapoor, Valentina Escott-Price, Carlos Cruchaga, Cornelia M. van Duijn, Alan E. Renton, Richard Mayeux, Céline Bellenguez, Jean-Charles Lambert, Lindsay A. Farrer, Vincent Chouraki, Rebecca Sims, Kuan-lin Huang, Margaret A. Pericak-Vance, Bin Zhang, M. Arfan Ikram, Antonio Fabio Di Narzo, Maria Victoria Fernandez, Philippe Amouyel, Alison Goate, Ingrid B. Borecki, Sheng Chih Jin, Albert V. Smith, Yuetiva Deming, Joshua C. Bis, Jonathan L. Haines, Andrew M. McKenzie, Sudha Seshadri, Lenore J. Launer, John S. K. Kauwe, Oscar Harari, Jake Czajkowski, Ke Hao, John P. Budde, and Epidemiology

Subjects
0301 basic medicine, Male, Linkage disequilibrium, Myeloid, Locus (genetics), Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Article, 03 medical and health sciences, Mice, Alzheimer Disease, Risk Factors, Proto-Oncogene Proteins, Gene expression, medicine, Animals, Humans, Genetic Predisposition to Disease, Allele, Gene, Alleles, SPI1, General Neuroscience, 030104 developmental biology, medicine.anatomical_structure, Cistrome, Haplotypes, Immunology, Cancer research, Trans-Activators, Female, Genome-Wide Association Study, Transcription Factors
Abstract

A genome-wide survival analysis of 14,406 Alzheimer's disease (AD) cases and 25,849 controls identified eight previously reported AD risk loci and 14 novel loci associated with age at onset. Linkage disequilibrium score regression of 220 cell types implicated the regulation of myeloid gene expression in AD risk. The minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, showed association with delayed AD onset and lower expression of SPI1 in monocytes and macrophages. SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability was enriched within the PU.1 cistrome, implicating a myeloid PU.1 target gene network in AD. Finally, experimentally altered PU.1 levels affected the expression of mouse orthologs of many AD risk genes and the phagocytic activity of mouse microglial cells. Our results suggest that lower SPI1 expression reduces AD risk by regulating myeloid gene expression and cell function.

Published
2017

25. Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms

Author

Meike W. Vernooij, Henning Tiemeier, F M S de Vrij, W F J van IJcken, M. A. Ikram, Rutger W W Brouwer, Wiro J. Niessen, Robin P. Peeters, O. Jovanova, J. van Rooij, E. C. M. van Leeuwen, Layal Chaker, K. Willems van Dijk, Hieab H.H. Adams, Najaf Amin, C M van Duijn, Ayse Demirkan, Steven A. Kushner, S. J. van der Lee, André G. Uitterlinden, Robert Kraaij, Maryam Kavousi, Abbas Dehghan, Albert Hofman, Thomas Hankemeier, Oscar H. Franco, Epidemiology, Radiology & Nuclear Medicine, Internal Medicine, Psychiatry, Cell biology, Medical Informatics, and Neurology

Subjects
Adult, Male, 0301 basic medicine, Heterozygote, Population, Mutation, Missense, Steroid biosynthesis, Polymorphism, Single Nucleotide, 03 medical and health sciences, Cellular and Molecular Neuroscience, Rotterdam Study, 0302 clinical medicine, Gene Frequency, Alzheimer Disease, Risk Factors, Genetic variation, Humans, Medicine, Exome, Genetic Predisposition to Disease, Allele, education, Molecular Biology, Allele frequency, Alleles, Exome sequencing, Genetics, Depressive Disorder, education.field_of_study, Depression, business.industry, Cholesterol, HDL, Genetic Variation, Exons, Lipase, Sequence Analysis, DNA, Odds ratio, Middle Aged, Psychiatry and Mental health, 030104 developmental biology, Female, business, 030217 neurology & neurosurgery
Abstract

Despite a substantial genetic component, efforts to identify common genetic variation underlying depression have largely been unsuccessful. In the current study we aimed to identify rare genetic variants that might have large effects on depression in the general population. Using high-coverage exome-sequencing, we studied the exonic variants in 1265 individuals from the Rotterdam study (RS), who were assessed for depressive symptoms. We identified a missense Asn396Ser mutation (rs77960347) in the endothelial lipase (LIPG) gene, occurring with an allele frequency of 1% in the general population, which was significantly associated with depressive symptoms (P-value=5.2 × 10 -08, β=7.2). Replication in three independent data sets (N=3612) confirmed the association of Asn396Ser (P-value=7.1 × 10 -03, β=2.55) with depressive symptoms. LIPG is predicted to have enzymatic function in steroid biosynthesis, cholesterol biosynthesis and thyroid hormone metabolic processes. The Asn396Ser variant is predicted to have a damaging effect on the function of LIPG. Within the discovery population, carriers also showed an increased burden of white matter lesions (P-value=3.3 × 1 -02) and a higher risk of Alzheimer's disease (odds ration=2.01; P-value=2.8 × 10 -02) compared with the non-carriers. Together, these findings implicate the Asn396Ser variant of LIPG in the pathogenesis of depressive symptoms in the general population.

Published
2017

26. Weakly supervised object detection with 2D and 3D regression neural networks

Author

M. Arfan Ikram, Florian Dubost, Pinar Yilmaz, Meike W. Vernooij, Gijs van Tulder, Wiro J. Niessen, Gerda Bortsova, Hieab H.H. Adams, Marleen de Bruijne, Medical Informatics, Radiology & Nuclear Medicine, Epidemiology, and Neurology

Subjects
FOS: Computer and information sciences, Computer science, Computer Vision and Pattern Recognition (cs.CV), Perivascular spaces, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Computer Science - Computer Vision and Pattern Recognition, Health Informatics, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Count, Weak-labels, Preprocessor, Humans, Radiology, Nuclear Medicine and imaging, Segmentation, Lesion, Enlarged perivascular spaces, Radiological and Ultrasound Technology, Artificial neural network, business.industry, Deep learning, Brain, Pattern recognition, Computer Graphics and Computer-Aided Design, Magnetic Resonance Imaging, Object detection, Regression, Detection, Feature (computer vision), Weakly-supervised, Computer Vision and Pattern Recognition, Artificial intelligence, Neural Networks, Computer, business, 030217 neurology & neurosurgery, MNIST database, Interpolation, MRI
Abstract

Finding automatically multiple lesions in large images is a common problem in medical image analysis. Solving this problem can be challenging if, during optimization, the automated method cannot access information about the location of the lesions nor is given single examples of the lesions. We propose a new weakly supervised detection method using neural networks, that computes attention maps revealing the locations of brain lesions. These attention maps are computed using the last feature maps of a segmentation network optimized only with global image-level labels. The proposed method can generate attention maps at full input resolution without need for interpolation during preprocessing, which allows small lesions to appear in attention maps. For comparison, we modify state-of-the-art methods to compute attention maps for weakly supervised object detection, by using a global regression objective instead of the more conventional classification objective. This regression objective optimizes the number of occurrences of the target object in an image, e.g. the number of brain lesions in a scan, or the number of digits in an image. We study the behavior of the proposed method in MNIST-based detection datasets, and evaluate it for the challenging detection of enlarged perivascular spaces - a type of brain lesion - in a dataset of 2202 3D scans with point-wise annotations in the center of all lesions in four brain regions. In the brain dataset, the weakly supervised detection methods come close to the human intrarater agreement in each region. The proposed method reaches the best area under the curve in two out of four regions, and has the lowest number of false positive detections in all regions, while its average sensitivity over all regions is similar to that of the other best methods. The proposed method can facilitate epidemiological and clinical studies of enlarged perivascular spaces., New formatting. A few changes in introduction, discussion and conclusion

Published
2019

27. A genome-wide association study identifies genetic loci associated with specific lobar brain volumes

Author

Diana van Heemst, Lisa R. Yanek, Tamara B. Harris, Fabrice Crivello, Hieab H.H. Adams, Paul A. Nyquist, Bernard Mazoyer, Najaf Amin, Pauline Maillard, Diane M. Becker, Marian Beekman, Shuo Li, Ganesh Chauhan, Charles DeCarli, Wanting Zhao, Neda Jahanshad, Rasika A. Mathias, Cornelia M. van Duijn, Manon Bernard, Derrek P. Hibar, Alexa S. Beiser, Meike W. Vernooij, Vilmundur Gudnason, Joshua C. Bis, Tomáš Paus, Edith Hofer, Lei Yu, Stéphanie Debette, Helena Schmidt, M. Kamran Ikram, P. Eline Slagboom, Erik B. van den Akker, Lenore J. Launer, Stefan Boehringer, Kent D. Taylor, Maria J. Knol, Wiro J. Niessen, Kenneth Rice, Zdenka Pausova, Gennady V. Roshchupkin, Sven J. van der Lee, Philip L. De Jager, Ching-Yu Cheng, Sudha Seshadri, Qiong Yang, Konstantinos Arfanakis, Yasaman Saba, Jeroen van der Grond, W. T. Longstreth, Albert V. Smith, Claudia L. Satizabal, Oscar L. Lopez, Bruce M. Psaty, Christopher Chen, Philippe Amouyel, Josh W. Cheung, M. Arfan Ikram, Tien Yin Wong, Reinhold Schmidt, David A. Bennett, Saima Hilal, Paul M. Thompson, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Medicine, University of Washington [Seattle], Keck School of Medicine [Los Angeles], University of Southern California (USC), National University of Singapore (NUS), Rush University Medical Center [Chicago], Groupe d'imagerie neurofonctionnelle (GIN), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Los Angeles Biomedical Research Institute (LA BioMed), School of Public Health [Boston], Boston University [Boston] (BU), Columbia University Medical Center (CUMC), Columbia University [New York], University of Glasgow, Leiden University Medical Center (LUMC), University of Texas Health Science Center, The University of Texas Health Science Center at Houston (UTHealth), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epidemiology, Radiology & Nuclear Medicine, Medical Informatics, Neurology, Clinical Genetics, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and Universiteit Leiden

Subjects
Pathology, Heredity, Neurology, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Medicine (miscellaneous), Genome-wide association study, Genome-wide association studies, Taugasjúkdómar, 0302 clinical medicine, Parietal Lobe, 2.1 Biological and endogenous factors, Developmental, Aetiology, lcsh:QH301-705.5, 0303 health sciences, Parietal lobe, Gene Expression Regulation, Developmental, Organ Size, Magnetic Resonance Imaging, Temporal Lobe, Frontal Lobe, 3. Good health, Phenotype, Mental Health, Neurological, symbols, Occipital Lobe, Erfðarannsóknir, General Agricultural and Biological Sciences, medicine.medical_specialty, Genotype, 1.1 Normal biological development and functioning, Biology, Article, General Biochemistry, Genetics and Molecular Biology, Temporal lobe, 03 medical and health sciences, symbols.namesake, Underpinning research, Genetics, medicine, Humans, Gene, 030304 developmental biology, Genetic association, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], Human Genome, Heilinn, Neurosciences, Genetic Variation, United Kingdom, Brain Disorders, Gene Expression Regulation, lcsh:Biology (General), Genetic Loci, Mendelian inheritance, Occipital lobe, Biomarkers, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Publisher's version (útgefin grein)., Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications (DAAM1 and THBS3), or close to genes causing Mendelian brain-related diseases (ZIC4 and FGFRL1). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes., 23Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA. 24Research Unit-Genetic Epidemiology, Gottfried Schatz Research Centre for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria. 25Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15260, USA. 26Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA. 27Department of Radiology, Leiden University Medical Center, Leiden 2333ZA, the Netherlands. 28Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto M4G 1R8, Canada. 29Departments of Psychology and Psychiatry, University of Toronto, Toronto M5S 1A1, Canada.

Published
2019

28. Genetic markers of ADHD-related variations in intracranial volume

Author

Raymond K. Walters, Russell Schachar, Sarah E. Medland, Anders D. Børglum, Nina Roth Mota, Stephen V. Faraone, Alejandro Arias-Vasquez, Jason L. Stein, Derrek P. Hibar, Barbara Franke, Paul M. Thompson, Manuel Mattheisen, Marieke Klein, Edmund J.S. Sonuga-Barke, Benjamin M. Neale, Janita Bralten, Ditte Demontis, and Hieab H.H. Adams

Subjects
Genetic Markers, Quantitative Trait Loci, Caudate nucleus, Biology, Bioinformatics, Genetic correlation, Amygdala, Hippocampus, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Nucleus Accumbens, Article, 03 medical and health sciences, 0302 clinical medicine, Neurodevelopmental disorder, Intracranial volume, mental disorders, medicine, Attention deficit hyperactivity disorder, Humans, 030304 developmental biology, Genetics, 0303 health sciences, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, Putamen, Brain, Organ Size, medicine.disease, Genetic architecture, 3. Good health, 030227 psychiatry, Psychiatry and Mental health, medicine.anatomical_structure, Genetic marker, Attention Deficit Disorder with Hyperactivity, Case-Control Studies, Etiology, Caudate Nucleus, business, Medical science, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Contains fulltext : 202907.pdf (Publisher’s version ) (Open Access) OBJECTIVE:: Attention deficit hyperactivity disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology. Intracranial volume (ICV) and volumes of the nucleus accumbens, amygdala, caudate nucleus, hippocampus, and putamen are smaller in people with ADHD compared with healthy individuals. The authors investigated the overlap between common genetic variation associated with ADHD risk and these brain volume measures to identify underlying biological processes contributing to the disorder. METHODS:: The authors combined genome-wide association results from the largest available studies of ADHD (N=55,374) and brain volumes (N=11,221-24,704), using a set of complementary methods to investigate overlap at the level of global common variant genetic architecture and at the single variant level. RESULTS:: Analyses revealed a significant negative genetic correlation between ADHD and ICV (rg=-0.22). Meta-analysis of single variants revealed two significant loci of interest associated with both ADHD risk and ICV; four additional loci were identified for ADHD and volumes of the amygdala, caudate nucleus, and putamen. Exploratory gene-based and gene-set analyses in the ADHD-ICV meta-analytic data showed association with variation in neurite outgrowth-related genes. CONCLUSIONS:: This is the first genome-wide study to show significant genetic overlap between brain volume measures and ADHD, both on the global and the single variant level. Variants linked to smaller ICV were associated with increased ADHD risk. These findings can help us develop new hypotheses about biological mechanisms by which brain structure alterations may be involved in ADHD disease etiology.

Published
2019

29. Independent multiple factor association analysis for multiblock data in imaging genetics

Author

Cornelia M. van Duijn, Meike W. Vernooij, Jordi Sunyer, Juan R. González, Hieab H.H. Adams, Alejandro Cáceres, Gennady V. Roshchupkin, Silvia Alemany, Wiro J. Niessen, Natalia Vilor-Tejedor, Mohammad Arfan Ikram, Epidemiology, Medical Informatics, and Radiology & Nuclear Medicine

Subjects
Multivariate statistics, Computer science, Population, Neuroimaging, Polymorphism, Single Nucleotide, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, Multiple factor analysis, Statistics, Humans, 0501 psychology and cognitive sciences, education, education.field_of_study, General Neuroscience, 05 social sciences, Univariate, Brain, Variance (accounting), Explained variation, Independent component analysis, Regression, Neurogenètica, Factor Analysis, Statistical, 030217 neurology & neurosurgery, Software, Algorithms, Information Systems
Abstract

Multivariate methods have the potential to better capture complex relationships that may exist between different biological levels. Multiple Factor Analysis (MFA) is one of the most popular methods to obtain factor scores and measures of discrepancy between data sets. However, singular value decomposition in MFA is based on PCA, which is adequate only if the data is normally distributed, linear or stationary. In addition, including strongly correlated variables can overemphasize the contribution of the estimated components. In this work, we introduced a novel method referred as Independent Multifactorial Analysis (ICA-MFA) to derive relevant features from multiscale data. This method is an extended implementation of MFA, where the component value decomposition is based on Independent Component Analysis. In addition, ICA-MFA incorporates a predictive step based on an Independent Component Regression. We evaluated and compared the performance of ICA-MFA with both, the MFA method and traditional univariate analyses, in a simulation study. We showed how ICA-MFA explained up to 10-fold more variance than MFA and univariate methods. We applied the proposed algorithm in a study of 4057 individuals belonging to the population-based Rotterdam Study with available genetic and neuroimaging data, as well as information about executive cognitive functioning. Specifically, we used ICA-MFA to detect relevant genetic features related to structural brain regions, which in turn were involved, in the mechanisms of executive cognitive function. The proposed strategy makes it possible to determine the degree to which the whole set of genetic and/or neuroimaging markers contribute to the variability of the symptomatology jointly, rather than individually. While univariate results and MFA combinations only explained a limited proportion of variance (less than 2%), our method increased the explained variance (10%) and allowed the identification of significant components that maximize the variance explained in the model. The potential application of the ICA-MFA algorithm constitutes an important aspect of integrating multivariate multiscale data, specifically in the field of Neurogenetics. Natalia Vilor-Tejedor is funded by a pre-doctoral grant from the Agència de Gestió d’Ajuts Universitaris i de Recerca (2017 FI_B 00636), Generalitat de Catalunya – Fons Social Europeu. This work has been partially supported by a STSM Grant from EU COST Action 15120 Open Multiscale Systems Medicine (OpenMultiMed) and Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP). Further support was obtained through the Ministerio de Economía e Innovación (Spain), grant MTM2015-68140-R. ISGlobal is a member of the CERCA Programme, Generalitat de Catalunya. Silvia Alemany thanks the Institute of Health Carlos III for her Sara Borrell postdoctoral grant (CD14/00214). The generation and management of GWAS genotype data for the Rotterdam Study are supported by the Netherlands Organization of Scientific Research NWO Investments (no. 175.010.2005.011, 911-03- 012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/ Netherlands Organization for Scientific Research (NWO) project no. 050- 060-810. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. This research is supported by the Dutch Technology Foundation STW (12723), which is part of the NWO, and which is partly funded by the Ministry of Economic Affairs. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project: ORACLE, grant agreement No: 678543)

Published
2019

30. Genetic variation underlying cognition and its relation with neurological outcomes and brain imaging

Author

Hieab H.H. Adams, Wiro J. Niessen, Cornelia M. van Duijn, M. Arfan Ikram, M. Kamran Ikram, André G. Uitterlinden, Alis Heshmatollah, Lotte G.M. Cremers, Maria J. Knol, Meike W. Vernooij, Epidemiology, Neurology, Radiology & Nuclear Medicine, Internal Medicine, and Medical Informatics

Subjects
Male, Aging, Population, Cognitive reserve, Neuroimaging, Neuropsychological Tests, Bioinformatics, 03 medical and health sciences, Rotterdam Study, Cognition, 0302 clinical medicine, Risk Factors, Genetics, medicine, Humans, Dementia, Cognitive Dysfunction, Genetic Predisposition to Disease, Cognitive decline, 10. No inequality, education, Aged, 030304 developmental biology, 0303 health sciences, education.field_of_study, business.industry, Parkinsonism, Brain, Genetic Variation, Parkinson Disease, Cell Biology, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Stroke, Female, business, Biomarkers, Neurological disorders, 030217 neurology & neurosurgery, Research Paper, Genome-Wide Association Study
Abstract

Cognition in adults shows variation due to developmental and degenerative components. A recent genomewide association study identified genetic variants for general cognitive function in 148 independent loci. Here, we aimed to elucidate possible developmental and neurodegenerative pathways underlying these genetic variants by relating them to functional, clinical and neuroimaging outcomes. This study was conducted within the population-based Rotterdam Study (N=11,496, mean age 65.3±9.9 years, 58.0% female). We used lead variants for general cognitive function to construct a polygenic score (PGS), and additionally excluded developmental variants at multiple significance thresholds. A higher PGS was related to more years of education (β=0.29, p=4.3×10 -7 ) and a larger intracranial volume (β=0.05, p=7.5×10 -4 ). To a smaller extent, the PGS was associated with less cognitive decline (βΔG-factor=0.03, p=1.3×10 -3 ), which became non-significant after adjusting for education (p=1.6×10 -2 ). No associations were found with daily functioning, dementia, parkinsonism, stroke or microstructural white matter integrity. Excluding developmental variants attenuated nearly all associations. In conclusion, this study suggests that the genetic variants identified for general cognitive function are acting mainly through the developmental pathway of cognition. Therefore, cognition, assessed cross-sectionally, seems to have limited value as a biomarker for neurodegeneration.

Published
2019

31. Enlarged perivascular spaces in brain MRI:Automated quantification in four regions

Author

Hieab H.H. Adams, Wiro J. Niessen, Marleen de Bruijne, Florian Dubost, Gerda Bortsova, Pinar Yilmaz, M. Arfan Ikram, Meike W. Vernooij, Medical Informatics, Radiology & Nuclear Medicine, Epidemiology, and Neurology

Subjects
Male, medicine.medical_specialty, Intraclass correlation, Cognitive Neuroscience, Population, Perivascular spaces, Neuroimaging, Virchow-Robin spaces, Convolutional neural network, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, Centrum semiovale, Image Interpretation, Computer-Assisted, Machine learning, medicine, Brain mri, Humans, 0501 psychology and cognitive sciences, Segmentation, Perivascular space, education, Aged, Enlarged perivascular spaces, education.field_of_study, business.industry, 05 social sciences, Brain, Deep learning, Magnetic Resonance Imaging, medicine.anatomical_structure, Neurology, Cerebral Small Vessel Diseases, cardiovascular system, Female, Dementia, Radiology, business, Glymphatic System, 030217 neurology & neurosurgery
Abstract

Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small vessel disease. As such, assessing the burden of PVS has promise as a brain imaging marker. Visual and manual scoring of PVS is a tedious and observer-dependent task. Automated methods would advance research into the etiology of PVS, could aid to assess what a “normal” burden is in aging, and could evaluate the potential of PVS as a biomarker of cerebral small vessel disease. In this work, we propose and evaluate an automated method to quantify PVS in the midbrain, hippocampi, basal ganglia and centrum semiovale. We also compare associations between (earlier established) determinants of PVS and visual PVS scores versus the automated PVS scores, to verify whether automated PVS scores could replace visual scoring of PVS in epidemiological and clinical studies. Our approach is a deep learning algorithm based on convolutional neural network regression, and is contingent on successful brain structure segmentation. In our work we used FreeSurfer segmentations. We trained and validated our method on T2-contrast MR images acquired from 2115 subjects participating in a population-based study. These scans were visually scored by an expert rater, who counted the number of PVS in each brain region. Agreement between visual and automated scores was found to be excellent for all four regions, with intraclass correlation coefficients (ICCs) between 0.75 and 0.88. These values were higher than the inter-observer agreement of visual scoring (ICCs between 0.62 and 0.80). Scan-rescan reproducibility was high (ICCs between 0.82 and 0.93). The association between 20 determinants of PVS, including aging, and the automated scores were similar to those between the same 20 determinants of PVS and visual scores. We conclude that this method may replace visual scoring and facilitate large epidemiological and clinical studies of PVS.

Published
2019

32. Stats: a trillion P values and counting

Author

Hieab H.H. Adams and Radiology & Nuclear Medicine

Subjects
Multidisciplinary, Actuarial science, Political science, Data Interpretation, Statistical, Health Policy, MEDLINE, Data interpretation, Humans, Reproducibility of Results, Educational Measurement, Health policy, Research data, Probability
Published
2019

33. Normative brain volumetry derived from different reference populations: impact on single-subject diagnostic assessment in dementia

Author

Alzheimer’s Disease Neuroimaging Initiative, M. Arfan Ikram, Elisabeth J Vinke, Hieab H.H. Adams, Fabian Wenzel, Frank Jan de Jong, Meike W. Vernooij, Rebecca M. E. Steketee, Wyke Huizinga, Wiro J. Niessen, Janne M. Papma, Martin Bergtholdt, Epidemiology, Radiology & Nuclear Medicine, Medical Informatics, and Neurology

Subjects
0301 basic medicine, Volumetric imaging, Aging, medicine.medical_specialty, Percentile, Population, Normative data, Imaging, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Physical medicine and rehabilitation, Neuroimaging, medicine, Dementia, Humans, education, Cognitive impairment, education.field_of_study, business.industry, General Neuroscience, Brain, Organ Size, medicine.disease, Magnetic Resonance Imaging, Subcortical brain volume, 030104 developmental biology, Normative, Diagnostic assessment, Neurology (clinical), Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, Developmental Biology, MRI
Abstract

Brain imaging data are increasingly made publicly accessible, and volumetric imaging measures derived from population-based cohorts may serve as normative data for individual patient diagnostic assessment. Yet, these normative cohorts are usually not a perfect reflection of a patient's base population, nor are imaging parameters such as field strength or scanner type similar. In this proof of principle study, we assessed differences between reference curves of subcortical structure volumes of normal controls derived from two population-based studies and a case-control study. We assessed the impact of any differences on individual assessment of brain structure volumes. Percentile curves were fitted on the three healthy cohorts. Next, percentile values for these subcortical structures for individual patients from these three cohorts, 91 mild cognitive impairment and 95 Alzheimer's disease cases and patients from the Alzheimer Center, were calculated, based on the distributions of each of the three cohorts. Overall, we found that the subcortical volume normative data from these cohorts are highly interchangeable, suggesting more flexibility in clinical implementation.

Published
2019
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34. Identification of additional risk loci for stroke and small vessel disease

Author

Matthew Traylor, Vilmundur Gudnason, Kerri L. Wiggins, Christophe Tzourio, Reinhold E. Schmidt, Hugo J. Aparicio, Tamara B. Harris, Audrey Y. Chu, Oscar R. Benavente, Anton J. M. de Craen, Nancy L. Pedersen, Lars Lannfelt, Didier Leys, Erkki Vartiainen, Myriam Fornage, Marileen L.P. Portegies, Nicholas L. Smith, Daniel Woo, Martin Dichgans, John W. Cole, Christina Jern, Christopher R Levi, Kenneth Rice, André G. Uitterlinden, Rebecca F. Gottesman, M. Arfan Ikram, Ralph L. Sacco, Cornelia M. van Duijn, Samuli Ripatti, Anita L. DeStefano, Donna K. Arnett, Curtis R. French, Tobias Kurth, Tomi Pastinen, Raji P. Grewal, Susan R. Heckbert, Jordi Jimenez-Conde, Jemma C. Hopewell, Cecilia M. Lindgren, Azadeh Reyahi, Michèle M. Sale, Marcello Ricardo Paulista Markus, Albert Hofman, Seung Hoan Choi, Peter J. Koudstaal, Veikko Salomaa, Robert Clarke, Arne Lindgren, B. Gwen Windham, Farid Radmanesh, Peter M. Rothwell, Carsten Oliver Schmidt, Xueqiu Jian, David S. Knopman, Yongmei Liu, Joan Montaner, Jean-François Dartigues, Paul M. Ridker, Julie A. Johnson, Stefan Gustafsson, Jerome I. Rotter, Manja Kloss, Tatjana Rundek, David J. Stott, Ganesh Chauhan, Ordan J. Lehmann, Ali Moussavi Nik, Marcel den Hoed, Alessandro Pezzini, Jin-Moo Lee, Hans J. Grabe, Sylvia Wassertheil-Smoller, Anders Hamsten, Thomas H. Mosley, Muralidharan Sargurupremraj, Lenore J. Launer, Kathryn M. Rexrode, Quenna Wong, Jonathan Rosand, David A. Bennett, Philip L. De Jager, James F. Meschia, Alexa S. Beiser, J. Wouter Jukema, Traci M. Bartz, Mike A. Nalls, Cathie Sudlow, Erik Ingelsson, Yoichiro Kamatani, Ulf Schminke, Joris Deelen, Stéphanie Debette, Andrew P. Morris, Aki S. Havulinna, Sudha Seshadri, Bradford B. Worrall, Stephen S. Rich, Lars Lindgren, Hieab H.H. Adams, Ani Manichaikul, Jean-Sébastien Vidal, Bruce M. Psaty, Julie E. Buring, Jean Dallongeville, Oscar L. Lopez, Corey R. Arnold, Olle Melander, Olafur Kjartansson, Alexander Teumer, Sarah J. Childs, William T. Longstreth, Charles C. White, Stefan T. Engelter, Daniel I. Chasman, Norrina B. Allen, Rainer Malik, Vincent Thijs, Stella Trompet, Joshua C. Bis, Ian Ford, Peter Carlsson, Céline Bellenguez, Sara L. Pulit, Pankaj Sharma, Patrik K. E. Magnusson, Flora Xue, Giorgio B. Boncoraglio, Mark Lathrop, Melissa E. Garcia, Andrew D. Johnson, Steve Bevan, Albert V. Smith, Claudia L. Satizabal, Agnieszka Slowik, Michael Griswold, Claudine Berr, and Hugh S. Markus

Subjects
Adult, Male, 0301 basic medicine, Adolescent, Population, Genome-wide association study, Biology, Bioinformatics, Article, Brain ischemia, Mice, Young Adult, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, medicine, Animals, Humans, Child, education, Allele frequency, Stroke, Aged, Aged, 80 and over, education.field_of_study, Cerebral infarction, Forkhead Transcription Factors, Odds ratio, Middle Aged, 16. Peace & justice, medicine.disease, R1, 3. Good health, Minor allele frequency, 030104 developmental biology, Genetic Loci, Cerebral Small Vessel Diseases, Child, Preschool, Female, Neurology (clinical), 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Background Genetic determinants of stroke, the leading neurological cause of death and disability, are poorly understood and have seldom been explored in the general population. Our aim was to identify additional loci for stroke by doing a meta-analysis of genome-wide association studies. Methods For the discovery sample, we did a genome-wide analysis of common genetic variants associated with incident stroke risk in 18 population-based cohorts comprising 84 961 participants, of whom 4348 had stroke. Stroke diagnosis was ascertained and validated by the study investigators. Mean age at stroke ranged from 45·8 years to 76·4 years, and data collection in the studies took place between 1948 and 2013. We did validation analyses for variants yielding a significant association (at p−6) with all-stroke, ischaemic stroke, cardioembolic ischaemic stroke, or non-cardioembolic ischaemic stroke in the largest available cross-sectional studies (70 804 participants, of whom 19 816 had stroke). Summary-level results of discovery and follow-up stages were combined using inverse-variance weighted fixed-effects meta-analysis, and in-silico lookups were done in stroke subtypes. For genome-wide significant findings (at p−8), we explored associations with additional cerebrovascular phenotypes and did functional experiments using conditional (inducible) deletion of the probable causal gene in mice. We also studied the expression of orthologs of this probable causal gene and its effects on cerebral vasculature in zebrafish mutants. Findings We replicated seven of eight known loci associated with risk for ischaemic stroke, and identified a novel locus at chromosome 6p25 (rs12204590, near FOXF2) associated with risk of all-stroke (odds ratio [OR] 1·08, 95% CI 1·05–1·12, p=1·48 × 10−8; minor allele frequency 21%). The rs12204590 stroke risk allele was also associated with increased MRI-defined burden of white matter hyperintensity—a marker of cerebral small vessel disease—in stroke-free adults (n=21 079; p=0·0025). Consistently, young patients (aged 2–32 years) with segmental deletions of FOXF2 showed an extensive burden of white matter hyperintensity. Deletion of Foxf2 in adult mice resulted in cerebral infarction, reactive gliosis, and microhaemorrhage. The orthologs of FOXF2 in zebrafish (foxf2b and foxf2a) are expressed in brain pericytes and mutant foxf2b−/− cerebral vessels show decreased smooth muscle cell and pericyte coverage. Interpretation We identified common variants near FOXF2 that are associated with increased stroke susceptibility. Epidemiological and experimental data suggest that FOXF2 mediates this association, potentially via differentiation defects of cerebral vascular mural cells. Further expression studies in appropriate human tissues, and further functional experiments with long follow-up periods are needed to fully understand the underlying mechanisms. Funding NIH, NINDS, NHMRC, CIHR, European national research institutions, Fondation Leducq.

Published
2016

35. Genetic risk of Parkinson's disease in the general population

Author

Sirwan K.L. Darweesh, André G. Uitterlinden, Hieab H.H. Adams, M. Arfan Ikram, Albert Hofman, Vincentius J.A. Verlinden, Bruno H. Stricker, Peter J. Koudstaal, Cornelia M. van Duijn, Epidemiology, Radiology & Nuclear Medicine, Internal Medicine, and Neurology

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Parkinson's disease, Population, Community Health Planning, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Risk Factors, Internal medicine, Epidemiology, Activities of Daily Living, Medicine, Dementia, Humans, Longitudinal Studies, education, Aged, Netherlands, Aged, 80 and over, education.field_of_study, Framingham Risk Score, business.industry, Parkinsonism, Hazard ratio, Genetic Variation, Parkinson Disease, Middle Aged, medicine.disease, 030104 developmental biology, Neurology, Physical therapy, Female, Neurology (clinical), Geriatrics and Gerontology, business, 030217 neurology & neurosurgery
Abstract

Introduction: We investigated whether a risk score based on genetic risk variants for Parkinson's disease (PD) is associated with the risk and improves prediction of incident PD, and whether the risk score is associated with basic activities of daily living (BADL) in healthy individuals. Methods: Within the population-based Rotterdam Study, we genotyped 26 independent risk variants for PD and constructed a genetic risk score in 7167 participants who were free of parkinsonism and dementia at baseline (1990 or 2000). Participants were followed for a maximum of twenty years for the onset of parkinsonism, dementia or death until January 1, 2011 (median follow-up 12.1 years). We studied the relationship between the genetic risk score and incident PD with adjustment for age, sex, smoking and parental history. In an independent sample of 2997 persons free of parkinsonism and dementia, we studied whether the PD risk score was associated with impaired BADL. Results: During follow-up (median 12.1 years), 99 persons were diagnosed with incident PD. The genetic risk score was associated with incident PD (hazard ratio per standard deviation risk 1.25 [95% confidence interval = 1.02; 1.551), but did not substantially improve prediction (change in C-statistic 0.687 [0.628; 0.745] to 0.698 [0.635; 0.760], Delta C = 0.011 [ 0.011; 0.0331). The genetic risk score was associated with a higher probability of any impairment in BADL (odds ratio = 1.11 [1.00; 1.23]). Conclusion: Genetic variants for PD are associated with the risk of incident PD in the general population and with impairment in daily functioning in individuals without clinical parkinsonism, but do not improve the clinical prediction of PD. However, we were probably underpowered to detect a small improvement in PD prediction. (C) 2016 Elsevier Ltd. All rights reserved.

Published
2016

36. Heritability and Genome-Wide Association Analyses of Intracranial Carotid Artery Calcification The Rotterdam Study

Author

André G. Uitterlinden, M. Arfan Ikram, Peter J. Koudstaal, Albert Hofman, Hieab H.H. Adams, Meike W. Vernooij, Oscar H. Franco, Aad van der Lugt, Daniel Bos, Anouk C. van Dijk, Cornelia M. van Duijn, Epidemiology, Neurology, Radiology & Nuclear Medicine, and Internal Medicine

Subjects
Carotid Artery Diseases, Male, medicine.medical_specialty, Pathology, Genotype, Population, Genome-wide association study, 030204 cardiovascular system & hematology, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Risk Factors, Internal medicine, medicine.artery, medicine, Humans, Genetic Predisposition to Disease, Prospective Studies, 1000 Genomes Project, education, Prospective cohort study, Vascular Calcification, Stroke, Aged, Advanced and Specialized Nursing, education.field_of_study, business.industry, Heritability, Middle Aged, medicine.disease, Radiography, Female, Neurology (clinical), Internal carotid artery, Cardiology and Cardiovascular Medicine, business, 030217 neurology & neurosurgery, Carotid Artery, Internal, Genome-Wide Association Study
Abstract

Background and Purpose— Intracranial carotid artery calcification (ICAC) is one of the most important risk factors for stroke. Although several environmental risk factors for ICAC have been identified, its genetic background remains unclear. Methods— Between 2003 and 2006, 2034 participants from the prospective population-based Rotterdam study (mean age: 69.6±6.8 years; 51.7% female) underwent computed tomography to quantify vascular calcification in the intracranial internal carotid artery. Blood samples were drawn for genotyping. Genotypes of the participants were imputed to the 1000 Genomes reference panel to generate genetic relationship matrices for the estimation of the heritability of ICAC volume. Adjustments were made for age and sex. Subsequently, genome-wide association analyses were performed to identify specific variants. Results— The age- and sex-adjusted heritability ( h 2 ) of ICAC was 47% [standard error (SE): 19%; P =0.009]. Genome-wide association analyses identified a variant on chromosome 9p21.3 (rs1537372; N=2034; P =4.75×10 −9 ) and 1 variant on chromosome 11p11.2 (rs11038042, N=2034; P =3.27×10 −8 ) that were significantly associated with ICAC volume. Rs1537372 replicated in an independent sample of 716 stroke patients ( P combined =1.38×10 −10 ). Conclusions— ICAC volume is a heritable trait, which is partly explained by common genetic variation. We identified specific genetic variants associated with ICAC, which given the importance of ICAC in stroke risk, needs replication in larger-scale studies to further elucidate its genetic basis.

Published
2016

37. Evaluating extent of resection in pediatric glioblastoma: a multiple propensity score-adjusted population-based analysis

Author

Hieab H.H. Adams, Alfredo Quinones-Hinojosa, Jordina Rincon-Torroella, Christina Jackson, Hadie Adams, George I. Jallo, and Epidemiology

Subjects
Male, Oncology, medicine.medical_specialty, Adolescent, Kaplan-Meier Estimate, Neurosurgical Procedures, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Epidemiology, Humans, Medicine, Child, Propensity Score, Survival analysis, Proportional Hazards Models, Retrospective Studies, Brain Neoplasms, business.industry, Proportional hazards model, Mortality rate, Infant, Retrospective cohort study, General Medicine, Surgery, Cancer registry, Child, Preschool, 030220 oncology & carcinogenesis, Pediatrics, Perinatology and Child Health, Propensity score matching, Cohort, Female, Neurology (clinical), Glioblastoma, business, 030217 neurology & neurosurgery, SEER Program
Abstract

The benefit of radical resections for glioblastoma patients remains a source of contention in the literature. Few studies have been conducted in pediatric patients, and it is becoming increasingly evident that data regarding adult glioblastoma (GB) patients cannot be generalized to pediatric patients affected by this neoplasm. A comparative effectiveness study is performed for different extent of resection (EOR) groups in the largest cohort of pediatric GB (pGB) patients. The Surveillance, Epidemiology, and End Results (SEER) cancer registry was used to identify pGB patients from 1988 through 2009. Multivariate- and multiple propensity score (mPS)-adjusted analyses were used to determine the effect of gross total resection (GTR), partial resection (PR), and biopsy (Bx) on overall survival. Survival prospects were summarized using direct adjusted survival curves. A total of 342 pGB patients were identified, and 35.4 % of patients received a GTR, 28.8 % PR, 17.3 % Bx, and 17.0 % did not undergo surgery. In our cohort, a median overall survival of 12 months was observed with 1-, 2-, and 5-year survival rates of 51.7, 28.3, and 15.7 %, respectively. EOR was a predictor of survival in both the multivariate- (P

Published
2016

38. Correction: The complex genetics of gait speed: genome-wide meta-analysis approach

Author

John D. Eicher, Dena G. Hernandez, Maria Nethander, Russell Thomson, Thomas H. Mosley, Amy M. Matteini, Lenore J. Launer, Gil Atzmon, A.B. Newman, Dan Mellström, Lital Sharvit, Stephen T. Turner, Joe Verghese, Simon P. Mooijaart, Douglas P. Kiel, Jessica D. Faul, Stefania Bandinelli, Jeremy D. Walston, D. S. Knopman, John M. Starr, David R. Weir, Wei Zhao, Jennifer A. Smith, Sharon L.R. Kardia, Ian J. Deary, Beverly G Windham, Joris Deelen, Alice M. Arnold, Denis A. Evans, Eline Slagboom, Gail Davies, Danielle Gutman, Rotem Vered, David C. Liewald, Magnus Karlsson, Alison Pattie, Kathryn L. Lunetta, Velandai Srikanth, Vilmundur Gudnason, Janie Corley, Joanne M. Murabito, Luigi Ferrucci, Vincent J. A. Verlinden, Michele L. Callisaya, Tamara B. Harris, Danny Ben-Avraham, Jos N. van der Geest, Lei Yu, David Karasik, Philip L. De Jager, Gregory J. Tranah, Toshiko Tanaka, Jeanine J. Houwing-Duistermaat, Aron S. Buchman, Hieab H.H. Adams, Myriam Fornage, Albert V. Smith, Matthijs Moed, Claes Ohlsson, Andrew D. Johnson, Marian Beekman, André G. Uitterlinden, Neeta Parimi, M. Arfan Ikram, Steven R. Cummings, Albert Hofman, Rebekah McWhirter, Yongmei Liu, Daniel S. Evans, and David A. Bennett

Subjects
Male, Aging, Pseudogene, Quantitative Trait Loci, Biology, Genome, Polymorphism, Single Nucleotide, GWAS, Humans, Small nucleolar RNA, Enhancer, PTPRT, Gene, Gait, Aged, Genetics, Aged, 80 and over, Serine Endopeptidases, Receptor-Like Protein Tyrosine Phosphatases, Class 2, RNA, Correction, Cell Biology, Middle Aged, Walking Speed, meta-analysis, Phenotype, Female, gait speed, Small nuclear RNA, Research Paper, Genome-Wide Association Study
Abstract

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.

Published
2017

39. High-dimensional mapping of cognition to the brain using voxel-based morphometry and subcortical shape analysis

Author

Wiro J. Niessen, Meike W. Vernooij, Hieab H.H. Adams, M. Arfan Ikram, Gennady V. Roshchupkin, Boris A. Gutman, Aad van der Lugt, Hazel I. Zonneveld, Epidemiology, Radiology & Nuclear Medicine, and Medical Informatics

Subjects
Male, 0301 basic medicine, Population, Caudate nucleus, Neuroimaging, Neuropsychological Tests, Grey matter, Biology, computer.software_genre, Lateralization of brain function, Temporal lobe, Executive Function, 03 medical and health sciences, Superior temporal gyrus, Cognition, 0302 clinical medicine, Memory, Voxel, medicine, Humans, Prospective Studies, Gray Matter, education, Aged, Brain Mapping, education.field_of_study, General Neuroscience, Brain, General Medicine, Voxel-based morphometry, Magnetic Resonance Imaging, Psychiatry and Mental health, Clinical Psychology, 030104 developmental biology, medicine.anatomical_structure, Female, Geriatrics and Gerontology, computer, Neuroscience, Psychomotor Performance, 030217 neurology & neurosurgery
Abstract

BackgroundIt is increasingly recognized that the complex functions of human cognition are not accurately represented by arbitrarily-defined anatomical brain regions. Given the considerable functional specialization within such regions, more fine-grained studies of brain structure could capture such localized associations. However, such analyses/studies in a large community-dwelling population are lacking.MethodsIn 3,813 stroke-free and non-demented persons from the Rotterdam Study (mean age 69.1 (±8.8) years; 55.8% women) with cognitive assessments and brain MRI, we performed voxel-based morphometry and subcortical shape analysis on global cognition and separate tests that tapped into memory, information processing speed, fine motor speed, and executive function domains.ResultsWe found that the different cognitive tests significantly associated with grey matter voxels in differential but also overlapping brain regions, primarily in the left hemisphere. Clusters of significantly associated voxels with global cognition were located within multiple anatomic regions: left amygdala, hippocampus, parietal lobule, superior temporal gyrus, insula and posterior temporal lobe. Subcortical shape analysis revealed associations primarily within the head and tail of the caudate nucleus, putamen, ventral part of the thalamus, and nucleus accumbens, more equally distributed among the left and right hemisphere. Within the caudate nucleus both positive (head) as well as negative (tail) associations were observed with global cognition.ConclusionsIn a large population-based sample, we mapped cognitive performance to (sub)cortical grey matter using a hypothesis-free approach with high-dimensional neuroimaging. Leveraging the power of our large sample size, we confirmed well-known associations as well as identified novel brain regions related to cognition.

Published
2018

40. Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume

Author

Charles DeCarli, Vilmundur Gudnason, Debra A. Fleischman, Henning Tiemeier, Rebecca F. Gottesman, William S. Kremen, Xueqiu Jian, Henry Brodaty, Maria del C. Valdés Hernández, Markus Loeffler, Reinhold Schmidt, Shahzad Ahmad, Paul A. Nyquist, Oscar L. Lopez, Anbupalam Thalamuthu, Helena Schmidt, Peter R. Schofield, Tonya White, Edith Hofer, Philip L. De Jager, David Ames, Qiong Yang, Ole A. Andreassen, Cora E. Lewis, Matthias Nauck, David S. Knopman, Anders M. Dale, Sven J. van der Lee, Jeroen van der Grond, Konstantinos Arfanakis, Margaret J. Wright, Jingyun Yang, John B.J. Kwok, Hieab H.H. Adams, Matthew S. Panizzon, Meike W. Vernooij, Yasaman Saba, David A. Bennett, Cornelia M. van Duijn, Tamara B. Harris, Pauline Maillard, Frauke Beyer, M. Arfan Ikram, Jerome I. Rotter, Ryan L. Muetzel, Tomáš Paus, Pamela J. Schreiner, Zdenka Pausova, Katharina Wittfeld, Diane M. Becker, Bruce M. Psaty, Alexander Teumer, Wei Wen, A. Veronica Witte, Karen A. Mather, Hanan El Marroun, William T. Longstreth, Perminder S. Sachdev, Mark E. Bastin, Nathan A. Gillespie, Kenneth Rice, Stella Trompet, Lisa R. Yanek, David J. Stott, Alexa S. Beiser, R. Nick Bryan, Alexander Neumann, Natalie A. Royle, Myriam Fornage, Manon Bernard, Dina Vojinovic, Najaf Amin, Ian J. Deary, Arno Villringer, Georg Homuth, Nicola J. Armstrong, Stephen Sidney, Sudha Seshadri, Joanna M. Wardlaw, Thomas H. Mosley, Hans J. Grabe, Michelle Luciano, Lenore J. Launer, J. Wouter Jukema, Robin Bülow, Markus Scholz, André G. Uitterlinden, Albert V. Smith, Shuo Li, Claudia L. Satizabal, Joshua C. Bis, Epidemiology, Radiology & Nuclear Medicine, Child and Adolescent Psychiatry / Psychology, Clinical Psychology, Internal Medicine, Psychiatry, Neurology, Faculty of Medicine (UI), Læknadeild (HÍ), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands (HÍ), and University of Iceland (UI)

Subjects
0301 basic medicine, Genetics of the nervous system, Cytoskeleton organization, General Physics and Astronomy, Genome-wide association study, Mental disorders, Genome-wide association studies, Genome, Lateral ventricles, 0302 clinical medicine, Lateral Ventricles, Ventricle (lateral), lcsh:Science, Genetics, anatomy & histology [Lateral Ventricles], education.field_of_study, Enlargement, Multidisciplinary, Brain, Organ Size, Middle Aged, Schizophrenia, ddc:500, Science, Population, Elderly people, Biology, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, medicine, Erfðafræði, Humans, Genomes, education, Aged, Genetic association, genetics [Organ Size], Genome, Human, Heilinn, Brain morphometry, Litningarannsóknir, Rannsóknir, General Chemistry, medicine.disease, 030104 developmental biology, Heritable quantitative trait, lcsh:Q, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Publisher's version (útgefin grein) Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations., The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (ρgenetic = −0.59, p-value = 3.14 × 10−6), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology., See Supplementary Note 2 for information on funding sources.

Published
2018

41. Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function

Author

Brian D. Hobbs, Myriam Fornage, Hae Kyung Im, Lenore J. Launer, Dennis O. Mook-Kanamori, Robert C. Kaplan, Hieab H.H. Adams, Maarten van den Berge, George T. O'Connor, Natalie Terzikhan, Rodney J. Scott, Ani Manichaikul, Ravi Kalhan, Guy Brusselle, Leslie A. Lange, Yohan Bossé, Qing Duan, Tamara B. Harris, Esteban G. Burchard, Albert M. Levin, Kent D. Taylor, Mi Kyeong Lee, Woo Jin Kim, Yongmei Liu, Vilmundur Gudnason, Nora Franceschini, Hongsheng Gui, James G. Wilson, Donglei Hu, Lavinia Paternoster, Thomas Hansen, Roby Joehanes, Tianyuan Wang, Jennifer Liberto, Victoria E. Jackson, Jianping Jin, Colleen M. Sitlani, Tianxiao Huan, Wei Gao, Michael A. Province, Christopher Oldmeadow, Tarunveer S. Ahluwalia, Alanna C. Morrison, Kari E. North, Stephen B. Kritchevsky, Michael H. Cho, Gleb Kichaev, Kaare Christensen, Renée de Mutsert, Lauren S. Mogil, Mark McEvoy, Xin-Qun Wang, Juan C. Celedón, Fernando Pires Hartwig, Wenbo Tang, Judith M. Vonk, Kristin M. Burkart, Heather E. Wheeler, Bharat Thyagarajan, John Attia, Kim de Jong, Bruce M. Psaty, Sina A. Gharib, Traci M. Bartz, Josée Dupuis, Stephanie J. London, Ma'en Obeidat, Jerome I. Rotter, Stephen S. Rich, Mary K. Wojczynski, Susan R. Heckbert, Albert V. Smith, Frits R. Rosendaal, Tobias Bonten, Tamar Sofer, Patricia A. Cassano, H. Marike Boezen, Sam S. Oh, Ana M. B. Menezes, Mary F. Feitosa, David C. Nickle, Jason L. Sanders, Bernardo L. Horta, Fernando C. Wehrmeister, Jennifer N. Nguyen, Annah B. Wyss, Jeanne C. Latourelle, Margaret M. Parker, R. Graham Barr, Elizabeth G. Holliday, Richard H. Myers, Cathy C. Laurie, Kurt Lohman, Lies Lahousse, Don D. Sin, André G. Uitterlinden, Shujie Xiao, Jennifer A. Brody, L. Keoki Williams, Joohon Sung, Raymond Noordam, Mariaelisa Graff, Erasmus MC other, Epidemiology, Radiology & Nuclear Medicine, Groningen Research Institute for Asthma and COPD (GRIAC), Life Course Epidemiology (LCE), Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, and University of Iceland

Subjects
0301 basic medicine, Lung Diseases, Male, Linkage disequilibrium, Epidemiology, Vital Capacity, General Physics and Astronomy, Genome-wide association study, VARIANTS, Genome-wide association studies, DISEASE, Linkage Disequilibrium, AIR-FLOW OBSTRUCTION, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, Forced Expiratory Volume, Genetics research, Medicine and Health Sciences, lcsh:Science, Lung, Genetics, education.field_of_study, Multidisciplinary, LARGE-SCALE, Smoking, SMOOTH-MUSCLE, Öndunarfærasjúkdómar, Genomics, Hispanic or Latino, 3. Good health, LUNG-FUNCTION, Meta-analysis, Regression Analysis, Female, Erfðarannsóknir, Science, Population, Quantitative Trait Loci, Black People, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, White People, 03 medical and health sciences, Humans, SMOKING-BEHAVIOR, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, 1000 Genomes Project, education, Genetic association, Respiratory tract diseases, Asian, Faraldsfræði, Biology and Life Sciences, General Chemistry, 030104 developmental biology, 030228 respiratory system, Sample Size, SEGREGATION ANALYSIS, lcsh:Q, FOLLOW-UP, Genome-Wide Association Study
Abstract

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci., Supported in part by the Intramural Research Program of the National Institutes of Health, NIEHS. Infrastructure for the CHARGE Consortium is supported in part by the National Heart, Lung, and Blood Institute Grant R01HL105756

Published
2018

42. Three Decades of Dementia Research: Insights from One Small Community of Indomitable Rotterdammers

Author

Hieab H.H. Adams, M. Arfan Ikram, Frank J. Wolters, Silvan Licher, Daniel Bos, Epidemiology, Neurology, and Radiology & Nuclear Medicine

Subjects
0301 basic medicine, Gerontology, medicine.medical_specialty, Population, Disease, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Intervention (counseling), Epidemiology, medicine, Dementia, Animals, Humans, education, Netherlands, education.field_of_study, General Neuroscience, Public health, General Medicine, medicine.disease, Psychiatry and Mental health, Clinical Psychology, 030104 developmental biology, Conviction, Geriatrics and Gerontology, Psychology, 030217 neurology & neurosurgery
Abstract

The most commonly encountered opening sentence in scientific publications about dementia undoubtedly relates to the overwhelming burden of disease. Finding an effective preventive or therapeutic intervention against dementia has been considered the most important unmet need in contemporary medicine. While efforts on tackling this devastating disease have increased exponentially, it is difficult to imagine that in the 1980s and early-1990s, the disease did not feature prominently on any public health report. Yet, it was already then that epidemiologists recognized the growing societal burden of dementia and rationalized that dementia is not necessarily part of aging. Indeed, the conviction that dementia is pathologically distinct from aging led to various efforts in search of unravelling its risk factors and understanding its pre-clinical phase. Among the early pioneers, the population-based Rotterdam Study was initiated in 1990 clearly aiming on chronic diseases including dementia, and among this Alzheimer's disease, as one of its focus points. Ever since, the Rotterdam Study has been an important cornerstone in increasing our knowledge about dementia from an epidemiological perspective. Here, we summarize the main findings originating from this study, and put these into perspective with previous and current work in the field. With an expanding scope of the Rotterdam Study over the years, we discuss findings on occurrence, modifiable risk factors, imaging, and its genetic underpinnings. Importantly, we conclude with recommendations- or, perhaps better stated, a wish list- for future research which may help us reach our finish line: finding an effective preventive or therapeutic intervention against dementia.

Published
2018

43. Heritability and genome-wide association study of diffusing capacity of the lung

Author

Bruno H. Stricker, Hieab H.H. Adams, Fangui Sun, Lies Lahousse, Josée Dupuis, George T. O'Connor, Natalie Terzikhan, Guy Brusselle, Daan Loth, Ken R. Bracke, Fien M. Verhamme, Epidemiology, Radiology & Nuclear Medicine, and Pulmonary Medicine

Subjects
Adult, Male, 0301 basic medicine, Pulmonary and Respiratory Medicine, medicine.medical_specialty, Population, Genome-wide association study, Polymorphism, Single Nucleotide, Receptors, G-Protein-Coupled, Pulmonary Disease, Chronic Obstructive, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Framingham Heart Study, DLCO, Internal medicine, Diffusing capacity, medicine, Humans, education, Lung, Aged, 030304 developmental biology, Carbon Monoxide, 0303 health sciences, COPD, education.field_of_study, Pulmonary Gas Exchange, business.industry, Middle Aged, respiratory system, Heritability, medicine.disease, 030104 developmental biology, 030228 respiratory system, Linear Models, Cardiology, Pulmonary Diffusing Capacity, Female, business, Genome-Wide Association Study
Abstract

Although several genome-wide association studies (GWAS) have investigated the genetics of pulmonary ventilatory function, little is known about the genetic factors that influence gas exchange. The aim of the study was to investigate the heritability of, and genetic variants associated with the diffusing capacity of the lung.GWAS was performed on diffusing capacity of the lung measured by carbon monoxide uptake (DLCO) and per alveolar volume (VA) using the single-breath technique, in 8372 individuals from two population-based cohort studies, the Rotterdam Study and the Framingham Heart Study. Heritability was estimated in related (n=6246) and unrelated (n=3286) individuals.Heritability of DLCO and DLCO/VA ranged between 23% and 28% in unrelated individuals and between 45% and 49% in related individuals. Meta-analysis identified a genetic variant in ADGRG6 that is significantly associated with DLCO/VA. Gene expression analysis of ADGRG6 in human lung tissue revealed a decreased expression in patients with chronic obstructive pulmonary disease (COPD) and subjects with decreased DLCO/VA.DLCO and DLCO/VA are heritable traits, with a considerable proportion of variance explained by genetics. A functional variant in ADGRG6 gene region was significantly associated with DLCO/VA. Pulmonary ADGRG6 expression was decreased in patients with COPD.

Published
2018

44. Genetic Determinants of Unruptured Intracranial Aneurysms in the General Population

Author

Meike W. Vernooij, Aad van der Lugt, Cornelia M. van Duijn, André G. Uitterlinden, Gabriel P. Krestin, Abbas Peymani, M. Arfan Ikram, Hieab H.H. Adams, Albert Hofman, Lotte G.M. Cremers, Epidemiology, Radiology & Nuclear Medicine, and Internal Medicine

Subjects
Male, medicine.medical_specialty, Population, Blood Pressure, Genome-wide association study, Polymorphism, Single Nucleotide, Asymptomatic, Cohort Studies, Rotterdam Study, Aneurysm, medicine, Humans, Genetic Predisposition to Disease, Prospective Studies, cardiovascular diseases, education, Prospective cohort study, Stroke, Aged, Netherlands, Advanced and Specialized Nursing, education.field_of_study, business.industry, Intracranial Aneurysm, Middle Aged, medicine.disease, Blood pressure, cardiovascular system, Female, Neurology (clinical), Radiology, medicine.symptom, Cardiology and Cardiovascular Medicine, business, Genome-Wide Association Study
Abstract

Background and Purpose— Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) for intracranial aneurysms in clinical samples. In addition, SNPs have been discovered for blood pressure, one of the strongest risk factors for intracranial aneurysms. We studied the role of these genetic variants on occurrence and size of unruptured intracranial aneurysms, discovered incidentally in a general community-dwelling population. Methods— In 4890 asymptomatic participants from the Rotterdam Study, 120 intracranial aneurysms were identified on brain imaging and segmented for maximum diameter and volume. Genetic risk scores (GRS) were calculated for intracranial aneurysms (10 SNPs), systolic blood pressure (33 SNPs), and diastolic blood pressure (41 SNPs). Results— The GRS for intracranial aneurysms was not statistically significantly associated with presence of aneurysms in this population (OR, 1.16; 95% CI, 0.96–1.40; P =0.119), but showed a significant association with both maximum diameter (difference in log-transformed mm per SD increase of GRS, 0.10; 95% CI, 0.02–0.19; P =0.018) and volume (difference in log-transformed µL per SD increase of GRS, 0.21; 95% CI, 0.01–0.41; P =0.040) of aneurysms. GRSs for blood pressures were associated with neither presence nor size of aneurysms. Conclusions— Genetic variants previously identified for intracranial aneurysms in clinical studies relate to the size rather than the presence of incidentally discovered, unruptured intracranial aneurysms in the general population.

Published
2015

45. Heritability and Genome-Wide Association Analyses of Human Gait Suggest Contribution of Common Variants

Author

Russell Thomson, Meike W. Vernooij, Vincentius J.A. Verlinden, Albert Hofman, Velandai Srikanth, Jos N. van der Geest, Hieab H.H. Adams, M. Arfan Ikram, Michele L. Callisaya, André G. Uitterlinden, Cornelia M. van Duijn, Epidemiology, Radiology & Nuclear Medicine, Internal Medicine, Neurosciences, and Neurology

Subjects
Male, 0301 basic medicine, Aging, medicine.medical_specialty, Genotype, Population, Poison control, Genome-wide association study, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Gait (human), Genetic variation, Humans, Medicine, Genetic Predisposition to Disease, Prospective Studies, education, Gait, Aged, Aged, 80 and over, Genetics, education.field_of_study, business.industry, Genetic Variation, Middle Aged, Heritability, Phenotype, 030104 developmental biology, Physical therapy, Female, Original Article, Geriatrics and Gerontology, business, human activities, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Human gait is a complex neurological and musculoskeletal function, of which the genetic basis remains largely unknown. To determine the influence of common genetic variants on gait parameters, we studied 2,946 participants of the Rotterdam Study, a population-based cohort of unrelated elderly individuals. We assessed 30 gait parameters using an electronic walkway, which yielded seven independent gait domains after principal component analysis. Genotypes of participants were imputed to the 1,000 Genomes reference panel for generating genetic relationship matrices to estimate heritability of gait parameters, and for subsequent genome-wide association scans (GWASs) to identify specific variants. Gait domains with the highest age- and sex-adjusted heritability were Variability (h (2) = 61%), Rhythm (37%), and Tandem (32%). For other gait domains, heritability estimates attenuated after adjustment for height and weight. Genome-wide association scans identified a variant on 1p22.3 that was significantly associated with single support time, a variable from the Rhythm domain (rs72953990; N = 2,946; beta [SE] = 0.0069 (0.0012), p = 2.30x10(-8)). This variant did not replicate in an independent sample (N = 362; p = .78). In conclusion, human gait has highly heritable components that are explained by common genetic variation, which are partly attributed to height and weight. Collaborative efforts are needed to identify robust single variant associations for the heritable parameters.

Published
2015

46. Genetic risk of neurodegenerative diseases is associated with mild cognitive impairment and conversion to dementia

Author

Peter J. Koudstaal, Hieab H.H. Adams, M. Arfan Ikram, Cornelia M. van Duijn, Meike W. Vernooij, André G. Uitterlinden, Renée F.A.G. de Bruijn, Albert Hofman, Epidemiology, Radiology & Nuclear Medicine, Neurology, and Internal Medicine

Subjects
Oncology, Male, medicine.medical_specialty, Parkinson's disease, Genotyping Techniques, Epidemiology, Population, Clinical Neurology, Frontotemporal lobar degeneration, Rotterdam Study, Cellular and Molecular Neuroscience, Developmental Neuroscience, Risk Factors, Internal medicine, mental disorders, medicine, Genetics, Dementia, Humans, Cognitive Dysfunction, Genetic Predisposition to Disease, Prospective Studies, Amyotrophic lateral sclerosis, Psychiatry, education, Aged, Netherlands, education.field_of_study, Framingham Risk Score, Health Policy, Mild cognitive impairment, Neurodegenerative Diseases, Odds ratio, Alzheimer's disease, medicine.disease, Psychiatry and Mental health, Disease Progression, Female, Neurology (clinical), Geriatrics and Gerontology, Psychology, Follow-Up Studies
Abstract

Introduction: Neurodegenerative diseases are a major cause of cognitive impairment and can ultimately lead to dementia. Genome-wide association studies have uncovered many genetic variants conferring risk of neurodegenerative diseases, but their role in cognitive impairment remains unexplored. Methods: In the prospective, population-based Rotterdam Study, 3605 nondemented persons aged >= 55 years were genotyped, screened for mild cognitive impairment (MCI) in 2002 to 2005 and underwent continuous follow-up for dementia until 2012. Weighted polygenic risk scores of genetic variants for Alzheimer's disease (AD), Parkinson's disease (PD), and the frontotemporal lobar degeneration/amyotrophic lateral sclerosis disease spectrum (FTLD/ALS) were constructed and investigated for association with MCI and the subsequent conversion to dementia. Results: In total, 360 (10.0%) persons had MCI, of whom 147 (4.1%) were amnestic and 213 (5.9%) nonamnestic. The AD risk score was associated with both MCI subtypes (odds ratio for all MCI 1.15 [95% CI, 1.03-1.28]), whereas PD and FTLD/ALS risk scores were associated only with nonamnestic MCI (odds ratios 1.15 [1.00-1.32] and 1.19 [1.03-1.37], respectively). The AD risk score, but not PD and FTLD/ALS risk scores, was associated with an increased risk of dementia (hazard ratio 1.55 [1.37-1.77]). Discussion: Genetic evidence supports the view that multiple neurodegenerative pathways lead to MCI and that the subsequent conversion to dementia, primarily of the AD subtype, is mainly due to the AD pathway(s). (C) 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Published
2015

47. The low single nucleotide polymorphism heritability of plasma and saliva cortisol levels

Author

Nese Direk, Jennifer L. Bolton, Alexander Neumann, Erin Payne, Yolanda B. de Rijke, Jennifer A. Smith, Brian R. Walker, Andrew A Crawford, Jouke J. Hottenga, Brenda W.J.H. Penninx, Saira Saeed Mirza, Eco J. C. de Geus, Caroline Hayward, Henning Tiemeier, David P. Strachan, Peter J. van der Most, Hieab H.H. Adams, Yuri Milaneschi, Albertine J. Oldehinkel, Child and Adolescent Psychiatry / Psychology, Epidemiology, Radiology & Nuclear Medicine, Clinical Chemistry, Biological Psychology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, APH - Digital Health, and Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE)

Subjects
Male, 0301 basic medicine, Saliva, Hydrocortisone, Endocrinology, Diabetes and Metabolism, CHILDHOOD, Genome-wide association study, Cortisol, Cohort Studies, Endocrinology, GWAS, DIURNAL CORTISOL, ASSOCIATIONS, Netherlands, Morning, Aged, 80 and over, OBJECTIVES, Middle Aged, Psychiatry and Mental health, ADOLESCENCE, Female, HEALTH, hormones, hormone substitutes, and hormone antagonists, medicine.drug, medicine.medical_specialty, endocrine system, DISORDERS, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Heritability, 03 medical and health sciences, Internal medicine, Genetics, Journal Article, medicine, Humans, SNP, METAANALYSIS, Biological Psychiatry, Aged, Genetic association, Endocrine and Autonomic Systems, Single nucleotide polymorphism, 030104 developmental biology, ATHEROSCLEROSIS, Single Nucleotide Polymorphism, PATTERNS, Genome-Wide Association Study
Abstract

Cortisol is an important stress hormone affected by a variety of biological and environmental factors, such as the circadian rhythm, exercise and psychological stress. Cortisol is mostly measured using blood or saliva samples. A number of genetic variants have been found to contribute to cortisol levels with these methods. While the effects of several specific single genetic variants is known, the joint genome-wide contribution to cortisol levels is unclear. Our aim was to estimate the amount of cortisol variance explained by common single nucleotide polymorphisms, i.e. the SNP heritability, using a variety of cortisol measures, cohorts and analysis approaches. We analyzed morning plasma (n = 5705) and saliva levels (n = 1717), as well as diurnal saliva levels (n = 1541), in the Rotterdam Study using genomic restricted maximum likelihood estimation. Additionally, linkage disequilibrium score regression was fitted on the results of genome-wide association studies (GWAS) performed by the CORNET consortium on morning plasma cortisol (n = 12,597) and saliva cortisol (n = 7703). No significant SNP heritability was detected for any cortisol measure, sample or analysis approach. Point estimates ranged from 0% to 9%. Morning plasma cortisol in the CORNET cohorts, the sample with the most power, had a 6% [95%CI: 0-13%] SNP heritability. The results consistently suggest a low SNP heritability of these acute and short-term measures of cortisol. The low SNP heritability may reflect the substantial environmental and, in particular, situational component of these cortisol measures. Future GWAS will require very large sample sizes. Alternatively, more long-term cortisol measures such as hair cortisol samples are needed to discover further genetic pathways regulating cortisol concentrations.

Published
2017

48. Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

Author

John Hardy, Nick C. Fox, Lena Lilius, Christine Van Broeckhoven, Mindy J. Katz, Carlos Cruchaga, Joshua W. Miller, Carol Brayne, Letizia Concari, Christopher Shaw, Minerva M. Carrasquillo, Richard Mayeux, Anne Boland, Charles DeCarli, Helena C. Chui, Laura B. Cantwell, Yoland Aladro Benito, Chuang Kuo Wu, Elaine R. Peskind, Andrew McDavid, M. Ilyas Kamboh, Amanda Smith, Pascual Sánchez-Juan, Jean-François Deleuze, Jayanadra J. Himali, Thomas H. Mosley, Thomas J. Montine, Chuanhai Cao, Andreas J. Forstner, Thomas G. Beach, Robert Barber, Miquel Aguilar, Liming Qu, Jerome I. Rotter, Matthew J. Huentelman, Christiane Reitz, Christopher J. O'Donnell, Steven G. Younkin, Bradley T. Hyman, Bruce L. Miller, Rachelle S. Doody, Eric B. Larson, Ronald L. Hamilton, Todd E. Golde, Steven E. Arnold, Melissa E. Garcia, Rachel Raybould, Lena Kilander, Mark A. Sager, Kevin Morgan, Kathryn L. Lunetta, William Perry, Joseph D. Buxbaum, Craig S. Atwood, Thomas D. Bird, Michael Conlon O'Donovan, Robert Olaso, Juan Fortea, Susanne Moebus, Lisa L. Barnes, Rachel Marshall, Huntington Potter, Mercè Boada, Shahzad Ahmad, Paolo Caffarra, Daniel C. Marson, Jonathan L. Haines, Perrie M. Adams, John M Olichney, Lars Lannfelt, Stefanie Heilmann-Heimbach, Markus M. Nöthen, Shubhabrata Mukherjee, John Malamon, Xue Wang, Christopher S. Carlson, Karen Ritchie, Roger N. Rosenberg, Paul K. Crane, Alexa S. Beiser, Céline Bellenguez, Robert C. Green, Maria Urbano, Petra Proitsi, John Powell, Elisa Majounie, Ammar Al-Chalabi, Hakon Hakonarson, Yogen Patel, Martin Scherer, Julie Williams, Richard B. Lipton, Vincent Dermecourt, Adam L. Boxer, Gerard D. Schellenberg, David G. Clark, Anita L. DeStefano, Joel H. Kramer, Victoria Alvarez, Nandini Badarinarayan, Oscar L. Lopez, Chris Corcoran, Ubaldo Bonuccelli, Donald R. Royall, James Bowen, Monica Diez Fairen, Tricia A. Thornton-Wells, Nilufer Ertekin-Taner, Florence Pasquier, Martin Ingelsson, Yi Zhao, John R. Gilbert, Valentina Escott-Price, Amanda B. Kuzma, Fabienne Garzia, Reinhard Heun, Otto Valladares, Andrew J. Saykin, Sara Ortega-Cubero, Liana G. Apostolova, Henry L. Paulson, John K Kauwe, Imelda Barber, Carolina Ceballos Diaz, Douglas Galasko, M. Arfan Ikram, Lluís Tárraga, Carlo Caltagirone, Joan S. Reisch, Wolfgang Maier, Bruno Vellas, Rebecca Sims, Angela Hodges, Matthew P. Frosch, Isabel Henández, Annakaisa Haapasalo, Thor Aspelund, Håkan Thonberg, Aimee Pierce, Roger L. Albin, Wayne W. Poon, Rebecca Sussams, Amy Braddel, Ranjan Duara, Albert V. Smith, Kirk C. Wilhelmsen, Gianfranco Spalletta, Simon Lovestone, Peter Passmore, Ana Frank-García, Cynthia M. Carlsson, Jade Chapman, Nathan D. Price, Philip L. De Jager, John M. Ringman, Seung Hoan Choi, Nicola Denning, Michael John Owen, Clinton T. Baldwin, Amalia C. Bruni, Denis A. Evans, Rudolph E. Tanzi, Dominique Campion, Laura Fratiglioni, Alberto Lleó, Per Hoffmann, Carole Dufouil, Charlotte Forsell, Alun Meggy, Charlene Thomas, Robert S. Stern, James B. Leverenz, Tatiana Foroud, William W. Seeley, James J. Lah, Brian A. Lawlor, Kenneth B. Fallon, Matthias Riemenschneider, Ryan M. Huebinger, Regina M. Carney, Clinton B. Wright, Didier Hannequin, Deborah Blacker, Anne Kinhult-Ståhlbom, Ekaterina Rogaeva, Andrew P. Lieberman, Bernardino Ghetti, Linda J. Van Eldik, Bernadette McGuinness, Thomas Fairchild, Margaret A. Pericak-Vance, Ashok Raj, Reinhold Schmidt, Ronald C. Petersen, Harald Hampel, María J. Bullido, Steven L. Carroll, Maria Candida Deniz Naranjo, Kathleen A. Welsh-Bohmer, Myriam Fornage, Joseph F. Quinn, Caroline Graff, Claudia L. Satizabal, Patrice L. Whitehead, David Wallon, Christopher Medway, Lindsay A. Farrer, Vilmundur Gudnason, Peter St George-Hyslop, Pau Pastor, Frank Jessen, Erin L. Abner, Johanna Jakobsdottir, Hieab H.H. Adams, Roberta Cecchetti, Walter A. Kukull, Thomas S. Wingo, Michelle K. Lupton, Valur Emilsson, Susan M. McCurry, Simon Mead, Hilkka Soininen, Sandra Weintraub, Amy Gerrish, Lindy E. Harrell, Lina Keller, Jean-Charles Lambert, Denise Harold, Stephen Todd, Wei Gu, Maura Gallo, Najaf Amin, Lenore J. Launer, Eleonora Sacchinelli, Mikko Hiltunen, Cécile Dulary, Eliecer Coto, Xueqiu Jian, Nathalie Fievet, Patrizia Mecocci, Sarah Taylor, Eric Boerwinkle, Maria Serpente, Ronald G. Munger, Ina Giegling, Carlo Masullo, Aoibhinn Lynch, Eliezer Masliah, Anne M. Koivisto, Chang En Yu, Qiong Yang, Benedetta Nacmias, Wayne C. McCormick, Kristelle Brown, Alessio Squassina, Deborah C. Mash, Brian W. Kunkle, Makrina Daniilidou, Alison Goate, David Carrell, Kara L. Hamilton-Nelson, Sandra Barral, Vincent Chouraki, Kristel Sleegers, Frank J. Wolters, Joseph E. Parisi, Iwona Kłoszewska, Ronald C. Kim, Sonia Moreno-Grau, Marina Arcaro, Carmen Muñoz Fernadez, Vernon S. Pankratz, Duane Beekly, Sabrina Pichler, Gislain Septier, Delphine Bacq, Amanda J. Myers, Adam C. Naj, Frank Martiniuk, Sudha Seshadri, Badri N. Vardarajan, Joshua A. Sonnen, M.-Marsel Mesulam, Howard J. Rosen, James T. Becker, Chiara Fenoglio, Ge Li, Alberto Pilotto, Mary Sano, Olivier Hanon, Honghuang Lin, Jean Paul G. Vonsattel, W. T. Longstreth, Daniela Galimberti, David C. Rubinsztein, RoseMarie Brundin, Vilmantas Giedraitis, Christine M. Hulette, Peter Holmans, Martin Dichgans, Maria Vronskaya, Céline Derbois, Michelangelo Mancuso, Constantine G. Lyketsos, Christophe Tzourio, Jacques Epelbaum, Raffaele Maletta, Mariet Allen, Hong-Dong Li, James R. Burke, Rik Vandenberghe, David G. Mann, Bruce M. Psaty, Lawrence S. Honig, Beth A. Dombroski, Erik D. Roberson, Cornelia M. van Duijn, Benjamin Grenier-Boley, Seppo Helisalmi, Jean-François Dartigues, Russell H. Swerdlow, Paola Bossù, Ashley R. Winslow, Elio Scarpini, Lesley Jones, Sebastien Engelborghs, John Q. Trojanowski, Jeffrey Kaye, Jenny Lord, Chiara Cupidi, Janet A. Johnston, Dan Rujescu, Feroze Golamaully, Anne Braae, Rafael Blesa, L. Adrienne Cupples, Dennis W. Dickson, Gail P. Jarvik, David W. Fardo, David H. Cribbs, Michael Gill, Jose Bras, Allan I. Levey, Jennifer Williamson, Rhodri Thomas, John C. Morris, Lei Yu, Debby W. Tsuang, Annette M. Hartmann, John H. Growdon, John Collinge, Claudine Berr, Fernando Rivadeneira, Oliver Peters, Albert Hofman, Frank M. LaFerla, Vivianna M. Van Deerlin, James Uphill, David A. Bennett, Onofre Combarros, Gudny Eiriksdottir, Jeremy D. Burgess, Melanie L. Dunstan, Elizabeth Crocco, Keeley J. Brookes, Robert R. Graham, Lon S. Schneider, Eden R. Martin, Matt Hill, Neill R. Graff-Radford, Joseph T. Hughes, Vincenzo Solfrizzi, Taniesha Morgan, Antonio Ciaramella, Bruno Dubois, Juan C. Troncoso, Paolo Bosco, Jordi Clarimón, Daniel H. Geschwind, Virginia Boccardi, Barry Reisberg, Timothy W. Behrens, Annette L. Fitzpatrick, Salvatore Spina, Alexis Brice, Eileen H. Bigio, Marla Gearing, Jeffrey M. Burns, Carol A. Miller, Marilyn S. Albert, Sven J. van der Lee, Sandro Sorbi, C. Dirk Keene, Daniel Levy, Antonio Daniele, Eric M. Reiman, Paramita Chakrabarty, Oscar Sotolongo-Grau, Helena Schmidt, Francesco Panza, Murray A. Raskind, Rita Guerreiro, Gyungah Jun, Anna Karydas, Markus Leber, Harry V. Vinters, Cory C. Funk, Charles C. White, Jill R. Murrell, Sid E. O'Bryant, Nigel J. Cairns, Josée Dupuis, Ann C. McKee, Julie A. Schneider, Megan L. Grove, Malcolm B. Dick, Bradley F. Boeve, Jennifer A. Brody, Sanjay Asthana, Agustín Ruiz, Stefan Herms, Yuning Chen, David Craig, Neil W. Kowall, Maria Donata Orfei, JoAnn T. Tschanz, Florentino Sanchez Garcia, Manuel Mayhaus, Alfredo Ramirez, James Turton, André G. Uitterlinden, Davide Seripa, Lee-Way Jin, Kelley Faber, Maria C. Norton, Shuo Li, Steven H. Ferris, Steffi G. Riedel-Heller, Joshua C. Bis, Li-San Wang, Johannes Kornhuber, Peter Paul De Deyn, Martin R. Farlow, Randall L. Woltjer, Gary W. Beecham, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Hospital of the University of Pennsylvania (HUP), Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia], Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Icelandic Heart Association [Kopavogur, Iceland] (IHA), John P. Hussman Institute for Human Genomics [Miami, FL, USA], University of Miami [Coral Gables], Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Department of Medicine, University of Washington [Seattle], Dr. John T. Macdonald Foundation [Miami, FL, USA] (Department of Human Genetics), Epidémiologie des maladies chroniques : impact des interactions gène environnement sur la santé des populations, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé, Department of Genomics [Bonn, Germany] (Institute of Human Genetics), University of Bonn-Institute of Human Genetics [Bonn, Germany], Department of Molecular Genetics, Institut Català de Neurociències Aplicades [Barcelona, Spain], Well Advanced Solutions, Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], The University of Texas Health Science Center at Houston (UTHealth), Columbia University [New York], University of Eastern Finland, Life & Brain Center - Department of Genomics, Rheinische Friedrich-Wilhelms-Universität Bonn, Génétique, Reproduction et Développement (GReD), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de la Santé et de la Recherche Médicale (INSERM), John P. Hussman Institute for Human Genomics, Neurobiologie de la Croissance et de la Senescence, Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Emmy Noether Project (SFB 833), Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, Boston University [Boston] (BU), Department of Genomics, Institute for Systems Biology [Seattle, WA, USA], Universitätsklinikum Bonn (UKB), Centre of Excellence for Robotic Vision [Canberra], Australian Research Council [Canberra] (ARC), Neuroscience and Mental Health Research Institute [Cardiff, UK] (School of Medicine), Boston University School of Medicine (BUSM), Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, University of Pennsylvania [Philadelphia], Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Department of Epidemiology and Biostatistics, ERASMUS, Hospital Universitario Doctor Negrín [Las Palmas de Gran Canaria, Spain], Department of Neurodegenerative Diseases, University of Mississippi Medical Center (UMMC), Pathology and Laboratory Medicine [Philadelphia, PA, USA] (Penn Neurodegeneration Genomics Center), UNIROUEN - UFR Santé (UNIROUEN UFR Santé), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Génétique du cancer et des maladies neuropsychiatriques (GMFC), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bioinformatics, GlaxoSmithKline, Aging Research Center [Karolinska Institutet] (ARC ), Stockholm University-Karolinska Institutet [Stockholm], University of Nottingham, UK (UON), University of Texas Health Science Center, Department of Neurobiology, Caring Sciences and Society (NVS), University of Bari Aldo Moro (UNIBA), Ageing Group, Centre for Public Health, Queen's University [Belfast] (QUB), Mayo Clinic [Jacksonville], Maurice Wohl Clinical Neuroscience Institut, King‘s College London, Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale Casa Sollievo della Sofferenza [San Giovanni Rotondo] (IRCCS), Università degli Studi di Perugia (UNIPG), Framingham Heart Study, Boston University [Boston] (BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), CHU Rouen, Normandie Université (NU), Universidad Autonoma de Madrid (UAM), Centro de Investigacion Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III [Madrid] (ISC), National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), University of Florida [Gainesville] (UF), University of Parma = Università degli studi di Parma [Parme, Italie], Center for Cognitive Disorders AUSL [Parma, Italy], School of Public Health [Boston], Uppsala University, Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Xi'an Jiaotong University (Xjtu), Department of Public health and Caring Sciences, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden, Institute of Gerontology and Geriatrics, Troubles cognitifs dégénératifs et vasculaires - U 1171 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Geriatric Medicine and Metabolic Diseases, Departments of Nuclear Medicine, University Medical Centre Hamburg-Eppendorf [Hamburg, Germany], University of Texas Southwestern Medical Center [Dallas], University of Cologne, Laboratoire d'Etudes et de Recherche en Informatique d'Angers (LERIA), Université d'Angers (UA), Johns Hopkins University (JHU), Universität Leipzig [Leipzig], University of Iceland [Reykjavik], Metacohorts Consortium, Harvard School of Public Health, Catholic University of Rome, Medical University Graz, Baylor College of Medicine (BCM), Baylor University, University of North Texas Health Science Center [Fort Worth], Santa Lucia Foundation (IRCCS), Nextel S.A. [Bilbao], Massachusetts General Hospital [Boston], Department of Pathology and Laboratory Medicine and Indiana Alzheimer disease Center, Indiana University School of Medicine, Indiana University System-Indiana University System, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), Beijing University of Technology, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Saul B. Korey Department of Neurology, Albert Einstein College of Medicine [New York]-Yeshiva University, Utah State University (USU), Fundació per la Recerca Biomèdica i Social Mútua Terrassa [Barcelona, Spain], Hospital Universitario Mutua de Terrassa, Département de neurologie [Montpellier], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [Montpellier]-Université de Montpellier (UM), Department of neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland, Department of neurology, University of Eastern Finland-University Hospital of Kuopio-University of Eastern Finland-University Hospital of Kuopio, Medical University of Łódź (MUL), University of Leicester, MRC Prion Unit, Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, University of Milan, Fondazione Istituto di Ricerca e Cura Carattere Scientifico [Rome], Università degli Studi di Roma Tor Vergata [Roma], Saarland University Hospital, Universitat Autònoma de Barcelona (UAB), Regional Neurogenetic Centre [Lamezia Terme, Italy] (CRN - ASP Catanzaro), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Universidade do Porto, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Experimental and Clinical Pharmacology, St. James Hospital and Trinity College [Dublin, Ireland], School of Medicine [Dublin], Trinity College Dublin, University of Sheffield [Sheffield], Lancaster University, University of Michigan [Ann Arbor], University of Michigan System, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, University of Wisconsin-Madison, Rush Alzheimer Disease Center [Chicago, IL, États-Unis], Rush University Medical Center [Chicago], Institute for Advanced Biosciences / Institut pour l'Avancée des Biosciences (Grenoble) (IAB), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), School of Engineering [Cardiff], Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Northwestern University Feinberg School of Medicine, Mayo Clinic [Rochester], Swedish Medical Center [Seattle, WA, USA], University of California [San Francisco] (UCSF), University of California, Duke University [Durham], University of Kansas Medical Center [Lawrence], Laboratory of Molecular Neuropsychiatry, Icahn School of Medicine at Mount Sinai [New York] (MSSM), Washington University in Saint Louis (WUSTL), University of South Florida [Tampa] (USF), Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Medical University of South Carolina [Charleston] (MUSC), University of Southern California (USC), Los Alamos National Laboratory (LANL), Centre de biologie du développement (CBD), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre de Biologie Intégrative (CBI), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Neurology Department, University of California, Davis (UCDavis-Neuro), University of California [Davis] (UC Davis), University of California [Irvine] (UCI), Mount Sinai Medical Center, Indiana State University, University of Alabama at Birmingham [ Birmingham] (UAB), University of Kentucky, New York University [New York] (NYU), NYU System (NYU), Department of Medical and Molecular Genetics, Department of Epidemiology and biostatistics, VU University Medical Center [Amsterdam], Emory University [Atlanta, GA], Department of Neurology, University of California-University of California-David Geffen School of Medicine [Los Angeles], Brigham & Women’s Hospital [Boston] (BWH), Harvard Medical School [Boston] (HMS), Department of Medical Genetics, HMNC Brain Health, Alzheimer Disease Research Laboratory, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Oregon Health and Science University [Portland] (OHSU), Cleveland Clinic, Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Department of Psychiatry, School of Medicine-Johns Hopkins University and Johns Hopkins Bayview Medical Center, Douglas Mental Health University Institute [Montréal], McGill University = Université McGill [Montréal, Canada], Department of neurosciences, University of California [San Diego] (UC San Diego), Department of Physics and Astronomy [Fort Worth], Texas Christian University (TCU), Department of Computer Science [University of California, Davis], Indiana University System, Institute for Aging and Alzheimer’s Disease Research [Fort Worth] (IAADR), Department of Laboratory Medicine and Pathology, Mayo Clinic, Institute for Memory Impairments and Neurological Disorders [Irvine], University of Colorado Anschutz [Aurora], Tanz Center Research in Neurodegenerative Diseases [Toronto], University of Toronto, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Keck School of Medicine [Los Angeles], Indiana University [South Bend], Massachusetts General Hospital, Novartis Institutes for Biomedical Research [Cambridge, MA, USA], Departments of Pathology and Laboratory Medicine (Neuropathology) and Neurology, UCLA Medical Center-David Geffen School of Medicine [Los Angeles], University of California-University of California-University of California [Los Angeles] (UCLA), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Institut de Génomique d'Evry (IG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, University of Antwerp (UA), Institute Born-Bunge, Karolinska Institutet [Stockholm], Karolinska University Hospital [Stockholm], University of Kuopio, Centre Mémoire de Ressources et de Recherche [Lille-Bailleul] (CMRR), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Hôpital Roger Salengro [Lille], Laboratoire d'Analyse Génomique, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Inserm-U1167, Dpt Gériatrie [CHU Broca], AP-HP - Hôpital Cochin Broca Hôtel Dieu [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Neuroépidémiologie, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Department of Epidemiology, University of Washington, School of Medicine [Los Angeles], Albert Einstein College of Medicine [New York], IdiPAZ - Instituto de Investigación La Paz [Madrid, Spain], Instituto de Física Teórica UAM/CSIC (IFT), Universidad Autonoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Department of Internal Medicine, University of Central Asturias [Oviedo, Spain], Human Genome Sequencing Center, Baylor College of Medicine, Baylor University-Baylor University, Department of Epidemiology, Erasmus Medical Centre, Translational Genomics Research Institute [Phoenix, AZ, USA], University of Arizona, Banner Alzheimer's Institute [Phoenix, AZ, États-Unis], University of Texas Health Science Center at San Antonio [San Antonio], Mount Sinai School of Medicine, Department of Psychiatry-Icahn School of Medicine at Mount Sinai [New York] (MSSM), Department. of Neurological Sciences, University of Milan, IRCCS Ospedale Maggiore Policlinico, Centre for Research in Neurodegenerative Diseases, VA Puget Sound Health Care System/GRECC [Seattle, WA, USA], University of Pisa - Università di Pisa, Pfizer Worldwide Research and Development [Cambridge, MA, USA], Università cattolica del Sacro Cuore [Piacenza e Cremona] (Unicatt), Texas Tech University Health Sciences Center, Texas Tech University [Lubbock] (TTU), Saarland University [Saarbrücken], University of Bonn, Department of Public Health and Primary Care, University of Cambridge [UK] (CAM), Cambridge Institute for Medical Research (CIMR), Department of Molecular Neurosciences, Institute of Neurology, UCL, Institute of Psychiatry, Institute of psychiatry, University of British Columbia (UBC), the Clinical Neuroscience Research Group, University of Manchester [Manchester]-Greater Manchester Neurosciences Centre, Aristotle University of Thessaloniki, Memory and Dementia Centre, 3rd Department of Neurology, G. Pa, University of Barcelona, University of Southampton, Department of Psychiatry [Oxford] (POWIC), University of Oxford [Oxford]-The Warneford Hospital, School of Psychology [Cardiff University], Department of Medical Sciences, UCL, Institute of Neurology [London], Washington University School of Medicine, Netherlands Genomics Initiative, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), School of Medecine, Center for Translational and Computational Neuroimmunology [New York, NY, États-Unis] (CTCN), Department of Neurology [New York, NY, États-Unis], Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York]-Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York], School of Life Sciences, Department of Neuroscience, Mayo Clinic Jacksonville, Icelandic Heart Association, Heart Preventive Clinic and Research Institute, Klinik für Psychiatrie, Martin-Luther-University Halle-Wittenberg, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Clínica Universidad de Navarra [Pamplona], Neurodegenerative Brain Diseases Group, VIB, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University-Medical Research Council, Brigham Young University (BYU), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, The Gertrude H Sergivesky Center, Columbia University College of Physicians and Surgeons, Genetic Epidemiology Unit, Section of Clinical and Molecular Neurogenetics, Universität zu Lübeck [Lübeck], University of Pennsylvania - Department of Pathology & Laboratory Medecine, Framingham Heart Study [Framingham, MA, USA], ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), European Project: 29845,LSH-ACC-MENTOR, University of Pennsylvania-University of Pennsylvania, Universität Bonn = University of Bonn-Institute of Human Genetics [Bonn, Germany], Universität Leipzig-Universität Leipzig, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Università degli Studi di Perugia = University of Perugia (UNIPG), Universidad Autónoma de Madrid (UAM), Università degli studi di Parma = University of Parma (UNIPR), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC)-CHU Pitié-Salpêtrière [AP-HP], Troubles cognitifs dégénératifs et vasculaires - U 1171 - EA 1046 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Universität Leipzig, Università cattolica del Sacro Cuore = Catholic University of the Sacred Heart [Roma] (Unicatt), Yeshiva University- Albert Einstein College of Medicine [New York], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [CHU Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université de Montpellier (UM), Università degli Studi di Milano = University of Milan (UNIMI), Saarland University Hospital (UKS), Università degli Studi di Firenze = University of Florence (UniFI), Universidade do Porto = University of Porto, University of California (UC)-University of California (UC), University of California [San Francisco] (UC San Francisco), University of California (UC), University of Kansas Medical Center [Kansas City, KS, USA], Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), University of California [Irvine] (UC Irvine), University of Kentucky (UK), University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Groupe de recherche clinique Alzheimer Precision Medicine (GRC 21 - APM), Sorbonne Université (SU), Universidad Autónoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), University of Texas Health Science Center at San Antonio [San Antonio, Tx, USA], Universität Bonn = University of Bonn, University of Oxford-The Warneford Hospital, Medical Research Council-Cardiff University, Universität zu Lübeck = University of Lübeck [Lübeck], Epidemiology, Neurology, Gastroenterology & Hepatology, Internal Medicine, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement (Inserm U1167 - RID-AGE - Institut Pasteur), Génétique, Reproduction et Développement - Clermont Auvergne (GReD), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Eberhard Karls Universität Tübingen, IRCCS 'Casa Sollievo della Sofferenza', Centro de Investigación Biomédica en Red para Enfermedades Neurodegenerativas (Ciberned), University of Florida [Gainesville], University of Parma, Troubles cognitifs dégénératifs et vasculaires (U1171), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-INSERM, Yeshiva University- Albert Einstein College of Medicine, Institut d’Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520 (IEMN), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Université Polytechnique Hauts-de-France (UPHF)-Ecole Centrale de Lille-Université Polytechnique Hauts-de-France (UPHF)-Institut supérieur de l'électronique et du numérique (ISEN), Autonomous University of Barcelona (UAB), Università degli Studi di Firenze [Firenze], Universidade do Porto [Porto], Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Washington University in St Louis, University of South Florida (USF), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, McGill University, Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Centre National de la Recherche Scientifique (CNRS), Neuropsychiatrie : recherche épidémiologique et clinique, Alzheimer Precision Medicine GRC n°21 (APM), CHU Pitié-Salpêtrière [APHP], Albert Einstein College of Medicine, Universidad Autonoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Università Cattolica del S. Cuore - Catholic University of the Sacred Hearth, University of Florence (UNIFI), CIBER de Enfermedades Neurodegenerativas (CIBERNED), Universität zu Lübeck [Lübeck] - University of Lübeck [Lübeck], [ANR-10-IAIHU-06],« Investissements d'avenir » ,Agence nationale de la recherche (ANR), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Icahn School of Medicine at Mount Sinai [New York] (MSSM)-Department of Psychiatry, van der Lee, Sven J [0000-0003-1606-8643], Naj, Adam C [0000-0002-9621-2942], Badarinarayan, Nandini [0000-0002-6944-748X], Chouraki, Vincent [0000-0002-4698-1794], Graham, Robert R [0000-0001-7151-4277], Hoffmann, Per [0000-0002-6573-983X], Smith, Albert V [0000-0003-1942-5845], Satizabal, Claudia L [0000-0002-1115-4430], Brody, Jennifer A [0000-0001-8509-148X], Wolters, Frank J [0000-0003-2226-4050], Lupton, Michelle K [0000-0002-7274-7299], Lin, Honghuang [0000-0003-3043-3942], Adams, Hieab H [0000-0003-3687-2508], Giedraitis, Vilmantas [0000-0003-3423-2021], Pasquier, Florence [0000-0001-9880-9788], Chen, Yuning [0000-0002-7358-7055], Bossù, Paola [0000-0002-1432-0078], Ghetti, Bernardino [0000-0002-1842-8019], Yang, Qiong [0000-0002-3658-1375], Aspelund, Thor [0000-0002-7998-5433], Bullido, María J [0000-0002-6477-1117], Rivadeneira, Fernando [0000-0001-9435-9441], Rubinsztein, David C [0000-0001-5002-5263], Al-Chalabi, Ammar [0000-0002-4924-7712], Tsolaki, Magda [0000-0002-2072-8010], De Jager, Philip L [0000-0002-8057-2505], Dickson, Dennis W [0000-0001-7189-7917], Van Broeckhoven, Christine [0000-0003-0183-7665], Ikram, M Arfan [0000-0003-0372-8585], Amouyel, Philippe [0000-0001-9088-234X], Lambert, Jean-Charles [0000-0003-0829-7817], Apollo - University of Cambridge Repository, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 APM), Berr, Claudine, Institut de Neurosciences Translationnelles de Paris - - IHU-A-ICM2010 - ANR-10-IAHU-0006 - IAHU - VALID, and Mentoring of LifeSciHealth-Multipliers in the Accession Candidate Countries - LSH-ACC-MENTOR - 29845 - OLD

Subjects
0301 basic medicine, Linkage disequilibrium, [SDV]Life Sciences [q-bio], Medizin, Sequence Homology, Genome-wide association study, genetics [Alzheimer Disease], metabolism [Microglia], Linkage Disequilibrium, 0302 clinical medicine, genetics [Protein Interaction Maps], genetics [Membrane Glycoproteins], Gene Frequency, Immunologic, genetics [Adaptor Proteins, Signal Transducing], Receptors, genetics [Exome], Odds Ratio, Innate, genetics [Receptors, Immunologic], Exome, Protein Interaction Maps, genetics [Genetic Predisposition to Disease], Receptors, Immunologic, ABI3 protein, human, Genetics, Adaptor Proteins, Signal Transducing, Alzheimer Disease, Amino Acid Sequence, Case-Control Studies, Gene Expression Profiling, Genetic Predisposition to Disease, Genotype, Humans, Immunity, Innate, Membrane Glycoproteins, Microglia, Phospholipase C gamma, Sequence Homology, Amino Acid, Polymorphism, Single Nucleotide, Adaptor Proteins, Single Nucleotide, 3. Good health, [SDV] Life Sciences [q-bio], Amino Acid, Settore MED/26 - NEUROLOGIA, genetics [Phospholipase C gamma], [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Alzheimer's disease, Common disease-common variant, Biology, Article, 03 medical and health sciences, ddc:570, medicine, Journal Article, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Polymorphism, Allele frequency, TREM2 protein, human, TREM2, Case-control study, Signal Transducing, Immunity, medicine.disease, R1, Minor allele frequency, genetics [Immunity, Innate], 030104 developmental biology, Human medicine, 030217 neurology & neurosurgery
Abstract

International audience; We identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10-8) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10-10, odds ratio (OR) = 0.68, minor allele frequency (MAF)cases = 0.0059, MAFcontrols = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10-10, OR = 1.43, MAFcases = 0.011, MAFcontrols = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10-14, OR = 1.67, MAFcases = 0.0143, MAFcontrols = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.

Published
2017

49. Novel genetic loci associated with hippocampal volume

Author

Benjamin S. Aribisala, Marjolein M.J. van Donkelaar, Randy L. Gollub, Rachel M. Brouwer, Norman Delanty, Tomas Axelsson, Oscar L. Lopez, Thomas Espeseth, Alejandro Arias-Vasquez, Kristel R. van Eijk, Tien Yin Wong, Jeroen van der Grond, Georg Homuth, James T. Becker, Sebastian Guelfi, Anton J. M. de Craen, Bruno Vellas, Christopher R.K. Ching, Charles C. DeCarli, Janita Bralten, Lars T. Westlye, Ryota Hashimoto, Sampath Arepalli, Bertram Müller-Myhsok, Loes M. Olde Loohuis, Sudha Seshadri, Simon E. Fisher, K Hegenscheid, Konstantinos Arfanakis, Zdenka Pausova, Robert C. Green, Simone Reppermund, Katie L. McMahon, Ashley Beecham, Daan van Rooij, Marcel P. Zwiers, Karen A. Mather, Randy L. Buckner, Edith Hofer, Marcella Rietschel, Fabrice Crivello, Ronald H. Zielke, G. Bruce Pike, Thomas W. Mühleisen, Myriam Fornage, Kazutaka Ohi, Gareth E. Davies, Chantal Depondt, Gabriel Cuellar-Partida, Iryna O. Fedko, Peter R. Schofield, Steven G. Potkin, Albert Hofman, Paul M. Thompson, Wiro J. Niessen, Deborah Janowitz, Nicholas G. Martin, Li Shen, Mina Ryten, Meike W. Vernooij, Michael E. Weale, Tonya White, Dennis van 't Ent, Sudheer Giddaluru, Nanda Rommelse, Wei Wen, Sven J. van der Lee, Eco J. C. de Geus, Aaron Goldman, Joanne E. Curran, Qiang Chen, Jean Shin, Wayne C. Drevets, Thomas H. Mosley, Matthias Nauck, Massimo Pandolfo, Anders M. Dale, Paul A. Nyquist, Girma Woldehawariat, Francis J. McMahon, Najaf Amin, Emma J. Rose, Norbert Hosten, David J. Stott, Sigurdur Sigursson, Andrew J. Saykin, M. Kamran Ikram, Pieter J. Hoekstra, Neda Jahanshad, Grant W. Montgomery, Michael Weiner, Aad van der Lugt, Esther Walton, Gunter Schumann, Clyde Francks, Narelle K. Hansell, Xinmin Liu, Herve Lemaitre, Cornelia M. van Duijn, Ralph L. Sacco, Clinton B. Wright, Arvin Saremi, Clifford R. Jack, Andre G. Uitterlinden, G. Donohoe, Tomáš Paus, Michael Griswold, Peter T. Fox, Alan B. Zonderman, Lukas Pirpamer, Christiane Wolf, Aiden Corvin, Shannon L. Risacher, Ian Ford, Philippe Amouyel, Henrik Walter, Beng-Choon Ho, William T. Longstreth, M. Arfan Ikram, Hieab H.H. Adams, Colin Smith, Sungeun Kim, Simon Lovestone, Stefan Ehrlich, Benno Pütz, Markus M. Nöthen, Susana Muñoz Maniega, Ian J. Deary, Elena Shumskaya, Susan H. Blanton, Jerome I. Rotter, Neeltje E.M. van Haren, Mar Matarin, I. Kloszewska, Ganesh Chauhan, Anita L. DeStefano, Barbara Franke, Lars Nyberg, Tatiana Foroud, Tianye Jia, Manon Bernard, Unn K. Haukvik, Rebecca F. Gottesman, Srdjan Djurovic, Ching-Yu Cheng, Lachlan T. Strike, Alex P. Zijdenbos, Jouke-Jan Hottenga, Vince D. Calhoun, Yuri Milaneschi, David C. Glahn, Phil Lee, Amelia A. Assareh, Adaikalavan Ramasamy, Emma Sprooten, Debra A. Fleischman, David R. McKay, J. Raphael Gibbs, Bruce M. Psaty, Kazima B. Bulayeva, Bryan J. Traynor, Vilmundur Gudnason, Jessika E. Sussmann, Alexander Teumer, Guillén Fernández, Katharina Wittfeld, Christophe Tzourio, Dennis van der Meer, Wolfgang Hoffmann, Sebastian Mohnke, David C. Liewald, Jordan W. Smoller, Theo G.M. van Erp, Marcel Van Der Brug, Dara M. Cannon, Lenore J. Launer, D. Ames, Juan C. Troncoso, Brenda W.J.H. Penninx, Dhananjay Vaidya, Thomas D. Dyer, Marie-José van Tol, Han G. Brunner, Andrew Singleton, Lavinia Athanasiu, Adam M. Brickman, Eric Westman, P. Mecocci, Sandra Barral, Dick J. Veltman, Catharina A. Hartman, Benedicto Crespo-Facorro, Alexa S. Beiser, Vincent Chouraki, Nhat Trung Doan, Marieke Klein, Jaap Oosterlaan, Natalie A. Royle, John B.J. Kwok, Saud Alhusaini, Ingrid Melle, Roberto Toro, Ravi Duggirala, Allissa Dillman, Reinhold Schmidt, Lisa R. Yanek, Anbupalam Thalamuthu, Helena Schmidt, Derrek P. Hibar, Albert V. Smith, Jean-Luc Martinot, Thomas H. Wassink, Jennifer S. Richards, Oliver Martinez, Joshua L. Roffman, Sylvane Desrivières, Hilkka Soininen, Rene L. Olvera, Ole A. Andreassen, Diana Tordesillas-Gutiérrez, Claudia L. Satizabal, Owen Carmichael, Lianne Schmaal, Bernd Kraemer, Martine Hoogman, Daniah Trabzuni, Oliver Grimm, Andrew M. McIntosh, René S. Kahn, Nazanin Karbalai, Margaret J. Wright, Harald H.H. Göring, Martina Papmeyer, Roberto Roiz-Santiañez, Luigi Ferrucci, David A. Bennett, Kwangsik Nho, Gianpiero L. Cavalleri, Andreas Meyer-Lindenberg, Masashi Ikeda, Avram J. Holmes, Greig I. de Zubicaray, Andreas Heinz, Tatjana Rundek, Maria del C. Valdés Hernández, Dalia Kasperaviciute, Dan L. Longo, Matthew J. Huentelman, Wiepke Cahn, Beverly G. Windham, Michael A. Nalls, Philipp G. Sämann, Stella Trompet, Vidar M. Steen, Marc M. Bohlken, Christopher D. Whelan, Hilleke E. Hulshoff Pol, Susanne Erk, Dorret I. Boomsma, Dirk J. Heslenfeld, Masaki Fukunaga, D. Hoehn, Stephen M. Lawrie, Mark E. Bastin, Marco P. Boks, M. Mallar Chakravarty, M. R. Cookson, C. McDonald, Magda Tsolaki, Badri N. Vardarajan, Jason L. Stein, Jan K. Buitelaar, Erik G. Jönsson, Oliver Gruber, Robert Johnson, Jingyun Yang, Joshua C. Bis, J. Wouter Jukema, Tulio Guadalupe, Nina Romanczuk-Seiferth, Kjetil Nordbø Jørgensen, Henry Brodaty, Diane M. Becker, Anouk den Braber, Allison C. Nugent, Thomas Wolfers, John Hardy, Joanna M. Wardlaw, Michelle Luciano, Christine Macare, Dena G. Hernandez, D. Morris, John Blangero, Andrew J. Schork, Daniel R. Weinberger, Johanna Hass, Andrew Simmons, Micael Andersson, Lucija Abramovic, David S. Knopman, Mark Jenkinson, Roel A. Ophoff, Sanjay M. Sisodiya, Boris A. Gutman, Asta Håberg, Stephanie Le Hellard, Stéphanie Debette, Nicola J. Armstrong, Sarah E. Medland, Hans J. Grabe, Henry Völzke, Thomas E. Nichols, Manuel Mattheisen, Sven Cichon, Venkata S. Mattay, Ingrid Agartz, Stefan Ropele, Lorna M. Lopez, Hans van Bokhoven, Philip L. De Jager, Miguel E. Rentería, Laura Almasy, Arthur W. Toga, Michael Czisch, Florian Holsboer, Ryota Kanai, Nic J.A. van der Wee, Peter Kochunov, Perminder S. Sachdev, Andre F. Marquand, Christian Enzinger, Anderson M. Winkler, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, Metacohorts Consortium, Institut Gilbert-Laustriat : Biomolécules, Biotechnologie, Innovation Thérapeutique, Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique (CNRS), INSERM Research Center for Epidemiology and Biostatistics (U897) Team Neuroepidemiology, Bordeaux, France College of Health Sciences, University of Bordeaux, Bordeaux, France, sans affiliation, QIMR Berghofer Medical Research Institute, University of Washington [Seattle], Department of Psychiatry, Donders Centre for Neuroscience, Radboud University Medical Center [Nijmegen]-Radboud university [Nijmegen]-Radboud University Medical Center [Nijmegen]-Radboud university [Nijmegen], Department of Human Genetics, Radboud University Medical Center [Nijmegen], Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, University Medical Center [Utrecht], Department of Neurology and Neurosurgery [Montreal], Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland (RCSI), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Sahlgrenska University Hospital [Gothenburg], Department of Biomedical Engineering, Illinois Institute of Technology (IIT), Rush University Medical Center [Chicago], University of Edinburgh, Lagos State University (LASU), Assistance Publique - Hôpitaux de Marseille (APHM), University of Oslo (UiO), Department of medical sciences, Uppsala University-Molecular Medicine-Science for Life Laboratory, John P. Hussman Institute for Human Genomics, University of Miami Leonard M. Miller School of Medicine (UMMSM), Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], Neurology Department, University of California, Davis (UCDavis-Neuro), University of California [Davis] (UC Davis), Douglas Mental Health University Institute, McGill University = Université McGill [Montréal, Canada], Université Lille Nord de France (COMUE), Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Groupe d'imagerie neurofonctionnelle (GIN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), MetaGenoPolis, Institut National de la Recherche Agronomique (INRA), Haukeland University Hospital, University of Bergen (UiB), Ames Laboratory [Ames, USA], Iowa State University (ISU)-U.S. Department of Energy [Washington] (DOE), Johns Hopkins University School of Medicine [Baltimore], Language and Genetics Department [Nijmegen], Max Planck Institute for Psycholinguistics, Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, International Max Planck Research School for Language Sciences (IMPRS ), Laboratory of Neuro Imaging [Los Angeles] (LONI), Department of Mathematics [UCLA], Georgia Institute of Technology [Atlanta], Medizinische Klinik, Universitätsklinikum Heidelberg, Heidelberg, Germany, Greifswald University Hospital, Beijing Normal University (BNU), Aalborg University [Denmark] (AAU), UCL Institute of Neurology and Epilepsy Society, Department of Medicine, Imperial College London, Service d'Endocrinologie [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen 37075, Germany, Medstar Research Institute, Clinical And Experimental Epilepsy, Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia, Department of Genomics, Life and Brain Center, University of Bonn, Institute of Human Genetics, Department of Biomedicine and the Centre for Integrative Sequencing, Aarhus University [Aarhus], VU University Medical Center [Amsterdam], Indiana University School of Medicine, Indiana University System, Indiana Alzheimer Disease Center, Indiana University System-Indiana University System, Institute of Food & Health, University College Dublin, University College Dublin [Dublin] (UCD), Department of Neurology, Statistical Genetics Group, Respiratory Epidemiology and Public Health, Imperial College London-School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU)-MRC-HPA Centre for Environment and Health, Centro de Investigación Biomédica en Red Salud Mental [Madrid] (CIBER-SAM), Karakter Child and Adolescent Psychiatry University Centre [Nijmegen], Department of Neurology [Austria], Medical University Graz, Institut Parisien de Chimie Moléculaire (IPCM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, INSERM, Neuroepidemiology U708, Bordeaux, France, Department of Neurosciences [San Diego], University of California [San Diego] (UC San Diego), Department of Cognitive Sciences [San Diego], Wuhan University [China], Plymouth University, Dpt of Psychiatry [New Haven], Yale University School of Medicine, Queensland Institute of Medical Research, School of Psychology, University of Queensland, Brisbane 4072, Australia, University of Queensland [Brisbane], Centre for Advanced Imaging, University of Queensland, Brisbane 4072, Australia, Gènes, Synapses et Cognition (CNRS - UMR3571 ), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Reta Lila Weston Institute and Department of Molecular Neuroscience, UCL, Institute of Neurology [London], Department of Genetics, King Faisal Specialist Hospital and Research Centre, Depts of Radiology, Leiden University Medical Center (LUMC), University of Twente [Netherlands], Department of Psychiatry and Human Behavior [Irvine], University of California [Irvine] (UCI), RCMG Ghent, Universiteit Gent = Ghent University [Belgium] (UGENT), Centre épigénétique et destin cellulaire (EDC (UMR_7216)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Department of Psychology [Oslo], Faculty of Social Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO), German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), National Institutes of Health [Bethesda] (NIH), Biospective [Montréal], KG Jebsen Centre for Psychosis Research, University of Oslo (UiO)-Institute of Clinical Medicine-Oslo University Hospital [Oslo], Southwest Foundation for Biomedical Research, Department of Psychiatry and National Ageing Research Institute, University of Melbourne, Université de Lille, Department of Clinical Genetics, Department of Experimental Physics, National University of Ireland Maynooth (Maynooth University), Texas Biomedical Research Institute [San Antonio, TX], The University of Texas Health Science Center at Houston (UTHealth), 849 Department of Human Genetics, Centre for Healthy Brain Ageing, University of New South Wales [Sydney] (UNSW), Dementia Collaborative Research Centre, Brain Center Rudolf Magnus, Department of Psychiatry, UMC Utrecht, Utrecht 3584 CX, The Netherlands, Department of Psychiatry [Boston], Massachusetts General Hospital [Boston], N.I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Icahn School of Medicine at Mount Sinai [New York] (MSSM), Department of Electrical and Computer Engineering [Albuquerque] (ECE Department), The University of New Mexico [Albuquerque], The Mind Research Network, Human Genetics Branch, National Institutes of Health [Bethesda] (NIH)-National Institute of Mental Health (NIMH), Division of Molecular and Cellular Therapeutics, Northwestern Polytechnical University [Xi'an] (NPU), Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Division of Medical Genetics, University of Basel (Unibas), Cell Biology and Gene Expression Section, National Institute of Health, Bethesda, Trinity College Dublin-St. James's Hospital, Neuropsychiatric Genetics Research Group, Trinity College Dublin, Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], York Structural Biology Laboratory, Department of Chemistry, University of York [York, UK], Harvard Medical School [Boston] (HMS), Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Program in Translational NeuroPsychiatric Genomics, Brigham and Women's Hospital [Boston], School of Psychology, University of Queensland, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Neurology Division, Beaumont Hospital, Dublin 9, Ireland, Beaumont Hospital, Hôpital Erasme [Bruxelles] (ULB), Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB)-Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB), Laboratory of Neurogenetics, Department of Genomics, Biological Psychology, Neuroscience Campus Amsterdam & EMGO Institute for Health and Care Research, VU University & VU Medical Center, Amsterdam 1081 BT, The Netherlands, Institut des Sciences du Mouvement Etienne Jules Marey (ISM), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), École des hautes études en sciences sociales (EHESS), Department of Radiology, Mayo Clinic, Robertson Centre for Biostatistics, University of Glasgow, Human Genetics Center, Department of Medical and Molecular Genetics, Rensselaer Polytechnic Institute (RPI), Department of Physics, Okayama University, Okayama University, University of New Haven [Connecticut], Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), Public Health Genomics Unit, Department of Mathematics, University of Colorado, University of Colorado [Boulder], Faculty of Medicine, University of Iceland [Reykjavik], Icelandic Heart Association, Kopavogur, Iceland., University of Science, VNU-HCM, University Medical Center Groningen [Groningen] (UMCG), Neuronal Plasticity / Mouse Behaviour, Interfaculty Institute for Genetics and Functional Genomics, Universität Greifswald - University of Greifswald, Department of Medical Genetics, HMNC Brain Health, University of Oxford [Oxford], University of Florida [Gainesville] (UF), Göteborgs Universitet (GU), Department of Medicine, Clinical Pharmacology Unit, Karolinska University Hospital [Stockholm], Brain Centre Rudolf Magnus [Utrecht], School of Psychology, University of Sussex, Brighton BN1 9QH, UK, University of Sussex, Institute of Cognitive Neuroscience, University College of London [London] (UCL), Medical University of Łódź (MUL), Mayo Clinic [Rochester], University of Maryland School of Medicine, University of Maryland System-University of Maryland System-University of Maryland [Baltimore County] (UMBC), University of Maryland System, School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Université de Cergy Pontoise (UCP), Université Paris-Seine, Lymphocyte Cell Biology Unit, Laboratory of Genetics, Psychiatry Institute, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Department of Health and Human Services, Department of Life Sciences, Mathematical Sciences Institute (MSI), Australian National University (ANU), Centre for Advanced Imaging, Institute of Gerontology and Geriatrics, Università degli Studi di Perugia (UNIPG), Division of Mental Health and Addiction, Oslo University Hospital [Oslo], Institute of Clinical Medicine [Oslo], Faculty of Medicine [Oslo], Medical Faculty [Mannheim], Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Genetic Epidemiology Unit, University of Mississippi Medical Center (UMMC), Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], Institute of Clinical Chemistry and Laboratory Medicine, Department of Statistics [Coventry], University of Warwick [Coventry], Delft University of Technology (TU Delft), Rheinische Friedrich-Wilhelms-Universität Bonn, Department of Health Science, Division of Health and Rehabilitation, Luleå University of Technology (LUT), Osaka University [Osaka], University Medical Center [Utrecht]-Brain Center Rudolf Magnus, University of Nottingham, UK (UON), McConnell Brain Imaging Centre (MNI), Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada, Psychiatry and Human Behavior, University of California, Irvine, California 92617, USA, Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health [Mannheim], Medical Faculty [Mannheim]-Medical Faculty [Mannheim], Cedars-Sinai Medical Center, Politecnico di Milano [Milan] (POLIMI), University of Applied Sciences [Munich], Dpt of Pharmacology and Personalised Medicine [Maastricht], Maastricht University [Maastricht], Genetics of Mental Illness and Brain Function, Neuroscience Research Australia, Department of neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland, Department of neurology, University of Eastern Finland-University Hospital of Kuopio-University of Eastern Finland-University Hospital of Kuopio, Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney 2052, Australia, National Institute of Aging, 3rd Department of Neurology, Aristotle University of Thessaloniki-General Hospital of Thessaloniki George Papanikolaou, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, Genentech, Inc. [San Francisco], Psychiatry and Leiden Institute for Brain and Cognition, Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps (LEASP), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Institute for Community Medicine, Berlin School of Mind and Brain [Berlin], Humboldt-Universität zu Berlin, Carver College of Medicine [Iowa City], University of Iowa [Iowa City]-University of Iowa [Iowa City], Centre for Population Health Sciences, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet [Stockholm], University of Pretoria [South Africa], University of Missouri [Columbia] (Mizzou), University of Missouri System, Department of Psychiatry and Psychotherapy, HELIOS Klinikum Stralsund Hanseatic-Greifswald University Hospital, Donders Center for Cognitive Neuroimaging, Donders Centre for Cognitive Neuroimaging, Radboud university [Nijmegen]-Radboud university [Nijmegen], University of Southern California (USC), University of California (UC)-University of California (UC), Sans affiliation, Radboud University [Nijmegen]-Radboud University Medical Center [Nijmegen]-Radboud University [Nijmegen]-Radboud University Medical Center [Nijmegen], University of Toronto, Radboud University [Nijmegen], Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Universität Bonn = University of Bonn, Department of Neurosciences [Univ California San Diego] (Neuro - UC San Diego), School of Medicine [Univ California San Diego] (UC San Diego), University of California (UC)-University of California (UC)-University of California [San Diego] (UC San Diego), Department of Cognitive Sciences [Univ California San Diego] (CogSci - UC San Diego), Yale School of Medicine [New Haven, Connecticut] (YSM), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), King Faisal Specialist Hospital and Research Centre (KFSH & RC), Universiteit Leiden-Universiteit Leiden, University of Twente, University of California [Irvine] (UC Irvine), Universiteit Gent = Ghent University (UGENT), Centre épigénétique et destin cellulaire (EDC), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], University of Oxford, University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System-University of Maryland School of Medicine, Università degli Studi di Perugia = University of Perugia (UNIPG), University Hospital Mannheim | Universitätsmedizin Mannheim, Universität Leipzig-Universität Leipzig, University Hospital Mannheim | Universitätsmedizin Mannheim-University Hospital Mannheim | Universitätsmedizin Mannheim, University of Eastern Finland, Universiteit Leiden, Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Humboldt University Of Berlin, Radboud University [Nijmegen]-Radboud University [Nijmegen], School of Medicine / Clinical Medicine, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Other departments, Adult Psychiatry, ARD - Amsterdam Reproduction and Development, Radboud university [Nijmegen]-Radboud University Medical Center [Nijmegen]-Radboud university [Nijmegen]-Radboud University Medical Center [Nijmegen], McGill University-McGill University, Sahlgrenska University Hospital, McGill University, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement (Inserm U1167 - RID-AGE - Institut Pasteur), University of Bergen (UIB), Iowa State University (ISU)-U.S. Department of Energy (DOE), Beijing Normal University, Karakter Child and Adolescent Psychiatry University Center Nijmegen, Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Gènes, Synapses et Cognition, Ghent University [Belgium] (UGENT), National University of Ireland Maynooth (NUIM), Texas Biomedical Research Institute [San Antonio, Texas], Bijvoet Center of Biomolecular Research, Université Libre de Bruxelles [Bruxelles] (ULB)-Hôpital Erasme (Bruxelles), Okayama University [Okayama], University of Florida [Gainesville], Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Aristotle University of Thessaloniki-G. Papanikolaou Hospital, Humboldt Universität zu Berlin, University of Missouri [Columbia], Epidemiology, Radiology & Nuclear Medicine, Medical Informatics, Internal Medicine, Neurology, Biological Psychology, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Health Behaviors & Chronic Diseases, Cognitive Psychology, IBBA, APH - Personalized Medicine, Amsterdam Neuroscience - Brain Imaging, MUMC+: DA Klinische Genetica (5), Klinische Genetica, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Anatomy and neurosciences, APH - Digital Health, Hal, GIN, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Universidad de Cantabria, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées

Subjects
Male, Netherlands Twin Register (NTR), Genome-wide association study, 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit, Spatial memory, 0302 clinical medicine, 610 Medicine & health, Child, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), Episodic memory, Aged, 80 and over, Subiculum, 220 Statistical Imaging Neuroscience, COMMON VARIANTS, ALZHEIMERS-DISEASE, ddc:500, Alzheimer's disease, genetics [Methionine Sulfoxide Reductases], Science, Locus (genetics), genetics [Protein-Serine-Threonine Kinases], Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Alzheimer Disease, ASTN2 protein, human, Humans, GENOME-WIDE ASSOCIATION, METAANALYSIS, Aged, Glycoproteins, Dentate gyrus, MEMORY, medicine.disease, R1, 030104 developmental biology, nervous system, Genetic Loci, MSRB3 protein, human, 030217 neurology & neurosurgery, 0301 basic medicine, General Physics and Astronomy, genetics [Alzheimer Disease], Hippocampal formation, Hippocampus, Genome-wide association studies, Taugasjúkdómar, Cohort Studies, DPP4 protein, human, TEMPORAL-LOBE EPILEPSY, BRAIN-REGIONS, genetics [Dipeptidyl Peptidase 4], genetics [Nerve Tissue Proteins], Genetics, Multidisciplinary, Neurodegenerative diseases, BIPOLAR DISORDER, Organ Size, Middle Aged, SUBFIELDS, Protein-Serine-Threonine Kinases, growth & development [Hippocampus], Female, genetics [Glycoproteins], Microtubule-Associated Proteins, Medical Genetics, Neuroinformatics, Adult, genetics [Microtubule-Associated Proteins], Adolescent, SUSCEPTIBILITY LOCI, Dipeptidyl Peptidase 4, genetics [Protein Serine-Threonine Kinases], Nerve Tissue Proteins, Bioinformatik och systembiologi, Protein Serine-Threonine Kinases, Biology, physiopathology [Alzheimer Disease], 150 000 MR Techniques in Brain Function, Young Adult, MAST4 protein, human, medicine, Journal Article, Erfðafræði, Genetic Predisposition to Disease, ddc:610, Medicinsk genetik, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Bioinformatics and Systems Biology, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Rannsóknir, General Chemistry, Methionine Sulfoxide Reductases, 150 Psychology, Genome-Wide Association Study
Abstract

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness., published version, peerReviewed

Published
2017

50. Genetics of vascular dementia - review from the ICVD working group

Author

Helena Schmidt, Benedetta Nacmias, Raquel Manso-Calderón, Anna Bersano, M. Arfan Ikram, Lefkos T. Middleton, Hieab H.H. Adams, Saima Siddiqi, Jianping Jia, Epidemiology, Neurology, and Radiology & Nuclear Medicine

Subjects
0301 basic medicine, Cerebral small vessel disease, Review, Disease, SMALL-VESSEL DISEASE, CEREBROVASCULAR-DISEASE, Vascular dementia, 03 medical and health sciences, Disease susceptibility, Genetics, Magnetic resonance imaging, Medicine (all), Apolipoproteins E, Medicine, General & Internal, 0302 clinical medicine, General & Internal Medicine, mental disorders, WHITE-MATTER HYPERINTENSITIES, Humans, Medicine, GENOME-WIDE ASSOCIATION, DRUG DEVELOPMENT, Stroke, Medicine(all), FABRY-DISEASE, Polymorphism, Genetic, Science & Technology, Aryldialkylphosphatase, business.industry, Dementia, Vascular, NECROSIS-FACTOR-ALPHA, 11 Medical And Health Sciences, General Medicine, COGNITIVE IMPAIRMENT, medicine.disease, 3. Good health, ALZHEIMERS-DISEASE, Clinical Practice, 030104 developmental biology, Disease Progression, Dementia, CEREBRORETINAL VASCULOPATHY, Small vessel, business, Life Sciences & Biomedicine, 030217 neurology & neurosurgery
Abstract

Background: Vascular dementia is a common disorder resulting in considerable morbidity and mortality. Determining the extent to which genes play a role in disease susceptibility and their pathophysiological mechanisms could improve our understanding of vascular dementia, leading to a potential translation of this knowledge to clinical practice. Discussion: In this review, we discuss what is currently known about the genetics of vascular dementia. The identification of causal genes remains limited to monogenic forms of the disease, with findings for sporadic vascular dementia being less robust. However, progress in genetic research on associated phenotypes, such as cerebral small vessel disease, Alzheimer’s disease, and stroke, have the potential to inform on the genetics of vascular dementia. We conclude by providing an overview of future developments in the field and how such work could impact patients and clinicians. Conclusion: The genetic background of vascular dementia is well established for monogenic disorders, but remains relatively obscure for the sporadic form. More work is needed for providing robust findings that might eventually lead to clinical translation.

Published
2017

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