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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.

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.

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

Background and Purpose: The prevalence of unruptured intracranial aneurysms (UIAs) in the adult population is ≈3%. Rupture of an intracranial aneurysm can have devastating consequences, which emphasizes the importance of identification of potentially modifiable determinants for the presence and size of UIAs. Our aim was to study the association of a broad spectrum of potential determinants with the presence and size of UIAs in a general adult population. Methods: Between 2005 and 2015, 5841 participants from the population-based Rotterdam Study (mean age, 64.4 years, 45.0% male) underwent brain magnetic resonance imaging (1.5T). These scans were evaluated for the presence of incidental UIAs. We determined number and volume of the UIAs. Using logistic and linear regression models, we assessed the association of cardiovascular, lifestyle and emerging inflammatory and hormonal determinants with the presence and volume of UIAs. Results: In 134 (2.3%) participants, ≥1 UIAs were detected (149 UIAs in total), with a median volume of 61.1 mm 3 (interquartile range, 33.2–134.0). In multivariable models, female sex (odds ratio, 1.92 [95% CI, 1.33–2.84]), hypertension (odds ratio, 1.73 [95% CI, 1.13–2.68]), and current smoking (odds ratio, 3.75 [95% CI, 2.27–6.33]) were associated with the presence of UIAs. We found no association of alcohol use, physical activity, or diet quality with UIA presence. Finally, we found white blood cell count to relate to larger aneurysm volume (difference in volume of 33.6 mm 3 per 10 9 /L increase in white blood cell [95% CI, 3.92–63.5]). Conclusions: In this population-based study, female sex, hypertension, and smoking, but no other lifestyle determinants, were associated with the presence of UIAs. White blood cell count is associated with size of UIAs. Preventive strategies should focus on treating hypertension and promoting cessation of smoking.

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

Perivascular space burden (PVS) is an emerging and possibly the earliest magnetic resonance imaging (MRI)-marker of cerebral small vessel disease (cSVD), a leading cause of stroke and dementia. Its molecular underpinnings are unknown. Genome-wide and whole-exome association studies in 40,095 participants (21 population-based cohorts, 66.3±8.6 years) revealed 24 genome-wide significant PVS risk loci. These showed association with white matter PVS already at age 20, suggesting an important role of early-life factors. PVS loci were enriched in genes causing early-onset leukodystrophies and genes expressed in fetal brain endothelial cells. Mendelian randomization analyses supported causal associations of high blood pressure with basal ganglia (BG) and hippocampal PVS, and of BG PVS with stroke. Transcriptome-wide association studies suggest causal implication of 11 genes, to prioritize for experimental follow-up as putative biotargets for cSVD. Two-thirds of PVS loci point to novel pathways, involving extracellular matrix, membrane transport, and developmental processes, with enrichment in targets of existing drugs for vascular/cognitive disorders.

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.

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.

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.

The size of the human head is determined by growth in the first years of life, while the rest of the body typically grows until early adulthood1. Such complex developmental processes are regulated by various genes and growth pathways2. Rare genetic syndromes have revealed genes that affect head size3, but the genetic drivers of variation in head size within the general population remain largely unknown. To elucidate biological pathways underlying the growth of the human head, we performed the largest genome-wide association study on human head size to date (N = 79,107). We identified 67 genetic loci, 50 of which are novel, and found that these loci are preferentially associated with head size and mostly independent from height. In subsequent neuroimaging analyses, the majority of genetic variants demonstrated widespread effects on the brain, whereas the effects of 17 variants could be localized to one or two specific brain regions. Through hypothesis-free approaches, we find a strong overlap of head size variants with both cancer pathways and cancer genes. Gene set analyses showed enrichment for different types of cancer and the p53, Wnt and ErbB signalling pathway. Genes overlapping or close to lead variants – such as TP53, PTEN and APC – were enriched for genes involved in macrocephaly syndromes (up to 37-fold) and high-fidelity cancer genes (up to 9-fold), whereas this enrichment was not seen for human height variants. This indicates that genes regulating early brain and cranial growth are associated with a propensity to neoplasia later in life, irrespective of height. Our results warrant further investigations of the link between head size and cancer, as well as its clinical implications in the general population.

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

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.

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.

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.

SummaryHuman brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genesGPR139, DACH1andAPOEare associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

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.

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.

Brain-derived neurotrophic factor (BDNF) plays an important role in brain development and function. Substantial amounts of BDNF are present in peripheral blood, and may serve as biomarkers for Alzheimer’s disease incidence as well as targets for intervention to reduce Alzheimer’s disease risk. With the exception of the genetic polymorphism in the BDNF gene, Val66Met, which has been extensively studied with regard to neurodegenerative diseases, the genetic variation that influences circulating BDNF levels is unknown. We aimed to explore the genetic determinants of circulating BDNF levels in order to clarify its mechanistic involvement in brain structure and function and Alzheimer’s disease pathophysiology in middle-aged and old adults. Thus, we conducted a meta-analysis of genome-wide association study of circulating BDNF in 11 785 middle- and old-aged individuals of European ancestry from the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES), the Framingham Heart Study (FHS), the Rotterdam Study and the Study of Health in Pomerania (SHIP-Trend). Furthermore, we performed functional annotation analysis and related the genetic polymorphism influencing circulating BDNF to common Alzheimer’s disease pathologies from brain autopsies. Mendelian randomization was conducted to examine the possible causal role of circulating BDNF levels with various phenotypes including cognitive function, stroke, diabetes, cardiovascular disease, physical activity and diet patterns. Gene interaction networks analysis was also performed. The estimated heritability of BDNF levels was 30% (standard error = 0.0246, P-value = 4 × 10−48). We identified seven novel independent loci mapped near the BDNF gene and in BRD3, CSRNP1, KDELC2, RUNX1 (two single-nucleotide polymorphisms) and BDNF-AS. The expression of BDNF was associated with neurofibrillary tangles in brain tissues from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). Seven additional genes (ACAT1, ATM, NPAT, WDR48, TTC21A, SCN114 and COX7B) were identified through expression and protein quantitative trait loci analyses. Mendelian randomization analyses indicated a potential causal role of BDNF in cardioembolism. Lastly, Ingenuity Pathway Analysis placed circulating BDNF levels in four major networks. Our study provides novel insights into genes and molecular pathways associated with circulating BDNF levels and highlights the possible involvement of plaque instability as an underlying mechanism linking BDNF with brain neurodegeneration. These findings provide a foundation for a better understanding of BDNF regulation and function in the context of brain aging and neurodegenerative pathophysiology., Thirty per cent of variation in circulating BDNF levels appears heritable. Loci adjacent to the BDNF gene and in BRD3, CSRNP1, KDELC2, RUNX1 and BDNF-AS influence levels. Using Ingenuity Pathway Analysis, these genes implicate major networks. Mendelian randomization suggests a role for BDNF in cardioembolism and BDNF expression associates with fewer neurofibrillary tangles., Graphical Abstract Graphical 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.

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.

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

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.

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).

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.

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.

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.

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.

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.

We conducted a genome-wide association meta-analysis of two ischemic white matter disease subtypes in the brain, periventricular and deep white matter hyperintensities (PVWMH and DWMH). In 26,654 participants, we found 10 independent genome-wide significant loci only associated with PVWMH, four of which have not been described previously for total WMH burden (16q24.2, 17q21.31, 10q23.1, 7q36.1). Additionally, in both PVWMH and DWMH we observed the previous association of the 17q25.1 locus with total WMH. We found that both phenotypes have shared but also distinct genetic architectures, consistent with both different underlying and related pathophysiology. PVWMH had more extensive genetic overlap with small vessel ischemic stroke, and unique associations with several loci implicated in ischemic stroke. DWMH were characterized by associations with loci previously implicated in vascular as well as astrocytic and neuronal function. Our study confirms the utility of these phenotypes and identifies new candidate genes associated only with PVWMH.

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.

Key PointsQuestionIs the gap between brain age predicted from MRI and chronological age associated with incident dementia in a general population of Dutch adults?FindingsBrain age was predicted using a deep learning model, using MRI-derived grey matter density maps. In a population based study including 5496 participants, the observed gap was significantly associated with the risk of dementia.MeaningThe gap between MRI-brain predicted and chronological age is potentially a biomarker for dementia risk screening.AbstractImportanceThe gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as biomarker for early-stage neurodegeneration and potentially as a risk indicator for dementia. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link.ObjectiveWe aimed to investigate the utility of such a gap as a risk biomarker for incident dementia in a general Dutch population, using a deep learning approach for predicting brain age based on MRI-derived grey matter maps.DesignData was collected from participants of the cohort-based Rotterdam Study who underwent brain magnetic resonance imaging between 2006 and 2015. This study was performed in a longitudinal setting and all participant were followed up for incident dementia until 2016.SettingThe Rotterdam Study is a prospective population-based study, initiated in 1990 in the suburb Ommoord of in Rotterdam, the Netherlands.ParticipantsAt baseline, 5496 dementia- and stroke-free participants (mean age 64.67±9.82, 54.73% women) were scanned and screened for incident dementia. During 6.66±2.46 years of follow-up, 159 people developed dementia.Main outcomes and measuresWe built a convolutional neural network (CNN) model to predict brain age based on its MRI. Model prediction performance was measured in mean absolute error (MAE). Reproducibility of prediction was tested using the intraclass correlation coefficient (ICC) computed on a subset of 80 subjects. Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for years of education, ApoEε4 allele carriership, grey matter volume and intracranial volume. Additionally, we computed the attention maps of CNN, which shows which brain regions are important for age prediction.ResultsMAE of brain age prediction was 4.45±3.59 years and ICC was 0.97 (95% confidence interval CI=0.96-0.98). Logistic regression and Cox proportional hazards 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 grey matter density around the amygdalae and hippocampi primarily drive the age estimation.Conclusion and relevanceWe show that the gap between predicted and chronological brain age is a biomarker associated with risk of dementia development. This suggests that it can be used as a biomarker, complimentary to those that are known, for dementia risk screening.

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.

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.

Localization of focal vascular lesions on brain MRI is an important component of research on the etiology of neurological disorders. However, manual annotation of lesions can be challenging, time-consuming and subject to observer bias. Automated detection methods often need voxel-wise annotations for training. We propose a novel approach for automated lesion detection that can be trained on scans only annotated with a dot per lesion instead of a full segmentation. From the dot annotations and their corresponding intensity images we compute various distance maps (DMs), indicating the distance to a lesion based on spatial distance, intensity distance, or both. We train a fully convolutional neural network (FCN) to predict these DMs for unseen intensity images. The local optima in the predicted DMs are expected to correspond to lesion locations. We show the potential of this approach to detect enlarged perivascular spaces in white matter on a large brain MRI dataset with an independent test set of 1000 scans. Our method matches the intra-rater performance of the expert rater that was computed on an independent set. We compare the different types of distance maps, showing that incorporating intensity information in the distance maps used to train an FCN greatly improves performance.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.