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The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The Alzheimer's Association International Conference held its sixth Satellite Symposium in Sydney, Australia in 2019, highlighting the leadership of Australian researchers in advancing the understanding of and treatment developments for Alzheimer's disease (AD) and other dementias. This leadership includes the Australian Imaging, Biomarker, and Lifestyle Flagship Study of Ageing (AIBL), which has fueled the identification and development of many biomarkers and novel therapeutics. Two multimodal lifestyle intervention studies have been launched in Australia; and Australian researchers have played leadership roles in other global studies in diverse populations. Australian researchers have also played an instrumental role in efforts to understand mechanisms underlying vascular contributions to cognitive impairment and dementia; and through the Women's Healthy Aging Project have elucidated hormonal and other factors that contribute to the increased risk of AD in women. Alleviating the behavioral and psychological symptoms of dementia has also been a strong research and clinical focus in Australia., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients ( N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD., Competing Interests: Eduard Vieta has received grants and served as consultant, advisor, or CME speaker for the following entities: AB-Biotics, Allergan, Angelini, AstraZeneca, Bristol-Myers Squibb, Dainippon Sumitomo Pharma, Farmindustria, Ferrer, Forest Research Institute, Gedeon Richter, GlaxoSmithKline, Janssen, Lundbeck, Otsuka, Pfizer, Roche, Sanofi-Aventis, Servier, Shire, Sunovion, Takeda, the Brain and Behaviour Foundation, the Spanish Ministry of Science and Innovation (CIBERSAM), and the Stanley Medical Research Institute. Michael Bauer has received grants from the Deutsche Forschungsgemeinschaft and Bundesministeriums für Bildung und Forschung and served as consultant, advisor, or CME speaker for the following entities: Allergan, Aristo, Janssen, Lilly, Lundbeck, neuraxpharm, Otsuka, Sandoz, Servier, and Sunovion outside the submitted work. Sarah Kittel-Schneider has received grants and served as consultant, advisor, or speaker for the following entities: Medice Arzneimittel Pütter GmbH and Shire. Bernhard Baune has received grants and served as consultant, advisor, or CME speaker for the following entities: AstraZeneca, Bristol-Myers Squibb, Janssen, Lundbeck, Otsuka, Servier, the National Health and Medical Research Council, the Fay Fuller Foundation, and the James and Diana Ramsay Foundation. Tadafumi Kato received honoraria for lectures, manuscripts, and/or consultancy, from Kyowa Hakko Kirin Co., Ltd., Eli Lilly Japan K.K., Otsuka Pharmaceutical Co., Ltd., GlaxoSmithKline K.K., Taisho Toyama Pharmaceutical Co., Ltd., Dainippon Sumitomo Pharma Co., Ltd., Meiji Seika Pharma Co., Ltd., Pfizer Japan Inc., Mochida Pharmaceutical Co., Ltd., Shionogi & Co., Ltd., Janssen Pharmaceutical K.K., Janssen Asia Pacific, Yoshitomiyakuhin, Astellas Pharma Inc., Wako Pure Chemical Industries, Ltd., Wiley Publishing Japan, Nippon Boehringer Ingelheim Co. Ltd., Kanae Foundation for the Promotion of Medical Science, MSD K.K., Kyowa Pharmaceutical Industry Co., Ltd., and Takeda Pharmaceutical Co., Ltd. T.K. also received a research grant from Takeda Pharmaceutical Co., Ltd. Peter Falkai has received grants and served as consultant, advisor, or CME speaker for the following entities Abbott, GlaxoSmithKline, Janssen, Essex, Lundbeck, Otsuka, Gedeon Richter, Servier, and Takeda as well as the German Ministry of Science and the German Ministry of Health. Eva Reininghaus has received grants and served as consultant, advisor, or CME speaker for the following entities: Janssen and Institut Allergosan. Mikael Landén declares that, over the past 36 months, he has received lecture honoraria from Lundbeck and served as scientific consultant for EPID Research Oy; no other equity ownership, profit-sharing agreements, royalties, or patent. Kazufumi Akiyama has received consulting honoraria from Taisho Toyama Pharmaceutical Co., Ltd. The other authors have no other conflict of interest to disclose., (Copyright © 2021 by S. Karger AG, Basel.)

Bipolar disorder (BD) is associated with a 20-30-fold increased suicide risk compared to the general population. First-degree relatives of BD patients show inflated rates of psychopathology including suicidal behaviors. As reliable biomarkers of suicide attempts (SA) are lacking, we examined associations between suicide-related polygenic risk scores (PRSs)-a quantitative index of genomic risk-and variability in brain structures implicated in SA. Participants (n = 206; aged 12-30 years) were unrelated individuals of European ancestry and comprised three groups: 41 BD cases, 96 BD relatives ("high risk"), and 69 controls. Genotyping employed PsychArray, followed by imputation. Three PRSs were computed using genome-wide association data for SA in BD (SA-in-BD), SA in major depressive disorder (SA-in-MDD) (Mullins et al., 2019, The American Journal of Psychiatry, 176(8), 651-660), and risky behavior (Karlsson Linnér et al., 2019, Nature Genetics, 51(2), 245-257). Structural magnetic resonance imaging processing employed FreeSurfer v5.3.0. General linear models were constructed using 32 regions-of-interest identified from suicide neuroimaging literature, with false-discovery-rate correction. SA-in-MDD and SA-in-BD PRSs negatively predicted parahippocampal thickness, with the latter association modified by group membership. SA-in-BD and Risky Behavior PRSs inversely predicted rostral and caudal anterior cingulate structure, respectively, with the latter effect driven by the "high risk" group. SA-in-MDD and SA-in-BD PRSs positively predicted cuneus structure, irrespective of group. This study demonstrated associations between PRSs for suicide-related phenotypes and structural variability in brain regions implicated in SA. Future exploration of extended PRSs, in conjunction with a range of biological, phenotypic, environmental, and experiential data in high risk populations, may inform predictive models for suicidal behaviors., (© 2021 Wiley Periodicals LLC.)

Background: Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools., Aims: To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics., Method: Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts., Results: Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = -0.34 years, s.e. = 0.08), major depression (β = -0.34 years, s.e. = 0.08), schizophrenia (β = -0.39 years, s.e. = 0.08), and educational attainment (β = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO., Conclusions: AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi + Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD., (© 2021. The Author(s).)

Whilst alterations in emotional face processing, as indicated by event-related potentials (ERPs), are associated with depression and anxiety symptoms in clinical and non-clinical samples, it has remained unclear whether they are related to mental wellbeing. The current study aimed to address this question in a non-clinical sample. The analysis included 402 adult twins from the TWIN-E study. The COMPAS-W and the Depression Anxiety Stress Scale (DASS-42) were used to measure mental wellbeing and depression/anxiety symptoms, respectively. Participants viewed facial expressions under Unmasked (conscious) and Masked (subliminal) conditions while ERPs were recorded. The associations of emotion processing with mental wellbeing and depression/anxiety symptoms were assessed using multivariate linear mixed models. There was a strong association between depression/anxiety symptoms and the N170 amplitude difference for the Fear - Happy contrast in the Masked condition after controlling for wellbeing scores (B = 0.34, p < .001). Specifically, higher depression/anxiety symptoms were associated with a lack of differentiation between fearful and happy faces. No associations were found between emotional face processing and mental wellbeing scores. These results indicate that even within a non-clinical sample, alterations in emotional ERPs, namely the N170, reflect differences in depression/anxiety symptoms rather than differences in wellbeing. Furthermore, this effect was limited to automatic processing, rather than conscious processing of emotional stimuli, suggesting the observed differences apply only to the subconscious pathway., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression., (© 2021. The Author(s).)

Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10 -3 ; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response., (© 2021. The Author(s).)

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates., (© 2020. The Author(s).)

Background: Due to trisomy of chromosome 21 and the resultant extra copy of the amyloid precursor protein gene, nearly all adults with Down syndrome develop Alzheimer's disease pathology by the age of 40 years and are at high risk for dementia given their increased life expectancy compared with adults with Down syndrome in the past. We aimed to compare CSF biomarker patterns in Down syndrome with those of carriers of autosomal dominant Alzheimer's disease mutations to enhance our understanding of disease mechanisms in these two genetic groups at high risk for Alzheimer's disease., Methods: We did a cross-sectional study using data from adults enrolled in the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study, a multisite longitudinal study of Alzheimer's disease in Down syndrome, as well as a cohort of carriers of autosomal dominant Alzheimer's disease mutations and non-carrier sibling controls enrolled in the Dominantly Inherited Alzheimer Network (DIAN) study. For ABC-DS, participants with baseline CSF, available clinical diagnosis, and apolipoprotein E genotype as of Jan 31, 2019, were included in the analysis. DIAN participants with baseline CSF, available clinical diagnosis, and apolipoprotein E genotype as of June 30, 2018, were evaluated as comparator groups. CSF samples obtained from adults with Down syndrome, similarly aged carriers of autosomal dominant Alzheimer's disease mutations, and non-carrier siblings (aged 30-61 years) were analysed for markers of amyloid β (Aβ 1-40 , Aβ 1-42 ); tau phosphorylated at threonine 181-related processes; neuronal, axonal, or synaptic injury (total tau, visinin-like protein 1, neurofilament light chain [NfL], synaptosomal-associated protein 25); and astrogliosis and neuroinflammation (chitinase-3-like protein 1 [YKL-40]) via immunoassay. Biomarker concentrations were compared as a function of dementia status (asymptomatic or symptomatic), and linear regression was used to evaluate and compare the relationship between biomarker concentrations and age among groups., Findings: We assessed CSF samples from 341 individuals (178 [52%] women, 163 [48%] men, aged 30-61 years). Participants were adults with Down syndrome (n=41), similarly aged carriers of autosomal dominant Alzheimer's disease mutations (n=192), and non-carrier siblings (n=108). Individuals with Down syndrome had patterns of Alzheimer's disease-related CSF biomarkers remarkably similar to carriers of autosomal dominant Alzheimer's disease mutations, including reductions (all p<0·0080) in Aβ 1-42 to Aβ 1-40 ratio and increases in markers of phosphorylated tau-related processes; neuronal, axonal, and synaptic injury (p<0·080); and astrogliosis and neuroinflammation, with greater degrees of abnormality in individuals with dementia. Differences included overall higher concentrations of Aβ and YKL-40 (both p<0·0008) in Down syndrome and potential elevations in CSF tau (p<0·010) and NfL (p<0·0001) in the asymptomatic stage (ie, no dementia symptoms)., Funding: National Institute on Aging, Eunice Kennedy Shriver National Institute of Child Health and Human Development, German Center for Neurodegenerative Diseases, and Japan Agency for Medical Research and Development., Competing Interests: Declaration of interests AMF has received research funding from the National Institutes of Health/National Institute on Aging, Biogen, Centene, Fujirebio, and Roche Diagnostics. She is a member of the scientific advisory boards for Roche Diagnostics, Genentech, and AbbVie and also consults for Araclon/Grifols, DiademRes, DiamiR, and Otsuka Pharmaceuticals, outside the submitted work. RJB has equity ownership interest in C2N Diagnostics and receives royalty income based on technology (stable isotope labelling kinetics and blood plasma assay) licensed by Washington University to C2N Diagnostics. He receives income from C2N Diagnostics for serving on the scientific advisory board. Washington University, with RJB as co-inventor, has submitted the US non-provisional patent application “Cerebrospinal fluid (CSF) tau rate of phosphorylation measurement to define stages of Alzheimer's disease and monitor brain kinases/phosphatases activity.” He has received honoraria from Janssen and Pfizer as a speaker, and from Merck and Pfizer as an advisory board member. He has been an invited speaker, advisory board member, and consultant for F Hoffman La Roche, an invited speaker and consultant for AC Immune and Janssen, and a consultant for Amgen and Eisai, outside the submitted work. AMG has consulted for Eisai, Biogen, Pfizer, AbbVie, Cognition Therapeutics, and GSK. She also served on the Scientific Advisory Board of Denali Therapeutics (2015–2018), outside the submitted work. BJH has received research funding from Roche Pharmaceuticals and Autism Speaks, outside the submitted work. JPC has served on a medical advisory board for Otsuka Pharmaceuticals, outside the submitted work. GSD is supported by National Institutes of Health/National Institute on Aging (K23AG064029). He serves as a topic editor on dementia for DynaMed Plus (EBSCO Industries), a consultant for Parabon NanoLabs, is the clinical director for the Anti-NMDA Receptor Encephalitis Foundation (uncompensated), has provided record review and expert medical testimony on legal cases pertaining to management of Wernicke encephalopathy, and holds stocks (>$10 000) in ANI Pharmaceuticals (a generic pharmaceutical company), outside the submitted work. NRGR takes part in multicentre trials supported by AbbVie, Eli Lilly, and Biogen, outside the submitted work. JL reports speaker fees from Bayer Vital and Roche, consulting fees from Axon Neuroscience and Ionis Pharmaceuticals, author fees from Thieme medical publishers and W Kohlhammer GmbH medical publishers, non-financial support from Abbvie, and compensation for duty as part-time CMO from MODAG, outside the submitted work. CJM has been a member of advisory scientific board for Biogen, IONIS, Wave, and Roche and consulted for Eisai, outside the submitted work. RNM has received funding from the US Alzheimer's Foundation to undertake an intervention trial for the prevention of Alzheimer's disease. He is a member of the scientific advisory board for Eisai, outside the submitted work. SS reports consulting to Eisai, Novartis, Genentech, F Hoffmann-La Roche, Gemvax, Avid Radiopharmaceuticals, and Eli Lilly and Company, outside the submitted work. All other authors declare no competing interests., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions., (© 2019. The Author(s).)

Introduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment., Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally., Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset., Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials., Competing Interests: Dr. Clifford Jack serves on an independent data monitoring board for Roche and has consulted for Eisai, but he receives no personal compensation from any commercial entity. He receives research support from NIH and the Alexander Family Alzheimer's Disease Research Professorship of the Mayo Clinic. Dr. Saykin receives support from Arkley BioTek (joint NIH SBIR grant); Avid Radiopharmaceuticals (in kind contribution of PET tracer precursor); Bayer Oncology (Scientific Advisory Board); Eli Lilly (collaborative research grant); and Springer‐Nature Publishing (Editorial Office Support as Editor in Chief, Brain Imaging and Behavior). Ophir Keret is an Atlantic Fellow for Equity in Brain Health and thanks the Global Brain Health Institute for supporting his work. Johannes Levin reports speaker fees from Bayer Vital and Roche; consulting fees from Axon Neuroscience; author fees from Thieme medical publishers and W. Kohlhammer GmbH medical publishers; non‐financial support from Abbvie; and compensation for duty as part‐time CMO from MODAG, outside the submitted work. John C. Morris reports support from NIH grants P30 AG066444, P01 AG003991, and P01 AG026276 during the conduct of the study. He serves on the Editorial Boards of Brain & Life and Alzheimer's & Dementia. Su Yi was a paid consultant for Green Valley Pharmaceuticals LLC in 2018. Adam M. Staffaroni provides consultation to Takeda and receives research funding from the NIH, the Larry L. Hillblom Foundation, and the Bluefield Project to Cure FTD. Stephan Salloway reports grants, personal fees, and non‐financial support from Biogen; grants and personal fees from Eisai; grants, personal fees, and non‐financial support from Avid; personal fees and non‐financial support from Novartis; grants, personal fees, and non‐financial support from Lilly; personal fees from Genentech; personal fees and non‐financial support from Roche, outside the submitted work. Michael Weiner receives support for his work from the following funding sources: NIH, DOD, PCORI, California Dept. of Public Health, U. Michigan, Siemens, Biogen, Hillblom Foundation, Alzheimer's Association, The State of California, Johnson & Johnson, Kevin and Connie Shanahan, GE, VUmc, Australian Catholic University (HBI‐BHR), The Stroke Foundation, Fidelity Charitable, and the Veterans Administration. Dr. Weiner has served on advisory boards for Cerecin/Accera, Alzheon, Inc., Nestle/Nestec, PCORI/PPRN, Dolby Family Ventures, National Institute on Aging (NIA), Boston University Alzheimer's Disease and CTE Center, MIRIADE at VUmc for Amsterdam UMC, Cytox, Indiana University, Acumen, Brain Health Registry and ADNI. He serves on the Editorial Boards for Alzheimer's & Dementia, TMRI and MRI. He has provided consulting and/or acted as a speaker/lecturer to Cerecin/Accera, Inc., Alzheimer's Drug Discovery Foundation (ADDF), BioClinica, The Buck Institute for Research on Aging, FUJIFILM‐Toyama Chemical (Japan), Garfield Weston, Baird Equity Capital, University of Southern California (USC), T3D Therapeutics, Cytox, Guidepoint, and Japanese Organization for Medical Device Development, Inc. (JOMDD). He holds stock options with Alzheon, Inc., Alzeca, and Anven. Bruce L. Miller reported serving on the advisory committee for Cambridge National Institute for Health Research Biomedical Research Centre; serving on the board of directors for J Douglas French Alzheimer's Foundation and Safely You; serving as medical advisor and receiving grant support from The Bluefield Project for Frontotemporal Dementia Research; consulting for Rainwater Charitable Foundation, Stanford Alzheimer's Disease Research Center, Buck Institute, Larry L. Hillblom Foundation, University of Texas Center for Brain Health, University of Washington Alzheimer's Disease Research Center, and Harvard University Alzheimer's Disease Research Center; receiving royalties from Guilford Press, Cambridge University Press, Johns Hopkins Press, and Oxford University Press; serving as editor for Neurocase; serving as section editor for Frontiers in Neurology; and receiving grants P30 AG062422, P01 AG019724, R01 AG057234, and T32 AG023481 from the NIH. Gil D. Rabinovici receives research support from Avid Radiopharmaceuticals, Eli Lilly, GE Healthcare, Genentech, Life Molecular Imaging. He has received consulting fees from Axon Neurosciences, Eisai, Genentech, GE Healthcare, Miller Medical Communications, Roche. He is an Associate Editor for JAMA Neurology. Howard J. Rosen reported consulting for Wave Neuroscience outside the submitted work. All other authors have no potential conflicts to disclose., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Introduction: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease., Methods: Longitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status., Results: The Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R 2  = 0.95), fluorodeoxyglucose (R 2  = 0.93), and atrophy (R 2  = 0.95) in mutation carriers compared to non-carriers., Discussion: Results suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions., (© 2021 the Alzheimer's Association.)

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi + Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD., (© 2020. The Author(s), under exclusive licence to Springer Nature Limited.)

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Ageing is associated with a decrease in odour identification. Additionally, deficits in olfaction have been linked to age-related disease and mortality. Heritability studies suggest genetic variation contributes to olfactory identification. The olfactory receptor (OR) gene family is the largest in the human genome and responsible for overall odour identification. In this study, we sought to find olfactory gene family variants associated with individual and overall odour identification and to examine the relationships between polygenic risk scores (PRS) for olfactory-related phenotypes and olfaction. Participants were Caucasian older adults from the Sydney Memory and Ageing Study and the Older Australian Twins Study with genome-wide genotyping data ( n = 1395, mean age = 75.52 ± 6.45). The Brief-Smell Identification Test (BSIT) was administered in both cohorts. PRS were calculated from independent GWAS summary statistics for Alzheimer's disease (AD), white matter hyperintensities (WMH), Parkinson's disease (PD), hippocampal volume and smoking. Associations with olfactory receptor genes ( n = 967), previously identified candidate olfaction-related SNPs ( n = 36) and different PRS with BSIT scores (total and individual smells) were examined. All of the relationships were analysed using generalised linear mixed models (GLMM), adjusted for age and sex. Genes with suggestive evidence for odour identification were found for 8 of the 12 BSIT items. Thirteen out of 36 candidate SNPs previously identified from the literature were suggestively associated with several individual BSIT items but not total score. PRS for smoking, WMH and PD were negatively associated with chocolate identification. This is the first study to conduct genetic analyses with individual odorant identification, which found suggestive olfactory-related genes and genetic variants for multiple individual BSIT odours. Replication in independent and larger cohorts is needed.

Aim: Identify a global resting-state functional connectivity (gFC) signature in mutation carriers (MC) from the Dominantly Inherited Alzheimer Network (DIAN). Assess the gFC with regard to amyloid (A), tau (T), and neurodegeneration (N) biomarkers, and estimated years to symptom onset (EYO). Introduction: Cross-sectional measures were assessed in MC ( n  = 171) and mutation noncarrier (NC) ( n  = 70) participants. A functional connectivity (FC) matrix that encompassed multiple resting-state networks was computed for each participant. Methods: A global FC was compiled as a single index indicating FC strength. The gFC signature was modeled as a nonlinear function of EYO. The gFC was linearly associated with other biomarkers used for assessing the AT(N) framework, including cerebrospinal fluid (CSF), positron emission tomography (PET) molecular biomarkers, and structural magnetic resonance imaging. Results: The gFC was reduced in MC compared with NC participants. When MC participants were differentiated by clinical dementia rating (CDR), the gFC was significantly decreased in MC CDR >0 (demented) compared with either MC CDR 0 (cognitively normal) or NC participants. The gFC varied nonlinearly with EYO and initially decreased at EYO = -24 years, followed by a stable period followed by a further decline near EYO = 0 years. Irrespective of EYO, a lower gFC associated with values of amyloid PET, CSF Aβ 1-42 , CSF p-tau, CSF t-tau, 18F-fluorodeoxyglucose, and hippocampal volume. Conclusions: The gFC correlated with biomarkers used for defining the AT(N) framework. A biphasic change in the gFC suggested early changes associated with CSF amyloid and later changes associated with hippocampal volume.

Introduction: A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti-amyloid clinical trials., Methods: In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity-a novel marker of cortical microstructure-changes in 389 participants from the Dominantly Inherited Alzheimer Network., Results: In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations., Discussion: These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials., (© 2020 the Alzheimer's Association.)

Bipolar disorder is associated with cognitive deficits and cortical changes for which the developmental dynamics are not well understood. The dopamine D2 receptor (DRD2) gene has been associated with both psychiatric disorders and cognitive variability. Here we examined the mediating role of brain structure in the relationship between DRD2 genomic variation and cognitive performance, with target cortical regions selected based on evidence of association with DRD2, bipolar disorder and/or cognition from prior literature. Participants (n = 143) were aged 12-30 years and comprised 62 first-degree relatives of bipolar patients (deemed 'at-risk'), 55 controls, and 26 patients with established bipolar disorder; all were unrelated Caucasian individuals with complete data across the three required modalities (structural magnetic resonance imaging, neuropsychological and genetic data). A DRD2 haplotype was derived from three functional polymorphisms (rs1800497, rs1076560, rs2283265) associated with alternative splicing (i.e., D2-short/-long isoforms). Moderated mediation analyses explored group differences in relationships between this DRD2 haplotype, three structural brain networks which subsume the identified cortical regions of interest (frontoparietal, dorsal-attention, and ventral-attention), and three cognitive indices (intelligence, attention, and immediate memory). Controls who were homozygous for the DRD2 major haplotype demonstrated greater cognitive performance as a result of dorsal-attention network mediation. However, this association was absent in the 'at-risk' group. This study provides the first evidence of a functional DRD2-brain-cognition pathway. The absence of typical brain-cognition relationships in young 'at-risk' individuals may reflect biological differences that precede illness onset. Further insight into early pathogenic processes may facilitate targeted early interventions., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective: To investigate the inherent clinical risks associated with the presence of cerebral microhemorrhages (CMHs) or cerebral microbleeds and characterize individuals at high risk for developing hemorrhagic amyloid-related imaging abnormality (ARIA-H), we longitudinally evaluated families with dominantly inherited Alzheimer disease (DIAD)., Methods: Mutation carriers (n = 310) and noncarriers (n = 201) underwent neuroimaging, including gradient echo MRI sequences to detect CMHs, and neuropsychological and clinical assessments. Cross-sectional and longitudinal analyses evaluated relationships between CMHs and neuroimaging and clinical markers of disease., Results: Three percent of noncarriers and 8% of carriers developed CMHs primarily located in lobar areas. Carriers with CMHs were older, had higher diastolic blood pressure and Hachinski ischemic scores, and more clinical, cognitive, and motor impairments than those without CMHs. APOE ε4 status was not associated with the prevalence or incidence of CMHs. Prevalent or incident CMHs predicted faster change in Clinical Dementia Rating although not composite cognitive measure, cortical thickness, hippocampal volume, or white matter lesions. Critically, the presence of 2 or more CMHs was associated with a significant risk for development of additional CMHs over time (8.95 ± 10.04 per year)., Conclusion: Our study highlights factors associated with the development of CMHs in individuals with DIAD. CMHs are a part of the underlying disease process in DIAD and are significantly associated with dementia. This highlights that in participants in treatment trials exposed to drugs, which carry the risk of ARIA-H as a complication, it may be challenging to separate natural incidence of CMHs from drug-related CMHs., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Background: Bipolar disorder is a highly heritable psychiatric condition for which specific genetic factors remain largely unknown. In the present study, we used combined whole-exome sequencing and linkage analysis to identify risk loci and dissect the contribution of common and rare variants in families with a high density of illness., Methods: Overall, 117 participants from 15 Australian extended families with bipolar disorder (72 with affective disorder, including 50 with bipolar disorder type I or II, 13 with schizoaffective disorder-manic type and 9 with recurrent unipolar disorder) underwent whole-exome sequencing. We performed genome-wide linkage analysis using MERLIN and conditional linkage analysis using LAMP. We assessed the contribution of potentially functional rare variants using a genebased segregation test., Results: We identified a significant linkage peak on chromosome 10q11-q21 (maximal single nucleotide polymorphism = rs10761725; exponential logarithm of the odds [LODexp] = 3.03; empirical p = 0.046). The linkage interval spanned 36 protein-coding genes, including a gene associated with bipolar disorder, ankyrin 3 (ANK3). Conditional linkage analysis showed that common ANK3 risk variants previously identified in genome-wide association studies - or variants in linkage disequilibrium with those variants - did not explain the linkage signal (rs10994397 LOD = 0.63; rs9804190 LOD = 0.04). A family-based segregation test with 34 rare variants from 14 genes under the linkage interval suggested rare variant contributions of 3 brain-expressed genes: NRBF2 (p = 0.005), PCDH15 (p = 0.002) and ANK3 (p = 0.014)., Limitations: We did not examine non-coding variants, but they may explain the remaining linkage signal., Conclusion: Combining family-based linkage analysis with next-generation sequencing data is effective for identifying putative disease genes and specific risk variants in complex disorders. We identified rare missense variants in ANK3, PCDH15 and NRBF2 that could confer disease risk, providing valuable targets for functional characterization., Competing Interests: P. Mitchell reports personal fees from Sanofi (Hangzhou) and Janssen-Cilag, outside the submitted work., (© 2021 Joule Inc. or its licensors.)

Plasma amyloid-beta (Aβ) has long been investigated as a blood biomarker candidate for Cerebral Amyloid Angiopathy (CAA), however previous findings have been inconsistent which could be attributed to the use of less sensitive assays. This study investigates plasma Aβ alterations between pre-symptomatic Dutch-type hereditary CAA (D-CAA) mutation-carriers (MC) and non-carriers (NC) using two Aβ measurement platforms. Seventeen pre-symptomatic members of a D-CAA pedigree were assembled and followed up 3-4 years later (NC = 8; MC = 9). Plasma Aβ1-40 and Aβ1-42 were cross-sectionally and longitudinally analysed at baseline (T1) and follow-up (T2) and were found to be lower in MCs compared to NCs, cross-sectionally after adjusting for covariates, at both T1(Aβ1-40: p = 0.001; Aβ1-42: p = 0.0004) and T2 (Aβ1-40: p = 0.001; Aβ1-42: p = 0.016) employing the Single Molecule Array (Simoa) platform, however no significant differences were observed using the xMAP platform. Further, pairwise longitudinal analyses of plasma Aβ1-40 revealed decreased levels in MCs using data from the Simoa platform ( p = 0.041) and pairwise longitudinal analyses of plasma Aβ1-42 revealed decreased levels in MCs using data from the xMAP platform ( p = 0.041). Findings from the Simoa platform suggest that plasma Aβ may add value to a panel of biomarkers for the diagnosis of pre-symptomatic CAA, however, further validation studies in larger sample sets are required.

In Alzheimer's disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNF Val66Met ) is associated with worse impact of primary AD pathology (beta-amyloid, Aβ) on neurodegeneration and cognitive decline, rendering BDNF Val66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNF Val66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNF Val66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNF Val66Met carriers compared to BDNF Val homozogytes. BDNF Val66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNF Val66Met could be also found in elderly subjects with sporadically occurring Aβ, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNF Val66Met was associated with a stronger effect of more abnormal Aβ-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNF Val66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.

This study assessed the effectiveness of cognitive and emotional brain training and transfer effects to wellbeing and depression and anxiety symptoms. 352 healthy adult twins were randomised to a training group where they were asked to play brain training games over a 30-day period, or a waitlist control group. This study focused on the impact of the brain training on explicit and implicit emotional cognition, and analysed effects using both Intention-To-Treat (ITT) and Per-Protocol (PP) approaches. Both analyses revealed significant training effects for improvement in the explicit identification of fear expressions (ITT: p < 0.001, d = 0.33; PP training 3 h+: p < 0.001, d = 0.55), and a reduction in implicit bias for anger expressions amongst males (ITT: p < 0.001, d = 0.94; PP training 3 h+: p = 0.04, d = 0.90). Female participants also showed improvements in implicit bias for happy expressions (ITT: p = 0.003, d = 0.34; PP training 3 h+: p = 0.03, d = 0.47). Improvements resulting from training in emotional cognition did not directly improve wellbeing, depression or anxiety symptoms. Regression modelling also suggested training improvements in emotional cognition yielded no indirect transfer effects for the mental health and wellbeing measures. The results suggest brain training in healthy populations has potential for improving emotional cognition, but the subsequent impact on improving wellbeing and mental health symptoms is still equivocal., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen's kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.

Background: Cerebral amyloid angiopathy (CAA) is one of the major causes of intracerebral hemorrhage and vascular dementia in older adults. Early diagnosis will provide clinicians with an opportunity to intervene early with suitable strategies, highlighting the importance of pre-symptomatic CAA biomarkers., Objective: Investigation of pre-symptomatic CAA related blood metabolite alterations in Dutch-type hereditary CAA mutation carriers (D-CAA MCs)., Methods: Plasma metabolites were measured using mass-spectrometry (AbsoluteIDQ® p400 HR kit) and were compared between pre-symptomatic D-CAA MCs (n = 9) and non-carriers (D-CAA NCs, n = 8) from the same pedigree. Metabolites that survived correction for multiple comparisons were further compared between D-CAA MCs and additional control groups (cognitively unimpaired adults)., Results: 275 metabolites were measured in the plasma, 22 of which were observed to be significantly lower in theD-CAAMCs compared to D-CAA NCs, following adjustment for potential confounding factors age, sex, and APOE ε4 (p < 00.05). After adjusting for multiple comparisons, only spermidine remained significantly lower in theD-CAAMCscompared to theD-CAA NCs (p  < 0.00018). Plasma spermidine was also significantly lower in D-CAA MCs compared to the cognitively unimpaired young adult and older adult groups (p < 0.01). Spermidinewas also observed to correlate with CSF Aβ40 (rs = 0.621, p = 0.024), CSF Aβ42 (rs = 0.714, p = 0.006), and brain Aβ load (rs = -0.527, p = 0.030)., Conclusion: The current study provides pilot data on D-CAA linked metabolite signals, that also associated with Aβ neuropathology and are involved in several biological pathways that have previously been linked to neurodegeneration and dementia.

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., Design, Setting, and Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., Main Outcomes and Measures: Interregional profiles of group difference in cortical thickness between cases and controls., Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., Conclusions and Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.

Objective: To determine the ordering of changes in Alzheimer disease (AD) biomarkers among cognitively normal individuals., Methods: Cross-sectional data, including CSF analytes, molecular imaging of cerebral fibrillar β-amyloid (Aβ) with PET using the [ 11 C] benzothiazole tracer Pittsburgh compound B (PiB), MRI-based brain structures, and clinical/cognitive outcomes harmonized from 8 studies, collectively involving 3,284 cognitively normal individuals 18 to 101 years of age, were analyzed. The age at which each marker exhibited an accelerated change (called the change point) was estimated and compared across the markers., Results: Accelerated changes in CSF Aβ 1-42 (Aβ 42 ) occurred at 48.28 years of age and in Aβ 42 /Aβ 40 ratio at 46.02 years, followed by PiB mean cortical standardized uptake value ratio (SUVR) with a change point at 54.47 years. CSF total tau (Tau) and tau phosphorylated at threonine 181 (Ptau) had a change point at ≈60 years, similar to those for MRI hippocampal volume and cortical thickness. The change point for a cognitive composite occurred at 62.41 years. The change points for CSF Aβ 42 and Aβ 42 /Aβ 40 ratio, albeit not significantly different from that for PiB SUVR, occurred significantly earlier than that for CSF Tau, Ptau, MRI markers, and the cognitive composite. Adjusted analyses confirmed that accelerated changes in CSF Tau, Ptau, MRI markers, and the cognitive composite occurred at ages not significantly different from each other., Conclusions: Our findings support the hypothesized early changes of amyloid in preclinical AD and suggest that changes in neuronal injury and neurodegeneration markers occur close in time to cognitive decline., (© 2020 American Academy of Neurology.)

Wellbeing, a key aspect of mental health, is moderately heritable with varying estimates reported from independent studies employing a variety of instruments. Recent genome-wide association studies (GWAS) have enabled the construction of polygenic scores (PGS) for wellbeing, providing the opportunity for direct comparisons of the variance explained by PGS for different instruments commonly employed in the field. Nine wellbeing measurements (multi-item and single-item), two personality domains (NEO-FFI neuroticism and extraversion), plus the depression domain of the DASS-42 were drawn from a larger self-report battery applied to the TWIN-E study-an Australian longitudinal twin cohort (N = 1660). Heritability was estimated using univariate twin modeling and 12-month test-retest reliability was estimated using intra-class correlation. PGS were constructed using wellbeing GWAS summary-statistics from Baselmans et al. (Nat Genet. 2019), and the variance explained estimated using linear models. Last, a GWAS was performed using COMPAS-W, a quantitative composite wellbeing measure, to explore its utility in genomic studies. Heritability estimates ranged from 23% to 47% across instruments, and multi-item measures showed higher heritability and test-retest reliability than single-item measures. The variance explained by PGS was ~0.5% to 1.5%, with considerable variation between measures, and within each measure over 12 months. Five loci with suggestive association (p < 1 × 10 -5 ) were identified from this initial COMPAS-W wellbeing GWAS. This work highlights the variability across measures currently employed in wellbeing research, with multi-item and composite measures favored over single-item measures. While wellbeing PGS are useful in a research setting, they explain little of the phenotypic variance, highlighting gaps for improved gene discovery., (© 2020 International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.)

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer's disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer's disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T 1 -weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset -9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer's disease, which is alike sporadic Alzheimer's disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer's disease., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Alterations to electroencephalography (EEG) power have been reported for psychiatric conditions such as depression and anxiety, but not for mental wellbeing in a healthy population. This study examined the resting EEG profiles associated with mental wellbeing, and how genetics and environment contribute to these associations using twin modelling. Mental wellbeing was assessed using the COMPAS-W Wellbeing Scale which measures both subjective and psychological wellbeing. In 422 healthy adult monozygotic and dizygotic twins aged 18-61 years, we examined the association between mental wellbeing and EEG power (alpha, beta, theta, delta) using linear mixed models. This was followed by univariate and multivariate twin modelling to assess the heritability of wellbeing and EEG power, and whether the association was driven by shared genetics or environment. A significant association between wellbeing and an interaction of alpha, beta, and delta (ABD) power was found (β = -0.33, p < 0.001) whereby a profile of high alpha and delta and low beta was associated with higher wellbeing, independent of depression and anxiety symptoms. This finding was supported by a five-fold cross-validation analysis. A significant genetic correlation (rG = -0.43) was found to account for 94% of the association between wellbeing and the EEG power interaction. Together, this study has identified a novel EEG profile with a common genetic component that may be a potential biomarker of mental wellbeing. Future studies need to clarify the causal direction of this association., Competing Interests: Declaration of competing interest JMG was a stockholder in MAP Corp Pte Ltd. CRC holds a small quantum of stock. LMW has received fees from BlackThorn Therapeutics for consultancies unrelated to this study. There are no other conflicts of interest to report., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

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.

The aim of this systematic review was to synthesize the existing evidence documenting the psychosocial implications of living with a familial risk of an adult-onset psychiatric disorder. Six databases were searched systematically to identify qualitative and quantitative studies, which explored perspectives of those at increased risk for psychiatric disorders, as well as the general public. Thematic analysis was used to identify major themes. Thirty-five articles met the eligibility criteria and reported on the views of 4,896 participants. The literature demonstrates strong interest in psychiatric genetic testing of adults as well as children, whereas attitudes toward prenatal testing were much less positive. Predictors of interest in testing, as well as perceived advantages and disadvantages were identified. Very few studies are available on anticipated and actual reactions to receiving results. Studies show that the majority of participants feel that having a genetic explanation would alleviate some of the stigma associated with mental illness. This review shows that interest in, and predictors of attitudes toward, psychiatric genetic testing are well researched, but the extent to which attitudes will translate into actual testing uptake is unknown. Future research also needs to assess the actual behavioral and psychological impact of genetic testing., (© 2020 Wiley Periodicals, Inc.)

Despite subjects with Dominantly-Inherited Alzheimer's Disease (DIAD) represent less than 1% of all Alzheimer's Disease (AD) cases, the Dominantly Inherited Alzheimer Network (DIAN) initiative constitutes a strong impact in the understanding of AD disease course with special emphasis on the presyptomatic disease phase. Until now, the 3 genes involved in DIAD pathogenesis (PSEN1, PSEN2 and APP) have been commonly merged into one group (Mutation Carriers, MC) and studied using conventional statistical analysis. Comparisons between groups using null-hypothesis testing or longitudinal regression procedures, such as the linear-mixed-effects models, have been assessed in the extant literature. Within this context, the work presented here performs a comparison between different groups of subjects by considering the 3 genes, either jointly or separately, and using tools based on Machine Learning (ML). This involves a feature selection step which makes use of ANOVA followed by Principal Component Analysis (PCA) to determine which features would be realiable for further comparison purposes. Then, the selected predictors are classified using a Support-Vector-Machine (SVM) in a nested k-Fold cross-validation resulting in maximum classification rates of 72-74% using PiB PET features, specially when comparing asymptomatic Non-Carriers (NC) subjects with asymptomatic PSEN1 Mutation-Carriers (PSEN1-MC). Results obtained from these experiments led to the idea that PSEN1-MC might be considered as a mixture of two different subgroups including: a first group whose patterns were very close to NC subjects, and a second group much more different in terms of imaging patterns. Thus, using a k-Means clustering algorithm it was determined both subgroups and a new classification scenario was conducted to validate this process. The comparison between each subgroup vs . NC subjects resulted in classification rates around 80% underscoring the importance of considering DIAN as an heterogeneous entity., Competing Interests: Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Declaration of interest: All authors disclose any financial and personal relationships with other people or organizations that could inappropriately influence (bias) their work or state if there are no interests to declare. Prof. JM Gorriz

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., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Importance: Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities., Objective: To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance., Design, Setting, and Participants: In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019., Main Outcomes and Measures: The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort., Results: Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = -0.41; SE, 0.08; P = 4.9 × 10-8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10-7), and a smaller nucleus accumbens (Cohen d = -0.27; SE, 0.07; P = 7.3 × 10-5). There was also a significant negative dose response on cortical thickness (β = -0.24; SE, 0.05; P = 6.8 × 10-7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks., Conclusions and Relevance: These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders.

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Background: Polygenic risk scores (PRSs) summarise genetic risk in complex genetic disorders such as bipolar disorder (BD). The aim of this study was to gain in-depth, nuanced information regarding the understanding and experience of receiving a PRS for BD from individuals who already have a BD diagnosis., Methods: Participants from a previous genetics study were invited to receive their PRS in a face-to-face consultation with a genetic counsellor or psychiatrist. Four weeks later, semi-structured interviews were conducted, with 14 'acceptors' (those who chose to receive their PRS) and 4 'decliners' (those who did not wish to receive their PRS)., Results: Four themes were developed: (1) An easy decision, (2) A positive experience, (3) The grey area, and (4) The future is exciting and frightening. Despite some reported initial shock and distress, all acceptors described the experience of receiving their PRS as a positive one. It allowed them to better understand their condition and/or reduced feelings of self-blame. Decliners chose not to receive their results because of a lack of perceived usefulness or concern that PRS may hinder personal recovery., Limitations: Given the qualitative design of the study, statistically valid generalisations cannot be undertaken, nor can causal relationships be established., Conclusions: PRS for BD were generally well accepted and understood. Knowledge regarding the impact of PRS for BD ensures that counselling frameworks are responsive to patient needs as well as informing education for psychiatrists and genetic counsellors, who will play pivotal roles in future polygenic testing provision., Competing Interests: Declaration of Competing Interest Bettina Meiser has a remunerated consultant role with the company AstraZeneca with respect to an unrelated project. The other authors have no conflicts of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10 -6 , 1.7 × 10 - 9 , 3.5 × 10 -12 and 1.0 × 10 -4 , respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.

Frontotemporal dementia and amyotrophic lateral sclerosis are clinically and pathologically overlapping disorders with shared genetic causes. We previously identified a disease locus on chromosome 16p12.1-q12.2 with genome-wide significant linkage in a large European Australian family with autosomal dominant inheritance of frontotemporal dementia and amyotrophic lateral sclerosis and no mutation in known amyotrophic lateral sclerosis or dementia genes. Here we demonstrate the segregation of a novel missense variant in CYLD (c.2155A>G, p.M719V) within the linkage region as the genetic cause of disease in this family. Immunohistochemical analysis of brain tissue from two CYLD p.M719V mutation carriers showed widespread glial CYLD immunoreactivity. Primary mouse neurons transfected with CYLDM719V exhibited increased cytoplasmic localization of TDP-43 and shortened axons. CYLD encodes a lysine 63 deubiquitinase and CYLD cutaneous syndrome, a skin tumour disorder, is caused by mutations that lead to reduced deubiquitinase activity. In contrast with CYLD cutaneous syndrome-causative mutations, CYLDM719V exhibited significantly increased lysine 63 deubiquitinase activity relative to the wild-type enzyme (paired Wilcoxon signed-rank test P = 0.005). Overexpression of CYLDM719V in HEK293 cells led to more potent inhibition of the cell signalling molecule NF-κB and impairment of autophagosome fusion to lysosomes, a key process in autophagy. Although CYLD mutations appear to be rare, CYLD's interaction with at least three other proteins encoded by frontotemporal dementia and/or amyotrophic lateral sclerosis genes (TBK1, OPTN and SQSTM1) suggests that it may play a central role in the pathogenesis of these disorders. Mutations in several frontotemporal dementia and amyotrophic lateral sclerosis genes, including TBK1, OPTN and SQSTM1, result in a loss of autophagy function. We show here that increased CYLD activity also reduces autophagy function, highlighting the importance of autophagy regulation in the pathogenesis of frontotemporal dementia and amyotrophic lateral sclerosis., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge., Methods: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated., Results: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R 2 = 24%) and memory (R 2 = 25%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50%-75%., Discussion: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD., (© 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.)

Development of tau-based therapies for Alzheimer's disease requires an understanding of the timing of disease-related changes in tau. We quantified the phosphorylation state at multiple sites of the tau protein in cerebrospinal fluid markers across four decades of disease progression in dominantly inherited Alzheimer's disease. We identified a pattern of tau staging where site-specific phosphorylation changes occur at different periods of disease progression and follow distinct trajectories over time. These tau phosphorylation state changes are uniquely associated with structural, metabolic, neurodegenerative and clinical markers of disease, and some (p-tau217 and p-tau181) begin with the initial increases in aggregate amyloid-β as early as two decades before the development of aggregated tau pathology. Others (p-tau205 and t-tau) increase with atrophy and hypometabolism closer to symptom onset. These findings provide insights into the pathways linking tau, amyloid-β and neurodegeneration, and may facilitate clinical trials of tau-based treatments.

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (n ADRC  = 381; n DIAN  = 145), preclinical (n ADRC  = 153; n DIAN  = 76), and cognitively impaired (n ADRC  = 54; n DIAN  = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11 C-Pittsburgh compound B or 18 F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)