Publications by authors named "Hieab H Adams"

81 Publications

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

Commun Biol 2021 Sep 17;4(1):1094. Epub 2021 Sep 17.

Department of Radiology and Nuclear Medicine, Erasmus MC, Medical Center, Rotterdam, the Netherlands.

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

Download full-text PDF

Source
http://dx.doi.org/10.1038/s42003-021-02622-zDOI Listing
September 2021

Genetic Influences on Hippocampal Subfields: An Emerging Area of Neuroscience Research.

Neurol Genet 2021 Jun 21;7(3):e591. Epub 2021 May 21.

Barcelonaβeta Brain Research Center (BBRC) (N.V.-T., J.M.G.-d-E., J.L.M., J.D.G., G.O.), Pasqual Maragall Foundation; Centre for Genomic Regulation (CRG) (N.V.-T., R.G.), the Barcelona Institute for Science and Technology, Spain; Department of Clinical Genetics (N.V.-T., T.E.E., H.H.A.), Erasmus Medical Center, Rotterdam, the Netherlands; Universitat Pompeu Fabra (N.V.-T., J.M.G.--E., J.L.M., R.G., J.D.G.), Barcelona, Spain; Department of Radiology and Nuclear Medicine (H.H.A.), Erasmus Medical Center, Rotterdam, the Netherlands; IMIM (Hospital del Mar Medical Research Institute) (J.L.M., J.D.G., G.O.), Barcelona, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES) (J.L.M., G.O.); and Centro de Investigación Biomédica en Red Bioingeniería (J.D.G.), Biomateriales y Nanomedicina, Madrid, Spain.

There is clear evidence that hippocampal subfield volumes have partly distinct genetic determinants associated with specific biological processes. The identification of genetic correlates of hippocampal subfield volumes may help to elucidate the mechanisms of neurologic diseases, as well as aging and neurodegenerative processes. However, despite the emerging interest in this area of research, the current knowledge of the genetic architecture of hippocampal subfields has not yet been consolidated. We aimed to provide a review of the current evidence from genetic studies of hippocampal subfields, highlighting current priorities and upcoming challenges. The limited number of studies investigating the influential genetic effects on hippocampal subfields, a lack of replicated results and longitudinal designs, and modest sample sizes combined with insufficient standardization of protocols are identified as the most pressing challenges in this emerging area of research.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1212/NXG.0000000000000591DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192059PMC
June 2021

The genetics of circulating BDNF: towards understanding the role of BDNF in brain structure and function in middle and old ages.

Brain Commun 2020 28;2(2):fcaa176. Epub 2020 Oct 28.

Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, 78229 TX, USA.

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

Download full-text PDF

Source
http://dx.doi.org/10.1093/braincomms/fcaa176DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734441PMC
October 2020

Cerebral small vessel disease genomics and its implications across the lifespan.

Nat Commun 2020 12 8;11(1):6285. Epub 2020 Dec 8.

University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-19111-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722866PMC
December 2020

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Nat Commun 2020 09 22;11(1):4796. Epub 2020 Sep 22.

Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-18367-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508833PMC
September 2020

Association of common genetic variants with brain microbleeds: A genome-wide association study.

Neurology 2020 12 10;95(24):e3331-e3343. Epub 2020 Sep 10.

From the Departments of Epidemiology (M.J.K., H.H.H.A., D.V., S.J.v.d.L., P.Y., M.W.V., N.A., C.M.v.D., M.A.I.), Radiology and Nuclear Medicine (H.H.H.A., P.Y., A.v.d.L., M.W.V.), and Clinical Genetics (H.H.H.A.), Erasmus MC University Medical Center, Rotterdam, the Netherlands; Stroke Research Group, Department of Clinical Neurosciences (D.L., M.T., J.L., D.J.T., H.S.M.), University of Cambridge, UK; Department of Neurology (J.R.J.R., C.L.S., J.J.H., A.S.B., C.D., S. Seshadri), Boston University School of Medicine; The Framingham Heart Study (J.R.J.R., C.L.S., J.J.H., A.S.B., S. Seshadri), MA; Department of Biostatistics (A.V.S.), University of Michigan, Ann Arbor; Icelandic Heart Association (A.V.S., S. Sigurdsson, V.G.), Kopavogur, Iceland; Brown Foundation Institute of Molecular Medicine, McGovern Medical School (M.F.), and Human Genetics Center, School of Public Health (M.F.), University of Texas Health Science Center at Houston; Clinical Division of Neurogeriatrics, Department of Neurology (E.H., L.P., R.S.), Institute for Medical Informatics, Statistics and Documentation (E.H.), and Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry (Y.S., H.S.), Medical University of Graz, Austria; Center of Cerebrovascular Diseases, Department of Neurology (J.L.), West China Hospital, Sichuan University, Chengdu; Stroke Research Centre, Queen Square Institute of Neurology (I.C.H., D.W., H.H., D.J.W.), University College London, UK; Department of Neurosurgery (I.C.H.), Klinikum rechts der Isar, University of Munich, Germany; Centre for Cognitive Ageing and Cognitive Epidemiology, Psychology (M.L., D.C.M.L., M.E.B., I.J.D., J.M.W.), and Centre for Clinical Brain Sciences, Edinburgh Imaging, UK Dementia Research Institute (M.E.B., J.M.W.), University of Edinburgh, UK; Department of Internal Medicine, Section of Gerontology and Geriatrics (S.T.), Department of Cardiology (S.T., J.v.d.G., J.W.J.), Section of Molecular Epidemiology, Biomedical Data Sciences (E.B.v.d.A., M.B., P.E.S.), Leiden Computational Biology Center, Biomedical Data Sciences (E.B.v.d.A.), Department of Radiology (J.v.d.G.), and Einthoven Laboratory for Experimental Vascular Medicine (J.W.J.), Leiden University Medical Center, the Netherlands; Department of Neurology (A.-K.G., N.S.R.), Massachusetts General Hospital, Harvard Medical School, Boston; Memory Aging and Cognition Center (S.H., C.C.), National University Health System, Singapore; Department of Pharmacology (S.H., C.C.) and Saw Swee Hock School of Public Health (S.H.), National University of Singapore and National University Health System, Singapore; Pattern Recognition & Bioinformatics (E.B.v.d.A.), Delft University of Technology, the Netherlands; Department of Biostatistics (S.L., J.J.H., Q.Y., A.S.B.), Boston University School of Public Health, MA; Department of Radiology (C.R.J., K.K.), Mayo Clinic, Rochester, MN; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (C.L.S., S. Seshadri), UT Health San Antonio, TX; Department of Medicine, Division of Geriatrics (B.G.W., T.H.M), and Memory Impairment and Neurodegenerative Dementia (MIND) Center (T.H.M.), University of Mississippi Medical Center, Jackson; Singapore Eye Research Institute (C.Y.C., J.Y.K., T.Y.W.); Department of Neuroradiology (Z.M., J.M.W.), NHS Lothian, Edinburgh; Institute of Cardiovascular and Medical Sciences (D.J.S.), College of Medical, Veterinary and Life Sciences, University of Glasgow, UK; Division of Cerebrovascular Neurology (R.F.G.), Johns Hopkins University, Baltimore, MD; Department of Neuroradiology (A.D.M.), Atkinson Morley Neurosciences Centre, St George's NHS Foundation Trust, London, UK; Department of Neurology (C.D.), University of California at Davis; Nuffield Department of Population Health (C.M.v.D.), University of Oxford, UK; Laboratory of Epidemiology and Population Sciences (L.J.L.), National Institute on Aging, Baltimore, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik, Iceland.

Objective: To identify common genetic variants associated with the presence of brain microbleeds (BMBs).

Methods: We performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.

Results: BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the region reached genome-wide significance for its association with BMB (lead rs769449; odds ratio [OR] [95% confidence interval (CI)] 1.33 [1.21-1.45]; = 2.5 × 10). ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; = 1.0 × 10) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; = 0.68). ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.

Conclusions: Genetic variants in the region are associated with the presence of BMB, most likely due to the ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1212/WNL.0000000000010852DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836652PMC
December 2020

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

Alzheimers Dement 2021 02 4;17(2):205-214. Epub 2020 Sep 4.

Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.

Introduction: Our aim was to study whether systemic metabolites are associated with magnetic resonance imaging (MRI) measures of brain and hippocampal atrophy and white matter hyperintensities (WMH).

Methods: We studied associations of 143 plasma-based metabolites with MRI measures of brain and hippocampal atrophy and WMH in three independent cohorts (n = 3962). We meta-analyzed the results of linear regression analyses to determine the association of metabolites with MRI measures.

Results: Higher glucose levels and lower levels of three small high density lipoprotein (HDL) particles were associated with brain atrophy. Higher glucose levels were associated with WMH.

Discussion: Glucose levels were associated with brain atrophy and WMH, and small HDL particle levels were associated with brain atrophy. Circulating metabolites may aid in developing future intervention trials.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/alz.12180DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984157PMC
February 2021

Effect of BDNF Val66Met on hippocampal subfields volumes and compensatory interaction with APOE-ε4 in middle-age cognitively unimpaired individuals from the ALFA study.

Brain Struct Funct 2020 Nov 17;225(8):2331-2345. Epub 2020 Aug 17.

Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.

Background: Current evidence supports the involvement of brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, and the ε4 allele of APOE gene in hippocampal-dependent functions. Previous studies on the association of Val66Met with whole hippocampal volume included patients of a variety of disorders. However, it remains to be elucidated whether there is an impact of BDNF Val66Met polymorphism on the volumes of the hippocampal subfield volumes (HSv) in cognitively unimpaired (CU) individuals, and the interactive effect with the APOE-ε4 status.

Methods: BDNF Val66Met and APOE genotypes were determined in a sample of 430 CU late/middle-aged participants from the ALFA study (ALzheimer and FAmilies). Participants underwent a brain 3D-T1-weighted MRI scan, and volumes of the HSv were determined using Freesurfer (v6.0). The effects of the BDNF Val66Met genotype on the HSv were assessed using general linear models corrected by age, gender, education, number of APOE-ε4 alleles and total intracranial volume. We also investigated whether the association between APOE-ε4 allele and HSv were modified by BDNF Val66Met genotypes.

Results: BDNF Val66Met carriers showed larger bilateral volumes of the subiculum subfield. In addition, HSv reductions associated with APOE-ε4 allele were significantly moderated by BDNF Val66Met status. BDNF Met carriers who were also APOE-ε4 homozygous showed patterns of higher HSv than BDNF Val carriers.

Conclusion: To our knowledge, the present study is the first to show that carrying the BDNF Val66Met polymorphisms partially compensates the decreased on HSv associated with APOE-ε4 in middle-age cognitively unimpaired individuals.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00429-020-02125-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544723PMC
November 2020

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

Geroscience 2021 04 11;43(2):829-843. Epub 2020 Aug 11.

Department of Geriatric Medicine, Radboudumc Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Reinier Postlaan 4, 6525GC, Nijmegen, The Netherlands.

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

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11357-020-00228-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110634PMC
April 2021

Aging-Dependent Genetic Effects Associated to ADHD Predict Longitudinal Changes of Ventricular Volumes in Adulthood.

Front Psychiatry 2020 29;11:574. Epub 2020 Jun 29.

Universitat Pompeu Fabra (UPF), Barcelona, Spain.

Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood-onset disorder that can persist into adult life. Most genetic studies have focused on investigating biological mechanisms of ADHD during childhood. However, little is known about whether genetic variants associated with ADHD influence structural brain changes throughout adulthood.

Methods: Participant of the study were drawn from a population-based sample of 3,220 healthy individuals drawn from the Rotterdam Study, with at least two magnetic resonance imaging (MRI)-scans (8,468 scans) obtained every 3-4 years. We investigate associations of genetic single nucleotide polymorphisms (SNPs) that have previously been identified in genome-wide association studies for ADHD, and trajectories of global and subcortical brain structures in an adult population (aged 50 years and older), acquired through MRI. We also evaluated the existence of age-dependent effects of these genetic variants on trajectories of brain structures. These analyses were reproduced among individuals 70 years of age or older to further explore aging-dependent mechanisms. We additionally tested baseline associations using the first MRI-scan of the 3,220 individuals.

Results: We observed significant age-dependent effects on the rs212178 in trajectories of ventricular size (lateral ventricles, P= 4E-05; inferior lateral ventricles, P=3.8E-03; third ventricle, P=2.5E-03; fourth ventricle, P=5.5E-03). Specifically, carriers of the G allele, which was reported as protective for ADHD, had a smaller increase of ventricular size compared with homozygotes for the A allele in elder stages. Post hoc analysis on the subset of individuals older than 70 years of age reinforced these results (lateral ventricles, P=7.3E-05). In addition, the rs4916723, and the rs281324 displayed nominal significant age-dependent effects in trajectories of the amygdala volume (P=1.4E-03), and caudate volume (P=1.8E-03), respectively.

Conclusions: To the best of our knowledge, this is the first study suggesting the involvement of protective genetic variants for ADHD on prevention of brain atrophy during adulthood.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fpsyt.2020.00574DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344235PMC
June 2020

Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities.

Stroke 2020 07 10;51(7):2111-2121. Epub 2020 Jun 10.

Department of Psychiatry (C.F.-N.), University of California, San Diego, La Jolla, CA.

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 (), 10q23.1 (), and 10q24.33 ( 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 () 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: (2q32.1), (3q27.1), (5q27.1), and (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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/STROKEAHA.119.027544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365038PMC
July 2020

Determinants of the Presence and Size of Intracranial Aneurysms in the General Population: The Rotterdam Study.

Stroke 2020 07 10;51(7):2103-2110. Epub 2020 Jun 10.

Department of Neurology (T.Y.C., D.W.J.D., B.R.), Erasmus MC - University Medical Center, Rotterdam, the Netherlands.

Background And Purpose: The prevalence of unruptured intracranial aneurysms (UIAs) in the adult population is ≈3%. Rupture of an intracranial aneurysm can have devastating consequences, which emphasizes the importance of identification of potentially modifiable determinants for the presence and size of UIAs. Our aim was to study the association of a broad spectrum of potential determinants with the presence and size of UIAs in a general adult population.

Methods: Between 2005 and 2015, 5841 participants from the population-based Rotterdam Study (mean age, 64.4 years, 45.0% male) underwent brain magnetic resonance imaging (1.5T). These scans were evaluated for the presence of incidental UIAs. We determined number and volume of the UIAs. Using logistic and linear regression models, we assessed the association of cardiovascular, lifestyle and emerging inflammatory and hormonal determinants with the presence and volume of UIAs.

Results: In 134 (2.3%) participants, ≥1 UIAs were detected (149 UIAs in total), with a median volume of 61.1 mm (interquartile range, 33.2-134.0). In multivariable models, female sex (odds ratio, 1.92 [95% CI, 1.33-2.84]), hypertension (odds ratio, 1.73 [95% CI, 1.13-2.68]), and current smoking (odds ratio, 3.75 [95% CI, 2.27-6.33]) were associated with the presence of UIAs. We found no association of alcohol use, physical activity, or diet quality with UIA presence. Finally, we found white blood cell count to relate to larger aneurysm volume (difference in volume of 33.6 mm per 10/L increase in white blood cell [95% CI, 3.92-63.5]).

Conclusions: In this population-based study, female sex, hypertension, and smoking, but no other lifestyle determinants, were associated with the presence of UIAs. White blood cell count is associated with size of UIAs. Preventive strategies should focus on treating hypertension and promoting cessation of smoking.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/STROKEAHA.120.029296DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306261PMC
July 2020

Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes.

Cereb Cortex 2020 06;30(7):4121-4139

Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04109 Leipzig, Germany.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/cercor/bhaa035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7947185PMC
June 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

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

Ann Neurol 2020 05 27;87(5):774-787. Epub 2020 Mar 27.

Department of Neurology, MS Center ErasMS, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands.

Objective: Multiple sclerosis (MS) is a neurological disease with a substantial genetic component and immune-mediated neurodegeneration. Patients with MS show structural brain differences relative to individuals without MS, including smaller regional volumes and alterations in white matter (WM) microstructure. Whether genetic risk for MS is associated with brain structure during early neurodevelopment remains unclear. In this study, we explore the association between MS polygenic risk scores (PRS) and brain imaging outcomes from a large, population-based pediatric sample to gain insight into the underlying neurobiology of MS.

Methods: We included 8- to 12-year-old genotyped participants from the Generation R Study in whom T1-weighted volumetric (n = 1,136) and/or diffusion tensor imaging (n = 1,088) had been collected. PRS for MS were calculated based on a large genome-wide association study of MS (n = 41,505) and were regressed on regional volumes, global and tract-specific fractional anisotropy (FA), and global mean diffusivity using linear regression.

Results: No associations were observed for the regional volumes. We observed a positive association between the MS PRS and global FA (β = 0.098, standard error [SE] = 0.030, p = 1.08 × 10 ). Tract-specific analyses showed higher FA and lower radial diffusivity in several tracts. We replicated our findings in an independent sample of children (n = 186) who were scanned in an earlier phase (global FA; β = 0.189, SE = 0.072, p = 9.40 × 10 ).

Interpretation: This is the first study to show that greater genetic predisposition for MS is associated with higher global brain WM FA at an early age in the general population. Our results suggest a preadolescent time window within neurodevelopment in which MS risk variants act upon the brain. ANN NEUROL 2020;87:774-787.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/ana.25717DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187244PMC
May 2020

Genetic Burden for Late-Life Neurodegenerative Disease and Its Association With Early-Life Lipids, Brain, Behavior, and Cognition.

Front Psychiatry 2020 7;11:33. Epub 2020 Feb 7.

Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.

Background: Genetics play a significant role in the etiology of late-life neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and frontotemporal dementia. Part of the individual differences in risk for these diseases can be traced back decades before the onset of disease symptoms. Previous studies have shown evidence for plausible links of apolipoprotein E (APOE), the most important genetic marker for Alzheimer's disease, with early-life cognition and neuroimaging markers. We aimed to assess whether genome-wide genetic burden for the aforementioned neurodegenerative diseases plays a role in early-life processes.

Methods: We studied children from the Generation R Study, a prospective birth cohort. APOE genotypes and polygenic genetic burdens for Alzheimer's disease, Parkinson's disease, and frontotemporal dementia were obtained through genome-wide genotyping. Non-verbal intelligence was assessed through cognitive tests at the research center around the age of 6 years, and educational attainment through a national school performance test around the age of 11 years. The Child Behavior Checklist was administered around the age of 10 years, and data from the anxious/depressed, withdrawn/depressed, and the internalizing behavior problems scales were used. Children participated in a neuroimaging study when they were 10 years old, in which structural brain metrics were obtained. Lipid serum profiles, which may be influenced by APOE genotype, were assessed from venal blood obtained around the age of 6 years. The sample size per analysis varied between 1,641 and 3,650 children due to completeness of data.

Results: We did not find evidence that APOE genotype or the polygenic scores impact on childhood nonverbal intelligence, educational attainment, internalizing behavior, and global brain structural measures including total brain volume and whole brain fractional anisotropy (all p > 0.05). Carriership of the APOE ε2 allele was associated with lower and APOE ε4 with higher low-density lipoprotein cholesterol concentrations when compared to APOE ε3/ε3 carriers.

Conclusion: We found no evidence that genetic burden for late-life neurodegenerative diseases associates with early-life cognition, internalizing behavior, or global brain structure.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fpsyt.2020.00033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018686PMC
February 2020

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

Neurology 2020 01 9;94(3):e254-e266. Epub 2019 Dec 9.

From the Harvard T.H. Chan School of Public Health (M.P.P.), Boston; Department of Neurology (J.J.H., A.S.B., C.L.S., H.J.A., S.S.), Boston University School of Medicine; Framingham Heart Study (M.P.P., J.J.H., A.S.B., C.D., E.R.M., C.L.S., H.J.A., D.L., S.S.), MA; Centre for Human Psychopharmacology (M.P.P.), Swinburne University of Technology; Melbourne Dementia Research Centre (M.P.P.), The Florey Institute for Neuroscience and Mental Health & The University of Melbourne, Australia; Department of Biostatistics (J.J.H., A.S.B.), Boston University School of Public Health, MA; Department of Neurology (C.D.), School of Medicine & Imaging of Dementia and Aging Laboratory, Center for Neuroscience, University of California Davis, Sacramento; Departments of Epidemiology (H.H.H.A.) and Radiology and Nuclear Medicine (H.H.H.A.), Erasmus MC, Rotterdam, the Netherlands; Department of Epidemiology (A.P.R., W.T.L., B.M.P.), Fred Hutchinson Cancer Research Center (A.P.R.), Department of Neurology (W.T.L.), Cardiovascular Health Research Unit, Department of Medicine (B.M.P., J.C.B.), and Department of Health Services (B.M.P.), University of Washington, Seattle; Human Genetics Center, Department of Epidemiology (M.F.), Human Genetics & Environmental Sciences, School of Public Health (M.F.), and The Brown Foundation Institute of Molecular Medicine, Research Center for Human Genetics (M.F.), University of Texas Health Science Center, Houston; Departments of Pathology and Laboratory Medicine (R.P.T.) and Biochemistry (R.P.T.), Larner College of Medicine, University of Vermont, Burlington; Department of Neurology (O.L.), School of Medicine, University of Pittsburgh, PA; Kaiser Permanente Washington Health Research Institute (B.M.P.), Seattle; The Population Sciences Branch of the National Heart, Lung and Blood Institute (D.L.), NIH, Bethesda, MD; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases (S.S.), University of Texas Health Sciences Center, San Antonio; Department of Neurology (E.R.M.), Brigham & Women's Hospital; and Harvard Medical School (E.R.M.), Boston, MA.

Objective: To test the hypothesis that the inflammatory marker plasma soluble CD14 (sCD14) associates with incident dementia and related endophenotypes in 2 community-based cohorts.

Methods: Our samples included the prospective community-based Framingham Heart Study (FHS) and Cardiovascular Health Study (CHS) cohorts. Plasma sCD14 was measured at baseline and related to the incidence of dementia, domains of cognitive function, and MRI-defined brain volumes. Follow-up for dementia occurred over a mean of 10 years (SD 4) in the FHS and a mean of 6 years (SD 3) in the CHS.

Results: We studied 1,588 participants from the FHS (mean age 69 ± 6 years, 47% male, 131 incident events) and 3,129 participants from the CHS (mean age 72 ± 5 years, 41% male, 724 incident events) for the risk of incident dementia. Meta-analysis across the 2 cohorts showed that each SD unit increase in sCD14 was associated with a 12% increase in the risk of incident dementia (95% confidence interval 1.03-1.23; = 0.01) following adjustments for age, sex, ε4 status, and vascular risk factors. Higher levels of sCD14 were associated with various cognitive and MRI markers of accelerated brain aging in both cohorts and with a greater progression of brain atrophy and a decline in executive function in the FHS.

Conclusion: sCD14 is an inflammatory marker related to brain atrophy, cognitive decline, and incident dementia.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1212/WNL.0000000000008682DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108812PMC
January 2020

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

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

Proc Natl Acad Sci U S A 2019 10 1;116(42):21213-21218. Epub 2019 Oct 1.

Department of Medical Informatics, Erasmus MC University Medical Center, 3015 CE, Rotterdam, The Netherlands;

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

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.1902376116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800321PMC
October 2019

Migraine Genetic Variants Influence Cerebral Blood Flow.

Headache 2020 01 26;60(1):90-100. Epub 2019 Sep 26.

Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.

Objective: To investigate the association of migraine genetic variants with cerebral blood flow (CBF).

Background: Migraine is a common disorder with many genetic and non-genetic factors affecting its occurrence. The exact pathophysiological mechanisms underlying the disease remain unclear, but are known to involve hemodynamic and vascular disruptions. Recent genome-wide association studies have identified 44 genetic variants in 38 genetic loci that affect the risk of migraine, which provide the opportunity to further disentangle these mechanisms.

Methods: We included 4665 participants of the population-based Rotterdam Study (mean age 65.0 ± 10.9 years, 55.6% women). Cross-sectional area (mm ), flow velocity (mm/s), and blood flow (mL/min) were measured in both carotids and the basilar artery using 2-dimensional phase-contrast magnetic resonance imaging. We analyzed 43 previously identified migraine variants separately and calculated a genetic risk score (GRS). To assess the association with CBF, we used linear regression models adjusted for age, sex, and total brain volume. Hierarchical clustering was performed based on the associations with CBF measures and tissue enrichment.

Results: The rs67338227 risk allele was associated with higher flow velocity and smaller cross-sectional area in the carotids (P  = 3.7 × 10 ). Other variants were related to CBF with opposite directions of effect, but not significantly after multiple testing adjustments (P < 1.4 × 10 ). The migraine GRS was not associated with CBF after multiple testing corrections. Migraine risk variants were found to be enriched for flow in the basilar artery (λ = 2.39).

Conclusions: These findings show that genetic migraine risk is complexly associated with alterations in cerebral hemodynamics.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/head.13651DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003871PMC
January 2020

The Uncovering Neurodegenerative Insights Through Ethnic Diversity consortium.

Lancet Neurol 2019 10;18(10):915

Department of Epidemiology, Erasmus University Medical Center Rotterdam 3015 CE, Netherlands.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/S1474-4422(19)30324-2DOI Listing
October 2019

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

Neurobiol Aging 2019 12 23;84:9-16. Epub 2019 Jul 23.

Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands. Electronic address:

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

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neurobiolaging.2019.07.008DOI Listing
December 2019

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

Commun Biol 2019 2;2:285. Epub 2019 Aug 2.

17Department of Biomedical Data Sciences, Statistical Genetics, Leiden University Medical Center, Leiden, 2333ZA the Netherlands.

Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications ( and ), or close to genes causing Mendelian brain-related diseases ( and ). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s42003-019-0537-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677735PMC
April 2020

High-Dimensional Mapping of Cognition to the Brain Using Voxel-Based Morphometry and Subcortical Shape Analysis.

J Alzheimers Dis 2019 ;71(1):141-152

Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.

Background: It is increasingly recognized that the complex functions of human cognition are not accurately represented by arbitrarily-defined anatomical brain regions. Given the considerable functional specialization within such regions, more fine-grained studies of brain structure could capture such localized associations. However, such analyses/studies in a large community-dwelling population are lacking.

Objective: To perform a fine-mapping of cognitive ability to cortical and subcortical grey matter on magnetic resonance imaging (MRI).

Methods: In 3,813 stroke-free and non-demented persons from the Rotterdam Study (mean age 69.1 (±8.8) years; 55.8% women) with cognitive assessments and brain MRI, we performed voxel-based morphometry and subcortical shape analysis on global cognition and separate tests that tapped into memory, information processing speed, fine motor speed, and executive function domains.

Results: We found that the different cognitive tests significantly associated with grey matter density in differential but also overlapping brain regions, primarily in the left hemisphere. Clusters of significantly associated voxels with global cognition were located within multiple anatomic regions: left amygdala, hippocampus, parietal lobule, superior temporal gyrus, insula and posterior temporal lobe. Subcortical shape analysis revealed associations primarily within the head and tail of the caudate nucleus, putamen, ventral part of the thalamus, and nucleus accumbens, more equally distributed among the left and right hemisphere. Within the caudate nucleus both positive (head) as well as negative (tail) associations were observed with global cognition.

Conclusions: In a large population-based sample, we mapped cognitive performance to cortical and subcortical grey matter density using a hypothesis-free approach with high-dimensional neuroimaging. Leveraging the power of our large sample size, we confirmed well-known associations as well as identified novel brain regions related to cognition.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3233/JAD-181297DOI Listing
October 2020

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

Hum Mutat 2019 11 7;40(11):2131-2145. Epub 2019 Aug 7.

Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.

Noncoding RNAs have been widely recognized as essential mediators of gene regulation. However, in contrast to protein-coding genes, much less is known about the influence of noncoding RNAs on human diseases. Here we examined the association of genetic variants located in primary microRNA sequences and long noncoding RNAs (lncRNAs) with Alzheimer disease (AD) by leveraging data from the largest genome-wide association meta-analysis of late-onset AD. Variants annotated to 5 miRNAs and 10 lncRNAs (in seven distinct loci) exceeded the Bonferroni-corrected significance threshold (p < 1.02 × 10 ). Among these, a leading variant (rs2526377:A>G) at the 17q22 locus annotated to two noncoding RNAs (MIR142 and BZRAP1-AS) was significantly associated with a reduced risk of AD and fulfilled predefined criteria for being a functional variant. Our functional genomic analyses revealed that rs2526377 affects the promoter activity and decreases the expression of miR-142. Moreover, differential expression analysis by RNA-Seq in human iPSC-derived neural progenitor cells and the hippocampus of miR-142 knockout mice demonstrated multiple target genes of miR-142 in the brain that are likely to be involved in the inflammatory and neurodegenerative manifestations of AD. These include TGFBR1 and PICALM, of which their derepression in the brain due to reduced expression levels of miR-142-3p may reduce the risk of AD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/humu.23872DOI Listing
November 2019

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

Cereb Cortex 2020 03;30(2):575-586

Bordeaux Population Health Research Center, INSERM UMR, University of Bordeaux, Bordeaux 33076, France.

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

Download full-text PDF

Source
http://dx.doi.org/10.1093/cercor/bhz108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444740PMC
March 2020

Multi-Site Meta-Analysis of Morphometry.

IEEE/ACM Trans Comput Biol Bioinform 2019 Sep-Oct;16(5):1508-1514. Epub 2019 May 23.

Genome-wide association studies (GWAS) link full genome data to a handful of traits. However, in neuroimaging studies, there is an almost unlimited number of traits that can be extracted for full image-wide big data analyses. Large populations are needed to achieve the necessary power to detect statistically significant effects, emphasizing the need to pool data across multiple studies. Neuroimaging consortia, e.g., ENIGMA and CHARGE, are now analyzing MRI data from over 30,000 individuals. Distributed processing protocols extract harmonized features at each site, and pool together only the cohort statistics using meta analysis to avoid data sharing. To date, such MRI projects have focused on single measures such as hippocampal volume, yet voxelwise analyses (e.g., tensor-based morphometry; TBM) may help better localize statistical effects. This can lead to $10^{13}$1013 tests for GWAS and become underpowered. We developed an analytical framework for multi-site TBM by performing multi-channel registration to cohort-specific templates. Our results highlight the reliability of the method and the added power over alternative options while preserving single site specificity and opening the doors for well-powered image-wide genome-wide discoveries.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1109/TCBB.2019.2914905DOI Listing
March 2020

Stats: a trillion P values and counting.

Authors:
Hieab H H Adams

Nature 2019 05;569(7756):336

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/d41586-019-01527-6DOI Listing
May 2019
-->