Publications by authors named "Hieab H H Adams"

62 Publications

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.
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http://dx.doi.org/10.1093/braincomms/fcaa176DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734441PMC
October 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.
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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.
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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.
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http://dx.doi.org/10.1002/alz.12180DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984157PMC
February 2021

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

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http://dx.doi.org/10.1016/S1474-4422(19)30324-2DOI Listing
October 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.
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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.
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http://dx.doi.org/10.3233/JAD-181297DOI Listing
October 2020

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.
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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.
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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

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

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Nat Commun 2019 May 1;10(1):2068. Epub 2019 May 1.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, 00014, Finland.

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.
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http://dx.doi.org/10.1038/s41467-019-10160-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494826PMC
May 2019

Full exploitation of high dimensionality in brain imaging: The JPND working group statement and findings.

Alzheimers Dement (Amst) 2019 Dec 30;11:286-290. Epub 2019 Mar 30.

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

Advances in technology enable increasing amounts of data collection from individuals for biomedical research. Such technologies, for example, in genetics and medical imaging, have also led to important scientific discoveries about health and disease. The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. In our previous EU Joint Programme-Neurodegenerative Disease Research (JPND) Working Group, called HD-READY, we developed methods that allowed successful combination of omics data with neuroimaging. Still, several issues remained to fully leverage high-dimensional multimodality data. For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. In this Full-HD Working Group, we focused on such harmonization of high-dimensional neuroimaging phenotypes in combination with other omics data and how to make the resulting ultra-high-dimensional data easily accessible in neurodegeneration research.
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http://dx.doi.org/10.1016/j.dadm.2019.02.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441785PMC
December 2019

The Epistasis Project: A Multi-Cohort Study of the Effects of BDNF, DBH, and SORT1 Epistasis on Alzheimer's Disease Risk.

J Alzheimers Dis 2019 ;68(4):1535-1547

Oxford Project to Investigate Memory and Ageing (OPTIMA), University Department of Pharmacology, Oxford, UK.

Pre-synaptic secretion of brain-derived neurotrophic factor (BDNF) from noradrenergic neurons may protect the Alzheimer's disease (AD) brain from amyloid pathology. While the BDNF polymorphism (rs6265) is associated with faster cognitive decline and increased hippocampal atrophy, a replicable genetic association of BDNF with AD risk has yet to be demonstrated. This could be due to masking by underlying epistatic interactions between BDNF and other loci that encode proteins involved in moderating BDNF secretion (DBH and Sortilin). We performed a multi-cohort case-control association study of the BDNF, DBH, and SORT1 loci comprising 5,682 controls and 2,454 AD patients from Northern Europe (87% of samples) and Spain (13%). The BDNF locus was associated with increased AD risk (odds ratios; OR = 1.1-1.2, p = 0.005-0.3), an effect size that was consistent in the Northern European (OR = 1.1-1.2, p = 0.002-0.8) but not the smaller Spanish (OR = 0.8-1.6, p = 0.4-1.0) subset. A synergistic interaction between BDNF and sex (synergy factor; SF = 1.3-1.5 p = 0.002-0.02) translated to a greater risk of AD associated with BDNF in women (OR = 1.2-1.3, p = 0.007-0.00008) than men (OR = 0.9-1.0, p = 0.3-0.6). While the DBH polymorphism (rs1611115) was also associated with increased AD risk (OR = 1.1, p = 0.04) the synergistic interaction (SF = 2.2, p = 0.007) between BDNF (rs6265) and DBH (rs1611115) contributed greater AD risk than either gene alone, an effect that was greater in women (SF = 2.4, p = 0.04) than men (SF = 2.0, p = 0.2). These data support a complex genetic interaction at loci encoding proteins implicated in the DBH-BDNF inflammatory pathway that modifies AD risk, particularly in women.
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http://dx.doi.org/10.3233/JAD-181116DOI Listing
August 2020

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

Aging (Albany NY) 2019 03;11(5):1440-1456

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

Cognition in adults shows variation due to developmental and degenerative components. A recent genome-wide association study identified genetic variants for general cognitive function in 148 independent loci. Here, we aimed to elucidate possible developmental and neurodegenerative pathways underlying these genetic variants by relating them to functional, clinical and neuroimaging outcomes. This study was conducted within the population-based Rotterdam Study (N=11,496, mean age 65.3±9.9 years, 58.0% female). We used lead variants for general cognitive function to construct a polygenic score (PGS), and additionally excluded developmental variants at multiple significance thresholds. A higher PGS was related to more years of education (β=0.29, p=4.3x10) and a larger intracranial volume (β=0.05, p=7.5x10). To a smaller extent, the PGS was associated with less cognitive decline (β=0.03, p=1.3x10), which became non-significant after adjusting for education (p=1.6x10). No associations were found with daily functioning, dementia, parkinsonism, stroke or microstructural white matter integrity. Excluding developmental variants attenuated nearly all associations. In conclusion, this study suggests that the genetic variants identified for general cognitive function are acting mainly through the developmental pathway of cognition. Therefore, cognition, assessed cross-sectionally, seems to have limited value as a biomarker for neurodegeneration.
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http://dx.doi.org/10.18632/aging.101844DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428100PMC
March 2019

Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

Neurology 2019 Jan 16. Epub 2019 Jan 16.

Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.

Methods: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.

Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, = 1.77 × 10; and LINC00539/ZDHHC20, = 5.82 × 10. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits ( value for BI, = 9.38 × 10; = 5.23 × 10 for hypertension), smoking ( = 4.4 × 10; = 1.2 × 10), diabetes ( = 1.7 × 10; = 2.8 × 10), previous cardiovascular disease ( = 1.0 × 10; = 2.3 × 10), stroke ( = 3.9 × 10; = 3.2 × 10), and MRI-defined white matter hyperintensity burden ( = 1.43 × 10; = 3.16 × 10), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI ( ≤ 0.0022), without indication of directional pleiotropy.

Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.
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http://dx.doi.org/10.1212/WNL.0000000000006851DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369905PMC
January 2019

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

Neurology 2018 08 1;91(9):e832-e842. Epub 2018 Aug 1.

From the Departments of Radiology and Nuclear Medicine (S.H., H.H.H.A., M.W.V., M.A.I.), Epidemiology (S.H., H.H.H.A., M.K.I., M.W.V., M.A.I.), and Neurology (M.K.I., M.A.I.), Erasmus Medical Center, Rotterdam, the Netherlands; Department of Pharmacology (S.H., C.C.), National University of Singapore; Memory, Aging and Cognition Center (S.H., C.C.), National University Health System; Saw Swee Hock School of Public Health (C.S.T.), National University of Singapore; Department of Radiology (M.H.), University of Pennsylvania, Philadelphia; Department of Psychiatry and Psychotherapy (M.H., H.J.G.), Institute for Community Medicine (M.H., H.V., H.J.G.), and Institute of Diagnostic Radiology and Neuroradiology (N.H.), University Medicine Greifswald, Germany; Therese Pei Fong Chow Research Center for Prevention of Dementia (V.M.), LuiChe Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Centre; Department of Medicine and Therapeutics (V.M.) and Department of Imaging & Interventional Radiology (J.A.), Chinese University of Hong Kong, China; Raffles Neuroscience Centre (N.V.), Raffles Hospital, Singapore; Department of Neurology (E.H.), Medical University of Graz, Austria; and German Center for Neurodegenerative Diseases (DZNE) (R.S.), Site Rostock/Greifswald, Germany.

Objective: To investigate the association of enlarged perivascular spaces (ePVS) with cognition in elderly without dementia.

Methods: We included 5 studies from the Uniform Neuro-Imaging of Virchow-Robin Space Enlargement (UNIVRSE) consortium, namely the Austrian Stroke Prevention Family Study, Study of Health in Pomerania, Rotterdam Study, Epidemiology of Dementia in Singapore study, and Risk Index for Subclinical Brain Lesions in Hong Kong study. ePVS were counted in 4 regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) with harmonized rating across studies. Mini-Mental State Examination (MMSE) and general fluid cognitive ability factor (G-factor) were used to assess cognitive function. For each study, a linear regression model was performed to estimate the effect of ePVS on MMSE and G-factor. Estimates were pooled across studies with the use of inverse variance meta-analysis with fixed- or random-effect models when appropriate.

Results: The final sample size consisted of 3,575 persons (age range 63.4-73.2 years, 50.6% women). Total ePVS counts were not significantly associated with MMSE score (mean difference per ePVS score increase 0.001, 95% confidence interval [CI] -0.007 to 0.008, = 0.885) or G-factor (mean difference per ePVS score increase 0.002, 95% CI -0.001 to 0.006, = 0.148) in age-, sex-, and education-adjusted models. Adjustments for cardiovascular risk factors and MRI markers did not change the results. Repeating the analyses with region-specific ePVS rendered similar results.

Conclusions: In this study, we found that ePVS counts were not associated with cognitive dysfunction in the general population. Future studies with longitudinal designs are warranted to examine whether ePVS contribute to cognitive decline.
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http://dx.doi.org/10.1212/WNL.0000000000006079DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133622PMC
August 2018

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

Nat Commun 2018 07 30;9(1):2976. Epub 2018 Jul 30.

University of California Los Angeles, Los Angeles, CA, 90095, USA.

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci.
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http://dx.doi.org/10.1038/s41467-018-05369-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6065313PMC
July 2018

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

Eur Respir J 2018 09 15;52(3). Epub 2018 Sep 15.

Pulmonary Center, Boston University Schools of Medicine and Public Health, Boston, MA, USA.

Although several genome-wide association studies (GWAS) have investigated the genetics of pulmonary ventilatory function, little is known about the genetic factors that influence gas exchange. The aim of the study was to investigate the heritability of, and genetic variants associated with the diffusing capacity of the lung.GWAS was performed on diffusing capacity of the lung measured by carbon monoxide uptake () and per alveolar volume () using the single-breath technique, in 8372 individuals from two population-based cohort studies, the Rotterdam Study and the Framingham Heart Study. Heritability was estimated in related (n=6246) and unrelated (n=3286) individuals.Heritability of and / ranged between 23% and 28% in unrelated individuals and between 45% and 49% in related individuals. Meta-analysis identified a genetic variant in that is significantly associated with / Gene expression analysis of in human lung tissue revealed a decreased expression in patients with chronic obstructive pulmonary disease (COPD) and subjects with decreased / and / are heritable traits, with a considerable proportion of variance explained by genetics. A functional variant in gene region was significantly associated with / Pulmonary expression was decreased in patients with COPD.
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http://dx.doi.org/10.1183/13993003.00647-2018DOI Listing
September 2018