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1. Multi-omics and pathway analyses of genome-wide associations implicate regulation and immunity in verbal declarative memory performance.

Author

Mei H, Simino J, Li L, Jiang F, Bis JC, Davies G, Hill WD, Xia C, Gudnason V, Yang Q, Lahti J, Smith JA, Kirin M, De Jager P, Armstrong NJ, Ghanbari M, Kolcic I, Moran C, Teumer A, Sargurupremraj M, Mahmud S, Fornage M, Zhao W, Satizabal CL, Polasek O, Räikkönen K, Liewald DC, Homuth G, Callisaya M, Mather KA, Windham BG, Zemunik T, Palotie A, Pattie A, van der Auwera S, Thalamuthu A, Knopman DS, Rudan I, Starr JM, Wittfeld K, Kochan NA, Griswold ME, Vitart V, Brodaty H, Gottesman R, Cox SR, Psaty BM, Boerwinkle E, Chasman DI, Grodstein F, Sachdev PS, Srikanth V, Hayward C, Wilson JF, Eriksson JG, Kardia SLR, Grabe HJ, Bennett DA, Ikram MA, Deary IJ, van Duijn CM, Launer L, Fitzpatrick AL, Seshadri S, Bressler J, Debette S, and Mosley TH Jr

Subjects
Humans, Aged, Multiomics, Memory, Cognition, Polymorphism, Single Nucleotide genetics, Genome-Wide Association Study methods, MicroRNAs
Abstract

Background: Uncovering the functional relevance underlying verbal declarative memory (VDM) genome-wide association study (GWAS) results may facilitate the development of interventions to reduce age-related memory decline and dementia., Methods: We performed multi-omics and pathway enrichment analyses of paragraph (PAR-dr) and word list (WL-dr) delayed recall GWAS from 29,076 older non-demented individuals of European descent. We assessed the relationship between single-variant associations and expression quantitative trait loci (eQTLs) in 44 tissues and methylation quantitative trait loci (meQTLs) in the hippocampus. We determined the relationship between gene associations and transcript levels in 53 tissues, annotation as immune genes, and regulation by transcription factors (TFs) and microRNAs. To identify significant pathways, gene set enrichment was tested in each cohort and meta-analyzed across cohorts. Analyses of differential expression in brain tissues were conducted for pathway component genes., Results: The single-variant associations of VDM showed significant linkage disequilibrium (LD) with eQTLs across all tissues and meQTLs within the hippocampus. Stronger WL-dr gene associations correlated with reduced expression in four brain tissues, including the hippocampus. More robust PAR-dr and/or WL-dr gene associations were intricately linked with immunity and were influenced by 31 TFs and 2 microRNAs. Six pathways, including type I diabetes, exhibited significant associations with both PAR-dr and WL-dr. These pathways included fifteen MHC genes intricately linked to VDM performance, showing diverse expression patterns based on cognitive status in brain tissues., Conclusions: VDM genetic associations influence expression regulation via eQTLs and meQTLs. The involvement of TFs, microRNAs, MHC genes, and immune-related pathways contributes to VDM performance in older individuals., (© 2024. The Author(s).)

Published
2024
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2. Genetic variants associated with longitudinal changes in brain structure across the lifespan.

Author

Brouwer RM, Klein M, Grasby KL, Schnack HG, Jahanshad N, Teeuw J, Thomopoulos SI, Sprooten E, Franz CE, Gogtay N, Kremen WS, Panizzon MS, Olde Loohuis LM, Whelan CD, Aghajani M, Alloza C, Alnæs D, Artiges E, Ayesa-Arriola R, Barker GJ, Bastin ME, Blok E, Bøen E, Breukelaar IA, Bright JK, Buimer EEL, Bülow R, Cannon DM, Ciufolini S, Crossley NA, Damatac CG, Dazzan P, de Mol CL, de Zwarte SMC, Desrivières S, Díaz-Caneja CM, Doan NT, Dohm K, Fröhner JH, Goltermann J, Grigis A, Grotegerd D, Han LKM, Harris MA, Hartman CA, Heany SJ, Heindel W, Heslenfeld DJ, Hohmann S, Ittermann B, Jansen PR, Janssen J, Jia T, Jiang J, Jockwitz C, Karali T, Keeser D, Koevoets MGJC, Lenroot RK, Malchow B, Mandl RCW, Medel V, Meinert S, Morgan CA, Mühleisen TW, Nabulsi L, Opel N, de la Foz VO, Overs BJ, Paillère Martinot ML, Redlich R, Marques TR, Repple J, Roberts G, Roshchupkin GV, Setiaman N, Shumskaya E, Stein F, Sudre G, Takahashi S, Thalamuthu A, Tordesillas-Gutiérrez D, van der Lugt A, van Haren NEM, Wardlaw JM, Wen W, Westeneng HJ, Wittfeld K, Zhu AH, Zugman A, Armstrong NJ, Bonfiglio G, Bralten J, Dalvie S, Davies G, Di Forti M, Ding L, Donohoe G, Forstner AJ, Gonzalez-Peñas J, Guimaraes JPOFT, Homuth G, Hottenga JJ, Knol MJ, Kwok JBJ, Le Hellard S, Mather KA, Milaneschi Y, Morris DW, Nöthen MM, Papiol S, Rietschel M, Santoro ML, Steen VM, Stein JL, Streit F, Tankard RM, Teumer A, van 't Ent D, van der Meer D, van Eijk KR, Vassos E, Vázquez-Bourgon J, Witt SH, Adams HHH, Agartz I, Ames D, Amunts K, Andreassen OA, Arango C, Banaschewski T, Baune BT, Belangero SI, Bokde ALW, Boomsma DI, Bressan RA, Brodaty H, Buitelaar JK, Cahn W, Caspers S, Cichon S, Crespo-Facorro B, Cox SR, Dannlowski U, Elvsåshagen T, Espeseth T, Falkai PG, Fisher SE, Flor H, Fullerton JM, Garavan H, Gowland PA, Grabe HJ, Hahn T, Heinz A, Hillegers M, Hoare J, Hoekstra PJ, Ikram MA, Jackowski AP, Jansen A, Jönsson EG, Kahn RS, Kircher T, Korgaonkar MS, Krug A, Lemaitre H, Malt UF, Martinot JL, McDonald C, Mitchell PB, Muetzel RL, Murray RM, Nees F, Nenadić I, Oosterlaan J, Ophoff RA, Pan PM, Penninx BWJH, Poustka L, Sachdev PS, Salum GA, Schofield PR, Schumann G, Shaw P, Sim K, Smolka MN, Stein DJ, Trollor JN, van den Berg LH, Veldink JH, Walter H, Westlye LT, Whelan R, White T, Wright MJ, Medland SE, Franke B, Thompson PM, and Hulshoff Pol HE

Subjects
Aging genetics, Brain, Humans, Magnetic Resonance Imaging, Genome-Wide Association Study, Longevity genetics
Abstract

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2022
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3. Genome-wide association study of circulating interleukin 6 levels identifies novel loci.

Author

Ahluwalia TS, Prins BP, Abdollahi M, Armstrong NJ, Aslibekyan S, Bain L, Jefferis B, Baumert J, Beekman M, Ben-Shlomo Y, Bis JC, Mitchell BD, de Geus E, Delgado GE, Marek D, Eriksson J, Kajantie E, Kanoni S, Kemp JP, Lu C, Marioni RE, McLachlan S, Milaneschi Y, Nolte IM, Petrelis AM, Porcu E, Sabater-Lleal M, Naderi E, Seppälä I, Shah T, Singhal G, Standl M, Teumer A, Thalamuthu A, Thiering E, Trompet S, Ballantyne CM, Benjamin EJ, Casas JP, Toben C, Dedoussis G, Deelen J, Durda P, Engmann J, Feitosa MF, Grallert H, Hammarstedt A, Harris SE, Homuth G, Hottenga JJ, Jalkanen S, Jamshidi Y, Jawahar MC, Jess T, Kivimaki M, Kleber ME, Lahti J, Liu Y, Marques-Vidal P, Mellström D, Mooijaart SP, Müller-Nurasyid M, Penninx B, Revez JA, Rossing P, Räikkönen K, Sattar N, Scharnagl H, Sennblad B, Silveira A, Pourcain BS, Timpson NJ, Trollor J, van Dongen J, Van Heemst D, Visvikis-Siest S, Vollenweider P, Völker U, Waldenberger M, Willemsen G, Zabaneh D, Morris RW, Arnett DK, Baune BT, Boomsma DI, Chang YC, Deary IJ, Deloukas P, Eriksson JG, Evans DM, Ferreira MA, Gaunt T, Gudnason V, Hamsten A, Heinrich J, Hingorani A, Humphries SE, Jukema JW, Koenig W, Kumari M, Kutalik Z, Lawlor DA, Lehtimäki T, März W, Mather KA, Naitza S, Nauck M, Ohlsson C, Price JF, Raitakari O, Rice K, Sachdev PS, Slagboom E, Sørensen TIA, Spector T, Stacey D, Stathopoulou MG, Tanaka T, Wannamethee SG, Whincup P, Rotter JI, Dehghan A, Boerwinkle E, Psaty BM, Snieder H, and Alizadeh BZ

Subjects
Cohort Studies, Gene Expression Regulation, Genetic Loci, Genetic Predisposition to Disease, Humans, Interleukin-6 blood, Polymorphism, Single Nucleotide, White People genetics, Genome-Wide Association Study, HLA-DRB1 Chains genetics, Interleukin 1 Receptor Antagonist Protein genetics, Interleukin-1 genetics, Interleukin-6 genetics, Receptors, Interleukin-6 genetics
Abstract

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology., (© The Author(s) 2021. Published by Oxford University Press.)

Published
2021
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4. Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders.

Author

Nabais MF, Laws SM, Lin T, Vallerga CL, Armstrong NJ, Blair IP, Kwok JB, Mather KA, Mellick GD, Sachdev PS, Wallace L, Henders AK, Zwamborn RAJ, Hop PJ, Lunnon K, Pishva E, Roubroeks JAY, Soininen H, Tsolaki M, Mecocci P, Lovestone S, Kłoszewska I, Vellas B, Furlong S, Garton FC, Henderson RD, Mathers S, McCombe PA, Needham M, Ngo ST, Nicholson G, Pamphlett R, Rowe DB, Steyn FJ, Williams KL, Anderson TJ, Bentley SR, Dalrymple-Alford J, Fowder J, Gratten J, Halliday G, Hickie IB, Kennedy M, Lewis SJG, Montgomery GW, Pearson J, Pitcher TL, Silburn P, Zhang F, Visscher PM, Yang J, Stevenson AJ, Hillary RF, Marioni RE, Harris SE, Deary IJ, Jones AR, Shatunov A, Iacoangeli A, van Rheenen W, van den Berg LH, Shaw PJ, Shaw CE, Morrison KE, Al-Chalabi A, Veldink JH, Hannon E, Mill J, Wray NR, and McRae AF

Subjects
Alleles, Biomarkers, Blood Cells metabolism, Case-Control Studies, Disease Susceptibility, Gene Expression Profiling, Genetic Loci, Genetic Predisposition to Disease, Humans, Neurodegenerative Diseases metabolism, DNA Methylation, Epigenesis, Genetic, Genome-Wide Association Study, Neurodegenerative Diseases etiology
Abstract

Background: People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease., Results: We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson's disease (and none with Alzheimer's disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights., Conclusions: We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.

Published
2021
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5. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Author

Hofer E, Roshchupkin GV, Adams HHH, Knol MJ, Lin H, Li S, Zare H, Ahmad S, Armstrong NJ, Satizabal CL, Bernard M, Bis JC, Gillespie NA, Luciano M, Mishra A, Scholz M, Teumer A, Xia R, Jian X, Mosley TH, Saba Y, Pirpamer L, Seiler S, Becker JT, Carmichael O, Rotter JI, Psaty BM, Lopez OL, Amin N, van der Lee SJ, Yang Q, Himali JJ, Maillard P, Beiser AS, DeCarli C, Karama S, Lewis L, Harris M, Bastin ME, Deary IJ, Veronica Witte A, Beyer F, Loeffler M, Mather KA, Schofield PR, Thalamuthu A, Kwok JB, Wright MJ, Ames D, Trollor J, Jiang J, Brodaty H, Wen W, Vernooij MW, Hofman A, Uitterlinden AG, Niessen WJ, Wittfeld K, Bülow R, Völker U, Pausova Z, Bruce Pike G, Maingault S, Crivello F, Tzourio C, Amouyel P, Mazoyer B, Neale MC, Franz CE, Lyons MJ, Panizzon MS, Andreassen OA, Dale AM, Logue M, Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, Lind PA, Pizzagalli F, Stein JL, Thompson PM, Medland SE, Sachdev PS, Kremen WS, Wardlaw JM, Villringer A, van Duijn CM, Grabe HJ, Longstreth WT Jr, Fornage M, Paus T, Debette S, Ikram MA, Schmidt H, Schmidt R, and Seshadri S

Subjects
Adult, Aged, Aged, 80 and over, Chromosome Structures, Cognition, Female, Genomics, Humans, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Aging genetics, Brain, Genome-Wide Association Study, Mental Disorders genetics, Neurodegenerative Diseases genetics
Abstract

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.

Published
2020
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6. Genetic architecture of subcortical brain structures in 38,851 individuals.

Author

Satizabal CL, Adams HHH, Hibar DP, White CC, Knol MJ, Stein JL, Scholz M, Sargurupremraj M, Jahanshad N, Roshchupkin GV, Smith AV, Bis JC, Jian X, Luciano M, Hofer E, Teumer A, van der Lee SJ, Yang J, Yanek LR, Lee TV, Li S, Hu Y, Koh JY, Eicher JD, Desrivières S, Arias-Vasquez A, Chauhan G, Athanasiu L, Rentería ME, Kim S, Hoehn D, Armstrong NJ, Chen Q, Holmes AJ, den Braber A, Kloszewska I, Andersson M, Espeseth T, Grimm O, Abramovic L, Alhusaini S, Milaneschi Y, Papmeyer M, Axelsson T, Ehrlich S, Roiz-Santiañez R, Kraemer B, Håberg AK, Jones HJ, Pike GB, Stein DJ, Stevens A, Bralten J, Vernooij MW, Harris TB, Filippi I, Witte AV, Guadalupe T, Wittfeld K, Mosley TH, Becker JT, Doan NT, Hagenaars SP, Saba Y, Cuellar-Partida G, Amin N, Hilal S, Nho K, Mirza-Schreiber N, Arfanakis K, Becker DM, Ames D, Goldman AL, Lee PH, Boomsma DI, Lovestone S, Giddaluru S, Le Hellard S, Mattheisen M, Bohlken MM, Kasperaviciute D, Schmaal L, Lawrie SM, Agartz I, Walton E, Tordesillas-Gutierrez D, Davies GE, Shin J, Ipser JC, Vinke LN, Hoogman M, Jia T, Burkhardt R, Klein M, Crivello F, Janowitz D, Carmichael O, Haukvik UK, Aribisala BS, Schmidt H, Strike LT, Cheng CY, Risacher SL, Pütz B, Fleischman DA, Assareh AA, Mattay VS, Buckner RL, Mecocci P, Dale AM, Cichon S, Boks MP, Matarin M, Penninx BWJH, Calhoun VD, Chakravarty MM, Marquand AF, Macare C, Kharabian Masouleh S, Oosterlaan J, Amouyel P, Hegenscheid K, Rotter JI, Schork AJ, Liewald DCM, de Zubicaray GI, Wong TY, Shen L, Sämann PG, Brodaty H, Roffman JL, de Geus EJC, Tsolaki M, Erk S, van Eijk KR, Cavalleri GL, van der Wee NJA, McIntosh AM, Gollub RL, Bulayeva KB, Bernard M, Richards JS, Himali JJ, Loeffler M, Rommelse N, Hoffmann W, Westlye LT, Valdés Hernández MC, Hansell NK, van Erp TGM, Wolf C, Kwok JBJ, Vellas B, Heinz A, Olde Loohuis LM, Delanty N, Ho BC, Ching CRK, Shumskaya E, Singh B, Hofman A, van der Meer D, Homuth G, Psaty BM, Bastin ME, Montgomery GW, Foroud TM, Reppermund S, Hottenga JJ, Simmons A, Meyer-Lindenberg A, Cahn W, Whelan CD, van Donkelaar MMJ, Yang Q, Hosten N, Green RC, Thalamuthu A, Mohnke S, Hulshoff Pol HE, Lin H, Jack CR Jr, Schofield PR, Mühleisen TW, Maillard P, Potkin SG, Wen W, Fletcher E, Toga AW, Gruber O, Huentelman M, Davey Smith G, Launer LJ, Nyberg L, Jönsson EG, Crespo-Facorro B, Koen N, Greve DN, Uitterlinden AG, Weinberger DR, Steen VM, Fedko IO, Groenewold NA, Niessen WJ, Toro R, Tzourio C, Longstreth WT Jr, Ikram MK, Smoller JW, van Tol MJ, Sussmann JE, Paus T, Lemaître H, Schroeter ML, Mazoyer B, Andreassen OA, Holsboer F, Depondt C, Veltman DJ, Turner JA, Pausova Z, Schumann G, van Rooij D, Djurovic S, Deary IJ, McMahon KL, Müller-Myhsok B, Brouwer RM, Soininen H, Pandolfo M, Wassink TH, Cheung JW, Wolfers T, Martinot JL, Zwiers MP, Nauck M, Melle I, Martin NG, Kanai R, Westman E, Kahn RS, Sisodiya SM, White T, Saremi A, van Bokhoven H, Brunner HG, Völzke H, Wright MJ, van 't Ent D, Nöthen MM, Ophoff RA, Buitelaar JK, Fernández G, Sachdev PS, Rietschel M, van Haren NEM, Fisher SE, Beiser AS, Francks C, Saykin AJ, Mather KA, Romanczuk-Seiferth N, Hartman CA, DeStefano AL, Heslenfeld DJ, Weiner MW, Walter H, Hoekstra PJ, Nyquist PA, Franke B, Bennett DA, Grabe HJ, Johnson AD, Chen C, van Duijn CM, Lopez OL, Fornage M, Wardlaw JM, Schmidt R, DeCarli C, De Jager PL, Villringer A, Debette S, Gudnason V, Medland SE, Shulman JM, Thompson PM, Seshadri S, and Ikram MA

Subjects
Adult, Aged, Animals, Cohort Studies, Drosophila melanogaster genetics, Drosophila melanogaster growth & development, Humans, Magnetic Resonance Imaging, Middle Aged, Organ Size, Brain anatomy & histology, Brain metabolism, Drosophila melanogaster metabolism, Genetic Variation, Genome-Wide Association Study, Neurodevelopmental Disorders genetics, Neurodevelopmental Disorders pathology
Abstract

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.

Published
2019
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7. Exceptional Longevity and Polygenic Risk for Cardiovascular Health.

Author

Revelas M, Thalamuthu A, Oldmeadow C, Evans TJ, Armstrong NJ, Riveros C, Kwok JB, Schofield PR, Brodaty H, Scott RJ, Attia JR, Sachdev PS, and Mather KA

Subjects
Aged, Aged, 80 and over, Cardiovascular Diseases blood, Cholesterol, HDL blood, Female, Humans, Male, Middle Aged, Multifactorial Inheritance, Risk Assessment, Triglycerides blood, Cardiovascular Diseases genetics, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Longevity
Abstract

Studies investigating exceptionally long-lived (ELL) individuals, including genetic studies, have linked cardiovascular-related pathways, particularly lipid and cholesterol homeostasis, with longevity. This study explored the genetic profiles of ELL individuals (cases: n = 294, 95⁻106 years; controls: n = 1105, 55⁻65 years) by assessing their polygenic risk scores (PRS) based on a genome wide association study (GWAS) threshold of p < 5 × 10 -5 . PRS were constructed using GWAS summary data from two exceptional longevity (EL) analyses and eight cardiovascular-related risk factors (lipids) and disease (myocardial infarction, coronary artery disease, stroke) analyses. A higher genetic risk for exceptional longevity (EL) was significantly associated with longevity in our sample (odds ratio (OR) = 1.19⁻1.20, p = 0.00804 and 0.00758, respectively). Two cardiovascular health PRS were nominally significant with longevity (HDL cholesterol, triglycerides), with higher PRS associated with EL, but these relationships did not survive correction for multiple testing. In conclusion, ELL individuals did not have significantly lower polygenic risk for the majority of the investigated cardiovascular health traits. Future work in larger cohorts is required to further explore the role of cardiovascular-related genetic variants in EL., Competing Interests: The authors declare no conflict of interest.

Published
2019
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8. Novel genetic loci underlying human intracranial volume identified through genome-wide association.

Author

Adams HH, Hibar DP, Chouraki V, Stein JL, Nyquist PA, Rentería ME, Trompet S, Arias-Vasquez A, Seshadri S, Desrivières S, Beecham AH, Jahanshad N, Wittfeld K, Van der Lee SJ, Abramovic L, Alhusaini S, Amin N, Andersson M, Arfanakis K, Aribisala BS, Armstrong NJ, Athanasiu L, Axelsson T, Beiser A, Bernard M, Bis JC, Blanken LM, Blanton SH, Bohlken MM, Boks MP, Bralten J, Brickman AM, Carmichael O, Chakravarty MM, Chauhan G, Chen Q, Ching CR, Cuellar-Partida G, Braber AD, Doan NT, Ehrlich S, Filippi I, Ge T, Giddaluru S, Goldman AL, Gottesman RF, Greven CU, Grimm O, Griswold ME, Guadalupe T, Hass J, Haukvik UK, Hilal S, Hofer E, Hoehn D, Holmes AJ, Hoogman M, Janowitz D, Jia T, Kasperaviciute D, Kim S, Klein M, Kraemer B, Lee PH, Liao J, Liewald DC, Lopez LM, Luciano M, Macare C, Marquand A, Matarin M, Mather KA, Mattheisen M, Mazoyer B, McKay DR, McWhirter R, Milaneschi Y, Mirza-Schreiber N, Muetzel RL, Maniega SM, Nho K, Nugent AC, Loohuis LM, Oosterlaan J, Papmeyer M, Pappa I, Pirpamer L, Pudas S, Pütz B, Rajan KB, Ramasamy A, Richards JS, Risacher SL, Roiz-Santiañez R, Rommelse N, Rose EJ, Royle NA, Rundek T, Sämann PG, Satizabal CL, Schmaal L, Schork AJ, Shen L, Shin J, Shumskaya E, Smith AV, Sprooten E, Strike LT, Teumer A, Thomson R, Tordesillas-Gutierrez D, Toro R, Trabzuni D, Vaidya D, Van der Grond J, Van der Meer D, Van Donkelaar MM, Van Eijk KR, Van Erp TG, Van Rooij D, Walton E, Westlye LT, Whelan CD, Windham BG, Winkler AM, Woldehawariat G, Wolf C, Wolfers T, Xu B, Yanek LR, Yang J, Zijdenbos A, Zwiers MP, Agartz I, Aggarwal NT, Almasy L, Ames D, Amouyel P, Andreassen OA, Arepalli S, Assareh AA, Barral S, Bastin ME, Becker DM, Becker JT, Bennett DA, Blangero J, van Bokhoven H, Boomsma DI, Brodaty H, Brouwer RM, Brunner HG, Buckner RL, Buitelaar JK, Bulayeva KB, Cahn W, Calhoun VD, Cannon DM, Cavalleri GL, Chen C, Cheng CY, Cichon S, Cookson MR, Corvin A, Crespo-Facorro B, Curran JE, Czisch M, Dale AM, Davies GE, De Geus EJ, De Jager PL, de Zubicaray GI, Delanty N, Depondt C, DeStefano AL, Dillman A, Djurovic S, Donohoe G, Drevets WC, Duggirala R, Dyer TD, Erk S, Espeseth T, Evans DA, Fedko IO, Fernández G, Ferrucci L, Fisher SE, Fleischman DA, Ford I, Foroud TM, Fox PT, Francks C, Fukunaga M, Gibbs JR, Glahn DC, Gollub RL, Göring HH, Grabe HJ, Green RC, Gruber O, Gudnason V, Guelfi S, Hansell NK, Hardy J, Hartman CA, Hashimoto R, Hegenscheid K, Heinz A, Le Hellard S, Hernandez DG, Heslenfeld DJ, Ho BC, Hoekstra PJ, Hoffmann W, Hofman A, Holsboer F, Homuth G, Hosten N, Hottenga JJ, Hulshoff Pol HE, Ikeda M, Ikram MK, Jack CR Jr, Jenkinson M, Johnson R, Jönsson EG, Jukema JW, Kahn RS, Kanai R, Kloszewska I, Knopman DS, Kochunov P, Kwok JB, Lawrie SM, Lemaître H, Liu X, Longo DL, Longstreth WT Jr, Lopez OL, Lovestone S, Martinez O, Martinot JL, Mattay VS, McDonald C, McIntosh AM, McMahon KL, McMahon FJ, Mecocci P, Melle I, Meyer-Lindenberg A, Mohnke S, Montgomery GW, Morris DW, Mosley TH, Mühleisen TW, Müller-Myhsok B, Nalls MA, Nauck M, Nichols TE, Niessen WJ, Nöthen MM, Nyberg L, Ohi K, Olvera RL, Ophoff RA, Pandolfo M, Paus T, Pausova Z, Penninx BW, Pike GB, Potkin SG, Psaty BM, Reppermund S, Rietschel M, Roffman JL, Romanczuk-Seiferth N, Rotter JI, Ryten M, Sacco RL, Sachdev PS, Saykin AJ, Schmidt R, Schofield PR, Sigurdsson S, Simmons A, Singleton A, Sisodiya SM, Smith C, Smoller JW, Soininen H, Srikanth V, Steen VM, Stott DJ, Sussmann JE, Thalamuthu A, Tiemeier H, Toga AW, Traynor BJ, Troncoso J, Turner JA, Tzourio C, Uitterlinden AG, Hernández MC, Van der Brug M, Van der Lugt A, Van der Wee NJ, Van Duijn CM, Van Haren NE, Van T Ent D, Van Tol MJ, Vardarajan BN, Veltman DJ, Vernooij MW, Völzke H, Walter H, Wardlaw JM, Wassink TH, Weale ME, Weinberger DR, Weiner MW, Wen W, Westman E, White T, Wong TY, Wright CB, Zielke HR, Zonderman AB, Deary IJ, DeCarli C, Schmidt H, Martin NG, De Craen AJ, Wright MJ, Launer LJ, Schumann G, Fornage M, Franke B, Debette S, Medland SE, Ikram MA, and Thompson PM

Subjects
Brain growth & development, Brain pathology, Genetic Loci genetics, Humans, Oncogene Protein v-akt genetics, Parkinson Disease genetics, Phenotype, Phosphatidylinositol 3-Kinases genetics, White People, Cognition physiology, Genetic Predisposition to Disease, Genome-Wide Association Study methods, Polymorphism, Single Nucleotide genetics
Abstract

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρ genetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N combined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Published
2016
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9. Common genetic variants influence human subcortical brain structures.

Author

Hibar DP, Stein JL, Renteria ME, Arias-Vasquez A, Desrivières S, Jahanshad N, Toro R, Wittfeld K, Abramovic L, Andersson M, Aribisala BS, Armstrong NJ, Bernard M, Bohlken MM, Boks MP, Bralten J, Brown AA, Chakravarty MM, Chen Q, Ching CR, Cuellar-Partida G, den Braber A, Giddaluru S, Goldman AL, Grimm O, Guadalupe T, Hass J, Woldehawariat G, Holmes AJ, Hoogman M, Janowitz D, Jia T, Kim S, Klein M, Kraemer B, Lee PH, Olde Loohuis LM, Luciano M, Macare C, Mather KA, Mattheisen M, Milaneschi Y, Nho K, Papmeyer M, Ramasamy A, Risacher SL, Roiz-Santiañez R, Rose EJ, Salami A, Sämann PG, Schmaal L, Schork AJ, Shin J, Strike LT, Teumer A, van Donkelaar MM, van Eijk KR, Walters RK, Westlye LT, Whelan CD, Winkler AM, Zwiers MP, Alhusaini S, Athanasiu L, Ehrlich S, Hakobjan MM, Hartberg CB, Haukvik UK, Heister AJ, Hoehn D, Kasperaviciute D, Liewald DC, Lopez LM, Makkinje RR, Matarin M, Naber MA, McKay DR, Needham M, Nugent AC, Pütz B, Royle NA, Shen L, Sprooten E, Trabzuni D, van der Marel SS, van Hulzen KJ, Walton E, Wolf C, Almasy L, Ames D, Arepalli S, Assareh AA, Bastin ME, Brodaty H, Bulayeva KB, Carless MA, Cichon S, Corvin A, Curran JE, Czisch M, de Zubicaray GI, Dillman A, Duggirala R, Dyer TD, Erk S, Fedko IO, Ferrucci L, Foroud TM, Fox PT, Fukunaga M, Gibbs JR, Göring HH, Green RC, Guelfi S, Hansell NK, Hartman CA, Hegenscheid K, Heinz A, Hernandez DG, Heslenfeld DJ, Hoekstra PJ, Holsboer F, Homuth G, Hottenga JJ, Ikeda M, Jack CR Jr, Jenkinson M, Johnson R, Kanai R, Keil M, Kent JW Jr, Kochunov P, Kwok JB, Lawrie SM, Liu X, Longo DL, McMahon KL, Meisenzahl E, Melle I, Mohnke S, Montgomery GW, Mostert JC, Mühleisen TW, Nalls MA, Nichols TE, Nilsson LG, Nöthen MM, Ohi K, Olvera RL, Perez-Iglesias R, Pike GB, Potkin SG, Reinvang I, Reppermund S, Rietschel M, Romanczuk-Seiferth N, Rosen GD, Rujescu D, Schnell K, Schofield PR, Smith C, Steen VM, Sussmann JE, Thalamuthu A, Toga AW, Traynor BJ, Troncoso J, Turner JA, Valdés Hernández MC, van 't Ent D, van der Brug M, van der Wee NJ, van Tol MJ, Veltman DJ, Wassink TH, Westman E, Zielke RH, Zonderman AB, Ashbrook DG, Hager R, Lu L, McMahon FJ, Morris DW, Williams RW, Brunner HG, Buckner RL, Buitelaar JK, Cahn W, Calhoun VD, Cavalleri GL, Crespo-Facorro B, Dale AM, Davies GE, Delanty N, Depondt C, Djurovic S, Drevets WC, Espeseth T, Gollub RL, Ho BC, Hoffmann W, Hosten N, Kahn RS, Le Hellard S, Meyer-Lindenberg A, Müller-Myhsok B, Nauck M, Nyberg L, Pandolfo M, Penninx BW, Roffman JL, Sisodiya SM, Smoller JW, van Bokhoven H, van Haren NE, Völzke H, Walter H, Weiner MW, Wen W, White T, Agartz I, Andreassen OA, Blangero J, Boomsma DI, Brouwer RM, Cannon DM, Cookson MR, de Geus EJ, Deary IJ, Donohoe G, Fernández G, Fisher SE, Francks C, Glahn DC, Grabe HJ, Gruber O, Hardy J, Hashimoto R, Hulshoff Pol HE, Jönsson EG, Kloszewska I, Lovestone S, Mattay VS, Mecocci P, McDonald C, McIntosh AM, Ophoff RA, Paus T, Pausova Z, Ryten M, Sachdev PS, Saykin AJ, Simmons A, Singleton A, Soininen H, Wardlaw JM, Weale ME, Weinberger DR, Adams HH, Launer LJ, Seiler S, Schmidt R, Chauhan G, Satizabal CL, Becker JT, Yanek L, van der Lee SJ, Ebling M, Fischl B, Longstreth WT Jr, Greve D, Schmidt H, Nyquist P, Vinke LN, van Duijn CM, Xue L, Mazoyer B, Bis JC, Gudnason V, Seshadri S, Ikram MA, Martin NG, Wright MJ, Schumann G, Franke B, Thompson PM, and Medland SE

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Aging genetics, Apoptosis genetics, Caudate Nucleus anatomy & histology, Child, Female, Gene Expression Regulation, Developmental genetics, Genetic Loci genetics, Hippocampus anatomy & histology, Humans, Magnetic Resonance Imaging, Male, Membrane Proteins genetics, Middle Aged, Organ Size genetics, Putamen anatomy & histology, Sex Characteristics, Skull anatomy & histology, Young Adult, Brain anatomy & histology, Genetic Variation genetics, Genome-Wide Association Study
Abstract

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Published
2015
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10. Genetics of hand grip strength in mid to late life.

Author

Chan JP, Thalamuthu A, Oldmeadow C, Armstrong NJ, Holliday EG, McEvoy M, Kwok JB, Assareh AA, Peel R, Hancock SJ, Reppermund S, Menant J, Trollor JN, Brodaty H, Schofield PR, Attia JR, Sachdev PS, Scott RJ, and Mather KA

Subjects
Age Factors, Aged, Aged, 80 and over, Australia, Cohort Studies, Female, Genotype, Humans, Linear Models, Male, Middle Aged, Genome-Wide Association Study, Hand Strength physiology, Polymorphism, Single Nucleotide genetics
Abstract

Hand grip strength (GS) is a predictor of mortality in older adults and is moderately to highly heritable, but no genetic variants have been consistently identified. We aimed to identify single nucleotide polymorphisms (SNPs) associated with GS in middle-aged to older adults using a genome-wide association study (GWAS). GS was measured using handheld dynamometry in community-dwelling men and women aged 55-85 from the Hunter Community Study (HCS, N = 2088) and the Sydney Memory and Ageing Study (Sydney MAS, N = 541). Genotyping was undertaken using Affymetrix microarrays with imputation to HapMap2. Analyses were performed using linear regression. No genome-wide significant results were observed in HCS nor were any of the top signals replicated in Sydney MAS. Gene-based analyses in HCS identified two significant genes (ZNF295, C2CD2), but these results were not replicated in Sydney MAS. One out of eight SNPs previously associated with GS, rs550942, located near the CNTF gene, was significantly associated with GS (p = 0.005) in the HCS cohort only. Study differences may explain the lack of consistent results between the studies, including the smaller sample size of the Sydney MAS cohort. Our modest sample size also had limited power to identify variants of small effect. Our results suggest that similar to various other complex traits, many genetic variants of small effect size may influence GS. Future GWAS using larger samples and consistent measures may prove more fruitful at identifying genetic contributors for GS in middle-aged to older adults.

Published
2015
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11. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data.

Author

Thompson PM, Stein JL, Medland SE, Hibar DP, Vasquez AA, Renteria ME, Toro R, Jahanshad N, Schumann G, Franke B, Wright MJ, Martin NG, Agartz I, Alda M, Alhusaini S, Almasy L, Almeida J, Alpert K, Andreasen NC, Andreassen OA, Apostolova LG, Appel K, Armstrong NJ, Aribisala B, Bastin ME, Bauer M, Bearden CE, Bergmann O, Binder EB, Blangero J, Bockholt HJ, Bøen E, Bois C, Boomsma DI, Booth T, Bowman IJ, Bralten J, Brouwer RM, Brunner HG, Brohawn DG, Buckner RL, Buitelaar J, Bulayeva K, Bustillo JR, Calhoun VD, Cannon DM, Cantor RM, Carless MA, Caseras X, Cavalleri GL, Chakravarty MM, Chang KD, Ching CR, Christoforou A, Cichon S, Clark VP, Conrod P, Coppola G, Crespo-Facorro B, Curran JE, Czisch M, Deary IJ, de Geus EJ, den Braber A, Delvecchio G, Depondt C, de Haan L, de Zubicaray GI, Dima D, Dimitrova R, Djurovic S, Dong H, Donohoe G, Duggirala R, Dyer TD, Ehrlich S, Ekman CJ, Elvsåshagen T, Emsell L, Erk S, Espeseth T, Fagerness J, Fears S, Fedko I, Fernández G, Fisher SE, Foroud T, Fox PT, Francks C, Frangou S, Frey EM, Frodl T, Frouin V, Garavan H, Giddaluru S, Glahn DC, Godlewska B, Goldstein RZ, Gollub RL, Grabe HJ, Grimm O, Gruber O, Guadalupe T, Gur RE, Gur RC, Göring HH, Hagenaars S, Hajek T, Hall GB, Hall J, Hardy J, Hartman CA, Hass J, Hatton SN, Haukvik UK, Hegenscheid K, Heinz A, Hickie IB, Ho BC, Hoehn D, Hoekstra PJ, Hollinshead M, Holmes AJ, Homuth G, Hoogman M, Hong LE, Hosten N, Hottenga JJ, Hulshoff Pol HE, Hwang KS, Jack CR Jr, Jenkinson M, Johnston C, Jönsson EG, Kahn RS, Kasperaviciute D, Kelly S, Kim S, Kochunov P, Koenders L, Krämer B, Kwok JB, Lagopoulos J, Laje G, Landen M, Landman BA, Lauriello J, Lawrie SM, Lee PH, Le Hellard S, Lemaître H, Leonardo CD, Li CS, Liberg B, Liewald DC, Liu X, Lopez LM, Loth E, Lourdusamy A, Luciano M, Macciardi F, Machielsen MW, Macqueen GM, Malt UF, Mandl R, Manoach DS, Martinot JL, Matarin M, Mather KA, Mattheisen M, Mattingsdal M, Meyer-Lindenberg A, McDonald C, McIntosh AM, McMahon FJ, McMahon KL, Meisenzahl E, Melle I, Milaneschi Y, Mohnke S, Montgomery GW, Morris DW, Moses EK, Mueller BA, Muñoz Maniega S, Mühleisen TW, Müller-Myhsok B, Mwangi B, Nauck M, Nho K, Nichols TE, Nilsson LG, Nugent AC, Nyberg L, Olvera RL, Oosterlaan J, Ophoff RA, Pandolfo M, Papalampropoulou-Tsiridou M, Papmeyer M, Paus T, Pausova Z, Pearlson GD, Penninx BW, Peterson CP, Pfennig A, Phillips M, Pike GB, Poline JB, Potkin SG, Pütz B, Ramasamy A, Rasmussen J, Rietschel M, Rijpkema M, Risacher SL, Roffman JL, Roiz-Santiañez R, Romanczuk-Seiferth N, Rose EJ, Royle NA, Rujescu D, Ryten M, Sachdev PS, Salami A, Satterthwaite TD, Savitz J, Saykin AJ, Scanlon C, Schmaal L, Schnack HG, Schork AJ, Schulz SC, Schür R, Seidman L, Shen L, Shoemaker JM, Simmons A, Sisodiya SM, Smith C, Smoller JW, Soares JC, Sponheim SR, Sprooten E, Starr JM, Steen VM, Strakowski S, Strike L, Sussmann J, Sämann PG, Teumer A, Toga AW, Tordesillas-Gutierrez D, Trabzuni D, Trost S, Turner J, Van den Heuvel M, van der Wee NJ, van Eijk K, van Erp TG, van Haren NE, van 't Ent D, van Tol MJ, Valdés Hernández MC, Veltman DJ, Versace A, Völzke H, Walker R, Walter H, Wang L, Wardlaw JM, Weale ME, Weiner MW, Wen W, Westlye LT, Whalley HC, Whelan CD, White T, Winkler AM, Wittfeld K, Woldehawariat G, Wolf C, Zilles D, Zwiers MP, Thalamuthu A, Schofield PR, Freimer NB, Lawrence NS, and Drevets W

Subjects
Cooperative Behavior, Humans, Meta-Analysis as Topic, Brain Mapping methods, Genome-Wide Association Study methods, Neuroimaging methods
Abstract

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Published
2014
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12. GWAS for executive function and processing speed suggests involvement of the CADM2 gene

Author

Ibrahim-Verbaas, CA, Bressler, J, Debette, S, Schuur, M, Smith, AV, Bis, JC, Davies, G, Trompet, S, Smith, JA, Wolf, C, Chibnik, LB, Liu, Y, Vitart, V, Kirin, M, Petrovic, K, Polasek, O, Zgaga, L, Fawns-Ritchie, C, Hoffmann, P, Karjalainen, J, Lahti, J, Llewellyn, DJ, Schmidt, CO, Mather, KA, Chouraki, V, Sun, Q, Resnick, SM, Rose, LM, Oldmeadow, C, Stewart, M, Smith, BH, Gudnason, V, Yang, Q, Mirza, SS, Jukema, JW, deJager, PL, Harris, TB, Liewald, DC, Amin, N, Coker, LH, Stegle, O, Lopez, OL, Schmidt, R, Teumer, A, Ford, I, Karbalai, N, Becker, JT, Jonsdottir, MK, Au, R, Fehrmann, RSN, Herms, S, Nalls, M, Zhao, W, Turner, ST, Yaffe, K, Lohman, K, van Swieten, JC, Kardia, SLR, Knopman, DS, Meeks, WM, Heiss, G, Holliday, EG, Schofield, PW, Tanaka, T, Stott, DJ, Wang, J, Ridker, P, Gow, AJ, Pattie, A, Starr, JM, Hocking, LJ, Armstrong, NJ, McLachlan, S, Shulman, JM, Pilling, LC, Eiriksdottir, G, Scott, RJ, Kochan, NA, Palotie, A, Hsieh, Y-C, Eriksson, JG, Penman, A, Gottesman, RF, Oostra, BA, Yu, L, DeStefano, AL, Beiser, A, Garcia, M, Rotter, JI, Nöthen, MM, Hofman, A, Slagboom, PE, Westendorp, RGJ, Buckley, BM, Wolf, PA, Uitterlinden, AG, Psaty, BM, Grabe, HJ, Bandinelli, S, and Chasman, DI

Subjects
Biological Psychology, Clinical and Health Psychology, Psychology, Human Genome, Neurosciences, Genetics, Clinical Research, Aging, Aetiology, 2.1 Biological and endogenous factors, Aged, Aged, 80 and over, Cell Adhesion Molecules, Cognition, Cohort Studies, Executive Function, Female, Genetic Association Studies, Genetic Variation, Genome-Wide Association Study, Genomics, Humans, Introns, Male, Middle Aged, Neuropsychological Tests, Polymorphism, Single Nucleotide, White People, gamma-Aminobutyric Acid, Generation Scotland, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.

Published
2016

13. CCR5-Δ32 genotype does not improve predictive value of IL28B polymorphisms for treatment response in chronic HCV infection

Author

V. Suppiah, Jacob Nattermann, Elizabeth E. Powell, Antonina Smedile, M. Michalk, Mandvi Bharadwaj, Sherie Smith, Shona Fletcher, Martin Weltman, Julie R. Jonsson, Elizabeth Snape, David Sheridan, Gregory J. Dore, Patrick McClure, Richard Norris, Helen Barrie, M.L. Abate, David R. Booth, Dianne How-Chow, Thomas Berg, Jacob George, Jason Grebely, G. J. Stewart, Stephen M. Riordan, Margaret Bassendine, Sacha Stelzer-Braid, Golo Ahlenstiel, William L. Irving, Ulrich Spengler, Tobias Mueller, Nicola J. Armstrong, Vincenzo Fragomeli, Barbara Malik, Kate S. O'Connor, Tanya L. Applegate, Gail V. Matthews, Suppiah, V, Armstrong, NJ, O'Connor, KS, Berg, T, Weltman, M, Abate, ML, Spengler, U, Bassendine, M, Dore, GJ, Irving, WL, Powell, E, Nattermann, J, Mueller, T, Riordan, S, Stewart, GJ, George, J, Booth, DR, Ahlenstiel, G, and International Hepatitis C Genetics Consortium (IHCGC)

Subjects
Male, Oncology, viruses, IL28B, Genome-wide association study, medicine.disease_cause, Cohort Studies, chemistry.chemical_compound, Interferon, Genotype, Genetics (clinical), Sequence Deletion, virus diseases, Middle Aged, Prognosis, Europe, Treatment Outcome, HCV, Cohort, Drug Therapy, Combination, Female, medicine.drug, Adult, medicine.medical_specialty, SVR, Receptors, CCR5, Hepatitis C virus, Immunology, Alpha interferon, Context (language use), Biology, Antiviral Agents, Polymorphism, Single Nucleotide, White People, Internal medicine, Ribavirin, Genetics, medicine, Humans, Base Sequence, Interleukins, Australia, Interferon-alpha, Epistasis, Genetic, Hepatitis C, Chronic, Cross-Sectional Studies, chemistry, Multivariate Analysis, Interferons, CCR5
Abstract

IL28B polymorphisms strongly predict spontaneous and treatment-induced clearance of hepatitis C virus (HCV) infection. A recent study proposed a 32-base pair deletion in the CC-chemokine receptor 5 (CCR5) gene (CCR5-D32) interacting with the IL28B polymorphisms to influence spontaneous HCV clearance. The aim of this study was to clarify the role of CCR5-D32 in treatmentinduced clearance of chronic hepatitis C (CHC). A cross-sectional cohort of 813 Caucasian patients with CHC genotype 1 (365 responders and 448 non-responders) who had received standard of care dual therapy with interferon (IFN)-a and ribavirin (RBV) was genotyped for the CCR5-D32 and IL28B polymorphisms to examine their interaction with respect to treatment response. CCR5-D32 did not influence treatment-induced recovery to IFN-a/RBV in CHC, and did not improve prediction of sustained virological response in the context of the IL28B polymorphisms in a multivariate model. CCR5-D32 homozygotes were significantly more frequent in those with CHC than healthy controls in the European cohorts (2.9% vs 0.4%, Po0.0001), but not in Australians of European ancestry. In conclusion, CCR5-D32 does not influence treatment response in the context of IL28B polymorphisms. Although CCR5-D32 may affect viral clearance within closely controlled geographical and genetic environments, we found no effect in larger cohorts treated with dual therapy. Refereed/Peer-reviewed

Published
2013

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