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Knol MJ, Poot RA, Evans TE, Satizabal CL, Mishra A, Sargurupremraj M, van der Auwera S, Duperron MG, Jian X, Hostettler IC, van Dam-Nolen DHK, Lamballais S, Pawlak MA, Lewis CE, Carrion-Castillo A, van Erp TGM, Reinbold CS, Shin J, Scholz M, Håberg AK, Kämpe A, Li GHY, Avinun R, Atkins JR, Hsu FC, Amod AR, Lam M, Tsuchida A, Teunissen MWA, Aygün N, Patel Y, Liang D, Beiser AS, Beyer F, Bis JC, Bos D, Bryan RN, Bülow R, Caspers S, Catheline G, Cecil CAM, Dalvie S, Dartigues JF, DeCarli C, Enlund-Cerullo M, Ford JM, Franke B, Freedman BI, Friedrich N, Green MJ, Haworth S, Helmer C, Hoffmann P, Homuth G, Ikram MK, Jack CR, Jahanshad N, Jockwitz C, Kamatani Y, Knodt AR, Li S, Lim K, Longstreth WT, Macciardi F, Mäkitie O, Mazoyer B, Medland SE, Miyamoto S, Moebus S, Mosley TH, Muetzel R, Mühleisen TW, Nagata M, Nakahara S, Palmer ND, Pausova Z, Preda A, Quidé Y, Reay WR, Roshchupkin GV, Schmidt R, Schreiner PJ, Setoh K, Shapland CY, Sidney S, St Pourcain B, Stein JL, Tabara Y, Teumer A, Uhlmann A, van der Lugt A, Vernooij MW, Werring DJ, Windham BG, Witte AV, Wittfeld K, Yang Q, Yoshida K, Brunner HG, Le Grand Q, Sim K, Stein DJ, Bowden DW, Cairns MJ, Hariri AR, Cheung CL, Andersson S, Villringer A, Paus T, Cichon S, Calhoun VD, Crivello F, Launer LJ, White T, Koudstaal PJ, Houlden H, Fornage M, Matsuda F, Grabe HJ, Ikram MA, Debette S, Thompson PM, Seshadri S, Adams HHH. Genetic variants for head size share genes and pathways with cancer. Cell Rep Med 2024; 5:101529. [PMID: 38703765 PMCID: PMC11148644 DOI: 10.1016/j.xcrm.2024.101529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 09/18/2023] [Accepted: 04/04/2024] [Indexed: 05/06/2024]
Abstract
The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.
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Medina-Gomez C, Mullin BH, Chesi A, Prijatelj V, Kemp JP, Shochat-Carvalho C, Trajanoska K, Wang C, Joro R, Evans TE, Schraut KE, Li-Gao R, Ahluwalia TS, Zillikens MC, Zhu K, Mook-Kanamori DO, Evans DS, Nethander M, Knol MJ, Thorleifsson G, Prokic I, Zemel B, Broer L, McGuigan FE, van Schoor NM, Reppe S, Pawlak MA, Ralston SH, van der Velde N, Lorentzon M, Stefansson K, Adams HHH, Wilson SG, Ikram MA, Walsh JP, Lakka TA, Gautvik KM, Wilson JF, Orwoll ES, van Duijn CM, Bønnelykke K, Uitterlinden AG, Styrkársdóttir U, Akesson KE, Spector TD, Tobias JH, Ohlsson C, Felix JF, Bisgaard H, Grant SFA, Richards JB, Evans DM, van der Eerden B, van de Peppel J, Ackert-Bicknell C, Karasik D, Kague E, Rivadeneira F. Bone mineral density loci specific to the skull portray potential pleiotropic effects on craniosynostosis. Commun Biol 2023; 6:691. [PMID: 37402774 PMCID: PMC10319806 DOI: 10.1038/s42003-023-04869-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 04/25/2023] [Indexed: 07/06/2023] Open
Abstract
Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of key genes in bone biology, particularly to intramembranous ossification, not captured at other skeletal sites. We perform a genome-wide association meta-analysis (n ~ 43,800) of SK-BMD, identifying 59 loci, collectively explaining 12.5% of the trait variance. Association signals cluster within gene-sets involved in skeletal development and osteoporosis. Among the four novel loci (ZIC1, PRKAR1A, AZIN1/ATP6V1C1, GLRX3), there are factors implicated in intramembranous ossification and as we show, inherent to craniosynostosis processes. Functional follow-up in zebrafish confirms the importance of ZIC1 on cranial suture patterning. Likewise, we observe abnormal cranial bone initiation that culminates in ectopic sutures and reduced BMD in mosaic atp6v1c1 knockouts. Mosaic prkar1a knockouts present asymmetric bone growth and, conversely, elevated BMD. In light of this evidence linking SK-BMD loci to craniofacial abnormalities, our study provides new insight into the pathophysiology, diagnosis and treatment of skeletal diseases.
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Grants
- UL1 TR000128 NCATS NIH HHS
- U01 AG042124 NIA NIH HHS
- U01 AG042145 NIA NIH HHS
- U01 AG042168 NIA NIH HHS
- U01 AG042140 NIA NIH HHS
- U24 AG051129 NIA NIH HHS
- R01 AR051124 NIAMS NIH HHS
- U01 AG027810 NIA NIH HHS
- U01 AR066160 NIAMS NIH HHS
- MC_UU_00007/10 Medical Research Council
- R01 HD058886 NICHD NIH HHS
- RC2 AR058973 NIAMS NIH HHS
- Wellcome Trust
- M01 RR000240 NCRR NIH HHS
- U01 AG042143 NIA NIH HHS
- UL1 RR026314 NCRR NIH HHS
- U01 AG042139 NIA NIH HHS
- EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
- European Cooperation in Science and Technology (COST)
- Wellcome Trust (Wellcome)
- Department of Health | National Health and Medical Research Council (NHMRC)
- U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
- ZonMw (Netherlands Organisation for Health Research and Development)
- EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013))
- Vetenskapsrådet (Swedish Research Council)
- U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
- Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research)
- NCHA (Netherlands Consortium Healthy Ageing) Leiden/ Rotterdam; Dutch Ministry of Economic Affairs, Agriculture and Innovation (project KB-15-004-003); the Research Institute for Diseases in the Elderly [Netherlands] (014-93-015; RIDE2)
- Clinical and Translational Research Center (5-MO1-RR-000240 and UL1 RR-026314); U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) GrantRecipient="Au50"
- European Commission FP6 STRP grant number 018947 (LSHG-CT-2006-01947); Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Netherlands Brain Foundation (project number F2013(1)-28) GrantRecipient="Au40"
- Chief Scientist Office of the Scottish Government (CZB/4/276, CZB/4/710) GrantRecipient="Au28"
- Chief Scientist Office of the Scottish Government (CZB/4/276, CZB/4/710) GrantRecipient="Au38"
- The Pawsey Supercomputing Centre (with Funding from the Australian Government and the Government of Western Australia; PG 16/0162, PG 17/director2025) GrantRecipient="Au45”
- European Commission (EC)
- U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS);NIH Roadmap for Medical Research [USA]: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128 GrantRecipient="Au39”
- Versus Arthritis [USA] 21937 GrantRecipient="Au57”
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Graham SE, Clarke SL, Wu KHH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, Locke AE, Marouli E, Hwang MY, Han S, Narita A, Choudhury A, Bentley AR, Ekoru K, Verma A, Trivedi B, Martin HC, Hunt KA, Hui Q, Klarin D, Zhu X, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Ruotsalainen SE, Havulinna AS, Veturi Y, Feng Q, Rosenthal EA, Lingren T, Pacheco JA, Pendergrass SA, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Hindy G, Rasheed A, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Willemsen G, Wood AR, Ji Y, Gao Z, Haworth S, Mitchell RE, Chai JF, Aadahl M, Yao J, Manichaikul A, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Sidore C, Fiorillo E, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Thuesen BH, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Feitosa MF, Wojczynski MK, Preuss M, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Kember RL, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Leonard HL, Marten J, Schmidt B, Arendt M, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Ahmed M, Jackson AU, Yousri NA, Irvin MR, Oldmeadow C, Kim HN, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Chai X, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Hung YJ, Chen S, Liu F, Yang J, Kentistou KA, Gorski M, Brumat M, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki AE, Hofer E, Lin M, Xue C, Zhang J, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, Lee J, van der Laan SW, Chitrala KN, Weiss S, Zimmermann ME, Lee JY, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin SY, Wang JS, Couture C, Lyytikäinen LP, Nikus K, Cuellar-Partida G, Vestergaard H, Hildalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, Li X, Schwander K, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Chen Z, Li L, Highland HM, Young KL, Kawaguchi T, Thiery J, Bis JC, Nadkarni GN, Launer LJ, Li H, Nalls MA, Raitakari OT, Ichihara S, Wild SH, Nelson CP, Campbell H, Jäger S, Nabika T, Al-Mulla F, Niinikoski H, Braund PS, Kolcic I, Kovacs P, Giardoglou T, Katsuya T, Bhatti KF, de Kleijn D, de Borst GJ, Kim EK, Adams HHH, Ikram MA, Zhu X, Asselbergs FW, Kraaijeveld AO, Beulens JWJ, Shu XO, Rallidis LS, Pedersen O, Hansen T, Mitchell P, Hewitt AW, Kähönen M, Pérusse L, Bouchard C, Tönjes A, Chen YDI, Pennell CE, Mori TA, Lieb W, Franke A, Ohlsson C, Mellström D, Cho YS, Lee H, Yuan JM, Koh WP, Rhee SY, Woo JT, Heid IM, Stark KJ, Völzke H, Homuth G, Evans MK, Zonderman AB, Polasek O, Pasterkamp G, Hoefer IE, Redline S, Pahkala K, Oldehinkel AJ, Snieder H, Biino G, Schmidt R, Schmidt H, Chen YE, Bandinelli S, Dedoussis G, Thanaraj TA, Kardia SLR, Kato N, Schulze MB, Girotto G, Jung B, Böger CA, Joshi PK, Bennett DA, De Jager PL, Lu X, Mamakou V, Brown M, Caulfield MJ, Munroe PB, Guo X, Ciullo M, Jonas JB, Samani NJ, Kaprio J, Pajukanta P, Adair LS, Bechayda SA, de Silva HJ, Wickremasinghe AR, Krauss RM, Wu JY, Zheng W, den Hollander AI, Bharadwaj D, Correa A, Wilson JG, Lind L, Heng CK, Nelson AE, Golightly YM, Wilson JF, Penninx B, Kim HL, Attia J, Scott RJ, Rao DC, Arnett DK, Hunt SC, Walker M, Koistinen HA, Chandak GR, Yajnik CS, Mercader JM, Tusié-Luna T, Aguilar-Salinas CA, Villalpando CG, Orozco L, Fornage M, Tai ES, van Dam RM, Lehtimäki T, Chaturvedi N, Yokota M, Liu J, Reilly DF, McKnight AJ, Kee F, Jöckel KH, McCarthy MI, Palmer CNA, Vitart V, Hayward C, Simonsick E, van Duijn CM, Lu F, Qu J, Hishigaki H, Lin X, März W, Parra EJ, Cruz M, Gudnason V, Tardif JC, Lettre G, 't Hart LM, Elders PJM, Damrauer SM, Kumari M, Kivimaki M, van der Harst P, Spector TD, Loos RJF, Province MA, Psaty BM, Brandslund I, Pramstaller PP, Christensen K, Ripatti S, Widén E, Hakonarson H, Grant SFA, Kiemeney LALM, de Graaf J, Loeffler M, Kronenberg F, Gu D, Erdmann J, Schunkert H, Franks PW, Linneberg A, Jukema JW, Khera AV, Männikkö M, Jarvelin MR, Kutalik Z, Cucca F, Mook-Kanamori DO, van Dijk KW, Watkins H, Strachan DP, Grarup N, Sever P, Poulter N, Rotter JI, Dantoft TM, Karpe F, Neville MJ, Timpson NJ, Cheng CY, Wong TY, Khor CC, Sabanayagam C, Peters A, Gieger C, Hattersley AT, Pedersen NL, Magnusson PKE, Boomsma DI, de Geus EJC, Cupples LA, van Meurs JBJ, Ghanbari M, Gordon-Larsen P, Huang W, Kim YJ, Tabara Y, Wareham NJ, Langenberg C, Zeggini E, Kuusisto J, Laakso M, Ingelsson E, Abecasis G, Chambers JC, Kooner JS, de Vries PS, Morrison AC, North KE, Daviglus M, Kraft P, Martin NG, Whitfield JB, Abbas S, Saleheen D, Walters RG, Holmes MV, Black C, Smith BH, Justice AE, Baras A, Buring JE, Ridker PM, Chasman DI, Kooperberg C, Wei WQ, Jarvik GP, Namjou B, Hayes MG, Ritchie MD, Jousilahti P, Salomaa V, Hveem K, Åsvold BO, Kubo M, Kamatani Y, Okada Y, Murakami Y, Thorsteinsdottir U, Stefansson K, Ho YL, Lynch JA, Rader DJ, Tsao PS, Chang KM, Cho K, O'Donnell CJ, Gaziano JM, Wilson P, Rotimi CN, Hazelhurst S, Ramsay M, Trembath RC, van Heel DA, Tamiya G, Yamamoto M, Kim BJ, Mohlke KL, Frayling TM, Hirschhorn JN, Kathiresan S, Boehnke M, Natarajan P, Peloso GM, Brown CD, Morris AP, Assimes TL, Deloukas P, Sun YV, Willer CJ. Author Correction: The power of genetic diversity in genome-wide association studies of lipids. Nature 2023; 618:E19-E20. [PMID: 37237109 PMCID: PMC10355188 DOI: 10.1038/s41586-023-06194-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
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Duperron MG, Knol MJ, Le Grand Q, Evans TE, Mishra A, Tsuchida A, Roshchupkin G, Konuma T, Trégouët DA, Romero JR, Frenzel S, Luciano M, Hofer E, Bourgey M, Dueker ND, Delgado P, Hilal S, Tankard RM, Dubost F, Shin J, Saba Y, Armstrong NJ, Bordes C, Bastin ME, Beiser A, Brodaty H, Bülow R, Carrera C, Chen C, Cheng CY, Deary IJ, Gampawar PG, Himali JJ, Jiang J, Kawaguchi T, Li S, Macalli M, Marquis P, Morris Z, Muñoz Maniega S, Miyamoto S, Okawa M, Paradise M, Parva P, Rundek T, Sargurupremraj M, Schilling S, Setoh K, Soukarieh O, Tabara Y, Teumer A, Thalamuthu A, Trollor JN, Valdés Hernández MC, Vernooij MW, Völker U, Wittfeld K, Wong TY, Wright MJ, Zhang J, Zhao W, Zhu YC, Schmidt H, Sachdev PS, Wen W, Yoshida K, Joutel A, Satizabal CL, Sacco RL, Bourque G, Lathrop M, Paus T, Fernandez-Cadenas I, Yang Q, Mazoyer B, Boutinaud P, Okada Y, Grabe HJ, Mather KA, Schmidt R, Joliot M, Ikram MA, Matsuda F, Tzourio C, Wardlaw JM, Seshadri S, Adams HHH, Debette S. Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease. Nat Med 2023; 29:950-962. [PMID: 37069360 PMCID: PMC10115645 DOI: 10.1038/s41591-023-02268-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 02/15/2023] [Indexed: 04/19/2023]
Abstract
Perivascular space (PVS) burden is an emerging, poorly understood, magnetic resonance imaging marker of cerebral small vessel disease, a leading cause of stroke and dementia. Genome-wide association studies in up to 40,095 participants (18 population-based cohorts, 66.3 ± 8.6 yr, 96.9% European ancestry) revealed 24 genome-wide significant PVS risk loci, mainly in the white matter. These were associated with white matter PVS already in young adults (N = 1,748; 22.1 ± 2.3 yr) and were enriched in early-onset leukodystrophy genes and genes expressed in fetal brain endothelial cells, suggesting early-life mechanisms. In total, 53% of white matter PVS risk loci showed nominally significant associations (27% after multiple-testing correction) in a Japanese population-based cohort (N = 2,862; 68.3 ± 5.3 yr). Mendelian randomization supported causal associations of high blood pressure with basal ganglia and hippocampal PVS, and of basal ganglia PVS and hippocampal PVS with stroke, accounting for blood pressure. Our findings provide insight into the biology of PVS and cerebral small vessel disease, pointing to pathways involving extracellular matrix, membrane transport and developmental processes, and the potential for genetically informed prioritization of drug targets.
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Yang Y, Knol MJ, Wang R, Mishra A, Liu D, Luciano M, Teumer A, Armstrong N, Bis JC, Jhun MA, Li S, Adams HHH, Aziz NA, Bastin ME, Bourgey M, Brody JA, Frenzel S, Gottesman RF, Hosten N, Hou L, Kardia SLR, Lohner V, Marquis P, Maniega SM, Satizabal CL, Sorond FA, Valdés Hernández MC, van Duijn CM, Vernooij MW, Wittfeld K, Yang Q, Zhao W, Boerwinkle E, Levy D, Deary IJ, Jiang J, Mather KA, Mosley TH, Psaty BM, Sachdev PS, Smith JA, Sotoodehnia N, DeCarli CS, Breteler MMB, Ikram MA, Grabe HJ, Wardlaw J, Longstreth WT, Launer LJ, Seshadri S, Debette S, Fornage M. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI. Brain 2023; 146:492-506. [PMID: 35943854 PMCID: PMC9924914 DOI: 10.1093/brain/awac290] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/23/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.
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Evans TE, Knol MJ, Schwingenschuh P, Wittfeld K, Hilal S, Ikram MA, Dubost F, van Wijnen KMH, Katschnig P, Yilmaz P, de Bruijne M, Habes M, Chen C, Langer S, Völzke H, Ikram MK, Grabe HJ, Schmidt R, Adams HHH, Vernooij MW. Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data. Neurology 2023; 100:e107-e122. [PMID: 36253103 PMCID: PMC9841448 DOI: 10.1212/wnl.0000000000201349] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 08/19/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Perivascular spaces (PVS) are emerging markers of cerebral small vessel disease (CSVD), but research on their determinants has been hampered by conflicting results from small single studies using heterogeneous rating methods. In this study, we therefore aimed to identify determinants of PVS burden in a pooled analysis of multiple cohort studies using 1 harmonized PVS rating method. METHODS Individuals from 10 population-based cohort studies with adult participants from the Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium and the UK Biobank were included. On MRI scans, we counted PVS in 4 brain regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) according to a uniform and validated rating protocol, both manually and automated using a deep learning algorithm. As potential determinants, we considered demographics, cardiovascular risk factors, APOE genotypes, and other imaging markers of CSVD. Negative binomial regression models were used to examine the association between these determinants and PVS counts. RESULTS In total, 39,976 individuals were included (age range 20-96 years). The average count of PVS in the 4 regions increased from the age 20 years (0-1 PVS) to 90 years (2-7 PVS). Men had more mesencephalic PVS (OR [95% CI] = 1.13 [1.08-1.18] compared with women), but less hippocampal PVS (0.82 [0.81-0.83]). Higher blood pressure, particularly diastolic pressure, was associated with more PVS in all regions (ORs between 1.04-1.05). Hippocampal PVS showed higher counts with higher high-density lipoprotein cholesterol levels (1.02 [1.01-1.02]), glucose levels (1.02 [1.01-1.03]), and APOE ε4-alleles (1.02 [1.01-1.04]). Furthermore, white matter hyperintensity volume and presence of lacunes were associated with PVS in multiple regions, but most strongly with the basal ganglia (1.13 [1.12-1.14] and 1.10 [1.09-1.12], respectively). DISCUSSION Various factors are associated with the burden of PVS, in part regionally specific, which points toward a multifactorial origin beyond what can be expected from PVS-related risk factor profiles. This study highlights the power of collaborative efforts in population neuroimaging research.
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Kanoni S, Graham SE, Wang Y, Surakka I, Ramdas S, Zhu X, Clarke SL, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJM, Wu KHH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Yousri NA, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Hwu CM, Hung YJ, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, Matteo F, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Ruotsalainen SE, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Vazquez-Moreno M, Feitosa MF, Wojczynski MK, Wang Z, Preuss MH, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Tsao NL, Verma A, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Demirkan A, Leonard HL, Marten J, Frank M, Schmidt B, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Nongmaithem SS, Bayyana S, Stringham HM, Irvin MR, Oldmeadow C, Kim HN, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Chen S, Liu F, Yang J, Kentistou KA, Banas B, Nardone GG, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki AE, Hofer E, Lin M, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, van der Laan SW, Chitrala KN, Weiss S, Bentley AR, Doumatey AP, Adeyemo AA, Lee JY, Petersen ERB, Nielsen AA, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin SY, Wang JS, Couture C, Lyytikäinen LP, Nikus K, Cuellar-Partida G, Vestergaard H, Hidalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, Li X, Liang J, Tang H, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Chen Z, Li L, Kawaguchi T, Thiery J, Bis JC, Launer LJ, Li H, Nalls MA, Raitakari OT, Ichihara S, Wild SH, Nelson CP, Campbell H, Jäger S, Nabika T, Al-Mulla F, Niinikoski H, Braund PS, Kolcic I, Kovacs P, Giardoglou T, Katsuya T, de Kleijn D, de Borst GJ, Kim EK, Adams HHH, Ikram MA, Zhu X, Asselbergs FW, Kraaijeveld AO, Beulens JWJ, Shu XO, Rallidis LS, Pedersen O, Hansen T, Mitchell P, Hewitt AW, Kähönen M, Pérusse L, Bouchard C, Tönjes A, Chen YDI, Pennell CE, Mori TA, Lieb W, Franke A, Ohlsson C, Mellström D, Cho YS, Lee H, Yuan JM, Koh WP, Rhee SY, Woo JT, Heid IM, Stark KJ, Zimmermann ME, Völzke H, Homuth G, Evans MK, Zonderman AB, Polasek O, Pasterkamp G, Hoefer IE, Redline S, Pahkala K, Oldehinkel AJ, Snieder H, Biino G, Schmidt R, Schmidt H, Bandinelli S, Dedoussis G, Thanaraj TA, Kardia SLR, Peyser PA, Kato N, Schulze MB, Girotto G, Böger CA, Jung B, Joshi PK, Bennett DA, De Jager PL, Lu X, Mamakou V, Brown M, Caulfield MJ, Munroe PB, Guo X, Ciullo M, Jonas JB, Samani NJ, Kaprio J, Pajukanta P, Tusié-Luna T, Aguilar-Salinas CA, Adair LS, Bechayda SA, de Silva HJ, Wickremasinghe AR, Krauss RM, Wu JY, Zheng W, Hollander AI, Bharadwaj D, Correa A, Wilson JG, Lind L, Heng CK, Nelson AE, Golightly YM, Wilson JF, Penninx B, Kim HL, Attia J, Scott RJ, Rao DC, Arnett DK, Hunt SC, Walker M, Koistinen HA, Chandak GR, Mercader JM, Costanzo MC, Jang D, Burtt NP, Villalpando CG, Orozco L, Fornage M, Tai ES, van Dam RM, Lehtimäki T, Chaturvedi N, Yokota M, Liu J, Reilly DF, McKnight AJ, Kee F, Jöckel KH, McCarthy MI, Palmer CNA, Vitart V, Hayward C, Simonsick E, van Duijn CM, Jin ZB, Qu J, Hishigaki H, Lin X, März W, Gudnason V, Tardif JC, Lettre G, Hart LM', Elders PJM, Damrauer SM, Kumari M, Kivimaki M, van der Harst P, Spector TD, Loos RJF, Province MA, Parra EJ, Cruz M, Psaty BM, Brandslund I, Pramstaller PP, Rotimi CN, Christensen K, Ripatti S, Widén E, Hakonarson H, Grant SFA, Kiemeney LALM, de Graaf J, Loeffler M, Kronenberg F, Gu D, Erdmann J, Schunkert H, Franks PW, Linneberg A, Jukema JW, Khera AV, Männikkö M, Jarvelin MR, Kutalik Z, Francesco C, Mook-Kanamori DO, van Dijk KW, Watkins H, Strachan DP, Grarup N, Sever P, Poulter N, Chuang LM, Rotter JI, Dantoft TM, Karpe F, Neville MJ, Timpson NJ, Cheng CY, Wong TY, Khor CC, Li H, Sabanayagam C, Peters A, Gieger C, Hattersley AT, Pedersen NL, Magnusson PKE, Boomsma DI, Willemsen AHM, Cupples LA, van Meurs JBJ, Ghanbari M, Gordon-Larsen P, Huang W, Kim YJ, Tabara Y, Wareham NJ, Langenberg C, Zeggini E, Kuusisto J, Laakso M, Ingelsson E, Abecasis G, Chambers JC, Kooner JS, de Vries PS, Morrison AC, Hazelhurst S, Ramsay M, North KE, Daviglus M, Kraft P, Martin NG, Whitfield JB, Abbas S, Saleheen D, Walters RG, Holmes MV, Black C, Smith BH, Baras A, Justice AE, Buring JE, Ridker PM, Chasman DI, Kooperberg C, Tamiya G, Yamamoto M, van Heel DA, Trembath RC, Wei WQ, Jarvik GP, Namjou B, Hayes MG, Ritchie MD, Jousilahti P, Salomaa V, Hveem K, Åsvold BO, Kubo M, Kamatani Y, Okada Y, Murakami Y, Kim BJ, Thorsteinsdottir U, Stefansson K, Zhang J, Chen YE, Ho YL, Lynch JA, Rader DJ, Tsao PS, Chang KM, Cho K, O'Donnell CJ, Gaziano JM, Wilson PWF, Frayling TM, Hirschhorn JN, Kathiresan S, Mohlke KL, Sun YV, Morris AP, Boehnke M, Brown CD, Natarajan P, Deloukas P, Willer CJ, Assimes TL, Peloso GM. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis. Genome Biol 2022; 23:268. [PMID: 36575460 PMCID: PMC9793579 DOI: 10.1186/s13059-022-02837-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 12/06/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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Yengo L, Vedantam S, Marouli E, Sidorenko J, Bartell E, Sakaue S, Graff M, Eliasen AU, Jiang Y, Raghavan S, Miao J, Arias JD, Graham SE, Mukamel RE, Spracklen CN, Yin X, Chen SH, Ferreira T, Highland HH, Ji Y, Karaderi T, Lin K, Lüll K, Malden DE, Medina-Gomez C, Machado M, Moore A, Rüeger S, Sim X, Vrieze S, Ahluwalia TS, Akiyama M, Allison MA, Alvarez M, Andersen MK, Ani A, Appadurai V, Arbeeva L, Bhaskar S, Bielak LF, Bollepalli S, Bonnycastle LL, Bork-Jensen J, Bradfield JP, Bradford Y, Braund PS, Brody JA, Burgdorf KS, Cade BE, Cai H, Cai Q, Campbell A, Cañadas-Garre M, Catamo E, Chai JF, Chai X, Chang LC, Chang YC, Chen CH, Chesi A, Choi SH, Chung RH, Cocca M, Concas MP, Couture C, Cuellar-Partida G, Danning R, Daw EW, Degenhard F, Delgado GE, Delitala A, Demirkan A, Deng X, Devineni P, Dietl A, Dimitriou M, Dimitrov L, Dorajoo R, Ekici AB, Engmann JE, Fairhurst-Hunter Z, Farmaki AE, Faul JD, Fernandez-Lopez JC, Forer L, Francescatto M, Freitag-Wolf S, Fuchsberger C, Galesloot TE, Gao Y, Gao Z, Geller F, Giannakopoulou O, Giulianini F, Gjesing AP, Goel A, Gordon SD, Gorski M, Grove J, Guo X, Gustafsson S, Haessler J, Hansen TF, Havulinna AS, Haworth SJ, He J, Heard-Costa N, Hebbar P, Hindy G, Ho YLA, Hofer E, Holliday E, Horn K, Hornsby WE, Hottenga JJ, Huang H, Huang J, Huerta-Chagoya A, Huffman JE, Hung YJ, Huo S, Hwang MY, Iha H, Ikeda DD, Isono M, Jackson AU, Jäger S, Jansen IE, Johansson I, Jonas JB, Jonsson A, Jørgensen T, Kalafati IP, Kanai M, Kanoni S, Kårhus LL, Kasturiratne A, Katsuya T, Kawaguchi T, Kember RL, Kentistou KA, Kim HN, Kim YJ, Kleber ME, Knol MJ, Kurbasic A, Lauzon M, Le P, Lea R, Lee JY, Leonard HL, Li SA, Li X, Li X, Liang J, Lin H, Lin SY, Liu J, Liu X, Lo KS, Long J, Lores-Motta L, Luan J, Lyssenko V, Lyytikäinen LP, Mahajan A, Mamakou V, Mangino M, Manichaikul A, Marten J, Mattheisen M, Mavarani L, McDaid AF, Meidtner K, Melendez TL, Mercader JM, Milaneschi Y, Miller JE, Millwood IY, Mishra PP, Mitchell RE, Møllehave LT, Morgan A, Mucha S, Munz M, Nakatochi M, Nelson CP, Nethander M, Nho CW, Nielsen AA, Nolte IM, Nongmaithem SS, Noordam R, Ntalla I, Nutile T, Pandit A, Christofidou P, Pärna K, Pauper M, Petersen ERB, Petersen LV, Pitkänen N, Polašek O, Poveda A, Preuss MH, Pyarajan S, Raffield LM, Rakugi H, Ramirez J, Rasheed A, Raven D, Rayner NW, Riveros C, Rohde R, Ruggiero D, Ruotsalainen SE, Ryan KA, Sabater-Lleal M, Saxena R, Scholz M, Sendamarai A, Shen B, Shi J, Shin JH, Sidore C, Sitlani CM, Slieker RC, Smit RAJ, Smith AV, Smith JA, Smyth LJ, Southam L, Steinthorsdottir V, Sun L, Takeuchi F, Tallapragada DSP, Taylor KD, Tayo BO, Tcheandjieu C, Terzikhan N, Tesolin P, Teumer A, Theusch E, Thompson DJ, Thorleifsson G, Timmers PRHJ, Trompet S, Turman C, Vaccargiu S, van der Laan SW, van der Most PJ, van Klinken JB, van Setten J, Verma SS, Verweij N, Veturi Y, Wang CA, Wang C, Wang L, Wang Z, Warren HR, Bin Wei W, Wickremasinghe AR, Wielscher M, Wiggins KL, Winsvold BS, Wong A, Wu Y, Wuttke M, Xia R, Xie T, Yamamoto K, Yang J, Yao J, Young H, Yousri NA, Yu L, Zeng L, Zhang W, Zhang X, Zhao JH, Zhao W, Zhou W, Zimmermann ME, Zoledziewska M, Adair LS, Adams HHH, Aguilar-Salinas CA, Al-Mulla F, Arnett DK, Asselbergs FW, Åsvold BO, Attia J, Banas B, Bandinelli S, Bennett DA, Bergler T, Bharadwaj D, Biino G, Bisgaard H, Boerwinkle E, Böger CA, Bønnelykke K, Boomsma DI, Børglum AD, Borja JB, Bouchard C, Bowden DW, Brandslund I, Brumpton B, Buring JE, Caulfield MJ, Chambers JC, Chandak GR, Chanock SJ, Chaturvedi N, Chen YDI, Chen Z, Cheng CY, Christophersen IE, Ciullo M, Cole JW, Collins FS, Cooper RS, Cruz M, Cucca F, Cupples LA, Cutler MJ, Damrauer SM, Dantoft TM, de Borst GJ, de Groot LCPGM, De Jager PL, de Kleijn DPV, Janaka de Silva H, Dedoussis GV, den Hollander AI, Du S, Easton DF, Elders PJM, Eliassen AH, Ellinor PT, Elmståhl S, Erdmann J, Evans MK, Fatkin D, Feenstra B, Feitosa MF, Ferrucci L, Ford I, Fornage M, Franke A, Franks PW, Freedman BI, Gasparini P, Gieger C, Girotto G, Goddard ME, Golightly YM, Gonzalez-Villalpando C, Gordon-Larsen P, Grallert H, Grant SFA, Grarup N, Griffiths L, Gudnason V, Haiman C, Hakonarson H, Hansen T, Hartman CA, Hattersley AT, Hayward C, Heckbert SR, Heng CK, Hengstenberg C, Hewitt AW, Hishigaki H, Hoyng CB, Huang PL, Huang W, Hunt SC, Hveem K, Hyppönen E, Iacono WG, Ichihara S, Ikram MA, Isasi CR, Jackson RD, Jarvelin MR, Jin ZB, Jöckel KH, Joshi PK, Jousilahti P, Jukema JW, Kähönen M, Kamatani Y, Kang KD, Kaprio J, Kardia SLR, Karpe F, Kato N, Kee F, Kessler T, Khera AV, Khor CC, Kiemeney LALM, Kim BJ, Kim EK, Kim HL, Kirchhof P, Kivimaki M, Koh WP, Koistinen HA, Kolovou GD, Kooner JS, Kooperberg C, Köttgen A, Kovacs P, Kraaijeveld A, Kraft P, Krauss RM, Kumari M, Kutalik Z, Laakso M, Lange LA, Langenberg C, Launer LJ, Le Marchand L, Lee H, Lee NR, Lehtimäki T, Li H, Li L, Lieb W, Lin X, Lind L, Linneberg A, Liu CT, Liu J, Loeffler M, London B, Lubitz SA, Lye SJ, Mackey DA, Mägi R, Magnusson PKE, Marcus GM, Vidal PM, Martin NG, März W, Matsuda F, McGarrah RW, McGue M, McKnight AJ, Medland SE, Mellström D, Metspalu A, Mitchell BD, Mitchell P, Mook-Kanamori DO, Morris AD, Mucci LA, Munroe PB, Nalls MA, Nazarian S, Nelson AE, Neville MJ, Newton-Cheh C, Nielsen CS, Nöthen MM, Ohlsson C, Oldehinkel AJ, Orozco L, Pahkala K, Pajukanta P, Palmer CNA, Parra EJ, Pattaro C, Pedersen O, Pennell CE, Penninx BWJH, Perusse L, Peters A, Peyser PA, Porteous DJ, Posthuma D, Power C, Pramstaller PP, Province MA, Qi Q, Qu J, Rader DJ, Raitakari OT, Ralhan S, Rallidis LS, Rao DC, Redline S, Reilly DF, Reiner AP, Rhee SY, Ridker PM, Rienstra M, Ripatti S, Ritchie MD, Roden DM, Rosendaal FR, Rotter JI, Rudan I, Rutters F, Sabanayagam C, Saleheen D, Salomaa V, Samani NJ, Sanghera DK, Sattar N, Schmidt B, Schmidt H, Schmidt R, Schulze MB, Schunkert H, Scott LJ, Scott RJ, Sever P, Shiroma EJ, Shoemaker MB, Shu XO, Simonsick EM, Sims M, Singh JR, Singleton AB, Sinner MF, Smith JG, Snieder H, Spector TD, Stampfer MJ, Stark KJ, Strachan DP, 't Hart LM, Tabara Y, Tang H, Tardif JC, Thanaraj TA, Timpson NJ, Tönjes A, Tremblay A, Tuomi T, Tuomilehto J, Tusié-Luna MT, Uitterlinden AG, van Dam RM, van der Harst P, Van der Velde N, van Duijn CM, van Schoor NM, Vitart V, Völker U, Vollenweider P, Völzke H, Wacher-Rodarte NH, Walker M, Wang YX, Wareham NJ, Watanabe RM, Watkins H, Weir DR, Werge TM, Widen E, Wilkens LR, Willemsen G, Willett WC, Wilson JF, Wong TY, Woo JT, Wright AF, Wu JY, Xu H, Yajnik CS, Yokota M, Yuan JM, Zeggini E, Zemel BS, Zheng W, Zhu X, Zmuda JM, Zonderman AB, Zwart JA, Chasman DI, Cho YS, Heid IM, McCarthy MI, Ng MCY, O'Donnell CJ, Rivadeneira F, Thorsteinsdottir U, Sun YV, Tai ES, Boehnke M, Deloukas P, Justice AE, Lindgren CM, Loos RJF, Mohlke KL, North KE, Stefansson K, Walters RG, Winkler TW, Young KL, Loh PR, Yang J, Esko T, Assimes TL, Auton A, Abecasis GR, Willer CJ, Locke AE, Berndt SI, Lettre G, Frayling TM, Okada Y, Wood AR, Visscher PM, Hirschhorn JN. A saturated map of common genetic variants associated with human height. Nature 2022; 610:704-712. [PMID: 36224396 PMCID: PMC9605867 DOI: 10.1038/s41586-022-05275-y] [Citation(s) in RCA: 154] [Impact Index Per Article: 77.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 08/24/2022] [Indexed: 02/08/2023]
Abstract
Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
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Ramdas S, Judd J, Graham SE, Kanoni S, Wang Y, Surakka I, Wenz B, Clarke SL, Chesi A, Wells A, Bhatti KF, Vedantam S, Winkler TW, Locke AE, Marouli E, Zajac GJM, Wu KHH, Ntalla I, Hui Q, Klarin D, Hilliard AT, Wang Z, Xue C, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Hwang MY, Han S, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Havulinna AS, Veturi Y, Pacheco JA, Rosenthal EA, Lingren T, Feng Q, Kullo IJ, Narita A, Takayama J, Martin HC, Hunt KA, Trivedi B, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Rasheed A, Hindy G, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Choudhury A, Sengupta D, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Wood AR, Ji Y, Gao Z, Haworth S, Mitchell RE, Chai JF, Aadahl M, Bjerregaard AA, Yao J, Manichaikul A, Lee WJ, Hsiung CA, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Mauro P, Matteo F, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Schönherr S, Forer L, Scholz M, Galesloot TE, Bradfield JP, Ruotsalainen SE, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Le P, Feitosa MF, Wojczynski MK, Hemerich D, Preuss M, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Noah TL, Verma A, Slieker RC, Lo KS, Zilhao NR, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Demirkan A, Leonard HL, Marten J, Emmel C, Schmidt B, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Nongmaithem SS, Sankareswaran A, Irvin MR, Oldmeadow C, Kim HN, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Chen S, Liu F, Yang J, Kentistou KA, Banas B, Morgan A, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki AE, Hofer E, Lin M, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, van der Laan SW, Chitrala KN, Weiss S, Bentley AR, Doumatey AP, Adeyemo AA, Lee JY, Petersen ERB, Nielsen AA, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin SY, Wang JS, Couture C, Lyytikäinen LP, Nikus K, Cuellar-Partida G, Vestergaard H, Hidalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, He KY, Tang H, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Chen Z, Li L, Kawaguchi T, Thiery J, Bis JC, Launer LJ, Li H, Nalls MA, Raitakari OT, Ichihara S, Wild SH, Nelson CP, Campbell H, Jäger S, Nabika T, Al-Mulla F, Niinikoski H, Braund PS, Kolcic I, Kovacs P, Giardoglou T, Katsuya T, de Kleijn D, de Borst GJ, Kim EK, Adams HHH, Ikram MA, Zhu X, Asselbergs FW, Kraaijeveld AO, Beulens JWJ, Shu XO, Rallidis LS, Pedersen O, Hansen T, Mitchell P, Hewitt AW, Kähönen M, Pérusse L, Bouchard C, Tönjes A, Ida Chen YD, Pennell CE, Mori TA, Lieb W, Franke A, Ohlsson C, Mellström D, Cho YS, Lee H, Yuan JM, Koh WP, Rhee SY, Woo JT, Heid IM, Stark KJ, Zimmermann ME, Völzke H, Homuth G, Evans MK, Zonderman AB, Polasek O, Pasterkamp G, Hoefer IE, Redline S, Pahkala K, Oldehinkel AJ, Snieder H, Biino G, Schmidt R, Schmidt H, Bandinelli S, Dedoussis G, Thanaraj TA, Peyser PA, Kato N, Schulze MB, Girotto G, Böger CA, Jung B, Joshi PK, Bennett DA, De Jager PL, Lu X, Mamakou V, Brown M, Caulfield MJ, Munroe PB, Guo X, Ciullo M, Jonas JB, Samani NJ, Kaprio J, Pajukanta P, Tusié-Luna T, Aguilar-Salinas CA, Adair LS, Bechayda SA, de Silva HJ, Wickremasinghe AR, Krauss RM, Wu JY, Zheng W, den Hollander AI, Bharadwaj D, Correa A, Wilson JG, Lind L, Heng CK, Nelson AE, Golightly YM, Wilson JF, Penninx B, Kim HL, Attia J, Scott RJ, Rao DC, Arnett DK, Walker M, Scott LJ, Koistinen HA, Chandak GR, Mercader JM, Villalpando CG, Orozco L, Fornage M, Tai ES, van Dam RM, Lehtimäki T, Chaturvedi N, Yokota M, Liu J, Reilly DF, McKnight AJ, Kee F, Jöckel KH, McCarthy MI, Palmer CNA, Vitart V, Hayward C, Simonsick E, van Duijn CM, Jin ZB, Lu F, Hishigaki H, Lin X, März W, Gudnason V, Tardif JC, Lettre G, T Hart LM, Elders PJM, Rader DJ, Damrauer SM, Kumari M, Kivimaki M, van der Harst P, Spector TD, Loos RJF, Province MA, Parra EJ, Cruz M, Psaty BM, Brandslund I, Pramstaller PP, Rotimi CN, Christensen K, Ripatti S, Widén E, Hakonarson H, Grant SFA, Kiemeney L, de Graaf J, Loeffler M, Kronenberg F, Gu D, Erdmann J, Schunkert H, Franks PW, Linneberg A, Jukema JW, Khera AV, Männikkö M, Jarvelin MR, Kutalik Z, Francesco C, Mook-Kanamori DO, Willems van Dijk K, Watkins H, Strachan DP, Grarup N, Sever P, Poulter N, Huey-Herng Sheu W, Rotter JI, Dantoft TM, Karpe F, Neville MJ, Timpson NJ, Cheng CY, Wong TY, Khor CC, Li H, Sabanayagam C, Peters A, Gieger C, Hattersley AT, Pedersen NL, Magnusson PKE, Boomsma DI, de Geus EJC, Cupples LA, van Meurs JBJ, Ikram A, Ghanbari M, Gordon-Larsen P, Huang W, Kim YJ, Tabara Y, Wareham NJ, Langenberg C, Zeggini E, Tuomilehto J, Kuusisto J, Laakso M, Ingelsson E, Abecasis G, Chambers JC, Kooner JS, de Vries PS, Morrison AC, Hazelhurst S, Ramsay M, North KE, Daviglus M, Kraft P, Martin NG, Whitfield JB, Abbas S, Saleheen D, Walters RG, Holmes MV, Black C, Smith BH, Baras A, Justice AE, Buring JE, Ridker PM, Chasman DI, Kooperberg C, Tamiya G, Yamamoto M, van Heel DA, Trembath RC, Wei WQ, Jarvik GP, Namjou B, Hayes MG, Ritchie MD, Jousilahti P, Salomaa V, Hveem K, Åsvold BO, Kubo M, Kamatani Y, Okada Y, Murakami Y, Kim BJ, Thorsteinsdottir U, Stefansson K, Zhang J, Chen YE, Ho YL, Lynch JA, Tsao PS, Chang KM, Cho K, O'Donnell CJ, Gaziano JM, Wilson P, Mohlke KL, Frayling TM, Hirschhorn JN, Kathiresan S, Boehnke M, Struan Grant, Natarajan P, Sun YV, Morris AP, Deloukas P, Peloso G, Assimes TL, Willer CJ, Zhu X, Brown CD. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. Am J Hum Genet 2022; 109:1366-1387. [PMID: 35931049 PMCID: PMC9388392 DOI: 10.1016/j.ajhg.2022.06.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 06/23/2022] [Indexed: 02/06/2023] Open
Abstract
A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
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Mishra A, Duplaà C, Vojinovic D, Suzuki H, Sargurupremraj M, Zilhão NR, Li S, Bartz TM, Jian X, Zhao W, Hofer E, Wittfeld K, Harris SE, van der Auwera-Palitschka S, Luciano M, Bis JC, Adams HHH, Satizabal CL, Gottesman RF, Gampawar PG, Bülow R, Weiss S, Yu M, Bastin ME, Lopez OL, Vernooij MW, Beiser AS, Völker U, Kacprowski T, Soumare A, Smith JA, Knopman DS, Morris Z, Zhu Y, Rotter JI, Dufouil C, Valdés Hernández M, Muñoz Maniega S, Lathrop M, Boerwinkle E, Schmidt R, Ihara M, Mazoyer B, Yang Q, Joutel A, Tournier-Lasserve E, Launer LJ, Deary IJ, Mosley TH, Amouyel P, DeCarli CS, Psaty BM, Tzourio C, Kardia SLR, Grabe HJ, Teumer A, van Duijn CM, Schmidt H, Wardlaw JM, Ikram MA, Fornage M, Gudnason V, Seshadri S, Matthews PM, Longstreth WT, Couffinhal T, Debette S. Gene-mapping study of extremes of cerebral small vessel disease reveals TRIM47 as a strong candidate. Brain 2022; 145:1992-2007. [PMID: 35511193 PMCID: PMC9255380 DOI: 10.1093/brain/awab432] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 10/11/2021] [Accepted: 10/28/2021] [Indexed: 12/11/2022] Open
Abstract
Cerebral small vessel disease is a leading cause of stroke and a major contributor to cognitive decline and dementia, but our understanding of specific genes underlying the cause of sporadic cerebral small vessel disease is limited. We report a genome-wide association study and a whole-exome association study on a composite extreme phenotype of cerebral small vessel disease derived from its most common MRI features: white matter hyperintensities and lacunes. Seventeen population-based cohorts of older persons with MRI measurements and genome-wide genotyping (n = 41 326), whole-exome sequencing (n = 15 965), or exome chip (n = 5249) data contributed 13 776 and 7079 extreme small vessel disease samples for the genome-wide association study and whole-exome association study, respectively. The genome-wide association study identified significant association of common variants in 11 loci with extreme small vessel disease, of which the chr12q24.11 locus was not previously reported to be associated with any MRI marker of cerebral small vessel disease. The whole-exome association study identified significant associations of extreme small vessel disease with common variants in the 5' UTR region of EFEMP1 (chr2p16.1) and one probably damaging common missense variant in TRIM47 (chr17q25.1). Mendelian randomization supports the causal association of extensive small vessel disease severity with increased risk of stroke and Alzheimer's disease. Combined evidence from summary-based Mendelian randomization studies and profiling of human loss-of-function allele carriers showed an inverse relation between TRIM47 expression in the brain and blood vessels and extensive small vessel disease severity. We observed significant enrichment of Trim47 in isolated brain vessel preparations compared to total brain fraction in mice, in line with the literature showing Trim47 enrichment in brain endothelial cells at single cell level. Functional evaluation of TRIM47 by small interfering RNAs-mediated knockdown in human brain endothelial cells showed increased endothelial permeability, an important hallmark of cerebral small vessel disease pathology. Overall, our comprehensive gene-mapping study and preliminary functional evaluation suggests a putative role of TRIM47 in the pathophysiology of cerebral small vessel disease, making it an important candidate for extensive in vivo explorations and future translational work.
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Le Grand Q, Satizabal CL, Sargurupremraj M, Mishra A, Soumaré A, Laurent A, Crivello F, Tsuchida A, Shin J, Macalli M, Singh B, Beiser AS, DeCarli C, Fletcher E, Paus T, Lathrop M, Adams HHH, Bis JC, Seshadri S, Tzourio C, Mazoyer B, Debette S. Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:616-628. [PMID: 34700051 PMCID: PMC9395126 DOI: 10.1016/j.bpsc.2021.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 09/28/2021] [Accepted: 10/14/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Subcortical brain structures play a key role in pathological processes of age-related neurodegenerative disorders. Mounting evidence also suggests that early-life factors may have an impact on the development of common late-life neurological diseases, including genetic factors that can influence both brain maturation and neurodegeneration. METHODS Using large population-based brain imaging datasets across the lifespan (N ≤ 40,628), we aimed to 1) estimate the heritability of subcortical volumes in young (18-35 years), middle (35-65 years), and older (65+ years) age, and their genetic correlation across age groups; 2) identify whether genetic loci associated with subcortical volumes in older persons also show associations in early adulthood, and explore underlying genes using transcriptome-wide association studies; and 3) explore their association with neurological phenotypes. RESULTS Heritability of subcortical volumes consistently decreased with increasing age. Genetic risk scores for smaller caudate nucleus, putamen, and hippocampus volume in older adults were associated with smaller volumes in young adults. Individually, 10 loci associated with subcortical volumes in older adults also showed associations in young adults. Within these loci, transcriptome-wide association studies showed that expression of several genes in brain tissues (especially MYLK2 and TUFM) was associated with subcortical volumes in both age groups. One risk variant for smaller caudate nucleus volume (TUFM locus) was associated with lower cognitive performance. Genetically predicted Alzheimer's disease was associated with smaller subcortical volumes in middle and older age. CONCLUSIONS Our findings provide novel insights into the genetic determinants of subcortical volumes across the lifespan. More studies are needed to decipher the underlying biology and clinical impact.
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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 VOG, 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, Hulshoff Pol HE. Genetic variants associated with longitudinal changes in brain structure across the lifespan. Nat Neurosci 2022; 25:421-432. [PMID: 35383335 PMCID: PMC10040206 DOI: 10.1038/s41593-022-01042-4] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 02/28/2022] [Indexed: 02/08/2023]
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.
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Taams NE, Knol MJ, Hanewinckel R, Drenthen J, Adams HHH, van Doorn PA, Ikram MA. Genetic evidence for the most common risk factors of chronic axonal polyneuropathy in the general population. Eur J Neurol 2022; 29:2066-2073. [PMID: 35247017 PMCID: PMC9314974 DOI: 10.1111/ene.15311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 02/24/2022] [Indexed: 11/28/2022]
Abstract
Background and purpose Chronic axonal polyneuropathy is a common disease, but the etiology remains only partially understood. Previous etiologic studies have identified clinical risk factors, but genetic evidence supporting causality between these factors and polyneuropathy are largely lacking. In this study, we investigate whether there is a genetic association of clinically established important risk factors (diabetes, body mass index [BMI], vitamin B12 levels, and alcohol intake) with chronic axonal polyneuropathy. Methods This study was performed within the population‐based Rotterdam Study and included 1565 participants (median age = 73.6 years, interquartile range = 64.6–78.8, 53.5% female), of whom 215 participants (13.7%) had polyneuropathy. Polygenic scores (PGSs) for diabetes, BMI, vitamin B12 levels, and alcohol intake were calculated at multiple significance thresholds based on published genome‐wide association studies. Results Higher PGSs of diabetes, BMI, and alcohol intake were associated with higher prevalence of chronic axonal polyneuropathy, whereas higher PGS of vitamin B12 levels was associated with lower prevalence of polyneuropathy. These effects were most pronounced for PGSs with lenient significance thresholds for diabetes and BMI (odds ratio [OR]diabetes, p < 1.0 = 1.21, 95% confidence interval [CI] = 1.05–1.39 and ORBMI, p < 1.0 = 1.21, 95% CI = 1.04–1.41) and for the strictest significance thresholds for vitamin B12 level and alcohol intake (OR vitamin B12, p < 5e‐6 = 0.79, 95% CI = 0.68–0.92 and ORalcohol, p < 5e‐8 = 1.17, 95% CI = 1.02–1.35). We did not find an association between different PGSs and sural sensory nerve action potential amplitude, nor between individual lead variants of PGSp < 5e‐8 and polyneuropathy. Conclusions This study provides evidence for polygenic associations of diabetes, BMI, vitamin B12 level, and alcohol intake with chronic axonal polyneuropathy. This supports the hypothesis of causal associations between well‐known clinical risk factors and polyneuropathy.
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Fohner AE, Bartz TM, Tracy RP, Adams HHH, Bis JC, Djousse L, Satizabal CL, Lopez OL, Seshadri S, Mukamal KJ, Kuller LH, Psaty BM, Longstreth WT. Association of Serum Neurofilament Light Chain Concentration and MRI Findings in Older Adults: The Cardiovascular Health Study. Neurology 2022; 98:e903-e911. [PMID: 34921102 PMCID: PMC8901174 DOI: 10.1212/wnl.0000000000013229] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 12/08/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Neurofilament light chain (NfL) in blood is a sensitive but nonspecific marker of brain injury. This study sought to evaluate associations between NfL concentration and MRI findings of vascular brain injury in older adults. METHODS A longitudinal cohort study included 2 cranial MRI scans performed about 5 years apart and assessed for white matter hyperintensities (WMH) and infarcts. About 1 year before their second MRI, 1,362 participants (median age 77 years, 61.4% women) without a history of TIA or stroke had measurement of 4 biomarkers: NfL, total tau, glial fibrillary acidic protein (GFAP), and ubiquitin carboxyl-terminal hydrolase L1. Most (n = 1,279) also had the first MRI scan, and some (n = 633) had quantitative measurements of hippocampal and WMH. In primary analyses, we assessed associations of NfL with a 10-point white matter grade (WMG) and prevalent infarcts on second MRI and with worsening WMG and incident infarct comparing the 2 scans. A p value <0.0125 (0.05/4) was considered significant for these analyses. We also assessed associations with hippocampal and WMH volume. RESULTS In fully adjusted models, log2(NfL) concentration was associated with WMG (β = 0.27; p = 2.3 × 10-4) and worsening WMG (relative risk [RR] 1.24; p = 0.0022), but less strongly with prevalent brain infarcts (RR 1.18; p = 0.013) and not with incident brain infarcts (RR 1.18; p = 0.18). Associations were also present with WMH volume (β = 2,242.9, p = 0.0036). For the other 3 biomarkers, the associations for log2 (GFAP) concentration with WMG and worsening WMG were significant. DISCUSSION Among older adults without a history of stroke, higher serum NfL concentration was associated with covert MRI findings of vascular brain injury, especially the burden of WMH and its worsening. Whether these results offer opportunities for the use of NfL as a noninvasive biomarker of WMH or to control vascular risk factors remains to be determined.
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Bressler J, Davies G, Smith AV, Saba Y, Bis JC, Jian X, Hayward C, Yanek L, Smith JA, Mirza SS, Wang R, Adams HHH, Becker D, Boerwinkle E, Campbell A, Cox SR, Eiriksdottir G, Fawns-Ritchie C, Gottesman RF, Grove ML, Guo X, Hofer E, Kardia SLR, Knol MJ, Koini M, Lopez OL, Marioni RE, Nyquist P, Pattie A, Polasek O, Porteous DJ, Rudan I, Satizabal CL, Schmidt H, Schmidt R, Sidney S, Simino J, Smith BH, Turner ST, van der Lee SJ, Ware EB, Whitmer RA, Yaffe K, Yang Q, Zhao W, Gudnason V, Launer LJ, Fitzpatrick AL, Psaty BM, Fornage M, Arfan Ikram M, van Duijn CM, Seshadri S, Mosley TH, Deary IJ. Correction: Association of low-frequency and rare coding variants with information processing speed. Transl Psychiatry 2022; 12:88. [PMID: 35232957 PMCID: PMC8888652 DOI: 10.1038/s41398-022-01852-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Graham SE, Clarke SL, Wu KHH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, Locke AE, Marouli E, Hwang MY, Han S, Narita A, Choudhury A, Bentley AR, Ekoru K, Verma A, Trivedi B, Martin HC, Hunt KA, Hui Q, Klarin D, Zhu X, Thorleifsson G, Helgadottir A, Gudbjartsson DF, Holm H, Olafsson I, Akiyama M, Sakaue S, Terao C, Kanai M, Zhou W, Brumpton BM, Rasheed H, Ruotsalainen SE, Havulinna AS, Veturi Y, Feng Q, Rosenthal EA, Lingren T, Pacheco JA, Pendergrass SA, Haessler J, Giulianini F, Bradford Y, Miller JE, Campbell A, Lin K, Millwood IY, Hindy G, Rasheed A, Faul JD, Zhao W, Weir DR, Turman C, Huang H, Graff M, Mahajan A, Brown MR, Zhang W, Yu K, Schmidt EM, Pandit A, Gustafsson S, Yin X, Luan J, Zhao JH, Matsuda F, Jang HM, Yoon K, Medina-Gomez C, Pitsillides A, Hottenga JJ, Willemsen G, Wood AR, Ji Y, Gao Z, Haworth S, Mitchell RE, Chai JF, Aadahl M, Yao J, Manichaikul A, Warren HR, Ramirez J, Bork-Jensen J, Kårhus LL, Goel A, Sabater-Lleal M, Noordam R, Sidore C, Fiorillo E, McDaid AF, Marques-Vidal P, Wielscher M, Trompet S, Sattar N, Møllehave LT, Thuesen BH, Munz M, Zeng L, Huang J, Yang B, Poveda A, Kurbasic A, Lamina C, Forer L, Scholz M, Galesloot TE, Bradfield JP, Daw EW, Zmuda JM, Mitchell JS, Fuchsberger C, Christensen H, Brody JA, Feitosa MF, Wojczynski MK, Preuss M, Mangino M, Christofidou P, Verweij N, Benjamins JW, Engmann J, Kember RL, Slieker RC, Lo KS, Zilhao NR, Le P, Kleber ME, Delgado GE, Huo S, Ikeda DD, Iha H, Yang J, Liu J, Leonard HL, Marten J, Schmidt B, Arendt M, Smyth LJ, Cañadas-Garre M, Wang C, Nakatochi M, Wong A, Hutri-Kähönen N, Sim X, Xia R, Huerta-Chagoya A, Fernandez-Lopez JC, Lyssenko V, Ahmed M, Jackson AU, Yousri NA, Irvin MR, Oldmeadow C, Kim HN, Ryu S, Timmers PRHJ, Arbeeva L, Dorajoo R, Lange LA, Chai X, Prasad G, Lorés-Motta L, Pauper M, Long J, Li X, Theusch E, Takeuchi F, Spracklen CN, Loukola A, Bollepalli S, Warner SC, Wang YX, Wei WB, Nutile T, Ruggiero D, Sung YJ, Hung YJ, Chen S, Liu F, Yang J, Kentistou KA, Gorski M, Brumat M, Meidtner K, Bielak LF, Smith JA, Hebbar P, Farmaki AE, Hofer E, Lin M, Xue C, Zhang J, Concas MP, Vaccargiu S, van der Most PJ, Pitkänen N, Cade BE, Lee J, van der Laan SW, Chitrala KN, Weiss S, Zimmermann ME, Lee JY, Choi HS, Nethander M, Freitag-Wolf S, Southam L, Rayner NW, Wang CA, Lin SY, Wang JS, Couture C, Lyytikäinen LP, Nikus K, Cuellar-Partida G, Vestergaard H, Hildalgo B, Giannakopoulou O, Cai Q, Obura MO, van Setten J, Li X, Schwander K, Terzikhan N, Shin JH, Jackson RD, Reiner AP, Martin LW, Chen Z, Li L, Highland HM, Young KL, Kawaguchi T, Thiery J, Bis JC, Nadkarni GN, Launer LJ, Li H, Nalls MA, Raitakari OT, Ichihara S, Wild SH, Nelson CP, Campbell H, Jäger S, Nabika T, Al-Mulla F, Niinikoski H, Braund PS, Kolcic I, Kovacs P, Giardoglou T, Katsuya T, Bhatti KF, de Kleijn D, de Borst GJ, Kim EK, Adams HHH, Ikram MA, Zhu X, Asselbergs FW, Kraaijeveld AO, Beulens JWJ, Shu XO, Rallidis LS, Pedersen O, Hansen T, Mitchell P, Hewitt AW, Kähönen M, Pérusse L, Bouchard C, Tönjes A, Chen YDI, Pennell CE, Mori TA, Lieb W, Franke A, Ohlsson C, Mellström D, Cho YS, Lee H, Yuan JM, Koh WP, Rhee SY, Woo JT, Heid IM, Stark KJ, Völzke H, Homuth G, Evans MK, Zonderman AB, Polasek O, Pasterkamp G, Hoefer IE, Redline S, Pahkala K, Oldehinkel AJ, Snieder H, Biino G, Schmidt R, Schmidt H, Chen YE, Bandinelli S, Dedoussis G, Thanaraj TA, Kardia SLR, Kato N, Schulze MB, Girotto G, Jung B, Böger CA, Joshi PK, Bennett DA, De Jager PL, Lu X, Mamakou V, Brown M, Caulfield MJ, Munroe PB, Guo X, Ciullo M, Jonas JB, Samani NJ, Kaprio J, Pajukanta P, Adair LS, Bechayda SA, de Silva HJ, Wickremasinghe AR, Krauss RM, Wu JY, Zheng W, den Hollander AI, Bharadwaj D, Correa A, Wilson JG, Lind L, Heng CK, Nelson AE, Golightly YM, Wilson JF, Penninx B, Kim HL, Attia J, Scott RJ, Rao DC, Arnett DK, Hunt SC, Walker M, Koistinen HA, Chandak GR, Yajnik CS, Mercader JM, Tusié-Luna T, Aguilar-Salinas CA, Villalpando CG, Orozco L, Fornage M, Tai ES, van Dam RM, Lehtimäki T, Chaturvedi N, Yokota M, Liu J, Reilly DF, McKnight AJ, Kee F, Jöckel KH, McCarthy MI, Palmer CNA, Vitart V, Hayward C, Simonsick E, van Duijn CM, Lu F, Qu J, Hishigaki H, Lin X, März W, Parra EJ, Cruz M, Gudnason V, Tardif JC, Lettre G, 't Hart LM, Elders PJM, Damrauer SM, Kumari M, Kivimaki M, van der Harst P, Spector TD, Loos RJF, Province MA, Psaty BM, Brandslund I, Pramstaller PP, Christensen K, Ripatti S, Widén E, Hakonarson H, Grant SFA, Kiemeney LALM, de Graaf J, Loeffler M, Kronenberg F, Gu D, Erdmann J, Schunkert H, Franks PW, Linneberg A, Jukema JW, Khera AV, Männikkö M, Jarvelin MR, Kutalik Z, Cucca F, Mook-Kanamori DO, van Dijk KW, Watkins H, Strachan DP, Grarup N, Sever P, Poulter N, Rotter JI, Dantoft TM, Karpe F, Neville MJ, Timpson NJ, Cheng CY, Wong TY, Khor CC, Sabanayagam C, Peters A, Gieger C, Hattersley AT, Pedersen NL, Magnusson PKE, Boomsma DI, de Geus EJC, Cupples LA, van Meurs JBJ, Ghanbari M, Gordon-Larsen P, Huang W, Kim YJ, Tabara Y, Wareham NJ, Langenberg C, Zeggini E, Kuusisto J, Laakso M, Ingelsson E, Abecasis G, Chambers JC, Kooner JS, de Vries PS, Morrison AC, North KE, Daviglus M, Kraft P, Martin NG, Whitfield JB, Abbas S, Saleheen D, Walters RG, Holmes MV, Black C, Smith BH, Justice AE, Baras A, Buring JE, Ridker PM, Chasman DI, Kooperberg C, Wei WQ, Jarvik GP, Namjou B, Hayes MG, Ritchie MD, Jousilahti P, Salomaa V, Hveem K, Åsvold BO, Kubo M, Kamatani Y, Okada Y, Murakami Y, Thorsteinsdottir U, Stefansson K, Ho YL, Lynch JA, Rader DJ, Tsao PS, Chang KM, Cho K, O'Donnell CJ, Gaziano JM, Wilson P, Rotimi CN, Hazelhurst S, Ramsay M, Trembath RC, van Heel DA, Tamiya G, Yamamoto M, Kim BJ, Mohlke KL, Frayling TM, Hirschhorn JN, Kathiresan S, Boehnke M, Natarajan P, Peloso GM, Brown CD, Morris AP, Assimes TL, Deloukas P, Sun YV, Willer CJ. The power of genetic diversity in genome-wide association studies of lipids. Nature 2021; 600:675-679. [PMID: 34887591 PMCID: PMC8730582 DOI: 10.1038/s41586-021-04064-3] [Citation(s) in RCA: 308] [Impact Index Per Article: 102.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 09/27/2021] [Indexed: 01/14/2023]
Abstract
Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
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Pawlak MA, Knol MJ, Vernooij MW, Ikram MA, Adams HHH, Evans TE. Neural correlates of orbital telorism. Cortex 2021; 145:315-326. [PMID: 34781092 DOI: 10.1016/j.cortex.2021.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 08/30/2021] [Accepted: 10/01/2021] [Indexed: 12/23/2022]
Abstract
Orbital telorism, the interocular distance, is clinically informative and in extremes is considered a minor physical anomaly. While its extremes, hypo- and hypertelorism, have been linked to disorders often related to cognitive ability, little is known about the neural correlates of normal variation of telorism within the general population. We derived measures of orbital telorism from cranial magnetic resonance imaging (MRI) by calculating the distance between the eyeball center of gravity in two population-based datasets (N = 5,653, N = 29,824; mean age 64.66, 63.75 years). This measure was found to be related to grey matter tissue density within numerous regions of the brain, including, but surprisingly not limited to, the frontal regions, in both positive and negative directions. Additionally, telorism was related to several cognitive functions, such as Purdue pegboard test (Beta, P-value (CI95%) -.02, 1.63 × 10-7 (-.03:-.01)) and fluid intelligence (.02, 4.75 × 10-6 (.01:0.02)), with some relationships driven by individuals with a smaller orbital telorism. This is reflective of the higher prevalence of hypotelorism in developmental disorders, specifically those that accompany lower cognitive lower functioning. This study suggests, despite previous links only made in clinical extremes, that orbital telorism holds some relation to structural brain development and cognitive function in the general population. This relationship is likely driven by shared developmental periods.
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Knol MJ, Pawlak MA, Lamballais S, Terzikhan N, Hofer E, Xiong Z, Klaver CCW, Pirpamer L, Vernooij MW, Ikram MA, Schmidt R, Kayser M, Evans TE, Adams HHH. Genetic architecture of orbital telorism. Hum Mol Genet 2021; 31:1531-1543. [PMID: 34791242 PMCID: PMC9071440 DOI: 10.1093/hmg/ddab334] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 11/09/2021] [Accepted: 11/10/2021] [Indexed: 11/19/2022] Open
Abstract
The interocular distance, or orbital telorism, is a distinctive craniofacial trait that also serves as a clinically informative measure. While its extremes, hypo- and hypertelorism, have been linked to monogenic disorders and are often syndromic, little is known about the genetic determinants of interocular distance within the general population. We derived orbital telorism measures from cranial magnetic resonance imaging by calculating the distance between the eyeballs’ centre of gravity, which showed a good reproducibility with an intraclass correlation coefficient of 0.991 (95% confidence interval 0.985–0.994). Heritability estimates were 76% (standard error = 12%) with a family-based method (N = 364) and 39% (standard error = 2.4%) with a single nucleotide polymorphism-based method (N = 34 130) and were unaffected by adjustment for height (model II) and intracranial volume (model III) or head width (model IV). Genome-wide association studies in 34 130 European individuals identified 56 significantly associated genomic loci (P < 5 × 10−8) across four different models of which 46 were novel for facial morphology, and overall these findings replicated in an independent sample (N = 10 115) with telorism-related horizontal facial distance measures. Genes located nearby these 56 identified genetic loci were 4.9-fold enriched for Mendelian hypotelorism and hypertelorism genes, underlining their biological relevance. This study provides novel insights into the genetic architecture underlying interocular distance in particular, and the face in general, and explores its potential for applications in a clinical setting.
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Knol MJ, Lu D, Traylor M, Adams HHH, Romero JRJ, Smith AV, Fornage M, Hofer E, Liu J, Hostettler IC, Luciano M, Trompet S, Giese AK, Hilal S, van den Akker EB, Vojinovic D, Li S, Sigurdsson S, van der Lee SJ, Jack CR, Wilson D, Yilmaz P, Satizabal CL, Liewald DCM, van der Grond J, Chen C, Saba Y, van der Lugt A, Bastin ME, Windham BG, Cheng CY, Pirpamer L, Kantarci K, Himali JJ, Yang Q, Morris Z, Beiser AS, Tozer DJ, Vernooij MW, Amin N, Beekman M, Koh JY, Stott DJ, Houlden H, Schmidt R, Gottesman RF, MacKinnon AD, DeCarli C, Gudnason V, Deary IJ, van Duijn CM, Slagboom PE, Wong TY, Rost NS, Jukema JW, Mosley TH, Werring DJ, Schmidt H, Wardlaw JM, Ikram MA, Seshadri S, Launer LJ, Markus HS. Association of common genetic variants with brain microbleeds: A genome-wide association study. Neurology 2020; 95:e3331-e3343. [PMID: 32913026 PMCID: PMC7836652 DOI: 10.1212/wnl.0000000000010852] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 08/03/2020] [Indexed: 02/07/2023] Open
Abstract
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 APOE 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 APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21-1.45]; p = 2.5 × 10-10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; p = 1.0 × 10-6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; p = 0.68). APOE 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 APOE region are associated with the presence of BMB, most likely due to the APOE 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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Li S, Weinstein G, Zare H, Teumer A, Völker U, Friedrich N, Knol MJ, Satizabal CL, Petyuk VA, Adams HHH, Launer LJ, Bennett DA, De Jager PL, Grabe HJ, Ikram MA, Gudnason V, Yang Q, Seshadri S. The genetics of circulating BDNF: towards understanding the role of BDNF in brain structure and function in middle and old ages. Brain Commun 2020; 2:fcaa176. [PMID: 33345186 PMCID: PMC7734441 DOI: 10.1093/braincomms/fcaa176] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 07/16/2020] [Accepted: 07/17/2020] [Indexed: 01/04/2023] Open
Abstract
Brain-derived neurotrophic factor (BDNF) plays an important role in brain development and function. Substantial amounts of BDNF are present in peripheral blood, and may serve as biomarkers for Alzheimer’s disease incidence as well as targets for intervention to reduce Alzheimer’s disease risk. With the exception of the genetic polymorphism in the BDNF gene, Val66Met, which has been extensively studied with regard to neurodegenerative diseases, the genetic variation that influences circulating BDNF levels is unknown. We aimed to explore the genetic determinants of circulating BDNF levels in order to clarify its mechanistic involvement in brain structure and function and Alzheimer’s disease pathophysiology in middle-aged and old adults. Thus, we conducted a meta-analysis of genome-wide association study of circulating BDNF in 11 785 middle- and old-aged individuals of European ancestry from the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES), the Framingham Heart Study (FHS), the Rotterdam Study and the Study of Health in Pomerania (SHIP-Trend). Furthermore, we performed functional annotation analysis and related the genetic polymorphism influencing circulating BDNF to common Alzheimer’s disease pathologies from brain autopsies. Mendelian randomization was conducted to examine the possible causal role of circulating BDNF levels with various phenotypes including cognitive function, stroke, diabetes, cardiovascular disease, physical activity and diet patterns. Gene interaction networks analysis was also performed. The estimated heritability of BDNF levels was 30% (standard error = 0.0246, P-value = 4 × 10−48). We identified seven novel independent loci mapped near the BDNF gene and in BRD3, CSRNP1, KDELC2, RUNX1 (two single-nucleotide polymorphisms) and BDNF-AS. The expression of BDNF was associated with neurofibrillary tangles in brain tissues from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). Seven additional genes (ACAT1, ATM, NPAT, WDR48, TTC21A, SCN114 and COX7B) were identified through expression and protein quantitative trait loci analyses. Mendelian randomization analyses indicated a potential causal role of BDNF in cardioembolism. Lastly, Ingenuity Pathway Analysis placed circulating BDNF levels in four major networks. Our study provides novel insights into genes and molecular pathways associated with circulating BDNF levels and highlights the possible involvement of plaque instability as an underlying mechanism linking BDNF with brain neurodegeneration. These findings provide a foundation for a better understanding of BDNF regulation and function in the context of brain aging and neurodegenerative pathophysiology.
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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, Fornage M, Paus T, Debette S, Ikram MA, Schmidt H, Schmidt R, Seshadri S. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults. Nat Commun 2020; 11:4796. [PMID: 32963231 PMCID: PMC7508833 DOI: 10.1038/s41467-020-18367-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 08/20/2020] [Indexed: 12/22/2022] Open
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. Cortex morphology varies with age, cognitive function, and in neurological and psychiatric diseases. Here the authors report 160 genome-wide significant associations with thickness, surface area and volume of the total cortex and 34 cortical regions from a GWAS meta-analysis in 22,824 adults.
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de Leeuw FA, Karamujić-Čomić H, Tijms BM, Peeters CFW, Kester MI, Scheltens P, Ahmad S, Vojinovic D, Adams HHH, Hankemeier T, Bos D, van der Lugt A, Vernooij MW, Ikram MA, Amin N, Barkhof F, Teunissen CE, van Duijn CM, van der Flier WM. Circulating metabolites are associated with brain atrophy and white matter hyperintensities. Alzheimers Dement 2020; 17:205-214. [PMID: 32886448 PMCID: PMC7984157 DOI: 10.1002/alz.12180] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 07/25/2020] [Accepted: 08/08/2020] [Indexed: 01/01/2023]
Abstract
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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Belbin O, Morgan K, Medway C, Warden D, Cortina-Borja M, van Duijn CM, Adams HHH, Frank-Garcia A, Brookes K, Sánchez-Juan P, Alvarez V, Heun R, Kölsch H, Coto E, Kehoe PG, Rodriguez-Rodriguez E, Bullido MJ, Ikram MA, Smith AD, Lehmann DJ. The Epistasis Project: A Multi-Cohort Study of the Effects of BDNF, DBH, and SORT1 Epistasis on Alzheimer's Disease Risk. J Alzheimers Dis 2020; 68:1535-1547. [PMID: 30909233 DOI: 10.3233/jad-181116] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
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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Uleman JF, Melis RJF, Quax R, van der Zee EA, Thijssen D, Dresler M, van de Rest O, van der Velpen IF, Adams HHH, Schmand B, de Kok IMCM, de Bresser J, Richard E, Verbeek M, Hoekstra AG, Rouwette EAJA, Olde Rikkert MGM. Mapping the multicausality of Alzheimer's disease through group model building. GeroScience 2020; 43:829-843. [PMID: 32780293 PMCID: PMC8110634 DOI: 10.1007/s11357-020-00228-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 07/06/2020] [Indexed: 12/02/2022] Open
Abstract
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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Cras TY, Bos D, Ikram MA, Vergouwen MDI, Dippel DWJ, Voortman T, Adams HHH, Vernooij MW, Roozenbeek B. Determinants of the Presence and Size of Intracranial Aneurysms in the General Population: The Rotterdam Study. Stroke 2020; 51:2103-2110. [PMID: 32517578 PMCID: PMC7306261 DOI: 10.1161/strokeaha.120.029296] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Supplemental Digital Content is available in the text. 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.
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