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Gunz P, Tilot AK, Wittfeld K, Teumer A, Shapland CY, van Erp TGM, Dannemann M, Vernot B, Neubauer S, Guadalupe T, Fernández G, Brunner HG, Enard W, Fallon J, Hosten N, Völker U, Profico A, Di Vincenzo F, Manzi G, Kelso J, St Pourcain B, Hublin JJ, Franke B, Pääbo S, Macciardi F, Grabe HJ, Fisher SE. Neandertal Introgression Sheds Light on Modern Human Endocranial Globularity. Curr Biol 2019; 29:895. [PMID: 30836076 DOI: 10.1016/j.cub.2019.02.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Fornage M, Adams HH, Bis JC, Deary IJ, Launer L, Smith JA, Teumer A, Seshadri S. Abstract WP216: Epigenome-Wide Association Study of Cerebral White Matter Hyperintensities. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.wp216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Cerebral white matter hyperintensities (WMH) on MRI are typical markers of small vessel disease and strong radiological correlates of stroke and age-related cognitive decline. Despite a recognized high heritability, the molecular basis of WMH has not been fully characterized. In particular, the contribution of epigenetic modifications, such as DNA methylation, has not been explored.
Methods:
We conducted a meta-analysis of epigenome-wide association studies of WMH burden in up to 5777 elderly participants of European and African ancestry from 9 population-based cohorts using blood-derived DNA methylation measured on the Infinium HumanMethylation450 BeadChip. Cohort-specific associations between burden of WMH and DNA methylation beta values were estimated using linear mixed-effect models and combined in a sample-size weighted fixed-effect meta-analysis. In addition, we used two different approaches to identify differentially methylated regions (DMRs), which may be more informative than individual loci. Bonferroni correction and False Discovery Rates were used to account for the multiple tests.
Results:
Single-site analyses identified a CpG site within the CLDN5 gene significantly associated with WMH (P= 2.3x10
-7
). Claudin-5 is an endothelial-specific component in the brain vasculature and regulates blood brain barrier permeability. Region-based analyses, which leverage the correlations between nearby CpG sites identified several DMRs significantly associated with WMH burden including: PRMT1, BTBD17, and IFITM10 (P=1.4x10
-10
, 2.3x10
-8
, and 3.6x10
-7
, respectively). PRMT1 encodes the Protein Arginine N-methylase 1, which methylates histones in genes involved in glioblastomagenesis. Mice lacking this gene are characterized by severe defects in oligodendrocyte maturation processes. The function of BTBD17 and IFITM10 is not characterized but both are expressed in the brain and exhibit changes in expression in response to viral infection.
Conclusions:
Consistent with our previously reported genetic association studies, this genome-wide DNA methylation analysis supports a role of genes involved in glial cell function in WMH etiology. It also suggests a novel role of genes involved in viral response.
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Dörr M, Hamburg NM, Müller C, Smith NL, Gustafsson S, Lehtimäki T, Teumer A, Zeller T, Li X, Lind L, Raitakari OT, Völker U, Blankenberg S, McKnight B, Morris AP, Kähönen M, Lemaitre RN, Wild PS, Nauck M, Völzke H, Münzel T, Mitchell GF, Psaty BM, Lindgren CM, Larson MG, Felix SB, Ingelsson E, Lyytikäinen LP, Herrington D, Benjamin EJ, Schnabel RB. Common Genetic Variation in Relation to Brachial Vascular Dimensions and Flow-Mediated Vasodilation. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2019; 12:e002409. [PMID: 30779634 PMCID: PMC7835110 DOI: 10.1161/circgen.118.002409] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Chauhan G, Adams HHH, Satizabal CL, Bis JC, Teumer A, Sargurupremraj M, Hofer E, Trompet S, Hilal S, Smith AV, Jian X, Malik R, Traylor M, Pulit SL, Amouyel P, Mazoyer B, Zhu YC, Kaffashian S, Schilling S, Beecham GW, Montine TJ, Schellenberg GD, Kjartansson O, Guðnason V, Knopman DS, Griswold ME, Windham BG, Gottesman RF, Mosley TH, Schmidt R, Saba Y, Schmidt H, Takeuchi F, Yamaguchi S, Nabika T, Kato N, Rajan KB, Aggarwal NT, De Jager PL, Evans DA, Psaty BM, Rotter JI, Rice K, Lopez OL, Liao J, Chen C, Cheng CY, Wong TY, Ikram MK, van der Lee SJ, Amin N, Chouraki V, DeStefano AL, Aparicio HJ, Romero JR, Maillard P, DeCarli C, Wardlaw JM, Hernández MDCV, Luciano M, Liewald D, Deary IJ, Starr JM, Bastin ME, Muñoz Maniega S, Slagboom PE, Beekman M, Deelen J, Uh HW, Lemmens R, Brodaty H, Wright MJ, Ames D, Boncoraglio GB, Hopewell JC, Beecham AH, Blanton SH, Wright CB, Sacco RL, Wen W, Thalamuthu A, Armstrong NJ, Chong E, Schofield PR, Kwok JB, van der Grond J, Stott DJ, Ford I, Jukema JW, Vernooij MW, Hofman A, Uitterlinden AG, van der Lugt A, Wittfeld K, Grabe HJ, Hosten N, von Sarnowski B, Völker U, Levi C, Jimenez-Conde J, Sharma P, Sudlow CLM, Rosand J, Woo D, Cole JW, Meschia JF, Slowik A, Thijs V, Lindgren A, Melander O, Grewal RP, Rundek T, Rexrode K, Rothwell PM, Arnett DK, Jern C, Johnson JA, Benavente OR, Wasssertheil-Smoller S, Lee JM, Wong Q, Mitchell BD, Rich SS, McArdle PF, Geerlings MI, van der Graaf Y, de Bakker PIW, Asselbergs FW, Srikanth V, Thomson R, McWhirter R, Moran C, Callisaya M, Phan T, Rutten-Jacobs LCA, Bevan S, Tzourio C, Mather KA, Sachdev PS, van Duijn CM, Worrall BB, Dichgans M, Kittner SJ, Markus HS, Ikram MA, Fornage M, Launer LJ, Seshadri S, Longstreth WT, Debette S. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting. Neurology 2019; 92:e486-e503. [PMID: 30651383 PMCID: PMC6369905 DOI: 10.1212/wnl.0000000000006851] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Accepted: 10/01/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. METHODS We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. RESULTS The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. CONCLUSION In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.
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Kraja AT, Liu C, Fetterman JL, Graff M, Have CT, Gu C, Yanek LR, Feitosa MF, Arking DE, Chasman DI, Young K, Ligthart S, Hill WD, Weiss S, Luan J, Giulianini F, Li-Gao R, Hartwig FP, Lin SJ, Wang L, Richardson TG, Yao J, Fernandez EP, Ghanbari M, Wojczynski MK, Lee WJ, Argos M, Armasu SM, Barve RA, Ryan KA, An P, Baranski TJ, Bielinski SJ, Bowden DW, Broeckel U, Christensen K, Chu AY, Corley J, Cox SR, Uitterlinden AG, Rivadeneira F, Cropp CD, Daw EW, van Heemst D, de Las Fuentes L, Gao H, Tzoulaki I, Ahluwalia TS, de Mutsert R, Emery LS, Erzurumluoglu AM, Perry JA, Fu M, Forouhi NG, Gu Z, Hai Y, Harris SE, Hemani G, Hunt SC, Irvin MR, Jonsson AE, Justice AE, Kerrison ND, Larson NB, Lin KH, Love-Gregory LD, Mathias RA, Lee JH, Nauck M, Noordam R, Ong KK, Pankow J, Patki A, Pattie A, Petersmann A, Qi Q, Ribel-Madsen R, Rohde R, Sandow K, Schnurr TM, Sofer T, Starr JM, Taylor AM, Teumer A, Timpson NJ, de Haan HG, Wang Y, Weeke PE, Williams C, Wu H, Yang W, Zeng D, Witte DR, Weir BS, Wareham NJ, Vestergaard H, Turner ST, Torp-Pedersen C, Stergiakouli E, Sheu WHH, Rosendaal FR, Ikram MA, Franco OH, Ridker PM, Perls TT, Pedersen O, Nohr EA, Newman AB, Linneberg A, Langenberg C, Kilpeläinen TO, Kardia SLR, Jørgensen ME, Jørgensen T, Sørensen TIA, Homuth G, Hansen T, Goodarzi MO, Deary IJ, Christensen C, Chen YDI, Chakravarti A, Brandslund I, Bonnelykke K, Taylor KD, Wilson JG, Rodriguez S, Davies G, Horta BL, Thyagarajan B, Rao DC, Grarup N, Davila-Roman VG, Hudson G, Guo X, Arnett DK, Hayward C, Vaidya D, Mook-Kanamori DO, Tiwari HK, Levy D, Loos RJF, Dehghan A, Elliott P, Malik AN, Scott RA, Becker DM, de Andrade M, Province MA, Meigs JB, Rotter JI, North KE. Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits. Am J Hum Genet 2019; 104:112-138. [PMID: 30595373 PMCID: PMC6323610 DOI: 10.1016/j.ajhg.2018.12.001] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Accepted: 12/06/2018] [Indexed: 12/16/2022] Open
Abstract
Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.
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Gunz P, Tilot AK, Wittfeld K, Teumer A, Shapland CY, van Erp TGM, Dannemann M, Vernot B, Neubauer S, Guadalupe T, Fernández G, Brunner HG, Enard W, Fallon J, Hosten N, Völker U, Profico A, Di Vincenzo F, Manzi G, Kelso J, St Pourcain B, Hublin JJ, Franke B, Pääbo S, Macciardi F, Grabe HJ, Fisher SE. Neandertal Introgression Sheds Light on Modern Human Endocranial Globularity. Curr Biol 2018; 29:120-127.e5. [PMID: 30554901 PMCID: PMC6380688 DOI: 10.1016/j.cub.2018.10.065] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 09/21/2018] [Accepted: 10/31/2018] [Indexed: 12/15/2022]
Abstract
One of the features that distinguishes modern humans from our extinct relatives and ancestors is a globular shape of the braincase [1-4]. As the endocranium closely mirrors the outer shape of the brain, these differences might reflect altered neural architecture [4, 5]. However, in the absence of fossil brain tissue, the underlying neuroanatomical changes as well as their genetic bases remain elusive. To better understand the biological foundations of modern human endocranial shape, we turn to our closest extinct relatives: the Neandertals. Interbreeding between modern humans and Neandertals has resulted in introgressed fragments of Neandertal DNA in the genomes of present-day non-Africans [6, 7]. Based on shape analyses of fossil skull endocasts, we derive a measure of endocranial globularity from structural MRI scans of thousands of modern humans and study the effects of introgressed fragments of Neandertal DNA on this phenotype. We find that Neandertal alleles on chromosomes 1 and 18 are associated with reduced endocranial globularity. These alleles influence expression of two nearby genes, UBR4 and PHLPP1, which are involved in neurogenesis and myelination, respectively. Our findings show how integration of fossil skull data with archaic genomics and neuroimaging can suggest developmental mechanisms that may contribute to the unique modern human endocranial shape.
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Franceschini N, Giambartolomei C, de Vries PS, Finan C, Bis JC, Huntley RP, Lovering RC, Tajuddin SM, Winkler TW, Graff M, Kavousi M, Dale C, Smith AV, Hofer E, van Leeuwen EM, Nolte IM, Lu L, Scholz M, Sargurupremraj M, Pitkänen N, Franzén O, Joshi PK, Noordam R, Marioni RE, Hwang SJ, Musani SK, Schminke U, Palmas W, Isaacs A, Correa A, Zonderman AB, Hofman A, Teumer A, Cox AJ, Uitterlinden AG, Wong A, Smit AJ, Newman AB, Britton A, Ruusalepp A, Sennblad B, Hedblad B, Pasaniuc B, Penninx BW, Langefeld CD, Wassel CL, Tzourio C, Fava C, Baldassarre D, O'Leary DH, Teupser D, Kuh D, Tremoli E, Mannarino E, Grossi E, Boerwinkle E, Schadt EE, Ingelsson E, Veglia F, Rivadeneira F, Beutner F, Chauhan G, Heiss G, Snieder H, Campbell H, Völzke H, Markus HS, Deary IJ, Jukema JW, de Graaf J, Price J, Pott J, Hopewell JC, Liang J, Thiery J, Engmann J, Gertow K, Rice K, Taylor KD, Dhana K, Kiemeney LALM, Lind L, Raffield LM, Launer LJ, Holdt LM, Dörr M, Dichgans M, Traylor M, Sitzer M, Kumari M, Kivimaki M, Nalls MA, Melander O, Raitakari O, Franco OH, Rueda-Ochoa OL, Roussos P, Whincup PH, Amouyel P, Giral P, Anugu P, Wong Q, Malik R, Rauramaa R, Burkhardt R, Hardy R, Schmidt R, de Mutsert R, Morris RW, Strawbridge RJ, Wannamethee SG, Hägg S, Shah S, McLachlan S, Trompet S, Seshadri S, Kurl S, Heckbert SR, Ring S, Harris TB, Lehtimäki T, Galesloot TE, Shah T, de Faire U, Plagnol V, Rosamond WD, Post W, Zhu X, Zhang X, Guo X, Saba Y, Dehghan A, Seldenrijk A, Morrison AC, Hamsten A, Psaty BM, van Duijn CM, Lawlor DA, Mook-Kanamori DO, Bowden DW, Schmidt H, Wilson JF, Wilson JG, Rotter JI, Wardlaw JM, Deanfield J, Halcox J, Lyytikäinen LP, Loeffler M, Evans MK, Debette S, Humphries SE, Völker U, Gudnason V, Hingorani AD, Björkegren JLM, Casas JP, O'Donnell CJ. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes. Nat Commun 2018; 9:5141. [PMID: 30510157 PMCID: PMC6277418 DOI: 10.1038/s41467-018-07340-5] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 09/24/2018] [Indexed: 02/08/2023] Open
Abstract
Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.
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Parmar P, Lowry E, Cugliari G, Suderman M, Wilson R, Karhunen V, Andrew T, Wiklund P, Wielscher M, Guarrera S, Teumer A, Lehne B, Milani L, de Klein N, Mishra PP, Melton PE, Mandaviya PR, Kasela S, Nano J, Zhang W, Zhang Y, Uitterlinden AG, Peters A, Schöttker B, Gieger C, Anderson D, Boomsma DI, Grabe HJ, Panico S, Veldink JH, van Meurs JBJ, van den Berg L, Beilin LJ, Franke L, Loh M, van Greevenbroek MMJ, Nauck M, Kähönen M, Hurme MA, Raitakari OT, Franco OH, Slagboom PE, van der Harst P, Kunze S, Felix SB, Zhang T, Chen W, Mori TA, Bonnefond A, Heijmans BT, Muka T, Kooner JS, Fischer K, Waldenberger M, Froguel P, Huang RC, Lehtimäki T, Rathmann W, Relton CL, Matullo G, Brenner H, Verweij N, Li S, Chambers JC, Järvelin MR, Sebert S. Association of maternal prenatal smoking GFI1-locus and cardio-metabolic phenotypes in 18,212 adults. EBioMedicine 2018; 38:206-216. [PMID: 30442561 PMCID: PMC6306313 DOI: 10.1016/j.ebiom.2018.10.066] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 10/26/2018] [Accepted: 10/26/2018] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND DNA methylation at the GFI1-locus has been repeatedly associated with exposure to smoking from the foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure to maternal prenatal smoking with offspring's adult cardio-metabolic health. METHODS We meta-analysed the association between DNA methylation at GFI1-locus with maternal prenatal smoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe, Australia, and USA (n = 18,212). DNA methylation at the GFI1-locus was measured in whole-blood. Multivariable regression models were fitted to examine its association with exposure to prenatal and own adult smoking. DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fasting glucose (FG), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), diastolic, and systolic blood pressure (BP). FINDINGS Lower DNA methylation at three out of eight GFI1-CpGs was associated with exposure to maternal prenatal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation at cg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when adjusted for sex, age, and adult smoking with Bonferroni-corrected P < 0·012. In contrast, lower DNA methylation at cg09935388, the strongest adult own smoking locus, was associated with decreased BMI, WC, and BP (adjusted 1 × 10-7 < P < 0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, and cg18146737 was associated with decreased BMI and WC (5 × 10-8 < P < 0.001). Lower DNA methylation at all the CpGs was consistently associated with higher TG levels. INTERPRETATION Epigenetic changes at the GFI1 were linked to smoking exposure in-utero/in-adulthood and robustly associated with cardio-metabolic risk factors. FUND: European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595 DynaHEALTH.
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Teumer A, Gambaro G, Corre T, Bochud M, Vollenweider P, Guessous I, Kleber ME, Delgado GE, Pilz S, März W, Barnes CLK, Joshi PK, Wilson JF, de Borst MH, Navis G, van der Harst P, Heerspink HJL, Homuth G, Endlich K, Nauck M, Köttgen A, Pattaro C, Ferraro PM. Negative effect of vitamin D on kidney function: a Mendelian randomization study. Nephrol Dial Transplant 2018; 33:2139-2145. [PMID: 29718335 PMCID: PMC6275146 DOI: 10.1093/ndt/gfy074] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Accepted: 02/23/2018] [Indexed: 01/08/2023] Open
Abstract
Background The kidney plays a central role in the regulation of vitamin D metabolism. It is not clear, however, whether vitamin D influences kidney function. Previous studies have reported conflicting results, which may have been influenced by reverse causation and residual confounding. We conducted a Mendelian randomization (MR) study to obtain unconfounded estimates of the association between genetically instrumented vitamin D metabolites and estimated glomerular filtration rate (eGFR) as well as the urinary albumin:creatinine ratio (UACR). Methods We performed a two-sample MR study based on three single nucleotide variants associated with 25(OH)D levels: rs2282679, rs10741657 and rs12785878, related to the genes GC, CYP2R1 and DHCR7, respectively. Estimates of the allele-dependent effects on serum 25(OH)D and eGFR/UACR were obtained from summary statistics of published genome-wide association meta-analyses. Additionally, we performed a one-sample MR analysis for both 25(OH)D and 1,25(OH)2 D using individual-level data from six cohorts. Results The combined MR estimate supported a negative causal effect of log transformed 25(OH)D on log transformed eGFR (β = -0.013, P = 0.003). The analysis of individual-level data confirmed the main findings and also revealed a significant association of 1,25(OH)2 D on eGFR (β = -0.094, P = 0.008). These results show that a 10% increase in serum 25(OH)D levels causes a 0.3% decrease in eGFR. There was no effect of 25(OH)D on UACR (β = 0.032, P = 0.265). Conclusion Our study suggests that circulating vitamin D metabolite levels are negatively associated with eGFR. Further studies are needed to elucidate the underlying mechanisms.
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Tan VY, Biernacka KM, Dudding T, Bonilla C, Gilbert R, Kaplan RC, Qibin Q, Teumer A, Martin RM, Perks CM, Timpson NJ, Holly JMP. Reassessing the Association between Circulating Vitamin D and IGFBP-3: Observational and Mendelian Randomization Estimates from Independent Sources. Cancer Epidemiol Biomarkers Prev 2018; 27:1462-1471. [PMID: 30072546 PMCID: PMC6837868 DOI: 10.1158/1055-9965.epi-18-0113] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 06/18/2018] [Accepted: 06/19/2018] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Circulating insulin-like growth factor binding protein 3 (IGFBP-3) has been associated with prostate cancer. Preclinical studies found that vitamin D regulates IGFBP-3 expression, although evidence from epidemiologic studies is conflicting. METHODS Mendelian randomization analyses (MR) were conducted to reassess associations between IGFBP-3 and prostate cancer risk and advanced prostate cancer using summary statistics from the PRACTICAL consortium (44,825 cases; 27,904 controls). Observational and MR analyses were conducted to assess the relationship between inactive vitamin D [25(OH)D] and IGFBP-3 using data from the ProtecT study (1,366 cases;1,071 controls) and summary statistics from the CHARGE consortium (n = 18,995). RESULTS The OR for prostate cancer per SD unit increase in circulating IGFBP-3 was 1.14 [95% confidence interval (CI), 1.02-1.28]. The OR for advanced prostate cancer per SD unit increase in IGFBP-3 was 1.22 (95% CI, 1.07-1.40). Observationally, a SD increase in 25(OH)D was associated with a 0.1SD (95% CI, 0.05-0.14) increase in IGFBP-3. MR analyses found little evidence for a causal relationship between circulating 25(OH)D and IGFBP-3 in the circulation. CONCLUSIONS This study provided confirmatory evidence that IGFBP-3 is a risk factor for prostate cancer risk and progression. Observationally, there was evidence that 25(OH)D is associated with IGFBP-3, but MR analyses suggested that these findings were unlikely to be causal. Findings may be limited by the nature of instrumentation of 25(OH)D and IGFBP-3 and the utility of circulating measures. 25(OH)D appears unlikely to be causally related to IGFBP-3 in the circulation, however, our findings do not preclude causal associations at the tissue level. IMPACT IGFBP-3 is a prostate cancer risk factor but 25(OH)D are unlikely to be causally related to IGFBP-3 in the circulation.
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Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, Ntritsos G, Dimou N, Cabrera CP, Karaman I, Ng FL, Evangelou M, Witkowska K, Tzanis E, Hellwege JN, Giri A, Velez Edwards DR, Sun YV, Cho K, Gaziano JM, Wilson PWF, Tsao PS, Kovesdy CP, Esko T, Mägi R, Milani L, Almgren P, Boutin T, Debette S, Ding J, Giulianini F, Holliday EG, Jackson AU, Li-Gao R, Lin WY, Luan J, Mangino M, Oldmeadow C, Prins BP, Qian Y, Sargurupremraj M, Shah N, Surendran P, Thériault S, Verweij N, Willems SM, Zhao JH, Amouyel P, Connell J, de Mutsert R, Doney ASF, Farrall M, Menni C, Morris AD, Noordam R, Paré G, Poulter NR, Shields DC, Stanton A, Thom S, Abecasis G, Amin N, Arking DE, Ayers KL, Barbieri CM, Batini C, Bis JC, Blake T, Bochud M, Boehnke M, Boerwinkle E, Boomsma DI, Bottinger EP, Braund PS, Brumat M, Campbell A, Campbell H, Chakravarti A, Chambers JC, Chauhan G, Ciullo M, Cocca M, Collins F, Cordell HJ, Davies G, de Borst MH, de Geus EJ, Deary IJ, Deelen J, Del Greco M F, Demirkale CY, Dörr M, Ehret GB, Elosua R, Enroth S, Erzurumluoglu AM, Ferreira T, Frånberg M, Franco OH, Gandin I, Gasparini P, Giedraitis V, Gieger C, Girotto G, Goel A, Gow AJ, Gudnason V, Guo X, Gyllensten U, Hamsten A, Harris TB, Harris SE, Hartman CA, Havulinna AS, Hicks AA, Hofer E, Hofman A, Hottenga JJ, Huffman JE, Hwang SJ, Ingelsson E, James A, Jansen R, Jarvelin MR, Joehanes R, Johansson Å, Johnson AD, Joshi PK, Jousilahti P, Jukema JW, Jula A, Kähönen M, Kathiresan S, Keavney BD, Khaw KT, Knekt P, Knight J, Kolcic I, Kooner JS, Koskinen S, Kristiansson K, Kutalik Z, Laan M, Larson M, Launer LJ, Lehne B, Lehtimäki T, Liewald DCM, Lin L, Lind L, Lindgren CM, Liu Y, Loos RJF, Lopez LM, Lu Y, Lyytikäinen LP, Mahajan A, Mamasoula C, Marrugat J, Marten J, Milaneschi Y, Morgan A, Morris AP, Morrison AC, Munson PJ, Nalls MA, Nandakumar P, Nelson CP, Niiranen T, Nolte IM, Nutile T, Oldehinkel AJ, Oostra BA, O'Reilly PF, Org E, Padmanabhan S, Palmas W, Palotie A, Pattie A, Penninx BWJH, Perola M, Peters A, Polasek O, Pramstaller PP, Nguyen QT, Raitakari OT, Ren M, Rettig R, Rice K, Ridker PM, Ried JS, Riese H, Ripatti S, Robino A, Rose LM, Rotter JI, Rudan I, Ruggiero D, Saba Y, Sala CF, Salomaa V, Samani NJ, Sarin AP, Schmidt R, Schmidt H, Shrine N, Siscovick D, Smith AV, Snieder H, Sõber S, Sorice R, Starr JM, Stott DJ, Strachan DP, Strawbridge RJ, Sundström J, Swertz MA, Taylor KD, Teumer A, Tobin MD, Tomaszewski M, Toniolo D, Traglia M, Trompet S, Tuomilehto J, Tzourio C, Uitterlinden AG, Vaez A, van der Most PJ, van Duijn CM, Vergnaud AC, Verwoert GC, Vitart V, Völker U, Vollenweider P, Vuckovic D, Watkins H, Wild SH, Willemsen G, Wilson JF, Wright AF, Yao J, Zemunik T, Zhang W, Attia JR, Butterworth AS, Chasman DI, Conen D, Cucca F, Danesh J, Hayward C, Howson JMM, Laakso M, Lakatta EG, Langenberg C, Melander O, Mook-Kanamori DO, Palmer CNA, Risch L, Scott RA, Scott RJ, Sever P, Spector TD, van der Harst P, Wareham NJ, Zeggini E, Levy D, Munroe PB, Newton-Cheh C, Brown MJ, Metspalu A, Hung AM, O'Donnell CJ, Edwards TL, Psaty BM, Tzoulaki I, Barnes MR, Wain LV, Elliott P, Caulfield MJ. Publisher Correction: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet 2018; 50:1755. [PMID: 30429575 DOI: 10.1038/s41588-018-0297-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
In the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper.
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Ligthart S, Vaez A, Võsa U, Stathopoulou MG, de Vries PS, Prins BP, Van der Most PJ, Tanaka T, Naderi E, Rose LM, Wu Y, Karlsson R, Barbalic M, Lin H, Pool R, Zhu G, Macé A, Sidore C, Trompet S, Mangino M, Sabater-Lleal M, Kemp JP, Abbasi A, Kacprowski T, Verweij N, Smith AV, Huang T, Marzi C, Feitosa MF, Lohman KK, Kleber ME, Milaneschi Y, Mueller C, Huq M, Vlachopoulou E, Lyytikäinen LP, Oldmeadow C, Deelen J, Perola M, Zhao JH, Feenstra B, Amini M, Lahti J, Schraut KE, Fornage M, Suktitipat B, Chen WM, Li X, Nutile T, Malerba G, Luan J, Bak T, Schork N, Del Greco M F, Thiering E, Mahajan A, Marioni RE, Mihailov E, Eriksson J, Ozel AB, Zhang W, Nethander M, Cheng YC, Aslibekyan S, Ang W, Gandin I, Yengo L, Portas L, Kooperberg C, Hofer E, Rajan KB, Schurmann C, den Hollander W, Ahluwalia TS, Zhao J, Draisma HHM, Ford I, Timpson N, Teumer A, Huang H, Wahl S, Liu Y, Huang J, Uh HW, Geller F, Joshi PK, Yanek LR, Trabetti E, Lehne B, Vozzi D, Verbanck M, Biino G, Saba Y, Meulenbelt I, O'Connell JR, Laakso M, Giulianini F, Magnusson PKE, Ballantyne CM, Hottenga JJ, Montgomery GW, Rivadineira F, Rueedi R, Steri M, Herzig KH, Stott DJ, Menni C, Frånberg M, St Pourcain B, Felix SB, Pers TH, Bakker SJL, Kraft P, Peters A, Vaidya D, Delgado G, Smit JH, Großmann V, Sinisalo J, Seppälä I, Williams SR, Holliday EG, Moed M, Langenberg C, Räikkönen K, Ding J, Campbell H, Sale MM, Chen YDI, James AL, Ruggiero D, Soranzo N, Hartman CA, Smith EN, Berenson GS, Fuchsberger C, Hernandez D, Tiesler CMT, Giedraitis V, Liewald D, Fischer K, Mellström D, Larsson A, Wang Y, Scott WR, Lorentzon M, Beilby J, Ryan KA, Pennell CE, Vuckovic D, Balkau B, Concas MP, Schmidt R, Mendes de Leon CF, Bottinger EP, Kloppenburg M, Paternoster L, Boehnke M, Musk AW, Willemsen G, Evans DM, Madden PAF, Kähönen M, Kutalik Z, Zoledziewska M, Karhunen V, Kritchevsky SB, Sattar N, Lachance G, Clarke R, Harris TB, Raitakari OT, Attia JR, van Heemst D, Kajantie E, Sorice R, Gambaro G, Scott RA, Hicks AA, Ferrucci L, Standl M, Lindgren CM, Starr JM, Karlsson M, Lind L, Li JZ, Chambers JC, Mori TA, de Geus EJCN, Heath AC, Martin NG, Auvinen J, Buckley BM, de Craen AJM, Waldenberger M, Strauch K, Meitinger T, Scott RJ, McEvoy M, Beekman M, Bombieri C, Ridker PM, Mohlke KL, Pedersen NL, Morrison AC, Boomsma DI, Whitfield JB, Strachan DP, Hofman A, Vollenweider P, Cucca F, Jarvelin MR, Jukema JW, Spector TD, Hamsten A, Zeller T, Uitterlinden AG, Nauck M, Gudnason V, Qi L, Grallert H, Borecki IB, Rotter JI, März W, Wild PS, Lokki ML, Boyle M, Salomaa V, Melbye M, Eriksson JG, Wilson JF, Penninx BWJH, Becker DM, Worrall BB, Gibson G, Krauss RM, Ciullo M, Zaza G, Wareham NJ, Oldehinkel AJ, Palmer LJ, Murray SS, Pramstaller PP, Bandinelli S, Heinrich J, Ingelsson E, Deary IJ, Mägi R, Vandenput L, van der Harst P, Desch KC, Kooner JS, Ohlsson C, Hayward C, Lehtimäki T, Shuldiner AR, Arnett DK, Beilin LJ, Robino A, Froguel P, Pirastu M, Jess T, Koenig W, Loos RJF, Evans DA, Schmidt H, Smith GD, Slagboom PE, Eiriksdottir G, Morris AP, Psaty BM, Tracy RP, Nolte IM, Boerwinkle E, Visvikis-Siest S, Reiner AP, Gross M, Bis JC, Franke L, Franco OH, Benjamin EJ, Chasman DI, Dupuis J, Snieder H, Dehghan A, Alizadeh BZ. Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. Am J Hum Genet 2018; 103:691-706. [PMID: 30388399 PMCID: PMC6218410 DOI: 10.1016/j.ajhg.2018.09.009] [Citation(s) in RCA: 253] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 09/20/2018] [Indexed: 02/07/2023] Open
Abstract
C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10-8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.
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Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, Ntritsos G, Dimou N, Cabrera CP, Karaman I, Ng FL, Evangelou M, Witkowska K, Tzanis E, Hellwege JN, Giri A, Velez Edwards DR, Sun YV, Cho K, Gaziano JM, Wilson PWF, Tsao PS, Kovesdy CP, Esko T, Mägi R, Milani L, Almgren P, Boutin T, Debette S, Ding J, Giulianini F, Holliday EG, Jackson AU, Li-Gao R, Lin WY, Luan J, Mangino M, Oldmeadow C, Prins BP, Qian Y, Sargurupremraj M, Shah N, Surendran P, Thériault S, Verweij N, Willems SM, Zhao JH, Amouyel P, Connell J, de Mutsert R, Doney ASF, Farrall M, Menni C, Morris AD, Noordam R, Paré G, Poulter NR, Shields DC, Stanton A, Thom S, Abecasis G, Amin N, Arking DE, Ayers KL, Barbieri CM, Batini C, Bis JC, Blake T, Bochud M, Boehnke M, Boerwinkle E, Boomsma DI, Bottinger EP, Braund PS, Brumat M, Campbell A, Campbell H, Chakravarti A, Chambers JC, Chauhan G, Ciullo M, Cocca M, Collins F, Cordell HJ, Davies G, de Borst MH, de Geus EJ, Deary IJ, Deelen J, Del Greco M F, Demirkale CY, Dörr M, Ehret GB, Elosua R, Enroth S, Erzurumluoglu AM, Ferreira T, Frånberg M, Franco OH, Gandin I, Gasparini P, Giedraitis V, Gieger C, Girotto G, Goel A, Gow AJ, Gudnason V, Guo X, Gyllensten U, Hamsten A, Harris TB, Harris SE, Hartman CA, Havulinna AS, Hicks AA, Hofer E, Hofman A, Hottenga JJ, Huffman JE, Hwang SJ, Ingelsson E, James A, Jansen R, Jarvelin MR, Joehanes R, Johansson Å, Johnson AD, Joshi PK, Jousilahti P, Jukema JW, Jula A, Kähönen M, Kathiresan S, Keavney BD, Khaw KT, Knekt P, Knight J, Kolcic I, Kooner JS, Koskinen S, Kristiansson K, Kutalik Z, Laan M, Larson M, Launer LJ, Lehne B, Lehtimäki T, Liewald DCM, Lin L, Lind L, Lindgren CM, Liu Y, Loos RJF, Lopez LM, Lu Y, Lyytikäinen LP, Mahajan A, Mamasoula C, Marrugat J, Marten J, Milaneschi Y, Morgan A, Morris AP, Morrison AC, Munson PJ, Nalls MA, Nandakumar P, Nelson CP, Niiranen T, Nolte IM, Nutile T, Oldehinkel AJ, Oostra BA, O'Reilly PF, Org E, Padmanabhan S, Palmas W, Palotie A, Pattie A, Penninx BWJH, Perola M, Peters A, Polasek O, Pramstaller PP, Nguyen QT, Raitakari OT, Ren M, Rettig R, Rice K, Ridker PM, Ried JS, Riese H, Ripatti S, Robino A, Rose LM, Rotter JI, Rudan I, Ruggiero D, Saba Y, Sala CF, Salomaa V, Samani NJ, Sarin AP, Schmidt R, Schmidt H, Shrine N, Siscovick D, Smith AV, Snieder H, Sõber S, Sorice R, Starr JM, Stott DJ, Strachan DP, Strawbridge RJ, Sundström J, Swertz MA, Taylor KD, Teumer A, Tobin MD, Tomaszewski M, Toniolo D, Traglia M, Trompet S, Tuomilehto J, Tzourio C, Uitterlinden AG, Vaez A, van der Most PJ, van Duijn CM, Vergnaud AC, Verwoert GC, Vitart V, Völker U, Vollenweider P, Vuckovic D, Watkins H, Wild SH, Willemsen G, Wilson JF, Wright AF, Yao J, Zemunik T, Zhang W, Attia JR, Butterworth AS, Chasman DI, Conen D, Cucca F, Danesh J, Hayward C, Howson JMM, Laakso M, Lakatta EG, Langenberg C, Melander O, Mook-Kanamori DO, Palmer CNA, Risch L, Scott RA, Scott RJ, Sever P, Spector TD, van der Harst P, Wareham NJ, Zeggini E, Levy D, Munroe PB, Newton-Cheh C, Brown MJ, Metspalu A, Hung AM, O'Donnell CJ, Edwards TL, Psaty BM, Tzoulaki I, Barnes MR, Wain LV, Elliott P, Caulfield MJ. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet 2018; 50:1412-1425. [PMID: 30224653 PMCID: PMC6284793 DOI: 10.1038/s41588-018-0205-x] [Citation(s) in RCA: 737] [Impact Index Per Article: 122.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 07/09/2018] [Indexed: 02/07/2023]
Abstract
High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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Jackson VE, Latourelle JC, Wain LV, Smith AV, Grove ML, Bartz TM, Obeidat M, Province MA, Gao W, Qaiser B, Porteous DJ, Cassano PA, Ahluwalia TS, Grarup N, Li J, Altmaier E, Marten J, Harris SE, Manichaikul A, Pottinger TD, Li-Gao R, Lind-Thomsen A, Mahajan A, Lahousse L, Imboden M, Teumer A, Prins B, Lyytikäinen LP, Eiriksdottir G, Franceschini N, Sitlani CM, Brody JA, Bossé Y, Timens W, Kraja A, Loukola A, Tang W, Liu Y, Bork-Jensen J, Justesen JM, Linneberg A, Lange LA, Rawal R, Karrasch S, Huffman JE, Smith BH, Davies G, Burkart KM, Mychaleckyj JC, Bonten TN, Enroth S, Lind L, Brusselle GG, Kumar A, Stubbe B, Kähönen M, Wyss AB, Psaty BM, Heckbert SR, Hao K, Rantanen T, Kritchevsky SB, Lohman K, Skaaby T, Pisinger C, Hansen T, Schulz H, Polasek O, Campbell A, Starr JM, Rich SS, Mook-Kanamori DO, Johansson Å, Ingelsson E, Uitterlinden AG, Weiss S, Raitakari OT, Gudnason V, North KE, Gharib SA, Sin DD, Taylor KD, O'Connor GT, Kaprio J, Harris TB, Pederson O, Vestergaard H, Wilson JG, Strauch K, Hayward C, Kerr S, Deary IJ, Barr RG, de Mutsert R, Gyllensten U, Morris AP, Ikram MA, Probst-Hensch N, Gläser S, Zeggini E, Lehtimäki T, Strachan DP, Dupuis J, Morrison AC, Hall IP, Tobin MD, London SJ. Meta-analysis of exome array data identifies six novel genetic loci for lung function. Wellcome Open Res 2018; 3:4. [PMID: 30175238 PMCID: PMC6081985 DOI: 10.12688/wellcomeopenres.12583.3] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/03/2018] [Indexed: 01/05/2023] Open
Abstract
Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV 1), forced vital capacity (FVC) and the ratio of FEV 1 to FVC (FEV 1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P<2·8x10 -7) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs ( SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.
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van Setten J, Brody JA, Jamshidi Y, Swenson BR, Butler AM, Campbell H, Del Greco FM, Evans DS, Gibson Q, Gudbjartsson DF, Kerr KF, Krijthe BP, Lyytikäinen LP, Müller C, Müller-Nurasyid M, Nolte IM, Padmanabhan S, Ritchie MD, Robino A, Smith AV, Steri M, Tanaka T, Teumer A, Trompet S, Ulivi S, Verweij N, Yin X, Arnar DO, Asselbergs FW, Bader JS, Barnard J, Bis J, Blankenberg S, Boerwinkle E, Bradford Y, Buckley BM, Chung MK, Crawford D, den Hoed M, Denny JC, Dominiczak AF, Ehret GB, Eijgelsheim M, Ellinor PT, Felix SB, Franco OH, Franke L, Harris TB, Holm H, Ilaria G, Iorio A, Kähönen M, Kolcic I, Kors JA, Lakatta EG, Launer LJ, Lin H, Lin HJ, Loos RJF, Lubitz SA, Macfarlane PW, Magnani JW, Leach IM, Meitinger T, Mitchell BD, Munzel T, Papanicolaou GJ, Peters A, Pfeufer A, Pramstaller PP, Raitakari OT, Rotter JI, Rudan I, Samani NJ, Schlessinger D, Silva Aldana CT, Sinner MF, Smith JD, Snieder H, Soliman EZ, Spector TD, Stott DJ, Strauch K, Tarasov KV, Thorsteinsdottir U, Uitterlinden AG, Van Wagoner DR, Völker U, Völzke H, Waldenberger M, Jan Westra H, Wild PS, Zeller T, Alonso A, Avery CL, Bandinelli S, Benjamin EJ, Cucca F, Dörr M, Ferrucci L, Gasparini P, Gudnason V, Hayward C, Heckbert SR, Hicks AA, Jukema JW, Kääb S, Lehtimäki T, Liu Y, Munroe PB, Parsa A, Polasek O, Psaty BM, Roden DM, Schnabel RB, Sinagra G, Stefansson K, Stricker BH, van der Harst P, van Duijn CM, Wilson JF, Gharib SA, de Bakker PIW, Isaacs A, Arking DE, Sotoodehnia N. PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity. Nat Commun 2018; 9:2904. [PMID: 30046033 PMCID: PMC6060178 DOI: 10.1038/s41467-018-04766-9] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Accepted: 05/21/2018] [Indexed: 12/24/2022] Open
Abstract
Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genome-wide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are over-represented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of ~105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ion-channel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development.
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Raman MR, Katharina W, Conner SC, Teumer A, Nauck M, Hosten N, DeCarli CS, Vasan RS, Beiser AS, Himali JJ, Seshadri S, Grabe HJ, Satizabal CL. P3‐237: IGF‐1 AND IGFBP‐3 ASSOCIATIONS WITH BRAIN MRI: META‐ANALYSIS IN MIDDLE‐AGED ADULTS FROM THE FRAMINGHAM HEART STUDY AND STUDY OF HEALTH IN POMERANIA. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.1596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Bakhsh AD, Ladas I, Hamshere ML, Bullock M, Kirov G, Zhang L, Taylor PN, Gregory JW, Scott-Coombes D, Völzke H, Teumer A, Mantripragada K, Williams ED, Clifton-Bligh RJ, Williams NM, Ludgate ME. An InDel in Phospholipase-C-B-1 Is Linked with Euthyroid Multinodular Goiter. Thyroid 2018; 28:891-901. [PMID: 29897006 DOI: 10.1089/thy.2017.0312] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
BACKGROUND Euthyroid multinodular goiter (MNG) is common, but little is known about the genetic variations conferring predisposition. Previously, a family with MNG of adolescent onset was reported in which some family members developed papillary thyroid carcinomas (PTC). METHODS Genome-wide linkage analysis and next-generation sequencing were conducted to identify genetic variants that may confer disease predisposition. A multipoint nonparametric LOD score of 3.01 was obtained, covering 19 cM on chromosome 20p. Haplotype analysis reduced the region of interest to 10 cM. RESULTS Analysis of copy number variation identified an intronic InDel (∼1000 bp) in the PLCB1 gene in all eight affected family members and carriers (an unaffected person who has inherited the genetic trait). This InDel is present in approximately 1% of "healthy" Caucasians. Next-generation sequencing of the region identified no additional disease-associated variant, suggesting a possible role of the InDel. Since PLCB1 contributes to thyrocyte growth regulation, the InDel was investigated in relevant Caucasian cohorts. It was detected in 0/70 PTC but 4/81 unrelated subjects with MNG (three females; age at thyroidectomy 27-59 years; no family history of MNG/PTC). The InDel frequency is significantly higher in MNG subjects compared to controls (χ2 = 5.076; p = 0.024. PLCB1 transcript levels were significantly higher in thyroids with the InDel than without (p < 0.02). CONCLUSIONS The intronic PLCB1 InDel is the first variant found in familial multiple papilloid adenomata-type MNG and in a subset of patients with sporadic MNG. It may function through overexpression, and increased PLC activity has been reported in thyroid neoplasms. The potential role of the deletion as a biomarker to identify MNG patients more likely to progress to PTC merits exploration.
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Fornage M, Adams HH, Bis JC, Boerwinkle E, Deary IJ, Grabe HJ, Hou L, Ikram MA, Jhun MA, Launer LJ, Luciano M, Seshadri S, Smith JA, Sotoodehnia N, Teumer A, Yang Q. O3‐03‐03: EPIGENOME‐WIDE ASSOCIATION STUDIES IMPLICATE GENES INVOLVED IN GLIAL CELL FUNCTION AND VIRAL RESPONSE IN CEREBRAL WHITE MATTER HYPERINTENSITIES. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.2784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Roselli C, Chaffin MD, Weng LC, Aeschbacher S, Ahlberg G, Albert CM, Almgren P, Alonso A, Anderson CD, Aragam KG, Arking DE, Barnard J, Bartz TM, Benjamin EJ, Bihlmeyer NA, Bis JC, Bloom HL, Boerwinkle E, Bottinger EB, Brody JA, Calkins H, Campbell A, Cappola TP, Carlquist J, Chasman DI, Chen LY, Chen YDI, Choi EK, Choi SH, Christophersen IE, Chung MK, Cole JW, Conen D, Cook J, Crijns HJ, Cutler MJ, Damrauer SM, Daniels BR, Darbar D, Delgado G, Denny JC, Dichgans M, Dörr M, Dudink EA, Dudley SC, Esa N, Esko T, Eskola M, Fatkin D, Felix SB, Ford I, Franco OH, Geelhoed B, Grewal RP, Gudnason V, Guo X, Gupta N, Gustafsson S, Gutmann R, Hamsten A, Harris TB, Hayward C, Heckbert SR, Hernesniemi J, Hocking LJ, Hofman A, Horimoto ARVR, Huang J, Huang PL, Huffman J, Ingelsson E, Ipek EG, Ito K, Jimenez-Conde J, Johnson R, Jukema JW, Kääb S, Kähönen M, Kamatani Y, Kane JP, Kastrati A, Kathiresan S, Katschnig-Winter P, Kavousi M, Kessler T, Kietselaer BL, Kirchhof P, Kleber ME, Knight S, Krieger JE, Kubo M, Launer LJ, Laurikka J, Lehtimäki T, Leineweber K, Lemaitre RN, Li M, Lim HE, Lin HJ, Lin H, Lind L, Lindgren CM, Lokki ML, London B, Loos RJF, Low SK, Lu Y, Lyytikäinen LP, Macfarlane PW, Magnusson PK, Mahajan A, Malik R, Mansur AJ, Marcus GM, Margolin L, Margulies KB, März W, McManus DD, Melander O, Mohanty S, Montgomery JA, Morley MP, Morris AP, Müller-Nurasyid M, Natale A, Nazarian S, Neumann B, Newton-Cheh C, Niemeijer MN, Nikus K, Nilsson P, Noordam R, Oellers H, Olesen MS, Orho-Melander M, Padmanabhan S, Pak HN, Paré G, Pedersen NL, Pera J, Pereira A, Porteous D, Psaty BM, Pulit SL, Pullinger CR, Rader DJ, Refsgaard L, Ribasés M, Ridker PM, Rienstra M, Risch L, Roden DM, Rosand J, Rosenberg MA, Rost N, Rotter JI, Saba S, Sandhu RK, Schnabel RB, Schramm K, Schunkert H, Schurman C, Scott SA, Seppälä I, Shaffer C, Shah S, Shalaby AA, Shim J, Shoemaker MB, Siland JE, Sinisalo J, Sinner MF, Slowik A, Smith AV, Smith BH, Smith JG, Smith JD, Smith NL, Soliman EZ, Sotoodehnia N, Stricker BH, Sun A, Sun H, Svendsen JH, Tanaka T, Tanriverdi K, Taylor KD, Teder-Laving M, Teumer A, Thériault S, Trompet S, Tucker NR, Tveit A, Uitterlinden AG, Van Der Harst P, Van Gelder IC, Van Wagoner DR, Verweij N, Vlachopoulou E, Völker U, Wang B, Weeke PE, Weijs B, Weiss R, Weiss S, Wells QS, Wiggins KL, Wong JA, Woo D, Worrall BB, Yang PS, Yao J, Yoneda ZT, Zeller T, Zeng L, Lubitz SA, Lunetta KL, Ellinor PT. Multi-ethnic genome-wide association study for atrial fibrillation. Nat Genet 2018; 50:1225-1233. [PMID: 29892015 PMCID: PMC6136836 DOI: 10.1038/s41588-018-0133-9] [Citation(s) in RCA: 445] [Impact Index Per Article: 74.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 04/18/2018] [Indexed: 12/13/2022]
Abstract
Atrial fibrillation (AF) affects more than 33 million individuals worldwide1 and has a complex heritability2. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.
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Teumer A. Common Methods for Performing Mendelian Randomization. Front Cardiovasc Med 2018; 5:51. [PMID: 29892602 PMCID: PMC5985452 DOI: 10.3389/fcvm.2018.00051] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 05/04/2018] [Indexed: 11/13/2022] Open
Abstract
Mendelian randomization (MR) is a framework for assessing causal inference using cross-sectional data in combination with genetic information. This paper summarizes statistical methods commonly applied and strait forward to use for conducting MR analyses including those taking advantage of the rich dataset of SNP-trait associations that were revealed in the last decade through large-scale genome-wide association studies. Using these data, powerful MR studies are possible. However, the causal estimate may be biased in case the assumptions of MR are violated. The source and the type of this bias are described while providing a summary of the mathematical formulas that should help estimating the magnitude and direction of the potential bias depending on the specific research setting. Finally, methods for relaxing the assumptions and for conducting sensitivity analyses are discussed. Future researches in the field of MR include the assessment of non-linear causal effects, and automatic detection of invalid instruments.
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Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, Guo X, Hendricks AE, Karaderi T, Lempradl A, Locke AE, Mahajan A, Marouli E, Sivapalaratnam S, Young KL, Alfred T, Feitosa MF, Masca NGD, Manning AK, Medina-Gomez C, Mudgal P, Ng MCY, Reiner AP, Vedantam S, Willems SM, Winkler TW, Abecasis G, Aben KK, Alam DS, Alharthi SE, Allison M, Amouyel P, Asselbergs FW, Auer PL, Balkau B, Bang LE, Barroso I, Bastarache L, Benn M, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Brumat M, Burt AA, Butterworth AS, Campbell PT, Cappellani S, Carey DJ, Catamo E, Caulfield MJ, Chambers JC, Chasman DI, Chen YDI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Corominas Galbany J, Cox AJ, Crosslin DS, Cuellar-Partida G, D'Eustacchio A, Danesh J, Davies G, Bakker PIW, Groot MCH, Mutsert R, Deary IJ, Dedoussis G, Demerath EW, Heijer M, Hollander AI, Ruijter HM, Dennis JG, Denny JC, Di Angelantonio E, Drenos F, Du M, Dubé MP, Dunning AM, Easton DF, Edwards TL, Ellinghaus D, Ellinor PT, Elliott P, Evangelou E, Farmaki AE, Farooqi IS, Faul JD, Fauser S, Feng S, Ferrannini E, Ferrieres J, Florez JC, Ford I, Fornage M, Franco OH, Franke A, Franks PW, Friedrich N, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Gibson J, Giedraitis V, Gjesing AP, Gordon-Larsen P, Gorski M, Grabe HJ, Grant SFA, Grarup N, Griffiths HL, Grove ML, Gudnason V, Gustafsson S, Haessler J, Hakonarson H, Hammerschlag AR, Hansen T, Harris KM, Harris TB, Hattersley AT, Have CT, Hayward C, He L, Heard-Costa NL, Heath AC, Heid IM, Helgeland Ø, Hernesniemi J, Hewitt AW, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Huang PL, Huffman JE, Ikram MA, Ingelsson E, Jackson AU, Jansson JH, Jarvik GP, Jensen GB, Jia Y, Johansson S, Jørgensen ME, Jørgensen T, Jukema JW, Kahali B, Kahn RS, Kähönen M, Kamstrup PR, Kanoni S, Kaprio J, Karaleftheri M, Kardia SLR, Karpe F, Kathiresan S, Kee F, Kiemeney LA, Kim E, Kitajima H, Komulainen P, Kooner JS, Kooperberg C, Korhonen T, Kovacs P, Kuivaniemi H, Kutalik Z, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange EM, Lange LA, Langenberg C, Larson EB, Lee NR, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin H, Lin KH, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu CT, Liu DJ, Liu Y, Lo KS, Lophatananon A, Lotery AJ, Loukola A, Luan J, Lubitz SA, Lyytikäinen LP, Männistö S, Marenne G, Mazul AL, McCarthy MI, McKean-Cowdin R, Medland SE, Meidtner K, Milani L, Mistry V, Mitchell P, Mohlke KL, Moilanen L, Moitry M, Montgomery GW, Mook-Kanamori DO, Moore C, Mori TA, Morris AD, Morris AP, Müller-Nurasyid M, Munroe PB, Nalls MA, Narisu N, Nelson CP, Neville M, Nielsen SF, Nikus K, Njølstad PR, Nordestgaard BG, Nyholt DR, O'Connel JR, O'Donoghue ML, Olde Loohuis LM, Ophoff RA, Owen KR, Packard CJ, Padmanabhan S, Palmer CNA, Palmer ND, Pasterkamp G, Patel AP, Pattie A, Pedersen O, Peissig PL, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers TH, Person TN, Peters A, Petersen ERB, Peyser PA, Pirie A, Polasek O, Polderman TJ, Puolijoki H, Raitakari OT, Rasheed A, Rauramaa R, Reilly DF, Renström F, Rheinberger M, Ridker PM, Rioux JD, Rivas MA, Roberts DJ, Robertson NR, Robino A, Rolandsson O, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Sapkota Y, Sattar N, Schoen RE, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe MP, Shah SH, Sheu WHH, Sim X, Slater AJ, Small KS, Smith AV, Southam L, Spector TD, Speliotes EK, Starr JM, Stefansson K, Steinthorsdottir V, Stirrups KE, Strauch K, Stringham HM, Stumvoll M, Sun L, Surendran P, Swift AJ, Tada H, Tansey KE, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorleifsson G, Thorsteinsdottir U, Thuesen BH, Tönjes A, Tromp G, Trompet S, Tsafantakis E, Tuomilehto J, Tybjaerg-Hansen A, Tyrer JP, Uher R, Uitterlinden AG, Uusitupa M, Laan SW, Duijn CM, Leeuwen N, van Setten J, Vanhala M, Varbo A, Varga TV, Varma R, Velez Edwards DR, Vermeulen SH, Veronesi G, Vestergaard H, Vitart V, Vogt TF, Völker U, Vuckovic D, Wagenknecht LE, Walker M, Wallentin L, Wang F, Wang CA, Wang S, Wang Y, Ware EB, Wareham NJ, Warren HR, Waterworth DM, Wessel J, White HD, Willer CJ, Wilson JG, Witte DR, Wood AR, Wu Y, Yaghootkar H, Yao J, Yao P, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zhao W, Zhou W, Zondervan KT, Rotter JI, Pospisilik JA, Rivadeneira F, Borecki IB, Deloukas P, Frayling TM, Lettre G, North KE, Lindgren CM, Hirschhorn JN, Loos RJF. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet 2018; 50:766-767. [PMID: 29549330 DOI: 10.1038/s41588-018-0082-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, Guo X, Hendricks AE, Karaderi T, Lempradl A, Locke AE, Mahajan A, Marouli E, Sivapalaratnam S, Young KL, Alfred T, Feitosa MF, Masca NGD, Manning AK, Medina-Gomez C, Mudgal P, Ng MCY, Reiner AP, Vedantam S, Willems SM, Winkler TW, Abecasis G, Aben KK, Alam DS, Alharthi SE, Allison M, Amouyel P, Asselbergs FW, Auer PL, Balkau B, Bang LE, Barroso I, Bastarache L, Benn M, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Brumat M, Burt AA, Butterworth AS, Campbell PT, Cappellani S, Carey DJ, Catamo E, Caulfield MJ, Chambers JC, Chasman DI, Chen YDI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Corominas Galbany J, Cox AJ, Crosslin DS, Cuellar-Partida G, D'Eustacchio A, Danesh J, Davies G, Bakker PIW, Groot MCH, Mutsert R, Deary IJ, Dedoussis G, Demerath EW, Heijer M, Hollander AI, Ruijter HM, Dennis JG, Denny JC, Angelantonio E, Drenos F, Du M, Dubé MP, Dunning AM, Easton DF, Edwards TL, Ellinghaus D, Ellinor PT, Elliott P, Evangelou E, Farmaki AE, Farooqi IS, Faul JD, Fauser S, Feng S, Ferrannini E, Ferrieres J, Florez JC, Ford I, Fornage M, Franco OH, Franke A, Franks PW, Friedrich N, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Gibson J, Giedraitis V, Gjesing AP, Gordon-Larsen P, Gorski M, Grabe HJ, Grant SFA, Grarup N, Griffiths HL, Grove ML, Gudnason V, Gustafsson S, Haessler J, Hakonarson H, Hammerschlag AR, Hansen T, Harris KM, Harris TB, Hattersley AT, Have CT, Hayward C, He L, Heard-Costa NL, Heath AC, Heid IM, Helgeland Ø, Hernesniemi J, Hewitt AW, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Huang PL, Huffman JE, Ikram MA, Ingelsson E, Jackson AU, Jansson JH, Jarvik GP, Jensen GB, Jia Y, Johansson S, Jørgensen ME, Jørgensen T, Jukema JW, Kahali B, Kahn RS, Kähönen M, Kamstrup PR, Kanoni S, Kaprio J, Karaleftheri M, Kardia SLR, Karpe F, Kathiresan S, Kee F, Kiemeney LA, Kim E, Kitajima H, Komulainen P, Kooner JS, Kooperberg C, Korhonen T, Kovacs P, Kuivaniemi H, Kutalik Z, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange EM, Lange LA, Langenberg C, Larson EB, Lee NR, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin H, Lin KH, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu CT, Liu DJ, Liu Y, Lo KS, Lophatananon A, Lotery AJ, Loukola A, Luan J, Lubitz SA, Lyytikäinen LP, Männistö S, Marenne G, Mazul AL, McCarthy MI, McKean-Cowdin R, Medland SE, Meidtner K, Milani L, Mistry V, Mitchell P, Mohlke KL, Moilanen L, Moitry M, Montgomery GW, Mook-Kanamori DO, Moore C, Mori TA, Morris AD, Morris AP, Müller-Nurasyid M, Munroe PB, Nalls MA, Narisu N, Nelson CP, Neville M, Nielsen SF, Nikus K, Njølstad PR, Nordestgaard BG, Nyholt DR, O'Connel JR, O'Donoghue ML, Olde Loohuis LM, Ophoff RA, Owen KR, Packard CJ, Padmanabhan S, Palmer CNA, Palmer ND, Pasterkamp G, Patel AP, Pattie A, Pedersen O, Peissig PL, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers TH, Person TN, Peters A, Petersen ERB, Peyser PA, Pirie A, Polasek O, Polderman TJ, Puolijoki H, Raitakari OT, Rasheed A, Rauramaa R, Reilly DF, Renström F, Rheinberger M, Ridker PM, Rioux JD, Rivas MA, Roberts DJ, Robertson NR, Robino A, Rolandsson O, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Sapkota Y, Sattar N, Schoen RE, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe MP, Shah SH, Sheu WHH, Sim X, Slater AJ, Small KS, Smith AV, Southam L, Spector TD, Speliotes EK, Starr JM, Stefansson K, Steinthorsdottir V, Stirrups KE, Strauch K, Stringham HM, Stumvoll M, Sun L, Surendran P, Swift AJ, Tada H, Tansey KE, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorleifsson G, Thorsteinsdottir U, Thuesen BH, Tönjes A, Tromp G, Trompet S, Tsafantakis E, Tuomilehto J, Tybjaerg-Hansen A, Tyrer JP, Uher R, Uitterlinden AG, Uusitupa M, Laan SW, Duijn CM, Leeuwen N, van Setten J, Vanhala M, Varbo A, Varga TV, Varma R, Velez Edwards DR, Vermeulen SH, Veronesi G, Vestergaard H, Vitart V, Vogt TF, Völker U, Vuckovic D, Wagenknecht LE, Walker M, Wallentin L, Wang F, Wang CA, Wang S, Wang Y, Ware EB, Wareham NJ, Warren HR, Waterworth DM, Wessel J, White HD, Willer CJ, Wilson JG, Witte DR, Wood AR, Wu Y, Yaghootkar H, Yao J, Yao P, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zhou W, Zondervan KT, Rotter JI, Pospisilik JA, Rivadeneira F, Borecki IB, Deloukas P, Frayling TM, Lettre G, North KE, Lindgren CM, Hirschhorn JN, Loos RJF. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet 2018; 50:765-766. [PMID: 29549329 DOI: 10.1038/s41588-018-0050-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.
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Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, Adams MJ, Agerbo E, Air TM, Andlauer TMF, Bacanu SA, Bækvad-Hansen M, Beekman AFT, Bigdeli TB, Binder EB, Blackwood DRH, Bryois J, Buttenschøn HN, Bybjerg-Grauholm J, Cai N, Castelao E, Christensen JH, Clarke TK, Coleman JIR, Colodro-Conde L, Couvy-Duchesne B, Craddock N, Crawford GE, Crowley CA, Dashti HS, Davies G, Deary IJ, Degenhardt F, Derks EM, Direk N, Dolan CV, Dunn EC, Eley TC, Eriksson N, Escott-Price V, Kiadeh FHF, Finucane HK, Forstner AJ, Frank J, Gaspar HA, Gill M, Giusti-Rodríguez P, Goes FS, Gordon SD, Grove J, Hall LS, Hannon E, Hansen CS, Hansen TF, Herms S, Hickie IB, Hoffmann P, Homuth G, Horn C, Hottenga JJ, Hougaard DM, Hu M, Hyde CL, Ising M, Jansen R, Jin F, Jorgenson E, Knowles JA, Kohane IS, Kraft J, Kretzschmar WW, Krogh J, Kutalik Z, Lane JM, Li Y, Li Y, Lind PA, Liu X, Lu L, MacIntyre DJ, MacKinnon DF, Maier RM, Maier W, Marchini J, Mbarek H, McGrath P, McGuffin P, Medland SE, Mehta D, Middeldorp CM, Mihailov E, Milaneschi Y, Milani L, Mill J, Mondimore FM, Montgomery GW, Mostafavi S, Mullins N, Nauck M, Ng B, Nivard MG, Nyholt DR, O'Reilly PF, Oskarsson H, Owen MJ, Painter JN, Pedersen CB, Pedersen MG, Peterson RE, Pettersson E, Peyrot WJ, Pistis G, Posthuma D, Purcell SM, Quiroz JA, Qvist P, Rice JP, Riley BP, Rivera M, Saeed Mirza S, Saxena R, Schoevers R, Schulte EC, Shen L, Shi J, Shyn SI, Sigurdsson E, Sinnamon GBC, Smit JH, Smith DJ, Stefansson H, Steinberg S, Stockmeier CA, Streit F, Strohmaier J, Tansey KE, Teismann H, Teumer A, Thompson W, Thomson PA, Thorgeirsson TE, Tian C, Traylor M, Treutlein J, Trubetskoy V, Uitterlinden AG, Umbricht D, Van der Auwera S, van Hemert AM, Viktorin A, Visscher PM, Wang Y, Webb BT, Weinsheimer SM, Wellmann J, Willemsen G, Witt SH, Wu Y, Xi HS, Yang J, Zhang F, Arolt V, Baune BT, Berger K, Boomsma DI, Cichon S, Dannlowski U, de Geus ECJ, DePaulo JR, Domenici E, Domschke K, Esko T, Grabe HJ, Hamilton SP, Hayward C, Heath AC, Hinds DA, Kendler KS, Kloiber S, Lewis G, Li QS, Lucae S, Madden PFA, Magnusson PK, Martin NG, McIntosh AM, Metspalu A, Mors O, Mortensen PB, Müller-Myhsok B, Nordentoft M, Nöthen MM, O'Donovan MC, Paciga SA, Pedersen NL, Penninx BWJH, Perlis RH, Porteous DJ, Potash JB, Preisig M, Rietschel M, Schaefer C, Schulze TG, Smoller JW, Stefansson K, Tiemeier H, Uher R, Völzke H, Weissman MM, Werge T, Winslow AR, Lewis CM, Levinson DF, Breen G, Børglum AD, Sullivan PF. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet 2018; 50:668-681. [PMID: 29700475 PMCID: PMC5934326 DOI: 10.1038/s41588-018-0090-3] [Citation(s) in RCA: 1669] [Impact Index Per Article: 278.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 02/14/2018] [Indexed: 12/12/2022]
Abstract
Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
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Chen H, Cade BE, Gleason KJ, Bjonnes AC, Stilp AM, Sofer T, Conomos MP, Ancoli-Israel S, Arens R, Azarbarzin A, Bell GI, Below JE, Chun S, Evans DS, Ewert R, Frazier-Wood AC, Gharib SA, Haba-Rubio J, Hagen EW, Heinzer R, Hillman DR, Johnson WC, Kutalik Z, Lane JM, Larkin EK, Lee SK, Liang J, Loredo JS, Mukherjee S, Palmer LJ, Papanicolaou GJ, Penzel T, Peppard PE, Post WS, Ramos AR, Rice K, Rotter JI, Sands SA, Shah NA, Shin C, Stone KL, Stubbe B, Sul JH, Tafti M, Taylor KD, Teumer A, Thornton TA, Tranah GJ, Wang C, Wang H, Warby SC, Wellman DA, Zee PC, Hanis CL, Laurie CC, Gottlieb DJ, Patel SR, Zhu X, Sunyaev SR, Saxena R, Lin X, Redline S. Multiethnic Meta-Analysis Identifies RAI1 as a Possible Obstructive Sleep Apnea-related Quantitative Trait Locus in Men. Am J Respir Cell Mol Biol 2018; 58:391-401. [PMID: 29077507 PMCID: PMC5854957 DOI: 10.1165/rcmb.2017-0237oc] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 10/24/2017] [Indexed: 12/19/2022] Open
Abstract
Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single ethnic groups, and a large proportion of the heritability remains unexplained. The apnea-hypopnea index (AHI) is a commonly used quantitative measure characterizing OSA severity. Because OSA differs by sex, and the pathophysiology of obstructive events differ in rapid eye movement (REM) and non-REM (NREM) sleep, we hypothesized that additional genetic association signals would be identified by analyzing the NREM/REM-specific AHI and by conducting sex-specific analyses in multiethnic samples. We performed genome-wide association tests for up to 19,733 participants of African, Asian, European, and Hispanic/Latino American ancestry in 7 studies. We identified rs12936587 on chromosome 17 as a possible quantitative trait locus for NREM AHI in men (N = 6,737; P = 1.7 × 10-8) but not in women (P = 0.77). The association with NREM AHI was replicated in a physiological research study (N = 67; P = 0.047). This locus overlapping the RAI1 gene and encompassing genes PEMT1, SREBF1, and RASD1 was previously reported to be associated with coronary artery disease, lipid metabolism, and implicated in Potocki-Lupski syndrome and Smith-Magenis syndrome, which are characterized by abnormal sleep phenotypes. We also identified gene-by-sex interactions in suggestive association regions, suggesting that genetic variants for AHI appear to vary by sex, consistent with the clinical observations of strong sexual dimorphism.
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Eriksson AL, Perry JRB, Coviello AD, Delgado GE, Ferrucci L, Hoffman AR, Huhtaniemi IT, Ikram MA, Karlsson MK, Kleber ME, Laughlin GA, Liu Y, Lorentzon M, Lunetta KL, Mellström D, Murabito JM, Murray A, Nethander M, Nielson CM, Prokopenko I, Pye SR, Raffel LJ, Rivadeneira F, Srikanth P, Stolk L, Teumer A, Travison TG, Uitterlinden AG, Vaidya D, Vanderschueren D, Zmuda JM, März W, Orwoll ES, Ouyang P, Vandenput L, Wu FCW, de Jong FH, Bhasin S, Kiel DP, Ohlsson C. Genetic Determinants of Circulating Estrogen Levels and Evidence of a Causal Effect of Estradiol on Bone Density in Men. J Clin Endocrinol Metab 2018; 103:991-1004. [PMID: 29325096 PMCID: PMC5868407 DOI: 10.1210/jc.2017-02060] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2017] [Accepted: 01/04/2018] [Indexed: 12/24/2022]
Abstract
Context Serum estradiol (E2) and estrone (E1) levels exhibit substantial heritability. Objective To investigate the genetic regulation of serum E2 and E1 in men. Design, Setting, and Participants Genome-wide association study in 11,097 men of European origin from nine epidemiological cohorts. Main Outcome Measures Genetic determinants of serum E2 and E1 levels. Results Variants in/near CYP19A1 demonstrated the strongest evidence for association with E2, resolving to three independent signals. Two additional independent signals were found on the X chromosome; FAMily with sequence similarity 9, member B (FAM9B), rs5934505 (P = 3.4 × 10-8) and Xq27.3, rs5951794 (P = 3.1 × 10-10). E1 signals were found in CYP19A1 (rs2899472, P = 5.5 × 10-23), in Tripartite motif containing 4 (TRIM4; rs17277546, P = 5.8 × 10-14), and CYP11B1/B2 (rs10093796, P = 1.2 × 10-8). E2 signals in CYP19A1 and FAM9B were associated with bone mineral density (BMD). Mendelian randomization analysis suggested a causal effect of serum E2 on BMD in men. A 1 pg/mL genetically increased E2 was associated with a 0.048 standard deviation increase in lumbar spine BMD (P = 2.8 × 10-12). In men and women combined, CYP19A1 alleles associated with higher E2 levels were associated with lower degrees of insulin resistance. Conclusions Our findings confirm that CYP19A1 is an important genetic regulator of E2 and E1 levels and strengthen the causal importance of E2 for bone health in men. We also report two independent loci on the X-chromosome for E2, and one locus each in TRIM4 and CYP11B1/B2, for E1.
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