351 results on '"Jarvelin, Mr"'
Search Results
102. Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes.
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Borges MC, Clayton GL, Freathy RM, Felix JF, Fernández-Sanlés A, Soares AG, Kilpi F, Yang Q, McEachan RRC, Richmond RC, Liu X, Skotte L, Irizar A, Hattersley AT, Bodinier B, Scholtens DM, Nohr EA, Bond TA, Hayes MG, West J, Tyrrell J, Wright J, Bouchard L, Murcia M, Bustamante M, Chadeau-Hyam M, Jarvelin MR, Vrijheid M, Perron P, Magnus P, Gaillard R, Jaddoe VWV, Lowe WL Jr, Feenstra B, Hivert MF, Sørensen TIA, Håberg SE, Serbert S, Magnus M, and Lawlor DA
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- Female, Humans, Infant, Newborn, Pregnancy, Body Mass Index, Cesarean Section, Mendelian Randomization Analysis, Diabetes, Gestational, Hypertension, Pregnancy-Induced epidemiology, Pre-Eclampsia epidemiology
- Abstract
Background: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear., Methods: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women., Results: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation., Conclusions: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications., Funding: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust., (© 2024. The Author(s).)
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- 2024
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103. Blood DNA methylation profiling identifies cathepsin Z dysregulation in pulmonary arterial hypertension.
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Ulrich A, Wu Y, Draisma H, Wharton J, Swietlik EM, Cebola I, Vasilaki E, Balkhiyarova Z, Jarvelin MR, Auvinen J, Herzig KH, Coghlan JG, Lordan J, Church C, Howard LS, Pepke-Zaba J, Toshner M, Wort SJ, Kiely DG, Condliffe R, Lawrie A, Gräf S, Morrell NW, Wilkins MR, Prokopenko I, and Rhodes CJ
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- Humans, Bone Morphogenetic Proteins, Cathepsin Z, DNA Methylation genetics, Endothelial Cells, Familial Primary Pulmonary Hypertension, Pulmonary Arterial Hypertension
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Pulmonary arterial hypertension (PAH) is characterised by pulmonary vascular remodelling causing premature death from right heart failure. Established DNA variants influence PAH risk, but susceptibility from epigenetic changes is unknown. We addressed this through epigenome-wide association study (EWAS), testing 865,848 CpG sites for association with PAH in 429 individuals with PAH and 1226 controls. Three loci, at Cathepsin Z (CTSZ, cg04917472), Conserved oligomeric Golgi complex 6 (COG6, cg27396197), and Zinc Finger Protein 678 (ZNF678, cg03144189), reached epigenome-wide significance (p < 10
-7 ) and are hypermethylated in PAH, including in individuals with PAH at 1-year follow-up. Of 16 established PAH genes, only cg10976975 in BMP10 shows hypermethylation in PAH. Hypermethylation at CTSZ is associated with decreased blood cathepsin Z mRNA levels. Knockdown of CTSZ expression in human pulmonary artery endothelial cells increases caspase-3/7 activity (p < 10-4 ). DNA methylation profiles are altered in PAH, exemplified by the pulmonary endothelial function modifier CTSZ, encoding protease cathepsin Z., (© 2024. The Author(s).)- Published
- 2024
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104. Epigenome-Wide Meta-analysis Reveals Associations Between Dietary Glycemic Index and Glycemic Load and DNA Methylation in Children and Adolescents of Different Body Sizes.
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Ott R, Stein R, Hauta-Alus HH, Ronkainen J, Fernández-Barrés S, Spielau U, Kirsten H, Poulain T, Melton PE, Küpers LK, Azaryah H, Colombo M, Landgraf K, Tobi EW, O'Sullivan T, Huang RC, Campoy C, Winkler C, Vioque J, Vrijheid M, Kiess W, Körner A, Sebert S, Jarvelin MR, Ziegler AG, and Hummel S
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- Humans, Child, Adolescent, Child, Preschool, Overweight, DNA Methylation genetics, Epigenome, Diet, Obesity, Proto-Oncogene Proteins, Adaptor Proteins, Signal Transducing, Glycemic Index physiology, Glycemic Load
- Abstract
Objective: Dietary glycemic index (GI) and glycemic load (GL) are associated with cardiometabolic health in children and adolescents, with potential distinct effects in people with increased BMI. DNA methylation (DNAm) may mediate these effects. Thus, we conducted meta-analyses of epigenome-wide association studies (EWAS) between dietary GI and GL and blood DNAm of children and adolescents., Research Design and Methods: We calculated dietary GI and GL and performed EWAS in children and adolescents (age range: 4.5-17 years) from six cohorts (N = 1,187). We performed stratified analyses of participants with normal weight (n = 801) or overweight or obesity (n = 386). We performed look-ups for the identified cytosine-phosphate-guanine (CpG) sites (false discovery rate [FDR] <0.05) with tissue-specific gene expression of 832 blood and 223 subcutaneous adipose tissue samples from children and adolescents., Results: Dietary GL was positively associated with DNAm of cg20274553 (FDR <0.05), annotated to WDR27. Several CpGs were identified in the normal-weight (GI: 85; GL: 17) and overweight or obese (GI: 136; GL: 298; FDR <0.05) strata, and none overlapped between strata. In participants with overweight or obesity, identified CpGs were related to RNA expression of genes associated with impaired metabolism (e.g., FRAT1, CSF3)., Conclusions: We identified 537 associations between dietary GI and GL and blood DNAm, mainly in children and adolescents with overweight or obesity. High-GI and/or -GL diets may influence epigenetic gene regulation and thereby promote metabolic derangements in young people with increased BMI., (© 2023 by the American Diabetes Association.)
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- 2023
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105. Associations of adolescents' diet and meal patterns with school performance in the Northern Finland Birth Cohort 1986: A Mendelian randomisation study.
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Zagkos L, Drenos F, Emmett P, Blakemore AI, Nordström T, Hurtig T, Jarvelin MR, and Dovey TM
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- Child, Humans, Adolescent, Follow-Up Studies, Cross-Sectional Studies, Finland, Diet, Feeding Behavior, Birth Cohort, Genome-Wide Association Study
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Background: Several observational studies indicate that dietary habits in children and adolescents are associated with school performance. These associations are heavily confounded by socio-economic characteristics, such as household income and parents' educational attainment, amongst other factors. The objective of this study was to explore the association between diet and school performance in adolescents from the Northern Finland Birth Cohort 1986 (NFBC1986)., Methods: Dietary and school performance data were collected using self-reported questionnaires from adolescents in the NFBC1986 cross-sectional, 16-year follow-up study. In this work we derived exploratory factors for the dietary variables, frequency of skipping main meals and school performance variables, performed genome-wide association studies (GWAS) against these factors to obtain genetic association data and conducted one-sample and two-sample Mendelian randomisation (MR) analyses using individual level data for up to 9220 adolescents in NFBC1986 and GWAS results from external cohorts. We report observational and MR effects of diet on school performance and cognition-related phenotypes., Results: The observational study and the one-sample Mendelian randomisation analysis showed that high fat, salt and sugar (HFSS) consumption was associated with poor school performance in general/science subjects (-0.080, -0.128 to -0.033) and staple food consumption with better school performance in general/science subjects (0.071, 0.024 to 0.119) and physical education (0.065, 0.021 to 0.110). Findings from our two-sample MR analysis identified dietary principal components described best as whole brain bread, wheat, cheese, oat cereal and red wine to be associated with higher educational attainment and other cognition-related phenotypes., Conclusion: Using genetics, we highlighted the potential role of HFSS food consumption and consumption of the components of a staple food diet for school performance. However, further research is required to find conclusive evidence that could support a causal role of diet on school performance., Competing Interests: Declaration of competing interest None declared., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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- 2023
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106. European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation.
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Budu-Aggrey A, Kilanowski A, Sobczyk MK, Shringarpure SS, Mitchell R, Reis K, Reigo A, Mägi R, Nelis M, Tanaka N, Brumpton BM, Thomas LF, Sole-Navais P, Flatley C, Espuela-Ortiz A, Herrera-Luis E, Lominchar JVT, Bork-Jensen J, Marenholz I, Arnau-Soler A, Jeong A, Fawcett KA, Baurecht H, Rodriguez E, Alves AC, Kumar A, Sleiman PM, Chang X, Medina-Gomez C, Hu C, Xu CJ, Qi C, El-Heis S, Titcombe P, Antoun E, Fadista J, Wang CA, Thiering E, Wu B, Kress S, Kothalawala DM, Kadalayil L, Duan J, Zhang H, Hadebe S, Hoffmann T, Jorgenson E, Choquet H, Risch N, Njølstad P, Andreassen OA, Johansson S, Almqvist C, Gong T, Ullemar V, Karlsson R, Magnusson PKE, Szwajda A, Burchard EG, Thyssen JP, Hansen T, Kårhus LL, Dantoft TM, Jeanrenaud ACSN, Ghauri A, Arnold A, Homuth G, Lau S, Nöthen MM, Hübner N, Imboden M, Visconti A, Falchi M, Bataille V, Hysi P, Ballardini N, Boomsma DI, Hottenga JJ, Müller-Nurasyid M, Ahluwalia TS, Stokholm J, Chawes B, Schoos AM, Esplugues A, Bustamante M, Raby B, Arshad S, German C, Esko T, Milani LA, Metspalu A, Terao C, Abuabara K, Løset M, Hveem K, Jacobsson B, Pino-Yanes M, Strachan DP, Grarup N, Linneberg A, Lee YA, Probst-Hensch N, Weidinger S, Jarvelin MR, Melén E, Hakonarson H, Irvine AD, Jarvis D, Nijsten T, Duijts L, Vonk JM, Koppelmann GH, Godfrey KM, Barton SJ, Feenstra B, Pennell CE, Sly PD, Holt PG, Williams LK, Bisgaard H, Bønnelykke K, Curtin J, Simpson A, Murray C, Schikowski T, Bunyavanich S, Weiss ST, Holloway JW, Min JL, Brown SJ, Standl M, and Paternoster L
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- Humans, Genetic Predisposition to Disease genetics, Hispanic or Latino genetics, Black People, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Dermatitis, Atopic genetics
- Abstract
Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities., (© 2023. Springer Nature Limited.)
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- 2023
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107. Author Correction: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.
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Shrine N, Izquierdo AG, Chen J, Packer R, Hall RJ, Guyatt AL, Batini C, Thompson RJ, Pavuluri C, Malik V, Hobbs BD, Moll M, Kim W, Tal-Singer R, Bakke P, Fawcett KA, John C, Coley K, Piga NN, Pozarickij A, Lin K, Millwood IY, Chen Z, Li L, Wijnant SRA, Lahousse L, Brusselle G, Uitterlinden AG, Manichaikul A, Oelsner EC, Rich SS, Barr RG, Kerr SM, Vitart V, Brown MR, Wielscher M, Imboden M, Jeong A, Bartz TM, Gharib SA, Flexeder C, Karrasch S, Gieger C, Peters A, Stubbe B, Hu X, Ortega VE, Meyers DA, Bleecker ER, Gabriel SB, Gupta N, Smith AV, Luan J, Zhao JH, Hansen AF, Langhammer A, Willer C, Bhatta L, Porteous D, Smith BH, Campbell A, Sofer T, Lee J, Daviglus ML, Yu B, Lim E, Xu H, O'Connor GT, Thareja G, Albagha OME, Suhre K, Granell R, Faquih TO, Hiemstra PS, Slats AM, Mullin BH, Hui J, James A, Beilby J, Patasova K, Hysi P, Koskela JT, Wyss AB, Jin J, Sikdar S, Lee M, May-Wilson S, Pirastu N, Kentistou KA, Joshi PK, Timmers PRHJ, Williams AT, Free RC, Wang X, Morrison JL, Gilliland FD, Chen Z, Wang CA, Foong RE, Harris SE, Taylor A, Redmond P, Cook JP, Mahajan A, Lind L, Palviainen T, Lehtimäki T, Raitakari OT, Kaprio J, Rantanen T, Pietiläinen KH, Cox SR, Pennell CE, Hall GL, Gauderman WJ, Brightling C, Wilson JF, Vasankari T, Laitinen T, Salomaa V, Mook-Kanamori DO, Timpson NJ, Zeggini E, Dupuis J, Hayward C, Brumpton B, Langenberg C, Weiss S, Homuth G, Schmidt CO, Probst-Hensch N, Jarvelin MR, Morrison AC, Polasek O, Rudan I, Lee JH, Sayers I, Rawlins EL, Dudbridge F, Silverman EK, Strachan DP, Walters RG, Morris AP, London SJ, Cho MH, Wain LV, Hall IP, and Tobin MD
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- 2023
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108. Author Correction: Genetic effects on the timing of parturition and links to fetal birth weight.
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Solé-Navais P, Flatley C, Steinthorsdottir V, Vaudel M, Juodakis J, Chen J, Laisk T, LaBella AL, Westergaard D, Bacelis J, Brumpton B, Skotte L, Borges MC, Helgeland Ø, Mahajan A, Wielscher M, Lin F, Briggs C, Wang CA, Moen GH, Beaumont RN, Bradfield JP, Abraham A, Thorleifsson G, Gabrielsen ME, Ostrowski SR, Modzelewska D, Nohr EA, Hypponen E, Srivastava A, Talbot O, Allard C, Williams SM, Menon R, Shields BM, Sveinbjornsson G, Xu H, Melbye M, Lowe W Jr, Bouchard L, Oken E, Pedersen OB, Gudbjartsson DF, Erikstrup C, Sørensen E, Lie RT, Teramo K, Hallman M, Juliusdottir T, Hakonarson H, Ullum H, Hattersley AT, Sletner L, Merialdi M, Rifas-Shiman SL, Steingrimsdottir T, Scholtens D, Power C, West J, Nyegaard M, Capra JA, Skogholt AH, Magnus P, Andreassen OA, Thorsteinsdottir U, Grant SFA, Qvigstad E, Pennell CE, Hivert MF, Hayes GM, Jarvelin MR, McCarthy MI, Lawlor DA, Nielsen HS, Mägi R, Rokas A, Hveem K, Stefansson K, Feenstra B, Njolstad P, Muglia LJ, Freathy RM, Johansson S, Zhang G, and Jacobsson B
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- 2023
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109. Author Correction: The power of genetic diversity in genome-wide association studies of lipids.
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Graham SE, Clarke SL, Wu KH, 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 YI, 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, and Willer CJ
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- 2023
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110. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis.
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Yarmolinsky J, Robinson JW, Mariosa D, Karhunen V, Huang J, Dimou N, Murphy N, Burrows K, Bouras E, Smith-Byrne K, Lewis SJ, Galesloot TE, Kiemeney LA, Vermeulen S, Martin P, Albanes D, Hou L, Newcomb PA, White E, Wolk A, Wu AH, Marchand LL, Phipps AI, Buchanan DD, Zhao SS, Gill D, Chanock SJ, Purdue MP, Smith GD, Brennan P, Herzig KH, Jarvelin MR, Dehghan A, Johansson M, Gunter MJ, Tsilidis KK, and Martin RM
- Abstract
Background: Tumour-promoting inflammation is a "hallmark" of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear., Methods: We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis -Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,162 cancer cases and up to 824,556 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant ( P < 5.0 x 10
-8 ) cis -acting SNPs (i.e. in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2 < 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-corrected P -value (" q -value") < 0.05 was used as a threshold to define "strong evidence" to support associations and 0.05 ≤ q -value < 0.20 to define "suggestive evidence". A colocalisation posterior probability (PPH4 ) > 70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes., Results: We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR 1.19, 95% CI 1.10-1.29, q -value=0.033, PPH4 =84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR 1.42, 95% CI 1.20-1.69, q -value=0.055, PPH4 =73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR 0.66, 95% CI 0.53-0.81, q -value=0.067, PPH4 =81.8%), macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR 1.14, 95% CI 1.05-1.23, q -value=0.072, PPH4 =76.1%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR 0.92, 95% CI 0.88-0.97, q -value=0.15), PPH4 =85.6%). For 22 of 30 cancer outcomes examined, there was little evidence ( q -value ≥ 0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk., Conclusion: Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 5 circulating inflammatory markers in risk of 5 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated.- Published
- 2023
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111. Genetic effects on the timing of parturition and links to fetal birth weight.
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Solé-Navais P, Flatley C, Steinthorsdottir V, Vaudel M, Juodakis J, Chen J, Laisk T, LaBella AL, Westergaard D, Bacelis J, Brumpton B, Skotte L, Borges MC, Helgeland Ø, Mahajan A, Wielscher M, Lin F, Briggs C, Wang CA, Moen GH, Beaumont RN, Bradfield JP, Abraham A, Thorleifsson G, Gabrielsen ME, Ostrowski SR, Modzelewska D, Nohr EA, Hypponen E, Srivastava A, Talbot O, Allard C, Williams SM, Menon R, Shields BM, Sveinbjornsson G, Xu H, Melbye M, Lowe W Jr, Bouchard L, Oken E, Pedersen OB, Gudbjartsson DF, Erikstrup C, Sørensen E, Lie RT, Teramo K, Hallman M, Juliusdottir T, Hakonarson H, Ullum H, Hattersley AT, Sletner L, Merialdi M, Rifas-Shiman SL, Steingrimsdottir T, Scholtens D, Power C, West J, Nyegaard M, Capra JA, Skogholt AH, Magnus P, Andreassen OA, Thorsteinsdottir U, Grant SFA, Qvigstad E, Pennell CE, Hivert MF, Hayes GM, Jarvelin MR, McCarthy MI, Lawlor DA, Nielsen HS, Mägi R, Rokas A, Hveem K, Stefansson K, Feenstra B, Njolstad P, Muglia LJ, Freathy RM, Johansson S, Zhang G, and Jacobsson B
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- Pregnancy, Infant, Newborn, Female, Humans, Birth Weight genetics, Gestational Age, Parturition genetics, Premature Birth genetics
- Abstract
The timing of parturition is crucial for neonatal survival and infant health. Yet, its genetic basis remains largely unresolved. We present a maternal genome-wide meta-analysis of gestational duration (n = 195,555), identifying 22 associated loci (24 independent variants) and an enrichment in genes differentially expressed during labor. A meta-analysis of preterm delivery (18,797 cases, 260,246 controls) revealed six associated loci and large genetic similarities with gestational duration. Analysis of the parental transmitted and nontransmitted alleles (n = 136,833) shows that 15 of the gestational duration genetic variants act through the maternal genome, whereas 7 act both through the maternal and fetal genomes and 2 act only via the fetal genome. Finally, the maternal effects on gestational duration show signs of antagonistic pleiotropy with the fetal effects on birth weight: maternal alleles that increase gestational duration have negative fetal effects on birth weight. The present study provides insights into the genetic effects on the timing of parturition and the complex maternal-fetal relationship between gestational duration and birth weight., (© 2023. The Author(s).)
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- 2023
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112. Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.
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Shrine N, Izquierdo AG, Chen J, Packer R, Hall RJ, Guyatt AL, Batini C, Thompson RJ, Pavuluri C, Malik V, Hobbs BD, Moll M, Kim W, Tal-Singer R, Bakke P, Fawcett KA, John C, Coley K, Piga NN, Pozarickij A, Lin K, Millwood IY, Chen Z, Li L, Wijnant SRA, Lahousse L, Brusselle G, Uitterlinden AG, Manichaikul A, Oelsner EC, Rich SS, Barr RG, Kerr SM, Vitart V, Brown MR, Wielscher M, Imboden M, Jeong A, Bartz TM, Gharib SA, Flexeder C, Karrasch S, Gieger C, Peters A, Stubbe B, Hu X, Ortega VE, Meyers DA, Bleecker ER, Gabriel SB, Gupta N, Smith AV, Luan J, Zhao JH, Hansen AF, Langhammer A, Willer C, Bhatta L, Porteous D, Smith BH, Campbell A, Sofer T, Lee J, Daviglus ML, Yu B, Lim E, Xu H, O'Connor GT, Thareja G, Albagha OME, Suhre K, Granell R, Faquih TO, Hiemstra PS, Slats AM, Mullin BH, Hui J, James A, Beilby J, Patasova K, Hysi P, Koskela JT, Wyss AB, Jin J, Sikdar S, Lee M, May-Wilson S, Pirastu N, Kentistou KA, Joshi PK, Timmers PRHJ, Williams AT, Free RC, Wang X, Morrison JL, Gilliland FD, Chen Z, Wang CA, Foong RE, Harris SE, Taylor A, Redmond P, Cook JP, Mahajan A, Lind L, Palviainen T, Lehtimäki T, Raitakari OT, Kaprio J, Rantanen T, Pietiläinen KH, Cox SR, Pennell CE, Hall GL, Gauderman WJ, Brightling C, Wilson JF, Vasankari T, Laitinen T, Salomaa V, Mook-Kanamori DO, Timpson NJ, Zeggini E, Dupuis J, Hayward C, Brumpton B, Langenberg C, Weiss S, Homuth G, Schmidt CO, Probst-Hensch N, Jarvelin MR, Morrison AC, Polasek O, Rudan I, Lee JH, Sayers I, Rawlins EL, Dudbridge F, Silverman EK, Strachan DP, Walters RG, Morris AP, London SJ, Cho MH, Wain LV, Hall IP, and Tobin MD
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- Humans, Genome-Wide Association Study, Genetic Predisposition to Disease genetics, Smoking adverse effects, Smoking genetics, Polymorphism, Single Nucleotide genetics, Lung, Pulmonary Disease, Chronic Obstructive genetics
- Abstract
Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies., (© 2023. The Author(s).)
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- 2023
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113. Novel Genetic Determinants of Dental Maturation in Children.
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Grgic O, Prijatelj V, Dudakovic A, Vucic S, Dhamo B, Trajanoska K, Monnereau C, Zrimsek M, Gautvik KM, Reppe S, Shimizu E, Haworth S, Timpson NJ, Jaddoe VWV, Jarvelin MR, Evans D, Uitterlinden AG, Ongkosuwito EM, van Wijnen AJ, Medina-Gomez C, Rivadeneira F, and Wolvius EB
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- Infant, Humans, Child, Animals, Mice, Alleles, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide genetics, Genetic Loci, Genome-Wide Association Study, Tooth
- Abstract
Dental occlusion requires harmonious development of teeth, jaws, and other elements of the craniofacial complex, which are regulated by environmental and genetic factors. We performed the first genome-wide association study (GWAS) on dental development (DD) using the Demirjian radiographic method. Radiographic assessments from participants of the Generation R Study (primary study population, N
1 = 2,793; mean age of 9.8 y) were correlated with ~30 million genetic variants while adjusting for age, sex, and genomic principal components (proxy for population stratification). Variants associated with DD at genome-wide significant level ( P < 5 × 10-8 ) mapped to 16q12.2 ( IRX5 ) (lead variant rs3922616, B = 0.16; P = 2.2 × 10-8 ). We used Fisher's combined probability tests weighted by sample size to perform a meta-analysis ( N = 14,805) combining radiographic DD at a mean age of 9.8 y from Generation R with data from a previous GWAS ( N2 = 12,012) on number of teeth (NT) in infants used as proxy of DD at a mean age of 9.8 y (including the ALSPAC and NFBC1966). This GWAS meta-analysis revealed 3 novel loci mapping to 7p15.3 ( IGF2BP3: P = 3.2 × 10-8 ), 14q13.3 ( PAX9: P = 1.9 × 10-8 ), and 16q12.2 ( IRX5: P = 1.2 × 10-9 ) and validated 8 previously reported NT loci. A polygenic allele score constructed from these 11 loci was associated with radiographic DD in an independent Generation R set of children ( N = 703; B = 0.05, P = 0.004). Furthermore, profiling of the identified genes across an atlas of murine and human stem cells observed expression in the cells involved in the formation of bone and/or dental tissues (>0.3 frequency per kilobase of transcript per million mapped reads), likely reflecting functional specialization. Our findings provide biological insight into the polygenic architecture of the pediatric dental maturation process.- Published
- 2023
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114. The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions.
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Rahmioglu N, Mortlock S, Ghiasi M, Møller PL, Stefansdottir L, Galarneau G, Turman C, Danning R, Law MH, Sapkota Y, Christofidou P, Skarp S, Giri A, Banasik K, Krassowski M, Lepamets M, Marciniak B, Nõukas M, Perro D, Sliz E, Sobalska-Kwapis M, Thorleifsson G, Topbas-Selcuki NF, Vitonis A, Westergaard D, Arnadottir R, Burgdorf KS, Campbell A, Cheuk CSK, Clementi C, Cook J, De Vivo I, DiVasta A, Dorien O, Donoghue JF, Edwards T, Fontanillas P, Fung JN, Geirsson RT, Girling JE, Harkki P, Harris HR, Healey M, Heikinheimo O, Holdsworth-Carson S, Hostettler IC, Houlden H, Houshdaran S, Irwin JC, Jarvelin MR, Kamatani Y, Kennedy SH, Kepka E, Kettunen J, Kubo M, Kulig B, Kurra V, Laivuori H, Laufer MR, Lindgren CM, MacGregor S, Mangino M, Martin NG, Matalliotaki C, Matalliotakis M, Murray AD, Ndungu A, Nezhat C, Olsen CM, Opoku-Anane J, Padmanabhan S, Paranjpe M, Peters M, Polak G, Porteous DJ, Rabban J, Rexrode KM, Romanowicz H, Saare M, Saavalainen L, Schork AJ, Sen S, Shafrir AL, Siewierska-Górska A, Słomka M, Smith BH, Smolarz B, Szaflik T, Szyłło K, Takahashi A, Terry KL, Tomassetti C, Treloar SA, Vanhie A, Vincent K, Vo KC, Werring DJ, Zeggini E, Zervou MI, Adachi S, Buring JE, Ridker PM, D'Hooghe T, Goulielmos GN, Hapangama DK, Hayward C, Horne AW, Low SK, Martikainen H, Chasman DI, Rogers PAW, Saunders PT, Sirota M, Spector T, Strapagiel D, Tung JY, Whiteman DC, Giudice LC, Velez-Edwards DR, Uimari O, Kraft P, Salumets A, Nyholt DR, Mägi R, Stefansson K, Becker CM, Yurttas-Beim P, Steinthorsdottir V, Nyegaard M, Missmer SA, Montgomery GW, Morris AP, and Zondervan KT
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- Female, Humans, Genetic Predisposition to Disease, Genome-Wide Association Study, Pain, Comorbidity, Endometriosis genetics, Endometriosis metabolism
- Abstract
Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)
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- 2023
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115. Inflammatory Diseases, Inflammatory Biomarkers, and Alzheimer Disease: An Observational Analysis and Mendelian Randomization.
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Huang J, Su B, Karhunen V, Gill D, Zuber V, Ahola-Olli A, Palaniswamy S, Auvinen J, Herzig KH, Keinänen-Kiukaanniemi S, Salmi M, Jalkanen S, Lehtimäki T, Salomaa V, Raitakari OT, Matthews PM, Elliott P, Tsilidis KK, Jarvelin MR, Tzoulaki I, and Dehghan A
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- Humans, Genome-Wide Association Study, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide genetics, Biomarkers, Alzheimer Disease epidemiology, Alzheimer Disease genetics, Crohn Disease
- Abstract
Background and Objectives: Whether chronic autoimmune inflammatory diseases causally affect the risk of Alzheimer disease (AD) is controversial. We characterized the relationship between inflammatory diseases and risk of AD and explored the role of circulating inflammatory biomarkers in the relationships between inflammatory diseases and AD., Methods: We performed observational analyses for chronic autoimmune inflammatory diseases and risk of AD using data from 2,047,513 participants identified in the UK Clinical Practice Research Datalink (CPRD). Using data of a total of more than 1,100,000 individuals from 15 large-scale genome-wide association study data sets, we performed 2-sample Mendelian randomizations (MRs) to investigate the relationships between chronic autoimmune inflammatory diseases, circulating inflammatory biomarker levels, and risk of AD., Results: Cox regression models using CPRD data showed that the overall incidence of AD was higher among patients with inflammatory bowel disease (hazard ratio [HR] 1.17; 95% CI 1.15-1.19; p = 2.1 × 10
-4 ), other inflammatory polyarthropathies and systematic connective tissue disorders (HR 1.13; 95% CI 1.12-1.14; p = 8.6 × 10-5 ), psoriasis (HR 1.13; 95% CI 1.10-1.16; p = 2.6 × 10-4 ), rheumatoid arthritis (HR 1.08; 95% CI 1.06-1.11; p = 4.0 × 10-4 ), and multiple sclerosis (HR 1.06; 95% CI 1.04-1.07; p = 2.8 × 10-4 ) compared with the age (±5 years) and sex-matched comparison groups free from all inflammatory diseases under investigation. Bidirectional MR analysis identified relationships between chronic autoimmune inflammatory diseases and circulating inflammatory biomarkers. Particularly, circulating monokine induced by gamma interferon (MIG) level was suggestively associated with a higher risk of AD (odds ratio from inverse variance weighted [ORIVW ] 1.23; 95% CI 1.06-1.42; pIVW = 0.007) and lower risk of Crohn disease (ORIVW 0.73; 95% CI -0.62 to 0.86; p ). Colocalization supported a common causal single nucleotide polymorphism for MIG and Crohn disease (posterior probability = 0.74), but not AD (posterior probability = 0.03). Using a 2-sample MR approach, genetically predicted risks of inflammatory diseases were not associated with higher AD risk.IVW = 1.3 × 10-4 ). Colocalization supported a common causal single nucleotide polymorphism for MIG and Crohn disease (posterior probability = 0.74), but not AD (posterior probability = 0.03). Using a 2-sample MR approach, genetically predicted risks of inflammatory diseases were not associated with higher AD risk., Discussion: Our data suggest that the association between inflammatory diseases and risk of AD is unlikely to be causal and may be a result of confounding. In support, although inflammatory biomarkers showed evidence for causal associations with inflammatory diseases, evidence was weak that they affected both inflammatory disease and AD., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)- Published
- 2023
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116. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
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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 KH, 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 E, 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 YI, 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 E, 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 L, 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 Y, 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, and Peloso GM
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- Humans, Sex Characteristics, Phenotype, Lipids genetics, Polymorphism, Single Nucleotide, Genetic Pleiotropy, Genome-Wide Association Study, Genetic Predisposition to Disease
- 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., (© 2022. The Author(s).)
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- 2022
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117. A saturated map of common genetic variants associated with human height.
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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 YA, 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 YI, 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, and Hirschhorn JN
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- Humans, Gene Frequency genetics, Genome, Human genetics, Genome-Wide Association Study, Haplotypes genetics, Linkage Disequilibrium genetics, Europe ethnology, Sample Size, Phenotype, Body Height genetics, Polymorphism, Single Nucleotide genetics, Chromosome Mapping
- 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 sizes
1 . 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., (© 2022. The Author(s).)- Published
- 2022
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118. The iHealth-T2D study: a cluster randomised trial for the prevention of type 2 diabetes amongst South Asians with central obesity and prediabetes-a statistical analysis plan.
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Muilwijk M, Loh M, Mahmood S, Palaniswamy S, Siddiqui S, Silva W, Frost GS, Gage HM, Jarvelin MR, Rannan-Eliya RP, Ahmad S, Jha S, Kasturiratne A, Katulanda P, Khawaja KI, Kooner JS, Wickremasinghe AR, van Valkengoed IGM, and Chambers JC
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- Adult, Aged, Asian People, Female, Humans, Male, Middle Aged, Obesity, Obesity, Abdominal diagnosis, Obesity, Abdominal prevention & control, Sri Lanka, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 2 prevention & control, Prediabetic State diagnosis, Prediabetic State therapy
- Abstract
Background: South Asians are at high risk of type 2 diabetes (T2D). Lifestyle modification is effective at preventing T2D amongst South Asians, but the approaches to screening and intervention are limited by high costs, poor scalability and thus low impact on T2D burden. An intensive family-based lifestyle modification programme for the prevention of T2D was developed. The aim of the iHealth-T2D trial is to compare the effectiveness of this programme with usual care., Methods: The iHealth-T2D trial is designed as a cluster randomised controlled trial (RCT) conducted at 120 sites across India, Pakistan, Sri Lanka and the UK. A total of 3682 South Asian men and women with age between 40 and 70 years without T2D but at elevated risk for T2D [defined by central obesity (waist circumference ≥ 95 cm in Sri Lanka or ≥ 100 cm in India, Pakistan and the UK) and/or prediabetes (HbA1c ≥ 6.0%)] were included in the trial. Here, we describe in detail the statistical analysis plan (SAP), which was finalised before outcomes were available to the investigators. The primary outcome will be evaluated after 3 years of follow-up after enrolment to the study and is defined as T2D incidence in the intervention arm compared to usual care. Secondary outcomes are evaluated both after 1 and 3 years of follow-up and include biochemical measurements, anthropometric measurements, behavioural components and treatment compliance., Discussion: The iHealth-T2D trial will provide evidence of whether an intensive family-based lifestyle modification programme for South Asians who are at high risk for T2D is effective in the prevention of T2D. The data from the trial will be analysed according to this pre-specified SAP., Ethics and Dissemination: The trial was approved by the international review board of each participating study site. Study findings will be disseminated through peer-reviewed publications and in conference presentations., Trial Registration: EudraCT 2016-001,350-18 . Registered on 14 April 2016., Clinicaltrials: gov NCT02949739 . Registered on 31 October 2016., (© 2022. The Author(s).)
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- 2022
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119. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention.
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Wang Z, Emmerich A, Pillon NJ, Moore T, Hemerich D, Cornelis MC, Mazzaferro E, Broos S, Ahluwalia TS, Bartz TM, Bentley AR, Bielak LF, Chong M, Chu AY, Berry D, Dorajoo R, Dueker ND, Kasbohm E, Feenstra B, Feitosa MF, Gieger C, Graff M, Hall LM, Haller T, Hartwig FP, Hillis DA, Huikari V, Heard-Costa N, Holzapfel C, Jackson AU, Johansson Å, Jørgensen AM, Kaakinen MA, Karlsson R, Kerr KF, Kim B, Koolhaas CM, Kutalik Z, Lagou V, Lind PA, Lorentzon M, Lyytikäinen LP, Mangino M, Metzendorf C, Monroe KR, Pacolet A, Pérusse L, Pool R, Richmond RC, Rivera NV, Robiou-du-Pont S, Schraut KE, Schulz CA, Stringham HM, Tanaka T, Teumer A, Turman C, van der Most PJ, Vanmunster M, van Rooij FJA, van Vliet-Ostaptchouk JV, Zhang X, Zhao JH, Zhao W, Balkhiyarova Z, Balslev-Harder MN, Baumeister SE, Beilby J, Blangero J, Boomsma DI, Brage S, Braund PS, Brody JA, Bruinenberg M, Ekelund U, Liu CT, Cole JW, Collins FS, Cupples LA, Esko T, Enroth S, Faul JD, Fernandez-Rhodes L, Fohner AE, Franco OH, Galesloot TE, Gordon SD, Grarup N, Hartman CA, Heiss G, Hui J, Illig T, Jago R, James A, Joshi PK, Jung T, Kähönen M, Kilpeläinen TO, Koh WP, Kolcic I, Kraft PP, Kuusisto J, Launer LJ, Li A, Linneberg A, Luan J, Vidal PM, Medland SE, Milaneschi Y, Moscati A, Musk B, Nelson CP, Nolte IM, Pedersen NL, Peters A, Peyser PA, Power C, Raitakari OT, Reedik M, Reiner AP, Ridker PM, Rudan I, Ryan K, Sarzynski MA, Scott LJ, Scott RA, Sidney S, Siggeirsdottir K, Smith AV, Smith JA, Sonestedt E, Strøm M, Tai ES, Teo KK, Thorand B, Tönjes A, Tremblay A, Uitterlinden AG, Vangipurapu J, van Schoor N, Völker U, Willemsen G, Williams K, Wong Q, Xu H, Young KL, Yuan JM, Zillikens MC, Zonderman AB, Ameur A, Bandinelli S, Bis JC, Boehnke M, Bouchard C, Chasman DI, Smith GD, de Geus EJC, Deldicque L, Dörr M, Evans MK, Ferrucci L, Fornage M, Fox C, Garland T Jr, Gudnason V, Gyllensten U, Hansen T, Hayward C, Horta BL, Hyppönen E, Jarvelin MR, Johnson WC, Kardia SLR, Kiemeney LA, Laakso M, Langenberg C, Lehtimäki T, Marchand LL, Magnusson PKE, Martin NG, Melbye M, Metspalu A, Meyre D, North KE, Ohlsson C, Oldehinkel AJ, Orho-Melander M, Pare G, Park T, Pedersen O, Penninx BWJH, Pers TH, Polasek O, Prokopenko I, Rotimi CN, Samani NJ, Sim X, Snieder H, Sørensen TIA, Spector TD, Timpson NJ, van Dam RM, van der Velde N, van Duijn CM, Vollenweider P, Völzke H, Voortman T, Waeber G, Wareham NJ, Weir DR, Wichmann HE, Wilson JF, Hevener AL, Krook A, Zierath JR, Thomis MAI, Loos RJF, and Hoed MD
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- Actinin genetics, Cross-Sectional Studies, Exercise physiology, Humans, Leisure Activities, Genome-Wide Association Study, Sedentary Behavior
- Abstract
Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type II
A muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention., (© 2022. The Author(s).)- Published
- 2022
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120. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids.
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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 KH, 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, and Brown CD
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- Chromatin genetics, Genomics, Humans, Lipids genetics, Genome-Wide Association Study, Polymorphism, Single Nucleotide genetics
- 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., Competing Interests: Declaration of interests G.C.-P. is currently an employee of 23andMe Inc. M.J.C. is the Chief Scientist for Genomics England, a UK Government company. B.M. Psaty serves on the steering committee of the Yale Open Data Access Project funded by Johnson & Johnson. G. Thorleifsson, A.H., D.F.G., H. Holm, U.T., and K.S. are employees of deCODE/Amgen Inc. V.S. has received honoraria for consultations from Novo Nordisk and Sanofi and has an ongoing research collaboration with Bayer Ltd. M. McCarthy has served on advisory panels for Pfizer, NovoNordisk, and Zoe Global and has received honoraria from Merck, Pfizer, Novo Nordisk, and Eli Lilly and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. M. McCarthy and A. Mahajan are employees of Genentech and holders of Roche stock. M.S. receives funding from Pfizer Inc. for a project unrelated to this work. M.E.K. is employed by SYNLAB MVZ Mannheim GmbH. W.M. has received grants from Siemens Healthineers, grants and personal fees from Aegerion Pharmaceuticals, grants and personal fees from AMGEN, grants from Astrazeneca, grants and personal fees from Sanofi, grants and personal fees from Alexion Pharmaceuticals, grants and personal fees from BASF, grants and personal fees from Abbott Diagnostics, grants and personal fees from Numares AG, grants and personal fees from Berlin-Chemie, grants and personal fees from Akzea Therapeutics, grants from Bayer Vital GmbH , grants from bestbion dx GmbH, grants from Boehringer Ingelheim Pharma GmbH Co KG, grants from Immundiagnostik GmbH, grants from Merck Chemicals GmbH, grants from MSD Sharp and Dohme GmbH, grants from Novartis Pharma GmbH, grants from Olink Proteomics, and other from Synlab Holding Deutschland GmbH, all outside the submitted work. A.V.K. has served as a consultant to Sanofi, Medicines Company, Maze Pharmaceuticals, Navitor Pharmaceuticals, Verve Therapeutics, Amgen, and Color Genomics; received speaking fees from Illumina and the Novartis Institute for Biomedical Research; received sponsored research agreements from the Novartis Institute for Biomedical Research and IBM Research, and reports a patent related to a genetic risk predictor (20190017119). S. Kathiresan is an employee of Verve Therapeutics and holds equity in Verve Therapeutics, Maze Therapeutics, Catabasis, and San Therapeutics. He is a member of the scientific advisory boards for Regeneron Genetics Center and Corvidia Therapeutics; he has served as a consultant for Acceleron, Eli Lilly, Novartis, Merck, Novo Nordisk, Novo Ventures, Ionis, Alnylam, Aegerion, Haug Partners, Noble Insights, Leerink Partners, Bayer Healthcare, Illumina, Color Genomics, MedGenome, Quest, and Medscape; and he reports patents related to a method of identifying and treating a person having a predisposition to or afflicted with cardiometabolic disease (20180010185) and a genetics risk predictor (20190017119). D.K. accepts consulting fees from Regeneron Pharmaceuticals. D.O.M.-K. is a part-time clinical research consultant for Metabolon, Inc. D. Saleheen has received support from the British Heart Foundation, Pfizer, Regeneron, Genentech, and Eli Lilly pharmaceuticals. P.N. reports investigator-initated grants from Amgen, Apple, AstraZeneca, Boston Scientific, and Novartis, personal fees from Apple, AstraZeneca, Blackstone Life Sciences, Foresite Labs, Novartis, Roche / Genentech, is a co-founder of TenSixteen Bio, is a scientific advisory board member of Esperion Therapeutics, geneXwell, and TenSixteen Bio, and spousal employment at Vertex, all unrelated to the present work. The spouse of C.J.W. is employed by Regeneron., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)
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121. The relationship of life-course patterns of adiposity with type 2 diabetes, depression, and their comorbidity in the Northern Finland Birth Cohort 1966.
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Choudhary P, Ronkainen J, Nedelec R, Tolvanen M, Lowry E, Miettunen J, Jarvelin MR, and Sebert S
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- Adult, Birth Cohort, Body Mass Index, Child, Preschool, Comorbidity, Depression epidemiology, Female, Finland epidemiology, Humans, Male, Obesity complications, Obesity epidemiology, Overweight complications, Overweight epidemiology, Risk Factors, Adiposity, Diabetes Mellitus, Type 2 epidemiology, Diabetes Mellitus, Type 2 etiology
- Abstract
Objectives: Type 2 diabetes (T2D) and comorbid depression challenges clinical management particularly in individuals with overweight. We aim to explore the shared etiology, via lifecourse adiposity, between T2D and depression., Methods: We used data from birth until 46years from Northern Finland Birth Cohort 1966 (n = 6,372; 53.8% females). We conducted multivariate analyses on three outcomes: T2D (4.2%), depression (19.2%) and as comorbidity (1.8%). We conducted (i) Path analysis to clarify time-dependent body mass index (BMI) related pathways, including BMI polygenic risk scores (PRS); and (ii) Cox regression models to assess whether reduction of overweight between 7years and 31years influence T2D, depression and/or comorbidity. The models were tested for covariation with sex, education, smoking, physical activity, and diet score., Results: The odd ratios (OR) of T2D in individuals with depression was 1.68 [95% confidence interval (CI): 1.34-2.11], and no change in estimate was observed when adjusted for covariates. T2D and comorbidity showed similar patterns of relationships in the path analyses (P < 0.001). The genetic risk for obesity (PRS BMI) did not show direct effect on T2D or comorbidity in adulthood but indirectly through measures of adiposity in early childhood and mid-adulthood in the path analysis (P < 0.001). Having early-onset of overweight at 7years and 31years showed highest risk of T2D (OR 3.8, 95%CI 2.4-6.1) and comorbidity (OR 5.0, 95%CI 2.7-9.5), with mild-to-moderate attenuation with adjustments. Depression showed no significant associations., Conclusions: We found evidence for overweight since childhood as a risk factor for T2D and co-morbidity between T2D and depression, influenced moderately by lifestyle factors in later life. However, no shared early life adiposity related risk factors were observed between T2D and depression when assessed independently in this Finnish setting., (© 2022. The Author(s).)
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122. Author Correction: Genetic analysis of over half a million people characterises C-reactive protein loci.
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Said S, Pazoki R, Karhunen V, Võsa U, Ligthart S, Bodinier B, Koskeridis F, Welsh P, Alizadeh BZ, Chasman DI, Sattar N, Chadeau-Hyam M, Evangelou E, Jarvelin MR, Elliott P, Tzoulaki I, and Dehghan A
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- 2022
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123. Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms.
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Jami ES, Hammerschlag AR, Ip HF, Allegrini AG, Benyamin B, Border R, Diemer EW, Jiang C, Karhunen V, Lu Y, Lu Q, Mallard TT, Mishra PP, Nolte IM, Palviainen T, Peterson RE, Sallis HM, Shabalin AA, Tate AE, Thiering E, Vilor-Tejedor N, Wang C, Zhou A, Adkins DE, Alemany S, Ask H, Chen Q, Corley RP, Ehli EA, Evans LM, Havdahl A, Hagenbeek FA, Hakulinen C, Henders AK, Hottenga JJ, Korhonen T, Mamun A, Marrington S, Neumann A, Rimfeld K, Rivadeneira F, Silberg JL, van Beijsterveldt CE, Vuoksimaa E, Whipp AM, Tong X, Andreassen OA, Boomsma DI, Brown SA, Burt SA, Copeland W, Dick DM, Harden KP, Harris KM, Hartman CA, Heinrich J, Hewitt JK, Hopfer C, Hypponen E, Jarvelin MR, Kaprio J, Keltikangas-Järvinen L, Klump KL, Krauter K, Kuja-Halkola R, Larsson H, Lehtimäki T, Lichtenstein P, Lundström S, Maes HH, Magnus P, Munafò MR, Najman JM, Njølstad PR, Oldehinkel AJ, Pennell CE, Plomin R, Reichborn-Kjennerud T, Reynolds C, Rose RJ, Smolen A, Snieder H, Stallings M, Standl M, Sunyer J, Tiemeier H, Wadsworth SJ, Wall TL, Whitehouse AJO, Williams GM, Ystrøm E, Nivard MG, Bartels M, and Middeldorp CM
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- Adolescent, Adult, Aggression, Anxiety genetics, Bipolar Disorder, Child, Child, Preschool, Depression genetics, Humans, Loneliness, Polymorphism, Single Nucleotide, Schizophrenia, Attention Deficit Disorder with Hyperactivity genetics, Autistic Disorder genetics, Genome-Wide Association Study, Sleep Initiation and Maintenance Disorders genetics
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Objective: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence., Method: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument., Results: The meta-analysis of overall internalizing symptoms (INT
overall ) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg | > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg | = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa., Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)- Published
- 2022
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124. Genetic analysis of over half a million people characterises C-reactive protein loci.
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Said S, Pazoki R, Karhunen V, Võsa U, Ligthart S, Bodinier B, Koskeridis F, Welsh P, Alizadeh BZ, Chasman DI, Sattar N, Chadeau-Hyam M, Evangelou E, Jarvelin MR, Elliott P, Tzoulaki I, and Dehghan A
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- Genetic Loci, Humans, Inflammation genetics, Male, Mendelian Randomization Analysis, Phenomics, Polymorphism, Single Nucleotide, C-Reactive Protein genetics, C-Reactive Protein metabolism, Genome-Wide Association Study
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Chronic low-grade inflammation is linked to a multitude of chronic diseases. We report the largest genome-wide association study (GWAS) on C-reactive protein (CRP), a marker of systemic inflammation, in UK Biobank participants (N = 427,367, European descent) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (total N = 575,531 European descent). We identify 266 independent loci, of which 211 are not previously reported. Gene-set analysis highlighted 42 gene sets associated with CRP levels (p ≤ 3.2 ×10
-6 ) and tissue expression analysis indicated a strong association of CRP related genes with liver and whole blood gene expression. Phenome-wide association study identified 27 clinical outcomes associated with genetically determined CRP and subsequent Mendelian randomisation analyses supported a causal association with schizophrenia, chronic airway obstruction and prostate cancer. Our findings identified genetic loci and functional properties of chronic low-grade inflammation and provided evidence for causal associations with a range of diseases., (© 2022. The Author(s).)- Published
- 2022
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125. Fat metabolism is associated with telomere length in six population-based studies.
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van der Spek A, Karamujić-Čomić H, Pool R, Bot M, Beekman M, Garmaeva S, Arp PP, Henkelman S, Liu J, Alves AC, Willemsen G, van Grootheest G, Aubert G, Ikram MA, Jarvelin MR, Lansdorp P, Uitterlinden AG, Zhernakova A, Slagboom PE, Penninx BWJH, Boomsma DI, Amin N, and van Duijn CM
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- Biomarkers metabolism, Cross-Sectional Studies, Fatty Acids metabolism, Humans, Lipids, Telomere genetics, Leukocytes metabolism, Telomere Shortening
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Telomeres are repetitive DNA sequences located at the end of chromosomes, which are associated to biological aging, cardiovascular disease, cancer and mortality. Lipid and fatty acid metabolism have been associated with telomere shortening. We have conducted an in-depth study investigating the association of metabolic biomarkers with telomere length (LTL). We performed an association analysis of 226 metabolic biomarkers with LTL using data from 11 775 individuals from six independent population-based cohorts (BBMRI-NL consortium). Metabolic biomarkers include lipoprotein lipids and subclasses, fatty acids, amino acids, glycolysis measures and ketone bodies. LTL was measured by quantitative polymerase chain reaction or FlowFISH. Linear regression analysis was performed adjusting for age, sex, lipid-lowering medication and cohort-specific covariates (model 1) and additionally for body mass index (BMI) and smoking (model 2), followed by inverse variance-weighted meta-analyses (significance threshold Pmeta = 6.5 × 10-4). We identified four metabolic biomarkers positively associated with LTL, including two cholesterol to lipid ratios in small VLDL (S-VLDL-C % and S-VLDL-CE %) and two omega-6 fatty acid ratios (FAw6/FA and LA/FA). After additionally adjusting for BMI and smoking, these metabolic biomarkers remained associated with LTL with similar effect estimates. In addition, cholesterol esters in very small VLDL (XS-VLDL-CE) became significantly associated with LTL (P = 3.6 × 10-4). We replicated the association of FAw6/FA with LTL in an independent dataset of 7845 individuals (P = 1.9 × 10-4). To conclude, we identified multiple metabolic biomarkers involved in lipid and fatty acid metabolism that may be involved in LTL biology. Longitudinal studies are needed to exclude reversed causation., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
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126. Maternal Glycemic Dysregulation During Pregnancy and Neonatal Blood DNA Methylation: Meta-analyses of Epigenome-Wide Association Studies.
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Tobi EW, Juvinao-Quintero DL, Ronkainen J, Ott R, Alfano R, Canouil M, Geurtsen ML, Khamis A, Küpers LK, Lim IY, Perron P, Pesce G, Tuhkanen J, Starling AP, Andrew T, Binder E, Caiazzo R, Chan JKY, Gaillard R, Gluckman PD, Keikkala E, Karnani N, Mustaniemi S, Nawrot TS, Pattou F, Plusquin M, Raverdy V, Tan KH, Tzala E, Raikkonen K, Winkler C, Ziegler AG, Annesi-Maesano I, Bouchard L, Chong YS, Dabelea D, Felix JF, Heude B, Jaddoe VWV, Lahti J, Reimann B, Vääräsmäki M, Bonnefond A, Froguel P, Hummel S, Kajantie E, Jarvelin MR, Steegers-Theunissen RPM, Howe CG, Hivert MF, and Sebert S
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- DNA Methylation genetics, Epigenesis, Genetic, Epigenome, Female, Fetal Blood metabolism, Humans, Infant, Newborn, Pregnancy, Diabetes Mellitus, Type 2 metabolism, Diabetes, Gestational genetics, Diabetes, Gestational metabolism
- Abstract
Objective: Maternal glycemic dysregulation during pregnancy increases the risk of adverse health outcomes in her offspring, a risk thought to be linearly related to maternal hyperglycemia. It is hypothesized that changes in offspring DNA methylation (DNAm) underline these associations., Research Design and Methods: To address this hypothesis, we conducted fixed-effects meta-analyses of epigenome-wide association study (EWAS) results from eight birth cohorts investigating relationships between cord blood DNAm and fetal exposure to maternal glucose (Nmaximum = 3,503), insulin (Nmaximum = 2,062), and area under the curve of glucose (AUCgluc) following oral glucose tolerance tests (Nmaximum = 1,505). We performed lookup analyses for identified cytosine-guanine dinucleotides (CpGs) in independent observational cohorts to examine associations between DNAm and cardiometabolic traits as well as tissue-specific gene expression., Results: Greater maternal AUCgluc was associated with lower cord blood DNAm at neighboring CpGs cg26974062 (β [SE] -0.013 [2.1 × 10-3], P value corrected for false discovery rate [PFDR] = 5.1 × 10-3) and cg02988288 (β [SE]-0.013 [2.3 × 10-3], PFDR = 0.031) in TXNIP. These associations were attenuated in women with GDM. Lower blood DNAm at these two CpGs near TXNIP was associated with multiple metabolic traits later in life, including type 2 diabetes. TXNIP DNAm in liver biopsies was associated with hepatic expression of TXNIP. We observed little evidence of associations between either maternal glucose or insulin and cord blood DNAm., Conclusions: Maternal hyperglycemia, as reflected by AUCgluc, was associated with lower cord blood DNAm at TXNIP. Associations between DNAm at these CpGs and metabolic traits in subsequent lookup analyses suggest that these may be candidate loci to investigate in future causal and mediation analyses., (© 2022 by the American Diabetes Association.)
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- 2022
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127. Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis.
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Bouras E, Karhunen V, Gill D, Huang J, Haycock PC, Gunter MJ, Johansson M, Brennan P, Key T, Lewis SJ, Martin RM, Murphy N, Platz EA, Travis R, Yarmolinsky J, Zuber V, Martin P, Katsoulis M, Freisling H, Nøst TH, Schulze MB, Dossus L, Hung RJ, Amos CI, Ahola-Olli A, Palaniswamy S, Männikkö M, Auvinen J, Herzig KH, Keinänen-Kiukaanniemi S, Lehtimäki T, Salomaa V, Raitakari O, Salmi M, Jalkanen S, Jarvelin MR, Dehghan A, and Tsilidis KK
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- Cytokines genetics, Female, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Risk Factors, Mendelian Randomization Analysis, Ovarian Neoplasms epidemiology, Ovarian Neoplasms genetics
- Abstract
Background: Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis., Methods: Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer)., Results: There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses., Conclusions: Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention., (© 2021. The Author(s).)
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128. Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function.
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Hawe JS, Wilson R, Schmid KT, Zhou L, Lakshmanan LN, Lehne BC, Kühnel B, Scott WR, Wielscher M, Yew YW, Baumbach C, Lee DP, Marouli E, Bernard M, Pfeiffer L, Matías-García PR, Autio MI, Bourgeois S, Herder C, Karhunen V, Meitinger T, Prokisch H, Rathmann W, Roden M, Sebert S, Shin J, Strauch K, Zhang W, Tan WLW, Hauck SM, Merl-Pham J, Grallert H, Barbosa EGV, Illig T, Peters A, Paus T, Pausova Z, Deloukas P, Foo RSY, Jarvelin MR, Kooner JS, Loh M, Heinig M, Gieger C, Waldenberger M, and Chambers JC
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- Arthritis, Rheumatoid genetics, Asia, Blood Pressure genetics, Body Mass Index, CD8-Positive T-Lymphocytes metabolism, CpG Islands, DNA Replication, Europe, Genome-Wide Association Study, Humans, Leukocytes metabolism, Polymorphism, Single Nucleotide, Quantitative Trait Loci, DNA Methylation genetics, Genetic Variation
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We determined the relationships between DNA sequence variation and DNA methylation using blood samples from 3,799 Europeans and 3,195 South Asians. We identify 11,165,559 SNP-CpG associations (methylation quantitative trait loci (meQTL), P < 10
-14 ), including 467,915 meQTL that operate in trans. The meQTL are enriched for functionally relevant characteristics, including shared chromatin state, High-throuhgput chromosome conformation interaction, and association with gene expression, metabolic variation and clinical traits. We use molecular interaction and colocalization analyses to identify multiple nuclear regulatory pathways linking meQTL loci to phenotypic variation, including UBASH3B (body mass index), NFKBIE (rheumatoid arthritis), MGA (blood pressure) and COMMD7 (white cell counts). For rs6511961 , chromatin immunoprecipitation followed by sequencing (ChIP-seq) validates zinc finger protein (ZNF)333 as the likely trans acting effector protein. Finally, we used interaction analyses to identify population- and lineage-specific meQTL, including rs174548 in FADS1, with the strongest effect in CD8+ T cells, thus linking fatty acid metabolism with immune dysregulation and asthma. Our study advances understanding of the potential pathways linking genetic variation to human phenotype., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)- Published
- 2022
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129. The iHealth-T2D study, prevention of type 2 diabetes amongst South Asians with central obesity and prediabetes: study protocol for a randomised controlled trial.
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Kasturiratne A, Khawaja KI, Ahmad S, Siddiqui S, Shahzad K, Athauda LK, Jayawardena R, Mahmood S, Muilwijk M, Batool T, Burney S, Glover M, Palaniswamy S, Bamunuarachchi V, Panda M, Madawanarachchi S, Rai B, Sattar I, Silva W, Waghdhare S, Jarvelin MR, Rannan-Eliya RP, Gage HM, van Valkengoed IGM, Valabhji J, Frost GS, Loh M, Wickremasinghe AR, Kooner JS, Katulanda P, Jha S, and Chambers JC
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- Adult, Aged, Asian People, Female, Humans, Life Style, Male, Middle Aged, Obesity, Abdominal, Randomized Controlled Trials as Topic, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 2 prevention & control, Prediabetic State diagnosis, Prediabetic State therapy
- Abstract
Background: People from South Asia are at increased risk of type 2 diabetes (T2D). There is an urgent need to develop approaches for the prevention of T2D in South Asians that are cost-effective, generalisable and scalable across settings., Hypothesis: Compared to usual care, the risk of T2D can be reduced amongst South Asians with central obesity or raised HbA1c, through a 12-month lifestyle modification programme delivered by community health workers., Design: Cluster randomised clinical trial (1:1 allocation to intervention or usual care), carried out in India, Pakistan, Sri Lanka and the UK, with 30 sites per country (120 sites total). Target recruitment 3600 (30 participants per site) with annual follow-up for 3 years., Entry Criteria: South Asian, men or women, age 40-70 years with (i) central obesity (waist circumference ≥ 100 cm in India and Pakistan; ≥90 cm in Sri Lanka) and/or (ii) prediabetes (HbA1c 6.0-6.4% inclusive)., Exclusion Criteria: known type 1 or 2 diabetes, normal or underweight (body mass index < 22 kg/m
2 ); pregnant or planning pregnancy; unstable residence or planning to leave the area; and serious illness., Endpoints: The primary endpoint is new-onset T2D at 3 years, defined as (i) HbA1c ≥ 6.5% or (ii) physician diagnosis and on treatment for T2D. Secondary endpoints at 1 and 3 years are the following: (i) physical measures: waist circumference, weight and blood pressure; (ii) lifestyle measures: smoking status, alcohol intake, physical activity and dietary intake; (iii) biochemical measures: fasting glucose, insulin and lipids (total and HDL cholesterol, triglycerides); and (iv) treatment compliance., Intervention: Lifestyle intervention (60 sites) or usual care (60 sites). Lifestyle intervention was delivered by a trained community health worker over 12 months (5 one-one sessions, 4 group sessions, 13 telephone sessions) with the goal of the participants achieving a 7% reduction in body mass index and a 10-cm reduction in waist circumference through (i) improved diet and (ii) increased physical activity. Usual care comprised a single 30-min session of lifestyle modification advice from the community health worker., Results: We screened 33,212 people for inclusion into the study. We identified 10,930 people who met study entry criteria, amongst whom 3682 agreed to take part in the intervention. Study participants are 49.2% female and aged 52.8 (SD 8.2) years. Clinical characteristics are well balanced between intervention and usual care sites. More than 90% of follow-up visits are scheduled to be complete in December 2020. Based on the follow-up to end 2019, the observed incidence of T2D in the study population is in line with expectations (6.1% per annum)., Conclusion: The iHealth-T2D study will advance understanding of strategies for the prevention of diabetes amongst South Asians, use approaches for screening and intervention that are adapted for low-resource settings. Our study will thus inform the implementation of strategies for improving the health and well-being of this major global ethnic group., Irb Approval: 16/WM/0171 TRIAL REGISTRATION: EudraCT 2016-001350-18 . Registered on 14 April 2016. ClinicalTrials.gov NCT02949739 . Registered on 31 October 2016, First posted on 31/10/2016., (© 2021. The Author(s).)- Published
- 2021
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130. Meta-analyses identify DNA methylation associated with kidney function and damage.
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Schlosser P, Tin A, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Weihs A, Yu Z, Hoppmann A, Grundner-Culemann F, Min JL, Adeyemo AA, Agyemang C, Ärnlöv J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Breteler MMB, Carmeli C, Chaker L, Chambers JC, Cole SA, Coresh J, Corre T, Correa A, Cox SR, de Klein N, Delgado GE, Domingo-Relloso A, Eckardt KU, Ekici AB, Endlich K, Evans KL, Floyd JS, Fornage M, Franke L, Fraszczyk E, Gao X, Gào X, Ghanbari M, Ghasemi S, Gieger C, Greenland P, Grove ML, Harris SE, Hemani G, Henneman P, Herder C, Horvath S, Hou L, Hurme MA, Hwang SJ, Jarvelin MR, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kramer H, Kronenberg F, Kühnel B, Lehtimäki T, Lind L, Liu D, Liu Y, Lloyd-Jones DM, Lohman K, Lorkowski S, Lu AT, Marioni RE, März W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Navas-Acien A, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Rosas SE, Schöttker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundström J, Swenson BR, Tellez-Plaza M, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Verweij N, Walker RM, Wielscher M, Winkelmann J, Wolffenbuttel BHR, Zhao W, Zheng Y, Loh M, Snieder H, Levy D, Waldenberger M, Susztak K, Köttgen A, and Teumer A
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- Adult, Aged, CpG Islands, Female, Glomerular Filtration Rate, Humans, Interferon Regulatory Factors genetics, Interferon Regulatory Factors metabolism, Kidney metabolism, Kidney physiopathology, Kidney Function Tests, LIM Domain Proteins genetics, LIM Domain Proteins metabolism, Male, Membrane Proteins genetics, Membrane Proteins metabolism, Middle Aged, Renal Insufficiency, Chronic metabolism, Renal Insufficiency, Chronic physiopathology, Transcription Factors genetics, Transcription Factors metabolism, DNA Methylation, Renal Insufficiency, Chronic genetics
- Abstract
Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. To extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. Associations of DNA methylation with kidney function, such as CpGs at JAZF1, PELI1 and CHD2 were validated in kidney tissue. Methylation at PHRF1, LDB2, CSRNP1 and IRF5 indicated causal effects on kidney function. Enrichment analyses revealed pathways related to hemostasis and blood cell migration for estimated glomerular filtration rate, and immune cell activation and response for urinary albumin-to-creatinineratio-associated CpGs., (© 2021. The Author(s).)
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- 2021
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131. The power of genetic diversity in genome-wide association studies of lipids.
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Graham SE, Clarke SL, Wu KH, 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 YI, 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, and Willer CJ
- Subjects
- Genetic Predisposition to Disease genetics, Humans, Linkage Disequilibrium, Multifactorial Inheritance, Polymorphism, Single Nucleotide genetics, Population Groups, Cardiovascular Diseases genetics, Genome-Wide Association Study methods
- Abstract
Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use
1 . 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., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)- Published
- 2021
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132. An agenda-setting paper on data sharing platforms: euCanSHare workshop.
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Devriendt T, Ammann C, W Asselbergs F, Bernier A, Costas R, Friedrich MG, Gelpi JL, Jarvelin MR, Kuulasmaa K, Lekadir K, Mayrhofer MT, Papez V, Pasterkamp G, Petersen SE, Schmidt CO, Schulz-Menger J, Söderberg S, Shabani M, Veronesi G, Viezzer DS, and Borry P
- Abstract
Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Devriendt T et al.)
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- 2021
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133. Rare variant analysis in eczema identifies exonic variants in DUSP1, NOTCH4 and SLC9A4.
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Grosche S, Marenholz I, Esparza-Gordillo J, Arnau-Soler A, Pairo-Castineira E, Rüschendorf F, Ahluwalia TS, Almqvist C, Arnold A, Baurecht H, Bisgaard H, Bønnelykke K, Brown SJ, Bustamante M, Curtin JA, Custovic A, Dharmage SC, Esplugues A, Falchi M, Fernandez-Orth D, Ferreira MAR, Franke A, Gerdes S, Gieger C, Hakonarson H, Holt PG, Homuth G, Hubner N, Hysi PG, Jarvelin MR, Karlsson R, Koppelman GH, Lau S, Lutz M, Magnusson PKE, Marks GB, Müller-Nurasyid M, Nöthen MM, Paternoster L, Pennell CE, Peters A, Rawlik K, Robertson CF, Rodriguez E, Sebert S, Simpson A, Sleiman PMA, Standl M, Stölzl D, Strauch K, Szwajda A, Tenesa A, Thompson PJ, Ullemar V, Visconti A, Vonk JM, Wang CA, Weidinger S, Wielscher M, Worth CL, Xu CJ, and Lee YA
- Subjects
- Cytokine Receptor Common beta Subunit, Dual Specificity Phosphatase 1 chemistry, Dual Specificity Phosphatase 1 metabolism, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Matrix Attachment Region Binding Proteins, Polymorphism, Single Nucleotide, Rare Diseases genetics, Receptor, Notch4 chemistry, Receptor, Notch4 metabolism, Sodium-Hydrogen Exchangers chemistry, Sodium-Hydrogen Exchangers metabolism, Dual Specificity Phosphatase 1 genetics, Eczema diagnosis, Eczema genetics, Receptor, Notch4 genetics, Sodium-Hydrogen Exchangers genetics
- Abstract
Previous genome-wide association studies revealed multiple common variants involved in eczema but the role of rare variants remains to be elucidated. Here, we investigate the role of rare variants in eczema susceptibility. We meta-analyze 21 study populations including 20,016 eczema cases and 380,433 controls. Rare variants are imputed with high accuracy using large population-based reference panels. We identify rare exonic variants in DUSP1, NOTCH4, and SLC9A4 to be associated with eczema. In DUSP1 and NOTCH4 missense variants are predicted to impact conserved functional domains. In addition, five novel common variants at SATB1-AS1/KCNH8, TRIB1/LINC00861, ZBTB1, TBX21/OSBPL7, and CSF2RB are discovered. While genes prioritized based on rare variants are significantly up-regulated in the skin, common variants point to immune cell function. Over 20% of the single nucleotide variant-based heritability is attributable to rare and low-frequency variants. The identified rare/low-frequency variants located in functional protein domains point to promising targets for novel therapeutic approaches to eczema., (© 2021. The Author(s).)
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- 2021
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134. Effects of a lifestyle intervention programme after 1 year of follow-up among South Asians at high risk of type 2 diabetes: a cluster randomised controlled trial.
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Muilwijk M, Loh M, Siddiqui S, Mahmood S, Palaniswamy S, Shahzad K, Athauda LK, Jayawardena R, Batool T, Burney S, Glover M, Bamunuarachchi V, Panda M, Madawanarachchi M, Rai B, Sattar I, Silva W, Waghdhare S, Jarvelin MR, Rannan-Eliya RP, Wijemunige N, Gage HM, Valabhji J, Frost GS, Wickremasinghe R, Kasturiratne A, Khawaja KI, Ahmad S, van Valkengoed IG, Katulanda P, Jha S, Kooner JS, and Chambers JC
- Subjects
- Adult, Asian People, Female, Follow-Up Studies, Humans, Life Style, Male, Weight Loss, Diabetes Mellitus, Type 2 prevention & control
- Abstract
Introduction: South Asians are at high risk of type 2 diabetes (T2D). We assessed whether intensive family-based lifestyle intervention leads to significant weight loss, improved glycaemia and blood pressure in adults at elevated risk for T2D., Methods: This cluster randomised controlled trial (iHealth-T2D) was conducted at 120 locations across India, Pakistan, Sri Lanka and the UK. We included 3684 South Asian men and women, aged 40-70 years, without T2D but with raised haemoglobin A1c (HbA1c) and/or waist circumference. Participants were randomly allocated either to the family-based lifestyle intervention or control group by location clusters. Participants in the intervention received 9 visits and 13 telephone contacts by community health workers over 1-year period, and the control group received usual care. Reductions in weight (aim >7% reduction), waist circumference (aim ≥5 cm reduction), blood pressure and HbA1C at 12 months of follow-up were assessed. Our linear mixed-effects regression analysis was based on intention-to-treat principle and adjusted for age, sex and baseline values., Results: There were 1846 participants in the control and 1838 in the intervention group. Between baseline and 12 months, mean weight of participants in the intervention group reduced by 1.8 kg compared with 0.4 kg in the control group (adjusted mean difference -1.10 kg (95% CI -1.70 to -1.06), p<0.001). The adjusted mean difference for waist circumference was -1.9 cm (95% CI -2.5; to 1.3), p<0.001). No overall difference was observed for blood pressure or HbA1c. People who attended multiple intervention sessions had a dose-dependent effect on waist circumference, blood pressure and HbA1c, but not on weight., Conclusion: An intensive family-based lifestyle intervention adopting low-resource strategies led to effective reduction in weight and waist circumference at 12 months, which has potential long-term benefits for preventing T2D. A higher number of attended sessions increased the effect on waist circumference, blood pressure and HbA1c., Trial Registration Number: EudraCT: 2016-001350-18; ClinicalTrials.gov: NCT02949739., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
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- 2021
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135. Rare and low-frequency exonic variants and gene-by-smoking interactions in pulmonary function.
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Yang T, Jackson VE, Smith AV, Chen H, Bartz TM, Sitlani CM, Psaty BM, Gharib SA, O'Connor GT, Dupuis J, Xu J, Lohman K, Liu Y, Kritchevsky SB, Cassano PA, Flexeder C, Gieger C, Karrasch S, Peters A, Schulz H, Harris SE, Starr JM, Deary IJ, Manichaikul A, Oelsner EC, Barr RG, Taylor KD, Rich SS, Bonten TN, Mook-Kanamori DO, Noordam R, Li-Gao R, Jarvelin MR, Wielscher M, Terzikhan N, Lahousse L, Brusselle G, Weiss S, Ewert R, Gläser S, Homuth G, Shrine N, Hall IP, Tobin M, London SJ, Wei P, and Morrison AC
- Subjects
- Adult, Aged, Aged, 80 and over, Cigarette Smoking adverse effects, Cyclic Nucleotide Phosphodiesterases, Type 3 genetics, Datasets as Topic, Exons genetics, Feasibility Studies, Female, Genome-Wide Association Study, Humans, Lung physiology, Male, Middle Aged, Polymorphism, Single Nucleotide, Receptors, G-Protein-Coupled genetics, Risk Factors, Cigarette Smoking epidemiology, Forced Expiratory Volume genetics, Gene-Environment Interaction
- Abstract
Genome-wide association studies have identified numerous common genetic variants associated with spirometric measures of pulmonary function, including forced expiratory volume in one second (FEV
1 ), forced vital capacity, and their ratio. However, variants with lower minor allele frequencies are less explored. We conducted a large-scale gene-smoking interaction meta-analysis on exonic rare and low-frequency variants involving 44,429 individuals of European ancestry in the discovery stage and sought replication in the UK BiLEVE study with 45,133 European ancestry samples and UK Biobank study with 59,478 samples. We leveraged data on cigarette smoking, the major environmental risk factor for reduced lung function, by testing gene-by-smoking interaction effects only and simultaneously testing the genetic main effects and interaction effects. The most statistically significant signal that replicated was a previously reported low-frequency signal in GPR126, distinct from common variant associations in this gene. Although only nominal replication was obtained for a top rare variant signal rs142935352 in one of the two studies, interaction and joint tests for current smoking and PDE3B were significantly associated with FEV1 . This study investigates the utility of assessing gene-by-smoking interactions and underscores their effects on potential pulmonary function., (© 2021. The Author(s).)- Published
- 2021
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136. Epigenome-Wide Association Study Reveals Methylation Loci Associated With Offspring Gestational Diabetes Mellitus Exposure and Maternal Methylome.
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Canouil M, Khamis A, Keikkala E, Hummel S, Lobbens S, Bonnefond A, Delahaye F, Tzala E, Mustaniemi S, Vääräsmäki M, Jarvelin MR, Sebert S, Kajantie E, Froguel P, and Andrew T
- Subjects
- DNA Methylation, DNA-Binding Proteins genetics, Epigenome, Female, GTPase-Activating Proteins, Humans, Pregnancy, Prospective Studies, Transcription Factors genetics, Diabetes Mellitus, Type 2 genetics, Diabetes, Gestational genetics
- Abstract
Objective: Gestational diabetes mellitus (GDM) is associated with an increased risk of obesity and insulin resistance in offspring later in life, which might be explained by epigenetic changes in response to maternal hyperglycemic exposure., Research Design and Methods: We explored the association between GDM exposure and maternal blood and newborn cord blood methylation in 536 mother-offspring pairs from the prospective FinnGeDi cohort using Illumina MethylationEPIC 850K BeadChip arrays. We assessed two hypotheses. First, we tested for shared maternal and offspring epigenetic effects resulting from GDM exposure. Second, we tested whether GDM exposure and maternal methylation had an epigenetic effect on the offspring., Results: We did not find any epigenetic marks (differentially methylated CpG probes) with shared and consistent effects between mothers and offspring. After including maternal methylation in the model, we identified a single significant (false discovery rate 1.38 × 10
-2 ) CpG at the cg22790973 probe ( TFCP2) associated with GDM. We identified seven additional FDR-significant interactions of maternal methylation and GDM status, with the strongest association at the same cg22790973 probe ( TFCP2) , as well as cg03456133, cg24440941 ( H3C6 ), cg20002843 ( LOC127841) , cg19107264, and cg11493553 located within the UBE3C gene and cg17065901 in FAM13A, both susceptibility genes for type 2 diabetes and BMI, and cg23355087 within the DLGAP2 gene, known to be involved in insulin resistance during pregnancy., Conclusions: Our study reveals the potential complexity of the epigenetic transmission between mothers with GDM and their offspring, likely determined by not only GDM exposure but also other factors indicated by maternal epigenetic status, such as maternal metabolic history., (© 2021 by the American Diabetes Association.)- Published
- 2021
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137. Markers of metabolic health and gut microbiome diversity: findings from two population-based cohort studies.
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Zouiouich S, Loftfield E, Huybrechts I, Viallon V, Louca P, Vogtmann E, Wells PM, Steves CJ, Herzig KH, Menni C, Jarvelin MR, Sinha R, and Gunter MJ
- Subjects
- Adult, Blood Glucose metabolism, C-Reactive Protein metabolism, Cohort Studies, Feces microbiology, Female, Finland, Glycated Hemoglobin metabolism, Humans, Male, Metabolic Syndrome physiopathology, Microbiota genetics, Middle Aged, RNA, Ribosomal, 16S genetics, Surveys and Questionnaires, Twin Studies as Topic, United Kingdom, Biomarkers, Energy Metabolism genetics, Gastrointestinal Microbiome genetics, Insulin Resistance genetics, Metabolic Syndrome genetics
- Abstract
Aims/hypothesis: The gut microbiome is hypothesised to be related to insulin resistance and other metabolic variables. However, data from population-based studies are limited. We investigated associations between serologic measures of metabolic health and the gut microbiome in the Northern Finland Birth Cohort 1966 (NFBC1966) and the TwinsUK cohort., Methods: Among 506 individuals from the NFBC1966 with available faecal microbiome (16S rRNA gene sequence) data, we estimated associations between gut microbiome diversity metrics and serologic levels of HOMA for insulin resistance (HOMA-IR), HbA
1c and C-reactive protein (CRP) using multivariable linear regression models adjusted for sex, smoking status and BMI. Associations between gut microbiome diversity measures and HOMA-IR and CRP were replicated in 1140 adult participants from TwinsUK, with available faecal microbiome (16S rRNA gene sequence) data. For both cohorts, we used general linear models with a quasi-Poisson distribution and Microbiome Regression-based Kernel Association Test (MiRKAT) to estimate associations of metabolic variables with alpha- and beta diversity metrics, respectively, and generalised additive models for location scale and shape (GAMLSS) fitted with the zero-inflated beta distribution to identify taxa associated with the metabolic markers., Results: In NFBC1966, alpha diversity was lower in individuals with higher HOMA-IR with a mean of 74.4 (95% CI 70.7, 78.3) amplicon sequence variants (ASVs) for the first quartile of HOMA-IR and 66.6 (95% CI 62.9, 70.4) for the fourth quartile of HOMA-IR. Alpha diversity was also lower with higher HbA1c (number of ASVs and Shannon's diversity, p < 0.001 and p = 0.003, respectively) and higher CRP (number of ASVs, p = 0.025), even after adjustment for BMI and other potential confounders. In TwinsUK, alpha diversity measures were also lower among participants with higher measures of HOMA-IR and CRP. When considering beta diversity measures, we found that microbial community profiles were associated with HOMA-IR in NFBC1966 and TwinsUK, using multivariate MiRKAT models, with binomial deviance dissimilarity p values of <0.001. In GAMLSS models, the relative abundances of individual genera Prevotella and Blautia were associated with HOMA-IR in both cohorts., Conclusions/interpretation: Overall, higher levels of HOMA-IR, CRP and HbA1c were associated with lower microbiome diversity in both the NFBC1966 and TwinsUK cohorts, even after adjustment for BMI and other variables. These results from two distinct population-based cohorts provide evidence for an association between metabolic variables and gut microbial diversity. Further experimental and mechanistic insights are now needed to provide understanding of the potential causal mechanisms that may link the gut microbiota with metabolic health.- Published
- 2021
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138. Signatures of TSPAN8 variants associated with human metabolic regulation and diseases.
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De T, Goncalves A, Speed D, Froguel P, Gaffney DJ, Johnson MR, Jarvelin MR, and Coin LJ
- Abstract
Here, with the example of common copy number variation (CNV) in the TSPAN8 gene, we present an important piece of work in the field of CNV detection, that is, CNV association with complex human traits such as
1 H NMR metabolomic phenotypes and an example of functional characterization of CNVs among human induced pluripotent stem cells (HipSci). We report TSPAN8 exon 11 (ENSE00003720745) as a pleiotropic locus associated with metabolomic regulation and show that its biology is associated with several metabolic diseases such as type 2 diabetes (T2D) and cancer. Our results further demonstrate the power of multivariate association models over univariate methods and define metabolomic signatures for variants in TSPAN8 ., Competing Interests: No external or financial interests to be declared., (© 2021 The Author(s).)- Published
- 2021
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139. Body size during adulthood, but not in childhood, associates with endometriosis, specifically in the peritoneal subtype-population-based life-course data from birth to late fertile age.
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Rossi HR, Nedelec R, Jarvelin MR, Sebert S, Uimari O, and Piltonen TT
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- Adolescent, Adult, Age Factors, Body Mass Index, Cohort Studies, Endometriosis pathology, Female, Finland, Humans, Middle Aged, Risk Factors, Waist Circumference, Young Adult, Adiposity, Body Size, Endometriosis diagnosis
- Abstract
Introduction: Endometriosis is a common gynecological condition causing chronic pain and infertility. Only limited data exist on body size during childhood and adolescence in affected women. A leaner body shape has been associated with endometriosis in adults. However, longitudinal follow-up data from birth to adulthood are lacking. The aim of this study was to assess the association between body size and endometriosis from birth to age 46 years. We also performed in-depth analysis of the endometriosis subtypes., Material and Methods: This was a population-based study including 96% of the children born in Northern Finland in 1966. Endometriosis case identification was based on (a) the World Health Organization's International Statistical Classification of Diseases code documentation from national hospital discharge registers and (b) self-reported diagnosis. A total of 348 women with endometriosis (203 in subtype analysis) and 3487 women without endometriosis were identified. Pregnancy, birth, and growth data up to adolescence were collected from welfare clinical records. Follow-up data of the Northern Finland Birth Cohort 1966 were collected at ages 14, 31, and 46 years through postal questionnaires and clinical examinations and included height, weight, and waist and hip circumference measurements. The associations between endometriosis and body size were assessed using logistic regression models., Results: Body sizes in childhood and adolescence were comparable between women developing endometriosis and those not developing endometriosis. On average, the risk for endometriosis was 2% lower for every kilogram of weight (odds ratio [OR] 0.98, 95% CI 0.97-1.00) and 6% lower for every body mass index unit (OR 0.94, 95% CI 0.90-0.99) at age 31. By age 46, a lower risk for peritoneal endometriosis was observed with greater weight (OR 0.95, 95% CI 0.92-0.98), weight gain from age 14 to age 46 years (OR 0.97, 95% CI 0.93-1.00), body mass index (OR 0.90, 95% CI 0.82-0.98), waist circumference (OR 0.95, 95% CI 0.92-0.99), and waist-hip ratio (OR 0.41, 95% CI 0.21-0.78)., Conclusions: This study provides further evidence of the associations between endometriosis and body size and adiposity, specifically in women with peritoneal endometriosis. The associations are evident in adulthood but not in childhood or adolescence., (© 2021 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)
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- 2021
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140. Genetic correlation and causal relationships between cardio-metabolic traits and lung function impairment.
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Wielscher M, Amaral AFS, van der Plaat D, Wain LV, Sebert S, Mosen-Ansorena D, Auvinen J, Herzig KH, Dehghan A, Jarvis DL, and Jarvelin MR
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- Biomarkers, Body Mass Index, Cardiovascular Diseases complications, Cardiovascular Diseases epidemiology, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Disease Susceptibility, Finland epidemiology, Genetic Predisposition to Disease, Humans, Inflammation Mediators, Linkage Disequilibrium, Lung Diseases epidemiology, Lung Diseases etiology, Metabolic Syndrome complications, Metabolic Syndrome epidemiology, Polymorphism, Single Nucleotide, Public Health Surveillance, Respiratory Function Tests, Risk Assessment, Cardiometabolic Risk Factors, Genetic Association Studies, Lung metabolism, Lung physiopathology, Quantitative Trait Loci, Quantitative Trait, Heritable
- Abstract
Background: Associations of low lung function with features of poor cardio-metabolic health have been reported. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability or are confounded by environmental factors., Methods: We performed three analyses: (1) cardio-metabolic health to lung function association tests in Northern Finland Birth cohort 1966, (2) cross-trait linkage disequilibrium score regression (LDSC) to compare genetic backgrounds and (3) Mendelian randomisation (MR) analysis to assess the causal effect of cardio-metabolic traits and disease on lung function, and vice versa (bidirectional MR). Genetic associations were obtained from the UK Biobank data or published large-scale genome-wide association studies (N > 82,000)., Results: We observed a negative genetic correlation between lung function and cardio-metabolic traits and diseases. In Mendelian Randomisation analysis (MR), we found associations between type 2 diabetes (T2D) instruments and forced vital capacity (FVC) as well as FEV1/FVC. Body mass index (BMI) instruments were associated to all lung function traits and C-reactive protein (CRP) instruments to FVC. These genetic associations provide evidence for a causal effect of cardio-metabolic traits on lung function. Multivariable MR suggested independence of these causal effects from other tested cardio-metabolic traits and diseases. Analysis of lung function specific SNPs revealed a potential causal effect of FEV1/FVC on blood pressure., Conclusions: The present study overcomes many limitations of observational studies by using Mendelian Randomisation. We provide evidence for an independent causal effect of T2D, CRP and BMI on lung function with some of the T2D effect on lung function being attributed to inflammatory mechanisms. Furthermore, this analysis suggests a potential causal effect of FEV1/FVC on blood pressure. Our detailed analysis of the interplay between cardio-metabolic traits and impaired lung function provides the opportunity to improve the quality of existing intervention strategies.
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- 2021
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141. The trans-ancestral genomic architecture of glycemic traits.
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Chen J, Spracklen CN, Marenne G, Varshney A, Corbin LJ, Luan J, Willems SM, Wu Y, Zhang X, Horikoshi M, Boutin TS, Mägi R, Waage J, Li-Gao R, Chan KHK, Yao J, Anasanti MD, Chu AY, Claringbould A, Heikkinen J, Hong J, Hottenga JJ, Huo S, Kaakinen MA, Louie T, März W, Moreno-Macias H, Ndungu A, Nelson SC, Nolte IM, North KE, Raulerson CK, Ray D, Rohde R, Rybin D, Schurmann C, Sim X, Southam L, Stewart ID, Wang CA, Wang Y, Wu P, Zhang W, Ahluwalia TS, Appel EVR, Bielak LF, Brody JA, Burtt NP, Cabrera CP, Cade BE, Chai JF, Chai X, Chang LC, Chen CH, Chen BH, Chitrala KN, Chiu YF, de Haan HG, Delgado GE, Demirkan A, Duan Q, Engmann J, Fatumo SA, Gayán J, Giulianini F, Gong JH, Gustafsson S, Hai Y, Hartwig FP, He J, Heianza Y, Huang T, Huerta-Chagoya A, Hwang MY, Jensen RA, Kawaguchi T, Kentistou KA, Kim YJ, Kleber ME, Kooner IK, Lai S, Lange LA, Langefeld CD, Lauzon M, Li M, Ligthart S, Liu J, Loh M, Long J, Lyssenko V, Mangino M, Marzi C, Montasser ME, Nag A, Nakatochi M, Noce D, Noordam R, Pistis G, Preuss M, Raffield L, Rasmussen-Torvik LJ, Rich SS, Robertson NR, Rueedi R, Ryan K, Sanna S, Saxena R, Schraut KE, Sennblad B, Setoh K, Smith AV, Sparsø T, Strawbridge RJ, Takeuchi F, Tan J, Trompet S, van den Akker E, van der Most PJ, Verweij N, Vogel M, Wang H, Wang C, Wang N, Warren HR, Wen W, Wilsgaard T, Wong A, Wood AR, Xie T, Zafarmand MH, Zhao JH, Zhao W, Amin N, Arzumanyan Z, Astrup A, Bakker SJL, Baldassarre D, Beekman M, Bergman RN, Bertoni A, Blüher M, Bonnycastle LL, Bornstein SR, Bowden DW, Cai Q, Campbell A, Campbell H, Chang YC, de Geus EJC, Dehghan A, Du S, Eiriksdottir G, Farmaki AE, Frånberg M, Fuchsberger C, Gao Y, Gjesing AP, Goel A, Han S, Hartman CA, Herder C, Hicks AA, Hsieh CH, Hsueh WA, Ichihara S, Igase M, Ikram MA, Johnson WC, Jørgensen ME, Joshi PK, Kalyani RR, Kandeel FR, Katsuya T, Khor CC, Kiess W, Kolcic I, Kuulasmaa T, Kuusisto J, Läll K, Lam K, Lawlor DA, Lee NR, Lemaitre RN, Li H, Lin SY, Lindström J, Linneberg A, Liu J, Lorenzo C, Matsubara T, Matsuda F, Mingrone G, Mooijaart S, Moon S, Nabika T, Nadkarni GN, Nadler JL, Nelis M, Neville MJ, Norris JM, Ohyagi Y, Peters A, Peyser PA, Polasek O, Qi Q, Raven D, Reilly DF, Reiner A, Rivideneira F, Roll K, Rudan I, Sabanayagam C, Sandow K, Sattar N, Schürmann A, Shi J, Stringham HM, Taylor KD, Teslovich TM, Thuesen B, Timmers PRHJ, Tremoli E, Tsai MY, Uitterlinden A, van Dam RM, van Heemst D, van Hylckama Vlieg A, van Vliet-Ostaptchouk JV, Vangipurapu J, Vestergaard H, Wang T, Willems van Dijk K, Zemunik T, Abecasis GR, Adair LS, Aguilar-Salinas CA, Alarcón-Riquelme ME, An P, Aviles-Santa L, Becker DM, Beilin LJ, Bergmann S, Bisgaard H, Black C, Boehnke M, Boerwinkle E, Böhm BO, Bønnelykke K, Boomsma DI, Bottinger EP, Buchanan TA, Canouil M, Caulfield MJ, Chambers JC, Chasman DI, Chen YI, Cheng CY, Collins FS, Correa A, Cucca F, de Silva HJ, Dedoussis G, Elmståhl S, Evans MK, Ferrannini E, Ferrucci L, Florez JC, Franks PW, Frayling TM, Froguel P, Gigante B, Goodarzi MO, Gordon-Larsen P, Grallert H, Grarup N, Grimsgaard S, Groop L, Gudnason V, Guo X, Hamsten A, Hansen T, Hayward C, Heckbert SR, Horta BL, Huang W, Ingelsson E, James PS, Jarvelin MR, Jonas JB, Jukema JW, Kaleebu P, Kaplan R, Kardia SLR, Kato N, Keinanen-Kiukaanniemi SM, Kim BJ, Kivimaki M, Koistinen HA, Kooner JS, Körner A, Kovacs P, Kuh D, Kumari M, Kutalik Z, Laakso M, Lakka TA, Launer LJ, Leander K, Li H, Lin X, Lind L, Lindgren C, Liu S, Loos RJF, Magnusson PKE, Mahajan A, Metspalu A, Mook-Kanamori DO, Mori TA, Munroe PB, Njølstad I, O'Connell JR, Oldehinkel AJ, Ong KK, Padmanabhan S, Palmer CNA, Palmer ND, Pedersen O, Pennell CE, Porteous DJ, Pramstaller PP, Province MA, Psaty BM, Qi L, Raffel LJ, Rauramaa R, Redline S, Ridker PM, Rosendaal FR, Saaristo TE, Sandhu M, Saramies J, Schneiderman N, Schwarz P, Scott LJ, Selvin E, Sever P, Shu XO, Slagboom PE, Small KS, Smith BH, Snieder H, Sofer T, Sørensen TIA, Spector TD, Stanton A, Steves CJ, Stumvoll M, Sun L, Tabara Y, Tai ES, Timpson NJ, Tönjes A, Tuomilehto J, Tusie T, Uusitupa M, van der Harst P, van Duijn C, Vitart V, Vollenweider P, Vrijkotte TGM, Wagenknecht LE, Walker M, Wang YX, Wareham NJ, Watanabe RM, Watkins H, Wei WB, Wickremasinghe AR, Willemsen G, Wilson JF, Wong TY, Wu JY, Xiang AH, Yanek LR, Yengo L, Yokota M, Zeggini E, Zheng W, Zonderman AB, Rotter JI, Gloyn AL, McCarthy MI, Dupuis J, Meigs JB, Scott RA, Prokopenko I, Leong A, Liu CT, Parker SCJ, Mohlke KL, Langenberg C, Wheeler E, Morris AP, and Barroso I
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- Alleles, Epigenesis, Genetic, Gene Expression Profiling, Genome, Human, Genome-Wide Association Study, Glycated Hemoglobin metabolism, Humans, Multifactorial Inheritance genetics, Physical Chromosome Mapping, Quantitative Trait Loci genetics, Blood Glucose genetics, Quantitative Trait, Heritable, White People genetics
- Abstract
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10
-8 ), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.- Published
- 2021
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142. Variation in the SERPINA6/SERPINA1 locus alters morning plasma cortisol, hepatic corticosteroid binding globulin expression, gene expression in peripheral tissues, and risk of cardiovascular disease.
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Crawford AA, Bankier S, Altmaier E, Barnes CLK, Clark DW, Ermel R, Friedrich N, van der Harst P, Joshi PK, Karhunen V, Lahti J, Mahajan A, Mangino M, Nethander M, Neumann A, Pietzner M, Sukhavasi K, Wang CA, Bakker SJL, Bjorkegren JLM, Campbell H, Eriksson J, Gieger C, Hayward C, Jarvelin MR, McLachlan S, Morris AP, Ohlsson C, Pennell CE, Price J, Rudan I, Ruusalepp A, Spector T, Tiemeier H, Völzke H, Wilson JF, Michoel T, Timpson NJ, Smith GD, and Walker BR
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- Adrenal Cortex Hormones blood, Adult, Biological Specimen Banks, Cardiovascular Diseases blood, Cardiovascular Diseases epidemiology, Cardiovascular Diseases pathology, Female, Gene Expression Regulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Liver metabolism, Liver pathology, Male, Mendelian Randomization Analysis, Middle Aged, Myocardial Infarction blood, Myocardial Infarction pathology, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, United Kingdom, Cardiovascular Diseases genetics, Myocardial Infarction genetics, Transcortin genetics, alpha 1-Antitrypsin genetics
- Abstract
The stress hormone cortisol modulates fuel metabolism, cardiovascular homoeostasis, mood, inflammation and cognition. The CORtisol NETwork (CORNET) consortium previously identified a single locus associated with morning plasma cortisol. Identifying additional genetic variants that explain more of the variance in cortisol could provide new insights into cortisol biology and provide statistical power to test the causative role of cortisol in common diseases. The CORNET consortium extended its genome-wide association meta-analysis for morning plasma cortisol from 12,597 to 25,314 subjects and from ~2.2 M to ~7 M SNPs, in 17 population-based cohorts of European ancestries. We confirmed the genetic association with SERPINA6/SERPINA1. This locus contains genes encoding corticosteroid binding globulin (CBG) and α1-antitrypsin. Expression quantitative trait loci (eQTL) analyses undertaken in the STARNET cohort of 600 individuals showed that specific genetic variants within the SERPINA6/SERPINA1 locus influence expression of SERPINA6 rather than SERPINA1 in the liver. Moreover, trans-eQTL analysis demonstrated effects on adipose tissue gene expression, suggesting that variations in CBG levels have an effect on delivery of cortisol to peripheral tissues. Two-sample Mendelian randomisation analyses provided evidence that each genetically-determined standard deviation (SD) increase in morning plasma cortisol was associated with increased odds of chronic ischaemic heart disease (0.32, 95% CI 0.06-0.59) and myocardial infarction (0.21, 95% CI 0.00-0.43) in UK Biobank and similarly in CARDIoGRAMplusC4D. These findings reveal a causative pathway for CBG in determining cortisol action in peripheral tissues and thereby contributing to the aetiology of cardiovascular disease.
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- 2021
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143. DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan.
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van Dongen J, Hagenbeek FA, Suderman M, Roetman PJ, Sugden K, Chiocchetti AG, Ismail K, Mulder RH, Hafferty JD, Adams MJ, Walker RM, Morris SW, Lahti J, Küpers LK, Escaramis G, Alemany S, Jan Bonder M, Meijer M, Ip HF, Jansen R, Baselmans BML, Parmar P, Lowry E, Streit F, Sirignano L, Send TS, Frank J, Jylhävä J, Wang Y, Mishra PP, Colins OF, Corcoran DL, Poulton R, Mill J, Hannon E, Arseneault L, Korhonen T, Vuoksimaa E, Felix JF, Bakermans-Kranenburg MJ, Campbell A, Czamara D, Binder E, Corpeleijn E, Gonzalez JR, Grazuleviciene R, Gutzkow KB, Evandt J, Vafeiadi M, Klein M, van der Meer D, Ligthart L, Kluft C, Davies GE, Hakulinen C, Keltikangas-Järvinen L, Franke B, Freitag CM, Konrad K, Hervas A, Fernández-Rivas A, Vetro A, Raitakari O, Lehtimäki T, Vermeiren R, Strandberg T, Räikkönen K, Snieder H, Witt SH, Deuschle M, Pedersen NL, Hägg S, Sunyer J, Franke L, Kaprio J, Ollikainen M, Moffitt TE, Tiemeier H, van IJzendoorn MH, Relton C, Vrijheid M, Sebert S, Jarvelin MR, Caspi A, Evans KL, McIntosh AM, Bartels M, and Boomsma DI
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- Adolescent, Adult, Aged, Aggression, Child, Child, Preschool, CpG Islands genetics, Epigenesis, Genetic genetics, Genome-Wide Association Study, Humans, Longevity, Middle Aged, Young Adult, DNA Methylation genetics, Epigenome
- Abstract
DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10
-7 ; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits., (© 2021. The Author(s).)- Published
- 2021
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144. Genetic variation in cervical preinvasive and invasive disease: a genome-wide association study.
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Bowden SJ, Bodinier B, Kalliala I, Zuber V, Vuckovic D, Doulgeraki T, Whitaker MD, Wielscher M, Cartwright R, Tsilidis KK, Bennett P, Jarvelin MR, Flanagan JM, Chadeau-Hyam M, and Kyrgiou M
- Subjects
- Adult, Aged, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, HLA Antigens genetics, Humans, Middle Aged, Polymorphism, Single Nucleotide genetics, Uterine Cervical Neoplasms pathology, Uterine Cervical Dysplasia pathology, Membrane Proteins genetics, Neoplasm Proteins genetics, PAX8 Transcription Factor genetics, Uterine Cervical Neoplasms genetics, Uterine Cervical Dysplasia genetics
- Abstract
Background: Most uterine cervical high-risk human papillomavirus (HPV) infections are transient, with only a small fraction developing into cervical cancer. Family aggregation studies and heritability estimates suggest a significant inherited genetic component. Candidate gene studies and previous genome-wide association studies (GWASs) report associations between the HLA region and cervical cancer. Adopting a genome-wide approach, we aimed to compare genetic variation in women with invasive cervical cancer and cervical intraepithelial neoplasia (CIN) grade 3 with that in healthy controls., Methods: We did a GWAS in a cohort of unrelated European individuals using data from UK Biobank, a population-based cohort including 273 377 women aged 40-69 years at recruitment between March 13, 2006, and Oct 1, 2010. We used an additive univariate logistic regression model to analyse genetic variants associated with invasive cervical cancer or CIN3. We sought replication of candidate associations in FinnGen, a large independent dataset of 128 123 individuals. We also did a two-sample mendelian randomisation approach to explore the role of risk factors in the genetic risk of cervical cancer., Findings: We included 4769 CIN3 and invasive cervical cancer case samples and 145 545 control samples in the GWAS. Of 9 600 464 assayed and imputed single-nucleotide polymorphisms (SNPs), six independent variants were associated with CIN3 and invasive cervical cancer. These included novel loci rs10175462 (PAX8; odds ratio [OR] 0·87, 95% CI 0·84-0·91; p=1·07 × 10
-9 ) and rs27069 (CLPTM1L; 0·88, 0·84-0·92; p=2·51 × 10-9 ), and previously reported signals at rs9272050 (HLA-DQA1; 1·27, 1·21-1·32; p=2·51 × 10-28 ), rs6938453 (MICA; 0·79, 0·75-0·83; p=1·97 × 10-17 ), rs55986091 (HLA-DQB1; 0·66, 0·60-0·72; p=6·42 × 10-28 ), and rs9266183 (HLA-B; 0·73, 0·64-0·83; p=1·53 × 10-6 ). Three SNPs were replicated in the independent Finnish dataset of 1648 invasive cervical cancer cases: PAX8 (rs10175462; p=0·015), CLPTM1L (rs27069; p=2·54 × 10-7 ), and HLA-DQA1 (rs9272050; p=7·90 × 10-8 ). Mendelian randomisation further supported the complementary role of smoking (OR 2·46, 95% CI 1·64-3·69), older age at first pregnancy (0·80, 0·68-0·95), and number of sexual partners (1·95, 1·44-2·63) in the risk of developing cervical cancer., Interpretation: Our results provide new evidence for the genetic susceptibility to cervical cancer, specifically the PAX8, CLPTM1L, and HLA genes, suggesting disruption in apoptotic and immune function pathways. Future studies integrating host and viral, genetic, and epigenetic variation, could further elucidate complex host-viral interactions., Funding: NIHR Imperial BRC Wellcome 4i Clinician Scientist Training Programme., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)- Published
- 2021
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145. Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.
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Lagou V, Mägi R, Hottenga JJ, Grallert H, Perry JRB, Bouatia-Naji N, Marullo L, Rybin D, Jansen R, Min JL, Dimas AS, Ulrich A, Zudina L, Gådin JR, Jiang L, Faggian A, Bonnefond A, Fadista J, Stathopoulou MG, Isaacs A, Willems SM, Navarro P, Tanaka T, Jackson AU, Montasser ME, O'Connell JR, Bielak LF, Webster RJ, Saxena R, Stafford JM, Pourcain BS, Timpson NJ, Salo P, Shin SY, Amin N, Smith AV, Li G, Verweij N, Goel A, Ford I, Johnson PCD, Johnson T, Kapur K, Thorleifsson G, Strawbridge RJ, Rasmussen-Torvik LJ, Esko T, Mihailov E, Fall T, Fraser RM, Mahajan A, Kanoni S, Giedraitis V, Kleber ME, Silbernagel G, Meyer J, Müller-Nurasyid M, Ganna A, Sarin AP, Yengo L, Shungin D, Luan J, Horikoshi M, An P, Sanna S, Boettcher Y, Rayner NW, Nolte IM, Zemunik T, Iperen EV, Kovacs P, Hastie ND, Wild SH, McLachlan S, Campbell S, Polasek O, Carlson O, Egan J, Kiess W, Willemsen G, Kuusisto J, Laakso M, Dimitriou M, Hicks AA, Rauramaa R, Bandinelli S, Thorand B, Liu Y, Miljkovic I, Lind L, Doney A, Perola M, Hingorani A, Kivimaki M, Kumari M, Bennett AJ, Groves CJ, Herder C, Koistinen HA, Kinnunen L, Faire U, Bakker SJL, Uusitupa M, Palmer CNA, Jukema JW, Sattar N, Pouta A, Snieder H, Boerwinkle E, Pankow JS, Magnusson PK, Krus U, Scapoli C, de Geus EJCN, Blüher M, Wolffenbuttel BHR, Province MA, Abecasis GR, Meigs JB, Hovingh GK, Lindström J, Wilson JF, Wright AF, Dedoussis GV, Bornstein SR, Schwarz PEH, Tönjes A, Winkelmann BR, Boehm BO, März W, Metspalu A, Price JF, Deloukas P, Körner A, Lakka TA, Keinanen-Kiukaanniemi SM, Saaristo TE, Bergman RN, Tuomilehto J, Wareham NJ, Langenberg C, Männistö S, Franks PW, Hayward C, Vitart V, Kaprio J, Visvikis-Siest S, Balkau B, Altshuler D, Rudan I, Stumvoll M, Campbell H, van Duijn CM, Gieger C, Illig T, Ferrucci L, Pedersen NL, Pramstaller PP, Boehnke M, Frayling TM, Shuldiner AR, Peyser PA, Kardia SLR, Palmer LJ, Penninx BW, Meneton P, Harris TB, Navis G, Harst PV, Smith GD, Forouhi NG, Loos RJF, Salomaa V, Soranzo N, Boomsma DI, Groop L, Tuomi T, Hofman A, Munroe PB, Gudnason V, Siscovick DS, Watkins H, Lecoeur C, Vollenweider P, Franco-Cereceda A, Eriksson P, Jarvelin MR, Stefansson K, Hamsten A, Nicholson G, Karpe F, Dermitzakis ET, Lindgren CM, McCarthy MI, Froguel P, Kaakinen MA, Lyssenko V, Watanabe RM, Ingelsson E, Florez JC, Dupuis J, Barroso I, Morris AP, and Prokopenko I
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- 2021
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146. DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures.
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Gomez-Alonso MDC, Kretschmer A, Wilson R, Pfeiffer L, Karhunen V, Seppälä I, Zhang W, Mittelstraß K, Wahl S, Matias-Garcia PR, Prokisch H, Horn S, Meitinger T, Serrano-Garcia LR, Sebert S, Raitakari O, Loh M, Rathmann W, Müller-Nurasyid M, Herder C, Roden M, Hurme M, Jarvelin MR, Ala-Korpela M, Kooner JS, Peters A, Lehtimäki T, Chambers JC, Gieger C, Kettunen J, and Waldenberger M
- Subjects
- Adult, Aged, Aged, 80 and over, Cohort Studies, Female, Germany, Humans, Male, Middle Aged, Myocardial Infarction genetics, Myocardial Infarction physiopathology, Obesity genetics, Obesity physiopathology, DNA Methylation genetics, Epigenesis, Genetic, Genome-Wide Association Study, Lipid Metabolism genetics, Metabolome genetics
- Abstract
Background: The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances., Results: We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10
-10 ), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations., Conclusion: Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.- Published
- 2021
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147. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.
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Lagou V, Mägi R, Hottenga JJ, Grallert H, Perry JRB, Bouatia-Naji N, Marullo L, Rybin D, Jansen R, Min JL, Dimas AS, Ulrich A, Zudina L, Gådin JR, Jiang L, Faggian A, Bonnefond A, Fadista J, Stathopoulou MG, Isaacs A, Willems SM, Navarro P, Tanaka T, Jackson AU, Montasser ME, O'Connell JR, Bielak LF, Webster RJ, Saxena R, Stafford JM, Pourcain BS, Timpson NJ, Salo P, Shin SY, Amin N, Smith AV, Li G, Verweij N, Goel A, Ford I, Johnson PCD, Johnson T, Kapur K, Thorleifsson G, Strawbridge RJ, Rasmussen-Torvik LJ, Esko T, Mihailov E, Fall T, Fraser RM, Mahajan A, Kanoni S, Giedraitis V, Kleber ME, Silbernagel G, Meyer J, Müller-Nurasyid M, Ganna A, Sarin AP, Yengo L, Shungin D, Luan J, Horikoshi M, An P, Sanna S, Boettcher Y, Rayner NW, Nolte IM, Zemunik T, Iperen EV, Kovacs P, Hastie ND, Wild SH, McLachlan S, Campbell S, Polasek O, Carlson O, Egan J, Kiess W, Willemsen G, Kuusisto J, Laakso M, Dimitriou M, Hicks AA, Rauramaa R, Bandinelli S, Thorand B, Liu Y, Miljkovic I, Lind L, Doney A, Perola M, Hingorani A, Kivimaki M, Kumari M, Bennett AJ, Groves CJ, Herder C, Koistinen HA, Kinnunen L, Faire U, Bakker SJL, Uusitupa M, Palmer CNA, Jukema JW, Sattar N, Pouta A, Snieder H, Boerwinkle E, Pankow JS, Magnusson PK, Krus U, Scapoli C, de Geus EJCN, Blüher M, Wolffenbuttel BHR, Province MA, Abecasis GR, Meigs JB, Hovingh GK, Lindström J, Wilson JF, Wright AF, Dedoussis GV, Bornstein SR, Schwarz PEH, Tönjes A, Winkelmann BR, Boehm BO, März W, Metspalu A, Price JF, Deloukas P, Körner A, Lakka TA, Keinanen-Kiukaanniemi SM, Saaristo TE, Bergman RN, Tuomilehto J, Wareham NJ, Langenberg C, Männistö S, Franks PW, Hayward C, Vitart V, Kaprio J, Visvikis-Siest S, Balkau B, Altshuler D, Rudan I, Stumvoll M, Campbell H, van Duijn CM, Gieger C, Illig T, Ferrucci L, Pedersen NL, Pramstaller PP, Boehnke M, Frayling TM, Shuldiner AR, Peyser PA, Kardia SLR, Palmer LJ, Penninx BW, Meneton P, Harris TB, Navis G, Harst PV, Smith GD, Forouhi NG, Loos RJF, Salomaa V, Soranzo N, Boomsma DI, Groop L, Tuomi T, Hofman A, Munroe PB, Gudnason V, Siscovick DS, Watkins H, Lecoeur C, Vollenweider P, Franco-Cereceda A, Eriksson P, Jarvelin MR, Stefansson K, Hamsten A, Nicholson G, Karpe F, Dermitzakis ET, Lindgren CM, McCarthy MI, Froguel P, Kaakinen MA, Lyssenko V, Watanabe RM, Ingelsson E, Florez JC, Dupuis J, Barroso I, Morris AP, and Prokopenko I
- Subjects
- Adult, Anorexia Nervosa blood, Anorexia Nervosa ethnology, Anorexia Nervosa physiopathology, Fasting blood, Female, Gene Expression, Genetic Loci, Genome-Wide Association Study, Glucose Intolerance blood, Glucose Intolerance ethnology, Glucose Intolerance physiopathology, Humans, Insulin Receptor Substrate Proteins blood, Kruppel-Like Transcription Factors blood, Male, Middle Aged, Phenotype, Sex Characteristics, Sex Factors, Waist-Hip Ratio, White People, Anorexia Nervosa genetics, Blood Glucose metabolism, Glucose Intolerance genetics, Insulin blood, Insulin Receptor Substrate Proteins genetics, Insulin Resistance genetics, Kruppel-Like Transcription Factors genetics
- Abstract
Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
- Published
- 2021
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148. DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies.
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Vehmeijer FOL, Küpers LK, Sharp GC, Salas LA, Lent S, Jima DD, Tindula G, Reese S, Qi C, Gruzieva O, Page C, Rezwan FI, Melton PE, Nohr E, Escaramís G, Rzehak P, Heiskala A, Gong T, Tuominen ST, Gao L, Ross JP, Starling AP, Holloway JW, Yousefi P, Aasvang GM, Beilin LJ, Bergström A, Binder E, Chatzi L, Corpeleijn E, Czamara D, Eskenazi B, Ewart S, Ferre N, Grote V, Gruszfeld D, Håberg SE, Hoyo C, Huen K, Karlsson R, Kull I, Langhendries JP, Lepeule J, Magnus MC, Maguire RL, Molloy PL, Monnereau C, Mori TA, Oken E, Räikkönen K, Rifas-Shiman S, Ruiz-Arenas C, Sebert S, Ullemar V, Verduci E, Vonk JM, Xu CJ, Yang IV, Zhang H, Zhang W, Karmaus W, Dabelea D, Muhlhausler BS, Breton CV, Lahti J, Almqvist C, Jarvelin MR, Koletzko B, Vrijheid M, Sørensen TIA, Huang RC, Arshad SH, Nystad W, Melén E, Koppelman GH, London SJ, Holland N, Bustamante M, Murphy SK, Hivert MF, Baccarelli A, Relton CL, Snieder H, Jaddoe VWV, and Felix JF
- Subjects
- Adolescent, Child, Child, Preschool, CpG Islands, Cross-Sectional Studies, Epigenome, Female, Fetal Blood, Humans, Male, Pediatric Obesity genetics, Pregnancy, Body Mass Index, DNA Methylation, Epigenesis, Genetic, Obesity genetics, Parturition
- Abstract
Background: DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits., Methods: We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment., Results: DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10
-7 , with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10-4 ; adolescence Penrichment = 2.10 × 10-7 )., Conclusions: There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.- Published
- 2020
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149. Common variation at 16p11.2 is associated with glycosuria in pregnancy: findings from a genome-wide association study in European women.
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Lee MA, McMahon G, Karhunen V, Wade KH, Corbin LJ, Hughes DA, Smith GD, Lawlor DA, Jarvelin MR, and Timpson NJ
- Subjects
- Adolescent, Adult, Body Mass Index, Chromosomes, Human, Pair 16 genetics, Diabetes Mellitus, Type 2 drug therapy, Diabetes Mellitus, Type 2 pathology, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Glycosuria epidemiology, Glycosuria pathology, Humans, Polymorphism, Single Nucleotide genetics, Pregnancy, Pregnancy Complications pathology, Young Adult, Diabetes Mellitus, Type 2 genetics, Glycosuria genetics, Pregnancy Complications genetics, Sodium-Glucose Transporter 2 genetics
- Abstract
Glycosuria is a condition where glucose is detected in urine at higher concentrations than normal (i.e. not detectable). Glycosuria at some point during pregnancy has an estimated prevalence of 50% and is associated with adverse outcomes in both mothers and offspring. Little is currently known about the genetic contribution to this trait or the extent to which it overlaps with other seemingly related traits, e.g. diabetes. We performed a genome-wide association study (GWAS) for self-reported glycosuria in pregnant mothers from the Avon Longitudinal Study of Parents and Children (cases/controls = 1249/5140). We identified two loci, one of which (lead SNP = rs13337037; chromosome 16; odds ratio of glycosuria per effect allele: 1.42; 95% CI: 1.30, 1.56; P = 1.97 × 10-13) was then validated using an obstetric measure of glycosuria measured in the same cohort (227/6639). We performed a secondary GWAS in the 1986 Northern Finland Birth Cohort (NFBC1986; 747/2991) using midwife-reported glycosuria and offspring genotype as a proxy for maternal genotype. The combined results revealed evidence for a consistent effect on glycosuria at the chromosome 16 locus. In follow-up analyses, we saw little evidence of shared genetic underpinnings with the exception of urinary albumin-to-creatinine ratio (Rg = 0.64; SE = 0.22; P = 0.0042), a biomarker of kidney disease. In conclusion, we identified a genetic association with self-reported glycosuria during pregnancy, with the lead SNP located 15kB upstream of SLC5A2, a target of antidiabetic drugs. The lack of strong genetic correlation with seemingly related traits such as type 2 diabetes suggests different genetic risk factors exist for glycosuria during pregnancy., (© The Author(s) 2020. Published by Oxford University Press.)
- Published
- 2020
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150. Genetic Associations Between Childhood Psychopathology and Adult Depression and Associated Traits in 42 998 Individuals: A Meta-analysis.
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Akingbuwa WA, Hammerschlag AR, Jami ES, Allegrini AG, Karhunen V, Sallis H, Ask H, Askeland RB, Baselmans B, Diemer E, Hagenbeek FA, Havdahl A, Hottenga JJ, Mbarek H, Rivadeneira F, Tesli M, van Beijsterveldt C, Breen G, Lewis CM, Thapar A, Boomsma DI, Kuja-Halkola R, Reichborn-Kjennerud T, Magnus P, Rimfeld K, Ystrom E, Jarvelin MR, Lichtenstein P, Lundstrom S, Munafò MR, Plomin R, Tiemeier H, Nivard MG, Bartels M, and Middeldorp CM
- Subjects
- Adolescent, Adult, Bipolar Disorder epidemiology, Bipolar Disorder genetics, Child, Europe epidemiology, Humans, Longitudinal Studies, Social Behavior, Young Adult, Attention Deficit Disorder with Hyperactivity epidemiology, Attention Deficit Disorder with Hyperactivity genetics, Behavioral Symptoms epidemiology, Behavioral Symptoms genetics, Body Mass Index, Depressive Disorder, Major epidemiology, Depressive Disorder, Major genetics, Educational Status, Multifactorial Inheritance genetics, Neuroticism, Personal Satisfaction, Sleep Initiation and Maintenance Disorders epidemiology, Sleep Initiation and Maintenance Disorders genetics
- Abstract
Importance: Adult mood disorders are often preceded by behavioral and emotional problems in childhood. It is yet unclear what explains the associations between childhood psychopathology and adult traits., Objective: To investigate whether genetic risk for adult mood disorders and associated traits is associated with childhood disorders., Design, Setting, and Participants: This meta-analysis examined data from 7 ongoing longitudinal birth and childhood cohorts from the UK, the Netherlands, Sweden, Norway, and Finland. Starting points of data collection ranged from July 1985 to April 2002. Participants were repeatedly assessed for childhood psychopathology from ages 6 to 17 years. Data analysis occurred from September 2017 to May 2019., Exposures: Individual polygenic scores (PGS) were constructed in children based on genome-wide association studies of adult major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI)., Main Outcomes and Measures: Regression meta-analyses were used to test associations between PGS and attention-deficit/hyperactivity disorder (ADHD) symptoms and internalizing and social problems measured repeatedly across childhood and adolescence and whether these associations depended on childhood phenotype, age, and rater., Results: The sample included 42 998 participants aged 6 to 17 years. Male participants varied from 43.0% (1040 of 2417 participants) to 53.1% (2434 of 4583 participants) by age and across all cohorts. The PGS of adult major depression, neuroticism, BMI, and insomnia were positively associated with childhood psychopathology (β estimate range, 0.023-0.042 [95% CI, 0.017-0.049]), while associations with PGS of subjective well-being and educational attainment were negative (β, -0.026 to -0.046 [95% CI, -0.020 to -0.057]). There was no moderation of age, type of childhood phenotype, or rater with the associations. The exceptions were stronger associations between educational attainment PGS and ADHD compared with internalizing problems (Δβ, 0.0561 [Δ95% CI, 0.0318-0.0804]; ΔSE, 0.0124) and social problems (Δβ, 0.0528 [Δ95% CI, 0.0282-0.0775]; ΔSE, 0.0126), and between BMI PGS and ADHD and social problems (Δβ, -0.0001 [Δ95% CI, -0.0102 to 0.0100]; ΔSE, 0.0052), compared with internalizing problems (Δβ, -0.0310 [Δ95% CI, -0.0456 to -0.0164]; ΔSE, 0.0074). Furthermore, the association between educational attainment PGS and ADHD increased with age (Δβ, -0.0032 [Δ 95% CI, -0.0048 to -0.0017]; ΔSE, 0.0008)., Conclusions and Relevance: Results from this study suggest the existence of a set of genetic factors influencing a range of traits across the life span with stable associations present throughout childhood. Knowledge of underlying mechanisms may affect treatment and long-term outcomes of individuals with psychopathology.
- Published
- 2020
- Full Text
- View/download PDF
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