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Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

ABSTRACT: Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery?+?replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

SUBMITTER: Noordam R

PROVIDER: S-EPMC6851116 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Noordam Raymond R Bos Maxime M MM Wang Heming H Winkler Thomas W TW Bentley Amy R AR Kilpeläinen Tuomas O TO de Vries Paul S PS Sung Yun Ju YJ Schwander Karen K Cade Brian E BE Manning Alisa A Aschard Hugues H Brown Michael R MR Chen Han H Franceschini Nora N Musani Solomon K SK Richard Melissa M Vojinovic Dina D Aslibekyan Stella S Bartz Traci M TM de las Fuentes Lisa L Feitosa Mary M Horimoto Andrea R AR Ilkov Marjan M Kho Minjung M Kraja Aldi A Li Changwei C Lim Elise E Liu Yongmei Y Mook-Kanamori Dennis O DO Rankinen Tuomo T Tajuddin Salman M SM van der Spek Ashley A Wang Zhe Z Marten Jonathan J Laville Vincent V Alver Maris M Evangelou Evangelos E Graff Maria E ME He Meian M Kühnel Brigitte B Lyytikäinen Leo-Pekka LP Marques-Vidal Pedro P Nolte Ilja M IM Palmer Nicholette D ND Rauramaa Rainer R Shu Xiao-Ou XO Snieder Harold H Weiss Stefan S Wen Wanqing W Yanek Lisa R LR Adolfo Correa C Ballantyne Christie C Bielak Larry L Biermasz Nienke R NR Boerwinkle Eric E Dimou Niki N Eiriksdottir Gudny G Gao Chuan C Gharib Sina A SA Gottlieb Daniel J DJ Haba-Rubio José J Harris Tamara B TB Heikkinen Sami S Heinzer Raphaël R Hixson James E JE Homuth Georg G Ikram M Arfan MA Komulainen Pirjo P Krieger Jose E JE Lee Jiwon J Liu Jingmin J Lohman Kurt K KK Luik Annemarie I AI Mägi Reedik R Martin Lisa W LW Meitinger Thomas T Metspalu Andres A Milaneschi Yuri Y Nalls Mike A MA O'Connell Jeff J Peters Annette A Peyser Patricia P Raitakari Olli T OT Reiner Alex P AP Rensen Patrick C N PCN Rice Treva K TK Rich Stephen S SS Roenneberg Till T Rotter Jerome I JI Schreiner Pamela J PJ Shikany James J Sidney Stephen S SS Sims Mario M Sitlani Colleen M CM Sofer Tamar T Strauch Konstantin K Swertz Morris A MA Taylor Kent D KD Uitterlinden André G AG van Duijn Cornelia M CM Völzke Henry H Waldenberger Melanie M Wallance Robert B RB van Dijk Ko Willems KW Yu Caizheng C Zonderman Alan B AB Becker Diane M DM Elliott Paul P Esko Tõnu T Gieger Christian C Grabe Hans J HJ Lakka Timo A TA Lehtimäki Terho T North Kari E KE Penninx Brenda W J H BWJH Vollenweider Peter P Wagenknecht Lynne E LE Wu Tangchun T Xiang Yong-Bing YB Zheng Wei W Arnett Donna K DK Bouchard Claude C Evans Michele K MK Gudnason Vilmundur V Kardia Sharon S Kelly Tanika N TN Kritchevsky Stephen B SB Loos Ruth J F RJF Pereira Alexandre C AC Province Mike M Psaty Bruce M BM Rotimi Charles C Zhu Xiaofeng X Amin Najaf N Cupples L Adrienne LA Fornage Myriam M Fox Ervin F EF Guo Xiuqing X Gauderman W James WJ Rice Kenneth K Kooperberg Charles C Munroe Patricia B PB Liu Ching-Ti CT Morrison Alanna C AC Rao Dabeeru C DC van Heemst Diana D Redline Susan S

Nature communications 20191112 1

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint ana ...[more]

PMID: 31719535

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Project description:Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10-8), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI [1.15, 1.27], P = 3x10-12) and PER2 (1.09 odds of morningness, 95% CI [1.06, 1.12], P = 4x10-10). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants; thirteen of the chronotype signals remained associated at P<5x10-8 on meta-analysis and eleven of these reached P<0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10-8). For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI [1.9, 3.2], P = 5.7x10-16) and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI [1.3, 2.7], P = 1.2x10-9; and 1.6 minutes per allele, 95% CI [1.1, 2.2], P = 7.6x10-9). Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05); undersleeping and BMI (rG = 0.147, P = 1x10-5) and oversleeping and BMI (rG = 0.097, P = 0.04), Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the biology of sleep and circadian rhythms in humans.

Project description:IntroductionHeritability estimates of nicotine dependence (ND) range from 40% to 70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction.MethodsWe employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, µ age = 40.08 [s.d. = 10.43]) and 3061 individuals from a nationally-representative sample with Fagerström Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day [CPD], the Alcohol Use Disorders Identification Test [AUDIT-Consumption and AUDIT-Problems], Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index [BMI], and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components.ResultsThe multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (β = -0.125; 95% CI: [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited.ConclusionsRisk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.ImplicationsThese findings enhance our understanding of inherited genetic factors for nicotine dependence. The data show that genome-wide association study (GWAS) findings across pre- and comorbid conditions of smoking are differentially associated with nicotine dependence and that when combined explain significantly more trait variance. These findings underscore the utility of multivariate approaches to understand the validity of polygenic scores for nicotine dependence, especially as the power of GWAS of broadly-defined smoking behaviors increases. Realizing the potential of GWAS to inform complex smoking behaviors will require similar theory-driven models that reflect the myriad of mechanisms that drive individual differences.

Dataset Information

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Publications

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

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