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10 results on '"Renström, F"'

1. A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.

Author

Sung YJ, Winkler TW, de las Fuentes L, Bentley AR, Brown MR, Kraja AT, Schwander K, Ntalla I, Guo X, Franceschini N, Lu Y, Cheng CY, Sim X, Vojinovic D, Marten J, Musani SK, Li C, Feitosa MF, Kilpeläinen TO, Richard MA, Noordam R, Aslibekyan S, Aschard H, Bartz TM, Dorajoo R, Liu Y, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Tayo BO, Warren HR, Zhao W, Zhou Y, Matoba N, Sofer T, Alver M, Amini M, Boissel M, Chai JF, Chen X, Divers J, Gandin I, Gao C, Giulianini F, Goel A, Harris SE, Hartwig FP, Horimoto ARVR, Hsu FC, Jackson AU, Kähönen M, Kasturiratne A, Kühnel B, Leander K, Lee WJ, Lin KH, 'an Luan J, McKenzie CA, Meian H, Nelson CP, Rauramaa R, Schupf N, Scott RA, Sheu WHH, Stančáková A, Takeuchi F, van der Most PJ, Varga TV, Wang H, Wang Y, Ware EB, Weiss S, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Alfred T, Amin N, Arking D, Aung T, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Braund PS, Brody JA, Broeckel U, Cabrera CP, Cade B, Caizheng Y, Campbell A, Canouil M, Chakravarti A, Chauhan G, Christensen K, Cocca M, Collins FS, Connell JM, de Mutsert R, de Silva HJ, Debette S, Dörr M, Duan Q, Eaton CB, Ehret G, Evangelou E, Faul JD, Fisher VA, Forouhi NG, Franco OH, Friedlander Y, Gao H, Gigante B, Graff M, Gu CC, Gu D, Gupta P, Hagenaars SP, Harris TB, He J, Heikkinen S, Heng CK, Hirata M, Hofman A, Howard BV, Hunt S, Irvin MR, Jia Y, Joehanes R, Justice AE, Katsuya T, Kaufman J, Kerrison ND, Khor CC, Koh WP, Koistinen HA, Komulainen P, Kooperberg C, Krieger JE, Kubo M, Kuusisto J, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Lim SH, Lin S, Liu CT, Liu J, Liu J, Liu K, Liu Y, Loh M, Lohman KK, Long J, Louie T, Mägi R, Mahajan A, Meitinger T, Metspalu A, Milani L, Momozawa Y, Morris AP, Mosley TH Jr, Munson P, Murray AD, Nalls MA, Nasri U, Norris JM, North K, Ogunniyi A, Padmanabhan S, Palmas WR, Palmer ND, Pankow JS, Pedersen NL, Peters A, Peyser PA, Polasek O, Raitakari OT, Renström F, Rice TK, Ridker PM, Robino A, Robinson JG, Rose LM, Rudan I, Sabanayagam C, Salako BL, Sandow K, Schmidt CO, Schreiner PJ, Scott WR, Seshadri S, Sever P, Sitlani CM, Smith JA, Snieder H, Starr JM, Strauch K, Tang H, Taylor KD, Teo YY, Tham YC, Uitterlinden AG, Waldenberger M, Wang L, Wang YX, Wei WB, Williams C, Wilson G, Wojczynski MK, Yao J, Yuan JM, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Chen YI, de Faire U, Deary IJ, Esko T, Farrall M, Forrester T, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Hung YJ, Jonas JB, Kato N, Kooner JS, Laakso M, Lehtimäki T, Liang KW, Magnusson PKE, Newman AB, Oldehinkel AJ, Pereira AC, Redline S, Rettig R, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Wu T, Zheng W, Kamatani Y, Laurie CC, Bouchard C, Cooper RS, Evans MK, Gudnason V, Kardia SLR, Kritchevsky SB, Levy D, O'Connell JR, Psaty BM, van Dam RM, Sims M, Arnett DK, Mook-Kanamori DO, Kelly TN, Fox ER, Hayward C, Fornage M, Rotimi CN, Province MA, van Duijn CM, Tai ES, Wong TY, Loos RJF, Reiner AP, Rotter JI, Zhu X, Bierut LJ, Gauderman WJ, Caulfield MJ, Elliott P, Rice K, Munroe PB, Morrison AC, Cupples LA, Rao DC, and Chasman DI

Subjects
Cohort Studies, Diastole genetics, Epistasis, Genetic, Female, Humans, Male, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, Reproducibility of Results, Systole genetics, Blood Pressure genetics, Genetic Loci, Genome-Wide Association Study, Racial Groups genetics, Smoking genetics
Abstract

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10 -8 ) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10 -8 ). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2)., (Copyright © 2018 American Society of Human Genetics. All rights reserved.)

Published
2018
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2. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Author

Justice AE, Winkler TW, Feitosa MF, Graff M, Fisher VA, Young K, Barata L, Deng X, Czajkowski J, Hadley D, Ngwa JS, Ahluwalia TS, Chu AY, Heard-Costa NL, Lim E, Perez J, Eicher JD, Kutalik Z, Xue L, Mahajan A, Renström F, Wu J, Qi Q, Ahmad S, Alfred T, Amin N, Bielak LF, Bonnefond A, Bragg J, Cadby G, Chittani M, Coggeshall S, Corre T, Direk N, Eriksson J, Fischer K, Gorski M, Neergaard Harder M, Horikoshi M, Huang T, Huffman JE, Jackson AU, Justesen JM, Kanoni S, Kinnunen L, Kleber ME, Komulainen P, Kumari M, Lim U, Luan J, Lyytikäinen LP, Mangino M, Manichaikul A, Marten J, Middelberg RPS, Müller-Nurasyid M, Navarro P, Pérusse L, Pervjakova N, Sarti C, Smith AV, Smith JA, Stančáková A, Strawbridge RJ, Stringham HM, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van der Most PJ, Van Vliet-Ostaptchouk JV, Vedantam SL, Verweij N, Vink JM, Vitart V, Wu Y, Yengo L, Zhang W, Hua Zhao J, Zimmermann ME, Zubair N, Abecasis GR, Adair LS, Afaq S, Afzal U, Bakker SJL, Bartz TM, Beilby J, Bergman RN, Bergmann S, Biffar R, Blangero J, Boerwinkle E, Bonnycastle LL, Bottinger E, Braga D, Buckley BM, Buyske S, Campbell H, Chambers JC, Collins FS, Curran JE, de Borst GJ, de Craen AJM, de Geus EJC, Dedoussis G, Delgado GE, den Ruijter HM, Eiriksdottir G, Eriksson AL, Esko T, Faul JD, Ford I, Forrester T, Gertow K, Gigante B, Glorioso N, Gong J, Grallert H, Grammer TB, Grarup N, Haitjema S, Hallmans G, Hamsten A, Hansen T, Harris TB, Hartman CA, Hassinen M, Hastie ND, Heath AC, Hernandez D, Hindorff L, Hocking LJ, Hollensted M, Holmen OL, Homuth G, Jan Hottenga J, Huang J, Hung J, Hutri-Kähönen N, Ingelsson E, James AL, Jansson JO, Jarvelin MR, Jhun MA, Jørgensen ME, Juonala M, Kähönen M, Karlsson M, Koistinen HA, Kolcic I, Kolovou G, Kooperberg C, Krämer BK, Kuusisto J, Kvaløy K, Lakka TA, Langenberg C, Launer LJ, Leander K, Lee NR, Lind L, Lindgren CM, Linneberg A, Lobbens S, Loh M, Lorentzon M, Luben R, Lubke G, Ludolph-Donislawski A, Lupoli S, Madden PAF, Männikkö R, Marques-Vidal P, Martin NG, McKenzie CA, McKnight B, Mellström D, Menni C, Montgomery GW, Musk AB, Narisu N, Nauck M, Nolte IM, Oldehinkel AJ, Olden M, Ong KK, Padmanabhan S, Peyser PA, Pisinger C, Porteous DJ, Raitakari OT, Rankinen T, Rao DC, Rasmussen-Torvik LJ, Rawal R, Rice T, Ridker PM, Rose LM, Bien SA, Rudan I, Sanna S, Sarzynski MA, Sattar N, Savonen K, Schlessinger D, Scholtens S, Schurmann C, Scott RA, Sennblad B, Siemelink MA, Silbernagel G, Slagboom PE, Snieder H, Staessen JA, Stott DJ, Swertz MA, Swift AJ, Taylor KD, Tayo BO, Thorand B, Thuillier D, Tuomilehto J, Uitterlinden AG, Vandenput L, Vohl MC, Völzke H, Vonk JM, Waeber G, Waldenberger M, Westendorp RGJ, Wild S, Willemsen G, Wolffenbuttel BHR, Wong A, Wright AF, Zhao W, Zillikens MC, Baldassarre D, Balkau B, Bandinelli S, Böger CA, Boomsma DI, Bouchard C, Bruinenberg M, Chasman DI, Chen YD, Chines PS, Cooper RS, Cucca F, Cusi D, Faire U, Ferrucci L, Franks PW, Froguel P, Gordon-Larsen P, Grabe HJ, Gudnason V, Haiman CA, Hayward C, Hveem K, Johnson AD, Wouter Jukema J, Kardia SLR, Kivimaki M, Kooner JS, Kuh D, Laakso M, Lehtimäki T, Marchand LL, März W, McCarthy MI, Metspalu A, Morris AP, Ohlsson C, Palmer LJ, Pasterkamp G, Pedersen O, Peters A, Peters U, Polasek O, Psaty BM, Qi L, Rauramaa R, Smith BH, Sørensen TIA, Strauch K, Tiemeier H, Tremoli E, van der Harst P, Vestergaard H, Vollenweider P, Wareham NJ, Weir DR, Whitfield JB, Wilson JF, Tyrrell J, Frayling TM, Barroso I, Boehnke M, Deloukas P, Fox CS, Hirschhorn JN, Hunter DJ, Spector TD, Strachan DP, van Duijn CM, Heid IM, Mohlke KL, Marchini J, Loos RJF, Kilpeläinen TO, Liu CT, Borecki IB, North KE, and Cupples LA

Subjects
Adiposity genetics, Adult, Body Fat Distribution, Body Mass Index, Epistasis, Genetic, Humans, Phenotype, Polymorphism, Single Nucleotide, Waist Circumference genetics, Waist-Hip Ratio, Genetic Predisposition to Disease genetics, Genome-Wide Association Study methods, Obesity genetics, Quantitative Trait Loci genetics, Smoking genetics
Abstract

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Published
2017
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3. Established BMI-associated genetic variants and their prospective associations with BMI and other cardiometabolic traits: the GLACIER Study.

Author

Ahmad S, Poveda A, Shungin D, Barroso I, Hallmans G, Renström F, and Franks PW

Subjects
Blood Pressure, Cholesterol blood, Cross-Sectional Studies, Fasting, Female, Genetic Predisposition to Disease epidemiology, Genetic Variation, Genotype, Glucose metabolism, Humans, Male, Middle Aged, Obesity blood, Obesity epidemiology, Phenotype, Prospective Studies, Triglycerides blood, Body Mass Index, Genetic Predisposition to Disease genetics, Genome-Wide Association Study, Obesity complications, Obesity genetics, Polymorphism, Single Nucleotide genetics
Abstract

Background: Recent cross-sectional genome-wide scans have reported associations of 97 independent loci with body mass index (BMI). In 3541 middle-aged adult participants from the GLACIER Study, we tested whether these loci are associated with 10-year changes in BMI and other cardiometabolic traits (fasting and 2-h glucose, triglycerides, total cholesterol, and systolic and diastolic blood pressures)., Methods: A BMI-specific genetic risk score (GRS) was calculated by summing the BMI-associated effect alleles at each locus. Trait-specific cardiometabolic GRSs comprised only the loci that show nominal association (P⩽0.10) with the respective trait in the original cross-sectional study. In longitudinal genetic association analyses, the second visit trait measure (assessed ~10 years after baseline) was used as the dependent variable and the models were adjusted for the baseline measure of the outcome trait, age, age(2), fasting time (for glucose and lipid traits), sex, follow-up time and population substructure., Results: The BMI-specific GRS was associated with increased BMI at follow-up (β=0.014 kg m(-2) per allele per 10-year follow-up, s.e.=0.006, P=0.019) as were three loci (PARK2 rs13191362, P=0.005; C6orf106 rs205262, P=0.043; and C9orf93 rs4740619, P=0.01). Although not withstanding Bonferroni correction, a handful of single-nucleotide polymorphisms was nominally associated with changes in blood pressure, glucose and lipid levels., Conclusions: Collectively, established BMI-associated loci convey modest but statistically significant time-dependent associations with long-term changes in BMI, suggesting a role for effect modification by factors that change with time in this population.

Published
2016
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4. Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Author

Kilpeläinen TO, Carli JF, Skowronski AA, Sun Q, Kriebel J, Feitosa MF, Hedman ÅK, Drong AW, Hayes JE, Zhao J, Pers TH, Schick U, Grarup N, Kutalik Z, Trompet S, Mangino M, Kristiansson K, Beekman M, Lyytikäinen LP, Eriksson J, Henneman P, Lahti J, Tanaka T, Luan J, Del Greco M F, Pasko D, Renström F, Willems SM, Mahajan A, Rose LM, Guo X, Liu Y, Kleber ME, Pérusse L, Gaunt T, Ahluwalia TS, Ju Sung Y, Ramos YF, Amin N, Amuzu A, Barroso I, Bellis C, Blangero J, Buckley BM, Böhringer S, I Chen YD, de Craen AJ, Crosslin DR, Dale CE, Dastani Z, Day FR, Deelen J, Delgado GE, Demirkan A, Finucane FM, Ford I, Garcia ME, Gieger C, Gustafsson S, Hallmans G, Hankinson SE, Havulinna AS, Herder C, Hernandez D, Hicks AA, Hunter DJ, Illig T, Ingelsson E, Ioan-Facsinay A, Jansson JO, Jenny NS, Jørgensen ME, Jørgensen T, Karlsson M, Koenig W, Kraft P, Kwekkeboom J, Laatikainen T, Ladwig KH, LeDuc CA, Lowe G, Lu Y, Marques-Vidal P, Meisinger C, Menni C, Morris AP, Myers RH, Männistö S, Nalls MA, Paternoster L, Peters A, Pradhan AD, Rankinen T, Rasmussen-Torvik LJ, Rathmann W, Rice TK, Brent Richards J, Ridker PM, Sattar N, Savage DB, Söderberg S, Timpson NJ, Vandenput L, van Heemst D, Uh HW, Vohl MC, Walker M, Wichmann HE, Widén E, Wood AR, Yao J, Zeller T, Zhang Y, Meulenbelt I, Kloppenburg M, Astrup A, Sørensen TI, Sarzynski MA, Rao DC, Jousilahti P, Vartiainen E, Hofman A, Rivadeneira F, Uitterlinden AG, Kajantie E, Osmond C, Palotie A, Eriksson JG, Heliövaara M, Knekt PB, Koskinen S, Jula A, Perola M, Huupponen RK, Viikari JS, Kähönen M, Lehtimäki T, Raitakari OT, Mellström D, Lorentzon M, Casas JP, Bandinelli S, März W, Isaacs A, van Dijk KW, van Duijn CM, Harris TB, Bouchard C, Allison MA, Chasman DI, Ohlsson C, Lind L, Scott RA, Langenberg C, Wareham NJ, Ferrucci L, Frayling TM, Pramstaller PP, Borecki IB, Waterworth DM, Bergmann S, Waeber G, Vollenweider P, Vestergaard H, Hansen T, Pedersen O, Hu FB, Eline Slagboom P, Grallert H, Spector TD, Jukema JW, Klein RJ, Schadt EE, Franks PW, Lindgren CM, Leibel RL, and Loos RJ

Subjects
Adipose Tissue metabolism, Animals, Gene Knockdown Techniques, Leptin genetics, Male, Mice, RNA, Messenger genetics, RNA, Messenger metabolism, Tissue Culture Techniques, Gene Expression Regulation physiology, Genome-Wide Association Study, Leptin blood, Leptin metabolism
Abstract

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.

Published
2016
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5. Inverse relationship between a genetic risk score of 31 BMI loci and weight change before and after reaching middle age.

Author

Rukh G, Ahmad S, Ericson U, Hindy G, Stocks T, Renström F, Almgren P, Nilsson PM, Melander O, Franks PW, and Orho-Melander M

Subjects
Adult, Alleles, Body Mass Index, Female, Follow-Up Studies, Genetic Loci, Humans, Life Style, Male, Middle Aged, Obesity genetics, Obesity metabolism, Risk Factors, Sweden epidemiology, Genetic Predisposition to Disease epidemiology, Genome-Wide Association Study, Obesity epidemiology, Polymorphism, Single Nucleotide genetics, Weight Gain genetics, White People
Abstract

Background/objective: Genome-wide-association studies have identified numerous body mass index (BMI)-associated variants, but it is unclear how these relate to weight gain in adults at different ages., Methods: We examined the association of a genetic risk score (GRS), consisting of 31 BMI-associated variants, with an annual weight change (AWC) and a substantial weight gain (SWG) of 10% by comparing self-reported weight at 20 years (y) with baseline weight (mean: 58 y; s.d.: 8 y) in 21407 participants from the Malmö Diet and Cancer Study (MDCS), and comparing baseline weight to weight at follow-up (mean: 73 y; s.d.: 6 y) among 2673 participants. Association between GRS and AWG and SWG was replicated in 4327 GLACIER (Gene x Lifestyle interactions And Complex traits Involved in Elevated disease Risk) participants (mean: 45 y; s.d.: 7 y) with 10 y follow-up. Cohort-specific results were pooled by fixed-effect meta-analyses., Results: In MDCS, the GRS was associated with increased AWC (β: 0.003; s.e: 0.01; P: 7 × 10(-8)) and increased odds for SWG (odds ratio (OR) 1.01 (95% confidence interval (CI): 1.00, 1.02); P: 0.013) per risk-allele from age 20y, but unexpectedly with decreased AWC (β: -0.006; s.e: 0.002; P: 0.009) and decreased odds for SWG OR 0.96 (95% CI: 0.93, 0.98); P: 0.001) between baseline and follow-up. Effect estimates from age 20 y to baseline differed significantly from those from baseline to follow-up (P: 0.0002 for AWC and P: 0.0001 for SWG). Similar to MDCS, the GRS was associated with decreased odds for SWG OR 0.98 (95% CI: 0.96, 1.00); P: 0.029) from baseline to follow-up in GLACIER. In meta-analyses (n=7000), the GRS was associated with decreased AWC (β: -0.005; s.e.m. 0.002; P: 0.002) and decreased odds for SWG OR 0.97 (95% CI: 0.96, 0.99); P: 0.001) per risk-allele., Conclusions: Our results provide convincing evidence for a paradoxical inversed relationship between a high number of BMI-associated risk-alleles and less weight gain during and after middle-age, in contrast to the expected increased weight gain seen in younger age.

Published
2016
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6. A novel interaction between the FLJ33534 locus and smoking in obesity: a genome-wide study of 14 131 Pakistani adults.

Author

Ahmad S, Zhao W, Renström F, Rasheed A, Zaidi M, Samuel M, Shah N, Mallick NH, Shungin D, Zaman KS, Ishaq M, Rasheed SZ, Memon FU, Hanif B, Lakhani MS, Ahmed F, Kazmi SU, Deloukas P, Frossard P, Franks PW, and Saleheen D

Subjects
Adult, Asian People genetics, Body Mass Index, Cross-Sectional Studies, Female, Genetic Predisposition to Disease, Humans, Life Style, Male, Obesity complications, Obesity epidemiology, Pakistan epidemiology, Polymorphism, Single Nucleotide, Receptors, Nicotinic, Smoking epidemiology, Genome-Wide Association Study, Obesity genetics, Smoking genetics
Abstract

Background: Obesity is a complex disease caused by the interplay of genetic and lifestyle factors, but identification of gene-lifestyle interactions in obesity has remained challenging. Few large-scale studies have reported use of genome-wide approaches to investigate gene-lifestyle interactions in obesity., Methods: In the Pakistan Risk of Myocardial Infraction Study, a cross-sectional study based in Pakistan, we calculated body mass index (BMI) variance estimates (square of the residual of inverse-normal transformed BMI z-score) in 14 131 participants and conducted genome-wide heterogeneity of variance analyses (GWHVA) for this outcome. All analyses were adjusted for age, age(2), sex and genetic ancestry., Results: The GWHVA analyses identified an intronic variant, rs140133294, in the FLJ33544 gene in association with BMI variance (P-value=3.1 × 10(-8)). In explicit tests of gene × lifestyle interaction, smoking was found to significantly modify the effect of rs140133294 on BMI (Pinteraction=0.0005), whereby the minor allele (T) was associated with lower BMI in current smokers, while positively associated with BMI in never smokers. Analyses of ENCODE data at the FLJ33534 locus revealed features indicative of open chromatin and high confidence DNA-binding motifs for several transcription factors, providing suggestive biological support for a mechanism of interaction., Conclusions: In summary, we have identified a novel interaction between smoking and variation at the FLJ33534 locus in relation to BMI in people from Pakistan.

Published
2016
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7. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Author

Winkler TW, Justice AE, Graff M, Barata L, Feitosa MF, Chu S, Czajkowski J, Esko T, Fall T, Kilpeläinen TO, Lu Y, Mägi R, Mihailov E, Pers TH, Rüeger S, Teumer A, Ehret GB, Ferreira T, Heard-Costa NL, Karjalainen J, Lagou V, Mahajan A, Neinast MD, Prokopenko I, Simino J, Teslovich TM, Jansen R, Westra HJ, White CC, Absher D, Ahluwalia TS, Ahmad S, Albrecht E, Alves AC, Bragg-Gresham JL, de Craen AJ, Bis JC, Bonnefond A, Boucher G, Cadby G, Cheng YC, Chiang CW, Delgado G, Demirkan A, Dueker N, Eklund N, Eiriksdottir G, Eriksson J, Feenstra B, Fischer K, Frau F, Galesloot TE, Geller F, Goel A, Gorski M, Grammer TB, Gustafsson S, Haitjema S, Hottenga JJ, Huffman JE, Jackson AU, Jacobs KB, Johansson Å, Kaakinen M, Kleber ME, Lahti J, Mateo Leach I, Lehne B, Liu Y, Lo KS, Lorentzon M, Luan J, Madden PA, Mangino M, McKnight B, Medina-Gomez C, Monda KL, Montasser ME, Müller G, Müller-Nurasyid M, Nolte IM, Panoutsopoulou K, Pascoe L, Paternoster L, Rayner NW, Renström F, Rizzi F, Rose LM, Ryan KA, Salo P, Sanna S, Scharnagl H, Shi J, Smith AV, Southam L, Stančáková A, Steinthorsdottir V, Strawbridge RJ, Sung YJ, Tachmazidou I, Tanaka T, Thorleifsson G, Trompet S, Pervjakova N, Tyrer JP, Vandenput L, van der Laan SW, van der Velde N, van Setten J, van Vliet-Ostaptchouk JV, Verweij N, Vlachopoulou E, Waite LL, Wang SR, Wang Z, Wild SH, Willenborg C, Wilson JF, Wong A, Yang J, Yengo L, Yerges-Armstrong LM, Yu L, Zhang W, Zhao JH, Andersson EA, Bakker SJ, Baldassarre D, Banasik K, Barcella M, Barlassina C, Bellis C, Benaglio P, Blangero J, Blüher M, Bonnet F, Bonnycastle LL, Boyd HA, Bruinenberg M, Buchman AS, Campbell H, Chen YD, Chines PS, Claudi-Boehm S, Cole J, Collins FS, de Geus EJ, de Groot LC, Dimitriou M, Duan J, Enroth S, Eury E, Farmaki AE, Forouhi NG, Friedrich N, Gejman PV, Gigante B, Glorioso N, Go AS, Gottesman O, Gräßler J, Grallert H, Grarup N, Gu YM, Broer L, Ham AC, Hansen T, Harris TB, Hartman CA, Hassinen M, Hastie N, Hattersley AT, Heath AC, Henders AK, Hernandez D, Hillege H, Holmen O, Hovingh KG, Hui J, Husemoen LL, Hutri-Kähönen N, Hysi PG, Illig T, De Jager PL, Jalilzadeh S, Jørgensen T, Jukema JW, Juonala M, Kanoni S, Karaleftheri M, Khaw KT, Kinnunen L, Kittner SJ, Koenig W, Kolcic I, Kovacs P, Krarup NT, Kratzer W, Krüger J, Kuh D, Kumari M, Kyriakou T, Langenberg C, Lannfelt L, Lanzani C, Lotay V, Launer LJ, Leander K, Lindström J, Linneberg A, Liu YP, Lobbens S, Luben R, Lyssenko V, Männistö S, Magnusson PK, McArdle WL, Menni C, Merger S, Milani L, Montgomery GW, Morris AP, Narisu N, Nelis M, Ong KK, Palotie A, Pérusse L, Pichler I, Pilia MG, Pouta A, Rheinberger M, Ribel-Madsen R, Richards M, Rice KM, Rice TK, Rivolta C, Salomaa V, Sanders AR, Sarzynski MA, Scholtens S, Scott RA, Scott WR, Sebert S, Sengupta S, Sennblad B, Seufferlein T, Silveira A, Slagboom PE, Smit JH, Sparsø TH, Stirrups K, Stolk RP, Stringham HM, Swertz MA, Swift AJ, Syvänen AC, Tan ST, Thorand B, Tönjes A, Tremblay A, Tsafantakis E, van der Most PJ, Völker U, Vohl MC, Vonk JM, Waldenberger M, Walker RW, Wennauer R, Widén E, Willemsen G, Wilsgaard T, Wright AF, Zillikens MC, van Dijk SC, van Schoor NM, Asselbergs FW, de Bakker PI, Beckmann JS, Beilby J, Bennett DA, Bergman RN, Bergmann S, Böger CA, Boehm BO, Boerwinkle E, Boomsma DI, Bornstein SR, Bottinger EP, Bouchard C, Chambers JC, Chanock SJ, Chasman DI, Cucca F, Cusi D, Dedoussis G, Erdmann J, Eriksson JG, Evans DA, de Faire U, Farrall M, Ferrucci L, Ford I, Franke L, Franks PW, Froguel P, Gansevoort RT, Gieger C, Grönberg H, Gudnason V, Gyllensten U, Hall P, Hamsten A, van der Harst P, Hayward C, Heliövaara M, Hengstenberg C, Hicks AA, Hingorani A, Hofman A, Hu F, Huikuri HV, Hveem K, James AL, Jordan JM, Jula A, Kähönen M, Kajantie E, Kathiresan S, Kiemeney LA, Kivimaki M, Knekt PB, Koistinen HA, Kooner JS, Koskinen S, Kuusisto J, Maerz W, Martin NG, Laakso M, Lakka TA, Lehtimäki T, Lettre G, Levinson DF, Lind L, Lokki ML, Mäntyselkä P, Melbye M, Metspalu A, Mitchell BD, Moll FL, Murray JC, Musk AW, Nieminen MS, Njølstad I, Ohlsson C, Oldehinkel AJ, Oostra BA, Palmer LJ, Pankow JS, Pasterkamp G, Pedersen NL, Pedersen O, Penninx BW, Perola M, Peters A, Polašek O, Pramstaller PP, Psaty BM, Qi L, Quertermous T, Raitakari OT, Rankinen T, Rauramaa R, Ridker PM, Rioux JD, Rivadeneira F, Rotter JI, Rudan I, den Ruijter HM, Saltevo J, Sattar N, Schunkert H, Schwarz PE, Shuldiner AR, Sinisalo J, Snieder H, Sørensen TI, Spector TD, Staessen JA, Stefania B, Thorsteinsdottir U, Stumvoll M, Tardif JC, Tremoli E, Tuomilehto J, Uitterlinden AG, Uusitupa M, Verbeek AL, Vermeulen SH, Viikari JS, Vitart V, Völzke H, Vollenweider P, Waeber G, Walker M, Wallaschofski H, Wareham NJ, Watkins H, Zeggini E, Chakravarti A, Clegg DJ, Cupples LA, Gordon-Larsen P, Jaquish CE, Rao DC, Abecasis GR, Assimes TL, Barroso I, Berndt SI, Boehnke M, Deloukas P, Fox CS, Groop LC, Hunter DJ, Ingelsson E, Kaplan RC, McCarthy MI, Mohlke KL, O'Connell JR, Schlessinger D, Strachan DP, Stefansson K, van Duijn CM, Hirschhorn JN, Lindgren CM, Heid IM, North KE, Borecki IB, Kutalik Z, and Loos RJ

Subjects
Adult, Age Factors, Aged, Chromosome Mapping, Female, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Sex Characteristics, Waist-Hip Ratio, White People, Body Mass Index, Body Size genetics, Genetic Predisposition to Disease, Genome-Wide Association Study
Abstract

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

Published
2015
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8. Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.

Author

Lindgren CM, Heid IM, Randall JC, Lamina C, Steinthorsdottir V, Qi L, Speliotes EK, Thorleifsson G, Willer CJ, Herrera BM, Jackson AU, Lim N, Scheet P, Soranzo N, Amin N, Aulchenko YS, Chambers JC, Drong A, Luan J, Lyon HN, Rivadeneira F, Sanna S, Timpson NJ, Zillikens MC, Zhao JH, Almgren P, Bandinelli S, Bennett AJ, Bergman RN, Bonnycastle LL, Bumpstead SJ, Chanock SJ, Cherkas L, Chines P, Coin L, Cooper C, Crawford G, Doering A, Dominiczak A, Doney AS, Ebrahim S, Elliott P, Erdos MR, Estrada K, Ferrucci L, Fischer G, Forouhi NG, Gieger C, Grallert H, Groves CJ, Grundy S, Guiducci C, Hadley D, Hamsten A, Havulinna AS, Hofman A, Holle R, Holloway JW, Illig T, Isomaa B, Jacobs LC, Jameson K, Jousilahti P, Karpe F, Kuusisto J, Laitinen J, Lathrop GM, Lawlor DA, Mangino M, McArdle WL, Meitinger T, Morken MA, Morris AP, Munroe P, Narisu N, Nordström A, Nordström P, Oostra BA, Palmer CN, Payne F, Peden JF, Prokopenko I, Renström F, Ruokonen A, Salomaa V, Sandhu MS, Scott LJ, Scuteri A, Silander K, Song K, Yuan X, Stringham HM, Swift AJ, Tuomi T, Uda M, Vollenweider P, Waeber G, Wallace C, Walters GB, Weedon MN, Witteman JC, Zhang C, Zhang W, Caulfield MJ, Collins FS, Davey Smith G, Day IN, Franks PW, Hattersley AT, Hu FB, Jarvelin MR, Kong A, Kooner JS, Laakso M, Lakatta E, Mooser V, Morris AD, Peltonen L, Samani NJ, Spector TD, Strachan DP, Tanaka T, Tuomilehto J, Uitterlinden AG, van Duijn CM, Wareham NJ, Hugh Watkins, Waterworth DM, Boehnke M, Deloukas P, Groop L, Hunter DJ, Thorsteinsdottir U, Schlessinger D, Wichmann HE, Frayling TM, Abecasis GR, Hirschhorn JN, Loos RJ, Stefansson K, Mohlke KL, Barroso I, and McCarthy MI

Subjects
Adult, Cohort Studies, Female, Humans, Male, Methionine Sulfoxide Reductases, Obesity metabolism, Polymorphism, Single Nucleotide, Waist Circumference, Waist-Hip Ratio, Adiposity, Body Fat Distribution, Genome-Wide Association Study, Lysophospholipase genetics, Obesity genetics, Oxidoreductases genetics, Transcription Factor AP-2 genetics
Abstract

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity., Competing Interests: The authors from Decode Genetics Inc. own stocks and stock options in the company. VM, NL, KS and DMW are full-time employees of GlaxoSmithKline, a pharmaceutical company. The other authors have no competing interests to declare.

Published
2009
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9. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Author

Justice, AE, Winkler, TW, Feitosa, MF, Graff, M, Fisher, VA, Young, K, Barata, L, Deng, X, Czajkowski, J, Hadley, D, Ngwa, JS, Ahluwalia, TS, Chu, AY, Heard-Costa, NL, Lim, E, Perez, J, Eicher, JD, Kutalik, Z, Xue, L, Mahajan, A, Renström, F, Wu, J, Qi, Q, Ahmad, S, Alfred, T, Amin, N, Bielak, LF, Bonnefond, A, Bragg, J, Cadby, G, Chittani, M, Coggeshall, S, Corre, T, Direk, N, Eriksson, J, Fischer, K, Gorski, M, Neergaard Harder, M, Horikoshi, M, Huang, T, Huffman, JE, Jackson, AU, Justesen, JM, Kanoni, S, Kinnunen, L, Kleber, ME, Komulainen, P, Kumari, M, Lim, U, Luan, J, Lyytikäinen, L-P, Mangino, M, Manichaikul, A, Marten, J, Middelberg, RPS, Müller-Nurasyid, M, Navarro, P, Pérusse, L, Pervjakova, N, Sarti, C, Smith, AV, Smith, JA, Stančáková, A, Strawbridge, RJ, Stringham, HM, Sung, YJ, Tanaka, T, Teumer, A, Trompet, S, Van Der Laan, SW, Van Der Most, PJ, Van Vliet-Ostaptchouk, JV, Vedantam, SL, Verweij, N, Vink, JM, Vitart, V, Wu, Y, Yengo, L, Zhang, W, Hua Zhao, J, Zimmermann, ME, Zubair, N, Abecasis, GR, Adair, LS, Afaq, S, Afzal, U, Bakker, SJL, Bartz, TM, Beilby, J, Bergman, RN, Bergmann, S, Biffar, R, Blangero, J, Boerwinkle, E, Bonnycastle, LL, Bottinger, E, Braga, D, Buckley, BM, Buyske, S, Campbell, H, Chambers, JC, Collins, FS, Curran, JE, De Borst, GJ, De Craen, AJM, De Geus, EJC, Dedoussis, G, Delgado, GE, Den Ruijter, HM, Eiriksdottir, G, Eriksson, AL, Esko, T, Faul, JD, Ford, I, Forrester, T, Gertow, K, Gigante, B, Glorioso, N, Gong, J, Grallert, H, Grammer, TB, Grarup, N, Haitjema, S, Hallmans, G, Hamsten, A, Hansen, T, Harris, TB, Hartman, CA, Hassinen, M, Hastie, ND, Heath, AC, Hernandez, D, Hindorff, L, Hocking, LJ, Hollensted, M, Holmen, OL, Homuth, G, Jan Hottenga, J, Huang, J, Hung, J, Hutri-Kähönen, N, Ingelsson, E, James, AL, Jansson, J-O, Jarvelin, M-R, Jhun, MA, Jørgensen, ME, Juonala, M, Kähönen, M, Karlsson, M, Koistinen, HA, Kolcic, I, Kolovou, G, Kooperberg, C, Krämer, BK, Kuusisto, J, Kvaløy, K, Lakka, TA, Langenberg, C, Launer, LJ, Leander, K, Lee, NR, Lind, L, Lindgren, CM, Linneberg, A, Lobbens, S, Loh, M, Lorentzon, M, Luben, R, Lubke, G, Ludolph-Donislawski, A, Lupoli, S, Madden, PAF, Männikkö, R, Marques-Vidal, P, Martin, NG, McKenzie, CA, McKnight, B, Mellström, D, Menni, C, Montgomery, GW, Musk, AB, Narisu, N, Nauck, M, Nolte, IM, Oldehinkel, AJ, Olden, M, Ong, KK, Padmanabhan, S, Peyser, PA, Pisinger, C, Porteous, DJ, Raitakari, OT, Rankinen, T, Rao, DC, Rasmussen-Torvik, LJ, Rawal, R, Rice, T, Ridker, PM, Rose, LM, Bien, SA, Rudan, I, Sanna, S, Sarzynski, MA, Sattar, N, Savonen, K, Schlessinger, D, Scholtens, S, Schurmann, C, Scott, RA, Sennblad, B, Siemelink, MA, Silbernagel, G, Slagboom, PE, Snieder, H, Staessen, JA, Stott, DJ, Swertz, MA, Swift, AJ, Taylor, KD, Tayo, BO, Thorand, B, Thuillier, D, Tuomilehto, J, Uitterlinden, AG, Vandenput, L, Vohl, M-C, Völzke, H, Vonk, JM, Waeber, G, Waldenberger, M, Westendorp, RGJ, Wild, S, Willemsen, G, Wolffenbuttel, BHR, Wong, A, Wright, AF, Zhao, W, Zillikens, MC, Baldassarre, D, Balkau, B, Bandinelli, S, Böger, CA, Boomsma, DI, Bouchard, C, Bruinenberg, M, Chasman, DI, Chen, Y-D, Chines, PS, Cooper, RS, Cucca, F, Cusi, D, Faire, UD, Ferrucci, L, Franks, PW, Froguel, P, Gordon-Larsen, P, Grabe, H-J, Gudnason, V, Haiman, CA, Hayward, C, Hveem, K, Johnson, AD, Wouter Jukema, J, Kardia, SLR, Kivimaki, M, Kooner, JS, Kuh, D, Laakso, M, Lehtimäki, T, Marchand, LL, März, W, McCarthy, MI, Metspalu, A, Morris, AP, Ohlsson, C, Palmer, LJ, Pasterkamp, G, Pedersen, O, Peters, A, Peters, U, Polasek, O, Psaty, BM, Qi, L, Rauramaa, R, Smith, BH, Sørensen, TIA, Strauch, K, Tiemeier, H, Tremoli, E, Van Der Harst, P, Vestergaard, H, Vollenweider, P, Wareham, NJ, Weir, DR, Whitfield, JB, Wilson, JF, Tyrrell, J, Frayling, TM, Barroso, I, Boehnke, M, Deloukas, P, Fox, CS, Hirschhorn, JN, Hunter, DJ, Spector, TD, Strachan, DP, Van Duijn, CM, Heid, IM, Mohlke, KL, Marchini, J, Loos, RJF, Kilpeläinen, TO, Liu, C-T, Borecki, IB, North, KE, and Cupples, LA

Subjects
Adult, Waist-Hip Ratio, Quantitative Trait Loci, Smoking, Epistasis, Genetic, Polymorphism, Single Nucleotide, 3. Good health, Body Mass Index, Phenotype, Body Fat Distribution, Humans, Genetic Predisposition to Disease, Obesity, Waist Circumference, Adiposity, Genome-Wide Association Study
Abstract

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

10. Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids

Author

Bentley, Amy R, Sung, Yun J, Brown, Michael R, Winkler, Thomas W, Kraja, Aldi T, Ntalla, Ioanna, Schwander, Karen, Chasman, Daniel I, Lim, Elise, Deng, Xuan, Guo, Xiuqing, Liu, Jingmin, Lu, Yingchang, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Huffman, Jennifer E, Musani, Solomon K, Li, Changwei, Feitosa, Mary F, Richard, Melissa A, Noordam, Raymond, Baker, Jenna, Chen, Guanjie, Aschard, Hugues, Bartz, Traci M, Ding, Jingzhong, Dorajoo, Rajkumar, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Zhao, Wei, Graff, Mariaelisa, Alver, Maris, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Evangelou, Evangelos, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, Hartwig, Fernando P, He, Meian, Horimoto, Andrea RVR, Hsu, Fang-Chi, Hung, Yi-Jen, Jackson, Anne U, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kuehnel, Brigitte, Leander, Karin, Lin, Keng-Hung, Luan, Jian'an, Lyytikainen, Leo-Pekka, Matoba, Nana, Nolte, Ilja M, Pietzner, Maik, Prins, Bram, Riaz, Muhammad, Robino, Antonietta, Said, M Abdullah, Schupf, Nicole, Scott, Robert A, Sofer, Tamar, Stancakova, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Wang, Tzung-Dau, Wang, Yajuan, Ware, Erin B, Wen, Wanqing, Xiang, Yong-Bing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Adeyemo, Adebowale, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Arzumanyan, Zorayr, Aung, Tin, Ballantyne, Christie, Barr, R Graham, Bielak, Lawrence F, Boerwinkle, Eric, Bottinger, Erwin P, Broeckel, Ulrich, Brown, Morris, Cade, Brian E, Campbell, Archie, Canouil, Mickael, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Christensen, Kaare, Concas, Maria Pina, Connell, John M, de las Fuentes, Lisa, de Silva, H Janaka, de Vries, Paul S, Doumatey, Ayo, Duan, Qing, Eaton, Charles B, Eppinga, Ruben N, Faul, Jessica D, Floyd, James S, Forouhi, Nita G, Forrester, Terrence, Friedlander, Yechiel, Gandin, Ilaria, Gao, He, Ghanbari, Mohsen, Gharib, Sina A, Gigante, Bruna, Giulianini, Franco, Grabe, Hans J, Gu, C Charles, Harris, Tamara B, Heikkinen, Sami, Heng, Chew-Kiat, Hirata, Makoto, Hixson, James E, Ikram, M Arfan, Jia, Yucheng, Joehanes, Roby, Johnson, Craig, Jonas, Jost Bruno, Justice, Anne E, Katsuya, Tomohiro, Khor, Chiea Chuen, Kilpelainen, Tuomas O, Koh, Woon-Puay, Kolcic, Ivana, Kooperberg, Charles, Krieger, Jose E, Kritchevsky, Stephen B, Kubo, Michiaki, Kuusisto, Johanna, Lakka, Timo A, Langefeld, Carl D, Langenberg, Claudia, Launer, Lenore J, Lehne, Benjamin, Lewis, Cora E, Li, Yize, Liang, Jingjing, Lin, Shiow, Liu, Ching-Ti, Liu, Jianjun, Liu, Kiang, Loh, Marie, Lohman, Kurt K, Louie, Tin, Luzzi, Anna, Magi, Reedik, Mahajan, Anubha, Manichaikul, Ani W, McKenzie, Colin A, Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Milani, Lili, Mohlke, Karen L, Momozawa, Yukihide, Morris, Andrew P, Murray, Alison D, Nalls, Mike A, Nauck, Matthias, Nelson, Christopher P, North, Kari E, O'Connell, Jeffrey R, Palmer, Nicholette D, Papanicolau, George J, Pedersen, Nancy L, Peters, Annette, Peyser, Patricia A, Polasek, Ozren, Poulter, Neil, Raitakari, Olli T, Reiner, Alex P, Renstrom, Frida, Rice, Treva K, Rich, Stephen S, Robinson, Jennifer G, Rose, Lynda M, Rosendaal, Frits R, Rudan, Igor, Schmidt, Carsten O, Schreiner, Pamela J, Scott, William R, Sever, Peter, Shi, Yuan, Sidney, Stephen, Sims, Mario, Smith, Jennifer A, Snieder, Harold, Starr, John M, Strauch, Konstantin, Stringham, Heather M, Tan, Nicholas YQ, Tang, Hua, Taylor, Kent D, Teo, Yik Ying, Tham, Yih Chung, Tiemeier, Henning, Turner, Stephen T, Uitterlinden, Andre G, van Heemst, Diana, Waldenberger, Melanie, Wang, Heming, Wang, Lan, Wang, Lihua, Wei, Wen Bin, Williams, Christine A, Sr, Wilson Gregory, Wojczynski, Mary K, Yao, Jie, Young, Kristin, Yu, Caizheng, Yuan, Jian-Min, Zhou, Jie, Zonderman, Alan B, Becker, Diane M, Boehnke, Michael, Bowden, Donald W, Chambers, John C, Cooper, Richard S, de Faire, Ulf, Deary, Ian J, Elliott, Paul, Esko, Tonu, Farrall, Martin, Franks, Paul W, Freedman, Barry I, Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Horta, Bernardo L, Juang, Jyh-Ming Jimmy, Kamatani, Yoichiro, Kammerer, Candace M, Kato, Norihiro, Kooner, Jaspal S, Laakso, Markku, Laurie, Cathy C, Lee, I-Te, Lehtimaki, Terho, Magnusson, Patrik KE, Oldehinkel, Albertine J, Penninx, Brenda WJH, Pereira, Alexandre C, Rauramaa, Rainer, Redline, Susan, Samani, Nilesh J, Scott, James, Shu, Xiao-Ou, van der Harst, Pim, Wagenknecht, Lynne E, Wang, Jun-Sing, Wang, Ya Xing, Wareham, Nicholas J, Watkins, Hugh, Weir, David R, Wickremasinghe, Ananda R, Wu, Tangchun, Zeggini, Eleftheria, Zheng, Wei, Bouchard, Claude, Evans, Michele K, Gudnason, Vilmundur, Kardia, Sharon LR, Liu, Yongmei, Psaty, Bruce M, Ridker, Paul M, van Dam, Rob M, Mook-Kanamori, Dennis O, Fornage, Myriam, Province, Michael A, Kelly, Tanika N, Fox, Ervin R, Hayward, Caroline, van Duijn, Cornelia M, Tai, E Shyong, Wong, Tien Yin, Loos, Ruth JF, Franceschini, Nora, Rotter, Jerome I, Zhu, Xiaofeng, Bierut, Laura J, Gauderman, W James, Rice, Kenneth, Munroe, Patricia B, Morrison, Alanna C, Rao, Dabeeru C, Rotimi, Charles N, Cupples, L Adrienne, Consortium, COGENT-Kidney, Consortium, EPIC-InterAct, Grp, Understanding Soc Sci, Cohort, Lifelines, National Institutes of Health [Bethesda] (NIH), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), The University of Texas Health Science Center at Houston (UTHealth), Universität Regensburg (UR), Queen Mary University of London (QMUL), Brigham and Women's Hospital [Boston], Harvard Medical School [Boston] (HMS), School of Public Health [Boston], Boston University [Boston] (BU), Los Angeles Biomedical Research Institute (LA BioMed), Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Icahn School of Medicine at Mount Sinai [New York] (MSSM), Singapore Eye Research Institute [Singapore] (SERI), Duke-NUS Medical School [Singapore], National University of Singapore (NUS), Erasmus University Medical Center [Rotterdam] (Erasmus MC), University of Edinburgh, University of Mississippi Medical Center (UMMC), University of Georgia [USA], Leiden University Medical Center (LUMC), Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Harvard T.H. Chan School of Public Health, University of Washington [Seattle], Wake Forest University, Genome Institute of Singapore (GIS), Massachusetts General Hospital [Boston], Pennington Biomedical Research Center, Louisiana State University (LSU), Icelandic Heart Association [Kopavogur, Iceland] (IHA), University of Iceland [Reykjavik], University of Michigan [Ann Arbor], University of Michigan System, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), University of Tartu, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Karolinska Institutet [Stockholm], Wake Forest School of Medicine [Winston-Salem], Wake Forest Baptist Medical Center, Imperial College London, University of Ioannina, University of Oxford [Oxford], University of Groningen [Groningen], Universidade Federal de Pelotas = Federal University of Pelotas (UFPel), University of Bristol [Bristol], Huazhong University of Science and Technology [Wuhan] (HUST), Universidade de São Paulo Medical School (FMUSP), Case Western Reserve University [Cleveland], University of Southern California (USC), This project was largely supported by a grant from the US National Heart, Lung, and Blood Institute of the National Institutes of Health (R01HL118305) and by the Intramural Research Program of the National Human Genome Research Institute of the National Institutes of Health through the Center for Research on Genomics and Global Health (CRGGH). The CRGGH is supported by the National Human Genome Research Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Center for Information Technology, and the Office of the Director at the National Institutes of Health (Z01HG200362)., Bentley, Ar, Sung, Yj, Brown, Mr, Winkler, Tw, Kraja, At, Ntalla, I, Schwander, K, Chasman, Di, Lim, E, Deng, X, Guo, X, Liu, J, Lu, Y, Cheng, Cy, Sim, X, Vojinovic, D, Huffman, Je, Musani, Sk, Li, C, Feitosa, Mf, Richard, Ma, Noordam, R, Baker, J, Chen, G, Aschard, H, Bartz, Tm, Ding, J, Dorajoo, R, Manning, Ak, Rankinen, T, Smith, Av, Tajuddin, Sm, Zhao, W, Graff, M, Alver, M, Boissel, M, Chai, Jf, Chen, X, Divers, J, Evangelou, E, Gao, C, Goel, A, Hagemeijer, Y, Harris, Se, Hartwig, Fp, He, M, Horimoto, Arvr, Hsu, Fc, Hung, Yj, Jackson, Au, Kasturiratne, A, Komulainen, P, Kühnel, B, Leander, K, Lin, Kh, Luan, J, Lyytikäinen, Lp, Matoba, N, Nolte, Im, Pietzner, M, Prins, B, Riaz, M, Robino, A, Said, Ma, Schupf, N, Scott, Ra, Sofer, T, Stancáková, A, Takeuchi, F, Tayo, Bo, van der Most, Pj, Varga, Tv, Wang, Td, Wang, Y, Ware, Eb, Wen, W, Xiang, Yb, Yanek, Lr, Zhang, W, Zhao, Jh, Adeyemo, A, Afaq, S, Amin, N, Amini, M, Arking, De, Arzumanyan, Z, Aung, T, Ballantyne, C, Barr, Rg, Bielak, Lf, Boerwinkle, E, Bottinger, Ep, Broeckel, U, Brown, M, Cade, Be, Campbell, A, Canouil, M, Charumathi, S, Chen, Yi, Christensen, K, COGENT-Kidney, Consortium, Concas, Mp, Connell, Jm, de Las Fuentes, L, de Silva, Hj, de Vries, P, Doumatey, A, Duan, Q, Eaton, Cb, Eppinga, Rn, Faul, Jd, Floyd, J, Forouhi, Ng, Forrester, T, Friedlander, Y, Gandin, I, Gao, H, Ghanbari, M, Gharib, Sa, Gigante, B, Giulianini, F, Grabe, Hj, Gu, Cc, Harris, Tb, Heikkinen, S, Heng, Ck, Hirata, M, Hixson, Je, Ikram, Ma, EPIC-InterAct, Consortium, Jia, Y, Joehanes, R, Johnson, C, Jonas, Jb, Justice, Ae, Katsuya, T, Khor, Cc, Kilpeläinen, To, Koh, Wp, Kolcic, I, Kooperberg, C, Krieger, Je, Kritchevsky, Sb, Kubo, M, Kuusisto, J, Lakka, Ta, Langefeld, Cd, Langenberg, C, Launer, Lj, Lehne, B, Lewis, Ce, Li, Y, Liang, J, Lin, S, Liu, Ct, Liu, K, Loh, M, Lohman, Kk, Louie, T, Luzzi, A, Mägi, R, Mahajan, A, Manichaikul, Aw, Mckenzie, Ca, Meitinger, T, Metspalu, A, Milaneschi, Y, Milani, L, Mohlke, Kl, Momozawa, Y, Morris, Ap, Murray, Ad, Nalls, Ma, Nauck, M, Nelson, Cp, North, Ke, O'Connell, Jr, Palmer, Nd, Papanicolau, Gj, Pedersen, Nl, Peters, A, Peyser, Pa, Polasek, O, Poulter, N, Raitakari, Ot, Reiner, Ap, Renström, F, Rice, Tk, Rich, S, Robinson, Jg, Rose, Lm, Rosendaal, Fr, Rudan, I, Schmidt, Co, Schreiner, Pj, Scott, Wr, Sever, P, Shi, Y, Sidney, S, Sims, M, Smith, Ja, Snieder, H, Starr, Jm, Strauch, K, Stringham, Hm, Tan, Nyq, Tang, H, Taylor, Kd, Teo, Yy, Tham, Yc, Tiemeier, H, Turner, St, Uitterlinden, Ag, Understanding Society Scientific, Group, van Heemst, D, Waldenberger, M, Wang, H, Wang, L, Wei, Wb, Williams, Ca, Wilson, G Sr, Wojczynski, Mk, Yao, J, Young, K, Yu, C, Yuan, Jm, Zhou, J, Zonderman, Ab, Becker, Dm, Boehnke, M, Bowden, Dw, Chambers, Jc, Cooper, R, de Faire, U, Deary, Ij, Elliott, P, Esko, T, Farrall, M, Franks, Pw, Freedman, Bi, Froguel, P, Gasparini, P, Gieger, C, Horta, Bl, Juang, Jj, Kamatani, Y, Kammerer, Cm, Kato, N, Kooner, J, Laakso, M, Laurie, Cc, Lee, It, Lehtimäki, T, Lifelines, Cohort, Magnusson, Pke, Oldehinkel, Aj, Penninx, Bwjh, Pereira, Ac, Rauramaa, R, Redline, S, Samani, Nj, Scott, J, Shu, Xo, van der Harst, P, Wagenknecht, Le, Wang, J, Wang, Yx, Wareham, Nj, Watkins, H, Weir, Dr, Wickremasinghe, Ar, Wu, T, Zeggini, E, Zheng, W, Bouchard, C, Evans, Mk, Gudnason, V, Kardia, Slr, Liu, Y, Psaty, Bm, Ridker, Pm, van Dam, Rm, Mook-Kanamori, Do, Fornage, M, Province, Ma, Kelly, Tn, Fox, Er, Hayward, C, van Duijn, Cm, Tai, E, Wong, Ty, Loos, Rjf, Franceschini, N, Rotter, Ji, Zhu, X, Bierut, Lj, Gauderman, Wj, Rice, K, Munroe, Pb, Morrison, Ac, Rao, Dc, Rotimi, Cn, Cupples, La., Luan, Jian'an [0000-0003-3137-6337], Pietzner, Maik [0000-0003-3437-9963], Zhao, Jing Hua [0000-0003-4930-3582], Forouhi, Nita [0000-0002-5041-248X], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, Epidemiology, Neurology, Radiology & Nuclear Medicine, Internal Medicine, Life Course Epidemiology (LCE), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Cardiovascular Centre (CVC), Home Office, Action on Hearing Loss, Imperial College Healthcare NHS Trust- BRC Funding, Medical Research Council (MRC), Universiteit Leiden, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), University of Oxford, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, and APH - Digital Health

Subjects
Male, Linkage disequilibrium, Blood lipids, Genome-wide association study, VARIANTS, SUSCEPTIBILITY, Environment interaction, Genome, Linkage Disequilibrium, MESH: Genotype, 0302 clinical medicine, MESH: Aged, 80 and over, Genotype, NICOTINE METABOLISM, 11 Medical and Health Sciences, Genetics & Heredity, Aged, 80 and over, Genetics, MESH: Aged, 0303 health sciences, ARCHITECTURE, [STAT.AP]Statistics [stat]/Applications [stat.AP], Genotype imputation, MESH: Middle Aged, CHOLESTEROL, Smoking, MESH: Life Style, Lifelines Cohort, Middle Aged, Lipids, 3. Good health, ENVIRONMENT INTERACTION, GENOTYPE IMPUTATION, RISK LOCI, METAANALYSIS, CIGARETTES, Cholesterol, MESH: Linkage Disequilibrium, MESH: Young Adult, Meta-analysis, Genome-Wide Association Study/methods, Smoking/blood, Medical genetics, Female, EPIC-InterAct Consortium, Life Sciences & Biomedicine, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Adult, Metaanalysi, Understanding Society Scientific Group, medicine.medical_specialty, MESH: Smoking, Adolescent, Genomics, COGENT-Kidney Consortium, Biology, Nicotine metabolism, Risk loci, Metaanalysis, Cigarettes, Article, Young Adult, 03 medical and health sciences, genomics, medicine, Humans, Linkage Disequilibrium/genetics, Life Style, Aged, 030304 developmental biology, MESH: Adolescent, Science & Technology, MESH: Humans, Lipids/blood, MESH: Adult, 06 Biological Sciences, MESH: Lipids, MESH: Male, cardiovascular diseases, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, genome-wide association studies, MESH: Genome-Wide Association Study, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], MESH: Female, 030217 neurology & neurosurgery, Developmental Biology, Genome-Wide Association Study
Abstract

The concentrations of high- and low-density lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 novel loci, some of which were detected only because the association differed by smoking status. Additionally, we demonstrated the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings., Editorial summary: A multi-ancestry genome-wide gene-smoking interaction study identifies 13 new loci associated with serum lipids.

Published
2019
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