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1. Genes, environment, and African ancestry in cardiometabolic disorders.

Author

Doumatey AP, Bentley AR, Akinyemi R, Olanrewaju TO, Adeyemo A, and Rotimi C

Subjects
Humans, Phenotype, Precision Medicine, Genomics, Cardiovascular Diseases genetics
Abstract

The past two decades have been characterized by a substantial global increase in cardiometabolic diseases, but the prevalence and incidence of these diseases and related traits differ across populations. African ancestry populations are among the most affected yet least included in research. Populations of African descent manifest significant genetic and environmental diversity and this under-representation is a missed opportunity for discovery and could exacerbate existing health disparities and curtail equitable implementation of precision medicine. Here, we discuss cardiometabolic diseases and traits in the context of African descent populations, including both genetic and environmental contributors and emphasizing novel discoveries. We also review new initiatives to include more individuals of African descent in genomics to address current gaps in the field., Competing Interests: Declaration of interests No interests are declared., (Published by Elsevier Ltd.)

Published
2023
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2. Mendelian randomization study reveals a causal relationship between adiponectin and LDL cholesterol in Africans.

Author

Meeks KAC, Bentley AR, Doumatey AP, Adeyemo AA, and Rotimi CN

Subjects
Male, Humans, Cholesterol, LDL, Mendelian Randomization Analysis, Adiponectin genetics, Overweight genetics, Overweight complications, Polymorphism, Single Nucleotide, Triglycerides, Obesity genetics, Obesity complications, Cholesterol, HDL, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Cardiovascular Diseases complications
Abstract

Adiponectin has been associated with cardiometabolic traits in observational studies across populations, yet it is unclear if these associations are causal. We performed Mendelian randomization (MR) analysis to assess the relationship between adiponectin and cardiometabolic traits in sub-Saharan Africans. We constructed a polygenic risk score (PRS) for adiponectin levels across 3354 unrelated sub-Saharan Africans. The PRS was used as the instrumental variable in two-stage least-squares MR analysis to assess its association with insulin resistance, HDL, LDL, total cholesterol, triglycerides, blood pressure, Type 2 Diabetes (T2D), and hypertension. The adiponectin PRS was causally related with LDL (β = 0.55, 95%CI 0.07-1.04, P-value = 0.024) but not the other traits. This association was observed in both overweight/obese and normal weight individuals, but only reached statistical significance among overweight/obese individuals (β = 0.55, 95%CI 0.01-1.08, P-value = 0.045). In normal weight individuals, the adiponectin PRS was associated with T2D (OR = 0.13, 95%CI 0.02-0.73, P-value = 0.021), and in men with HDL (β = 1.03, 95%CI 0.14-1.92, P-value = 0.023). The findings of this first MR study in sub-Saharan Africans support a causal relationship of adiponectin with LDL, with T2D in normal weight individuals only, and with HDL in men only. These observations add to the small but growing literature on adiponectin MR studies., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Published
2022
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3. The power of genetic diversity in genome-wide association studies of lipids.

Author

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 levels 2 , heart disease remains the leading cause of death worldwide 3 . 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 GWAS 4-23 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 patterns 24 . 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 medicine 25 , we anticipate that increased diversity of participants will lead to more accurate and equitable 26 application of polygenic scores in clinical practice., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Published
2021
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4. Genome-wide analyses of multiple obesity-related cytokines and hormones informs biology of cardiometabolic traits.

Author

Meeks KAC, Bentley AR, Gouveia MH, Chen G, Zhou J, Lei L, Adeyemo AA, Doumatey AP, and Rotimi CN

Subjects
Adipokines, Adult, Black or African American genetics, Body Mass Index, Diabetes Mellitus, Type 2 genetics, Female, Genetic Predisposition to Disease genetics, Humans, Insulin, Male, Middle Aged, Nigeria, Cardiovascular Diseases genetics, Cytokines metabolism, Genome-Wide Association Study, Hormones metabolism, Obesity genetics, Phenotype
Abstract

Background: A complex set of perturbations occur in cytokines and hormones in the etiopathogenesis of obesity and related cardiometabolic conditions such as type 2 diabetes (T2D). Evidence for the genetic regulation of these cytokines and hormones is limited, particularly in African-ancestry populations. In order to improve our understanding of the biology of cardiometabolic traits, we investigated the genetic architecture of a large panel of obesity- related cytokines and hormones among Africans with replication analyses in African Americans., Methods: We performed genome-wide association studies (GWAS) in 4432 continental Africans, enrolled from Ghana, Kenya, and Nigeria as part of the Africa America Diabetes Mellitus (AADM) study, for 13 obesity-related cytokines and hormones, including adipsin, glucose-dependent insulinotropic peptide (GIP), glucagon-like peptide-1 (GLP-1), interleukin-1 receptor antagonist (IL1-RA), interleukin-6 (IL-6), interleukin-10 (IL-10), leptin, plasminogen activator inhibitor-1 (PAI-1), resistin, visfatin, insulin, glucagon, and ghrelin. Exact and local replication analyses were conducted in African Americans (n = 7990). The effects of sex, body mass index (BMI), and T2D on results were investigated through stratified analyses., Results: GWAS identified 39 significant (P value < 5 × 10 -8 ) loci across all 13 traits. Notably, 14 loci were African-ancestry specific. In this first GWAS for adipsin and ghrelin, we detected 13 and 4 genome-wide significant loci respectively. Stratified analyses by sex, BMI, and T2D showed a strong effect of these variables on detected loci. Eight novel loci were successfully replicated: adipsin (3), GIP (1), GLP-1 (1), and insulin (3). Annotation of these loci revealed promising links between these adipocytokines and cardiometabolic outcomes as illustrated by rs201751833 for adipsin and blood pressure and locus rs759790 for insulin level and T2D in lean individuals., Conclusions: Our study identified genetic variants underlying variation in multiple adipocytokines, including the first loci for adipsin and ghrelin. We identified population differences in variants associated with adipocytokines and highlight the importance of stratification for discovery of loci. The high number of African-specific loci detected emphasizes the need for GWAS in African-ancestry populations, as these loci could not have been detected in other populations. Overall, our work contributes to the understanding of the biology linking adipocytokines to cardiometabolic traits., (© 2021. The Author(s).)

Published
2021
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5. Genetic risk scores for cardiometabolic traits in sub-Saharan African populations.

Author

Ekoru K, Adeyemo AA, Chen G, Doumatey AP, Zhou J, Bentley AR, Shriner D, and Rotimi CN

Subjects
Africa South of the Sahara epidemiology, Humans, Polymorphism, Single Nucleotide, Risk Factors, Cardiovascular Diseases epidemiology, Cardiovascular Diseases genetics, Genetic Predisposition to Disease
Abstract

Background: There is growing support for the use of genetic risk scores (GRS) in routine clinical settings. Due to the limited diversity of current genomic discovery samples, there are concerns that the predictive power of GRS will be limited in non-European ancestry populations. GRS for cardiometabolic traits were evaluated in sub-Saharan Africans in comparison with African Americans and European Americans., Methods: We evaluated the predictive utility of GRS for 12 cardiometabolic traits in sub-Saharan Africans (AF; n = 5200), African Americans (AA; n = 9139) and European Americans (EUR; n = 9594). GRS were constructed as weighted sums of the number of risk alleles. Predictive utility was assessed using the additional phenotypic variance explained and the increase in discriminatory ability over traditional risk factors [age, sex and body mass index (BMI)], with adjustment for ancestry-derived principal components., Results: Across all traits, GRS showed up to a 5-fold and 20-fold greater predictive utility in EUR relative to AA and AF, respectively. Predictive utility was most consistent for lipid traits, with percentage increase in explained variation attributable to GRS ranging from 10.6% to 127.1% among EUR, 26.6% to 65.8% among AA and 2.4% to 37.5% among AF. These differences were recapitulated in the discriminatory power, whereby the predictive utility of GRS was 4-fold greater in EUR relative to AA and up to 44-fold greater in EUR relative to AF. Obesity and blood pressure traits showed a similar pattern of greater predictive utility among EUR., Conclusions: This work demonstrates the poorer performance of GRS in AF and highlights the need to improve representation of multiple ethnic populations in genomic studies to ensure equitable clinical translation of GRS., (Published by Oxford University Press on behalf of the International Epidemiological Association 2021. This work is written by US Government employees and is in the public domain in the US.)

Published
2021
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6. Genetics of Circulating Resistin Level, a Biomarker for Cardiovascular Diseases, Is Informed by Mendelian Randomization and the Unique Characteristics of African Genomes.

Author

Meeks KAC, Doumatey AP, Bentley AR, Gouveia MH, Chen G, Zhou J, Lei L, Adeyemo AA, and Rotimi CN

Subjects
Adult, Black or African American genetics, Cardiovascular Diseases diagnosis, Female, Genome-Wide Association Study, Haplotypes, Humans, Linkage Disequilibrium, Male, Mendelian Randomization Analysis, Middle Aged, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Quantitative Trait Loci, Biomarkers metabolism, Black People genetics, Cardiovascular Diseases genetics, Resistin genetics
Abstract

Background: Resistin, a protein linked with inflammation and cardiometabolic diseases, is one of few proteins for which genome-wide association studies consistently report variants within and near the coding gene ( RETN ). Here, we took advantage of the reduced linkage disequilibrium in African populations to infer genetic causality for circulating resistin levels by performing genome-wide association studies, whole-exome analysis, fine mapping, Mendelian randomization, and transcriptomic data analyses., Methods: Genome-wide association studies and fine-mapping analyses for resistin were performed in 5621 African-ancestry individuals, including 3754 continental Africans and 1867 African Americans. Causal variants identified were subsequently used as an instrumental variable in Mendelian randomization analyses for homeostatic modeling-derived insulin resistance index, body mass index, and type 2 diabetes., Results: The lead variant (rs3219175, in the promoter region of RETN ) for the single locus detected was the same for continental Africans ( P =5.0×10 -111 ) and for African Americans (9.5×10 -38 ), respectively explaining 12.1% and 8.5% of variance in circulating resistin. Fine-mapping analyses and functional annotation revealed this variant as likely causal affecting circulating resistin levels as a cis-eQTL increasing RETN expression. Additional variants regulating resistin levels were upstream of RETN with genes PCP2 , STXBP2 , and XAB2 showing the strongest association using integrative analysis of genome-wide association studies with transcriptomic data. Mendelian randomization analyses did not provide evidence for resistin increasing insulin resistance, body mass index, or type 2 diabetes risk in African-ancestry populations., Conclusions: Taking advantage of the fine-mapping resolution power of African genomes, we identified a single variant (rs3219175) as the likely causal variant responsible for most of the variability in circulating resistin levels. In contrast to findings in some other ancestry populations, we showed that resistin does not seem to increase insulin resistance and related cardiometabolic traits in African-ancestry populations.

Published
2020
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7. Interethnic Differences in Serum Lipids and Implications for Cardiometabolic Disease Risk in African Ancestry Populations.

Author

Bentley AR and Rotimi CN

Subjects
Africa ethnology, Cardiovascular Diseases blood, Humans, Metabolic Syndrome blood, United States epidemiology, Black or African American, Cardiovascular Diseases ethnology, Lipids blood, Metabolic Syndrome ethnology
Abstract

African Americans generally have a healthier lipid profile (lower triglycerides and higher high-density lipoprotein cholesterol concentration) compared with those of other ethnicities. Paradoxically, African Americans do not experience a decreased risk of the cardiometabolic diseases that serum lipids are expected to predict. This review explores this mismatch between biomarker and disease among African ancestry individuals by investigating the presence of interethnic differences in the biological relationships underlying the serum lipids-disease association. This review also discusses the physiologic and genomic factors underlying these interethnic differences. Additionally, because of the importance of serum lipids in assessing disease risk, interethnic differences in serum lipids have implications for identifying African ancestry individuals at risk of cardiometabolic disease. Where possible, data from Africa is included, to further elucidate these ancestral differences in the context of a different environmental background., (Published by Elsevier B.V.)

Published
2017
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8. 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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