Genome-wide analyses of multiple obesity-related cytokines and hormones informs biology of cardiometabolic traits.
Genome-wide analyses of multiple obesity-related cytokines and hormones informs biology of cardiometabolic traits.
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多种肥胖相关细胞因子和激素的全基因组分析为心脏代谢特征的生物学提供信息。
DOI：
10.1186/s13073-021-00971-2
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发表时间：
2021-10-07
期刊：
影响因子：
12.3
通讯作者：
Rotimi CN
中科院分区：
文献类型：
--
作者：
Meeks KAC;Bentley AR;Gouveia MH;Chen G;Zhou J;Lei L;Adeyemo AA;Doumatey AP;Rotimi CN
在肥胖和相关的心脏代谢疾病，如2型糖尿病(T2D)的发病机制中，细胞因子和激素发生了一系列复杂的扰动。对这些细胞因子和激素进行遗传调控的证据有限，尤其是在非洲裔人群中。为了提高我们对心脏代谢特征生物学的理解，我们用非裔美国人的复制分析研究了非洲人中与肥胖相关的一大组细胞因子和激素的遗传结构。作为非洲-美洲糖尿病(AADM)研究的一部分，我们对来自加纳、肯尼亚和尼日利亚的4432名非洲大陆人进行了全基因组关联研究(GWAS)，研究了13种与肥胖相关的细胞因子和激素，包括脂肪酶、葡萄糖依赖的胰岛素样多肽(GIP)、胰高血糖素样肽-1(GLP-1)、白介素1受体拮抗剂(IL1-RA)、白介素6(IL-6)、白介素10(IL-10)、瘦素、纤溶酶原激活物抑制物-1(PAI-1)、抵抗素、内脂素、胰岛素、高血糖素和Ghrelin。在非裔美国人(n=7990)中进行了精确和局部复制分析。通过分层分析研究性别、体重指数(BMI)和T2D对结果的影响。在13个性状中均检测到39个显著(P值和lt； 5×10−8)基因座。值得注意的是，有14个基因座是非洲血统特有的。在第一次针对脂蛋白和Ghrelin的GWA中，我们分别检测到了13个和4个全基因组有意义的基因座。按性别、BMI和T2D进行的分层分析表明，这些变量对检测到的基因座有很强的影响。成功复制了8个新的基因座：脂蛋白(3)、GIP(1)、GLP-1(1)和胰岛素(3)。这些基因座的注释揭示了这些脂肪细胞因子和心脏代谢结果之间有希望的联系，如脂肪蛋白和血压的rs201751833和瘦削个体的胰岛素水平和T2D的rs759790基因座。我们的研究确定了多种脂肪细胞因子变异的遗传变异，包括脂肪酶和胃促生长素的第一个基因座。我们确定了与脂肪细胞因子相关的变异的群体差异，并强调了分层对发现基因座的重要性。检测到的大量非洲特有基因座强调了在非洲血统人口中进行GWAS的必要性，因为这些基因座不可能在其他人群中检测到。总体而言，我们的工作有助于理解脂肪细胞因子与心脏代谢特征之间的生物学联系。网上版载有补充材料，可在10.1186/s13073-021-00971-2查阅。
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. 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. 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. 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. The online version contains supplementary material available at 10.1186/s13073-021-00971-2.
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影响因子：
11
作者：
de Las Fuentes L;Sung YJ;Noordam R;Winkler T;Feitosa MF;Schwander K;Bentley AR;Brown MR;Guo X;Manning A;Chasman DI;Aschard H;Bartz TM;Bielak LF;Campbell A;Cheng CY;Dorajoo R;Hartwig FP;Horimoto ARVR;Li C;Li-Gao R;Liu Y;Marten J;Musani SK;Ntalla I;Rankinen T;Richard M;Sim X;Smith AV;Tajuddin SM;Tayo BO;Vojinovic D;Warren HR;Xuan D;Alver M;Boissel M;Chai JF;Chen X;Christensen K;Divers J;Evangelou E;Gao C;Girotto G;Harris SE;He M;Hsu FC;Kühnel B;Laguzzi F;Li X;Lyytikäinen LP;Nolte IM;Poveda A;Rauramaa R;Riaz M;Rueedi R;Shu XO;Snieder H;Sofer T;Takeuchi F;Verweij N;Ware EB;Weiss S;Yanek LR;Amin N;Arking DE;Arnett DK;Bergmann S;Boerwinkle E;Brody JA;Broeckel U;Brumat M;Burke G;Cabrera CP;Canouil M;Chee ML;Chen YI;Cocca M;Connell J;de Silva HJ;de Vries PS;Eiriksdottir G;Faul JD;Fisher V;Forrester T;Fox EF;Friedlander Y;Gao H;Gigante B;Giulianini F;Gu CC;Gu D;Harris TB;He J;Heikkinen S;Heng CK;Hunt S;Ikram MA;Irvin MR;Kähönen M;Kavousi M;Khor CC;Kilpeläinen TO;Koh WP;Komulainen P;Kraja AT;Krieger JE;Langefeld CD;Li Y;Liang J;Liewald DCM;Liu CT;Liu J;Lohman KK;Mägi R;McKenzie CA;Meitinger T;Metspalu A;Milaneschi Y;Milani L;Mook-Kanamori DO;Nalls MA;Nelson CP;Norris JM;O'Connell J;Ogunniyi A;Padmanabhan S;Palmer ND;Pedersen NL;Perls T;Peters A;Petersmann A;Peyser PA;Polasek O;Porteous DJ;Raffel LJ;Rice TK;Rotter JI;Rudan I;Rueda-Ochoa OL;Sabanayagam C;Salako BL;Schreiner PJ;Shikany JM;Sidney SS;Sims M;Sitlani CM;Smith JA;Starr JM;Strauch K;Swertz MA;Teumer A;Tham YC;Uitterlinden AG;Vaidya D;van der Ende MY;Waldenberger M;Wang L;Wang YX;Wei WB;Weir DR;Wen W;Yao J;Yu B;Yu C;Yuan JM;Zhao W;Zonderman AB;Becker DM;Bowden DW;Deary IJ;Dörr M;Esko T;Freedman BI;Froguel P;Gasparini P;Gieger C;Jonas JB;Kammerer CM;Kato N;Lakka TA;Leander K;Lehtimäki T;Lifelines Cohort Study;Magnusson PKE;Marques-Vidal P;Penninx BWJH;Samani NJ;van der Harst P;Wagenknecht LE;Wu T;Zheng W;Zhu X;Bouchard C;Cooper RS;Correa A;Evans MK;Gudnason V;Hayward C;Horta BL;Kelly TN;Kritchevsky SB;Levy D;Palmas WR;Pereira AC;Province MM;Psaty BM;Ridker PM;Rotimi CN;Tai ES;van Dam RM;van Duijn CM;Wong TY;Rice K;Gauderman WJ;Morrison AC;North KE;Kardia SLR;Caulfield MJ;Elliott P;Munroe PB;Franks PW;Rao DC;Fornage M
通讯作者：
Fornage M
影响因子：
14.9
作者：
Buniello, Annalisa;MacArthur, Jacqueline A. L.;Parkinson, Helen
通讯作者：
Parkinson, Helen
影响因子：
7
作者：
Boyle AP;Hong EL;Hariharan M;Cheng Y;Schaub MA;Kasowski M;Karczewski KJ;Park J;Hitz BC;Weng S;Cherry JM;Snyder M
通讯作者：
Snyder M
DOI：
10.1900/rds.2011.8.418
发表时间：
2011-01-01
期刊：
The review of diabetic studies : RDS
影响因子：
--
作者：
Cabou, Cendrine;Burcelin, Remy
通讯作者：
Burcelin, Remy
影响因子：
9.8
作者：
Ahola-Olli, Ari V.;Wurtz, Peter;Raitakari, Olli T.
通讯作者：
Raitakari, Olli T.