Shuai Liu, Jingjing Zhu, Hua Zhong, Chong Wu, Haoran Xue, Burcu F Darst, Xiuqing Guo, Peter Durda, Russell P Tracy, Yongmei Liu, W Craig Johnson, Kent D Taylor, Ani W Manichaikul, Mark O Goodarzi, Robert E Gerszten, Clary B Clish, Yii-Der Ida Chen, Heather Highland, Christopher A Haiman, Christopher R Gignoux, Leslie Lange, David V Conti, Laura M Raffield, Lynne Wilkens, Loïc Le Marchand, Kari E North, Kristin L Young, Ruth J Loos, Steve Buyske, Tara Matise, Ulrike Peters, Charles Kooperberg, Alexander P Reiner, Bing Yu, Eric Boerwinkle, Quan Sun, Mary R Rooney, Justin B Echouffo-Tcheugui, Martha L Daviglus, Qibin Qi, Nicholas Mancuso, Changwei Li, Youping Deng, Alisa Manning, James B Meigs, Stephen S Rich, Jerome I Rotter, Lang Wu
{"title":"鉴定不同种族和民族人群中与 2 型糖尿病风险相关的蛋白质。","authors":"Shuai Liu, Jingjing Zhu, Hua Zhong, Chong Wu, Haoran Xue, Burcu F Darst, Xiuqing Guo, Peter Durda, Russell P Tracy, Yongmei Liu, W Craig Johnson, Kent D Taylor, Ani W Manichaikul, Mark O Goodarzi, Robert E Gerszten, Clary B Clish, Yii-Der Ida Chen, Heather Highland, Christopher A Haiman, Christopher R Gignoux, Leslie Lange, David V Conti, Laura M Raffield, Lynne Wilkens, Loïc Le Marchand, Kari E North, Kristin L Young, Ruth J Loos, Steve Buyske, Tara Matise, Ulrike Peters, Charles Kooperberg, Alexander P Reiner, Bing Yu, Eric Boerwinkle, Quan Sun, Mary R Rooney, Justin B Echouffo-Tcheugui, Martha L Daviglus, Qibin Qi, Nicholas Mancuso, Changwei Li, Youping Deng, Alisa Manning, James B Meigs, Stephen S Rich, Jerome I Rotter, Lang Wu","doi":"10.1007/s00125-024-06277-3","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims/hypothesis: </strong>Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European.</p><p><strong>Methods: </strong>Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations.</p><p><strong>Results: </strong>We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development.</p><p><strong>Conclusions/interpretation: </strong>Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations.</p><p><strong>Data availability: </strong>The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. All code is available on GitHub ( https://github.com/Arthur1021/MESA-1K-PWAS ).</p>","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":null,"pages":null},"PeriodicalIF":8.4000,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations.\",\"authors\":\"Shuai Liu, Jingjing Zhu, Hua Zhong, Chong Wu, Haoran Xue, Burcu F Darst, Xiuqing Guo, Peter Durda, Russell P Tracy, Yongmei Liu, W Craig Johnson, Kent D Taylor, Ani W Manichaikul, Mark O Goodarzi, Robert E Gerszten, Clary B Clish, Yii-Der Ida Chen, Heather Highland, Christopher A Haiman, Christopher R Gignoux, Leslie Lange, David V Conti, Laura M Raffield, Lynne Wilkens, Loïc Le Marchand, Kari E North, Kristin L Young, Ruth J Loos, Steve Buyske, Tara Matise, Ulrike Peters, Charles Kooperberg, Alexander P Reiner, Bing Yu, Eric Boerwinkle, Quan Sun, Mary R Rooney, Justin B Echouffo-Tcheugui, Martha L Daviglus, Qibin Qi, Nicholas Mancuso, Changwei Li, Youping Deng, Alisa Manning, James B Meigs, Stephen S Rich, Jerome I Rotter, Lang Wu\",\"doi\":\"10.1007/s00125-024-06277-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims/hypothesis: </strong>Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European.</p><p><strong>Methods: </strong>Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations.</p><p><strong>Results: </strong>We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development.</p><p><strong>Conclusions/interpretation: </strong>Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations.</p><p><strong>Data availability: </strong>The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. 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Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations.
Aims/hypothesis: Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European.
Methods: Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations.
Results: We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development.
Conclusions/interpretation: Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations.
Data availability: The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. All code is available on GitHub ( https://github.com/Arthur1021/MESA-1K-PWAS ).
期刊介绍：
Diabetologia, the authoritative journal dedicated to diabetes research, holds high visibility through society membership, libraries, and social media. As the official journal of the European Association for the Study of Diabetes, it is ranked in the top quartile of the 2019 JCR Impact Factors in the Endocrinology & Metabolism category. The journal boasts dedicated and expert editorial teams committed to supporting authors throughout the peer review process.
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