用于预测不同血统人群2型糖尿病及其并发症的多血统多基因风险评分。

Multi-ancestry polygenic risk scores for the prediction of type 2 diabetes and complications in diverse ancestries.

作者信息

Huerta-Chagoya Alicia, Kim Joohyun, Mandla Ravi, Lu Yingchang, Suzuki Ken, Petty Lauren E, Ng Hong Kiat, Choi Jaewon, Lee Simon, Rout Madhusmita, Lin Kuang, Adair Linda S, Adeyemo Adebowale, Ahsan Habibul, Akiyama Masato, An Ping, Anand Sonia S, Becker Diane M, Bertoni Alain G, Bian Zheng, Bielak Lawrence F, Blangero John, Boehnke Michael, Bottinger Erwin P, Bowden Donald W, Bragg Fiona, Brody Jennifer A, Buchanan Thomas A, Cade Brian E, Chai Jin-Fang, Chambers John C, Chandak Giriraj R, Chang Li-Ching, Chang Kyong-Mi, Chee Miao-Li, Chen Chien-Hsiun, Chen Yuan-Tsong, Chen Zhengming, Chen Yii-Der I, Chen Ji, Chen Guanjie, Chen Shyh-Huei, Chen Wei-Min, Cheng Ching-Yu, Cho Yoon Shin, Choi Hyeok Sun, Chuang Lee-Ming, Cruz Miguel, Cushman Mary, Das Swapan K, DeFronzo Ralph A, deSilva H Janaka, Dimitrov Latchezar, Doumatey Ayo P, Du Shufa, Duan Qing, Duggirala Ravindranath, Emery Leslie S, Engert James C, Evans Daniel S, Evans Michele K, Finer Sarah, Florez Jose C, Floyd James S, Fornage Myriam, Frankel Elizabeth G, Freedman Barry I, García-García Lourdes, Genter Pauline, Gerstein Hertzel C, Goodarzi Mark O, Gordon-Larsen Penny, Graff Mariaelisa, Gross Myron, Guo Yu, Guo Xiuqing, Hai Yang, Hanis Craig L, Hayes MGeoffrey, Horikoshi Momoko, Howard Annie-Green, Hsu Sarah, Hsueh Willa, Huang Wei, Huang Mengna, Hung Yi-Jen, Hwang Mi Yeong, Hwu Chii-Min, Ichihara Sahoko, Igase Michiya, Ipp Eli, Islam Mohammad T, Isono Masato, Jang Hye-Mi, Jasmine Farzana, Jonas Jost B, Joo Yoonjung Y, Kabagambe Edmond, Kadowaki Takashi, Kamatani Yoichiro, Kandeel Fouad R, Kardia Sharon L R, Karlson Elizabeth W, Kasturiratne Anuradhani, Kato Norihiro, Katsuya Tomohiro, Kaur Varinderpal, Kawaguchi Takahisa, Keaton Jacob M, Kho Abel N, Khor Chiea-Chuen, Kibriya Muhammad, Kim Bong-Jo, Koh Woon-Puay, Kohara Katsuhiko, Kooner Jaspal S, Kooperberg Charles, Kreienkamp Raymond J, Lamri Amel, Lange Leslie A, Lee Nanette R, Lee Myung-Shik, Lee Jung-Jin, Lehman Donna M, Li Liming, Li Yun, Lim Victor Jy, Liu Jianjun, Liu Yongmei, Liu Simin, Long Jirong, Louie Tin, Luo Xi, Lv Jun, Lynch Julie A, Maeda Shiro, Mahajan Anubha, Maruthur Nisa M, Matsuda Fumihiko, McCarthy Mark I, McKean-Cowdin Roberta, Meigs James B, Millwood Iona Y, Mohlke Karen L, Motala Ayesha A, Nadkarni Girish N, Nadler Jerry L, Nakatochi Masahiro, Nalls Mike A, Nayak Uma, Nicolas Aude, North Kari E, Nousome Darryl, Okada Yukinori, Pan Ian, Pankow James S, Paré Guillaume, Park Jaehyun, Park Kyong Soo, Parra Esteban J, Patel Sanjay R, Pereira Mark A, Peyser Patricia A, Pirie Fraser J, Preuss Michael, Province Michael A, Psaty Bruce M, Raffel Leslie J, Raffield Laura M, Rasmussen-Torvik Laura J, Redline Susan, Reiner Alexander P, Rich Stephen S, Rohde Rebecca, Roll Kathryn, Roshani Rashedeh, Rotimi Charles N, Sabanayagam Charumathi, Saleheen Danish, Sandow Kevin, Schurmann Claudia, Shahriar Mohammad, Shaw Douglas M, Sheu Wayne H-H, Shi Jinxiu, Shu Xiao-Ou, Shuey Megan M, Siddiqui Moneeza K, Smith Jennifer A, Sofer Tamar, Spracklen Cassandra N, Stilp Adrienne M, Sun Meng, Tabara Yasuharu, Tai E-Shyong, Tajuddin Salman M, Takahashi Atsushi, Takeuchi Fumihiko, Tan Jingyi, Taylor Kent D, Taylor Katherine, Thameem Farook, Tong Lin, Tsai Fuu-Jen, Tsao Philip S, Udler Miriam S, Valladares-Salgado Adan, van Heel David A, vanDam Rob M, Varma Rohit, Vora Maheak, Wacher-Rodarte Niels, Wang Ya-Xing, Wheeler Ellie, Whitsel Eric A, Wickremasinghe Ananda R, Wojcik Genevieve L, Wong Tien Y, Wu Jer-Yuarn, Xiang Yong-Bing, Xiang Anny H, Yajnik Chittaranjan S, Yamamoto Ken, Yamauchi Toshimasa, Yanek Lisa R, Yao Jie, Yokota Mitsuhiro, Yu Canqing, Yuan Jian-Min, Yusuf Salim, Zeggini Eleftheria, Zhang Liang, Zhang Weihua, Zheng Wei, Zonderman Alan B, Aguilar-Salinas Carlos A, González-Villalpando Clicerio, Haiman Christopher A, Kim Young Jin, Kwak Soo Heon, Leong Aaron, Loos Ruth J F, Moreno-Estrada Andres, Morris Andrew P, Orozco Lorena, Rotter Jerome I, Sanghera Dharambir, Tusie-Luna Teresa, Voight Benjamin F, Vujkovic Marijana, Walters Robin G, Ge Tian, Manning Alisa K, Loh Marie, Below Jennifer E, Sim Xueling, Mercader Josep M, Ng Maggie C Y

出版信息

medRxiv. 2025 Jul 23:2025.07.21.25331778. doi: 10.1101/2025.07.21.25331778.

DOI:10.1101/2025.07.21.25331778

PMID:40778152

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12330429/

Abstract

BACKGROUND

Polygenic risk scores (PRSs) improve type 2 diabetes (T2D) prediction beyond clinical risk factors but perform poorly in non-European populations, where T2D burden is often higher, undermining their global clinical utility.

METHODS

We conducted the largest global effort to date to harmonize T2D genome-wide association study (GWAS) meta- analyses across five ancestries-European (EUR), African/African American (AFR), Admixed American (AMR), South Asian (SAS), and East Asian (EAS)-including 360,000 T2D cases and 1·8 million controls (41% non-EUR). We constructed ancestry-specific and multi-ancestry PRSs in training datasets including 11,000 T2D cases and 32,000 controls, and validated their performance in independent datasets including 39,000 T2D cases and 126,000 controls of diverse ancestries. In the All of Us Research Program, we compared these PRSs to those from the Polygenic Score Catalog and assessed their ability to predict diabetes micro- and macrovascular complications.

FINDINGS

Ancestry-specific PRSs showed limited prediction power for T2D in AFR, AMR, and SAS compared to EUR and EAS. In contrast, multi-ancestry PRSs, built using GWAS data from five ancestries, substantially improved T2D prediction across all ancestries. Compared to those in the interquartile range, individuals at the 97·5 percentile of their PRSs had a 6-fold increased T2D risk in AMR, EAS, and EUR, and ≥3-fold in AFR and SAS. These PRSs were also associated with the development of microvascular complications and outperformed all previously reported PRSs for all ancestries.

INTERPRETATION

We developed and extensively validated the most up-to-date T2D PRSs across diverse ancestry groups. These PRSs are publicly available to support further evaluation of their clinical utility in diverse ancestries.

摘要

背景

多基因风险评分（PRSs）在2型糖尿病（T2D）预测方面超越了临床风险因素，但在非欧洲人群中表现不佳，而这些人群的T2D负担往往更高，这削弱了它们在全球范围内的临床实用性。

方法

我们开展了迄今为止规模最大的全球研究，对来自欧洲（EUR）、非洲/非裔美国人（AFR）、混血美洲人（AMR）、南亚（SAS）和东亚（EAS）五个祖先群体的T2D全基因组关联研究（GWAS）荟萃分析进行了统一，其中包括360,000例T2D病例和180万对照（41%为非欧洲人）。我们在包含11,000例T2D病例和32,000例对照的训练数据集中构建了特定祖先群体和多祖先群体的PRSs，并在包含39,000例T2D病例和126,000例不同祖先群体对照的独立数据集中验证了它们的性能。在“我们所有人研究计划”中，我们将这些PRSs与多基因评分目录中的评分进行了比较，并评估了它们预测糖尿病微血管和大血管并发症的能力。

研究结果

与EUR和EAS相比，特定祖先群体的PRSs在AFR、AMR和SAS中的T2D预测能力有限。相比之下，使用来自五个祖先群体的GWAS数据构建的多祖先群体PRSs显著提高了所有祖先群体的T2D预测能力。与四分位间距内的个体相比，PRSs处于第97.5百分位的个体在AMR、EAS和EUR中的T2D风险增加了6倍，在AFR和SAS中增加了≥3倍。这些PRSs还与微血管并发症的发生有关，并且在所有祖先群体中均优于所有先前报道的PRSs。