Metabolic polygenic risk scores for prediction of obesity, type 2 diabetes, and related morbidities

Min Seo Kim; Qiuli Chen; Yang Sui; Xiong Yang; Shaoqi Wang; Lu-Chen Weng; So Mi Jemma Cho; Satoshi Koyama; Xinyu Zhu; Kang Yu; Xingyu Chen; Rufan Zhang; Wanqing Yin; Shuangqiao Liao; Zhaoqi Liu; Fowzan S Alkuraya; Pradeep Natarajan; Patrick T Ellinor; Akl C Fahed; Minxian Wang

doi:10.1016/j.cmet.2026.02.009

Metabolic polygenic risk scores for prediction of obesity, type 2 diabetes, and related morbidities

Cell Metab. 2026 May 5;38(5):863-875.e5. doi: 10.1016/j.cmet.2026.02.009. Epub 2026 Mar 16.

Authors

Min Seo Kim¹, Qiuli Chen², Yang Sui³, Xiong Yang⁴, Shaoqi Wang², Lu-Chen Weng⁵, So Mi Jemma Cho⁵, Satoshi Koyama⁵, Xinyu Zhu⁶, Kang Yu², Xingyu Chen², Rufan Zhang⁴, Wanqing Yin², Shuangqiao Liao², Zhaoqi Liu⁷, Fowzan S Alkuraya⁸, Pradeep Natarajan⁹, Patrick T Ellinor¹⁰, Akl C Fahed¹¹, Minxian Wang¹²

Affiliations

¹ Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Heart and Vascular Institute, Mass General Brigham, Boston, MA, USA.
² National Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
³ Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Heart and Vascular Institute, Mass General Brigham, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
⁴ National Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
⁵ Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
⁶ National Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; College of Future Technology, Sino-Danish College, University of Chinese Academy of Sciences, Beijing 101408, China.
⁷ National Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; College of Future Technology, Sino-Danish College, University of Chinese Academy of Sciences, Beijing 101408, China.
⁸ Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia; Lifera Omics, Riyadh, Saudi Arabia; College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
⁹ Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Heart and Vascular Institute, Mass General Brigham, Boston, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
¹⁰ Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Heart and Vascular Institute, Mass General Brigham, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address: ellinor@mgb.org.
¹¹ Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Heart and Vascular Institute, Mass General Brigham, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address: afahed@mgh.harvard.edu.
¹² National Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; College of Future Technology, Sino-Danish College, University of Chinese Academy of Sciences, Beijing 101408, China; Department of Cardiovascular Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China; Hubei Provincial Engineering Research Center of Minimally Invasive Cardiovascular Surgery, Wuhan 430071, China; Wuhan Clinical Research Center for Minimally Invasive Treatment of Structural Heart Disease, Wuhan 430071, China. Electronic address: wangmx@big.ac.cn.

PMID: 41844147
PMCID: PMC13092120 (available on 2027-03-16)
DOI: 10.1016/j.cmet.2026.02.009

Abstract

Obesity and type 2 diabetes (T2D) are metabolic diseases with shared pathophysiology. Traditional polygenic risk scores (PRSs) have focused on these conditions individually, yet the single-disease approach falls short in capturing the full dimension of metabolic dysfunction. We derived a biologically enriched metabolic PRS (MetPRS), a composite score that uses multi-ancestry genome-wide association studies of 20 metabolic traits from over 8.5 million individuals. MetPRS, optimized to predict obesity (O-MetPRS) and T2D (D-MetPRS), outperformed existing PRSs in predicting obesity and T2D across six ancestries. O-MetPRS and D-MetPRS effectively identify individuals at high risk for metabolic multimorbidity and predict clinical outcomes, including GLP-1 receptor agonist initiation. O-MetPRS and D-MetPRS showed an ∼2-fold increased risk of GLP-1 receptor agonist initiation for the top decile versus the middle quintile. The biologically enriched MetPRS has the potential to add an extra layer of information to disease prediction and management approaches for metabolic diseases.

Keywords: GLP-1 receptor agonist; metabolic traits; multi-ancestry GWAS; multimorbidity; obesity; polygenic risk score; type 2 diabetes.

MeSH terms

Diabetes Mellitus, Type 2* / epidemiology
Diabetes Mellitus, Type 2* / genetics
Diabetes Mellitus, Type 2* / metabolism
Female
Genetic Predisposition to Disease
Genetic Risk Score
Genome-Wide Association Study
Humans
Male
Multifactorial Inheritance* / genetics
Obesity* / epidemiology
Obesity* / genetics
Obesity* / metabolism
Risk Factors

Abstract

MeSH terms

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