Evidence map›Paper›PMID 41844147›Full record

ArticleCell metabolism2026

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 and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Min Seo KimMedical 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.
Qiuli ChenNational 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.
Yang SuiMedical 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.
Xiong YangNational Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Shaoqi WangNational 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.
Lu-Chen WengMedical 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.
So Mi Jemma ChoMedical 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.
Satoshi KoyamaMedical 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.
Xinyu ZhuNational 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.
Kang YuNational 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.
Xingyu ChenNational 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.
Rufan ZhangNational Genomics Data Center, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Wanqing YinNational 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.
Shuangqiao LiaoNational 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.
Zhaoqi LiuNational 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.
Fowzan S AlkurayaDepartment 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.
Pradeep NatarajanMedical 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.
Patrick T EllinorMedical 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.
Akl C FahedMedical 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.
Minxian WangNational 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.

Funding

IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
Using genetic variation to study biology of blood lipids & coronary heart diseaseR01HL127564 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Pradeep Natarajan, Gina Marie Peloso · 2015 to 2026
$7.3M
Enabling improved applicability and transferability of polygenic scores across populationsU01HG011719 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI Alicia Martin · 2021 to 2026
$5.5M
Genomics of Cardiac ArrhythmiasR01HL139731 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI ELLINOR, PATRICK THOMAS · 2018 to 2022
$3.3M
Coronary plaque changes with statin and colchicine among people with high polygenic risk- a mechanistic pilot studyR01HL164629 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Akl C Fahed, Michael TseYin Lu · 2023 to 2026
$3.3M
Using Electrocardiogram Genetics to Inform Arrhythmia RiskR01HL157635 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI ELLINOR, PATRICK THOMAS, MIRSHAHI, TOORAJ · 2022 to 2025
$2.9M
From genetic basis to mechanisms for Heart FailureR01HL177209 · NHLBI · BROAD INSTITUTE, INC. · PI Patrick Thomas Ellinor, Ling Xiao · 2025 to 2026
$1.6M
Integrating genomic and nongenomic risk for coronary artery diseaseK08HL161448 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Akl C Fahed · 2022 to 2026
$751k
Integration of novel contextual and genomic blood pressure measures to enhance cardiovascular disease prediction and management in young adultsK99HL177340 · NHLBI · BROAD INSTITUTE, INC. · PI So Mi Cho · 2025 to 2026
$331k
American Heart Association-American Stroke Association 961045 - PATRICK ELLINORNHGRI NIH HHS U01 HG011719NHLBI NIH HHS K08 HL161448NHLBI NIH HHS K99 HL177340NHLBI NIH HHS R01 HL092577NHLBI NIH HHS R01 HL127564NHLBI NIH HHS R01 HL139731NHLBI NIH HHS R01 HL157635NHLBI NIH HHS R01 HL164629NHLBI NIH HHS R01 HL177209
6 · The paper itself

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.

Indexed as

Diabetes Mellitus, Type 2Multifactorial InheritanceObesityGenetic Predisposition to DiseaseGenetic Risk ScoreGenome-Wide Association StudyHumansRisk FactorsGLP-1 receptor agonistmetabolic traitsmulti-ancestry GWASmultimorbidityobesitypolygenic risk scoretype 2 diabetes

Identifiers

PMID41844147
PMCPMC13092120

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.