Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts
Author(s) -
Daniel DiCorpo,
Jessica LeClair,
Joanne B. Cole,
Chloé Sarnowski,
Fariba Ahmadizar,
Lawrence F. Bielak,
Anneke Blokstra,
Erwin P. Böttinger,
Layal Chaker,
YiiDer I. Chen,
Ye Chen,
Paul S. de Vries,
Tariq Faquih,
Mohsen Ghanbari,
Valborg Guðmundsdóttir,
Xiuqing Guo,
Natalie R. Hasbani,
Dorina Ibi,
M. Arfan Ikram,
Maryam Kavousi,
Hampton L. Leonard,
Aaron Leong,
Josep M. Mercader,
Alanna C. Morrison,
Girish N. Nadkarni,
Mike A. Nalls,
Raymond Noordam,
Michael Preuß,
Jennifer A. Smith,
Stella Trompet,
Petra Vissink,
Jie Yao,
Wei Zhao,
Eric Boerwinkle,
Mark O. Goodarzi,
Vilmundur Guðnason,
J. Wouter Jukema,
Sharon L. R. Kardia,
Ruth J. F. Loos,
Yongmei Liu,
Alisa K. Manning,
Dennis O. MookKanamori,
James S. Pankow,
H. Susan J. Picavet,
Naveed Sattar,
Eleanor M. Simonsick,
W. M. Monique Verschuren,
Ko Willems van Dijk,
José C. Florez,
Jerome I. Rotter,
James B. Meigs,
Josée Dupuis,
Miriam S. Udler
Publication year - 2022
Publication title -
diabetes care
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.636
H-Index - 363
eISSN - 1935-5548
pISSN - 0149-5992
DOI - 10.2337/dc21-1395
Subject(s) - medicine , type 2 diabetes , diabetes mellitus , genetic epidemiology , disease , obesity , lipodystrophy , blood pressure , endocrinology , bioinformatics , biology , immunology , human immunodeficiency virus (hiv) , antiretroviral therapy , viral load
OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.
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