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Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 individuals Across 13 Cohorts

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posted on 27.01.2022, 21:38 authored by Daniel DiCorpo, Jessica LeClair, Joanne B. Cole, Chloé Sarnowski, Fariba Ahmadizar, Lawrence F. Bielak, Anneke Blokstra, Erwin P. Bottinger, Layal Chaker, Yii-Der I. Chen, Ye Chen, Paul S de Vries, Tariq Faquih, Mohsen Ghanbari, Valborg Gudmundsdottir, 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 Gudnason, J. Wouter Jukema, Sharon L. R. Kardia, Ruth J. F. Loos, Ching-Ti Liu, Alisa K. Manning, Dennis Mook-Kanamori, James S. Pankow, , H.Susan J. PIcavet, Naveed Sattar, Eleanor M. Simonsick, W.M.Monique Verschuren, Ko Willems van Dijk, Jose C. Florez, Jerome I. Rotter, James B. Meigs, Josée Dupuis, Miriam S. Udler
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: Beta 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 twelve 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’s, 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’s 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.

Conclusion: Our findings support that genetically-driven pathways leading to T2D also predispose differentially to clinical outcomes.


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