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

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 KavousiHampton 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

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and out-comes. 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 b-cell, proinsulin, obesity, lipodystro-phy, 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 hyperten-sion. 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 predis-pose differentially to clinical outcomes.

Original languageEnglish (US)
Pages (from-to)674-683
Number of pages10
JournalDiabetes care
Volume45
Issue number3
DOIs
StatePublished - Mar 2022

Bibliographical note

Funding Information:
Acknowledgments and Funding. AGES. The authors thank all AGES-Reykjavik study participants and the staff of the Icelandic Heart Association for their contribution to the AGES-Reykjavik study. This AGES-Reykjavik study has been funded by National Institutes of Health (NIH) contract N01-AG-1-2100 and HHSN271201200022C, the National Institute on Aging (NIA) Intramural Research Program, Hjarta-vernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). VGudm. is supported by the Icelandic Centre for Research (grant no. 184845-051). ARIC. The authors thank the staff and participants of the ARIC study for their important contributions. The Atherosclerosis Risk in Communities study has been funded in whole or in part with funds from the National Heart, Lung, and Blood Institute (NHLB), NIH, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HH-SN268201700003I, HHSN268201700004I, and HHSN268201700005I), R01HL087641, R01HL-059367, and R01HL086694, National Human Genome Research Institute (NHGRI) contract U01HG004402, and NIH contract HHSN26-8200625226C. Infrastructure was partly supported by the National Institutes of Health Roadmap for Medical Research, a component of the NIH, grant number UL1RR025005. BioMe. The authors thank all participants in the Mount Sinai Biobank and all of the recruiters who have assisted and continue to assist in data collection and management. The authors are grateful for the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. The Mount Sinai BioMe Biobank has been supported by The Andrea and Charles Bronfman Philanthropies and in part by Federal funds from the NHLBI (X01HL134588) and NHGRI (U01HG007417). G.N.N. is funded by the NIH NIDDK (R01DK127139, R56DK126930, K23DK107908). R.J.F.L. is funded by NIH NIDDK (R01DK 110113, R01DK107786), NHLBI (R01HL142302), and NHGRI (R56HG010297). Doetinchem. The authors would like to thank the field workers of the Municipal Health Services in Doetinchem (C. te Boekhorst, I. Thus, M. Zwiers, and B. Heusinkveld) for their contribution to the data collection for the current study. Principal investigator is Prof. Dr. Ir. W.M.M. Verschuren, project leader Dr. H.S.J. Picavet, data manager A. Blokstra, and logistic manager P. Vissink. The Doetinchem Cohort Study was financially supported by the Ministry of Health, Welfare and Sport of the Netherlands and the National Institute for Public Health and the Environment. FHS. Supported by from NHLBI contracts HHSN268201500001I and N01-HC-25195, and its contract with Affymetrix, Inc. for genotyping services (contract number N02-HL-6-4278). The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. Also supported by NIDDK (R01 DK078616, U01 DK0 78616, and UM1 DK078616), NHLBI (R01 HL151855), and by the National Institute of General Medical Sciences (NIGMS) Interdisciplinary Training Grant for Biostatisticians (T32 GM74905). C.S., C.T.L., D.D., J.B.M., and J.D. received funding from NIDDK (UM1 DK078616) and NHLBI (R01 HL151855). J.L. received funding from NIGMS (T32GM074905). GENOA. Genotyping was performed at the Mayo Clinic by Stephan T. Turner, MD, Mariza de Andrade, PhD, and Julie Cunningham, PhD. The authors thank Eric Boerwinkle, PhD, and Megan L. Grove, from the Human Genetics Center and

Funding Information:
Institute of Molecular Medicine and Division of Epidemiology, University of Texas Health Science Center, Houston, Texas, for their help with geno-typing. The authors would also like to thank the families that participated in the GENOA study. GENOA was supported by the NIH NBLBI grant numbers HL054457, HL054464, HL054481, HL087660, and HL119443. Health ABC. This research was supported by NIA contracts N01-AG-6-2101, N01-AG-6-2103, N01-AG-6-2106, NIA grant R01-AG028050, and National Institute of Nursing Research grant R01-NR012459. This research was funded in part by the Intramural Research Program of the NIH, NIA. MGB. The authors thank Partners HealthCare Biobank for providing samples, genomic data, and health information data. M.S.U. was supported by NIDDK K23DK114551. A.K.M. and Y.C. were supported by NIH NIDDK R03DK118305. J.M.M. is supported by American Diabetes Association Innovative and Clinical Translational Award 1-19-ICTS-068, and by NHGRI, grant FAIN no. U01HG011723. J.B.C. is supported by an NIDDK Pathway to Independence Award K99DK127196. A.L. is supported by grant 2020096 from the Doris Duke Charitable Foundation. MESA. Genotyping was performed at Affyme-trix (Santa Clara, CA) and the Broad Institute of Harvard and Massachusetts Institutes of Technology (Boston, MA) using the Affymetrix Genome-Wide Human SNP Array 6.0. MESA and the MESA SHARe project are conducted and supported by the NHLBI in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N920 20D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95 162, 75N92020D00006, N01-HC-95163, 75N 92020D00004, N01-HC-95164, 75N92020D0 0007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169, and National Center for Advancing Translational Sciences grants UL1-TR-000040, UL1-TR-001079, and UL1-TR-001420. Funding for SHARe genotyping was provided by NHLBI contract N02-HL-64278. Also supported in part by the National Center for Advancing Translational Sciences, Clinical and Translational Science Institute CTSI grant UL1TR001881, and the NIDDK Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. NEO. The authors of the NEO study thank all individuals who participated in the NEO study, all participating general practitioners for inviting eligible participants, and all research nurses for collection of the data. The authors thank the NEO study group, Pat van Beelen, Petra Noordijk, and Ingeborg de Jonge, for the coordination, laboratory, and data management of the NEO study. The genotyping in the NEO study was supported by the Centre National de Génotypage (Paris, France), headed by Jean-Francois Deleuze. The NEO study is supported by the participating Departments, the Division, and the Board of Directors of the Leiden University Medical Center, and by the Leiden University, Research Profile Area Vascular and Regenerative Medicine.

Funding Information:
D.M.-K. is supported by Dutch Science Organization (ZonMW-VENI Grant 916.14.023). PROSPER. Prof. Dr. J.W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping was provided by the Seventh Framework Program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). Rotterdam. The Rotterdam Study is supported by Erasmus MC and Erasmus University Rotterdam, Netherlands Organisation for Scientific Research (NWO), Netherlands Organisation for Health Research and Development (ZonMW), Research Institute for Diseases in the Elderly (RIDE), Netherlands Genomics Initiative, Ministry of Education, Culture and Science, Ministry of Health, Welfare and Sports, European Commission (DG XII), and Municipality of Rotterdam. Duality of Interest. J.B.M. is an academic associate for Quest Diagnostics. The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. No other potential conflicts of interest relevant to this article were reported. Author Contributions. D.D., J.L., J.B.C., C.S., and M.S.U. performed the analysis. D.D., J.I.R., J.B.M., J.D., and M.S.U. conceived the study. D.D., J.L., and M.S.U. wrote the first draft of the manuscript. F.A., L.F.B., A.B., E.P.B., L.C., Y.-D.I.C., Y.C., P.S.d.V., T.F., M.G., V.Gudm., X.G., N.R.H., D.I., M.A.I., M.K., H.L.L., A.L., J.M.M., A.C.M., G.N.N., M.A.N., R.N., M.P., J.A.S., S.T., P.V., J.Y., W.Z., E.B., M.O.G., V.Gudn., J.W.J., S.L.R.K., R.J.F.L., C.-T.L., A.K.M., D.M.-K., J.S.P., H.S.J.P., N.S., E.M.S., W.M.M.V., K.W.D., and J.C.F. provided data, contributed to data interpretation, and aided in manuscript revision. D.D. and M.S.U. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Publisher Copyright:
© 2022 by the American Diabetes Association.

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