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

Author:

DiCorpo Daniel1,LeClair Jessica1,Cole Joanne B.234,Sarnowski Chloé1,Ahmadizar Fariba56ORCID,Bielak Lawrence F.7,Blokstra Anneke8,Bottinger Erwin P.910,Chaker Layal51112,Chen Yii-Der I.13,Chen Ye14,de Vries Paul S.15,Faquih Tariq16,Ghanbari Mohsen5,Gudmundsdottir Valborg1718,Guo Xiuqing13,Hasbani Natalie R.15,Ibi Dorina819,Ikram M. Arfan5,Kavousi Maryam5ORCID,Leonard Hampton L.202122,Leong Aaron232324ORCID,Mercader Josep M.2323ORCID,Morrison Alanna C.14,Nadkarni Girish N.2526ORCID,Nalls Mike A.202122,Noordam Raymond27ORCID,Preuss Michael25,Smith Jennifer A.728,Trompet Stella27,Vissink Petra8,Yao Jie13,Zhao Wei7,Boerwinkle Eric1529,Goodarzi Mark O.30ORCID,Gudnason Vilmundur1718ORCID,Jukema J. Wouter313233,Kardia Sharon L.R.7,Loos Ruth J.F.23,Liu Ching-Ti1ORCID,Manning Alisa K.14,Mook-Kanamori Dennis16,Pankow James S.34,Picavet H. Susan J.8,Sattar Naveed35ORCID,Simonsick Eleanor M.36,Verschuren W.M. Monique837,Willems van Dijk Ko19,Florez Jose C.2338ORCID,Rotter Jerome I.13,Meigs James B.22324ORCID,Dupuis Josée1,Udler Miriam S.233839ORCID

Affiliation:

1. Department of Biostatistics, Boston University School of Public Health, Boston, MA

2. Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA

3. Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA

4. Division of Endocrinology, Boston Children’s Hospital, Boston, MA

5. Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands

6. Julius Global Health, University Utrecht Medical Center, Utrecht, the Netherlands

7. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI

8. National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands

9. Hasso Plattner Institute Digital Health, Potsdam, Germany

10. Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY

11. Department of Internal Medicine, Division of Endocrinology, Erasmus University Medical Center, Rotterdam, the Netherlands

12. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA

13. The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA

14. Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA

15. Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX

16. Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands

17. Icelandic Heart Association, Kopavogur, Iceland

18. Faculty of Medicine, University of Iceland, Reykjavik, Iceland

19. Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands

20. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD

21. Data Tecnica International, Glen Echo, MD

22. Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD

23. Department of Medicine, Harvard Medical School, Boston, MA

24. Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA

25. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY

26. Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY

27. Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands

28. Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI

29. Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX

30. Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA

31. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands

32. Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands

33. Netherlands Heart Institute, Utrecht, the Netherlands

34. Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN

35. British Heart Foundation Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, U.K.

36. Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD

37. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands

38. Endocrine Division, Massachusetts General Hospital, Boston, MA

39. Harvard Medical School, Boston, MA

Abstract

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.

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3