Type 2 diabetes partitioned polygenic scores associate with disease outcomes in 454,193 individuals across 13 cohorts
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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.
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The authors have high suspicion that the nominal association between β-cell cluster pPS and diabetes incidence is a true association.
“We have high suspicion that it is a true association because all the individual alleles in the pPS are associated with T2D risk (by design) and the β-cell cluster pPS has been shown in prior work to have the strongest association with prevalent T2D of any cluster (11).”
From Increased genetic risk for β-cell failure is associated with β-cell function decline in people with prediabetes (2024) · cites this paper as [11]
The citation is attached to the assertion that the β-cell cluster pPS has the strongest association with prevalent T2D. The Conclusions (page unavailable) instead say it is the cluster most strongly associated with fasting glucose and HbA1c; the searched passages do not establish its ranking for prevalent T2D. The citing authors’ suspicion about diabetes incidence is their own inference, not a conclusion attributed to this source. (LLM, conf=0.76)
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Leptin acutely increases hepatic triglyceride secretion in patients with lipodystrophy
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On the Verge of Precision Medicine in Diabetes
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ResultSelf-citationActionability of Genetic Variants in Diabetes: Core Aspects and Applied Examples
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“Many scores are derived from the cumulative effects of independent genetic signals identi fi ed in genome-wide association studies (30) and may be further re fi ned into pathway-or cell-type – speci fi c scores (31 – 33).”
Mapping disease loci to biological processes via joint pleiotropic and epigenomic partitioning
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Converging TCF7L2 and CDKAL1 pathways in the pathogenesis of type 2 diabetes mellitus
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“These loci still support mechanistic stratification in studies that measure incretin-potentiated insulin secretion, proinsulin-to-insulin ratio, and beta cell stress markers under standardized metabolic challenges [ 65 , 66 ].”
Precision Medicine in Type 2 Diabetes
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Dynamic measures of insulin action identify genetic determinants of dysglycemia
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Diabetes Genetic Clusters and Clinical Outcomes in the Chronic Renal Insufficiency Cohort
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Genetic Predictors of Response to Oral Insulin for Type 1 Diabetes Prevention
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“Consequently, conventional genome-wide polygenic risk scores (PRSs), which aggregate genetic risk across pathogenic mechanisms, may obscure biologically distinct effects by combining heterogeneous genetic signals into a single measure (26).”
Obesity Endotypes Unmask Heterogeneous Responses to Healthy Lifestyle BehaviorsPreprint
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Multifaceted role of genetic and epigenetic architecture of glucose homeostasis and diabetes
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“…hepatic or adipose-muscle hub burden should preferentially respond to metformin or insulin-sensitising agents — astrati fi cationhypothesisbeginningtobesupportedbypartitioned PRS analyses in observational cohorts 12,114 but requiring dedicated randomised pharmacogenomic trials for con fi rmation.”
- Authors
- DiCorpo, D., LeClair, J., Cole, J. B., Sarnowski, C., Ahmadizar, F., Bielak, L. F., Blokstra, A., Bottinger, E. P., Chaker, L., Chen, Y.-D. I., Chen, Y., de Vries, P. S., Faquih, T., Ghanbari, M., Gudmundsdottir, V., Guo, X., Hasbani, N. R., Ibi, D., Ikram, M. A., Kavousi, M., Leonard, H. L., Leong, A., Mercader, J. M., Morrison, A. C., Nadkarni, G. N., Nalls, M. A., Noordam, R., Preuss, M., Smith, J. A., Trompet, S., Vissink, P., Yao, J., Zhao, W., Boerwinkle, E., Goodarzi, M. O., Gudnason, V., Jukema, J. W., Kardia, S. L. R., Loos, R. J. F., Liu, C.-T., Manning, A. K., Mook-Kanamori, D., Pankow, J. S., Picavet, H. S. J., Sattar, N., Simonsick, E. M., Verschuren, W. M. M., Willems van Dijk, K., Florez, J. C., Rotter, J. I., Meigs, J. B., Dupuis, J., & Udler, M. S.
- Affiliations
- Boston University (US)
- Broad Institute (US)
- Erasmus MC (NL)
- University of Michigan (US)
- National Institute for Public Health and the Environment (NL)
- 9Hasso Plattner Institute Digital Health, Potsdam, Germany
- Harvard University (US)
- The Lundquist Institute (US)
- 15Human 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
- Leiden University Medical Center (NL)
- 17Icelandic Heart Association, Kopavogur, Iceland
- The University of Texas Health Science Center at Houston (US)
- National Institutes of Health (US)
- Massachusetts General Hospital (US)
- Icahn School of Medicine at Mount Sinai (US)
- Baylor College of Medicine (US)
- Cedars-Sinai Medical Center (US)
- University of Iceland (IS)
- 16Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- University of Minnesota (US)
- 35British Heart Foundation Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, U.K.
- Utrecht University (NL)
- 19Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- 23Department of Medicine, Harvard Medical School, Boston, MA
- Corresponding author
- Udler, Miriam S.
- ORCID
- DiCorpo, Daniel
- LeClair, Jessica
- Cole, Joanne B.
- Sarnowski, Chloé
- Ahmadizar, Fariba
- Bielak, Lawrence F.
- Chaker, Layal
- Chen, Yii-Der I.
- Chen, Ye
- Faquih, Tariq
- Ghanbari, Mohsen
- Guo, Xiuqing
- Hasbani, Natalie R.
- Ibi, Dorina
- Ikram, M. Arfan
- Kavousi, Maryam
- Leonard, Hampton L.
- Leong, Aaron
- Mercader, Josep M.
- Morrison, Alanna C.
- Nadkarni, Girish N.
- Nalls, Mike A.
- Noordam, Raymond
- Preuss, Michael
- Smith, Jennifer A.
- Trompet, Stella
- Yao, Jie
- Zhao, Wei
- Boerwinkle, Eric
- Goodarzi, Mark O.
- Gudnason, Vilmundur
- Jukema, J. Wouter
- Loos, Ruth J.F.
- Liu, Ching-Ti
- Manning, Alisa K.
- Pankow, James S.
- Picavet, H. Susan J.
- Sattar, Naveed
- Simonsick, Eleanor M.
- Verschuren, W.M. Monique
- Florez, Jose C.
- Rotter, Jerome I.
- Meigs, James B.
- Dupuis, Josée
- Udler, Miriam S.
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2022-01-27
- Volume
- 45
- Issue
- 3
- Pages
- 674-683
- ISSN
- 0149-5992 (ISSN-L)
- PMC
- PMC8918228
- OpenAlex
- W4210360628
- Cited by
- 66
- References
- 41
- Citations by year
- 2026: 10 · 2025: 20 · 2024: 15 · 2023: 13 · 2022: 8
- FWCI
- 8.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes Care (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, cc-by)
- Leiden Repository (Leiden University) (submittedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
- Rivm (National Institute for Public Health and the Environment) (submittedVersion)
- Funders
- U.S. Department of Health and Human Services (N01-HC-25195, R01HL086694, UL1-TR-000040, U01HG011723, N01-HC-95159, UL1TR001079, N01-HC-95161, DK063491, 75N92020D00003, N01-HC-95168, UL1TR001420, 75N92020D00001, HHSN268201700001I, UL1-TR-001881, N01-HC-95160, 75N92020D00002, N01HC95169, N01-HC-95164, HHSN268201500001I, N01-HC-95167, HHSN268201500003I, N01-HC-95165, HL151855, R01HL087641, R01-AG028050, R56DK126930, R01DK107786, 75N92020D00006, K99DK127196, HHSN268201700002I, N02-HL-64278, HHSN268201700005I, HHSN268201700004I, R01DK127139, R01HL142302, HHSN271201200022C, N01-HC-95163, N01HC95166, R01-NR012459, DK078616)
- American Diabetes Association (DK078616, 75N92020D00002, N01-HC-95159, N01-HC-95169, UL1-TR-000040, HHSN268201500003I, N01-HC-95163, 75N92020D00001, N01-HC-95164, N01-HC-95161, 1-19-ICTS-068, N01-HC-95160, UL1-TR-001079, N01-HC-95166, N01-HC-95167, 75N92020D00003, N01-HC-95168, 75N92020D00006, UL1-TR-001420, N01-HC-95165)
- Mayo Clinic
- Andrea and Charles Bronfman Philanthropies
- Bristol-Myers Squibb (2001 D 032)
- Icahn School of Medicine at Mount Sinai
- Broad Institute (U01HG007417)
- Quest Diagnostics
- European Commission (223004)
- Universiteit Leiden (050-060-810)
- ZonMw (91614023, VENI Grant 916.14.023, 050-060-810)
- Erasmus Universiteit Rotterdam
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (050.060.810, 64278, N02-HL-64278, UL1-TR-001420, N01-HC-95168, N01-HC-95165, HHSN268201500003I, N01-HC-95169, UL1-TR-000040, N01-HC-95167, 75N92020D00001, N01-HC-95159, UL1-TR-001079, N01-HC-95166, 916.14.023)
- Leids Universitair Medisch Centrum
- Hjartavernd (HHSN271201200022C, N01-AG-1-2100)
- National Institutes of Health (n01hc95164-17-0-1, HHSN268201700002I, n01ag12100-57-0-2, UL1TR001420, HHSN271201200022C, HHSN268201700004I, n01hc95165-34-0-1, n01hc95161-24-0-1, n01hc095169-003, N01-HC- 95166, N01-AG-1-2100, HHSN268201700001I, n01hc95166-21-0-1, N01-HC9-5168, n01hc95162-31-0-1, HHSN268201700005I, n01hc95168-27-0-1, n01hc95160-18-0-1, n01hc095167-000, N01-HC- 95159, UL1TR001079, n01hc25195-41-0-1, n01hc95163-22-0-1, n02hl64278-6-0-0, HHSN268201500003I, n01hc95159-40-0-1, UL1TR000040, HHSN268201500001I, N01‐HC‐95161, N01- HC-95163, N01- HC-95165, N01‐HC‐95160, N01 HC95164, N01-HC-95167, N02-HL-64278, N01‐HC‐95169, DK078616, N01-HC 25195, DK-063491, HL054457, UL1TR001881)
- Medical Research Council (MC_PC_17228)
- National Institute on Aging (N01‐AG‐6–2101, R01‐NR012459, N01‐HC‐95163, N01-HC-95169, R01AG028050, N01-HC-95167, NIA grant R01-AG-028050, N01-AG12100, N01‐HC‐95159, HHSN268201700002I, N01‐HC‐95166, N01‐HC‐95164, N02-HL-6-4278, N01-HC-25195, N01-HC-95168, AG-6-2106, R00AG066849, 75N92020D00001, UL1-TR-001079, N01‐HC‐95160, 75N92020D00006, N01-HC-95165, HHSN268201500001I, 75N92020D00003, N01‐HC‐95161, AG-6-2101, UL1-TR-000040, HHSN268201700005I, N01AG62106, 75N92020D00002, HHSN268201700004I, HHSN268201500003I, HHSN268201700001I, K99AG066849, N01-AG-62103, HHSN271201200022C)
- National Heart, Lung, and Blood Institute (DK-063491, R01HL151855, HHSN268201700004I, N01 HC-95159, N01-HC-95160, N01-HC095169, HC25195, HL-054481, 75N92020D00001, R01-NR012459, N01 HC-95168, N01-HC-095165, 75N92020D00006, U10HL054464, N01 HC95167, X01HL134588, (N01-HC-95163, N01 HC095163, N01-HC-95, N01‐HC25195, 75N92020D00007, HHSN268201500001I, HL-054457, N01 HC-95161, N01 HC95165, N01HC95164, N02 HL064278, HL054464, HHSN268201500001C, R01HL087660, 75N92020D00002, UL1-TR-, N01-HC-095159, N01-HC, N01 HC095168, N02- HL-64278, N01AG62101, HHSN268201700001I, N01-HC-095162, R01HL119443, HC-95168, N01-HC-095161, 75N92020D00005, HHSN268201700005C, HHSN268201700003I, DK078616, HHSN268201500003C, HL-087660, HHSN26820150 0003I, 75N92020D00003, N01-HC-025195, N01AG62106, R01HL087641, R01HL059367, U10HL054457, HHSN268201700005I, N01 HC095167, HL119443, R01HL105756, HHSN268201700001C, N01-HC-095160, R01 HL, N01 HC095166, U01HL054457, N01 HC095164, HL151855, N01‐HC‐95166, HHSN268201700002I, U10HL054481, HHSN268201700003C, HHSN268201700002C, U01HL054464, 75N920, HC95159, HHSN268201700004C, 75N92020D00004, U01HL054481, K24HL157960, R01HL142302, R01HL086694, HL64278, N01 HC95169)
- National Institute on Drug Abuse (HHSN271201200022C)
- National Human Genome Research Institute (HHSN268201700002I, HHSN268201700005I, HHSN268201700004I, N01-HC-25195, 2020096, HHSN268201700001I, N02-HL-6-4278, U01HG004402, U01HG007417, contract U01HG004402, R56HG010297, HHSN268201500001I, U01HG011723)
- National Institute of Nursing Research (N01-AG-6–2101, N01-HC-95167, N01-HC-95165, N01-HC-95160, N01-HC-95164, N01-HC-95161, N01-AG-6–2106, N01-HC-95169, NR012459, R01NR012459, N01-HC-95159, N01-HC-95168, N01-HC-95163, N01-HC-95166)
- National Institute of General Medical Sciences (T32GM74905, T32GM074905)
- National Institute of Diabetes and Digestive and Kidney Diseases (UL1-TR001079, R03DK118305, DK063491, DK078616, HHSN268201700002I, N01-HC-95163, N01-HC-95167, K99DK127196, N01-HC-25195, HHSN268201700004I, N01-HC-95166, N01-HC-95160, N01-HC-95169, N01-HC-95165, K23DK107908, HHSN268201700001I, HHSN268201500001I, N02-HL-64278, R01DK078616, R01DK107786, R01DK110113, U01DK078616, N01-HC-95168, N01-HC-95161, K23DK114551, R56DK126930, N01-HC-95159, N01-HC-95164, UM1DK078616, P30DK063491, R01DK127139, HHSN268201700005I)
- National Center for Research Resources (UL1RR025005)
- National Center for Advancing Translational Sciences (N01-HC-95161, 75N92020D00006, N01-HC-95168, UL1-TR, N01-HC-95159, DK063491, N01-HC-95160, 75N92020D00002, 75N92020D00001, HHSN268201500003I, N01-HC-95166, N01-HC-95169, N01-HC-95163, 75N92020D00003, N01-HC-95167, N01-HC-95165, N01-HC-95164)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- type 2 diabetes, genetic heterogeneity, obesity, lipodystrophy, hepatic lipid metabolism, blood pressure, hypertension, coronary artery disease, renal function, insulin use, age at diabetes diagnosis, GCKR, PNPLA3, TM6SF2, cardiovascular risk
- MeSH terms
- Alleles, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Pharmaceutical Preparations, Humans, Obesity, Genetic Loci
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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