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Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes

Nature Genetics volume 53, pages 1534–1542 (2021)Cite this article

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Abstract

Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the TCF7L2 locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near LRMDA was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.

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Fig. 1: Total heritability and FHD differs between subtypes.
Fig. 2: Distribution and association of T1D and T2D GRS with diabetes subtypes.
Fig. 3: Genetic risk of T1D estimated by T1D GRS.
Fig. 4: Association of insulin secretion and insulin sensitivity GRS with diabetes subtypes.
Fig. 5: Association of GRS of adiposity-related traits and lipids with diabetes subtypes.

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Data availability

Individual-level data are not publicly available due to ethical and legal restrictions related to the Swedish Biobanks in Medical Care Act (2002:297) and Personal Data Act (1998:204), the European Union’s General Data Protection Regulation 2016/679 and the Data Protection Act 2018:218. Supporting data are available from the corresponding author upon reasonable request but access to data must be granted by the ANDIS and MDC steering committees. Summary statistics are available in the GWAS Catalog (www.ebi.ac.uk/gwas/) under accession no. GCST90026412-7. SNPs and the weights for GRS are available in the supplementary tables and in the Polygenic Score Catalog (www.pgscatalog.org) under IDs PGS000832-64 and PGS000024.

Code availability

No custom code was used for the analysis of data.

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Acknowledgements

This study was supported by grants from the Swedish Research Council (project grant nos. 2017-02688 and 2020-02191 to E.A.), project grant no. 2015-2558 and infrastructure grant nos. 2010-5983, 2012-5538 and 2014-6395, Linnaeus grant no. 349-2006-237, a strategic research grant no. 2009-1039 (EXODIAB) all to L.G., project grant no. 2018-02635 to O.H. and Indo-Swedish joint network grant no. 2015-06722 to R.B.P.; a Vinnova Swelife grant (no. 2017-05284); and grants from the Academy of Finland (nos. 263401 and 267882 to L.G.), Novo Nordisk Foundation (no. NNF18OC0034408), Scania University Hospital (ALF grant), Diabetes Wellness Sweden (no. 25-420 PG), the Swedish Heart and Lung Foundation (no. 20180640), all to E.A., the Swedish Diabetes Foundation (no. DIA2019-468 to E.A., no. DIA2020-511 to O.H.), the EFSD/Lilly European Diabetes Research Programme to E.A., the Hjelt Foundation and the Albert Påhlsson Research Foundation to E.A. and O.H., the Crafoord Foundation (nos. 20180778, 20190912 and 20200867 to E.A., no. 20200828 to O.H. and no. 20200891 to R.B.P.) and Åke Wiberg Foundation (no. M20-0214) to R.B.P. This project was also financially supported by the Swedish Foundation for Strategic Research (no. IRC15-0067). The genotyping of ANDIS was funded by Pfizer. DIREVA was supported by the Vaasa Hospital District and the Jakobstadsnejden Heart, Folkhalsan Research and Ollqvist Foundations (to T.T. and A.K.). The Botnia Study (L.G., T.T.) has been supported by grants from the Folkhälsan Research and Sigrid Juselius Foundations, Academy of Finland (grants nos. 263401, 267882 and 312063 to L.G., 312072 to T.T. and 317599 to O.P.D.), University of Helsinki, Nordic Center of Excellence in Disease Genetics, European Union (EXGENESIS FP6-2004-005272, MOSAIC FP7-600914), Ollqvist Foundation, Swedish Cultural Foundation in Finland, Finnish Diabetes Research Foundation, Foundation for Life and Health in Finland, Signe and Ane Gyllenberg Foundation, Finnish Medical Society, Paavo Nurmi Foundation, State Research Funding via Helsinki University Hospital and the Perklén, Närpes Health Care and Ahokas Foundations. The study has also been supported by the Ministry of Education in Finland, Municipal Heath Care Center and Hospital in Jakobstad and Health Care Centers in Vaasa, Närpes and Korsholm. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (no. FP7/2007-2013)/ERC grant agreement no. 269045 and the Innovative Medicines Initiative 2 Joint Undertaking (no. 115881, RHAPSODY). The skillful assistance of the Botnia Study Group is gratefully acknowledged. The genotyping of Botnia was funded by Regeneron Pharmaceuticals. The study sponsors had no role in the analysis and interpretation of the data, writing of the manuscript or decision to submit the manuscript for publication. E.A. had full access to all the data in the study and had the final responsibility for the decision to submit for publication. We thank all patients and healthcare providers for their support and willingness to participate. We also thank J. Hultman, M. Borell, J. Kravic, G. Gremsperger, M. Sterner, M. Neptin and U. Blom-Nilsson for excellent technical and administrative support, Region Skåne (Scania County) and the ANDIS steering committee for their support.

Author information

Author notes

  1. Anubha Mahajan & Mark I. McCarthy

    Present address: Genentech, South San Francisco, CA, USA

  2. Deceased Julia Brosnan.

Authors and Affiliations

  1. Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden

    Dina Mansour Aly, Rashmi B. Prasad, Manonanthini Thangam, Mikael Åkerlund, Olle Melander, Ola Hansson, Tiinamaija Tuomi, Leif Groop & Emma Ahlqvist

  2. Finnish Institute for Molecular Medicine, Helsinki University, Helsinki, Finland

    Om Prakash Dwivedi, Ola Hansson, Tiinamaija Tuomi & Leif Groop

  3. Department of Primary Health Care, Vaasa Central Hospital, Vaasa, Finland

    Annemari Käräjämäki

  4. Diabetes Center, Vaasa Health Care Center, Vaasa, Finland

    Annemari Käräjämäki

  5. Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden

    Rebecka Hjort & Sofia Carlsson

  6. Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK

    Anubha Mahajan

  7. Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA

    Miriam S. Udler & Jose C. Florez

  8. Programs in Metabolism and Medical & Population Genetics, Broad Institute, Boston, MA, USA

    Miriam S. Udler & Jose C. Florez

  9. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Miriam S. Udler & Jose C. Florez

  10. Oxford Centre for Diabetes Endocrinology & Metabolism, University of Oxford, Oxford, UK

    Mark I. McCarthy

  11. Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

    Mark I. McCarthy

  12. Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, UK

    Mark I. McCarthy

  13. Pfizer Inc., Cambridge, MA, USA

    Caitlin Forsythe & Julia Brosnan

  14. Folkhälsan Research Center, Helsinki, Finland

    Tiinamaija Tuomi

  15. Abdominal Center, Endocrinology, Helsinki University Central Hospital, Research Program for Diabetes and Obesity, Center of Helsinki, Helsinki, Finland

    Tiinamaija Tuomi

  16. Regeneron Pharmaceuticals Inc., Tarrytown, NY, USA

    Goncalo Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Aris Economides, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Andrew Blumenfeld, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Evan K. Maxwell, William Salerno, Jeffrey C. Staples, Marcus B. Jones & Lyndon J. Mitnaul

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  1. Dina Mansour Aly
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Consortia

Regeneron Genetics Center

  • RGC Management and Leadership Team

    • Goncalo Abecasis
    • , Aris Baras
    • , Michael Cantor
    • , Giovanni Coppola
    • , Aris Economides
    • , Luca A. Lotta
    • , John D. Overton
    • , Jeffrey G. Reid
    •  & Alan Shuldiner

  • Sequencing and Lab Operations

    • Christina Beechert
    • , Caitlin Forsythe
    • , Erin D. Fuller
    • , Zhenhua Gu
    • , Michael Lattari
    • , Alexander Lopez
    • , John D. Overton
    • , Thomas D. Schleicher
    • , Maria Sotiropoulos Padilla
    • , Louis Widom
    • , Sarah E. Wolf
    • , Manasi Pradhan
    • , Kia Manoochehri
    •  & Ricardo H. Ulloa

  • Genome Informatics

    • Xiaodong Bai
    • , Suganthi Balasubramanian
    • , Andrew Blumenfeld
    • , Gisu Eom
    • , Lukas Habegger
    • , Alicia Hawes
    • , Shareef Khalid
    • , Jeffrey G. Reid
    • , Evan K. Maxwell
    • , William Salerno
    •  & Jeffrey C. Staples

  • Research Program Management

    • Marcus B. Jones
    •  & Lyndon J. Mitnaul

Contributions

D.M.A., O.P.D., R.B.P., J.C.F., M.I.M., T.T., L.G. and E.A. contributed to the conception of the work. A.K., J.B., R.G.C., O.M., S.C., O.H., T.T., L.G. and E.A. contributed to data collection. D.M.A., O.P.D., R.H., M.T., M.Å., A.M., M.S.U. and E.A. contributed to the data analysis. D.M.A., O.P.D., T.T., L.G. and E.A. drafted the manuscript. All authors contributed to the interpretation of the data and critical revision of the manuscript. All authors gave final approval of the version to be published.

Corresponding author

Correspondence to Emma Ahlqvist.

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Competing interests

The views expressed in this article are those of the authors and not necessarily those of the National Health Service, National Institute for Health Research or Department of Health. M.I.M. has served on advisory panels for Pfizer, Novo Nordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly and research funding from AbbVie, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, Novo Nordisk, Pfizer, Roche, Sanofi Aventis, Servier and Takeda. As of June 2019, M.I.M. is an employee of Genentech and a holder of Roche stock. As of January 2020, A.M. is an employee of Genentech and a holder of Roche stock. J.B. is an employee and shareholder of Pfizer. J.C.F. has received consulting honoraria from Goldfinch Bio and speaking honoraria from Novo Nordisk. The other authors declare no competing interests.

Additional information

Peer review information Nature Genetics thanks Stephen Rich, Constantin Polychronakos, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Association of GRS of diabetic complications with diabetes subtypes.

a-e, Association of GRS for chronic kidney disease (CKD) (a), estimated glomerular filtration rate (eGFR) (b), urine albumin creatinine ratio (UACR) (c), diabetic retinopathy (DR) (d) and cardiovascular disease (CVD) (e). Each subtype was compared to diabetes-free controls using logistic regression adjusted for sex and PCs. ANDIS (nSAID = 452, nSIDD = 1,193, nSIRD = 1,129, nMOD = 1,374, nMARD = 2,861, nT2D = 7,676, ncontrols = 2,744), and DIREVA (nSAID = 327, nSIDD = 394, nSIRD = 453, nMOD = 596, nMARD = 1,178, nT2D = 2,621, ncontrols = 1,683). In ANDIS, eGFR-GRS, UACR-GRS and CVD-GRS showed no association with any subtype. CKD-GRS was associated with SIRD with nominal significance in ANDIS (P = 0.047) but not in DIREVA (P = 0.38). DR was associated with SIRD (P = 0.016) and MOD (P = 0.015) with nominal significance but not in DIREVA (P = 0.37 and P = 0.36). None of the GRS were significant after adjustment for multiple comparisons (n = 5 tests). Data are presented as odds ratio and 95% confidence interval per s.d. increase of GRS. Exact numbers and statistics are in Supplementary Table 13. P-values are two-sided and not adjusted for multiple comparisons.

Extended Data Fig. 2 Manhattan and QQ plots of GWAS in ANDIS-MDC.

a-e, GWAS of each subtype in ANDIS using diabetes-free controls (n = 2,744) from the MDC study: SAID (n = 452) (a), SIDD (n = 1,193) (b), SIRD (n = 1,130) (c), MOD (n = 1,374) (d), MARD (n = 2,861) (e). Variants in the HLA region were associated with SAID (rs9273368 OR = 2.89 [2.31-3.10], P = 6.5 ×10−40). The rs7903146TCF7L2 locus was associated with SIDD (OR = 1.56 [1.39-1.75], P = 8.6 ×10−15), MOD (OR = 1.40 [1.26-1.56], P = 3.1 ×10−10) and MARD (1.42 [1.30-1.54], P = 6.1 ×10−16). rs10824307 near the LRMDA gene was associated with MOD (OR = 1.35 [1.22-1.49], P = 1.3 ×10−9). The red line indicates the genome-wide significance threshold (P < 5 ×10−8) and the blue line suggestive association (P < 10−5). Statistics were calculated using the additive SNPtest score method adjusting for sex and 4 PCs. P-values are two-sided and not adjusted for multiple comparisons.

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Mansour Aly, D., Dwivedi, O.P., Prasad, R.B. et al. Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes. Nat Genet 53, 1534–1542 (2021). https://doi.org/10.1038/s41588-021-00948-2

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