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[Preprint]. 2025 May 7:2025.05.05.25326966.

doi: 10.1101/2025.05.05.25326966.

The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities

Ana Luiza Arruda^{1

2}, Ozvan Bocher^{1

3}, Henry J Taylor^{4

5

6}, Davis Cammann⁷, Satoshi Yoshiji^{8

9

10}, Xianyong Yin^{11

12}, Chi Zhao¹³, Jingchun Chen⁷, Alexis C Wood¹⁴, Ken Suzuki¹⁵, Josep M Mercader^{8

16

17}, Cassandra N Spracklen¹³, James B Meigs^{8

18

19}, Marijana Vujkovic^{20

21

22}, George Davey Smith²³, Jerome I Rotter²⁴, Benjamin F Voight^{20

21

25

26}, Andrew P Morris²⁷, Eleftheria Zeggini^{1

28}

Affiliations

¹ Institute of Translational Genomics, Helmholtz Munich, Neuherberg, 85764, Germany.
² Technical University of Munich (TUM), School of Medicine and Health, Graduate School of Experimental Medicine, Munich, 81675, Germany.
³ Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France.
⁴ Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
⁵ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
⁶ Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
⁷ Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas, 4505 S. Maryland Parkway, Las Vegas, NV 89154, USA.
⁸ Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁹ Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
¹⁰ McGill Genome Centre, McGill University, Montreal, QC, Canada.
¹¹ Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
¹² Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
¹³ Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA.
¹⁴ USDA/ARS Children's Nutrition Center, Baylor College of Medicine, Houston, TX, USA.
¹⁵ Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
¹⁶ Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁷ Harvard Medical School, Boston, MA, USA.
¹⁸ Department of Medicine, Harvard Medical School, Boston, MA, USA.
¹⁹ Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
²⁰ Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
²¹ Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²² Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²³ MRC Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
²⁴ Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
²⁵ Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²⁶ Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²⁷ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, United Kingdom.
²⁸ TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, Munich, 81675, Germany.

PMID: 40385452
PMCID: PMC12083600
DOI: 10.1101/2025.05.05.25326966

The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities

Ana Luiza Arruda et al. medRxiv. 2025.

[Preprint]. 2025 May 7:2025.05.05.25326966.

doi: 10.1101/2025.05.05.25326966.

Authors

Affiliations

¹ Institute of Translational Genomics, Helmholtz Munich, Neuherberg, 85764, Germany.
² Technical University of Munich (TUM), School of Medicine and Health, Graduate School of Experimental Medicine, Munich, 81675, Germany.
³ Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France.
⁴ Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
⁵ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
⁶ Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
⁷ Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas, 4505 S. Maryland Parkway, Las Vegas, NV 89154, USA.
⁸ Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁹ Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
¹⁰ McGill Genome Centre, McGill University, Montreal, QC, Canada.
¹¹ Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
¹² Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
¹³ Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA.
¹⁴ USDA/ARS Children's Nutrition Center, Baylor College of Medicine, Houston, TX, USA.
¹⁵ Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
¹⁶ Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁷ Harvard Medical School, Boston, MA, USA.
¹⁸ Department of Medicine, Harvard Medical School, Boston, MA, USA.
¹⁹ Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
²⁰ Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
²¹ Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²² Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²³ MRC Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
²⁴ Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
²⁵ Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²⁶ Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
²⁷ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, United Kingdom.
²⁸ TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, Munich, 81675, Germany.

PMID: 40385452
PMCID: PMC12083600
DOI: 10.1101/2025.05.05.25326966

Update in

The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities.
Arruda AL, Bocher O, Taylor HJ, Cammann D, Yoshiji S, Yin X, Zhao C, Chen J, Wood AC, Suzuki K, Mercader JM, Spracklen CN, Meigs JB, Vujkovic M, Smith GD, Rotter JI, Voight BF, Morris AP, Zeggini E. Arruda AL, et al. Nat Commun. 2025 Oct 10;16(1):9042. doi: 10.1038/s41467-025-64927-5. Nat Commun. 2025. PMID: 41073432 Free PMC article.

Abstract

Type 2 diabetes (T2D) is epidemiologically associated with a wide range of non-cardiovascular comorbidities, yet their shared etiology has not been fully elucidated. Leveraging eight non-overlapping mechanistic clusters of T2D genetic profiles, each representing distinct biological pathways, we investigate putative causal links between cluster-stratified T2D genetic predisposition and 21 non-cardiovascular comorbidities. Most of the identified putative causal effects are driven by distinct T2D genetic clusters. For example, the risk-increasing effects of T2D genetic predisposition on cataracts and erectile dysfunction are primarily attributed to obesity and glucose regulation mechanisms, respectively. When surveyed in populations across the globe, we observe opposing effect directions for depression, asthma and chronic obstructive pulmonary disease between populations. We identify a putative causal link between T2D genetic predisposition and osteoarthritis. To underscore the translational potential of our findings, we intersect high-confidence effector genes for osteoarthritis with targets of T2D-approved drugs and identify metformin as a potential candidate for drug repurposing in osteoarthritis.

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Figures

**Extended Figure 1:**
Results of cluster-stratified two-sample Mendelian randomization (MR) analysis of genetic predisposition to type 2 diabetes (T2D) on non-cardiovascular comorbidities risk. Causal estimates are expressed as the odds ratio (OR) of each comorbidity per doubling (2-fold increase) in genetically determined dichotomous T2D risk. Filled circles mark estimates with a q-value < 0.05 that passed all sensitivity analyses to assess the validity of the MR assumptions. (T2DGGI = Type 2 Diabetes Global Genomics Initiative; CI = confidence interval; PI = proinsulin; CTS = Carpal tunnel syndrome; ADHD = attention-deficit/hyperactivity disorder; OCD = obsessive-compulsive disorder; PCOS = polycystic ovary syndrome; COPD = chronic obstructive pulmonary disease)

**Extended Figure 2:**
Results of the single-ancestry cluster-stratified two-sample Mendelian randomization (MR) analysis of genetic predisposition to type 2 diabetes (T2D) on non-cardiovascular comorbidities risk. Causal estimates are expressed as the odds ratio (OR) of each comorbidity per doubling (2-fold increase) in genetically determined dichotomous T2D risk. Filled circles mark estimates with a q-value < 0.05 that passed all sensitivity analyses to assess the validity of the MR assumptions. (T2DGGI = Type 2 Diabetes Global Genomics Initiative; CI = confidence interval; PI = proinsulin; COPD = chronic obstructive pulmonary disease)

**Figure 1:**
Overview of study design (MR = Mendelian randomization; T2D = type 2 diabetes; IVs = genetic instrumental variables; P = p-value).

**Figure 2:**
Results of two-sample Mendelian randomization (MR) analysis of genetic predisposition to type 2 diabetes (T2D) on non-cardiovascular comorbidity risk for the putative causal relationships (q-value < 0.05). Causal estimates are expressed as the odds ratio (OR) for each comorbidity per doubling (2-fold increase) in genetically determined dichotomous T2D risk. Filled circles mark estimates that passed the sensitivity analyses to assess the validity of the MR assumptions. (CI = confidence interval; CTS = Carpal tunnel syndrome; ADHD = attention-deficit/hyperactivity disorder; OCD = obsessive-compulsive disorder; PCOS = polycystic ovary syndrome)

**Figure 3:**
Results of cluster-stratified two-sample Mendelian randomization (MR) analysis of genetic predisposition to type 2 diabetes (T2D) on non-cardiovascular comorbidities risk for the putative causal relationships (q-value < 0.05). Causal estimates are expressed as the odds ratio (OR) for each comorbidity per doubling (2-fold increase) in genetically determined dichotomous T2D risk. Filled circles mark estimates that passed all sensitivity analyses to assess the validity of the MR assumptions. (T2DGGI = Type 2 Diabetes Global Genomics Initiative; CI = confidence interval; PI = proinsulin; CTS = Carpal tunnel syndrome; ADHD = attention-deficit/hyperactivity disorder; OCD = obsessive-compulsive disorder; PCOS = polycystic ovary syndrome; COPD = chronic obstructive pulmonary disease)

**Figure 4:**
Mendelian randomization (MR) results for different global genetic ancestry groups using cluster-stratified genetic predisposition to T2D and risk for T2D non-cardiovascular comorbidities (EUR=individuals genetically similar to Europeans, EAS=individuals genetically similar to East Asians) for the putative causal relationships (q-value < 0.05). Causal estimates are expressed as the odds ratio (OR) of each comorbidity per doubling (2-fold increase) in genetically determined dichotomous T2D risk. Filled circles mark robust estimates that passed all sensitivity analyses (T2DGGI = Type 2 Diabetes Global Genomics Initiative; CI = confidence interval; PI = proinsulin).

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References

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This is a preprint.

The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities

Affiliations

The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities

Authors

Affiliations

Update in

Abstract

Figures

References

Publication types

Grants and funding

LinkOut - more resources

Full Text Sources