Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
Triglyceride-glucose index, genetic susceptibility, and trajectory of microvascular multimorbidity in type 2 diabetes
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 11 February 2026

Triglyceride-glucose index, genetic susceptibility, and trajectory of microvascular multimorbidity in type 2 diabetes

  • Xiangling Yuan1,2 na1,
  • Min Peng2 na1,
  • Xuan Shi3,
  • Dahong Yang4,
  • Fang Wang5,
  • Chao Hou6 &
  • …
  • Gelin Xu1,2 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Clinical epigenetics
  • Endocrine system and metabolic diseases

Abstract

The role of the triglyceride-glucose (TyG) index in the progression of diabetic microvascular complication (DMC) multimorbidity remains unclear. Moreover, its interaction with genetic susceptibility to type 2 diabetes (T2D) has not been fully elucidated. This study included T2D patients from the UK Biobank. Primary outcomes were the incidence of first DMC and DMC multimorbidity (including retinopathy, neuropathy, and nephropathy). Multivariable Cox regression and multistate models were used to assess associations between the TyG index and DMC progression. Interaction analyses examined the joint association of the TyG index and T2D genetic risk. A total of 19,512 T2D patients were included, with a median follow-up of 12.9 years. Among them, 5,875 (30.11%) developed a first DMC, and 1,314 (22.37%) progressed to multimorbidity. Each 1-SD increase in TyG was associated with a 19% increased risk of first DMC and a 38% higher risk of multimorbidity. Multistate models showed TyG was a significant predictor of progression from first DMC to multimorbidity (HR = 1.25; 95% CI: 1.15–1.37; P < 0.001), particularly among those with retinopathy (HR = 1.39) or nephropathy (HR = 1.14). A combined association was observed between high TyG index and elevated genetic risk, demonstrating a stepwise increase in risk for DMC onset and progression. In this large, population-based cohort of T2D patients, an elevated TyG index independently predicted both the onset and progression of DMC multimorbidity. This association was particularly evident in patients with retinopathy or nephropathy, with the highest risk observed among individuals with higher genetic risk, highlighting the potential utility of TyG for risk stratification and precision prevention strategies.

Data availability

The datasets generated and/or analyzed during the current study are available in the UK Biobank repository, [https://www.ukbiobank.ac.uk/]

Abbreviations

T2D:

Type 2 diabetes

DMC:

Diabetic microvascular complication

DMCs:

Diabetic microvascular complications

TyG:

Triglyceride-glucose

IR:

Insulin resistance

FBG:

Fasting blood glucose

TG:

Triglyceride

PRS:

Polygenic risk scores

SD:

Standard deviation

HR:

Hazard ratio

HbA1c:

Hyperglycemia

BMI:

Body mass index

HDL-C:

High density lipoprotein cholesterol

TDI:

Townsend deprivation index

LDL-C:

Low-density lipoprotein cholesterol

DBP:

Diastolic blood pressure

SBP:

Systolic blood pressure

References

  1. Zheng, Y., Ley, S. H. & Hu, F. B. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat. Reviews Endocrinol. 14 (2), 88–98 (2018).

    Google Scholar 

  2. Hou, X. et al. Prevalence of diabetic retinopathy and vision-threatening diabetic retinopathy in adults with diabetes in China. Nat. Commun. 14, 4296 (2023).

    Google Scholar 

  3. Global burden of 369 diseases and injuries in 204 countries and territories, In: 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. 396(10258): 1204–1222. (Lancet, 2020).

  4. Horton, W. B. & Barrett, E. J. Microvascular dysfunction in diabetes mellitus and cardiometabolic Disease. Endocr. Rev. 42 (1), 29–55 (2020).

    Google Scholar 

  5. Gregg, E. W., Sattar, N. & Ali, M. K. The changing face of diabetes complications. Lancet Diabetes Endocrinol. 4 (6), 537–547 (2016).

    Google Scholar 

  6. Sacchetta, L. et al. Synergistic effect of chronic kidney disease, neuropathy, and retinopathy on all-cause mortality in type 1 and type 2 diabetes: a 21-year longitudinal study. Cardiovasc. Diabetol. 21 (1), 233 (2022).

    Google Scholar 

  7. Shi, J. et al. mTOR pathway: A key player in diabetic nephropathy progression and therapeutic targets. Genes Dis. 12(2), 101260 (2024).

    Google Scholar 

  8. Sun, D. et al. Molecular mechanisms of coronary microvascular endothelial dysfunction in diabetes mellitus: focus on mitochondrial quality surveillance. Angiogenesis 25 (3), 307–329 (2022).

    Google Scholar 

  9. Navarro-González, D. et al. Triglyceride–glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: the Vascular-Metabolic CUN cohort. Prev. Med. 86, 99–105 (2016).

    Google Scholar 

  10. Gastaldelli, A. Measuring and estimating insulin resistance in clinical and research settings. Obes. (Silver Spring Md). 30 (8), 1549–1563 (2022).

    Google Scholar 

  11. Zhou, Y. et al. The U-Shape relationship between Triglyceride-Glucose index and the risk of diabetic retinopathy among the US Population. J. Personalized Med. 13 (3), 495 (2023).

    Google Scholar 

  12. Tu, Z. et al. Triglyceride glucose index for the detection of diabetic kidney disease and diabetic peripheral neuropathy in hospitalized patients with type 2 Diabetes. Diabetes Therapy. 15 (8), 1799–1810 (2024).

    Google Scholar 

  13. Neelam, K. et al. Association of Triglyceride glucose index with prevalence and incidence of diabetic retinopathy in a Singaporean population. Clin. Ophthalmol. 17, 445–454 (2023).

    Google Scholar 

  14. Huang, Q. et al. Association of baseline and trajectory of triglyceride-glucose index with the incidence of cardiovascular autonomic neuropathy in type 2 diabetes mellitus. Cardiovasc. Diabetol. 24 (1), 66 (2025).

    Google Scholar 

  15. Lyssenko, V. & Vaag, A. Genetics of diabetes-associated microvascular complications. Diabetologia 66 (9), 1601–1613 (2023).

    Google Scholar 

  16. Hodgson, S. et al. Genetic basis of early onset and progression of type 2 diabetes in South Asians. Nat. Med. 31 (1), 323–331 (2025).

    Google Scholar 

  17. Sudlow, C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old Age. PLoS Med. 12 (3), e1001779 (2015).

    Google Scholar 

  18. Zhang, X. et al. Diabetes-Related macrovascular complications are associated with an increased risk of diabetic microvascular complications: A prospective study of 1518 patients with type 1 diabetes and 20 802 patients with type 2 diabetes in the UK Biobank. J. Am. Heart Association. 13 (11), e032626 (2024).

    Google Scholar 

  19. Li, F. R. et al. Microvascular burden and incident heart failure among Middle-Aged and older adults with type 1 or type 2 Diabetes. Diabetes Care. 45 (12), 2999–3006 (2022).

    Google Scholar 

  20. Ge, T. et al. Polygenic prediction via bayesian regression and continuous shrinkage priors. Nat. Commun. 10 (1), 1776 (2019).

    Google Scholar 

  21. Bycroft, C. et al. The UK biobank resource with deep phenotyping and genomic data. Nature 562 (7726), 203–209 (2018).

    Google Scholar 

  22. Jiang, Y. & Lai, X. Association between the triglyceride glucose index, triglyceride-glucose body mass index and diabetic kidney disease in adults with newly diagnosed type 2 diabetes. Front. Med. 11, 1328601 (2024).

    Google Scholar 

  23. Zhang, J. et al. Relation of life’s essential 8 to the genetic predisposition for cardiovascular outcomes and all-cause mortality: results from a National prospective cohort. Eur. J. Prev. Cardiol. 30 (15), 1676–1685 (2023).

    Google Scholar 

  24. Said, M. A., Verweij, N. & van der Harst, P. Associations of combined genetic and lifestyle risks with incident cardiovascular disease and diabetes in the UK biobank Study. JAMA Cardiol. 3 (8), 693–702 (2018).

    Google Scholar 

  25. Zhang, Y. B. et al. Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies. BMJ Clin. Res. 373, n604 (2021).

    Google Scholar 

  26. Luo, H. et al. Long-term exposure to ambient air pollution is a risk factor for trajectory of cardiometabolic multimorbidity: A prospective study in the UK Biobank. EBioMedicine 84, 104282 (2022).

    Google Scholar 

  27. Han, Y. et al. Lifestyle, cardiometabolic disease, and Multimorbidity in a prospective Chinese study. Eur. Heart J. 42 (34), 3374–3384 (2021).

    Google Scholar 

  28. American Diabetes Association. 11. Microvascular complications and foot care: standards of medical care in Diabetes-2020. Diabetes Care. 43 (Suppl 1), S135–S151 (2020).

    Google Scholar 

  29. Li, J. et al. Correlations among diabetic microvascular complications: A systematic review and Meta-analysis. Sci. Rep. 9 (1), 3137 (2019).

    Google Scholar 

  30. Bjerg, L. et al. Effect of duration and burden of microvascular complications on mortality rate in type 1 diabetes: an observational clinical cohort study. Diabetologia 62 (4), 633–643 (2019).

    Google Scholar 

  31. Garofolo, M. et al. Microvascular complications burden (nephropathy, retinopathy and peripheral polyneuropathy) affects risk of major vascular events and all-cause mortality in type 1 diabetes: a 10-year follow-up study. Cardiovasc. Diabetol. 18 (1), 159 (2019).

    Google Scholar 

  32. Liu, L. et al. Association between the triglyceride–glucose index and diabetic nephropathy in patients with type 2 diabetes: A cross-sectional study. J. Diabetes Invest. 12 (4), 557–565 (2021).

    Google Scholar 

  33. Yan, H. et al. Associations between cardiometabolic indices and the risk of diabetic kidney disease in patients with type 2 diabetes. Cardiovasc. Diabetol. 23 (1), 142 (2024).

    Google Scholar 

  34. Wang, H. et al. The threshold effect of triglyceride glucose index on diabetic kidney disease risk in patients with type 2 diabetes: unveiling a non-linear association. Front. Endocrinol. 15, 1411486 (2024).

    Google Scholar 

  35. Valencia, W. M. & Florez, H. How to prevent the microvascular complications of type 2 diabetes beyond glucose control. BMJ 2017, i6505 (2017).

    Google Scholar 

  36. Kearney, K. et al. Hypofibrinolysis in diabetes: a therapeutic target for the reduction of cardiovascular risk. Cardiovasc. Diabetol. 16, 34 (2017).

    Google Scholar 

  37. Paul, S., Ali, A. & Katare, R. Molecular complexities underlying the vascular complications of diabetes mellitus - a comprehensive review. J. Diabetes Complicat. 34 (8), 107613 (2020).

    Google Scholar 

  38. Wu, M. Y. et al. The oxidative stress and mitochondrial dysfunction during the pathogenesis of diabetic retinopathy. Oxidat. Med. Cell. Longev. 2018, 3420187 (2018).

    Google Scholar 

  39. Park, S. et al. Recent advances in the pathogenesis of microvascular complications in diabetes. Arch. Pharm. Res. 42 (3), 252–262 (2019).

    Google Scholar 

  40. Ye, X. et al. Serum triglycerides as a risk factor for cardiovascular diseases in type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. Cardiovasc. Diabetol. 18 (1), 48 (2019).

    Google Scholar 

  41. Dyck, P. J. et al. Longitudinal assessment of diabetic polyneuropathy using a composite score in the Rochester diabetic neuropathy study cohort. Neurology 49 (1), 229–239 (1997).

    Google Scholar 

  42. Dey, I. et al. Diabetic Schwann cells suffer from nerve growth factor and neurotrophin-3 underproduction and poor associability with axons. Glia 61 (12), 1990–1999 (2013).

    Google Scholar 

  43. Feldman, E. L. et al. Diabetic neuropathy. Nat. Reviews Disease Primers. 5 (1), 41 (2019).

    Google Scholar 

  44. Niimi, N. et al. Aldose reductase and the polyol pathway in Schwann cells: old and new problems. Int. J. Mol. Sci. 22 (3), 1031 (2021).

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank the UK Biobank team for their support and contribution to this study (Project ID: 540121).

Funding

The study was supported by Shenzhen High-level Hospital Construction Foundation of No.4004013.

Author information

Author notes
  1. Xiangling Yuan and Min Peng contributed equally to this work.

Authors and Affiliations

  1. Guangxi University of Chinese Medicine, Nanning, 530200, Guangxi, China

    Xiangling Yuan & Gelin Xu

  2. Department of Neurology, Shenzhen Second People’s Hospital and the First, Affiliated Hospital of Shenzhen University, Shenzhen, 518000, Guangdong, China

    Xiangling Yuan, Min Peng & Gelin Xu

  3. Department of Geriatric Medicine, Affiliated Hospital of Medical School, Nanjing Drum Tower Hospital, Nanjing University, 321 Zhongshan Rd, Nanjing, 210008, China

    Xuan Shi

  4. Department of Neurology, Xinqiao Hospital and the Second Affiliated Hospital, Army Medical University, Third Military Medical University), Chongqing, China

    Dahong Yang

  5. Department of Neurology, Shaoxing People’s Hospital, Shaoxing, Zhejiang, China

    Fang Wang

  6. Department of Neurology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China

    Chao Hou

Authors
  1. Xiangling Yuan
    View author publications

    Search author on:PubMed Google Scholar

  2. Min Peng
    View author publications

    Search author on:PubMed Google Scholar

  3. Xuan Shi
    View author publications

    Search author on:PubMed Google Scholar

  4. Dahong Yang
    View author publications

    Search author on:PubMed Google Scholar

  5. Fang Wang
    View author publications

    Search author on:PubMed Google Scholar

  6. Chao Hou
    View author publications

    Search author on:PubMed Google Scholar

  7. Gelin Xu
    View author publications

    Search author on:PubMed Google Scholar

Contributions

XY and MP conceived and designed the study. XY performed the data analysis and drafted the manuscript. XY, MP, XS, DY, FW and CH provided statistical and methodological support. GX and CH contributed to data interpretation and manuscript revision. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Chao Hou or Gelin Xu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

This study was conducted using data from the UK Biobank under application number 540121. Ethical approval was obtained from the North West Multi-Centre Research Ethics Committee.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yuan, X., Peng, M., Shi, X. et al. Triglyceride-glucose index, genetic susceptibility, and trajectory of microvascular multimorbidity in type 2 diabetes. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39777-w

Download citation

  • Received: 24 June 2025

  • Accepted: 06 February 2026

  • Published: 11 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-39777-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Genetic susceptibility
  • Diabetic microvascular multimorbidity
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing