| Title: | Glycaemic variability underlies myocyte dysfunction and myocardial injury risk in diabetes |
| Journal: | Nature Communications |
| Published: | 18 Apr 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42000722/ |
| DOI: | https://doi.org/10.1038/s41467-026-71809-x |
| URL: | https://www.nature.com/articles/s41467-026-71809-x_reference.pdf |
Publication 20656
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Abstract
Heart disease is the leading cause of morbidity and mortality in individuals with diabetes, due largely to risks associated with ischaemic injuries such as myocardial infarction (MI). We use human population genetic data to demonstrate that classical cardiovascular disease risk biomarkers, including common measures of hyperglycaemia, do not fully account for the increased risk of post-MI mortality in patients with diabetes. This study therefore systematically evaluates glycaemic stress underpinning cardiovascular risk in diabetes. Here, we show using in vivo studies in adult male mice and in vitro models that glycaemic variability, rather than sustained hyperglycaemia alone, is a key risk factor for cardiomyocyte dysfunction and increased susceptibility to myocardial injury in diabetes. We further demonstrate that patient plasma assays can elucidate the predictive potential of glycaemic variability as a primary contributor to cardiomyocyte dysfunction and subclinical cardiac injury in diabetes. These findings provide preclinical models for mechanistic and drug discovery studies and inform strategies for managing cardiovascular outcomes in patients with diabetes.</p>
12 Keywords
- Animals
- Biomarkers
- Blood Glucose
- Diabetes Mellitus, Type 2
- Humans
- Hyperglycemia
- Male
- Mice
- Mice, Inbred C57BL
- Myocardial Infarction
- Myocytes, Cardiac
- Risk Factors
25 Authors
- Yuanzhao Cao
- Meredith A. Redd
- Jennifer E. Outhwaite
- Dalia Mizikovsky
- Woo Jun Shim
- Chen Fang
- Courtney Vedelago
- Clarissa Tan
- Zhixuan Wu
- Dara Daygon
- Terra Stark
- Robin Palfreyman
- Han Sheng Chiu
- Ulrich Thomas
- Elena Dragicevic
- Julian D. J. Sng
- Natalie J. Saez
- Helen L. Barrett
- Emily S. Dorey
- Glenn F. King
- Alain Wuethrich
- Matt Trau
- Sonia Shah
- Kirsty R. Short
- Nathan J. Palpant
1 Application
| Application ID | Title |
|---|---|
| 899824 | Advancing complex trait prediction and genetic understanding using genome sequence data |
Enabling scientific discoveries that improve human health