Identification of pre-diabetes subphenotypes for type 2 diabetes, related vascular complications and mortality
2
Issued Date
2025-06-09
Resource Type
eISSN
20524897
Scopus ID
2-s2.0-105008082139
Journal Title
BMJ Open Diabetes Research and Care
Volume
13
Issue
3
Rights Holder(s)
SCOPUS
Bibliographic Citation
BMJ Open Diabetes Research and Care Vol.13 No.3 (2025)
Suggested Citation
Washirasaksiri C., Borrisut N., Lapinee V., Sitasuwan T., Tinmanee R., Kositamongkol C., Ariyakunaphan P., Tangjittipokin W., Plengvidhya N., Srivanichakorn W. Identification of pre-diabetes subphenotypes for type 2 diabetes, related vascular complications and mortality. BMJ Open Diabetes Research and Care Vol.13 No.3 (2025). doi:10.1136/bmjdrc-2024-004803 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/110813
Title
Identification of pre-diabetes subphenotypes for type 2 diabetes, related vascular complications and mortality
Author's Affiliation
Corresponding Author(s)
Other Contributor(s)
Abstract
Introduction Pre-diabetes comprises diverse subphenotypes linked to varying complications, type 2 diabetes, and mortality outcomes. This study aimed to explore these outcomes across different pre-diabetes subphenotypes. Research design and methods The dataset included adults without type 2 diabetes with baseline HbA1c and fasting plasma glucose (FPG) measurements from Siriraj Hospital, Bangkok, Thailand. The participants were classified into six subphenotypes via the k-means clustering method on the basis of age, body mass index, FPG, HbA1c, high-density lipoprotein cholesterol and alanine aminotransferase levels. The incidences of type 2 diabetes, long-term vascular complications and mortality were compared among subphenotypes over a median follow-up of 8.8 years, employing Kaplan-Meier curves and Cox regression analysis adjusted for sex, statin use and hypertension status. Results Among the 4915 participants (mean age 60.1±10.1 years; 54.6% female), six clusters emerged: cluster 1, low risk (n=650; 13.2%); cluster 2, mild dysglycemia elderly (n=791; 16.1%); cluster 3, severe dysglycemia obese (n=1127; 22.9%); cluster 4, mild dysglycemia obese (n=963; 19.7%); cluster 5, severe dysmetabolic obese (n=337; 6.9%); and cluster 6, severe dysglycemia elderly (n=1042; 21.2%). Clusters were classified into diabetes risk subgroups: low risk (clusters 1 and 4) and high risk (clusters 3 and 5). Cluster 6 exhibited the highest risk, with significantly increased incidences of macrovascular complications (adjusted HR 2.22, 1.51-3.27) and type 2 diabetes (1.73, 1.42-2.12). In contrast, cluster 4 demonstrated the lowest risk, with significantly decreased incidences of new chronic kidney disease (0.65, 0.44-0.96), microvascular complications (0.62, 0.43-0.89) and mortality (0.25, 0.10-0.63). Conclusions Our pre-diabetes phenotyping approach effectively provides valuable insights into the risk of type 2 diabetes, vascular complications and mortality in individuals with pre-diabetes. Those with high-risk phenotypes should be prioritized for type 2 diabetes and cardiovascular interventions to mitigate risks.