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Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study
Open accessAbstract
Introduction: Type 2 diabetes is characterized by considerable heterogeneity in its etiopathogenesis and clinical presentation. We aimed to identify clusters of type 2 diabetes in Asian Indians and to look at the clinical implications and outcomes of this clustering. Research design and methods: From a network of 50 diabetes centers across nine states of India, we selected 19 084 individuals with type 2 diabetes (aged 10–97 years) with diabetes duration of less than 5 years at the time of first clinic visit and performed k-means clustering using the following variables: age at diagnosis, body mass index, waist circumference, glycated hemoglobin, serum triglycerides, serum high-density lipoprotein cholesterol and C peptide (fasting and stimulated). This was then validated in a national epidemiological data set of representative individuals from 15 states across India. Results: We identified four clusters of patients, differing in phenotypic characteristics as well as disease outcomes: cluster 1 (Severe Insulin Deficient Diabetes, SIDD), cluster 2 (Insulin Resistant Obese Diabetes, IROD), cluster 3 (Combined Insulin Resistant and Deficient Diabetes, CIRDD) and cluster 4 (Mild Age-Related Diabetes, MARD). While SIDD and MARD are similar to clusters reported in other populations, IROD and CIRDD are novel clusters. Cox proportional hazards showed that SIDD had the highest hazards for developing retinopathy, followed by CIRDD, while CIRDD had the highest hazards for kidney disease. Conclusions: Compared with previously reported clustering, we show two novel subgroups of type 2 diabetes in the Asian Indian population with important implications for prognosis and management. The coexistence of insulin deficiency and insulin resistance seems to be peculiar to the Asian Indian population and is associated with an increased risk of microvascular complications.
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Cited by
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Phenotypic and genetic classification of diabetes
Deutsch, A. J., Ahlqvist, E., & Udler, M. S. (2022) · Diabetologia · doi:10.1007/s00125-022-05769-4 · Cited by 108
Artificial intelligence for diabetes care: current and future prospects
Sheng, B., Pushpanathan, K., Guan, Z., Lim, Q. H., Lim, Z. W., Yew, S. M. E., Goh, J. H. L., Bee, Y. M., Sabanayagam, C., Sevdalis, N., et al. (2024) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(24)00154-2 · Cited by 106
Pigeyre, M., Hess, S., Gomez, M. F., Asplund, O., Groop, L., Paré, G., & Gerstein, H. (2022) · Diabetologia · doi:10.1007/s00125-021-05567-4 · Cited by 79
Dwibedi, C., Ekström, O., Brandt, J., Adiels, M., Franzén, S., Abrahamsson, B., & Rosengren, A. H. (2024) · Nature Metabolism · doi:10.1038/s42255-023-00943-3 · Cited by 40
Metadata
- Authors
- Anjana, R. M., Baskar, V., Nair, A. T. N., Jebarani, S., Siddiqui, M. K., Pradeepa, R., Unnikrishnan, R., Palmer, C., Pearson, E., & Mohan, V.
- Venue
- BMJ Open Diabetes Research & Care
- Publisher
- BMJ
- Published
- 2020-08
- Volume
- 8
- Issue
- 1
- Pages
- e001506
- ISSN
- 2052-4897 (ISSN-L)
- OpenAlex
- W3072343284
- Cited by
- 224
- References
- 0
- FWCI
- 17.51
- Type
- journal article
- Language
- en
- Open access
- gold
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- Anjana, R. M., Baskar, V., Nair, A. T. N., Jebarani, S., Siddiqui, M. K., Pradeepa, R., Unnikrishnan, R., Palmer, C., Pearson, E., & Mohan, V. (2020). Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study. BMJ Open Diabetes Research & Care. https://doi.org/10.1136/bmjdrc-2020-001506
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