2025年5月6日
Energy landscape analysis of health checkup data clarified multiple pathways to diabetes development in obese and non-obese subjects
Frontiers in Endocrinology
- 巻
- 16
- 号
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.3389/fendo.2025.1576431
- 出版者・発行元
- Frontiers Media SA
Aims
To clarify the pathways from a healthy state to the diabetes onset via pre-disease states, we applied energy landscape analysis (ELA) to Specific Health Checkup data in Japan.
Methods
This retrospective and observational cohort study analyzed data from 4,928 males aged 56.0 ± 3.2 years, including 242 individuals with diabetes, over a period of 5.26 ± 3.21 years. A total of 22,326 records were examined using six features: hemoglobin A1c, plasma glucose, high-density lipoprotein-cholesterol, body mass index (BMI), uric acid, and alanine aminotransferase. ELA was also applied to subdata from the 242 individuals with diabetes.
Results
ELA revealed three stable states: healthy, intermediate, and unhealthy (pre-diabetes) states. The intermediate state was characterized by obesity. Obese individuals with BMI ≥ 25 kg/m2 (n = 1,460) preferred a pathway via the intermediate state, whereas non-obese individuals with BMI < 25 kg/m2 (n = 3,468) preferred to transit directly to the unhealthy state. There was a significant difference between the preferences of the two groups (p = 0.0085, chi-squared test). Two distinct pathways were also observed for obese and non-obese individuals with diabetes.
Conclusions
We demonstrated that ELA could indicate different pathways of diabetes development in obese and non-obese individuals in a data-driven manner. These insights could inform more targeted diabetes prevention measures, such as reducing visceral fat in obese individuals and protecting beta-cells in non-obese individuals.
To clarify the pathways from a healthy state to the diabetes onset via pre-disease states, we applied energy landscape analysis (ELA) to Specific Health Checkup data in Japan.
Methods
This retrospective and observational cohort study analyzed data from 4,928 males aged 56.0 ± 3.2 years, including 242 individuals with diabetes, over a period of 5.26 ± 3.21 years. A total of 22,326 records were examined using six features: hemoglobin A1c, plasma glucose, high-density lipoprotein-cholesterol, body mass index (BMI), uric acid, and alanine aminotransferase. ELA was also applied to subdata from the 242 individuals with diabetes.
Results
ELA revealed three stable states: healthy, intermediate, and unhealthy (pre-diabetes) states. The intermediate state was characterized by obesity. Obese individuals with BMI ≥ 25 kg/m2 (n = 1,460) preferred a pathway via the intermediate state, whereas non-obese individuals with BMI < 25 kg/m2 (n = 3,468) preferred to transit directly to the unhealthy state. There was a significant difference between the preferences of the two groups (p = 0.0085, chi-squared test). Two distinct pathways were also observed for obese and non-obese individuals with diabetes.
Conclusions
We demonstrated that ELA could indicate different pathways of diabetes development in obese and non-obese individuals in a data-driven manner. These insights could inform more targeted diabetes prevention measures, such as reducing visceral fat in obese individuals and protecting beta-cells in non-obese individuals.
- リンク情報
- ID情報
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- DOI : 10.3389/fendo.2025.1576431
- eISSN : 1664-2392