Body Composition Phenotypes and Their Metabolic Associations in Treatment-Naïve Patients With Newly Diagnosed Type 2 Diabetes: A DXA-Based Cluster Analysis.
- 1Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
- 2Department of Endocrinology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Abstract
Background and aims
We characterized body-composition heterogeneity in treatment-naive type 2 diabetes (T2DM) using dual-energy X-ray absorptiometry (DXA), and assessed whether cluster-metabolic associations persisted after accounting for sex-related body-composition differences.Methods
K-means clustering of 50 DXA-derived body-composition variables classified 185 treatment-naive T2DM patients. Variance decomposition, sex-stratified analyses, sex-stratified clustering, sex-specific standardization clustering and multiple imputation (20 datasets) addressed sex confounding and missing data.Results
Four exploratory body-composition clusters were identified: Low Fat-Low Muscle, Male-Predominant Central Obesity (98.6% male), Female-Predominant Low-Muscle High-Adiposity (98.0% female) and High Fat-High Muscle. Two clusters showed strong sex predominance; sex-specific normalization reduced sex-cluster dependence while preserving metabolic associations. In multiple-imputation-adjusted models, Clusters 2 and 4 had markedly higher MASLD odds (OR = 9.69 and 8.55, respectively), while Cluster 4 had lower osteoporosis (OR = 0.16) and higher hyperuricemia (OR = 6.36) odds versus Cluster 1. Bone turnover markers, diabetic retinopathy and diabetic kidney disease showed no significant associations.Conclusions
DXA-based body-composition clusters are associated with distinct metabolic and comorbidity profiles-particularly MASLD, osteoporosis and hyperuricemia-that persisted after sex-specific standardization and multiple imputation. Given the sex-cluster overlap and modest silhouette width, these findings are hypothesis-generating and require prospective validation.
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BibTeX
@article{zhang2026body,
title = {{Body Composition Phenotypes and Their Metabolic Associations in Treatment-Naïve Patients With Newly Diagnosed Type 2 Diabetes: A DXA-Based Cluster Analysis.}},
author = {Xintong Zhang and Rui Zhang and Tao Jiang},
journal = {Endocrinology, diabetes \& metabolism},
year = {2026},
month = oct,
doi = {10.1002/edm2.70366},
url = {https://europepmc.org/article/MED/42897745},
note = {CC BY},
}
RIS
TY - JOUR
TI - Body Composition Phenotypes and Their Metabolic Associations in Treatment-Naïve Patients With Newly Diagnosed Type 2 Diabetes: A DXA-Based Cluster Analysis.
AU - Xintong Zhang
AU - Rui Zhang
AU - Tao Jiang
PY - 2026
DA - 2026/10/30
JO - Endocrinology, diabetes & metabolism
DO - 10.1002/edm2.70366
UR - https://europepmc.org/article/MED/42897745
AB - Background and aims We characterized body-composition heterogeneity in treatment-naive type 2 diabetes (T2DM) using dual-energy X-ray absorptiometry (DXA), and assessed whether cluster-metabolic associations persisted after accounting for sex-related body-composition differences.Methods K-means clustering of 50 DXA-derived body-composition variables classified 185 treatment-naive T2DM patients. Variance decomposition, sex-stratified analyses, sex-stratified clustering, sex-specific standardization clustering and multiple imputation (20 datasets) addressed sex confounding and missing data.Results Four exploratory body-composition clusters were identified: Low Fat-Low Muscle, Male-Predominant Central Obesity (98.6% male), Female-Predominant Low-Muscle High-Adiposity (98.0% female) and High Fat-High Muscle. Two clusters showed strong sex predominance; sex-specific normalization reduced sex-cluster dependence while preserving metabolic associations. In multiple-imputation-adjusted models, Clusters 2 and 4 had markedly higher MASLD odds (OR = 9.69 and 8.55, respectively), while Cluster 4 had lower osteoporosis (OR = 0.16) and higher hyperuricemia (OR = 6.36) odds versus Cluster 1. Bone turnover markers, diabetic retinopathy and diabetic kidney disease showed no significant associations.Conclusions DXA-based body-composition clusters are associated with distinct metabolic and comorbidity profiles-particularly MASLD, osteoporosis and hyperuricemia-that persisted after sex-specific standardization and multiple imputation. Given the sex-cluster overlap and modest silhouette width, these findings are hypothesis-generating and require prospective validation.
SN - 2398-9238
ER -