Connections between body composition and dysregulation of islet α- and β-cells in type 2 diabetes

Jia-Xi Miao; Jia-Ping Xu; Rui Wang; Yu-Xian Xu; Feng Xu; Chun-Hua Wang; Chao Yu; Dong-Mei Zhang; Jian-Bin Su

doi:10.1186/s13098-023-01250-3

Connections between body composition and dysregulation of islet α- and β-cells in type 2 diabetes

Diabetol Metab Syndr. 2024 Jan 9;16(1):11. doi: 10.1186/s13098-023-01250-3.

Authors

Jia-Xi Miao¹, Jia-Ping Xu¹, Rui Wang¹, Yu-Xian Xu¹, Feng Xu¹, Chun-Hua Wang¹, Chao Yu², Dong-Mei Zhang³, Jian-Bin Su⁴

Affiliations

¹ Department of Endocrinology, Affiliated Hospital 2 of Nantong University, and First People's Hospital of Nantong, No.666 Shengli Road, Nantong, 226001, China.
² Department of Clinical Laboratory, Affiliated Hospital 2 of Nantong University, and First People's Hospital of Nantong, No.666 Shengli Road, Nantong, 226001, China.
³ Medical Research Center, Affiliated Hospital 2 of Nantong University, and First People's Hospital of Nantong, No.666 Shengli Road, Nantong, 226001, China.
⁴ Department of Endocrinology, Affiliated Hospital 2 of Nantong University, and First People's Hospital of Nantong, No.666 Shengli Road, Nantong, 226001, China. sujbzjx@ntu.edu.cn.

Abstract

Background: Accompanying islet α- and β-cell dysregulation in type 2 diabetes (T2D) at the microscopic scale, alterations in body composition at the macroscopic scale may affect the pathogenesis of T2D. However, the connections between body composition and islet α-cell and β-cell functions in T2D have not been thoroughly explored.

Methods: For this cross-sectional study, we recruited a total of 729 Chinese Han patients with T2D in a consecutive manner. Dual-energy X-ray absorptiometry (DXA) was used to measure body composition, which included total bone-free mass, total fat and lean mass, trunk fat and lean mass and limb fat and lean mass. Every patient underwent an oral glucose tolerance test to simultaneously detect glucose, C-peptide and glucagon. The indices of islet α-cell function included fasting glucagon levels and the area under the curve of glucagon after a challenge (AUC_glucagon), while the indices of β-cell function included the insulin sensitivity index derived from C-peptide (ISI_C-peptide) and the area under the curve of C-peptide after a challenge (AUC_C-peptide).

Results: Among all patients, fat mass, especially trunk fat mass, was significantly correlated with ISI_C-peptide and AUC_C-peptide levels (r = - 0.330 and 0.317, respectively, p < 0.001), while lean mass, especially limb lean mass, was significantly correlated with fasting glucagon and AUC_glucagon levels (r = - 0.196 and - 0.214, respectively, p < 0.001). Moreover, after adjusting for other relevant variables via multivariate linear regression analysis, increased trunk fat mass was independently associated with decreased ISI_C-peptide (β = - 0.247, t = - 3.628, p < 0.001, partial R² = 10.9%) and increased AUC_C-peptide (β = 0.229, t = 3.581, p < 0.001, partial R² = 8.2%), while decreased limb lean mass was independently associated with increased fasting glucagon (β = - 0.226, t = - 2.127, p = 0.034, partial R² = 3.8%) and increased AUC_glucagon (β = - 0.218, t = - 2.050, p = 0.041, partial R² = 2.3%). Additionally, when separate analyses were performed with the same concept for both sexes, we found that increased trunk fat mass was still independently associated with decreased ISI_C-peptide and increased AUC_C-peptide, while decreased limb lean mass was still independently associated with increased fasting glucagon and AUC_glucagon.

Conclusions: Increased trunk fat mass may partly account for decreased insulin sensitivity and increased insulin secretion, while decreased limb lean mass may be connected to increased fasting glucagon and postprandial glucagon secretion.

Keywords: Body composition; C-peptide; Glucagon; Type 2 diabetes.

Abstract

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