A bidirectional link between metabolic syndrome and elevation in alanine aminotransferase in elderly female: a longitudinal community study

Na Wu; Mofan Feng; Hanhua Zhao; Nan Tang; Yalan Xiong; Xinyu Shi; Dong Li; Hualing Song; Shengfu You; Jianying Wang; Lei Zhang; Guang Ji; Baocheng Liu

doi:10.3389/fcvm.2023.1156123

A bidirectional link between metabolic syndrome and elevation in alanine aminotransferase in elderly female: a longitudinal community study

Front Cardiovasc Med. 2023 Jun 20:10:1156123. doi: 10.3389/fcvm.2023.1156123. eCollection 2023.

Authors

Na Wu^#¹, Mofan Feng^#², Hanhua Zhao^#³, Nan Tang¹, Yalan Xiong¹, Xinyu Shi¹, Dong Li⁴, Hualing Song¹, Shengfu You⁵, Jianying Wang¹, Lei Zhang¹, Guang Ji⁵, Baocheng Liu¹

Affiliations

¹ Shanghai Innovation Center of Traditional Chinese Medicine Health Service, School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
² Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.
³ Department of Sport Science, College of Education, Zhejiang University, Hangzhou, China.
⁴ Zhangjiang Community Health Service Center of Pudong New District, Shanghai, China.
⁵ Institute of Digestive Diseases, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

^# Contributed equally.

Abstract

Pre-obesity, as a significant risk factor for the progression of metabolic syndrome (MS), has become a prevalent public health threat globally. In this three-year longitudinal study of pre-obese women at baseline, the goal was to clarify the female-specific bidirectional relationship between the risk of MS and blood alanine aminotransferase. In this manuscript, the MS score was determined using the following equation: MS score = 2*waist/height + fasting glucose/5.6 + TG/1.7 + SBP/130-HDL/1.02 for men and 1.28 for women, which is highly related to the risk of MS. With 2,338 participants, a hierarchical nonlinear model with random effects was utilized to analyze the temporal trends of serum characteristics from 2017 to 2019. A bivariate cross-lagged panel model (CLPM) was employed to estimate the structural relations of frequently measured variables at three different time points to determine the directionality of the relationship between the risk of MS and serum characteristics. MassARRAY Analyzer 4 platforms were used to evaluate and genotype candidate SNPs. In this study, the MS score only rose with age in females; it was positively correlated with serum alanine aminotransferase (ALT) in females; the CLPM revealed that the MS score in 2017 predicted ALT in 2018 (β = 0.066, p < 0.001); and ALT in 2018 predicted an MS score in 2019 (β = 0.037, p < 0.050); both relationships were seen in females. Additionally, the MS score in elderly females with NAFLD was related to the rs295 in the lipoprotein lipase (LPL) gene (p = 0.042). Our work showed that there may be female-specific causal correlations between elevated ALT and risk of MS and that the polymorphism rs295 in LPL may serve as a marker for the prognosis of MS. The genetic roles of rs295 in the LPL gene in the onset of MS and the development of ALT in the elderly Chinese Han population are thus provided by this, offering one potential mechanism.

Keywords: alanine aminotransferase; bidirectional relation; elderly population; longitudinal study; metabolic syndrome.

Grants and funding

This study was supported by China Postdoctoral Science Foundation, No.72 General Fund, 2022 (2022M722164); Shanghai 2023 “Science and Technology Innovation Action Plan” Qi Ming Xing Cultivation (Yang Fan Project, 23YF1447700); Shanghai Health Commission for Traditional Chinese Medicine Research (2022QN014); Three-year action plan for Shanghai (project number: ZY (2021–2023)-0211), National Natural Science Foundation of China (81973730), Local Colleges Faculty Constitution of Shanghai MSTC 2022 (22010504300), Shanghai Collaborative Innovation Center for Chronic Disease Prevention and Health Services (2021 Science and Technology 02–37).