AUTHOR=Wu Na , Zhai Xiangyu , Feng Mofan , Li Jie , Yu Ning , Zhang Fengwei , Li Dong , Wang Jianying , Zhang Lei , Shi Yi , He Guang , Ji Guang , Liu Baocheng TITLE=The gender-specific bidirectional relations between chronic diseases and total bilirubin/urea in the elderly population: A 3-year longitudinal study JOURNAL=Frontiers in Public Health VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.1003505 DOI=10.3389/fpubh.2022.1003505 ISSN=2296-2565 ABSTRACT=

Aging is accompanied by changes in physiology over time, which remains the largest risk of chronic diseases. The aim of this study was to explore the gender-specific bidirectional relations between the risk of chronic diseases and serum traits in a 3-year longitudinal study. A hierarchical non-linear model with random effects was used to assess the temporal patterns of anthropometric and serum traits from 2017 to 2019 among 2,338 participants. To assess the directional effect between the risk of chronic diseases and serum traits, a bivariate cross-lagged panel model (CLPM) was used to estimate the structural relations of repeatedly measured variables at three different time points. Candidate SNPs were analyzed and genotyped in MassARRAY Analyzer 4 platforms. In this study, metabolic syndrome (MS) score increased with aging in females, whereas the fatty liver disease (FLD) index decreased with aging in males; the MS score was negatively correlated with TB in females, and FLD index was positively related to urea in males; CLPM showed that the MS score predicted total bilirubin (TB) in females, and urea predicted the FLD index in males. Additionally, rs2292354 in G protein-coupled receptor kinase interactor 2 (GIT2) was associated with the MS score and TB in aged females. Our study suggests the potential gender-specific causal associations between development in MS and increase in TB level in females, and rise in urea level and improved FLD index in males. The SNP rs2292354 we investigated might be a biomarker for predicting MS in the elderly Chinese Han population.