已发表论文

基因表达特征综合生物信息分析及中医体质分析揭示非酒精性脂肪肝脂肪变性的代谢特征及靶点

 

Authors Qiao C, Gu C, Wen S , He Y, Yang S, Feng X, Zeng Y

Received 21 July 2023

Accepted for publication 30 September 2023

Published 6 October 2023 Volume 2023:15 Pages 165—183

DOI https://doi.org/10.2147/HMER.S428161

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Gerry Lake-Bakaar

Purpose: In this study, our primary aim is to analyze the genetic expression feature and analyze specific Traditional Chinese medicine (TCM) constitution distribution in non-alcoholic fatty liver disease (NAFLD) and reveal the metabolic characteristic of NAFLD.
Materials and Methods: For revealing genetic features, we obtained the gene expression data from the Gene Expression Omnibus (GEO) database of the National Center for Biotechnology Information (NCBI). The genetic data on NAFLD were analyzed by identifying differentially expressed genes (DEGs), associated pathways, co-expressed genetic networks, and gene set enrichment function. Concurrently, we assessed specific constitution distributions among local NAFLD patients through established TCM constitution models and determined the independent variable, including specific constitution to the NAFLD via the regression analyses.
Results: The analyses on GEO datasets showed that simple steatosis in NAFLD is strongly associated with HOMA-insulin resistance (HOMA-IR). Analyses of GEO datasets revealed significantly altered genetic expression profiles between NAFLD and normal populations. For TCM constitution analyses, we demonstrated a decline in yin-yang harmony (YYH) and yang-asthenia (YAAC) constitution, whereas there was an increase in qi-stagnation (QSC) and phlegm-dampness (PDC) in NAFLD. The binary logistic regression analysis indicated that besides other metabolic parameters, YYH, qi asthenia (QAC), YYAC, and yin-asthenia (YAC) were the independent variables of NAFLD, while YAC was the independent variables of T2D. The multilinear regression analyses suggested that NAFLD, DM, BMI, waist, TC, TG, hypertension, ALT, AST, and YAC were the significant determinators of the FPG.
Conclusion: This study presents a relatively comprehensive metabolic profile in steatosis of NAFLD, revealed by significant genetic expression feature alterations and different TCM constitution distribution in NAFLD. Through this method, the study intends to associate the genetic feature with the phenotype of TCM constitution. The results could be applied to assist integrative medicine research in exploring the appropriate personalized approaches for NAFLD.
Keywords: NAFLD, T2D, bioinformatics, TCM constitution