The Circadian Rhythm Regulates the Hepato-ovarian Axis Linking Polycystic Ovary Syndrome and Non-alcoholic Fatty Liver Disease

被引:0
作者
Lan, Yibing [1 ,2 ]
Jin, Bihui [3 ,4 ]
Fan, Yuhang [5 ]
Huang, Yizhou [1 ,2 ]
Zhou, Jianhong [1 ,2 ]
机构
[1] Zhejiang Univ, Womens Hosp, Dept Gynecol, Sch Med, Hangzhou, Peoples R China
[2] Zhejiang Prov Clin Res Ctr Obstet & Gynecol, Hangzhou, Peoples R China
[3] Zhejiang Prov Peoples Hosp, Affiliated Peoples Hosp, Hangzhou Med Coll, Dept Reprod Endocrinol, Hangzhou, Peoples R China
[4] Key Lab Endocrine Gland Dis Zhejiang Prov, Hangzhou, Peoples R China
[5] Zhejiang Chinese Med Univ, Hangzhou, Peoples R China
关键词
Polycystic ovary syndrome; Non-alcoholic fatty liver disease; Circadian rhythm; Bioinformatics; Inflammation mediators; INSULIN-RESISTANCE; GENE-EXPRESSION; CLOCK; INFLAMMATION; PREVALENCE; CRITERIA; GLUCOSE; SYSTEM; EGR-1;
D O I
10.1007/s10528-024-11010-1
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
This study aimed to identify shared gene expression related to circadian rhythm disruption in polycystic ovary syndrome (PCOS) and non-alcoholic fatty liver disease (NAFLD) to discover common diagnostic biomarkers. Visceral fat RNA samples were collected from 12 PCOS and 14 non-PCOS patients, a sample size representing the clinical situation and sufficient to capture PCOS gene expression profiles. Along with liver transcriptome profiles from NAFLD patients, these data were analyzed to identify crosstalk circadian rhythm-related genes (CRRGs) between the diseases. Single-sample and single-gene gene set enrichment analyses explored immune infiltration and pathways associated with CRRGs. Diagnostic biomarkers were identified using a random forest algorithm and validated through nomograms and a mouse model. Seven crosstalk CRRGs (FOS, ACHE, FOSB, EGR1, NR4A1, DUSP1, and EGR3) were associated with clinical features, immunoinflammatory microenvironment, and metabolic pathways in both diseases. EGR1, DUSP1, and NR4A1 were identified as diagnostic biomarkers, exhibiting robust diagnostic capacity (AUC = 0.7679 for PCOS, AUG = 0.9981 for NAFLD). Nomogram validation showed excellent calibration, and independent datasets confirmed their discriminatory ability (AUC = 0.6528 for PCOS, AUC = 0.8275 for NAFLD). Additionally, ceRNA networks and androgen receptor binding sites were identified, suggesting their regulatory roles. Mouse model validation confirmed significant downregulation of EGR1, DUSP1, and NR4A1 in liver tissues, consistent with sequencing data. This study identifies crosstalk CRRGs and diagnostic biomarkers shared between PCOS and NAFLD, highlighting their roles in immune and metabolic dysregulation. These biomarkers offer the potential for improving diagnosis and guiding targeted treatments for both diseases.
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页数:24
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