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Jing Ni

Publications and source records attributed to Jing Ni.

2 recordsLinked to original sources

Multi-omics uncovers the pleiotropic genetic mechanisms linking MASLD and cardiometabolic syndromes.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular-kidney-metabolic (CKM) syndrome are interrelated conditions with shared pathophysiological features; however, the genetic architecture underlying their relationship has not been fully elucidated. Deciphering this shared genetic basis holds promise for advancing mechanistic insights and therapeutic discovery. METHODS: We performed an integrated genome-wide cross-trait analysis using GWAS summary statistics for MASLD and 38 CKM traits. Our analysis estimated genetic correlations, inferred causal relationships, and identified pleiotropic variants. Candidate causal genes and druggable targets were subsequently prioritized through integrating multi-omics data. RESULTS: MASLD exhibited significant genetic correlations with 16 CKM traits, especially metabolic and cardiovascular conditions. Bidirectional causal relationships were observed between MASLD and T2D, adiposity, and lipid traits. We discovered 116 pleiotropic loci, including 65 shared causal variants such as rs429358 near APOE, which exerted influence across multiple traits. Gene-based analyses prioritized 152 unique candidate pleiotropic genes, enriched in lipid and cholesterol metabolism, and highly expressed in the liver, adipose, and immune-related cell types, such as macrophages and endothelial cells. Multi-omics integration validated 131 genes using eQTL and pQTL data from multiple tissues and cohorts. Notably, FTO and APOE emerged as central pleiotropic hubs, and druggability evaluation highlighted APOE, LPL, PPARG, and GPBAR1 as established therapeutic targets for metabolic diseases. CONCLUSION: This study provides a comprehensive map of the shared genetic architecture between MASLD and CKM syndrome, reveals novel causal genes and repurposable drug targets, and offers insights into precision medicine approaches for cardiometabolic and liver diseases.

Humans

TCGA molecular subtypes in endometriosis-associated ovarian cancer: a systematic review and meta-analysis.

BACKGROUND: Endometriosis-associated ovarian cancer (EAOC) mainly includes endometrioid ovarian cancer (ENOC) and clear cell ovarian cancer (CCOC). The Cancer Genome Atlas (TCGA) revealed four molecular subtypes of endometrial cancer (EC) in 2013, which have been proven pivotal in the diagnostic, prognostic and therapeutic domains of EC. Existing evidence indicates that EC and EAOC molecular analysis have similar significance. This review aims to investigate the distribution, staging and prognostic characteristics of molecular subtypes in EAOC. METHODS: PubMed, Embase and Web of Science were systematically searched from January 2013 to December 2023 using predefined keywords. Patient characteristics, including stage and prognostic characteristics, were extracted from the selected studies. Data analysis was carried out using Stata 14MP. RESULTS: A total of 6 studies involving 1,133 patients with ENOC and 4 studies comprising 377 patients with CCOC were included. ENOC had a higher frequency of the POLE mutation (POLEmut) subtype (odds ratio (OR) = 2.29, 95% CI: 1.03-5.11, p = 0.043) and the mismatch repair deficient (MMRd) subtype (OR = 3.54, 95% CI: 2.05-6.11, p = 0.000) than CCOC; ENOC had a lower frequency of the no specific molecular profile (NSMP) subtype (OR = 0.55, 95% CI: 0.41-0.73, p = 0.000) and the p53 abnormal (p53abn) subtype (OR = 0.97, 95% CI: 0.67-1.42, p = 0.893). The hazard ratios (HR) of the p53abn subtype in ENOC were disease-free survival (DFS) (HR = 3.25, 95% CI: 1.46-7.21, p = 0.004) and progression-free survival (PFS) (HR = 4.11, 95% CI: 2.86-5.92, p = 0.000). The DFS of the p53abn subtype in CCOC was calculated (HR = 5.52, 95% CI: 3.43-8.90, p = 0.000). CONCLUSION: The TCGA subtypes of EC may exhibit similarities in prognosis between ENOC and CCOC.

Humans