诊断前血浆代谢物与肝细胞癌相关:一项前瞻性分析

Robert M Wilechansky, Prasanna K Challa, Xijing Han, Xinwei Hua, Alisa K Manning, Kathleen E Corey, Raymond T Chung, Wei Zheng, Andrew T Chan, Tracey G Simon
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引用次数: 0

摘要

尽管肝细胞癌(HCC)在弱势人群中的发病率不断上升,但缺乏准确的早期检测工具。我们的目的是在不同人群中调查诊断前血浆代谢物与HCC发生率之间的关系。在南方社区队列研究(SCCS)的一项前瞻性巢式病例对照研究中,我们对150例HCC事件(中位诊断时间为7.9年)和100例肝硬化对照进行了诊断前液相色谱-质谱代谢组学分析。Logistic回归评估了代谢物与HCC风险的关系。代谢物集富集分析确定富集途径,并使用随机森林分类器建立风险分类模型。候选代谢物在UK Biobank中得到验证(N=12例HCC病例和24例肝硬化对照)。在logistic回归分析中,七种代谢物与HCC的发生有关(Meff p
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediagnostic Plasma Metabolites Are Associated with Incident Hepatocellular Carcinoma: A Prospective Analysis.

Despite increasing incidence of hepatocellular carcinoma (HCC) in vulnerable populations, accurate early detection tools are lacking. We aimed to investigate the associations between prediagnostic plasma metabolites and incident HCC in a diverse population. In a prospective, nested case-control study within the Southern Community Cohort Study, we conducted prediagnostic LC/MS metabolomic profiling in 150 incident HCC cases (median time to diagnosis, 7.9 years) and 100 controls with cirrhosis. Logistic regression assessed metabolite associations with HCC risk. Metabolite set enrichment analysis identified enriched pathways, and a random forest classifier was used for risk classification models. Candidate metabolites were validated in the UK Biobank (N = 12 incident HCC cases and 24 cirrhosis controls). In logistic regression analysis, seven metabolites were associated with incident HCC (MeffP < 0.0004), including N-acetylmethionine (OR = 0.46; 95% confidence interval, 0.31-0.66). Multiple pathways were enriched in HCC, including histidine and CoA metabolism (FDR P < 0.001). The random forest classifier identified 10 metabolites for inclusion in HCC risk classification models, which improved HCC risk classification compared with clinical covariates alone (AUC = 0.66 for covariates vs. 0.88 for 10 metabolites plus covariates; P < 0.0001). Findings were consistent in the UK Biobank (AUC = 0.72 for covariates vs. 0.88 for four analogous metabolites plus covariates; P = 0.04), assessed via nuclear magnetic resonance spectroscopy. Prediagnostic metabolites, primarily amino acid and sphingolipid derivatives, are associated with HCC risk and improve HCC risk classification beyond clinical covariates. These metabolite profiles, detectable years before diagnosis, could serve as early biomarkers for HCC detection and risk stratification if validated in larger studies. Prevention Relevance: Our findings support the need for larger prospective studies examining the role of prediagnostic plasma metabolomics for the preventive management of HCC in diverse patients across multiple etiologies of liver disease. This approach could improve HCC care by identifying metabolic changes years before diagnosis, potentially enhancing screening and early detection practices.

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