Abbas Syed Muzaffar, Hussain Zeeshan, Asghar Nimra, Shabbir Mahnoor, Akhlaq Muhammad Armaghan, Mughal Hafiz Muhammad Faizan, Hussain Asma, Asif Abdul Eizad, Mzahri Ehsan Ul Haq
Department of General Medicine, Bangor Hospital, Bangor, GBR.
Department of Underwater and Hyperbaric Medicine, PNS (Pakistan Navy Station) Shifa Hospital, Karachi, PAK.
Cureus. 2025 Apr 28;17(4):e83133. doi: 10.7759/cureus.83133. eCollection 2025 Apr.
Non-alcoholic fatty liver disease (NAFLD) is seen as a health concern globally and is identified via complex interactions of metabolic dysfunctions. Metabolomic and lipidomic profiling has been emerged as a promising tool for non-invasive diagnosis and precision therapy. This systematic review and meta-analysis aimed to assess the affect of metabolic signatures associated with NAFLD progression and their utility in paving path for precision medicine. A comprehensive literature search was conducted in adherence to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020. Appropriate data studies were pooled to check the disease progression using a random effects model. Risk of bias and certainty of evidence were assessed using the Cochrane risk of bias tool, ROBINS-I ("Risk Of Bias In Non-randomized Studies - of Interventions"), and the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework respectively. Studies found distinct metabolite patterns especially in amino acids, lipids, and gut-derived metabolites that correlated with the severity of NAFLD. The meta-analysis findings revealed a pooled hazard ratio of 0.98 (95% CI: 0.83-1.15) that indicated that no significant association was found between studies for assessment of metabolic signatures and their link to disease progression. High heterogeneity was observed (I² = 82%). Risk of bias was generally low to moderate, but overall certainty of evidence was rated low to moderate due to inconsistency and imprecision. Metabolic profiling offered valuable insights and discoveries into pathophysiology of NAFLD and stratification. However, high heterogeneity found across studies limited current clinical applicability. Standardized methodologies and longitudinal validation were needed to combine metabolic signatures into precision NAFLD care.
非酒精性脂肪性肝病（NAFLD）被视为全球范围内的一个健康问题，它是通过代谢功能障碍的复杂相互作用来识别的。代谢组学和脂质组学分析已成为一种有前景的非侵入性诊断和精准治疗工具。本系统评价和荟萃分析旨在评估与NAFLD进展相关的代谢特征的影响及其在为精准医学铺平道路方面的效用。按照《系统评价和荟萃分析的首选报告项目》（PRISMA）2020指南进行了全面的文献检索。使用随机效应模型汇总适当的数据研究以检查疾病进展。分别使用Cochrane偏倚风险工具ROBINS-I（“非随机干预研究中的偏倚风险”）以及推荐分级、评估、制定和评价（GRADE）框架评估偏倚风险和证据的确定性。研究发现了独特的代谢物模式，特别是在氨基酸、脂质和肠道衍生代谢物中，这些与NAFLD的严重程度相关。荟萃分析结果显示合并风险比为0.98（95%CI：0.83-1.15），这表明在评估代谢特征及其与疾病进展的联系的研究之间未发现显著关联。观察到高度异质性（I² = 82%）。偏倚风险一般为低到中度，但由于不一致性和不精确性，证据的总体确定性被评为低到中度。代谢谱分析为NAFLD的病理生理学和分层提供了有价值的见解和发现。然而，各研究中发现的高度异质性限制了当前的临床适用性。需要标准化方法和纵向验证，以将代谢特征纳入精准NAFLD护理中。
