Sezione di Gastroenterologia, PROMISE, University of Palermo, Palermo, Italy.
Dipartimento di Biomedicina, Neuroscienze e Diagnostica Avanzata (BIND), University of Palermo, Palermo, Italy.
United European Gastroenterol J. 2024 Jun;12(5):638-648. doi: 10.1002/ueg2.12556. Epub 2024 Apr 24.
Metabolic dysfunction-associated steatotic liver disease (MASLD), with its steadily increasing prevalence, represents now a major problem in public health. A proper referral could benefit from tools allowing more precise risk stratification. To this end, in recent decades, several genetic variants that may help predict and refine the risk of development and progression of MASLD have been investigated. In this review, we aim to discuss the role genetics in MASLD plays in everyday clinical practice. We performed a comprehensive literature search of PubMed for relevant publications. Available evidence highlights the emergence of genetic-based noninvasive algorithms for diagnosing fatty liver, metabolic dysfunction-associated steatohepatitis, fibrosis progression and occurrence of liver-related outcomes including hepatocellular carcinoma. Nevertheless, their accuracy is not optimal and application in everyday clinical practice remains challenging. Furthermore, susceptible genetic markers have recently become subjects of great scientific interest as therapeutic targets in precision medicine. In conclusion, decisional algorithms based on genetic testing in MASLD to facilitate the clinician decisions on management and treatment are under growing investigation and could benefit from artificial intelligence methodology.
代谢相关脂肪性肝病(MASLD)的患病率不断上升,现已成为公共卫生领域的一个主要问题。恰当的转诊可以受益于能更精确地进行风险分层的工具。为此,近几十年来,人们研究了多种遗传变异,这些遗传变异可能有助于预测和改善 MASLD 的发生和进展风险。在这篇综述中,我们旨在讨论遗传因素在 MASLD 中的作用及其在日常临床实践中的应用。我们对 PubMed 中的相关文献进行了全面的文献检索。现有证据强调了基于遗传的非侵入性算法在诊断脂肪肝、代谢相关脂肪性肝炎、纤维化进展以及包括肝细胞癌在内的肝脏相关结局中的应用。然而,这些算法的准确性并不理想,在日常临床实践中的应用仍具有挑战性。此外,易感遗传标志物最近已成为精准医学中治疗靶点的研究热点。总之,基于 MASLD 遗传检测的决策算法有助于临床医生在管理和治疗方面做出决策,目前正在深入研究,并可能受益于人工智能方法。