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PNPLA3基因对肝脏疾病自然史的影响。

Contribution of PNPLA3 gene to the natural history of liver diseases.

作者信息

Trépo E

出版信息

Acta Gastroenterol Belg. 2017 Jan-Mar;80(1):43-51.

PMID:29364097
Abstract

n 2008, a genome-wide association studies (GWAS) showed a strong association between a variant (rs738409 C>G p.I148M) in the PNPLA3 and nonalcoholic fatty liver disease. Further replication studies have shown robust associations between PNPLA3 and steatosis, fibrosis/cirrhosis, and hepatocellular carcinoma on a background of metabolic, alcoholic, and viral insults. The PNPLA3 protein has lipase activity towards triglycerides in hepatocytes and retinyl esters in hepatic stellate cells. The I148M substitution leads to a loss of function promoting triglyceride accumulation in hepatocytes. Although PNPLA3 function has been extensively studied, the molecular mechanisms leading to hepatic fibrosis and carcinogenesis remain unclear. This unsuspected association has highlighted the fact that liver fat metabolism may have a major impact on the pathophysiology of liver disease. Conversely, alone, this locus may have limited predictive value with regard to liver disease outcomes in clinical practice. Additional studies at the genome-wide level will be required to identify new variants associated with liver damage and cancer to explain a greater proportion of the heritability of these phenotypes. Thus, incorporating PNPLA3 and other genetic variants in combination with clinical data will allow for the development of tailored predictive models. This attractive approach should be evaluated in prospective cohorts. (Acta gastroenterol. belg., 2017, 80, 43-51).

摘要

2008年,一项全基因组关联研究(GWAS)显示,PNPLA3基因中的一个变异(rs738409 C>G p.I148M)与非酒精性脂肪性肝病之间存在强关联。进一步的重复研究表明,在代谢、酒精和病毒损伤背景下,PNPLA3与脂肪变性、纤维化/肝硬化以及肝细胞癌之间存在紧密关联。PNPLA3蛋白对肝细胞中的甘油三酯和肝星状细胞中的视黄酯具有脂肪酶活性。I148M替代导致功能丧失,促进肝细胞内甘油三酯积累。尽管对PNPLA3的功能进行了广泛研究,但导致肝纤维化和致癌的分子机制仍不清楚。这种意外的关联凸显了肝脏脂肪代谢可能对肝脏疾病病理生理学产生重大影响这一事实。相反,仅该基因座在临床实践中对肝脏疾病预后的预测价值可能有限。需要在全基因组水平上进行更多研究,以确定与肝损伤和癌症相关的新变异,从而解释这些表型更大比例的遗传度。因此,将PNPLA3和其他基因变异与临床数据相结合,将有助于开发定制的预测模型。这种有吸引力的方法应在前瞻性队列中进行评估。(《比利时胃肠病学学报》,2017年,80卷,43 - 51页)

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