Development and Validation of a Scoring System, Based on Genetic and Clinical Factors, to Determine Risk of Steatohepatitis in Asian Patients with Nonalcoholic Fatty Liver Disease
Development and Validation of a Scoring System, Based on Genetic and Clinical Factors, to Determine Risk of Steatohepatitis in Asian Patients with Nonalcoholic Fatty Liver Disease
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DOI：
10.1016/j.cgh.2020.02.011
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发表时间：
2020-10-01
影响因子：
12.6
通讯作者：
Kim, Won
中科院分区：
文献类型：
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作者：
Koo, Bo Kyung;Joo, Sae Kyung;Kim, Won
背景与目的：目前还没有非酒精性脂肪性肝炎（NASH）的生物标志物可用于常规临床应用。我们研究了PNPLA3和TM6SF2基因型（rs738409和rss58542926）的分析是否可以用于识别伴有和不伴有糖尿病的非酒精性脂肪性肝病（NAFLD）患者。方法：我们从韩国Boramae登记处收集了453例活检证实的NAFLD患者的数据，这些数据具有足够的临床数据来计算评分。2014年2月至2016年3月入组的患者被分配到队列1 （n = 302，发现队列），随后入组的患者被分配到队列2 （n = 151，验证队列）。提取所有参与者的DNA样本，分析PNPLA3 rs738409 C G、TM6SF2 rss58542926 C>T、SREBF2 rs133291 C>T、MBOAT7-TMC4 rs641738 C>T和HSD17B13 rs72613567腺嘌呤插入（A-INS）多态性。我们使用多变量logistic回归分析和逐步后向选择，利用队列1的基因型和临床数据建立了一个模型，以确定患者患NASH （NASH PT）的风险，并在队列2中检验了其准确性。我们使用受试者工作特征（ROC）曲线来比较NASH PT和NASH评分系统的诊断性能。结果：我们开发了一个基于PNPLA3和TM6SF2基因型、糖尿病状态、胰岛素抵抗、天冬氨酸转氨酶和高敏c反应蛋白水平的NASH PT评分系统。在队列1中，NASH PT评分确定NASH患者的ROC下面积（AUROC）为0.859 （95% CI, 0.817-0.901）。在队列2中，NASH PT评分识别NASH患者的AUROC为0.787 (95% CI, 0.715-0.860)，显著高于NASH评分的AUROC （AUROC, 0.729; 95% CI, 0.647-0.812; P = 0.007）。NAFLD合并糖尿病患者NASH PT评分检测NASH的AUROC为0.835 (95% CI, 0.776-0.895)，非糖尿病患者NASH PT评分检测NASH的AUROC为0.809 （95% CI, 0.757-0.861）。NASH PT评分的阴性预测值
BACKGROUND & AIMS: There are no biomarkers of nonalcoholic steatohepatitis (NASH) that are ready for routine clinical use. We investigated whether an analysis of PNPLA3 and TM6SF2 genotypes (rs738409 and rs58542926) can be used to identify patients with nonalcoholic fatty liver disease (NAFLD), with and without diabetes, who also have NASH.METHODS: We collected data from the Boramae registry in Korea on 453 patients with biopsy-proven NAFLD with sufficient clinical data for calculating scores. Patients enrolled from February 2014 through March 2016 were assigned to cohort 1 (n = 302; discovery cohort) and patients enrolled thereafter were assigned to cohort 2 (n = 151; validation cohort). DNA samples were obtained from all participants and analyzed for the PNPLA3 rs738409 C G, TM6SF2 rs58542926 C>T, SREBF2 rs133291 C>T, MBOAT7-TMC4 rs641738 C>T, and HSD17B13 rs72613567 adenine insertion (A-INS) polymorphisms. We used multivariable logistic regression analyses with stepwise backward selection to build a model to determine patients' risk for NASH (NASH PT) using the genotype and clinical data from cohort 1 and tested its accuracy in cohort 2. We used the receiver operating characteristic (ROC) curve to compare the diagnostic performances of the NASH PT and the NASH scoring systems.RESULTS: We developed a NASH PT scoring system based on PNPLA3 and TM6SF2 genotypes, diabetes status, insulin resistance, and levels of aspartate aminotransferase and high-sensitivity C-reactive protein. NASH PT scores identified patients with NASH with an area under the ROC (AUROC) of 0.859 (95% CI, 0.817-0.901) in cohort 1. In cohort 2, NASH PT scores identified patients with NASH with an AUROC of 0.787 (95% CI, 0.715-0.860), which was significantly higher than the AUROC of the NASH score (AUROC, 0.729; 95% CI, 0.647-0.812; P = .007). The AUROC of the NASH PT score for detecting NASH in patients with NAFLD with diabetes was 0.835 (95% CI, 0.776-0.895) and in patients without diabetes was 0.809 (95% CI, 0.757-0.861). The negative predictive value of the NASH PT score