Division of Gastroenterology, University of British Columbia, Vancouver, Canada.
Division of Biostatistics, Hospital for Sick Children, University of Toronto, Toronto, Canada.
Hepatol Int. 2022 Apr;16(2):325-336. doi: 10.1007/s12072-022-10304-z. Epub 2022 Feb 18.
Lean NAFLD may differ from NAFLD found in overweight or obese patients. We used the UK biobank to conduct a cross-sectional study that examined features that distinguish lean NAFLD from overweight or obese NAFLD.
MRI-PDFF data were used to identify patients with NAFLD, with NAFLD defined as PDFF ≥ 5%. BMI patient cohorts were identified, with lean defined as a BMI < 25, and overweight or obese defined as a BMI ≥ 25. Variables of interest to fatty liver disease, including single nucleotide polymorphisms, were chosen from the UK biobank data portal. Logistic regression was used to generate models predictive of NAFLD in each cohort.
1007 patients had NAFLD, and of these, 871 had BMI ≥ 25, and 136 BMI < 25. Factors associated with NAFLD in patients with BMI < 25 included male sex, white blood cell count, red blood cell count, triglycerides, ALT, creatinine, visceral adipose tissue, rs58542926 T, and rs738409 G. In contrast, factors associated with NAFLD in patients with BMI ≥ 25 included male sex, waist circumference, HDL cholesterol, triglycerides, serum glucose, ALT, creatinine, urate, visceral adipose tissue, rs1260326 T, rs1044498 C, rs58542926 T, and rs738409 G. For lean patients, our generated prediction score had an AUC of 0.92, sensitivity of 0.90 and specificity of 0.81. For overweight or obese patients, the prediction score had an AUC of 0.86, sensitivity of 0.87 and specificity of 0.70.
Our analysis suggests that lean and overweight or obese NAFLD are distinct entities. We have developed a risk score incorporating both clinical and genetic factors that accurately classify lean patients with NAFLD, with the potential to serve as a tool for screening purposes.
瘦型非酒精性脂肪性肝病（NAFLD）可能与超重或肥胖患者的 NAFLD 不同。我们使用英国生物银行进行了一项横断面研究，以检查区分瘦型 NAFLD 与超重或肥胖型 NAFLD 的特征。
使用 MRI-PDFF 数据来识别 NAFLD 患者，NAFLD 的定义为 PDFF≥5%。确定 BMI 患者队列，其中瘦型定义为 BMI<25，超重或肥胖型定义为 BMI≥25。从英国生物银行数据门户中选择与脂肪肝相关的感兴趣变量，包括单核苷酸多态性。使用逻辑回归生成每个队列中预测 NAFLD 的模型。
1007 名患者患有 NAFLD，其中 871 名患者 BMI≥25，136 名患者 BMI<25。BMI<25 的患者中与 NAFLD 相关的因素包括男性、白细胞计数、红细胞计数、甘油三酯、ALT、肌酐、内脏脂肪组织、rs58542926T 和 rs738409G。相比之下，BMI≥25 的患者中与 NAFLD 相关的因素包括男性、腰围、HDL 胆固醇、甘油三酯、血糖、ALT、肌酐、尿酸、内脏脂肪组织、rs1260326T、rs1044498C、rs58542926T 和 rs738409G。对于瘦型患者，我们生成的预测评分的 AUC 为 0.92，敏感性为 0.90，特异性为 0.81。对于超重或肥胖患者，预测评分的 AUC 为 0.86，敏感性为 0.87，特异性为 0.70。
我们的分析表明，瘦型和超重或肥胖型 NAFLD 是不同的实体。我们已经开发了一种包含临床和遗传因素的风险评分，可以准确分类患有 NAFLD 的瘦型患者，有可能作为一种筛查工具。
