Clustering NAFLD: phenotypes of nonalcoholic fatty liver disease and their differing trajectories

Globally, in the general adult population, the prevalence of NAFLD is estimated at 25%.[1] The prevalence of NAFLD is higher (∼40%–60%) in overweight and obese subjects, particularly in the presence of impaired metabolic health,[2] and the highest global prevalence of NAFLD (∼55%–70%) is found in patients with diabetes.[3] NAFLD is the main cause of chronic liver disease and HCC.[4] Furthermore, the strong epidemiological relationships of NAFLD with type 2 diabetes and cardiovascular diseases indicate very close pathophysiological relationships between NAFLD and obesityassociated cardiometabolic diseases.[5] However, there is large heterogeneity among patients with NAFLD with respect to their risk of cardiometabolic diseases.[3] This may result from the fact that different major pathways are involved in the pathogenesis of NAFLD. Among them is NAFLD associated with a stronger hepatic genetic component. For example, genetic variants in PNPLA3 (148Met allele) and TM6SF2 (167Lys allele) strongly associate with steatosis and progression to NASH, cirrhosis, and HCC, but also with the absence of insulin resistance, low blood triglycerides, low LDL cholesterol concentration, and protection from coronary artery disease. Furthermore, NAFLD predominantly driven by de novo lipogenesis and NAFLD predominantly driven by adipose tissue dysfunction exist, which are both associated with insulin resistance but are also thought to differ in their risk of cardiometabolic diseases.[3] Yi et al[6] set out to identify clinically important groups among patients with NAFLD and assess the long-term outcomes between different subphenotypes and, most recently, published their findings in Hepatology Communications. For this, they analyzed the data from the US Third National Health and Nutrition Examination Survey, where fatty liver was diagnosed in individuals by abdominal ultrasound and used their linked mortality data through December 2019. As a data dimensionality reduction approach, the authors performed a 2-stage cluster analysis (a hierarchical cluster analysis using the Ward method to determine the optimum number of clusters, followed by an allocation of each patient into a particular cluster). Using 21 baseline variables, body mass index (BMI), waist circumference, hemoglobin, glycohemoglobin, waist-to-hip ratio, uric acid, HDL cholesterol, and homeostasis model assessment of insulin resistance were identified as the most important variables in the prediction of the patient clusters. Three distinct clusters were identified. Cluster 1 predominantly comprised younger (mean age 40 y), lean (mean BMI 24 kg/m2) females (76%) with a low cardiometabolic risk profile and a lower prevalence of comorbidities. Cluster 2 consisted mostly of older (mean age 50 y), obese (mean BMI 34 kg/m2) females (75%) with a high prevalence of insulin resistance (83%) and diabetes (34%). Cluster 3 was predominantly composed of older (mean age 49 y), overweight/obese (mean BMI 30 kg/m2) males (75%) with insulin resistance (72%), a moderately elevated prevalence of diabetes (15%), hypertension, and atherogenic dyslipidemia. During a median follow-up period of 312 months compared with patients in cluster 1, patients in cluster 2 and cluster 3 had higher all-cause and cardiovascular mortality, also after the adjustment for age, sex, BMI, and race/ethnicity. No differences in all-cause mortality were observed between patients in clusters 2 and 3.[6] The authors concluded that patients with NAFLD, who were allocated to cluster 1 and who did not have insulin resistance, hypertension, or dyslipidemia, may have a pathophysiology of NAFLD, which is stronger related to the hepatic genetic component. Unfortunately, the authors could not study incident fibrosis or cirrhosis, as it would be expected that no differences in the incidence of these advanced stages of liver disease would exist between the clusters. The authors further hypothesized that in patients in cluster 2, predominantly being obese and having severe insulin resistance and a high prevalence of diabetes, hepatic steatosis may