Risk stratification of liver outcomes in NAFLD
| Author, year [Ref.] | Series | Findings | Conclusion |
|---|---|---|---|
| Dongiovanni et al., 2018 [46] | 9,414 individuals from three study populations were recruited: the liver biopsy cohort, the Swedish Obese Subjects Study and the population-based Dallas Heart Study | Intra-hepatic fat accumulation was associated with liver disease and dysmetabolic traits Genetic variants affect liver damage proportionally to their steatogenic capacity | Long-term accumulation of fat in the liver causes CLD |
| Labenz et al., 2018 [47] | 261 non‐cirrhotic biopsy-proven NAFLD German patients were enrolled | LSM identified advanced fibrosis with an AUC of 0.81 (95% CI 0.72–0.91) while NFS, FIB‐4, and APRI exhibited a lower performance (AUCs of 0.74, 0.71, and 0.67, respectively) | LSM outperformed wet tests in ruling out advanced fibrosis |
| Ioannou et al., 2019 [48] | 7,068 individuals with NAFLD-cirrhosis identified in 2012 were evaluated for the development of incident HCC retrospectively till January 2018 | 7 variables, namely age, sex, BMI, diabetes, platelet count, serum albumin and serum AST/√ALT ratio, selected out of 25 considered potential predictors, were included in the final statistical model | Age, platelet count, serum AST/√ALT ratio and albumin accounted for 93.9% of the risk of incident HCC among individuals with NAFLD-cirrhosis |
| De Vincentis et al., 2022 [49] | The UKBB database was used to assess prospectively incident cirrhosis, decompensated liver disease, HCC, and/or liver transplantation among 266,687 recruited individuals followed during a median 9-year time | PRS-HFC based on polymorphisms in PNPLA3, TM6SF2, MBOAT7, and GCKR improved diagnostic accuracy and PPV for severe liver disease among those classified as at intermediate-high risk with NFS, FIB-4, APRI, or Forns. Risk stratification and prediction were either not or were poorly affected by unfavorable genetics in subjects not having metabolic risk factors | To the ends of identifying severe incident CLD, common genetic variants provide additional prognostic information which is not captured by validated clinical/biochemical parameters |
| Fujiwara et al., 2022 [50] | Derivation set = 48 patients previously submitted to curative HCC ablation Tissue validation set 1 = 106 HCC-naive individuals Tissue validation set 2 = 59 previously submitted to curative HCC resection Serum validation set = 59 HCC-naive | A 133-gene signature, (PLS)-NAFLD predicted incident HCC over a 15-year follow-up High-risk PLS-NAFLD was associated with specific immune cell phenotypes in fibrotic portal tracts along with impaired metabolic regulators PLS-NAFLD was bioinformatically translated into a four-protein secretome signature, PLSec-NAFLD, which was validated in an independent cohort of HCC-naive patients with NAFLD and cirrhosis. Combination of PLSec-NAFLD with a previously defined index (the etiology-agnostic PLSec-AFP) further improved HCC risk stratification | This proof-of-concept study developed and validated PLS/PLSec-NAFLD. Given that they predict long-term HCC risk and estimate effects of therapeutic interventions in patients with NAFLD, these signatures may potentially improve the poor outcome of NAFLD-HCC and disclose novel avenues for HCC chemoprevention |
| Jambulingam et al., 2023 [51] | All 189 patients consecutive new referrals for NAFLD services between 2011 and 2019 were enrolled, 58.7% of whom were submitted to liver biopsy | The fast fibrosis progressors were identified by a combination of metabolites and lipoproteins (AUROC 0.788, 95% CI: 0.703–0.874, P < 0.001) better than with noninvasive markers | The combination of metabolites and lipids may help in the risk-stratification of fast fibrosis progression among NAFLD patients |
| Chen et al., 2023 [52] | NAFLD, defined as otherwise unexplained raised ALT, was assessed in a total of 54,773 individuals belonging to 2 independent: study populations: the MGI (7,893 individuals) and the UKBB (46,880 individuals) cohorts | PNPLA3-rs738409 genotype and diabetes identified patients with FIB-4, 1.3–2.67, currently considered indeterminate risk for NAFLD, who exhibited a risk of cirrhosis similar to those with FIB-4, 2.67, who are considered high-risk | PNPLA3 genotyping improves prognostication of liver outcomes compared to common judgement based on clinical and laboratory assessment |
| Liu et al., 2023 [53] | 550 Chinese with biopsy-proven NAFLD | The combination of serum BAs with WC, DBP, ALT, or HOMA-IR identified mild fibrosis, in either sex, irrespective of obesity with AUROCs 0.80, 0.88, 0.75 and 0.78 in the training set (n = 385), and 0.69, 0.80, 0.61 and 0.69 in the testing set (n = 165), respectively. Interestingly, these AUROCs were more accurately than those yielded by FIB-4, NFS, and Hepamet fibrosis score | Mild fibrosis is accurately identified non-invasively with analysis of secondary BA levels combined with anthropometric and hepato-metabolic biomarkers |
ALT: alanine transaminase; AUROC/AUC: area under the curve; AFP: alpha-fetoprotein; APRI: aspartate transaminase-to-platelet ratio index; AST: aspartate transaminase; PLSec: prognostic liver secretome signature; BAs: bile acids; BMI: body mass index; CLD: chronic liver disease; DBP: diastolic blood pressure; HOMA-IR: homeostatic model assessment for insulin resistance; MGI: Michigan genomics initiative; PLS: prognostic liver signature; PPV: positive predictive value; PRS-HFC: polygenic risk score-hepatic fat content; UKBB: United Kingdom Biobank; WC: waist circumference
