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- Bianco, Cristina, et al.
(författare)
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Non-invasive stratification of hepatocellular carcinoma risk in non-alcoholic fatty liver using polygenic risk scores.
- 2021
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Ingår i: Journal of hepatology. - : Elsevier BV. - 1600-0641 .- 0168-8278. ; 74:4, s. 775-782
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Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC) risk stratification in individuals with dysmetabolism is a major unmet need. Genetic predisposition contributes to non-alcoholic fatty liver disease (NAFLD). We aimed to exploit robust polygenic risk scores (PRS) that can be evaluated in the clinic to gain insight into the causal relationship between NAFLD and HCC, and to improve HCC risk stratification.We examined at-risk individuals (NAFLD cohort, n=2,566; 226 with HCC; and a replication cohort of 427 German patients with NAFLD) and the general population (UK Biobank [UKBB] cohort, n=364,048; 202 with HCC). Variants in PNPLA3-TM6SF2-GCKR-MBOAT7 were combined in a hepatic fat PRS (PRS-HFC), and then adjusted for HSD17B13 (PRS-5).In the NAFLD cohort, the adjusted impact of genetic risk variants on HCC was proportional to the predisposition to fatty liver (p=0.002) with some heterogeneity in the effect. PRS predicted HCC more robustly than single variants (p<10-13). The association between PRS and HCC was mainly mediated through severe fibrosis, but was independent of fibrosis in clinically relevant subgroups, and was also observed in those without severe fibrosis (p<0.05). In the UKBB cohort, PRS predicted HCC independently of classical risk factors and cirrhosis (p<10-7). In the NAFLD cohort, we identified high PRS cut-offs (≥0.532/0.495 for PRS-HFC/PRS-5) that in the UKBB cohort detected HCC with ∼90% specificity but limited sensitivity; PRS predicted HCC both in individuals with (p<10-5) and without cirrhosis (p<0.05).Our results are consistent with a causal relationship between hepatic fat and HCC. PRS improved the accuracy to detect HCC and may help stratify HCC risk in individuals with dysmetabolism, including those without severe liver fibrosis. Further studies are needed to validate our findings.
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| 2. |
- Qadri, Sami, et al.
(författare)
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Obesity Modifies the Performance of Fibrosis Biomarkers in Nonalcoholic Fatty Liver Disease
- 2022
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Ingår i: Journal of Clinical Endocrinology and Metabolism. - : Oxford University Press. - 0021-972X .- 1945-7197. ; 107:5, s. e2008-e2020
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Tidskriftsartikel (refereegranskat)abstract
- Context: Guidelines recommend blood-based fibrosis biomarkers to identify advanced nonalcoholic fatty liver disease (NAFLD), which is particularly prevalent in patients with obesity. Objective: To study whether the degree of obesity affects the performance of liver fibrosis biomarkers in NAFLD. Design: Cross-sectional cohort study comparing simple fibrosis scores [Fibrosis-4 Index (FIB-4); NAFLD Fibrosis Score (NFS); aspartate aminotransferase to platelet ratio index; BARD (body mass index, aspartate-to-alanine aminotransferase ratio, diabetes); Hepamet Fibrosis Score (HFS)] and newer scores incorporating neo-epitope biomarkers PRO-C3 (ADAPT, FIBC3) or cytokeratin 18 (MACK-3). Setting: Tertiary referral center. Patients: We recruited overweight/obese patients from endocrinology (n = 307) and hepatology (n = 71) clinics undergoing a liver biopsy [median body mass index (BMI) 40.3 (interquartile range 36.0-44.7) kg/m(2)]. Additionally, we studied 859 less obese patients with biopsy-proven NAFLD to derive BMI-adjusted cutoffs for NFS. Main Outcome Measures: Biomarker area under the receiver operating characteristic (AUROC), sensitivity, specificity, and predictive values to identify histological stage >= F3 fibrosis or nonalcoholic steatohepatitis with >= F2 fibrosis [fibrotic nonalcoholic steatohepatitis (NASH)]. Results: The scores with an AUROC >= 0.85 to identify >= F3 fibrosis were ADAPT, FIB-4, FIBC3, and HFS. For fibrotic NASH, the best predictors were MACK-3 and ADAPT. The specificities of NFS, BARD, and FIBC3 deteriorated as a function of BMI. We derived and validated new cutoffs for NFS to rule in/out >= F3 fibrosis in groups with BM Is <30.0, 30.0 to 39.9, and >= 40.0 kg/m(2). This optimized its performance at all levels of BMI. Sequentially combining FIB-4 with ADAPT or FIBC3 increased specificity to diagnose >= F3 fibrosis. Conclusions: In obese patients, the best-performing fibrosis biomarkers are ADAPT and the inexpensive FIB-4, which are unaffected by BMI. The widely used NFS loses specificity in obese individuals, which may be corrected with BMI-adjusted cutoffs.
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