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. 2021 Aug;15(4):922-933.
doi: 10.1007/s12072-021-10200-y. Epub 2021 Jun 2.

Combined effects of PNPLA3, TM6SF2 and HSD17B13 variants on severity of biopsy-proven non-alcoholic fatty liver disease

Rafael Paternostro  1 , Katharina Staufer  1   2 , Stefan Traussnigg  1 , Albert-Friedrich Stättermayer  1 , Emina Halilbasic  1 , Omar Keritam  1 , Elias L Meyer  3 , Judith Stift  4 , Fritz Wrba  4 , Bence Sipos  5 , Ali Canbay  6 , Martin Schlattjan  7 , Elmar Aigner  8 , Christian Datz  9 , Felix Stickel  10 , Clemens Schafmayer  11 , Jochen Hampe  12 , Stephan Buch  12 , Gerhard Prager  13 , Petra Munda  1 , Mattias Mandorfer  1 , Peter Ferenci  1 , Michael Trauner  14
Affiliations

Combined effects of PNPLA3, TM6SF2 and HSD17B13 variants on severity of biopsy-proven non-alcoholic fatty liver disease

Rafael Paternostro et al. Hepatol Int. 2021 Aug.

Abstract

Objective: Several single-nucleotide polymorphisms have been identified to be disadvantageous or protective in regard to disease severity in patients with non-alcoholic fatty liver disease (NAFLD). However, it is unclear, whether including genetic risk factor(s) either alone or combined into risk stratification algorithms for NAFLD actually provides incremental benefit over clinical risk factors.

Design: Patients with biopsy-proven NAFLD were genotyped for the PNPLA3-rs738409(minor allele:G), TM6SF2-rs58542926(minor allele:T) and HSD17B13- rs72613567 (minor allele:TA) variants. The NAFLD activity score (NAS) and fibrosis stage (F0-F4) were used to grade and stage all liver biopsy samples. Patients from seven centers throughout Central Europe were considered for the study.

Results: 703 patients were included: NAS ≥ 5:173(24.6%); Fibrosis: F3-4:81(11.5%). PNPLA3 G/G genotype was associated with a NAS ≥ 5(aOR 2.23, p = 0.007) and advanced fibrosis (aOR-3.48, p < 0.001).TM6SF2 T/- was associated with advanced fibrosis (aOR 1.99, p = 0.023). HSD17B13 TA/- was associated with a lower probability of NAS ≥ 5(TA/T: aOR 0.65, p = 0.041, TA/TA: aOR 0.40, p = 0.033). Regarding the predictive capability for NAS ≥ 5, well-known risk factors (age, sex, BMI, diabetes, and ALT; baseline model) had an AUC of 0.758, Addition of PNPLA3(AUC 0.766), HSB17B13(AUC 0.766), and their combination(AUC 0.775), but not of TM6SF2(AUC 0.762), resulted in a higher diagnostic accuracy of the model. Addition of genetic markers for the prediction of advanced fibrosis (baseline model: age, sex, BMI, diabetes: AUC 0.777) resulted in a higher AUC if PNPLA3(AUC 0.789), and TM6SF2(AUC 0.786) but not if HSD17B13(0.777) were added.

Conclusion: In biopsy-proven NAFLD, PNPLA3 G/-, TM6SF2 T/- and HSD17B13 TA/- carriage are associated with severity of NAFLD. Incorporating these genetic risk factors into risk stratification models might improve their predictive accuracy for severity of NAFLD and/or advanced fibrosis on liver biopsy.

Keywords: Advanced fibrosis; Cirrhosis; Fibrosis; Genetic risk factors; HSD17B13; Liver biopsy; NAFLD; NASH; PNPLA3; TM6SF2.

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Conflict of interest statement

RP, KS, ST, AFS, EH, OK, JS, FW, BS, AC, MS, CD, CS, JH, SB, GP, PF, PM: none. FS: None in relation to the contents of this study. EM: reports funding for unrelated research from Novartis. EA: speaker fees, travel support or advisory fees from Intercept, Gilead, Takeda, Shire, Alexion; MM received speaker fees from AbbVie, Bristol-Myers Squibb, Gilead, and W. L. Gore and Associates; travel support from AbbVie, Bristol-Myers Squibb, and Gilead. PF: Adboard: Univar, Alexion and Vivet Therapeutics, Gliead, Abbvie, MSD. MT received speaker fees from Bristol-Myers Squibb (BMS), Falk Foundation, Gilead, Intercept and Merck Sharp and Dohme (MSD); advisory board fees from Albireo, Boehringer Ingelheim, BiomX, Falk Pharma GmbH, GENFIT, Gilead, Intercept, Janssen, MSD, Novartis, Phenex, Regulus and Shire; travel grants from AbbVie, Falk, Gilead, and Intercept; and research grants from Albireo, CymaBay, Falk, Gilead, Intercept, MSD, and Takeda. He is also coinventor of patents on the medical use of norUDCA filed by the Medical University of Graz. All the other authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1
AUC for predicting NAS ≥ 5 applying a baseline model (BL; age, sex, BMI, diabetes, and ALT), b BL + PNPLA3, c BL + HSD17B13, d BL + TM6SF2, and e BL + PNPLA3 + HSD17B13; P-values: b, c, d vs. BL model; e vs. PNPLA3 model
Fig. 2
Fig. 2
AUC for predicting advanced fibrosis (≥ F3) using a baseline model (BL; age, sex, BMI, and diabetes), b BL + PNPLA3, c BL + HSD17B13 d, BL + TM6SF2, e BL + PNPLA3 + TM6SF2; P-values: b, c, and d vs. BL model; e vs. PNPLA model)
Fig. 3
Fig. 3
Distribution of risk alleles (PNPLA3 G, TM6SF2 T and HSD17B13 T-allele) across disease severity strata (a—NAS; b—Steatosis; c—Inflammation; d—Ballooning; e—F ≥ 3; f—F ≤ 2)
See this image and copyright information in PMC

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