Editorial: Time to Genotype—Genetic Risk and Prognosis in Steatotic Liver Disease

As the global burden of steatotic liver disease (SLD), including metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-associated liver disease (ALD), continues to grow, hepatology faces a critical need for better tools to predict disease progression. In the last two decades, human genetic studies on SLD identified several variants associated with this disease [1, 2]. The meta-analysis by Kubina et al. [3] provides timely evidence that common variants in key genetic determinants of SLD, namely, PNPLA3, TM6SF2 and MBOAT7, may help address this gap. By using data from 40 independent studies for a total of more than 270,000 people, the authors demonstrate that these variants are not just risk factors for SLD onset but meaningful predictors of major adverse liver outcomes (MALO). Among all the genetic variants studied, homozygosity for the PNPLA3-rs738409 minor (G) allele emerges as the most powerful and consistent marker of adverse hepatic outcomes. It increases the risk of MALO by 2.3-fold (95% CI 1.66–3.18) [3], hepatocellular carcinoma (HCC) by 2.18-fold (95% CI 1.46–3.27) [3], cirrhosis/advanced liver disease by 2.47-fold (95% CI 1.81–3.37) [3] and, critically, liver-related mortality by 2.83-fold (95% CI 1.58–5.06) [3]. These are substantial effect sizes, comparable to, and in some cases greater than, those of traditional clinical risk factors such as diabetes, highlighting that PNPLA3 is a key driver of MASLD progression and, ultimately, liver-related mortality. Interestingly, a recent study showed that PNPLA3 homozygosis was associated with higher liver fibrosis by age 44, with an increased impact with aging [4, 5]. Importantly, TM6SF2-rs58542926 also proved clinically meaningful, particularly for HCC. People carrying the CT or TT genotype had more than a twofold increased risk of HCC (sHR 2.12; 95% CI 1.66–2.70) [3]. Mechanistically, TM6SF2 stabilises APOB [6] and when its function is impaired, hepatocellular lipids accumulate due to reduced very low-density lipoprotein secretion [6]. This is consistent with prior studies showing an enrichment of APOB loss-of-function variants in a cohort of people with HCC [7]. Crucially, the utility of genetic information is highest when known early. By the time someone reaches advanced fibrosis, the effects of deleterious variants like those in PNPLA3 and TM6SF2 have often already played out across decades of unrecognised liver injury. Genotyping at the first signs of SLD, namely, elevated transaminases, SLD on imaging or initial fibrosis, offers a window of opportunity to change liver disease trajectory. Early identification of high-risk people may allow for targeted diet, lifestyle and pharmacological intervention. MBOAT7 TT allele showed more modest associations with MALO (sHR 1.21; 95% CI 1.10–1.33) [3], cirrhosis/advanced liver disease (sHR 1.49; 95% CI 1.14–1.94) [3] and HCC (sHR 1.43; 95% CI 1.04–1.99) [3]. Interestingly, it was linked to lower all-cause mortality in two small studies comprising a total 1505 participants (sHR 0.78; 95% CI 0.62–0.98) [3], a finding that deserves further scrutiny but may reflect complex metabolic trade-offs. Despite the evidence, genotyping remains absent from clinical guidelines. Yet, in many tertiary care centres and specialised liver clinics, genotyping for PNPLA3 and TM6SF2 is already routinely performed to support risk stratification. This meta-analysis moves the field a step closer to precision hepatology. One cannot help but wonder whether the time to implement genotyping is already upon us, or what further evidence would still be needed to compel us. Rosellina M. Mancina: conceptualization, writing – original draft, writing – review and editing. Stefano Romeo: conceptualization, writing – original draft, writing – review and editing. S.R. has been consulting for AstraZeneca, GSK, Celgene Corporation, Ribo-cure AB and Pfizer in the last 5 years and received the research grant from AstraZeneca. The funders had no role in this editorial. R.M.M. has none to declare. This article is linked to Kubina et al. papers. To view these articles, visit https://doi.org/10.1111/apt.70256 and https://doi.org/10.1111/apt.70361. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.