Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most common form of chronic liver disease, following the growing rates of obesity and type 2 diabetes (T2D). The disorder currently affects 38% of adults worldwide and is among the leading causes of cirrhosis, liver cancer and liver failure [
1]. MASLD results from the interplay of genetic and environmental factors. Obesity and T2D are two major metabolic risk factors that have fueled MASLD’s surge. However, heritable factors play an important role, explaining 20–70% of interindividual differences in disease susceptibility, according to family studies [
2].
Genome-wide association studies (GWAS) have identified several genetic variants that modify MASLD risk. Yet, known variants explain only a fraction of heritable disease variation. The missing heritability has been attributed in part to gene-environment interactions, where phenotypic effects of genetic variants depend on environmental exposures [
3]. Traditional GWAS look at additive allele-dosage effects and may miss synergistic relationships, which can mask as non-linear trends. The effects of several genetic risk factors for MASLD (including
PNPLA3, TM6SF2, and
HSD17B13) have been consistently shown to be magnified by adiposity [
4-
7]. This prompts the question of whether looking for obesity-dependent effects might uncover additional genes contributing to MASLD. Only one previous study attempted an agnostic genome-wide screen of gene-bybody-mass index (BMI) interactions for MASLD-related traits [
8].
In a recent issue of
Clinical and Molecular Hepatology, Jamialahmadi and colleagues leveraged this approach and performed the largest to date genome-wide BMI-interaction analysis for MASLD [
9]. To maximize the sample size, the authors first tested for BMI-dependent effects of over 9 million genetic variants on blood levels of ALT—a proxy measure of MASLD—in nearly 380K individuals of European ancestry from the UK Biobank (UKB), a general population sample of adults from the UK. This analysis identified 13 independent loci with significant BMI interactions, including 8 MASLD loci with previously reported BMI-dependent effects (e.g.,
PNPLA3, TM6SF2, HSD17B13, MARC1, and
APOE), 1 locus reported in an earlier genome-wide BMIinteraction study but with no independently confirmed role in MASLD (
UBXN2B/CYP7A1), and 3 loci not hitherto known to affect MASLD or to interact with BMI (
DPM3, HLA-B, and
GIPR). In addition, the study identified a novel BMI-dependent effect at a previously reported MASLD locus,
COBLL1 [
10]. In stratified analysis, most loci had larger effects in obese subjects (BMI≥30 kg/m
2) compared to those of normal weight (BMI<25 kg/m
2), consistent with prior reports [
4-
8], though some had non-significant effects in low-BMI participants. Only
DPM3 variant showed an opposite trend, with a stronger effect among the lean than the obese. While in the previous study in a subset of UKB participants, the
UBXN2B/CYP7A1 locus was associated with ALT only in the top BMI quartile [
8], in the current study, the lead
UBXN2B/CYP7A1 variant was also associated with ALT in the lean group, but with an opposite direction of effect: higher ALT level among obese subjects and lower ALT among the lean. As a result, similar to prior study, the variant did not have an overall additive effect on ALT and was only uncovered by interaction analysis.
To confirm the findings, the authors tested the identified loci for association with MRI-derived liver proton density fat fraction (PDFF), an accurate measure of hepatic steatosis, in an independent set of over 35K UKB participants, who were not included in the first-stage analysis. Though only 1 of the 4 novel loci showed evidence of interaction with BMI (HLA-B), all 4 had nominal (P<0.05) main-effect associations with PDFF. Surprisingly, DPM3 variant appeared to have an opposite direction of effect on PDFF than on ALT, which may reflect either biological difference between the two traits or chance variation. Curiously, the UBXN2B/CYP7A1 variant had an additive-effect association with PDFF despite having no additive effect on ALT; this was further confirmed in four independent European cohorts with imaging-derived measures of liver fat content.
Like most GWAS signals, newly identified variants were in non-coding regions. To pinpoint the causal genes and biological mechanisms underlying statistical associations at these loci, the authors performed several bioinformatic analyses, followed by a phenome-wide association study and functional experiments. HLA-B locus was excluded from further investigation due to its known complex variation structure, which makes it difficult to draw valid conclusions.
For the remaining loci, the authors first used fine-mapping— a statistical approach that integrates the association and linkage patterns in a genomic region together with functional genomic annotations, to narrow down the signal to a small set of variants, called a “credible set”, that collectively have a high probability of capturing the causal variant [
11]. No credible set was identified around
DPM3; however, the most likely causal variant was upstream of
EFNA1, a gene previously associated with ALT levels and cirrhosis [
7]. At the
UBXN2B/CYP7A1 locus, the most likely causal variant was downstream of
CYP7A1. At
GIPR, two credible sets were identified that partially overlapped with the known
APOE locus [
12], suggesting the existence of multiple causal variants in this region.
To determine whether these variants modify MASLD risk by altering the expression of nearby genes [
13], the authors compared BMI-interaction effects with publicly available databases of expression quantitative trait loci (eQTLs). BMI-interacting variants did not coincide with eQTLs of the putative causal genes in liver or other relevant tissues. Limited overlap between GWAS signals and eQTLs can occur for multiple reasons [
14]. In the current study, lack of agreement between BMI-interacting variants and eQTLs may, in addition, be due to the fact that eQTL effects were estimated in additive models, and do not reflect BMI-dependent effects.
To gain further insight into the phenotypic consequences of the novel variants, the authors examined their association with an array of biomarkers and disease traits, focus-ing on the two most promising loci: GIPR and CYP7A1. The DPM3 locus was not pursued further perhaps due to its discordant association with ALT and PDFF or the uncertainty about the causal gene.
The intronic
GIPR variant (rs34783010) was associated with higher PDFF, worse glycemic control, higher odds of diabetes, but, surprisingly, lower BMI, resembling phenotypic characteristics of lipodystrophy.
GIPR encodes the receptor for the gastric inhibitory polypeptide (GIP). Tirzepatide, a dual agonist of GIPR and glucagon-like peptide-1 receptor (GLP1R), was recently approved in the US and Europe to treat T2D and obesity and was subsequently demonstrated to be efficacious in reducing liver inflammation and fibrosis [
15]. Given the opposite effect of rs34783010 on PDFF and BMI, the nature of the underlying effect on receptor function is unclear. Nevertheless, the current study provides further support for the role of
GIPR in MASLD and the use of GIPR agonists as a therapeutic strategy for MASLD.
At the
UBXN2B/CYP7A1 locus, PDFF-increasing allele of the lead intergenic variant (rs7826120) was associated with increased circulating triglycerides and cholesterol levels, and higher odds of cardiovascular and gallstone disease (GSD), similar to the phenotypic effects of missense variants in
CYP7A1 [
16]. The same allele was also associated with higher odds of chronic liver disease and several metabolites involved in bile acid metabolism.
CYP7A1 encodes the enzyme cholesterol 7α-hydroxylase, which catalyzes the first step in the conversion of cholesterol to bile acids, the main pathway for removal of cholesterol from the body. Loss of CYP7A1 activity has been described to result in severe hypercholesterolemia and premature GSD [
17]. These data suggest that the causal variant at this locus likely reduces enzymatic activity of CYP7A1. Further epigenomic analysis revealed that the putative causal variant at
CYP7A1 (rs10504255) lies within a transcriptional enhancer. Activation of the enhancer in a human hepatic cell line led to upregulation of CYP7A1. CRISPR/Cas9-mediated disruption of CYP7A1 orthologues resulted in lower liver fat content in zebrafish larvae subjected to metabolic challenge (though not under normal metabolic conditions). The result contradicted the observed effect in humans, but was in agreement with data in 7α-hydroxylase-deficient mice [
18], and may reflect either cross-species differences or the variable context-dependent effects of CYP7A1. Nonetheless, these data support the role of CYP7A1 as a modulator of MASLD pathogenesis.
In summary, using a genome-wide BMI-interaction screen, the current study identified 2 potentially new loci for MASLD. The results further illustrate the role of adiposity in MASLD and suggest that the effect of weight loss in MASLD treatment may depend on genetic background, as previously demonstrated for
PNPLA3. The findings also give rise to several questions. The mechanisms responsible for the observed associations (in particular, the opposite effect of CYP7A1 on ALT in high and low BMI) will need to be clarified in future studies. Compared with other cardiometabolic diseases, the number of loci associated with MASLD remains low. Whether this is due to relatively small sample sizes in GWAS of MASLD endpoints or reflects a true oligogenic architecture of MASLD, remains to be seen. Regardless, the data suggest that discovering new loci for MASLD will require very large sample sizes and innovative study designs. The current study only considered interactions with BMI. BMI is an imperfect measure of adiposity [
19]. Examining interactions with other measures of adiposity, more strongly correlated with MASLD, e.g., visceral fat, could reveal additional loci [
20]. Finally, the current study focused on individuals of European ancestry. The results should be validated in other ancestries.
FOOTNOTES
-
Conflicts of Interest
The author has no conflicts of interest to declare.
Abbreviations
expression quantitative trait loci
gastric inhibitory polypeptide
glucagon-like peptide-1 receptor
genome-wide association studies
metabolic dysfunction-associated steatotic liver disease
proton density fat fraction
REFERENCES
- 1. Younossi ZM, Kalligeros M, Henry L. Epidemiology of metabolic dysfunction-associated steatotic liver disease. Clin Mol Hepatol 2025;31(Suppl):S32-S50.
- 2. Sookoian S, Pirola CJ. Genetic predisposition in nonalcoholic fatty liver disease. Clin Mol Hepatol 2017;23:1-12.
- 3. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, et al. Finding the missing heritability of complex diseases. Nature 2009;461:747-753.
- 4. Romeo S, Sentinelli F, Dash S, Yeo GS, Savage DB, Leonetti F, et al. Morbid obesity exposes the association between PNPLA3 I148M (rs738409) and indices of hepatic injury in individuals of European descent. Int J Obes (Lond) 2010;34:190-194.
- 5. Stender S, Kozlitina J, Nordestgaard BG, Tybjærg-Hansen A, Hobbs HH, Cohen JC. Adiposity amplifies the genetic risk of fatty liver disease conferred by multiple loci. Nat Genet 2017;49:842-847.
- 6. Gellert-Kristensen H, Nordestgaard BG, Tybjaerg-Hansen A, Stender S. High risk of fatty liver disease amplifies the alanine transaminase-lowering effect of a HSD17B13 variant. Hepatology 2020;71:56-66.
- 7. Emdin CA, Haas M, Ajmera V, Simon TG, Homburger J, Neben C, et al. Association of genetic variation with cirrhosis: A multi-trait genome-wide association and gene-environment interaction study. Gastroenterology 2021;160:1620-1633.e13.
- 8. Gao C, Marcketta A, Backman JD, O’Dushlaine C, Staples J, Ferreira MAR, et al. Genome-wide association analysis of serum alanine and aspartate aminotransferase, and the modifying effects of BMI in 388k European individuals. Genet Epidemiol 2021;45:664-681.
- 9. Jamialahmadi O, Mujica E, Morris L, Mancina RM, Ciociola E, Qadri SF, et al. Genome-wide interaction study with body mass index identifies CYP7A1 and GIPR as genetic modulators of metabolic dysfunction-associated steatotic liver disease. Clin Mol Hepatol 2025;31:1252-1268.
- 10. Vujkovic M, Ramdas S, Lorenz KM, Guo X, Darlay R, Cordell HJ, et al. A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation. Nat Genet 2022;54:761-771.
- 11. Schaid DJ, Chen W, Larson NB. From genome-wide associations to candidate causal variants by statistical fine-mapping. Nat Rev Genet 2018;19:491-504.
- 12. Jamialahmadi O, Mancina RM, Ciociola E, Tavaglione F, Luukkonen PK, Baselli G, et al. Exome-wide association study on alanine aminotransferase identifies sequence variants in the GPAM and APOE associated with fatty liver disease. Gastroenterology 2021;160:1634-1646 e7.
- 13. Gallagher MD, Chen-Plotkin AS. The post-GWAS era: From association to function. Am J Hum Genet 2018;102:717-730.
- 14. Mostafavi H, Spence JP, Naqvi S, Pritchard JK. Systematic differences in discovery of genetic effects on gene expression and complex traits. Nat Genet 2023;55:1866-1875.
- 15. Loomba R, Hartman ML, Lawitz EJ, Vuppalanchi R, Boursier J, Bugianesi E, et al. Tirzepatide for metabolic dysfunctionassociated steatohepatitis with liver fibrosis. N Engl J Med 2024;391:299-310.
- 16. Qayyum F, Lauridsen BK, Frikke-Schmidt R, Kofoed KF, Nordestgaard BG, Tybjærg-Hansen A. Genetic variants in CYP7A1 and risk of myocardial infarction and symptomatic gallstone disease. Eur Heart J 2018;39:2106-2116.
- 17. Pullinger CR, Eng C, Salen G, Shefer S, Batta AK, Erickson SK, et al. Human cholesterol 7alpha-hydroxylase (CYP7A1) deficiency has a hypercholesterolemic phenotype. J Clin Invest 2002;110:109-117.
- 18. Ferrell JM, Boehme S, Li F, Chiang JY. Cholesterol 7α-hydroxylase-deficient mice are protected from high-fat/highcholesterol diet-induced metabolic disorders. J Lipid Res 2016;57:1144-1154.
- 19. Jamialahmadi O, De Vincentis A, Tavaglione F, Malvestiti F, Li-Gao R, Mancina RM, et al. Partitioned polygenic risk scores identify distinct types of metabolic dysfunction-associated steatotic liver disease. Nat Med 2024;30:3614-3623.
- 20. Graff M, North KE, Franceschini N, Reiner AP, Feitosa M, Carr JJ, et al. PNPLA3 gene-by-visceral adipose tissue volume interaction and the pathogenesis of fatty liver disease: the NHLBI family heart study. Int J Obes (Lond) 2013;37:432-438.
