Integrative common and rare variant analyses provide insights into the genetic architecture of liver cirrhosis.

Journal

Nature genetics

ISSN: 1546-1718

Titre abrégé: Nat Genet

Pays: United States

ID NLM: 9216904

Informations de publication

Date de publication:
17 Apr 2024

Historique:

received: 23 06 2023

accepted: 18 03 2024

medline: 18 4 2024

pubmed: 18 4 2024

entrez: 17 4 2024

Statut: aheadofprint

Résumé

We report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from common variant analyses, we find that rare coding variants in GPAM associate with lower ALT, supporting GPAM as a potential target for therapeutic inhibition. In conclusion, this study provides insights into the genetic underpinnings of cirrhosis.

Identifiants

DOI: 10.1038/s41588-024-01720-y PMID: 38632349

pubmed: 38632349

doi: 10.1038/s41588-024-01720-y

pii: 10.1038/s41588-024-01720-y

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Investigateurs

Luca A Lotta (LA)

Informations de copyright

Références

Ginès, P. et al. Liver cirrhosis. Lancet Lond. Engl. 398, 1359–1376 (2021).

doi: 10.1016/S0140-6736(21)01374-X

Huang, D. Q. et al. Global epidemiology of cirrhosis—aetiology, trends and predictions. Nat. Rev. Gastroenterol. Hepatol. 20, 388–398 (2023).

pubmed: 36977794 pmcid: 10043867 doi: 10.1038/s41575-023-00759-2

Loomba, R. et al. Heritability of hepatic fibrosis and steatosis based on a prospective twin study. Gastroenterology 149, 1784–1793 (2015).

pubmed: 26299412 doi: 10.1053/j.gastro.2015.08.011

Emdin, C. A. et al. Association of genetic variation with cirrhosis: a multi-trait genome-wide association and gene–environment interaction study. Gastroenterology 160, 1620–1633 (2021).

pubmed: 33310085 doi: 10.1053/j.gastro.2020.12.011

Gellert-Kristensen, H. et al. Combined effect of PNPLA3, TM6SF2, and HSD17B13 variants on risk of cirrhosis and hepatocellular carcinoma in the general population. Hepatology 72, 845–856 (2020).

pubmed: 32190914 doi: 10.1002/hep.31238

Abul-Husn, N. S. et al. A protein-truncating HSD17B13 variant and protection from chronic liver disease. N. Engl. J. Med. 378, 1096–1106 (2018).

pubmed: 29562163 pmcid: 6668033 doi: 10.1056/NEJMoa1712191

Emdin, C. A. et al. A missense variant in mitochondrial amidoxime reducing component 1 gene and protection against liver disease. PLoS Genet. 16, e1008629 (2020).

pubmed: 32282858 pmcid: 7200007 doi: 10.1371/journal.pgen.1008629

Schneider, C. V. et al. A genome-first approach to mortality and metabolic phenotypes in MTARC1 p.Ala165Thr (rs2642438) heterozygotes and homozygotes. Med 2, 851–863 (2021).

pubmed: 34258604 doi: 10.1016/j.medj.2021.04.011

Verweij, N. et al. Germline mutations in CIDEB and protection against liver disease. N. Engl. J. Med. 387, 332–344 (2022).

pubmed: 35939579 doi: 10.1056/NEJMoa2117872

Buch, S. et al. A genome-wide association study confirms PNPLA3 and identifies TM6SF2 and MBOAT7 as risk loci for alcohol-related cirrhosis. Nat. Genet. 47, 1443–1448 (2015).

pubmed: 26482880 doi: 10.1038/ng.3417

Stender, S. et al. Adiposity amplifies the genetic risk of fatty liver disease conferred by multiple loci. Nat. Genet. 49, 842–847 (2017).

pubmed: 28436986 pmcid: 5562020 doi: 10.1038/ng.3855

GTEX ConsortiumThe GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020).

doi: 10.1126/science.aaz1776

Mikaelsdottir, E. et al. Genetic variants associated with platelet count are predictive of human disease and physiological markers. Commun. Biol. 4, 1–13 (2021).

doi: 10.1038/s42003-021-02642-9

Ferkingstad, E. et al. Large-scale integration of the plasma proteome with genetics and disease. Nat. Genet. 53, 1712–1721 (2021).

pubmed: 34857953 doi: 10.1038/s41588-021-00978-w

Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature 622, 329–338 (2023).

Akbari, P. et al. Multiancestry exome sequencing reveals INHBE mutations associated with favorable fat distribution and protection from diabetes. Nat. Commun. 13, 4844 (2022).

pubmed: 35999217 pmcid: 9399235 doi: 10.1038/s41467-022-32398-7

Lotta, L. A. et al. Association of genetic variants related to gluteofemoral vs abdominal fat distribution with type 2 diabetes, coronary disease, and cardiovascular risk factors. JAMA 320, 2553–2563 (2018).

pubmed: 30575882 pmcid: 6583513 doi: 10.1001/jama.2018.19329

Pulit, S. L. et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum. Mol. Genet. 28, 166–174 (2019).

pubmed: 30239722 doi: 10.1093/hmg/ddy327

Cho, Y. et al. Genetic influences on alcohol flushing in East Asian population. BMC Genomics 24, 638 (2023).

Sveinbjornsson, G. et al. Multiomics study of nonalcoholic fatty liver disease. Nat. Genet. 54, 1652–1663 (2022).

pubmed: 36280732 pmcid: 9649432 doi: 10.1038/s41588-022-01199-5

Jamialahmadi, O. et al. Exome-wide association study on alanine aminotransferase identifies sequence variants in the GPAM and APOE associated with fatty liver disease. Gastroenterology 160, 1634–1646 (2021).

pubmed: 33347879 doi: 10.1053/j.gastro.2020.12.023

Hakim, A. et al. Genetic variation in the mitochondrial glycerol-3-phosphate acyltransferase is associated with liver injury. Hepatology 74, 3394–3408 (2021).

pubmed: 34216018 doi: 10.1002/hep.32038

Vujkovic, M. 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. 54, 761–771 (2022).

pubmed: 35654975 pmcid: 10024253 doi: 10.1038/s41588-022-01078-z

Koyama, S. et al. Population-specific and trans-ancestry genome-wide analyses identify distinct and shared genetic risk loci for coronary artery disease. Nat. Genet. 52, 1169–1177 (2020).

pubmed: 33020668 doi: 10.1038/s41588-020-0705-3

Márquez-Luna, C., Loh, P.-R. & Price, A. L. South Asian Type 2 Diabetes (SAT2D) Consortium, SIGMA Type 2 Diabetes Consortium Multiethnic polygenic risk scores improve risk prediction in diverse populations. Genet. Epidemiol. 41, 811–823 (2017).

pubmed: 29110330 pmcid: 5726434 doi: 10.1002/gepi.22083

Kurniansyah, N. et al. A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. Nat. Commun. 13, 3549 (2022).

pubmed: 35729114 pmcid: 9213527 doi: 10.1038/s41467-022-31080-2

Ge, T. et al. Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations. Genome Med. 14, 70 (2022).

pubmed: 35765100 pmcid: 9241245 doi: 10.1186/s13073-022-01074-2

Kamatani, Y. et al. A genome-wide association study identifies variants in the HLA-DP locus associated with chronic hepatitis B in Asians. Nat. Genet. 41, 591–595 (2009).

pubmed: 19349983 doi: 10.1038/ng.348

Westerman, K. E. et al. Variance-quantitative trait loci enable systematic discovery of gene–environment interactions for cardiometabolic serum biomarkers. Nat. Commun. 13, 3993 (2022).

pubmed: 35810165 pmcid: 9271055 doi: 10.1038/s41467-022-31625-5

Lyon, M. S., Millard, L. A. C., Smith, G. D., Gaunt, T. R. & Tilling, K. Hypothesis-free detection of gene-interaction effects on biomarker concentration in UK Biobank using variance prioritisation. Preprint at medRxiv https://doi.org/10.1101/2022.01.05.21268406 (2022).

Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

pubmed: 20616382 pmcid: 2922887 doi: 10.1093/bioinformatics/btq340

Bulik-Sullivan, B. K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

pubmed: 25642630 pmcid: 4495769 doi: 10.1038/ng.3211

Nielsen, J. B. et al. Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease. Nat. Commun. 11, 6417 (2020).

pubmed: 33339817 pmcid: 7749177 doi: 10.1038/s41467-020-20086-3

Pazoki, R. et al. Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes. Nat. Commun. 12, 2579 (2021).

pubmed: 33972514 pmcid: 8110798 doi: 10.1038/s41467-021-22338-2

El-Serag, H. B. et al. Risk factors for cirrhosis in contemporary hepatology practices—findings from Texas Hepatocellular Carcinoma Consortium Cohort. Gastroenterology 159, 376–377 (2020).

pubmed: 32234536 doi: 10.1053/j.gastro.2020.03.049

Davies, N. M., Holmes, M. V. & Smith, G. D. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ 362, k601 (2018).

pubmed: 30002074 pmcid: 6041728 doi: 10.1136/bmj.k601

McLaren, W. et al. The ensembl variant effect predictor. Genome Biol. 17, 122 (2016).

pubmed: 27268795 pmcid: 4893825 doi: 10.1186/s13059-016-0974-4

Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).

pubmed: 24830394 pmcid: 4022491 doi: 10.1371/journal.pgen.1004383

Wallace, C. Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses. PLoS Genet. 16, e1008720 (2020).

pubmed: 32310995 pmcid: 7192519 doi: 10.1371/journal.pgen.1008720

Weeks, E. M. et al. Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases. Nat. Genet. 55, 1267–1276 (2023).

De Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).

pubmed: 25885710 pmcid: 4401657 doi: 10.1371/journal.pcbi.1004219

Backman, J. D. et al. Exome sequencing and analysis of 454,787 UK Biobank participants. Nature 599, 628–634 (2021).

pubmed: 34662886 pmcid: 8596853 doi: 10.1038/s41586-021-04103-z

Mbatchou, J. et al. Computationally efficient whole-genome regression for quantitative and binary traits. Nat. Genet. 53, 1097–1103 (2021).

pubmed: 34017140 doi: 10.1038/s41588-021-00870-7

Ge, T., Chen, C.-Y., Ni, Y., Feng, Y.-C. A. & Smoller, J. W. Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat. Commun. 10, 1776 (2019).

pubmed: 30992449 pmcid: 6467998 doi: 10.1038/s41467-019-09718-5

Lee, S. H., Goddard, M. E., Wray, N. R. & Visscher, P. M. A better coefficient of determination for genetic profile analysis. Genet. Epidemiol. 36, 214–224 (2012).

pubmed: 22714935 doi: 10.1002/gepi.21614

Robin, X. et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12, 77 (2011).

pubmed: 21414208 pmcid: 3068975 doi: 10.1186/1471-2105-12-77

Aalen, O. O. & Johansen, S. An empirical transition matrix for non-homogeneous Markov chains based on censored observations. Scand. J. Stat. 5, 141–150 (1978).