GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network

Bahram Namjou; Todd Lingren; Yongbo Huang; Sreeja Parameswaran; Beth L Cobb; Ian B Stanaway; John J Connolly; Frank D Mentch; Barbara Benoit; Xinnan Niu; Wei-Qi Wei; Robert J Carroll; Jennifer A Pacheco; Isaac T W Harley; Senad Divanovic; David S Carrell; Eric B Larson; David J Carey; Shefali Verma; Marylyn D Ritchie; Ali G Gharavi; Shawn Murphy; Marc S Williams; David R Crosslin; Gail P Jarvik; Iftikhar J Kullo; Hakon Hakonarson; Rongling Li; eMERGE Network; Stavra A Xanthakos; John B Harley

doi:10.1186/s12916-019-1364-z

GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network

BMC Med. 2019 Jul 17;17(1):135. doi: 10.1186/s12916-019-1364-z.

Authors

Bahram Namjou^{1

2}, Todd Lingren^{3

4}, Yongbo Huang⁵, Sreeja Parameswaran⁵, Beth L Cobb⁵, Ian B Stanaway⁶, John J Connolly⁷, Frank D Mentch⁷, Barbara Benoit⁸, Xinnan Niu⁹, Wei-Qi Wei⁹, Robert J Carroll⁹, Jennifer A Pacheco¹⁰, Isaac T W Harley¹¹, Senad Divanovic¹¹, David S Carrell¹², Eric B Larson¹², David J Carey¹³, Shefali Verma¹⁴, Marylyn D Ritchie¹⁴, Ali G Gharavi¹⁵, Shawn Murphy¹⁶, Marc S Williams¹⁷, David R Crosslin⁶, Gail P Jarvik¹⁸, Iftikhar J Kullo¹⁹, Hakon Hakonarson^{7

20}, Rongling Li²¹; eMERGE Network; Stavra A Xanthakos²², John B Harley^{5

3

23}

Affiliations

¹ Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA. bahram.namjou@cchmc.org.
² College of Medicine, University of Cincinnati, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA. bahram.namjou@cchmc.org.
³ College of Medicine, University of Cincinnati, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA.
⁴ Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
⁵ Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA.
⁶ Department of Biomedical Informatics Medical Education, School of Medicine, University of Washington, Seattle, WA, USA.
⁷ Center for Applied Genomics, Children's Hospital of Philadelphia, Bethesda, MD, USA.
⁸ Research IS and Computing, Partners HealthCare, Harvard University, Somerville, MA, USA.
⁹ Departments of Biomedical Informatics and Medicine, Vanderbilt University, Nashville, TN, USA.
¹⁰ Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
¹¹ Division of Immunobiology, Department of Pediatrics, Cincinnati Children's Hospital Research Foundation and the University of Cincinnati College of Medicine, Cincinnati, OH, USA.
¹² Kaiser Permanente Washington Health Research Institute (Formerly Group Health Cooperative-Seattle), Kaiser Permanente, Seattle, WA, USA.
¹³ Department of Molecular and Functional Genomics, Geisinger, Danville, PA, USA.
¹⁴ Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
¹⁵ Department of Medicine, Columbia University, New York City, NY, USA.
¹⁶ Research Information Science and Computing, Partners HealthCare, Boston, MA, USA.
¹⁷ Genomic Medicine Institute (M.S.W.), Geisinger, Danville, PA, USA.
¹⁸ Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington Medical Center, Seattle, WA, USA.
¹⁹ Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.
²⁰ Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
²¹ National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
²² Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati School of Medicine, Cincinnati, OH, USA.
²³ U.S. Department of Veterans Affairs Medical Center, Cincinnati, OH, USA.

Abstract

Background: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pathogenesis and progression of NAFLD is complex with many unanswered questions. We conducted genome-wide association studies (GWASs) using both adult and pediatric participants from the Electronic Medical Records and Genomics (eMERGE) Network to identify novel genetic contributors to this condition.

Methods: First, a natural language processing (NLP) algorithm was developed, tested, and deployed at each site to identify 1106 NAFLD cases and 8571 controls and histological data from liver tissue in 235 available participants. These include 1242 pediatric participants (396 cases, 846 controls). The algorithm included billing codes, text queries, laboratory values, and medication records. Next, GWASs were performed on NAFLD cases and controls and case-only analyses using histologic scores and liver function tests adjusting for age, sex, site, ancestry, PC, and body mass index (BMI).

Results: Consistent with previous results, a robust association was detected for the PNPLA3 gene cluster in participants with European ancestry. At the PNPLA3-SAMM50 region, three SNPs, rs738409, rs738408, and rs3747207, showed strongest association (best SNP rs738409 p = 1.70 × 10^{- 20}). This effect was consistent in both pediatric (p = 9.92 × 10^{- 6}) and adult (p = 9.73 × 10^{- 15}) cohorts. Additionally, this variant was also associated with disease severity and NAFLD Activity Score (NAS) (p = 3.94 × 10^{- 8}, beta = 0.85). PheWAS analysis link this locus to a spectrum of liver diseases beyond NAFLD with a novel negative correlation with gout (p = 1.09 × 10^{- 4}). We also identified novel loci for NAFLD disease severity, including one novel locus for NAS score near IL17RA (rs5748926, p = 3.80 × 10^{- 8}), and another near ZFP90-CDH1 for fibrosis (rs698718, p = 2.74 × 10^{- 11}). Post-GWAS and gene-based analyses identified more than 300 genes that were used for functional and pathway enrichment analyses.

Conclusions: In summary, this study demonstrates clear confirmation of a previously described NAFLD risk locus and several novel associations. Further collaborative studies including an ethnically diverse population with well-characterized liver histologic features of NAFLD are needed to further validate the novel findings.

Keywords: Fatty liver; GWAS; Genetic polymorphism; NAFLD; PheWAS; Polygenic risk score.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Adult
Aged
Body Mass Index
Case-Control Studies
Community Networks / organization & administration
Community Networks / statistics & numerical data
Disease Progression
Electronic Health Records / organization & administration
Electronic Health Records / statistics & numerical data
Female
Genetic Predisposition to Disease
Genome-Wide Association Study
Genomics / organization & administration
Genomics / statistics & numerical data
Humans
Lipase / genetics
Male
Membrane Proteins / genetics
Middle Aged
Morbidity
Non-alcoholic Fatty Liver Disease / epidemiology
Non-alcoholic Fatty Liver Disease / genetics*
Phenotype
Polymorphism, Single Nucleotide
Signal Transduction / genetics

Substances

Membrane Proteins
Lipase
adiponutrin, human

Abstract

Publication types

MeSH terms

Substances

Grants and funding