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      Genome‐Wide Association Study of NAFLD Using Electronic Health Records

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          Abstract

          Genome‐wide association studies (GWAS) have identified several risk loci for nonalcoholic fatty liver disease (NAFLD). Previous studies have largely relied on small sample sizes and have assessed quantitative traits. We performed a case‐control GWAS in the UK Biobank using recorded diagnosis of NAFLD based on diagnostic codes recommended in recent consensus guidelines. We performed a GWAS of 4,761 cases of NAFLD and 373,227 healthy controls without evidence of NAFLD. Sensitivity analyses were performed excluding other co‐existing hepatic pathology, adjusting for body mass index (BMI) and adjusting for alcohol intake. A total of 9,723,654 variants were assessed by logistic regression adjusted for age, sex, genetic principal components, and genotyping batch. We performed a GWAS meta‐analysis using available summary association statistics. Six risk loci were identified ( P < 5*10 −8) (apolipoprotein E [ APOE], patatin‐like phospholipase domain containing 3 [ PNPLA3, transmembrane 6 superfamily member 2 [ TM6SF2], glucokinase regulator [ GCKR], mitochondrial amidoxime reducing component 1 [ MARC1], and tribbles pseudokinase 1 [ TRIB1]). All loci retained significance in sensitivity analyses without co‐existent hepatic pathology and after adjustment for BMI. PNPLA3 and TM6SF2 remained significant after adjustment for alcohol (alcohol intake was known in only 158,388 individuals), with others demonstrating consistent direction and magnitude of effect. All six loci were significant on meta‐analysis. Rs429358 ( P = 2.17*10 −11) is a missense variant within the APOE gene determining ϵ4 versus ϵ2/ϵ3 alleles. The ϵ4 allele of APOE offered protection against NAFLD (odds ratio for heterozygotes 0.84 [95% confidence interval 0.78‐0.90] and homozygotes 0.64 [0.50‐0.79]). Conclusion: This GWAS replicates six known NAFLD‐susceptibility loci and confirms that the ϵ4 allele of APOE is associated with protection against NAFLD. The results are consistent with published GWAS using histological and radiological measures of NAFLD, confirming that NAFLD identified through diagnostic codes from consensus guidelines is a valid alternative to more invasive and costly approaches.

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          Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention

          NAFLD is one of the most important causes of liver disease worldwide and will probably emerge as the leading cause of end-stage liver disease in the coming decades, with the disease affecting both adults and children. The epidemiology and demographic characteristics of NAFLD vary worldwide, usually parallel to the prevalence of obesity, but a substantial proportion of patients are lean. The large number of patients with NAFLD with potential for progressive liver disease creates challenges for screening, as the diagnosis of NASH necessitates invasive liver biopsy. Furthermore, individuals with NAFLD have a high frequency of metabolic comorbidities and could place a growing strain on health-care systems from their need for management. While awaiting the development effective therapies, this disease warrants the attention of primary care physicians, specialists and health policy makers.
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            LD Score regression distinguishes confounding from polygenicity in genome-wide association studies.

            Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.
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              METAL: fast and efficient meta-analysis of genomewide association scans

              Summary: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: goncalo@umich.edu
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                Author and article information

                Contributors
                ewen.harrison@ed.ac.uk
                Journal
                Hepatol Commun
                Hepatol Commun
                10.1002/(ISSN)2471-254X
                HEP4
                Hepatology Communications
                John Wiley and Sons Inc. (Hoboken )
                2471-254X
                17 September 2021
                February 2022
                : 6
                : 2 ( doiID: 10.1002/hep4.v6.2 )
                : 297-308
                Affiliations
                [ 1 ] Centre for Medical Informatics Usher Institute University of Edinburgh Edinburgh Scotland
                [ 2 ] MRC Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh Scotland
                [ 3 ] Centre for Genomic and Experimental Medicine Institute of Genetics & Molecular Medicine University of Edinburgh Edinburgh Scotland
                [ 4 ] Health Data Research UK University of Edinburgh Edinburgh Scotland
                [ 5 ] Centre for Global Health Research Usher Institute University of Edinburgh Edingburgh Scotland
                [ 6 ] Centre for Inflammation Research Queen’s Medical Research Institute University of Edinburgh Edingburgh Scotland
                [ 7 ] Centre for Cardiovascular Science Queen’s Medical Research Institute University of Edinburgh Edingburgh Scotland
                [ 8 ] Department of Clinical Surgery Division of Health Sciences University of Edinburgh Edingburgh Scotland
                Author notes
                [*] [* ] ADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO:

                Ewen M. Harrison, Ph.D.

                Centre for Medical Informatics, NINE Bioquarter

                Little France Road

                Edinburgh, EH16 4UX, Scotland

                E‐mail: ewen.harrison@ 123456ed.ac.uk

                Tel.: +0131‐242‐3616

                [ * ]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0001-7635-1868
                https://orcid.org/0000-0002-5741-1471
                https://orcid.org/0000-0002-2273-4094
                Article
                HEP41805
                10.1002/hep4.1805
                8793997
                34535985
                77994012-0173-4061-91d4-d446dd3847b4
                © 2021 The Authors. Hepatology Communications published by Wiley Periodicals LLC on behalf of the American Association for the Study of Liver Diseases.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 02 June 2021
                : 04 July 2021
                Page count
                Figures: 5, Tables: 2, Pages: 12, Words: 7384
                Funding
                Funded by: Medical Research Council , doi 10.13039/501100000265;
                Award ID: MR/T008008/1
                Award ID: U. MC_UU_00007/10
                Funded by: Wellcome Trust , doi 10.13039/100010269;
                Award ID: 104036/Z/14/Z
                Award ID: 204979/Z/16/Z
                Award ID: 210752/Z/18/Z
                Award ID: 216767/Z/19/Z
                Award ID: 219542/Z/19/Z
                Funded by: Scottish Funding Council , doi 10.13039/501100000360;
                Award ID: HR03006
                Funded by: Chief Scientist Office , doi 10.13039/501100000589;
                Award ID: CZD/16/6
                Funded by: British Heart Foundation , doi 10.13039/501100000274;
                Award ID: FS/16/14/32023
                Award ID: RE/18/5/34216
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                February 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.0 mode:remove_FC converted:27.01.2022

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