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      Multiomics study of nonalcoholic fatty liver disease

      research-article
      1 , , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 3 , 4 , 5 , 3 , 6 , DBDS Genomic consortium, 1 , 7 , 1 , 1 , 1 , 1 , 7 , 1 , 8 , 9 , 1 , 1 , 10 , 1 , 11 , 4 , 1 , 12 , 13 , 13 , 14 , 1 , 15 , 16 , 1 , 12 , 1 , 4 , 1 , 1 , 3 , 13 , 17 , 8 , 3 , 4 , 18 , 1 , 1 , 1 , 3 , 1 , 1 , 2 , 19 , 1 , 1 , 3 ,
      Nature Genetics
      Nature Publishing Group US
      Genome-wide association studies, Liver diseases

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          Abstract

          Nonalcoholic fatty liver (NAFL) and its sequelae are growing health problems. We performed a genome-wide association study of NAFL, cirrhosis and hepatocellular carcinoma, and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and 4 with cirrhosis, and found rare, protective, predicted loss-of-function variants in MTARC1 and GPAM, underscoring them as potential drug targets. We leveraged messenger RNA expression, splicing and predicted coding effects to identify 16 putative causal genes, of which many are implicated in lipid metabolism. We analyzed levels of 4,907 plasma proteins in 35,559 Icelanders and 1,459 proteins in 47,151 UK Biobank participants, identifying multiple proteins involved in disease pathogenesis. We show that proteomics can discriminate between NAFL and cirrhosis. The present study provides insights into the development of noninvasive evaluation of NAFL and new therapeutic options.

          Abstract

          Genome-wide analyses identify loci associated with nonalcoholic fatty liver disease, including rare, protective loss-of-function variants in MTARC1 and GPAM. Plasma proteomic analyses provide insight into proteins involved in disease pathogenesis.

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          Most cited references103

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes.

            Nonalcoholic fatty liver disease (NAFLD) is a major cause of liver disease worldwide. We estimated the global prevalence, incidence, progression, and outcomes of NAFLD and nonalcoholic steatohepatitis (NASH). PubMed/MEDLINE were searched from 1989 to 2015 for terms involving epidemiology and progression of NAFLD. Exclusions included selected groups (studies that exclusively enrolled morbidly obese or diabetics or pediatric) and no data on alcohol consumption or other liver diseases. Incidence of hepatocellular carcinoma (HCC), cirrhosis, overall mortality, and liver-related mortality were determined. NASH required histological diagnosis. All studies were reviewed by three independent investigators. Analysis was stratified by region, diagnostic technique, biopsy indication, and study population. We used random-effects models to provide point estimates (95% confidence interval [CI]) of prevalence, incidence, mortality and incidence rate ratios, and metaregression with subgroup analysis to account for heterogeneity. Of 729 studies, 86 were included with a sample size of 8,515,431 from 22 countries. Global prevalence of NAFLD is 25.24% (95% CI: 22.10-28.65) with highest prevalence in the Middle East and South America and lowest in Africa. Metabolic comorbidities associated with NAFLD included obesity (51.34%; 95% CI: 41.38-61.20), type 2 diabetes (22.51%; 95% CI: 17.92-27.89), hyperlipidemia (69.16%; 95% CI: 49.91-83.46%), hypertension (39.34%; 95% CI: 33.15-45.88), and metabolic syndrome (42.54%; 95% CI: 30.06-56.05). Fibrosis progression proportion, and mean annual rate of progression in NASH were 40.76% (95% CI: 34.69-47.13) and 0.09 (95% CI: 0.06-0.12). HCC incidence among NAFLD patients was 0.44 per 1,000 person-years (range, 0.29-0.66). Liver-specific mortality and overall mortality among NAFLD and NASH were 0.77 per 1,000 (range, 0.33-1.77) and 11.77 per 1,000 person-years (range, 7.10-19.53) and 15.44 per 1,000 (range, 11.72-20.34) and 25.56 per 1,000 person-years (range, 6.29-103.80). Incidence risk ratios for liver-specific and overall mortality for NAFLD were 1.94 (range, 1.28-2.92) and 1.05 (range, 0.70-1.56).
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              UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

              Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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                Author and article information

                Contributors
                gardars@decode.is
                kstefans@decode.is
                Journal
                Nat Genet
                Nat Genet
                Nature Genetics
                Nature Publishing Group US (New York )
                1061-4036
                1546-1718
                24 October 2022
                24 October 2022
                2022
                : 54
                : 11
                : 1652-1663
                Affiliations
                [1 ]GRID grid.421812.c, ISNI 0000 0004 0618 6889, deCODE genetics/Amgen, Inc., ; Reykjavik, Iceland
                [2 ]GRID grid.14013.37, ISNI 0000 0004 0640 0021, Faculty of Electrical and Computer Engineering, , University of Iceland, ; Reykjavik, Iceland
                [3 ]GRID grid.14013.37, ISNI 0000 0004 0640 0021, Faculty of Medicine, , University of Iceland, ; Reykjavik, Iceland
                [4 ]GRID grid.410540.4, ISNI 0000 0000 9894 0842, Internal Medicine and Emergency Services, , Landspitali—The National University Hospital of Iceland, ; Reykjavik, Iceland
                [5 ]Röntgen Domus, Reykjavík, Iceland
                [6 ]GRID grid.410540.4, ISNI 0000 0000 9894 0842, Children’s Medical Center, , Landspítali—The National University Hospital of Iceland, ; Reykjavík, Iceland
                [7 ]GRID grid.154185.c, ISNI 0000 0004 0512 597X, Department of Clinical Immunology, , Aarhus University Hospital, ; Aarhus, Denmark
                [8 ]GRID grid.420884.2, ISNI 0000 0004 0460 774X, Intermountain Healthcare, ; St. George, UT USA
                [9 ]GRID grid.420884.2, ISNI 0000 0004 0460 774X, Intermountain Healthcare, ; Salt Lake City, UT USA
                [10 ]GRID grid.14013.37, ISNI 0000 0004 0640 0021, Faculty of Mechanical Engineering, Industrial Engineering and Computer Science, , University of Iceland, ; Reykjavik, Iceland
                [11 ]GRID grid.410540.4, ISNI 0000 0000 9894 0842, Clinical Laboratory Services, Diagnostics and Blood Bank, , Landspitali—The National University Hospital of Iceland, ; Reykjavik, Iceland
                [12 ]GRID grid.475435.4, Department of Clinical Immunology, , Copenhagen University Hospital, Rigshospitalet, ; Cophenhagen, Denmark
                [13 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Department of Clinical Medicine, , University of Copenhagen, ; Copenhagen, Denmark
                [14 ]GRID grid.512923.e, ISNI 0000 0004 7402 8188, Department of Clinical Immunology, , Zealand University Hospital, ; Køge, Denmark
                [15 ]Development Centre for Primary Health Care in Iceland, Reykjavík, Iceland
                [16 ]GRID grid.14013.37, ISNI 0000 0004 0640 0021, Department of Family Medicine, , University of Iceland, ; Reykjavik, Iceland
                [17 ]GRID grid.475435.4, Department of Cardiology, The Heart Centre, , Copenhagen University Hospital, Rigshospitalet, ; Copenhagen, Denmark
                [18 ]GRID grid.417886.4, ISNI 0000 0001 0657 5612, Amgen, Cardiometabolic Disorders, ; South San Francisco, CA USA
                [19 ]GRID grid.14013.37, ISNI 0000 0004 0640 0021, School of Engineering and Natural Sciences, , University of Iceland, ; Reykjavik, Iceland
                Author information
                http://orcid.org/0000-0003-2429-9468
                http://orcid.org/0000-0003-1009-7398
                http://orcid.org/0000-0001-6551-6647
                http://orcid.org/0000-0002-1806-2467
                http://orcid.org/0000-0001-9439-3906
                http://orcid.org/0000-0002-9580-6685
                http://orcid.org/0000-0002-3806-2296
                http://orcid.org/0000-0002-1842-8799
                http://orcid.org/0000-0001-5288-3851
                http://orcid.org/0000-0003-2312-5976
                http://orcid.org/0000-0002-3496-2991
                http://orcid.org/0000-0003-1846-6274
                http://orcid.org/0000-0003-4623-9087
                http://orcid.org/0000-0001-8339-150X
                http://orcid.org/0000-0003-0491-7046
                http://orcid.org/0000-0002-9517-6636
                http://orcid.org/0000-0003-1676-864X
                Article
                1199
                10.1038/s41588-022-01199-5
                9649432
                36280732
                6122e98b-4f4c-4115-955f-3549e48bae6c
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 December 2021
                : 2 September 2022
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                © The Author(s), under exclusive licence to Springer Nature America, Inc. 2022

                Genetics
                genome-wide association studies,liver diseases
                Genetics
                genome-wide association studies, liver diseases

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