Systematic analysis of the gene expression in the livers of nonalcoholic steatohepatitis: implications on potential biomarkers and molecular pathological mechanism
Non-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic fatty liver disease (NAFLD). The molecular pathological mechanism of NASH is poorly understood. Recently, high throughput data such as microarray data together with bioinformatics methods have become a powerful way to identify bi...
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description | Non-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic fatty liver disease (NAFLD). The molecular pathological mechanism of NASH is poorly understood. Recently, high throughput data such as microarray data together with bioinformatics methods have become a powerful way to identify biomarkers and to investigate pathogenesis of diseases. Taking advantage of well characterized microarray datasets of NASH livers, we performed a systematic analysis of potential biomarkers and possible pathological mechanism of NASH from a bioinformatics perspective.CodeLink Human Whole Genome Bioarrays were analyzed to find differentially expressed genes (DEGs) between controls and NASH patients. Four methods were used to identify DEGs and the intersection of DEGs identified by these methods was subsequently used for both biomarker prediction and molecular pathological mechanism analysis. For biomarker prediction, rank aggregation was used to rank DEGs identified by all these methods according to their significance of different expression. Alcohol dehydrogenase 4 (ADH4) exhibited the highest rank suggesting the most significant differential expression between normal and disease condition. Together with the previous report demonstrating the association between ADH4 and the pathogenesis of NASH, our data suggest that ADH4 could be a potential biomarker for NASH. For molecular pathological mechanism analysis, two clusters of highly correlated annotation terms and genes in these terms were identified based on the intersection of DEGs. Then, pathways enriched with these genes were identified to construct the network. Using this network, both for the first time, amino acid catabolism is implicated to play a pivotal role and urea cycle is implicated to be involved in the development of NASH.The results of our study identified potential biomarkers and suggested possible molecular pathological mechanism of NASH. These findings provide a comprehensive and systematic understanding of the pathogenesis of NASH and may facilitate the diagnosis, prevention and treatment of NASH. |
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The molecular pathological mechanism of NASH is poorly understood. Recently, high throughput data such as microarray data together with bioinformatics methods have become a powerful way to identify biomarkers and to investigate pathogenesis of diseases. Taking advantage of well characterized microarray datasets of NASH livers, we performed a systematic analysis of potential biomarkers and possible pathological mechanism of NASH from a bioinformatics perspective.CodeLink Human Whole Genome Bioarrays were analyzed to find differentially expressed genes (DEGs) between controls and NASH patients. Four methods were used to identify DEGs and the intersection of DEGs identified by these methods was subsequently used for both biomarker prediction and molecular pathological mechanism analysis. For biomarker prediction, rank aggregation was used to rank DEGs identified by all these methods according to their significance of different expression. Alcohol dehydrogenase 4 (ADH4) exhibited the highest rank suggesting the most significant differential expression between normal and disease condition. Together with the previous report demonstrating the association between ADH4 and the pathogenesis of NASH, our data suggest that ADH4 could be a potential biomarker for NASH. For molecular pathological mechanism analysis, two clusters of highly correlated annotation terms and genes in these terms were identified based on the intersection of DEGs. Then, pathways enriched with these genes were identified to construct the network. Using this network, both for the first time, amino acid catabolism is implicated to play a pivotal role and urea cycle is implicated to be involved in the development of NASH.The results of our study identified potential biomarkers and suggested possible molecular pathological mechanism of NASH. These findings provide a comprehensive and systematic understanding of the pathogenesis of NASH and may facilitate the diagnosis, prevention and treatment of NASH.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0051131</identifier><identifier>PMID: 23300535</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>ADH4 protein ; Alcohol dehydrogenase ; Alcoholic beverages ; Alcoholism ; Amino acids ; Analysis ; Annotations ; Bioindicators ; Bioinformatics ; Biological markers ; Biology ; Biomarkers ; Biomarkers - metabolism ; Biopsy ; Catabolism ; Cluster analysis ; Computational Biology ; Correlation analysis ; Dehydrogenases ; Diabetes ; DNA microarrays ; Ethanol ; Fatty acids ; Fatty liver ; Fatty Liver - genetics ; Fatty Liver - pathology ; Gene expression ; Gene Expression Profiling ; Genes ; Genetic research ; Genomes ; Hepatitis ; Hepatology ; Humans ; Identification methods ; Lipids ; Liver ; Liver cancer ; Liver diseases ; Medical research ; Medicine ; Metabolism ; Non-alcoholic Fatty Liver Disease ; Nutrition ; Obesity ; Oligonucleotide Array Sequence Analysis ; Oxidative stress ; Pathogenesis ; Pathology, Molecular ; Pediatrics ; Real-Time Polymerase Chain Reaction ; Reverse Transcriptase Polymerase Chain Reaction ; RNA, Messenger - genetics ; Rodents ; Signal Transduction ; Studies ; Type 2 diabetes ; Urea</subject><ispartof>PloS one, 2012-12, Vol.7 (12), p.e51131-e51131</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>2012 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2012 Zhang et al 2012 Zhang et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c758t-49a1bb31dd61df0e5f9fb8a29d80863077103d020bc336e56e810c87df89e04e3</citedby><cites>FETCH-LOGICAL-c758t-49a1bb31dd61df0e5f9fb8a29d80863077103d020bc336e56e810c87df89e04e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530598/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530598/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23300535$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Alisi, Anna</contributor><creatorcontrib>Zhang, Yida</creatorcontrib><creatorcontrib>Baker, Susan S</creatorcontrib><creatorcontrib>Baker, Robert D</creatorcontrib><creatorcontrib>Zhu, Ruixin</creatorcontrib><creatorcontrib>Zhu, Lixin</creatorcontrib><title>Systematic analysis of the gene expression in the livers of nonalcoholic steatohepatitis: implications on potential biomarkers and molecular pathological mechanism</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Non-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic fatty liver disease (NAFLD). The molecular pathological mechanism of NASH is poorly understood. Recently, high throughput data such as microarray data together with bioinformatics methods have become a powerful way to identify biomarkers and to investigate pathogenesis of diseases. Taking advantage of well characterized microarray datasets of NASH livers, we performed a systematic analysis of potential biomarkers and possible pathological mechanism of NASH from a bioinformatics perspective.CodeLink Human Whole Genome Bioarrays were analyzed to find differentially expressed genes (DEGs) between controls and NASH patients. Four methods were used to identify DEGs and the intersection of DEGs identified by these methods was subsequently used for both biomarker prediction and molecular pathological mechanism analysis. For biomarker prediction, rank aggregation was used to rank DEGs identified by all these methods according to their significance of different expression. Alcohol dehydrogenase 4 (ADH4) exhibited the highest rank suggesting the most significant differential expression between normal and disease condition. Together with the previous report demonstrating the association between ADH4 and the pathogenesis of NASH, our data suggest that ADH4 could be a potential biomarker for NASH. For molecular pathological mechanism analysis, two clusters of highly correlated annotation terms and genes in these terms were identified based on the intersection of DEGs. Then, pathways enriched with these genes were identified to construct the network. Using this network, both for the first time, amino acid catabolism is implicated to play a pivotal role and urea cycle is implicated to be involved in the development of NASH.The results of our study identified potential biomarkers and suggested possible molecular pathological mechanism of NASH. These findings provide a comprehensive and systematic understanding of the pathogenesis of NASH and may facilitate the diagnosis, prevention and treatment of NASH.</description><subject>ADH4 protein</subject><subject>Alcohol dehydrogenase</subject><subject>Alcoholic beverages</subject><subject>Alcoholism</subject><subject>Amino acids</subject><subject>Analysis</subject><subject>Annotations</subject><subject>Bioindicators</subject><subject>Bioinformatics</subject><subject>Biological markers</subject><subject>Biology</subject><subject>Biomarkers</subject><subject>Biomarkers - metabolism</subject><subject>Biopsy</subject><subject>Catabolism</subject><subject>Cluster analysis</subject><subject>Computational Biology</subject><subject>Correlation analysis</subject><subject>Dehydrogenases</subject><subject>Diabetes</subject><subject>DNA microarrays</subject><subject>Ethanol</subject><subject>Fatty acids</subject><subject>Fatty liver</subject><subject>Fatty Liver - genetics</subject><subject>Fatty Liver - pathology</subject><subject>Gene expression</subject><subject>Gene Expression Profiling</subject><subject>Genes</subject><subject>Genetic research</subject><subject>Genomes</subject><subject>Hepatitis</subject><subject>Hepatology</subject><subject>Humans</subject><subject>Identification methods</subject><subject>Lipids</subject><subject>Liver</subject><subject>Liver cancer</subject><subject>Liver diseases</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Metabolism</subject><subject>Non-alcoholic Fatty Liver Disease</subject><subject>Nutrition</subject><subject>Obesity</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Oxidative stress</subject><subject>Pathogenesis</subject><subject>Pathology, Molecular</subject><subject>Pediatrics</subject><subject>Real-Time Polymerase Chain Reaction</subject><subject>Reverse Transcriptase Polymerase Chain Reaction</subject><subject>RNA, Messenger - genetics</subject><subject>Rodents</subject><subject>Signal Transduction</subject><subject>Studies</subject><subject>Type 2 diabetes</subject><subject>Urea</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk91u1DAQhSMEoqXwBggiISG42MWOkzjhAqmq-FmpUiUK3FqOM9m4OHYaO1X3eXhRZnfTaoN6gXKRePKd48yJJ4peUrKkjNMPV24crDTL3llYEpJRyuij6JiWLFnkCWGPD56PomfeXyHEijx_Gh0ljG0X2XH053LjA3QyaBVLtNt47WPXxKGFeA0WYrjtB_BeOxtruysbfQPDDrIOFcq1zqAabWRwLfToFbT_GOuuxzqunEXaxr0LYIOWJq606-Twe-sibR13zoAajRxi1KKZW6PMxB2oVlrtu-fRk0YaDy-m-0n088vnH2ffFucXX1dnp-cLxbMiLNJS0qpitK5zWjcEsqZsqkImZV2QImeEc0pYTRJSKcZyyHIoKFEFr5uiBJICO4le731747yY8vWCsoQnNMcwkVjtidrJK9EPGtvYCCe12BXcsBZywCgNCK4qCmnaUMKLtJa8TLM6LbkEWpEmUxK9Pk27jVUHtcJsBmlmpvM3Vrdi7W4EyxjJygIN3k0Gg7sewQfRaa_AGGnBjfjdCWcsZVmZIvrmH_Th7iZqLbEBbRuH-6qtqThNOScpZXmO1PIBCq8aOq3wMDYa6zPB-5kAmQC3YS1H78Xq8vv_sxe_5uzbA7YFaULrnRl3B24OpntQDc77AZr7kCkR21m6S0NsZ0lMs4SyV4c_6F50NzzsL-7XHZc</recordid><startdate>20121226</startdate><enddate>20121226</enddate><creator>Zhang, Yida</creator><creator>Baker, Susan S</creator><creator>Baker, Robert D</creator><creator>Zhu, Ruixin</creator><creator>Zhu, Lixin</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20121226</creationdate><title>Systematic analysis of the gene expression in the livers of nonalcoholic steatohepatitis: implications on potential biomarkers and molecular pathological mechanism</title><author>Zhang, Yida ; Baker, Susan S ; Baker, Robert D ; Zhu, Ruixin ; Zhu, Lixin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c758t-49a1bb31dd61df0e5f9fb8a29d80863077103d020bc336e56e810c87df89e04e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>ADH4 protein</topic><topic>Alcohol dehydrogenase</topic><topic>Alcoholic beverages</topic><topic>Alcoholism</topic><topic>Amino acids</topic><topic>Analysis</topic><topic>Annotations</topic><topic>Bioindicators</topic><topic>Bioinformatics</topic><topic>Biological markers</topic><topic>Biology</topic><topic>Biomarkers</topic><topic>Biomarkers - metabolism</topic><topic>Biopsy</topic><topic>Catabolism</topic><topic>Cluster analysis</topic><topic>Computational Biology</topic><topic>Correlation analysis</topic><topic>Dehydrogenases</topic><topic>Diabetes</topic><topic>DNA microarrays</topic><topic>Ethanol</topic><topic>Fatty acids</topic><topic>Fatty liver</topic><topic>Fatty Liver - genetics</topic><topic>Fatty Liver - pathology</topic><topic>Gene expression</topic><topic>Gene Expression Profiling</topic><topic>Genes</topic><topic>Genetic research</topic><topic>Genomes</topic><topic>Hepatitis</topic><topic>Hepatology</topic><topic>Humans</topic><topic>Identification methods</topic><topic>Lipids</topic><topic>Liver</topic><topic>Liver cancer</topic><topic>Liver diseases</topic><topic>Medical research</topic><topic>Medicine</topic><topic>Metabolism</topic><topic>Non-alcoholic Fatty Liver Disease</topic><topic>Nutrition</topic><topic>Obesity</topic><topic>Oligonucleotide Array Sequence Analysis</topic><topic>Oxidative stress</topic><topic>Pathogenesis</topic><topic>Pathology, Molecular</topic><topic>Pediatrics</topic><topic>Real-Time Polymerase Chain Reaction</topic><topic>Reverse Transcriptase Polymerase Chain Reaction</topic><topic>RNA, Messenger - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yida</au><au>Baker, Susan S</au><au>Baker, Robert D</au><au>Zhu, Ruixin</au><au>Zhu, Lixin</au><au>Alisi, Anna</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Systematic analysis of the gene expression in the livers of nonalcoholic steatohepatitis: implications on potential biomarkers and molecular pathological mechanism</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2012-12-26</date><risdate>2012</risdate><volume>7</volume><issue>12</issue><spage>e51131</spage><epage>e51131</epage><pages>e51131-e51131</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Non-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic fatty liver disease (NAFLD). The molecular pathological mechanism of NASH is poorly understood. Recently, high throughput data such as microarray data together with bioinformatics methods have become a powerful way to identify biomarkers and to investigate pathogenesis of diseases. Taking advantage of well characterized microarray datasets of NASH livers, we performed a systematic analysis of potential biomarkers and possible pathological mechanism of NASH from a bioinformatics perspective.CodeLink Human Whole Genome Bioarrays were analyzed to find differentially expressed genes (DEGs) between controls and NASH patients. Four methods were used to identify DEGs and the intersection of DEGs identified by these methods was subsequently used for both biomarker prediction and molecular pathological mechanism analysis. For biomarker prediction, rank aggregation was used to rank DEGs identified by all these methods according to their significance of different expression. Alcohol dehydrogenase 4 (ADH4) exhibited the highest rank suggesting the most significant differential expression between normal and disease condition. Together with the previous report demonstrating the association between ADH4 and the pathogenesis of NASH, our data suggest that ADH4 could be a potential biomarker for NASH. For molecular pathological mechanism analysis, two clusters of highly correlated annotation terms and genes in these terms were identified based on the intersection of DEGs. Then, pathways enriched with these genes were identified to construct the network. Using this network, both for the first time, amino acid catabolism is implicated to play a pivotal role and urea cycle is implicated to be involved in the development of NASH.The results of our study identified potential biomarkers and suggested possible molecular pathological mechanism of NASH. These findings provide a comprehensive and systematic understanding of the pathogenesis of NASH and may facilitate the diagnosis, prevention and treatment of NASH.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23300535</pmid><doi>10.1371/journal.pone.0051131</doi><tpages>e51131</tpages><oa>free_for_read</oa></addata></record> |
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subjects | ADH4 protein Alcohol dehydrogenase Alcoholic beverages Alcoholism Amino acids Analysis Annotations Bioindicators Bioinformatics Biological markers Biology Biomarkers Biomarkers - metabolism Biopsy Catabolism Cluster analysis Computational Biology Correlation analysis Dehydrogenases Diabetes DNA microarrays Ethanol Fatty acids Fatty liver Fatty Liver - genetics Fatty Liver - pathology Gene expression Gene Expression Profiling Genes Genetic research Genomes Hepatitis Hepatology Humans Identification methods Lipids Liver Liver cancer Liver diseases Medical research Medicine Metabolism Non-alcoholic Fatty Liver Disease Nutrition Obesity Oligonucleotide Array Sequence Analysis Oxidative stress Pathogenesis Pathology, Molecular Pediatrics Real-Time Polymerase Chain Reaction Reverse Transcriptase Polymerase Chain Reaction RNA, Messenger - genetics Rodents Signal Transduction Studies Type 2 diabetes Urea |
title | Systematic analysis of the gene expression in the livers of nonalcoholic steatohepatitis: implications on potential biomarkers and molecular pathological mechanism |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T15%3A42%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Systematic%20analysis%20of%20the%20gene%20expression%20in%20the%20livers%20of%20nonalcoholic%20steatohepatitis:%20implications%20on%20potential%20biomarkers%20and%20molecular%20pathological%20mechanism&rft.jtitle=PloS%20one&rft.au=Zhang,%20Yida&rft.date=2012-12-26&rft.volume=7&rft.issue=12&rft.spage=e51131&rft.epage=e51131&rft.pages=e51131-e51131&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0051131&rft_dat=%3Cgale_plos_%3EA477041366%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1327216193&rft_id=info:pmid/23300535&rft_galeid=A477041366&rft_doaj_id=oai_doaj_org_article_7cb1e44f10784da7945d497ae1b0f5ca&rfr_iscdi=true |