Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death
We present here the differential analysis of metabolite–metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 patients of which 123 died within 2 years from acute myocardial infarctio...
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| Veröffentlicht in: | Journal of proteome research 2020-02, Vol.19 (2), p.949-961 |
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| container_title | Journal of proteome research |
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| creator | Vignoli, Alessia Tenori, Leonardo Giusti, Betti Valente, Serafina Carrabba, Nazario Balzi, Daniela Barchielli, Alessandro Marchionni, Niccolò Gensini, Gian Franco Marcucci, Rossella Gori, Anna Maria Luchinat, Claudio Saccenti, Edoardo |
| description | We present here the differential analysis of metabolite–metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 patients of which 123 died within 2 years from acute myocardial infarction (AMI). We investigated differences in metabolite connectivity of patients who survived, at 2 years, the AMI event, and we characterized metabolite–metabolite association networks specific to high and low risks of death according to four different risk parameters, namely, acute coronary syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomics NOESY RF risk score. We show significant differences in the connectivity patterns of several low-molecular-weight molecules, implying variations in the regulation of several metabolic pathways regarding branched-chain amino acids, alanine, creatinine, mannose, ketone bodies, and energetic metabolism. Our results demonstrate that the characterization of metabolite–metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level. |
| doi_str_mv | 10.1021/acs.jproteome.9b00779 |
| format | Article |
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We investigated differences in metabolite connectivity of patients who survived, at 2 years, the AMI event, and we characterized metabolite–metabolite association networks specific to high and low risks of death according to four different risk parameters, namely, acute coronary syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomics NOESY RF risk score. We show significant differences in the connectivity patterns of several low-molecular-weight molecules, implying variations in the regulation of several metabolic pathways regarding branched-chain amino acids, alanine, creatinine, mannose, ketone bodies, and energetic metabolism. Our results demonstrate that the characterization of metabolite–metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level.</description><identifier>ISSN: 1535-3893</identifier><identifier>ISSN: 1535-3907</identifier><identifier>EISSN: 1535-3907</identifier><identifier>DOI: 10.1021/acs.jproteome.9b00779</identifier><identifier>PMID: 31899863</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>alanine ; biochemical pathways ; blood serum ; branched chain amino acids ; creatinine ; ketone bodies ; mannose ; metabolism ; metabolomics ; mortality ; myocardial infarction ; nuclear magnetic resonance spectroscopy ; patients ; proteome ; risk</subject><ispartof>Journal of proteome research, 2020-02, Vol.19 (2), p.949-961</ispartof><rights>Copyright © 2020 American Chemical Society 2020 American Chemical Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a486t-34019f4557ba01f752b61b2f5ebc537048dbb0058d9958d90b83f53f909f1683</citedby><cites>FETCH-LOGICAL-a486t-34019f4557ba01f752b61b2f5ebc537048dbb0058d9958d90b83f53f909f1683</cites><orcidid>0000-0001-6438-059X ; 0000-0003-2271-8921 ; 0000-0002-5190-5227 ; 0000-0001-8284-4829 ; 0000-0003-4038-6596</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.9b00779$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.jproteome.9b00779$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>230,314,776,780,881,2752,27053,27901,27902,56713,56763</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31899863$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Vignoli, Alessia</creatorcontrib><creatorcontrib>Tenori, Leonardo</creatorcontrib><creatorcontrib>Giusti, Betti</creatorcontrib><creatorcontrib>Valente, Serafina</creatorcontrib><creatorcontrib>Carrabba, Nazario</creatorcontrib><creatorcontrib>Balzi, Daniela</creatorcontrib><creatorcontrib>Barchielli, Alessandro</creatorcontrib><creatorcontrib>Marchionni, Niccolò</creatorcontrib><creatorcontrib>Gensini, Gian Franco</creatorcontrib><creatorcontrib>Marcucci, Rossella</creatorcontrib><creatorcontrib>Gori, Anna Maria</creatorcontrib><creatorcontrib>Luchinat, Claudio</creatorcontrib><creatorcontrib>Saccenti, Edoardo</creatorcontrib><title>Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death</title><title>Journal of proteome research</title><addtitle>J. Proteome Res</addtitle><description>We present here the differential analysis of metabolite–metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 patients of which 123 died within 2 years from acute myocardial infarction (AMI). We investigated differences in metabolite connectivity of patients who survived, at 2 years, the AMI event, and we characterized metabolite–metabolite association networks specific to high and low risks of death according to four different risk parameters, namely, acute coronary syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomics NOESY RF risk score. We show significant differences in the connectivity patterns of several low-molecular-weight molecules, implying variations in the regulation of several metabolic pathways regarding branched-chain amino acids, alanine, creatinine, mannose, ketone bodies, and energetic metabolism. Our results demonstrate that the characterization of metabolite–metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level.</description><subject>alanine</subject><subject>biochemical pathways</subject><subject>blood serum</subject><subject>branched chain amino acids</subject><subject>creatinine</subject><subject>ketone bodies</subject><subject>mannose</subject><subject>metabolism</subject><subject>metabolomics</subject><subject>mortality</subject><subject>myocardial infarction</subject><subject>nuclear magnetic resonance spectroscopy</subject><subject>patients</subject><subject>proteome</subject><subject>risk</subject><issn>1535-3893</issn><issn>1535-3907</issn><issn>1535-3907</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqNks1uEzEUhUcIREvhEUBeskmw4_F4vEGKUn4qNRDRsLY8nuvEZcZObU-reVZeBoekEaxgY_vK3z069-oUxWuCpwTPyDul4_R2F3wC38NUNBhzLp4U54RRNqEC86eP71rQs-JFjLcYE8YxfV6cUVILUVf0vPh5aY2BAC5Z1aEvkB58-IHmTnVjtBF9g3tQXURLSKrxndXoEhKE3jrlUkTzGL22KkGLHmzaoqUPSXU2jcg6NNdDArQcvVah3atfOaOCTtY7tFLJwl5BuRbdDJsNxFys8jQHI0vQW-Vs7CP67loI3WjdBp28okVnndUZvNE-QIZitrD2aBWgtTpllyptXxbPTDYPr473RbH--GG9-Dy5_vrpajG_nqiyrtKElpgIUzLGG4WJ4WzWVKSZGQaNZpTjsm6bvF5Wt0LsD9zU1DBqBBaGVDW9KN4fZHdD00Ors7-gOrkLtldhlF5Z-fePs1u58feSY0IIp1ng7VEg-Lshb0L2NmroOuXAD1HOSipKWpXiP1BKaYU5nfGMsgOqg48xgDk5IljuIyRzhOQpQvIYodz35s9xTl2PmckAOQC_-_0QcljiP0R_AbRa3dM</recordid><startdate>20200207</startdate><enddate>20200207</enddate><creator>Vignoli, Alessia</creator><creator>Tenori, Leonardo</creator><creator>Giusti, Betti</creator><creator>Valente, Serafina</creator><creator>Carrabba, Nazario</creator><creator>Balzi, Daniela</creator><creator>Barchielli, Alessandro</creator><creator>Marchionni, Niccolò</creator><creator>Gensini, Gian Franco</creator><creator>Marcucci, Rossella</creator><creator>Gori, Anna Maria</creator><creator>Luchinat, Claudio</creator><creator>Saccenti, Edoardo</creator><general>American Chemical Society</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-6438-059X</orcidid><orcidid>https://orcid.org/0000-0003-2271-8921</orcidid><orcidid>https://orcid.org/0000-0002-5190-5227</orcidid><orcidid>https://orcid.org/0000-0001-8284-4829</orcidid><orcidid>https://orcid.org/0000-0003-4038-6596</orcidid></search><sort><creationdate>20200207</creationdate><title>Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death</title><author>Vignoli, Alessia ; Tenori, Leonardo ; Giusti, Betti ; Valente, Serafina ; Carrabba, Nazario ; Balzi, Daniela ; Barchielli, Alessandro ; Marchionni, Niccolò ; Gensini, Gian Franco ; Marcucci, Rossella ; Gori, Anna Maria ; Luchinat, Claudio ; Saccenti, Edoardo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a486t-34019f4557ba01f752b61b2f5ebc537048dbb0058d9958d90b83f53f909f1683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>alanine</topic><topic>biochemical pathways</topic><topic>blood serum</topic><topic>branched chain amino acids</topic><topic>creatinine</topic><topic>ketone bodies</topic><topic>mannose</topic><topic>metabolism</topic><topic>metabolomics</topic><topic>mortality</topic><topic>myocardial infarction</topic><topic>nuclear magnetic resonance spectroscopy</topic><topic>patients</topic><topic>proteome</topic><topic>risk</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vignoli, Alessia</creatorcontrib><creatorcontrib>Tenori, Leonardo</creatorcontrib><creatorcontrib>Giusti, Betti</creatorcontrib><creatorcontrib>Valente, Serafina</creatorcontrib><creatorcontrib>Carrabba, Nazario</creatorcontrib><creatorcontrib>Balzi, Daniela</creatorcontrib><creatorcontrib>Barchielli, Alessandro</creatorcontrib><creatorcontrib>Marchionni, Niccolò</creatorcontrib><creatorcontrib>Gensini, Gian Franco</creatorcontrib><creatorcontrib>Marcucci, Rossella</creatorcontrib><creatorcontrib>Gori, Anna Maria</creatorcontrib><creatorcontrib>Luchinat, Claudio</creatorcontrib><creatorcontrib>Saccenti, Edoardo</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of proteome research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vignoli, Alessia</au><au>Tenori, Leonardo</au><au>Giusti, Betti</au><au>Valente, Serafina</au><au>Carrabba, Nazario</au><au>Balzi, Daniela</au><au>Barchielli, Alessandro</au><au>Marchionni, Niccolò</au><au>Gensini, Gian Franco</au><au>Marcucci, Rossella</au><au>Gori, Anna Maria</au><au>Luchinat, Claudio</au><au>Saccenti, Edoardo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death</atitle><jtitle>Journal of proteome research</jtitle><addtitle>J. Proteome Res</addtitle><date>2020-02-07</date><risdate>2020</risdate><volume>19</volume><issue>2</issue><spage>949</spage><epage>961</epage><pages>949-961</pages><issn>1535-3893</issn><issn>1535-3907</issn><eissn>1535-3907</eissn><abstract>We present here the differential analysis of metabolite–metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 patients of which 123 died within 2 years from acute myocardial infarction (AMI). We investigated differences in metabolite connectivity of patients who survived, at 2 years, the AMI event, and we characterized metabolite–metabolite association networks specific to high and low risks of death according to four different risk parameters, namely, acute coronary syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomics NOESY RF risk score. We show significant differences in the connectivity patterns of several low-molecular-weight molecules, implying variations in the regulation of several metabolic pathways regarding branched-chain amino acids, alanine, creatinine, mannose, ketone bodies, and energetic metabolism. Our results demonstrate that the characterization of metabolite–metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>31899863</pmid><doi>10.1021/acs.jproteome.9b00779</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-6438-059X</orcidid><orcidid>https://orcid.org/0000-0003-2271-8921</orcidid><orcidid>https://orcid.org/0000-0002-5190-5227</orcidid><orcidid>https://orcid.org/0000-0001-8284-4829</orcidid><orcidid>https://orcid.org/0000-0003-4038-6596</orcidid><oa>free_for_read</oa></addata></record> |
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| source | American Chemical Society Journals |
| subjects | alanine biochemical pathways blood serum branched chain amino acids creatinine ketone bodies mannose metabolism metabolomics mortality myocardial infarction nuclear magnetic resonance spectroscopy patients proteome risk |
| title | Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death |
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