Combinatory data‐independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities
Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra‐performance liquid chromatography–high‐resolution mass spectrometry in data‐independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, w...
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| Veröffentlicht in: | Journal of separation science 2024-04, Vol.47 (8), p.e2300848-n/a |
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| creator | Wu, Hao Yang, Lijuan Ren, Dabing Gu, Ying Ding, Xiaoxue Zhao, Yan Fu, Guanghui Zhang, Hong Yi, Lunzhao |
| description | Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra‐performance liquid chromatography–high‐resolution mass spectrometry in data‐independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high‐throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention. |
| doi_str_mv | 10.1002/jssc.202300848 |
| format | Article |
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In this study, ultra‐performance liquid chromatography–high‐resolution mass spectrometry in data‐independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high‐throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention.</description><identifier>ISSN: 1615-9306</identifier><identifier>EISSN: 1615-9314</identifier><identifier>DOI: 10.1002/jssc.202300848</identifier><identifier>PMID: 38682821</identifier><language>eng</language><publisher>Germany: Wiley Subscription Services, Inc</publisher><subject>Annotations ; Biomarkers ; Biomarkers - analysis ; Biomarkers - blood ; Cardiovascular disease ; Chromatography ; Chromatography, High Pressure Liquid ; Comorbidity ; Coronary Disease - blood ; Coronary Disease - metabolism ; coronary heart disease ; data‐independent acquisition ; Female ; Heart diseases ; Humans ; Lipid Metabolism ; lipidomics ; Lipids ; Lipids - blood ; Liquid chromatography ; Male ; Mass spectrometry ; Metabolic disorders ; Metabolism ; Metabolites ; Middle Aged ; Monitoring ; Multivariate statistical analysis ; parallel reaction monitoring ; Scientific imaging ; Statistical analysis ; Tandem Mass Spectrometry ; Telemedicine ; UHPLC‐HRMS</subject><ispartof>Journal of separation science, 2024-04, Vol.47 (8), p.e2300848-n/a</ispartof><rights>2024 Wiley‐VCH GmbH.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3237-7d13836085601d7679d95bf4923b3c7df4634b0fa15d37d0e10da495f8a02d343</cites><orcidid>0009-0005-7353-5545</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjssc.202300848$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjssc.202300848$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38682821$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wu, Hao</creatorcontrib><creatorcontrib>Yang, Lijuan</creatorcontrib><creatorcontrib>Ren, Dabing</creatorcontrib><creatorcontrib>Gu, Ying</creatorcontrib><creatorcontrib>Ding, Xiaoxue</creatorcontrib><creatorcontrib>Zhao, Yan</creatorcontrib><creatorcontrib>Fu, Guanghui</creatorcontrib><creatorcontrib>Zhang, Hong</creatorcontrib><creatorcontrib>Yi, Lunzhao</creatorcontrib><title>Combinatory data‐independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities</title><title>Journal of separation science</title><addtitle>J Sep Sci</addtitle><description>Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra‐performance liquid chromatography–high‐resolution mass spectrometry in data‐independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high‐throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention.</description><subject>Annotations</subject><subject>Biomarkers</subject><subject>Biomarkers - analysis</subject><subject>Biomarkers - blood</subject><subject>Cardiovascular disease</subject><subject>Chromatography</subject><subject>Chromatography, High Pressure Liquid</subject><subject>Comorbidity</subject><subject>Coronary Disease - blood</subject><subject>Coronary Disease - metabolism</subject><subject>coronary heart disease</subject><subject>data‐independent acquisition</subject><subject>Female</subject><subject>Heart diseases</subject><subject>Humans</subject><subject>Lipid Metabolism</subject><subject>lipidomics</subject><subject>Lipids</subject><subject>Lipids - blood</subject><subject>Liquid chromatography</subject><subject>Male</subject><subject>Mass spectrometry</subject><subject>Metabolic disorders</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Middle Aged</subject><subject>Monitoring</subject><subject>Multivariate statistical analysis</subject><subject>parallel reaction monitoring</subject><subject>Scientific imaging</subject><subject>Statistical analysis</subject><subject>Tandem Mass Spectrometry</subject><subject>Telemedicine</subject><subject>UHPLC‐HRMS</subject><issn>1615-9306</issn><issn>1615-9314</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkb-O1DAQxiME4o6DlhJZoqHZxf9iOyVawQE6ieKgjibxhPXi2Dk7C9qOR7hH4Zl4EpzbYwsaGtua7zffjPxV1XNG14xS_nqXc7_mlAtKjTQPqnOmWL1qBJMPT2-qzqonOe8oZdo09HF1Jowy3HB2Xv3axLFzAeaYDsTCDL9_3rpgccJyhJlAf7N32c0uBgLBkgkSeI-eJIT-rjrG4Eq3C1_JiPM2WjLEVOTvCH4pzlsk3k3OLjJ00bs8ks7FEdI3TJnEgfQxxQBlgS1Cmol1GSHj3Tw35yKPMXXOli0wP60eDeAzPru_L6ov795-3rxfXX26_LB5c7XqBRd6pS0TRihqakWZ1Uo3tqm7QTZcdKLXdpBKyI4OwGortKXIqAXZ1IMByq2Q4qJ6dfSdUrzZY57b0eUevYeAcZ9bQaXRyhiuCvryH3QX9ymU7RZKm7pRjBdqfaT6FHNOOLRTcuUTDi2j7ZJlu2TZnrIsDS_ubffdiPaE_w2vAPII_HAeD_-xaz9eX28Ml1r8AYy3r3A</recordid><startdate>202404</startdate><enddate>202404</enddate><creator>Wu, Hao</creator><creator>Yang, Lijuan</creator><creator>Ren, Dabing</creator><creator>Gu, Ying</creator><creator>Ding, Xiaoxue</creator><creator>Zhao, Yan</creator><creator>Fu, Guanghui</creator><creator>Zhang, Hong</creator><creator>Yi, Lunzhao</creator><general>Wiley Subscription Services, Inc</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>7U5</scope><scope>8FD</scope><scope>L7M</scope><scope>7X8</scope><orcidid>https://orcid.org/0009-0005-7353-5545</orcidid></search><sort><creationdate>202404</creationdate><title>Combinatory data‐independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities</title><author>Wu, Hao ; Yang, Lijuan ; Ren, Dabing ; Gu, Ying ; Ding, Xiaoxue ; Zhao, Yan ; Fu, Guanghui ; Zhang, Hong ; Yi, Lunzhao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3237-7d13836085601d7679d95bf4923b3c7df4634b0fa15d37d0e10da495f8a02d343</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Annotations</topic><topic>Biomarkers</topic><topic>Biomarkers - analysis</topic><topic>Biomarkers - blood</topic><topic>Cardiovascular disease</topic><topic>Chromatography</topic><topic>Chromatography, High Pressure Liquid</topic><topic>Comorbidity</topic><topic>Coronary Disease - blood</topic><topic>Coronary Disease - metabolism</topic><topic>coronary heart disease</topic><topic>data‐independent acquisition</topic><topic>Female</topic><topic>Heart diseases</topic><topic>Humans</topic><topic>Lipid Metabolism</topic><topic>lipidomics</topic><topic>Lipids</topic><topic>Lipids - blood</topic><topic>Liquid chromatography</topic><topic>Male</topic><topic>Mass spectrometry</topic><topic>Metabolic disorders</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Middle Aged</topic><topic>Monitoring</topic><topic>Multivariate statistical analysis</topic><topic>parallel reaction monitoring</topic><topic>Scientific imaging</topic><topic>Statistical analysis</topic><topic>Tandem Mass Spectrometry</topic><topic>Telemedicine</topic><topic>UHPLC‐HRMS</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Hao</creatorcontrib><creatorcontrib>Yang, Lijuan</creatorcontrib><creatorcontrib>Ren, Dabing</creatorcontrib><creatorcontrib>Gu, Ying</creatorcontrib><creatorcontrib>Ding, Xiaoxue</creatorcontrib><creatorcontrib>Zhao, Yan</creatorcontrib><creatorcontrib>Fu, Guanghui</creatorcontrib><creatorcontrib>Zhang, Hong</creatorcontrib><creatorcontrib>Yi, Lunzhao</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of separation science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Hao</au><au>Yang, Lijuan</au><au>Ren, Dabing</au><au>Gu, Ying</au><au>Ding, Xiaoxue</au><au>Zhao, Yan</au><au>Fu, Guanghui</au><au>Zhang, Hong</au><au>Yi, Lunzhao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Combinatory data‐independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities</atitle><jtitle>Journal of separation science</jtitle><addtitle>J Sep Sci</addtitle><date>2024-04</date><risdate>2024</risdate><volume>47</volume><issue>8</issue><spage>e2300848</spage><epage>n/a</epage><pages>e2300848-n/a</pages><issn>1615-9306</issn><eissn>1615-9314</eissn><abstract>Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra‐performance liquid chromatography–high‐resolution mass spectrometry in data‐independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high‐throughput characterization of plasma lipids. 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| subjects | Annotations Biomarkers Biomarkers - analysis Biomarkers - blood Cardiovascular disease Chromatography Chromatography, High Pressure Liquid Comorbidity Coronary Disease - blood Coronary Disease - metabolism coronary heart disease data‐independent acquisition Female Heart diseases Humans Lipid Metabolism lipidomics Lipids Lipids - blood Liquid chromatography Male Mass spectrometry Metabolic disorders Metabolism Metabolites Middle Aged Monitoring Multivariate statistical analysis parallel reaction monitoring Scientific imaging Statistical analysis Tandem Mass Spectrometry Telemedicine UHPLC‐HRMS |
| title | Combinatory data‐independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities |
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