Erythrocyte membrane fluidity: A novel biomarker of residual cardiovascular risk in type 2 diabetes
Aims Improving the composition of circulating fatty acids (FA) leads to a reduction in cardiovascular diseases (CVD) in high‐risk individuals. The membrane fluidity of red blood cells (RBC), which reflects circulating FA status, may be a valid biomarker of cardiovascular (CV) risk in type 2 diabetes...
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| Veröffentlicht in: | European journal of clinical investigation 2024-03, Vol.54 (3), p.e14121-n/a |
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| container_title | European journal of clinical investigation |
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| creator | Bianchetti, Giada Cefalo, Chiara Maria Assunta Ferreri, Carla Sansone, Anna Vitale, Marilena Serantoni, Cassandra Abeltino, Alessio Mezza, Teresa Ferraro, Pietro Manuel De Spirito, Marco Riccardi, Gabriele Giaccari, Andrea Maulucci, Giuseppe |
| description | Aims
Improving the composition of circulating fatty acids (FA) leads to a reduction in cardiovascular diseases (CVD) in high‐risk individuals. The membrane fluidity of red blood cells (RBC), which reflects circulating FA status, may be a valid biomarker of cardiovascular (CV) risk in type 2 diabetes (T2D).
Methods
Red blood cell membrane fluidity, quantified as general polarization (GP), was assessed in 234 subjects with T2D, 86 with prior major CVD. Based on GP distribution, a cut‐off of .445 was used to divide the study cohort into two groups: the first with higher GP, called GEL, and the second, defined as lower GP (LGP). Lipidomic analysis was performed to evaluate FA composition of RBC membranes.
Results
Although with comparable CV risk factors, the LGP group had a greater percentage of patients with major CVD than the GEL group (40% vs 24%, respectively, p |
| doi_str_mv | 10.1111/eci.14121 |
| format | Article |
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Improving the composition of circulating fatty acids (FA) leads to a reduction in cardiovascular diseases (CVD) in high‐risk individuals. The membrane fluidity of red blood cells (RBC), which reflects circulating FA status, may be a valid biomarker of cardiovascular (CV) risk in type 2 diabetes (T2D).
Methods
Red blood cell membrane fluidity, quantified as general polarization (GP), was assessed in 234 subjects with T2D, 86 with prior major CVD. Based on GP distribution, a cut‐off of .445 was used to divide the study cohort into two groups: the first with higher GP, called GEL, and the second, defined as lower GP (LGP). Lipidomic analysis was performed to evaluate FA composition of RBC membranes.
Results
Although with comparable CV risk factors, the LGP group had a greater percentage of patients with major CVD than the GEL group (40% vs 24%, respectively, p < .05). Moreover, in a logistic regression analysis, a lower GP value was independently associated with the presence of macrovascular complications. Lipidomic analysis showed a clear shift of LGP membranes towards a pro‐inflammatory condition due to higher content of arachidonic acid and increased omega 6/omega 3 index.
Conclusions
Increased membrane fluidity is associated with a higher CV risk in subjects with T2D. If confirmed in prospective studies, membrane fluidity could be a new biomarker for residual CV risk assessment in T2D.</description><identifier>ISSN: 0014-2972</identifier><identifier>EISSN: 1365-2362</identifier><identifier>DOI: 10.1111/eci.14121</identifier><identifier>PMID: 37929812</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Arachidonic acid ; Biomarkers ; Biomarkers - metabolism ; Blood circulation ; cardiovascular disease ; Cardiovascular Diseases ; cardiovascular risk assessment ; Cell membranes ; Composition ; Diabetes ; Diabetes mellitus (non-insulin dependent) ; Diabetes Mellitus, Type 2 ; Erythrocyte Membrane - metabolism ; Erythrocytes ; Erythrocytes - metabolism ; fatty acids ; Fatty Acids - metabolism ; Fluidity ; fluorescence microscopy ; Health risks ; Heart Disease Risk Factors ; Humans ; Inflammation ; machine‐learning ; Membrane Fluidity ; Membranes ; Prospective Studies ; Regression analysis ; Risk assessment ; Risk Factors ; type 2 diabetes</subject><ispartof>European journal of clinical investigation, 2024-03, Vol.54 (3), p.e14121-n/a</ispartof><rights>2023 The Authors. published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation.</rights><rights>2023 The Authors. European Journal of Clinical Investigation published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3881-4dd03124672615ab561854739a9139490269c91269992308617177204037ed8c3</citedby><cites>FETCH-LOGICAL-c3881-4dd03124672615ab561854739a9139490269c91269992308617177204037ed8c3</cites><orcidid>0000-0002-8665-8406 ; 0000-0003-1257-2295 ; 0000-0002-7462-7792 ; 0000-0002-2154-319X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Feci.14121$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Feci.14121$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27923,27924,45573,45574</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37929812$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bianchetti, Giada</creatorcontrib><creatorcontrib>Cefalo, Chiara Maria Assunta</creatorcontrib><creatorcontrib>Ferreri, Carla</creatorcontrib><creatorcontrib>Sansone, Anna</creatorcontrib><creatorcontrib>Vitale, Marilena</creatorcontrib><creatorcontrib>Serantoni, Cassandra</creatorcontrib><creatorcontrib>Abeltino, Alessio</creatorcontrib><creatorcontrib>Mezza, Teresa</creatorcontrib><creatorcontrib>Ferraro, Pietro Manuel</creatorcontrib><creatorcontrib>De Spirito, Marco</creatorcontrib><creatorcontrib>Riccardi, Gabriele</creatorcontrib><creatorcontrib>Giaccari, Andrea</creatorcontrib><creatorcontrib>Maulucci, Giuseppe</creatorcontrib><title>Erythrocyte membrane fluidity: A novel biomarker of residual cardiovascular risk in type 2 diabetes</title><title>European journal of clinical investigation</title><addtitle>Eur J Clin Invest</addtitle><description>Aims
Improving the composition of circulating fatty acids (FA) leads to a reduction in cardiovascular diseases (CVD) in high‐risk individuals. The membrane fluidity of red blood cells (RBC), which reflects circulating FA status, may be a valid biomarker of cardiovascular (CV) risk in type 2 diabetes (T2D).
Methods
Red blood cell membrane fluidity, quantified as general polarization (GP), was assessed in 234 subjects with T2D, 86 with prior major CVD. Based on GP distribution, a cut‐off of .445 was used to divide the study cohort into two groups: the first with higher GP, called GEL, and the second, defined as lower GP (LGP). Lipidomic analysis was performed to evaluate FA composition of RBC membranes.
Results
Although with comparable CV risk factors, the LGP group had a greater percentage of patients with major CVD than the GEL group (40% vs 24%, respectively, p < .05). Moreover, in a logistic regression analysis, a lower GP value was independently associated with the presence of macrovascular complications. Lipidomic analysis showed a clear shift of LGP membranes towards a pro‐inflammatory condition due to higher content of arachidonic acid and increased omega 6/omega 3 index.
Conclusions
Increased membrane fluidity is associated with a higher CV risk in subjects with T2D. If confirmed in prospective studies, membrane fluidity could be a new biomarker for residual CV risk assessment in T2D.</description><subject>Arachidonic acid</subject><subject>Biomarkers</subject><subject>Biomarkers - metabolism</subject><subject>Blood circulation</subject><subject>cardiovascular disease</subject><subject>Cardiovascular Diseases</subject><subject>cardiovascular risk assessment</subject><subject>Cell membranes</subject><subject>Composition</subject><subject>Diabetes</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diabetes Mellitus, Type 2</subject><subject>Erythrocyte Membrane - metabolism</subject><subject>Erythrocytes</subject><subject>Erythrocytes - metabolism</subject><subject>fatty acids</subject><subject>Fatty Acids - metabolism</subject><subject>Fluidity</subject><subject>fluorescence microscopy</subject><subject>Health risks</subject><subject>Heart Disease Risk Factors</subject><subject>Humans</subject><subject>Inflammation</subject><subject>machine‐learning</subject><subject>Membrane Fluidity</subject><subject>Membranes</subject><subject>Prospective Studies</subject><subject>Regression analysis</subject><subject>Risk assessment</subject><subject>Risk Factors</subject><subject>type 2 diabetes</subject><issn>0014-2972</issn><issn>1365-2362</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kE1v1DAQQC0EokvhwB9AlrjAIa1nnPiDW7VaoFIlLnC2HGdWuE3Wi520yr_HsIUDEj6ML09PM4-x1yAuoL5LCvECWkB4wjYgVdegVPiUbYSAtkGr8Yy9KOVWCGFA4nN2JrVFawA3LOzyOn_PKawz8YmmPvsD8f24xCHO6wd-xQ_pnkbexzT5fEeZpz3PVOKw-JEHn4eY7n0Jy-gzz7Hc8Xjg83okjnyIvqeZykv2bO_HQq8e_3P27ePu6_Zzc_Pl0_X26qYJ0hho2mEQErBVGhV0vu8UmK7V0noL0rZWoLLBQp3WohRGgQatUbRCahpMkOfs3cl7zOnHQmV2UyyBxrGelJbi0BjVWS2Uqujbf9DbtORD3c6hxU7WNqKt1PsTFXIqJdPeHXOsGVYHwv0q72p597t8Zd88Gpd-ouEv-Sd1BS5PwEMcaf2_ye221yflT_qoiao</recordid><startdate>202403</startdate><enddate>202403</enddate><creator>Bianchetti, Giada</creator><creator>Cefalo, Chiara Maria Assunta</creator><creator>Ferreri, Carla</creator><creator>Sansone, Anna</creator><creator>Vitale, Marilena</creator><creator>Serantoni, Cassandra</creator><creator>Abeltino, Alessio</creator><creator>Mezza, Teresa</creator><creator>Ferraro, Pietro Manuel</creator><creator>De Spirito, Marco</creator><creator>Riccardi, Gabriele</creator><creator>Giaccari, Andrea</creator><creator>Maulucci, Giuseppe</creator><general>Blackwell Publishing Ltd</general><scope>24P</scope><scope>WIN</scope><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>7QO</scope><scope>7U7</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-8665-8406</orcidid><orcidid>https://orcid.org/0000-0003-1257-2295</orcidid><orcidid>https://orcid.org/0000-0002-7462-7792</orcidid><orcidid>https://orcid.org/0000-0002-2154-319X</orcidid></search><sort><creationdate>202403</creationdate><title>Erythrocyte membrane fluidity: A novel biomarker of residual cardiovascular risk in type 2 diabetes</title><author>Bianchetti, Giada ; Cefalo, Chiara Maria Assunta ; Ferreri, Carla ; Sansone, Anna ; Vitale, Marilena ; Serantoni, Cassandra ; Abeltino, Alessio ; Mezza, Teresa ; Ferraro, Pietro Manuel ; De Spirito, Marco ; Riccardi, Gabriele ; Giaccari, Andrea ; Maulucci, Giuseppe</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3881-4dd03124672615ab561854739a9139490269c91269992308617177204037ed8c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Arachidonic acid</topic><topic>Biomarkers</topic><topic>Biomarkers - metabolism</topic><topic>Blood circulation</topic><topic>cardiovascular disease</topic><topic>Cardiovascular Diseases</topic><topic>cardiovascular risk assessment</topic><topic>Cell membranes</topic><topic>Composition</topic><topic>Diabetes</topic><topic>Diabetes mellitus (non-insulin dependent)</topic><topic>Diabetes Mellitus, Type 2</topic><topic>Erythrocyte Membrane - metabolism</topic><topic>Erythrocytes</topic><topic>Erythrocytes - metabolism</topic><topic>fatty acids</topic><topic>Fatty Acids - metabolism</topic><topic>Fluidity</topic><topic>fluorescence microscopy</topic><topic>Health risks</topic><topic>Heart Disease Risk Factors</topic><topic>Humans</topic><topic>Inflammation</topic><topic>machine‐learning</topic><topic>Membrane Fluidity</topic><topic>Membranes</topic><topic>Prospective Studies</topic><topic>Regression analysis</topic><topic>Risk assessment</topic><topic>Risk Factors</topic><topic>type 2 diabetes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bianchetti, Giada</creatorcontrib><creatorcontrib>Cefalo, Chiara Maria Assunta</creatorcontrib><creatorcontrib>Ferreri, Carla</creatorcontrib><creatorcontrib>Sansone, Anna</creatorcontrib><creatorcontrib>Vitale, Marilena</creatorcontrib><creatorcontrib>Serantoni, Cassandra</creatorcontrib><creatorcontrib>Abeltino, Alessio</creatorcontrib><creatorcontrib>Mezza, Teresa</creatorcontrib><creatorcontrib>Ferraro, Pietro Manuel</creatorcontrib><creatorcontrib>De Spirito, Marco</creatorcontrib><creatorcontrib>Riccardi, Gabriele</creatorcontrib><creatorcontrib>Giaccari, Andrea</creatorcontrib><creatorcontrib>Maulucci, Giuseppe</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of clinical investigation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bianchetti, Giada</au><au>Cefalo, Chiara Maria Assunta</au><au>Ferreri, Carla</au><au>Sansone, Anna</au><au>Vitale, Marilena</au><au>Serantoni, Cassandra</au><au>Abeltino, Alessio</au><au>Mezza, Teresa</au><au>Ferraro, Pietro Manuel</au><au>De Spirito, Marco</au><au>Riccardi, Gabriele</au><au>Giaccari, Andrea</au><au>Maulucci, Giuseppe</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Erythrocyte membrane fluidity: A novel biomarker of residual cardiovascular risk in type 2 diabetes</atitle><jtitle>European journal of clinical investigation</jtitle><addtitle>Eur J Clin Invest</addtitle><date>2024-03</date><risdate>2024</risdate><volume>54</volume><issue>3</issue><spage>e14121</spage><epage>n/a</epage><pages>e14121-n/a</pages><issn>0014-2972</issn><eissn>1365-2362</eissn><abstract>Aims
Improving the composition of circulating fatty acids (FA) leads to a reduction in cardiovascular diseases (CVD) in high‐risk individuals. The membrane fluidity of red blood cells (RBC), which reflects circulating FA status, may be a valid biomarker of cardiovascular (CV) risk in type 2 diabetes (T2D).
Methods
Red blood cell membrane fluidity, quantified as general polarization (GP), was assessed in 234 subjects with T2D, 86 with prior major CVD. Based on GP distribution, a cut‐off of .445 was used to divide the study cohort into two groups: the first with higher GP, called GEL, and the second, defined as lower GP (LGP). Lipidomic analysis was performed to evaluate FA composition of RBC membranes.
Results
Although with comparable CV risk factors, the LGP group had a greater percentage of patients with major CVD than the GEL group (40% vs 24%, respectively, p < .05). Moreover, in a logistic regression analysis, a lower GP value was independently associated with the presence of macrovascular complications. Lipidomic analysis showed a clear shift of LGP membranes towards a pro‐inflammatory condition due to higher content of arachidonic acid and increased omega 6/omega 3 index.
Conclusions
Increased membrane fluidity is associated with a higher CV risk in subjects with T2D. If confirmed in prospective studies, membrane fluidity could be a new biomarker for residual CV risk assessment in T2D.</abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>37929812</pmid><doi>10.1111/eci.14121</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-8665-8406</orcidid><orcidid>https://orcid.org/0000-0003-1257-2295</orcidid><orcidid>https://orcid.org/0000-0002-7462-7792</orcidid><orcidid>https://orcid.org/0000-0002-2154-319X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Arachidonic acid Biomarkers Biomarkers - metabolism Blood circulation cardiovascular disease Cardiovascular Diseases cardiovascular risk assessment Cell membranes Composition Diabetes Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 2 Erythrocyte Membrane - metabolism Erythrocytes Erythrocytes - metabolism fatty acids Fatty Acids - metabolism Fluidity fluorescence microscopy Health risks Heart Disease Risk Factors Humans Inflammation machine‐learning Membrane Fluidity Membranes Prospective Studies Regression analysis Risk assessment Risk Factors type 2 diabetes |
| title | Erythrocyte membrane fluidity: A novel biomarker of residual cardiovascular risk in type 2 diabetes |
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