Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis
BackgroundChronic kidney disease (CKD) patients under hemodialysis show a higher risk of cardiovascular (CV) mortality and morbidity than the general population. This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis. Methods A total of 245 CKD patients...
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Veröffentlicht in: | Clinical Kidney Journal 2020-08, Vol.13 (4), p.666-673 |
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creator | Terranegra, Annalisa Arcidiacono, Teresa Macrina, Lorenza Brasacchio, Caterina Pivari, Francesca Mingione, Alessandra Tomei, Sara Mezzavilla, Massimo Silcock, Lee Cozzolino, Mario Palmieri, Nicola Conte, Ferruccio Sirtori, Marcella Rubinacci, Alessandro Soldati, Laura Vezzoli, Giuseppe |
description | BackgroundChronic kidney disease (CKD) patients under hemodialysis show a higher risk of cardiovascular (CV) mortality and morbidity than the general population. This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis. Methods A total of 245 CKD patients under hemodialysis were recruited and followed up for 5 years to record CV events. Genetic analysis was performed using single-nucleotide polymorphisms (SNPs) genotyping by Infinium Expanded Multi-Ethnic Genotyping Array (Illumina, San Diego, CA, USA) comparing patients with and without a history of CV events [161 cardiovascular diseases (CVDs) and 84 no CVDs]. The fixation index (Fst) measure was used to identify the most differentiated SNPs, and gene ontology analysis [Protein Analysis THrough Evolutionary Relationships (PANTHER) and Ingenuity Pathway Analysis (IPA)] was applied to define the biological/pathological roles of the associated SNPs. Partitioning tree analysis interrogated the genotype–phenotype relationship between discovered genetic variants and CV phenotypes. Cox regression analysis measured the effect of these SNPs on new CV events during the follow-up (FU).ResultsFst analysis identified 3218 SNPs that were significantly different between CVD and no CVD. Gene ontology analysis identified two of these SNPs as involved in cardiovascular disease pathways (Ingenuity Pathway) and heart development (Panther) and belonging to 2 different genes: Glucagon-like peptide-1 receptor (GLP1R) and Sarcoglycan delta (SGCD). The phenotype–genotype analysis found a higher percentage of CVD patients carrying the GLP1R rs10305445 allele A (P = 0.03) and lower percentages of CVD patients carrying the SGCD rs145292439 allele A (P = 0.038). Moreover, SGCD rs145292439 was associated with higher levels of high-density lipoprotein (P = 0.015). Cox analysis confirmed the increased frequency of CV events during the 5-year FU in patients carrying GLP1R rs1035445 allele A but it did not show any significant association with SGCD rs145292439.ConclusionsThis study identified GLP1R rs10305445 and SCGD rs145292439 as potential genetic markers that may explain the higher risk of CVD in hemodialysis patients. |
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This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis. Methods A total of 245 CKD patients under hemodialysis were recruited and followed up for 5 years to record CV events. Genetic analysis was performed using single-nucleotide polymorphisms (SNPs) genotyping by Infinium Expanded Multi-Ethnic Genotyping Array (Illumina, San Diego, CA, USA) comparing patients with and without a history of CV events [161 cardiovascular diseases (CVDs) and 84 no CVDs]. The fixation index (Fst) measure was used to identify the most differentiated SNPs, and gene ontology analysis [Protein Analysis THrough Evolutionary Relationships (PANTHER) and Ingenuity Pathway Analysis (IPA)] was applied to define the biological/pathological roles of the associated SNPs. Partitioning tree analysis interrogated the genotype–phenotype relationship between discovered genetic variants and CV phenotypes. Cox regression analysis measured the effect of these SNPs on new CV events during the follow-up (FU).ResultsFst analysis identified 3218 SNPs that were significantly different between CVD and no CVD. Gene ontology analysis identified two of these SNPs as involved in cardiovascular disease pathways (Ingenuity Pathway) and heart development (Panther) and belonging to 2 different genes: Glucagon-like peptide-1 receptor (GLP1R) and Sarcoglycan delta (SGCD). The phenotype–genotype analysis found a higher percentage of CVD patients carrying the GLP1R rs10305445 allele A (P = 0.03) and lower percentages of CVD patients carrying the SGCD rs145292439 allele A (P = 0.038). Moreover, SGCD rs145292439 was associated with higher levels of high-density lipoprotein (P = 0.015). Cox analysis confirmed the increased frequency of CV events during the 5-year FU in patients carrying GLP1R rs1035445 allele A but it did not show any significant association with SGCD rs145292439.ConclusionsThis study identified GLP1R rs10305445 and SCGD rs145292439 as potential genetic markers that may explain the higher risk of CVD in hemodialysis patients.</description><identifier>ISSN: 2048-8505</identifier><identifier>ISSN: 2048-8513</identifier><identifier>EISSN: 2048-8513</identifier><identifier>DOI: 10.1093/ckj/sfz182</identifier><identifier>PMID: 32905248</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Care and treatment ; Chronic kidney failure ; Health aspects ; Hemodialysis ; Original ; Patient outcomes ; Peptides</subject><ispartof>Clinical Kidney Journal, 2020-08, Vol.13 (4), p.666-673</ispartof><rights>The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA. 2019</rights><rights>The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA.</rights><rights>COPYRIGHT 2020 Oxford University Press</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c475t-2e67f708d1728364e141edd66b08be0efa0a6acf038721377ee56f997055258a3</citedby><cites>FETCH-LOGICAL-c475t-2e67f708d1728364e141edd66b08be0efa0a6acf038721377ee56f997055258a3</cites><orcidid>0000-0002-8494-6252 ; 0000-0001-9274-5373</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467592/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467592/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32905248$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Terranegra, Annalisa</creatorcontrib><creatorcontrib>Arcidiacono, Teresa</creatorcontrib><creatorcontrib>Macrina, Lorenza</creatorcontrib><creatorcontrib>Brasacchio, Caterina</creatorcontrib><creatorcontrib>Pivari, Francesca</creatorcontrib><creatorcontrib>Mingione, Alessandra</creatorcontrib><creatorcontrib>Tomei, Sara</creatorcontrib><creatorcontrib>Mezzavilla, Massimo</creatorcontrib><creatorcontrib>Silcock, Lee</creatorcontrib><creatorcontrib>Cozzolino, Mario</creatorcontrib><creatorcontrib>Palmieri, Nicola</creatorcontrib><creatorcontrib>Conte, Ferruccio</creatorcontrib><creatorcontrib>Sirtori, Marcella</creatorcontrib><creatorcontrib>Rubinacci, Alessandro</creatorcontrib><creatorcontrib>Soldati, Laura</creatorcontrib><creatorcontrib>Vezzoli, Giuseppe</creatorcontrib><title>Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis</title><title>Clinical Kidney Journal</title><addtitle>Clin Kidney J</addtitle><description>BackgroundChronic kidney disease (CKD) patients under hemodialysis show a higher risk of cardiovascular (CV) mortality and morbidity than the general population. This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis. Methods A total of 245 CKD patients under hemodialysis were recruited and followed up for 5 years to record CV events. Genetic analysis was performed using single-nucleotide polymorphisms (SNPs) genotyping by Infinium Expanded Multi-Ethnic Genotyping Array (Illumina, San Diego, CA, USA) comparing patients with and without a history of CV events [161 cardiovascular diseases (CVDs) and 84 no CVDs]. The fixation index (Fst) measure was used to identify the most differentiated SNPs, and gene ontology analysis [Protein Analysis THrough Evolutionary Relationships (PANTHER) and Ingenuity Pathway Analysis (IPA)] was applied to define the biological/pathological roles of the associated SNPs. Partitioning tree analysis interrogated the genotype–phenotype relationship between discovered genetic variants and CV phenotypes. Cox regression analysis measured the effect of these SNPs on new CV events during the follow-up (FU).ResultsFst analysis identified 3218 SNPs that were significantly different between CVD and no CVD. Gene ontology analysis identified two of these SNPs as involved in cardiovascular disease pathways (Ingenuity Pathway) and heart development (Panther) and belonging to 2 different genes: Glucagon-like peptide-1 receptor (GLP1R) and Sarcoglycan delta (SGCD). The phenotype–genotype analysis found a higher percentage of CVD patients carrying the GLP1R rs10305445 allele A (P = 0.03) and lower percentages of CVD patients carrying the SGCD rs145292439 allele A (P = 0.038). Moreover, SGCD rs145292439 was associated with higher levels of high-density lipoprotein (P = 0.015). Cox analysis confirmed the increased frequency of CV events during the 5-year FU in patients carrying GLP1R rs1035445 allele A but it did not show any significant association with SGCD rs145292439.ConclusionsThis study identified GLP1R rs10305445 and SCGD rs145292439 as potential genetic markers that may explain the higher risk of CVD in hemodialysis patients.</description><subject>Care and treatment</subject><subject>Chronic kidney failure</subject><subject>Health aspects</subject><subject>Hemodialysis</subject><subject>Original</subject><subject>Patient outcomes</subject><subject>Peptides</subject><issn>2048-8505</issn><issn>2048-8513</issn><issn>2048-8513</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNp9klFrFDEQxxdRbKl98QNIQAQpbJtkN5vdF6EUW4WCL_oc5pLJXXq55Ex2D66fxQ9rjq2HBTF5yJD5zX8m4V9Vbxm9ZHRorvT64SrbR9bzF9Upp21f94I1L48xFSfVec4PtKySoa14XZ00fKCCt_1p9evOTxqWMdTerZFscTs6gzUjCXWJYyIQDMmQdFz6vYZADPoRyBIDjk6THSQHYczkkAJrUY8lTMbFHWQ9eUgkubwmLhC9SjGUkrUzAffEuIyQS0sYHR4UpmAwkRVuonHg99nlN9UrCz7j-dN5Vv24_fz95kt9_-3u6831fa1bKcaaYyetpL1hkvdN1yJrGRrTdQvaL5CiBQodaEubXnLWSIkoOjsMkgrBRQ_NWfVp1t1Oiw0aXcZJ4NU2uQ2kvYrg1PNMcCu1jDsl206KgReBj08CKf6cMI9q47JG7yFgnLLibcu68v0DK-j7GV2CR-WCjUVRH3B13bWCSt6IoVCX_6DKNrhxOga0rtw_K7iYC3SKOSe0x-kZVQejqGIUNRulwO_-fu8R_WOLAnyYgTht_yf0G10HyaQ</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>Terranegra, Annalisa</creator><creator>Arcidiacono, Teresa</creator><creator>Macrina, Lorenza</creator><creator>Brasacchio, Caterina</creator><creator>Pivari, Francesca</creator><creator>Mingione, Alessandra</creator><creator>Tomei, Sara</creator><creator>Mezzavilla, Massimo</creator><creator>Silcock, Lee</creator><creator>Cozzolino, Mario</creator><creator>Palmieri, Nicola</creator><creator>Conte, Ferruccio</creator><creator>Sirtori, Marcella</creator><creator>Rubinacci, Alessandro</creator><creator>Soldati, Laura</creator><creator>Vezzoli, Giuseppe</creator><general>Oxford University Press</general><scope>TOX</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-8494-6252</orcidid><orcidid>https://orcid.org/0000-0001-9274-5373</orcidid></search><sort><creationdate>20200801</creationdate><title>Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis</title><author>Terranegra, Annalisa ; Arcidiacono, Teresa ; Macrina, Lorenza ; Brasacchio, Caterina ; Pivari, Francesca ; Mingione, Alessandra ; Tomei, Sara ; Mezzavilla, Massimo ; Silcock, Lee ; Cozzolino, Mario ; Palmieri, Nicola ; Conte, Ferruccio ; Sirtori, Marcella ; Rubinacci, Alessandro ; Soldati, Laura ; Vezzoli, Giuseppe</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c475t-2e67f708d1728364e141edd66b08be0efa0a6acf038721377ee56f997055258a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Care and treatment</topic><topic>Chronic kidney failure</topic><topic>Health aspects</topic><topic>Hemodialysis</topic><topic>Original</topic><topic>Patient outcomes</topic><topic>Peptides</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Terranegra, Annalisa</creatorcontrib><creatorcontrib>Arcidiacono, Teresa</creatorcontrib><creatorcontrib>Macrina, Lorenza</creatorcontrib><creatorcontrib>Brasacchio, Caterina</creatorcontrib><creatorcontrib>Pivari, Francesca</creatorcontrib><creatorcontrib>Mingione, Alessandra</creatorcontrib><creatorcontrib>Tomei, Sara</creatorcontrib><creatorcontrib>Mezzavilla, Massimo</creatorcontrib><creatorcontrib>Silcock, Lee</creatorcontrib><creatorcontrib>Cozzolino, Mario</creatorcontrib><creatorcontrib>Palmieri, Nicola</creatorcontrib><creatorcontrib>Conte, Ferruccio</creatorcontrib><creatorcontrib>Sirtori, Marcella</creatorcontrib><creatorcontrib>Rubinacci, Alessandro</creatorcontrib><creatorcontrib>Soldati, Laura</creatorcontrib><creatorcontrib>Vezzoli, Giuseppe</creatorcontrib><collection>Access via Oxford University Press (Open Access Collection)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Clinical Kidney Journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Terranegra, Annalisa</au><au>Arcidiacono, Teresa</au><au>Macrina, Lorenza</au><au>Brasacchio, Caterina</au><au>Pivari, Francesca</au><au>Mingione, Alessandra</au><au>Tomei, Sara</au><au>Mezzavilla, Massimo</au><au>Silcock, Lee</au><au>Cozzolino, Mario</au><au>Palmieri, Nicola</au><au>Conte, Ferruccio</au><au>Sirtori, Marcella</au><au>Rubinacci, Alessandro</au><au>Soldati, Laura</au><au>Vezzoli, Giuseppe</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis</atitle><jtitle>Clinical Kidney Journal</jtitle><addtitle>Clin Kidney J</addtitle><date>2020-08-01</date><risdate>2020</risdate><volume>13</volume><issue>4</issue><spage>666</spage><epage>673</epage><pages>666-673</pages><issn>2048-8505</issn><issn>2048-8513</issn><eissn>2048-8513</eissn><abstract>BackgroundChronic kidney disease (CKD) patients under hemodialysis show a higher risk of cardiovascular (CV) mortality and morbidity than the general population. This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis. Methods A total of 245 CKD patients under hemodialysis were recruited and followed up for 5 years to record CV events. Genetic analysis was performed using single-nucleotide polymorphisms (SNPs) genotyping by Infinium Expanded Multi-Ethnic Genotyping Array (Illumina, San Diego, CA, USA) comparing patients with and without a history of CV events [161 cardiovascular diseases (CVDs) and 84 no CVDs]. The fixation index (Fst) measure was used to identify the most differentiated SNPs, and gene ontology analysis [Protein Analysis THrough Evolutionary Relationships (PANTHER) and Ingenuity Pathway Analysis (IPA)] was applied to define the biological/pathological roles of the associated SNPs. Partitioning tree analysis interrogated the genotype–phenotype relationship between discovered genetic variants and CV phenotypes. Cox regression analysis measured the effect of these SNPs on new CV events during the follow-up (FU).ResultsFst analysis identified 3218 SNPs that were significantly different between CVD and no CVD. Gene ontology analysis identified two of these SNPs as involved in cardiovascular disease pathways (Ingenuity Pathway) and heart development (Panther) and belonging to 2 different genes: Glucagon-like peptide-1 receptor (GLP1R) and Sarcoglycan delta (SGCD). The phenotype–genotype analysis found a higher percentage of CVD patients carrying the GLP1R rs10305445 allele A (P = 0.03) and lower percentages of CVD patients carrying the SGCD rs145292439 allele A (P = 0.038). Moreover, SGCD rs145292439 was associated with higher levels of high-density lipoprotein (P = 0.015). Cox analysis confirmed the increased frequency of CV events during the 5-year FU in patients carrying GLP1R rs1035445 allele A but it did not show any significant association with SGCD rs145292439.ConclusionsThis study identified GLP1R rs10305445 and SCGD rs145292439 as potential genetic markers that may explain the higher risk of CVD in hemodialysis patients.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>32905248</pmid><doi>10.1093/ckj/sfz182</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-8494-6252</orcidid><orcidid>https://orcid.org/0000-0001-9274-5373</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Care and treatment Chronic kidney failure Health aspects Hemodialysis Original Patient outcomes Peptides |
title | Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis |
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