Influence of genetic variation on plasma protein levels in older adults using a multi-analyte panel
Proteins, widely studied as potential biomarkers, play important roles in numerous physiological functions and diseases. Genetic variation may modulate corresponding protein levels and point to the role of these variants in disease pathophysiology. Effects of individual single nucleotide polymorphis...
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| Veröffentlicht in: | PloS one 2013-07, Vol.8 (7), p.e70269-e70269 |
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| creator | Kim, Sungeun Swaminathan, Shanker Inlow, Mark Risacher, Shannon L Nho, Kwangsik Shen, Li Foroud, Tatiana M Petersen, Ronald C Aisen, Paul S Soares, Holly Toledo, Jon B Shaw, Leslie M Trojanowski, John Q Weiner, Michael W McDonald, Brenna C Farlow, Martin R Ghetti, Bernardino Saykin, Andrew J |
| description | Proteins, widely studied as potential biomarkers, play important roles in numerous physiological functions and diseases. Genetic variation may modulate corresponding protein levels and point to the role of these variants in disease pathophysiology. Effects of individual single nucleotide polymorphisms (SNPs) within a gene were analyzed for corresponding plasma protein levels using genome-wide association study (GWAS) genotype data and proteomic panel data with 132 quality-controlled analytes from 521 Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Linear regression analysis detected 112 significant (Bonferroni threshold p=2.44×10(-5)) associations between 27 analytes and 112 SNPs. 107 out of these 112 associations were tested in the Indiana Memory and Aging Study (IMAS) cohort for replication and 50 associations were replicated at uncorrected p |
| doi_str_mv | 10.1371/journal.pone.0070269 |
| format | Article |
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Genetic variation may modulate corresponding protein levels and point to the role of these variants in disease pathophysiology. Effects of individual single nucleotide polymorphisms (SNPs) within a gene were analyzed for corresponding plasma protein levels using genome-wide association study (GWAS) genotype data and proteomic panel data with 132 quality-controlled analytes from 521 Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Linear regression analysis detected 112 significant (Bonferroni threshold p=2.44×10(-5)) associations between 27 analytes and 112 SNPs. 107 out of these 112 associations were tested in the Indiana Memory and Aging Study (IMAS) cohort for replication and 50 associations were replicated at uncorrected p<0.05 in the same direction of effect as those in the ADNI. We identified multiple novel associations including the association of rs7517126 with plasma complement factor H-related protein 1 (CFHR1) level at p<1.46×10(-60), accounting for 40 percent of total variation of the protein level. We serendipitously found the association of rs6677604 with the same protein at p<9.29×10(-112). Although these two SNPs were not in the strong linkage disequilibrium, 61 percent of total variation of CFHR1 was accounted for by rs6677604 without additional variation by rs7517126 when both SNPs were tested together. 78 other SNP-protein associations in the ADNI sample exceeded genome-wide significance (5×10(-8)). Our results confirmed previously identified gene-protein associations for interleukin-6 receptor, chemokine CC-4, angiotensin-converting enzyme, and angiotensinogen, although the direction of effect was reversed in some cases. This study is among the first analyses of gene-protein product relationships integrating multiplex-panel proteomics and targeted genes extracted from a GWAS array. With intensive searches taking place for proteomic biomarkers for many diseases, the role of genetic variation takes on new importance and should be considered in interpretation of proteomic results.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0070269</identifier><identifier>PMID: 23894628</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adults ; Aged ; Aged, 80 and over ; Aging ; Alzheimer Disease - blood ; Alzheimer Disease - genetics ; Alzheimer's disease ; Angiotensin ; Angiotensinogen ; Apolipoproteins E - blood ; Apolipoproteins E - genetics ; Bioindicators ; Bioinformatics ; Biology ; Biomarkers ; Blood pressure ; Blood proteins ; Chromosomes ; Complement C3b Inactivator Proteins - analysis ; Complement C3b Inactivator Proteins - genetics ; Complement factor H ; Data processing ; Disease ; Disease control ; Elderly ; Female ; Genes ; Genetic aspects ; Genetic diversity ; Genetics ; Genome-wide association studies ; Genome-Wide Association Study ; Genomes ; Genomics ; Haplotypes ; Humans ; Hypertension ; Interleukin ; Interleukin 6 ; Laboratories ; Linear Models ; Linkage disequilibrium ; Male ; Medical imaging ; Medical research ; Medicine ; Middle Aged ; Multiplexing ; Neuroimaging ; Neurology ; Older people ; Pathology ; Peptidyl-dipeptidase A ; Physicians ; Plasma ; Polymorphism, Single Nucleotide ; Proteins ; Proteomics ; Regression analysis ; Single nucleotide polymorphisms ; Single-nucleotide polymorphism ; Studies ; Variation</subject><ispartof>PloS one, 2013-07, Vol.8 (7), p.e70269-e70269</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Kim 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>2013 Kim et al 2013 Kim et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-7a72185d4fa92f8579f09638df6c6632a55420bfb5de47d41c3d181f6613af0d3</citedby><cites>FETCH-LOGICAL-c692t-7a72185d4fa92f8579f09638df6c6632a55420bfb5de47d41c3d181f6613af0d3</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/PMC3720913/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720913/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23894628$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Sungeun</creatorcontrib><creatorcontrib>Swaminathan, Shanker</creatorcontrib><creatorcontrib>Inlow, Mark</creatorcontrib><creatorcontrib>Risacher, Shannon L</creatorcontrib><creatorcontrib>Nho, Kwangsik</creatorcontrib><creatorcontrib>Shen, Li</creatorcontrib><creatorcontrib>Foroud, Tatiana M</creatorcontrib><creatorcontrib>Petersen, Ronald C</creatorcontrib><creatorcontrib>Aisen, Paul S</creatorcontrib><creatorcontrib>Soares, Holly</creatorcontrib><creatorcontrib>Toledo, Jon B</creatorcontrib><creatorcontrib>Shaw, Leslie M</creatorcontrib><creatorcontrib>Trojanowski, John Q</creatorcontrib><creatorcontrib>Weiner, Michael W</creatorcontrib><creatorcontrib>McDonald, Brenna C</creatorcontrib><creatorcontrib>Farlow, Martin R</creatorcontrib><creatorcontrib>Ghetti, Bernardino</creatorcontrib><creatorcontrib>Saykin, Andrew J</creatorcontrib><creatorcontrib>Alzheimer’s Disease Neuroimaging Initiative (ADNI)</creatorcontrib><creatorcontrib>for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)</creatorcontrib><title>Influence of genetic variation on plasma protein levels in older adults using a multi-analyte panel</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Proteins, widely studied as potential biomarkers, play important roles in numerous physiological functions and diseases. Genetic variation may modulate corresponding protein levels and point to the role of these variants in disease pathophysiology. Effects of individual single nucleotide polymorphisms (SNPs) within a gene were analyzed for corresponding plasma protein levels using genome-wide association study (GWAS) genotype data and proteomic panel data with 132 quality-controlled analytes from 521 Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Linear regression analysis detected 112 significant (Bonferroni threshold p=2.44×10(-5)) associations between 27 analytes and 112 SNPs. 107 out of these 112 associations were tested in the Indiana Memory and Aging Study (IMAS) cohort for replication and 50 associations were replicated at uncorrected p<0.05 in the same direction of effect as those in the ADNI. We identified multiple novel associations including the association of rs7517126 with plasma complement factor H-related protein 1 (CFHR1) level at p<1.46×10(-60), accounting for 40 percent of total variation of the protein level. We serendipitously found the association of rs6677604 with the same protein at p<9.29×10(-112). Although these two SNPs were not in the strong linkage disequilibrium, 61 percent of total variation of CFHR1 was accounted for by rs6677604 without additional variation by rs7517126 when both SNPs were tested together. 78 other SNP-protein associations in the ADNI sample exceeded genome-wide significance (5×10(-8)). Our results confirmed previously identified gene-protein associations for interleukin-6 receptor, chemokine CC-4, angiotensin-converting enzyme, and angiotensinogen, although the direction of effect was reversed in some cases. This study is among the first analyses of gene-protein product relationships integrating multiplex-panel proteomics and targeted genes extracted from a GWAS array. With intensive searches taking place for proteomic biomarkers for many diseases, the role of genetic variation takes on new importance and should be considered in interpretation of proteomic results.</description><subject>Adults</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging</subject><subject>Alzheimer Disease - blood</subject><subject>Alzheimer Disease - genetics</subject><subject>Alzheimer's disease</subject><subject>Angiotensin</subject><subject>Angiotensinogen</subject><subject>Apolipoproteins E - blood</subject><subject>Apolipoproteins E - genetics</subject><subject>Bioindicators</subject><subject>Bioinformatics</subject><subject>Biology</subject><subject>Biomarkers</subject><subject>Blood pressure</subject><subject>Blood proteins</subject><subject>Chromosomes</subject><subject>Complement C3b Inactivator Proteins - analysis</subject><subject>Complement C3b Inactivator Proteins - genetics</subject><subject>Complement factor H</subject><subject>Data processing</subject><subject>Disease</subject><subject>Disease control</subject><subject>Elderly</subject><subject>Female</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genetic diversity</subject><subject>Genetics</subject><subject>Genome-wide association studies</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Haplotypes</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Interleukin</subject><subject>Interleukin 6</subject><subject>Laboratories</subject><subject>Linear Models</subject><subject>Linkage disequilibrium</subject><subject>Male</subject><subject>Medical imaging</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Middle Aged</subject><subject>Multiplexing</subject><subject>Neuroimaging</subject><subject>Neurology</subject><subject>Older people</subject><subject>Pathology</subject><subject>Peptidyl-dipeptidase A</subject><subject>Physicians</subject><subject>Plasma</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Proteins</subject><subject>Proteomics</subject><subject>Regression analysis</subject><subject>Single nucleotide polymorphisms</subject><subject>Single-nucleotide 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of genetic variation on plasma protein levels in older adults using a multi-analyte panel</title><author>Kim, Sungeun ; Swaminathan, Shanker ; Inlow, Mark ; Risacher, Shannon L ; Nho, Kwangsik ; Shen, Li ; Foroud, Tatiana M ; Petersen, Ronald C ; Aisen, Paul S ; Soares, Holly ; Toledo, Jon B ; Shaw, Leslie M ; Trojanowski, John Q ; Weiner, Michael W ; McDonald, Brenna C ; Farlow, Martin R ; Ghetti, Bernardino ; Saykin, Andrew J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-7a72185d4fa92f8579f09638df6c6632a55420bfb5de47d41c3d181f6613af0d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adults</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Aging</topic><topic>Alzheimer Disease - blood</topic><topic>Alzheimer Disease - genetics</topic><topic>Alzheimer's disease</topic><topic>Angiotensin</topic><topic>Angiotensinogen</topic><topic>Apolipoproteins E 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disequilibrium</topic><topic>Male</topic><topic>Medical imaging</topic><topic>Medical research</topic><topic>Medicine</topic><topic>Middle Aged</topic><topic>Multiplexing</topic><topic>Neuroimaging</topic><topic>Neurology</topic><topic>Older people</topic><topic>Pathology</topic><topic>Peptidyl-dipeptidase A</topic><topic>Physicians</topic><topic>Plasma</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Proteins</topic><topic>Proteomics</topic><topic>Regression analysis</topic><topic>Single nucleotide polymorphisms</topic><topic>Single-nucleotide polymorphism</topic><topic>Studies</topic><topic>Variation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Sungeun</creatorcontrib><creatorcontrib>Swaminathan, Shanker</creatorcontrib><creatorcontrib>Inlow, Mark</creatorcontrib><creatorcontrib>Risacher, Shannon L</creatorcontrib><creatorcontrib>Nho, Kwangsik</creatorcontrib><creatorcontrib>Shen, 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Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - 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>Kim, Sungeun</au><au>Swaminathan, Shanker</au><au>Inlow, Mark</au><au>Risacher, Shannon L</au><au>Nho, Kwangsik</au><au>Shen, Li</au><au>Foroud, Tatiana M</au><au>Petersen, Ronald C</au><au>Aisen, Paul S</au><au>Soares, Holly</au><au>Toledo, Jon B</au><au>Shaw, Leslie M</au><au>Trojanowski, John Q</au><au>Weiner, Michael W</au><au>McDonald, Brenna C</au><au>Farlow, Martin R</au><au>Ghetti, Bernardino</au><au>Saykin, Andrew J</au><aucorp>Alzheimer’s Disease Neuroimaging Initiative (ADNI)</aucorp><aucorp>for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Influence of genetic variation on plasma protein levels in older adults using a multi-analyte panel</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-07-23</date><risdate>2013</risdate><volume>8</volume><issue>7</issue><spage>e70269</spage><epage>e70269</epage><pages>e70269-e70269</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Proteins, widely studied as potential biomarkers, play important roles in numerous physiological functions and diseases. Genetic variation may modulate corresponding protein levels and point to the role of these variants in disease pathophysiology. Effects of individual single nucleotide polymorphisms (SNPs) within a gene were analyzed for corresponding plasma protein levels using genome-wide association study (GWAS) genotype data and proteomic panel data with 132 quality-controlled analytes from 521 Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Linear regression analysis detected 112 significant (Bonferroni threshold p=2.44×10(-5)) associations between 27 analytes and 112 SNPs. 107 out of these 112 associations were tested in the Indiana Memory and Aging Study (IMAS) cohort for replication and 50 associations were replicated at uncorrected p<0.05 in the same direction of effect as those in the ADNI. We identified multiple novel associations including the association of rs7517126 with plasma complement factor H-related protein 1 (CFHR1) level at p<1.46×10(-60), accounting for 40 percent of total variation of the protein level. We serendipitously found the association of rs6677604 with the same protein at p<9.29×10(-112). Although these two SNPs were not in the strong linkage disequilibrium, 61 percent of total variation of CFHR1 was accounted for by rs6677604 without additional variation by rs7517126 when both SNPs were tested together. 78 other SNP-protein associations in the ADNI sample exceeded genome-wide significance (5×10(-8)). Our results confirmed previously identified gene-protein associations for interleukin-6 receptor, chemokine CC-4, angiotensin-converting enzyme, and angiotensinogen, although the direction of effect was reversed in some cases. This study is among the first analyses of gene-protein product relationships integrating multiplex-panel proteomics and targeted genes extracted from a GWAS array. With intensive searches taking place for proteomic biomarkers for many diseases, the role of genetic variation takes on new importance and should be considered in interpretation of proteomic results.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23894628</pmid><doi>10.1371/journal.pone.0070269</doi><tpages>e70269</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2013-07, Vol.8 (7), p.e70269-e70269 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1974628926 |
| source | MEDLINE; Public Library of Science; DOAJ Directory of Open Access Journals; PubMed Central; Free Full-Text Journals in Chemistry; EZB Electronic Journals Library |
| subjects | Adults Aged Aged, 80 and over Aging Alzheimer Disease - blood Alzheimer Disease - genetics Alzheimer's disease Angiotensin Angiotensinogen Apolipoproteins E - blood Apolipoproteins E - genetics Bioindicators Bioinformatics Biology Biomarkers Blood pressure Blood proteins Chromosomes Complement C3b Inactivator Proteins - analysis Complement C3b Inactivator Proteins - genetics Complement factor H Data processing Disease Disease control Elderly Female Genes Genetic aspects Genetic diversity Genetics Genome-wide association studies Genome-Wide Association Study Genomes Genomics Haplotypes Humans Hypertension Interleukin Interleukin 6 Laboratories Linear Models Linkage disequilibrium Male Medical imaging Medical research Medicine Middle Aged Multiplexing Neuroimaging Neurology Older people Pathology Peptidyl-dipeptidase A Physicians Plasma Polymorphism, Single Nucleotide Proteins Proteomics Regression analysis Single nucleotide polymorphisms Single-nucleotide polymorphism Studies Variation |
| title | Influence of genetic variation on plasma protein levels in older adults using a multi-analyte panel |
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