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Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset
Cumulative genetic profiles can help identify individuals at high-risk for developing RA. We examined the impact of 39 validated genetic risk alleles on the risk of RA phenotypes characterized by serologic and erosive status. We evaluated single nucleotide polymorphisms at 31 validated RA risk loci...
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Published in: | PloS one 2011-09, Vol.6 (9), p.e24380-e24380 |
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description | Cumulative genetic profiles can help identify individuals at high-risk for developing RA. We examined the impact of 39 validated genetic risk alleles on the risk of RA phenotypes characterized by serologic and erosive status.
We evaluated single nucleotide polymorphisms at 31 validated RA risk loci and 8 Human Leukocyte Antigen alleles among 542 Caucasian RA cases and 551 Caucasian controls from Nurses' Health Study and Nurses' Health Study II. We created a weighted genetic risk score (GRS) and evaluated it as 7 ordinal groups using logistic regression (adjusting for age and smoking) to assess the relationship between GRS group and odds of developing seronegative (RF- and CCP-), seropositive (RF+ or CCP+), erosive, and seropositive, erosive RA phenotypes. In separate case only analyses, we assessed the relationships between GRS and age of symptom onset. In 542 RA cases, 317 (58%) were seropositive, 163 (30%) had erosions and 105 (19%) were seropositive with erosions. Comparing the highest GRS risk group to the median group, we found an OR of 1.2 (95% CI = 0.8-2.1) for seronegative RA, 3.0 (95% CI = 1.9-4.7) for seropositive RA, 3.2 (95% CI = 1.8-5.6) for erosive RA, and 7.6 (95% CI = 3.6-16.3) for seropositive, erosive RA. No significant relationship was seen between GRS and age of onset.
Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies. |
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We evaluated single nucleotide polymorphisms at 31 validated RA risk loci and 8 Human Leukocyte Antigen alleles among 542 Caucasian RA cases and 551 Caucasian controls from Nurses' Health Study and Nurses' Health Study II. We created a weighted genetic risk score (GRS) and evaluated it as 7 ordinal groups using logistic regression (adjusting for age and smoking) to assess the relationship between GRS group and odds of developing seronegative (RF- and CCP-), seropositive (RF+ or CCP+), erosive, and seropositive, erosive RA phenotypes. In separate case only analyses, we assessed the relationships between GRS and age of symptom onset. In 542 RA cases, 317 (58%) were seropositive, 163 (30%) had erosions and 105 (19%) were seropositive with erosions. Comparing the highest GRS risk group to the median group, we found an OR of 1.2 (95% CI = 0.8-2.1) for seronegative RA, 3.0 (95% CI = 1.9-4.7) for seropositive RA, 3.2 (95% CI = 1.8-5.6) for erosive RA, and 7.6 (95% CI = 3.6-16.3) for seropositive, erosive RA. No significant relationship was seen between GRS and age of onset.
Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0024380</identifier><identifier>PMID: 21931699</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Age ; Age of Onset ; Alleles ; Arthritis ; Arthritis, Rheumatoid - blood ; Arthritis, Rheumatoid - epidemiology ; Arthritis, Rheumatoid - genetics ; Arthritis, Rheumatoid - pathology ; Biology ; Case-Control Studies ; Chromosomes ; Electronic health records ; Female ; Genetic aspects ; Genetic Predisposition to Disease ; Genetic research ; Genomics ; Genotype & phenotype ; Group dynamics ; Haplotypes ; Health - statistics & numerical data ; Health risk assessment ; Histocompatibility antigen HLA ; HLA antigens ; Hospitals ; Humans ; Immunoglobulins ; Immunology ; Leukocytes ; Medical personnel ; Medicine ; Middle Aged ; Nurses ; Nurses - statistics & numerical data ; Odds Ratio ; Peptides ; Phenotype ; Phenotypes ; Proteins ; Regression analysis ; Rheumatoid arthritis ; Rheumatoid factor ; Rheumatology ; Risk Factors ; Risk groups ; ROC Curve ; Single nucleotide polymorphisms ; Single-nucleotide polymorphism ; Smoking ; Studies ; United States - epidemiology ; Womens health</subject><ispartof>PloS one, 2011-09, Vol.6 (9), p.e24380-e24380</ispartof><rights>COPYRIGHT 2011 Public Library of Science</rights><rights>2011 Chibnik 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>Chibnik et al. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c757t-a2755bc36962f1f313ee7dac84e6b52a96f450e930521a8cc28c27c3b495c0673</citedby><cites>FETCH-LOGICAL-c757t-a2755bc36962f1f313ee7dac84e6b52a96f450e930521a8cc28c27c3b495c0673</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1308800980/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1308800980?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21931699$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ahuja, Sunil K.</contributor><creatorcontrib>Chibnik, Lori B</creatorcontrib><creatorcontrib>Keenan, Brendan T</creatorcontrib><creatorcontrib>Cui, Jing</creatorcontrib><creatorcontrib>Liao, Katherine P</creatorcontrib><creatorcontrib>Costenbader, Karen H</creatorcontrib><creatorcontrib>Plenge, Robert M</creatorcontrib><creatorcontrib>Karlson, Elizabeth W</creatorcontrib><title>Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Cumulative genetic profiles can help identify individuals at high-risk for developing RA. We examined the impact of 39 validated genetic risk alleles on the risk of RA phenotypes characterized by serologic and erosive status.
We evaluated single nucleotide polymorphisms at 31 validated RA risk loci and 8 Human Leukocyte Antigen alleles among 542 Caucasian RA cases and 551 Caucasian controls from Nurses' Health Study and Nurses' Health Study II. We created a weighted genetic risk score (GRS) and evaluated it as 7 ordinal groups using logistic regression (adjusting for age and smoking) to assess the relationship between GRS group and odds of developing seronegative (RF- and CCP-), seropositive (RF+ or CCP+), erosive, and seropositive, erosive RA phenotypes. In separate case only analyses, we assessed the relationships between GRS and age of symptom onset. In 542 RA cases, 317 (58%) were seropositive, 163 (30%) had erosions and 105 (19%) were seropositive with erosions. Comparing the highest GRS risk group to the median group, we found an OR of 1.2 (95% CI = 0.8-2.1) for seronegative RA, 3.0 (95% CI = 1.9-4.7) for seropositive RA, 3.2 (95% CI = 1.8-5.6) for erosive RA, and 7.6 (95% CI = 3.6-16.3) for seropositive, erosive RA. No significant relationship was seen between GRS and age of onset.
Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies.</description><subject>Adult</subject><subject>Age</subject><subject>Age of Onset</subject><subject>Alleles</subject><subject>Arthritis</subject><subject>Arthritis, Rheumatoid - blood</subject><subject>Arthritis, Rheumatoid - epidemiology</subject><subject>Arthritis, Rheumatoid - genetics</subject><subject>Arthritis, Rheumatoid - pathology</subject><subject>Biology</subject><subject>Case-Control Studies</subject><subject>Chromosomes</subject><subject>Electronic health records</subject><subject>Female</subject><subject>Genetic aspects</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic research</subject><subject>Genomics</subject><subject>Genotype & phenotype</subject><subject>Group dynamics</subject><subject>Haplotypes</subject><subject>Health - statistics & numerical data</subject><subject>Health risk assessment</subject><subject>Histocompatibility antigen HLA</subject><subject>HLA antigens</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Immunoglobulins</subject><subject>Immunology</subject><subject>Leukocytes</subject><subject>Medical personnel</subject><subject>Medicine</subject><subject>Middle Aged</subject><subject>Nurses</subject><subject>Nurses - statistics & numerical data</subject><subject>Odds Ratio</subject><subject>Peptides</subject><subject>Phenotype</subject><subject>Phenotypes</subject><subject>Proteins</subject><subject>Regression analysis</subject><subject>Rheumatoid arthritis</subject><subject>Rheumatoid factor</subject><subject>Rheumatology</subject><subject>Risk Factors</subject><subject>Risk groups</subject><subject>ROC Curve</subject><subject>Single nucleotide polymorphisms</subject><subject>Single-nucleotide polymorphism</subject><subject>Smoking</subject><subject>Studies</subject><subject>United States - epidemiology</subject><subject>Womens health</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9-L1DAQx4so3nn6H4gWBMWHXZMmTZoX4Tj0XDg48NejIZtO26xt00tScf97U7d3bOUeJA8JM5_5TjKZSZLnGK0x4fjdzo6uV-16sD2sEcooKdCD5BQLkq1YhsjDo_NJ8sT7HUI5KRh7nJxk0YOZEKfJj0voIRidOuN_pl5bB-ngoDQ6mL4-WG2VugbGTgVrylS50DgTjE-HBnob9gP4VPXRUcOE-n03BNultvcQniaPKtV6eDbvZ8m3jx--XnxaXV1fbi7Or1aa5zysVMbzfKsJEyyrcEUwAeCl0gUFts0zJVhFcwSCoDzDqtA6K3TGNdlSkWvEODlLXh50h9Z6OZfGS0xQUSAkChSJzYEordrJwZlOub20ysi_ButqGV9mdAuyEhXdMlpyyhTN4w0Eo7nGVBXAM15NWu_nbOO2g1JDH5xqF6JLT28aWdtfkmCOKc6jwJtZwNmbEXyQnfEa2lb1YEcvC0EiSgSL5Kt_yPsfN1O1ivc3fWVjWj1pynPKWcQwn6j1PVRcJXRGxzaqTLQvAt4uAiIT4Heo1ei93Hz5_P_s9fcl-_qIbUC1ofG2HYOJTbME6QHUznrvoLqrMUZymoLbashpCuQ8BTHsxfH_3AXdtj35A1DfAhs</recordid><startdate>20110912</startdate><enddate>20110912</enddate><creator>Chibnik, Lori B</creator><creator>Keenan, Brendan T</creator><creator>Cui, Jing</creator><creator>Liao, Katherine P</creator><creator>Costenbader, Karen H</creator><creator>Plenge, Robert M</creator><creator>Karlson, Elizabeth W</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20110912</creationdate><title>Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset</title><author>Chibnik, Lori B ; Keenan, Brendan T ; Cui, Jing ; Liao, Katherine P ; Costenbader, Karen H ; Plenge, Robert M ; Karlson, Elizabeth W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c757t-a2755bc36962f1f313ee7dac84e6b52a96f450e930521a8cc28c27c3b495c0673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Adult</topic><topic>Age</topic><topic>Age of Onset</topic><topic>Alleles</topic><topic>Arthritis</topic><topic>Arthritis, Rheumatoid - blood</topic><topic>Arthritis, Rheumatoid - epidemiology</topic><topic>Arthritis, Rheumatoid - genetics</topic><topic>Arthritis, Rheumatoid - pathology</topic><topic>Biology</topic><topic>Case-Control Studies</topic><topic>Chromosomes</topic><topic>Electronic health records</topic><topic>Female</topic><topic>Genetic aspects</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic research</topic><topic>Genomics</topic><topic>Genotype & phenotype</topic><topic>Group dynamics</topic><topic>Haplotypes</topic><topic>Health - statistics & numerical data</topic><topic>Health risk assessment</topic><topic>Histocompatibility antigen HLA</topic><topic>HLA antigens</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Immunoglobulins</topic><topic>Immunology</topic><topic>Leukocytes</topic><topic>Medical personnel</topic><topic>Medicine</topic><topic>Middle Aged</topic><topic>Nurses</topic><topic>Nurses - statistics & numerical data</topic><topic>Odds Ratio</topic><topic>Peptides</topic><topic>Phenotype</topic><topic>Phenotypes</topic><topic>Proteins</topic><topic>Regression analysis</topic><topic>Rheumatoid arthritis</topic><topic>Rheumatoid factor</topic><topic>Rheumatology</topic><topic>Risk Factors</topic><topic>Risk groups</topic><topic>ROC Curve</topic><topic>Single nucleotide polymorphisms</topic><topic>Single-nucleotide polymorphism</topic><topic>Smoking</topic><topic>Studies</topic><topic>United States - 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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>Chibnik, Lori B</au><au>Keenan, Brendan T</au><au>Cui, Jing</au><au>Liao, Katherine P</au><au>Costenbader, Karen H</au><au>Plenge, Robert M</au><au>Karlson, Elizabeth W</au><au>Ahuja, Sunil K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2011-09-12</date><risdate>2011</risdate><volume>6</volume><issue>9</issue><spage>e24380</spage><epage>e24380</epage><pages>e24380-e24380</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Cumulative genetic profiles can help identify individuals at high-risk for developing RA. We examined the impact of 39 validated genetic risk alleles on the risk of RA phenotypes characterized by serologic and erosive status.
We evaluated single nucleotide polymorphisms at 31 validated RA risk loci and 8 Human Leukocyte Antigen alleles among 542 Caucasian RA cases and 551 Caucasian controls from Nurses' Health Study and Nurses' Health Study II. We created a weighted genetic risk score (GRS) and evaluated it as 7 ordinal groups using logistic regression (adjusting for age and smoking) to assess the relationship between GRS group and odds of developing seronegative (RF- and CCP-), seropositive (RF+ or CCP+), erosive, and seropositive, erosive RA phenotypes. In separate case only analyses, we assessed the relationships between GRS and age of symptom onset. In 542 RA cases, 317 (58%) were seropositive, 163 (30%) had erosions and 105 (19%) were seropositive with erosions. Comparing the highest GRS risk group to the median group, we found an OR of 1.2 (95% CI = 0.8-2.1) for seronegative RA, 3.0 (95% CI = 1.9-4.7) for seropositive RA, 3.2 (95% CI = 1.8-5.6) for erosive RA, and 7.6 (95% CI = 3.6-16.3) for seropositive, erosive RA. No significant relationship was seen between GRS and age of onset.
Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21931699</pmid><doi>10.1371/journal.pone.0024380</doi><tpages>e24380</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Age Age of Onset Alleles Arthritis Arthritis, Rheumatoid - blood Arthritis, Rheumatoid - epidemiology Arthritis, Rheumatoid - genetics Arthritis, Rheumatoid - pathology Biology Case-Control Studies Chromosomes Electronic health records Female Genetic aspects Genetic Predisposition to Disease Genetic research Genomics Genotype & phenotype Group dynamics Haplotypes Health - statistics & numerical data Health risk assessment Histocompatibility antigen HLA HLA antigens Hospitals Humans Immunoglobulins Immunology Leukocytes Medical personnel Medicine Middle Aged Nurses Nurses - statistics & numerical data Odds Ratio Peptides Phenotype Phenotypes Proteins Regression analysis Rheumatoid arthritis Rheumatoid factor Rheumatology Risk Factors Risk groups ROC Curve Single nucleotide polymorphisms Single-nucleotide polymorphism Smoking Studies United States - epidemiology Womens health |
title | Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset |
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