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Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset

BACKGROUND: 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. METHODS/PRINCIPAL FINDINGS: We evaluated single nucleotide pol...

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Autores principales: Chibnik, Lori B., Keenan, Brendan T., Cui, Jing, Liao, Katherine P., Costenbader, Karen H., Plenge, Robert M., Karlson, Elizabeth W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171415/
https://www.ncbi.nlm.nih.gov/pubmed/21931699
http://dx.doi.org/10.1371/journal.pone.0024380
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author Chibnik, Lori B.
Keenan, Brendan T.
Cui, Jing
Liao, Katherine P.
Costenbader, Karen H.
Plenge, Robert M.
Karlson, Elizabeth W.
author_facet Chibnik, Lori B.
Keenan, Brendan T.
Cui, Jing
Liao, Katherine P.
Costenbader, Karen H.
Plenge, Robert M.
Karlson, Elizabeth W.
author_sort Chibnik, Lori B.
collection PubMed
description BACKGROUND: 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. METHODS/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: 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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spelling pubmed-31714152011-09-19 Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset Chibnik, Lori B. Keenan, Brendan T. Cui, Jing Liao, Katherine P. Costenbader, Karen H. Plenge, Robert M. Karlson, Elizabeth W. PLoS One Research Article BACKGROUND: 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. METHODS/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies. Public Library of Science 2011-09-12 /pmc/articles/PMC3171415/ /pubmed/21931699 http://dx.doi.org/10.1371/journal.pone.0024380 Text en Chibnik et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chibnik, Lori B.
Keenan, Brendan T.
Cui, Jing
Liao, Katherine P.
Costenbader, Karen H.
Plenge, Robert M.
Karlson, Elizabeth W.
Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset
title Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset
title_full Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset
title_fullStr Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset
title_full_unstemmed Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset
title_short Genetic Risk Score Predicting Risk of Rheumatoid Arthritis Phenotypes and Age of Symptom Onset
title_sort genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171415/
https://www.ncbi.nlm.nih.gov/pubmed/21931699
http://dx.doi.org/10.1371/journal.pone.0024380
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