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A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis

Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA w...

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Autores principales: Nakaoka, Hirofumi, Cui, Tailin, Tajima, Atsushi, Oka, Akira, Mitsunaga, Shigeki, Kashiwase, Koichi, Homma, Yasuhiko, Sato, Shinji, Suzuki, Yasuo, Inoko, Hidetoshi, Inoue, Ituro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182219/
https://www.ncbi.nlm.nih.gov/pubmed/21980439
http://dx.doi.org/10.1371/journal.pone.0025389
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author Nakaoka, Hirofumi
Cui, Tailin
Tajima, Atsushi
Oka, Akira
Mitsunaga, Shigeki
Kashiwase, Koichi
Homma, Yasuhiko
Sato, Shinji
Suzuki, Yasuo
Inoko, Hidetoshi
Inoue, Ituro
author_facet Nakaoka, Hirofumi
Cui, Tailin
Tajima, Atsushi
Oka, Akira
Mitsunaga, Shigeki
Kashiwase, Koichi
Homma, Yasuhiko
Sato, Shinji
Suzuki, Yasuo
Inoko, Hidetoshi
Inoue, Ituro
author_sort Nakaoka, Hirofumi
collection PubMed
description Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: “leukocyte activation and differentiation”, “pattern-recognition receptor signaling pathway”, and “chemokines and their receptors”. These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways.
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spelling pubmed-31822192011-10-06 A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis Nakaoka, Hirofumi Cui, Tailin Tajima, Atsushi Oka, Akira Mitsunaga, Shigeki Kashiwase, Koichi Homma, Yasuhiko Sato, Shinji Suzuki, Yasuo Inoko, Hidetoshi Inoue, Ituro PLoS One Research Article Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: “leukocyte activation and differentiation”, “pattern-recognition receptor signaling pathway”, and “chemokines and their receptors”. These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways. Public Library of Science 2011-09-28 /pmc/articles/PMC3182219/ /pubmed/21980439 http://dx.doi.org/10.1371/journal.pone.0025389 Text en Nakaoka 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
Nakaoka, Hirofumi
Cui, Tailin
Tajima, Atsushi
Oka, Akira
Mitsunaga, Shigeki
Kashiwase, Koichi
Homma, Yasuhiko
Sato, Shinji
Suzuki, Yasuo
Inoko, Hidetoshi
Inoue, Ituro
A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis
title A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis
title_full A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis
title_fullStr A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis
title_full_unstemmed A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis
title_short A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis
title_sort systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182219/
https://www.ncbi.nlm.nih.gov/pubmed/21980439
http://dx.doi.org/10.1371/journal.pone.0025389
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