Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis

Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific tre...

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Main Authors: Anna Tyler, J. Matthew Mahoney, Gregory W. Carter
Format: Article
Language:English
Published: Oxford University Press 2020-01-01
Series:G3: Genes, Genomes, Genetics
Subjects:
Online Access:http://g3journal.org/lookup/doi/10.1534/g3.119.400775
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author Anna Tyler
J. Matthew Mahoney
Gregory W. Carter
author_facet Anna Tyler
J. Matthew Mahoney
Gregory W. Carter
author_sort Anna Tyler
collection DOAJ
description Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.
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spelling doaj.art-ae44e58514db4d158f5f9b0d8e4e0b5b2022-12-21T18:27:42ZengOxford University PressG3: Genes, Genomes, Genetics2160-18362020-01-0110115116310.1534/g3.119.40077514Genetic Interactions Affect Lung Function in Patients with Systemic SclerosisAnna TylerJ. Matthew MahoneyGregory W. CarterScleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.http://g3journal.org/lookup/doi/10.1534/g3.119.400775epistasissystemic sclerosissclerodermawnt signaling
spellingShingle Anna Tyler
J. Matthew Mahoney
Gregory W. Carter
Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis
G3: Genes, Genomes, Genetics
epistasis
systemic sclerosis
scleroderma
wnt signaling
title Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis
title_full Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis
title_fullStr Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis
title_full_unstemmed Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis
title_short Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis
title_sort genetic interactions affect lung function in patients with systemic sclerosis
topic epistasis
systemic sclerosis
scleroderma
wnt signaling
url http://g3journal.org/lookup/doi/10.1534/g3.119.400775
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AT gregorywcarter geneticinteractionsaffectlungfunctioninpatientswithsystemicsclerosis