Proteins encoded in genomic regions associated with immune-mediated diseasephysically interact and suggest underlying biology.

Mario Cottone, Elizabeth J. Rossin, Yair Benita, Chris Cotsapas, Kasper Lage, Diana Tatar, Soumya Raychaudhuri, Ramnik J. Xavier, Mark J. Daly

Risultato della ricerca: Article

329 Citazioni (Scopus)

Abstract

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.
Lingua originaleEnglish
pagine (da-a)e1001273-e100127
Numero di pagine6
RivistaPLoS Genetics
Volume1
Stato di pubblicazionePublished - 2011

Fingerprint

genomics
Genome-Wide Association Study
Biological Sciences
loci
protein
Proteins
proteins
rheumatoid arthritis
Crohn disease
gene
Crohn Disease
Genes
Rheumatoid Arthritis
genome
genes
Phenotype
Protein Interaction Maps
phenotype
Immune System Diseases
protein products

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Genetics(clinical)
  • Cancer Research

Cita questo

Cottone, M., Rossin, E. J., Benita, Y., Cotsapas, C., Lage, K., Tatar, D., ... Daly, M. J. (2011). Proteins encoded in genomic regions associated with immune-mediated diseasephysically interact and suggest underlying biology. PLoS Genetics, 1, e1001273-e100127.

Proteins encoded in genomic regions associated with immune-mediated diseasephysically interact and suggest underlying biology. / Cottone, Mario; Rossin, Elizabeth J.; Benita, Yair; Cotsapas, Chris; Lage, Kasper; Tatar, Diana; Raychaudhuri, Soumya; Xavier, Ramnik J.; Daly, Mark J.

In: PLoS Genetics, Vol. 1, 2011, pag. e1001273-e100127.

Risultato della ricerca: Article

Cottone, M, Rossin, EJ, Benita, Y, Cotsapas, C, Lage, K, Tatar, D, Raychaudhuri, S, Xavier, RJ & Daly, MJ 2011, 'Proteins encoded in genomic regions associated with immune-mediated diseasephysically interact and suggest underlying biology.', PLoS Genetics, vol. 1, pagg. e1001273-e100127.
Cottone, Mario ; Rossin, Elizabeth J. ; Benita, Yair ; Cotsapas, Chris ; Lage, Kasper ; Tatar, Diana ; Raychaudhuri, Soumya ; Xavier, Ramnik J. ; Daly, Mark J. / Proteins encoded in genomic regions associated with immune-mediated diseasephysically interact and suggest underlying biology. In: PLoS Genetics. 2011 ; Vol. 1. pagg. e1001273-e100127.
@article{779073fc6dbe4fadaa53518585941f49,
title = "Proteins encoded in genomic regions associated with immune-mediated diseasephysically interact and suggest underlying biology.",
abstract = "Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.",
keywords = "Proteins, biology, encoded, genomic, immune-mediated, physically, regions",
author = "Mario Cottone and Rossin, {Elizabeth J.} and Yair Benita and Chris Cotsapas and Kasper Lage and Diana Tatar and Soumya Raychaudhuri and Xavier, {Ramnik J.} and Daly, {Mark J.}",
year = "2011",
language = "English",
volume = "1",
pages = "e1001273--e100127",
journal = "PLoS Genetics",
issn = "1553-7390",
publisher = "Public Library of Science",

}

TY - JOUR

T1 - Proteins encoded in genomic regions associated with immune-mediated diseasephysically interact and suggest underlying biology.

AU - Cottone, Mario

AU - Rossin, Elizabeth J.

AU - Benita, Yair

AU - Cotsapas, Chris

AU - Lage, Kasper

AU - Tatar, Diana

AU - Raychaudhuri, Soumya

AU - Xavier, Ramnik J.

AU - Daly, Mark J.

PY - 2011

Y1 - 2011

N2 - Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.

AB - Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.

KW - Proteins

KW - biology

KW - encoded

KW - genomic

KW - immune-mediated

KW - physically

KW - regions

UR - http://hdl.handle.net/10447/63635

M3 - Article

VL - 1

SP - e1001273-e100127

JO - PLoS Genetics

JF - PLoS Genetics

SN - 1553-7390

ER -