A human phenome-interactome network of protein complexes implicated in genetic disorders

TY - JOUR

T1 - A human phenome-interactome network of protein complexes implicated in genetic disorders

AU - Lage, Kasper

AU - Karlberg, E Olof

AU - Størling, Zenia M

AU - Olason, Páll I

AU - Pedersen, Anders G

AU - Rigina, Olga

AU - Hinsby, Anders M

AU - Tümer, Zeynep

AU - Pociot, Flemming

AU - Tommerup, Niels

AU - Moreau, Yves

AU - Brunak, Søren

N1 - Keywords: Bayes Theorem; Databases, Genetic; Databases, Protein; Genetic Diseases, Inborn; Genetic Predisposition to Disease; Humans; Mutation; Phenotype; Protein Conformation; Protein Interaction Mapping; Proteins; Proteome; Proteomics

PY - 2007

Y1 - 2007

N2 - We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking of protein complexes linked to human disease, we developed a Bayesian predictor that in 298 of 669 linkage intervals correctly ranks the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease. Our publicly available draft of protein complexes associated with pathology comprises 506 complexes, which reveal functional relationships between disease-promoting genes that will inform future experimentation.

AB - We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking of protein complexes linked to human disease, we developed a Bayesian predictor that in 298 of 669 linkage intervals correctly ranks the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease. Our publicly available draft of protein complexes associated with pathology comprises 506 complexes, which reveal functional relationships between disease-promoting genes that will inform future experimentation.

U2 - 10.1038/nbt1295

DO - 10.1038/nbt1295

M3 - Journal article

C2 - 17344885

SN - 1087-0156

VL - 25

SP - 309

EP - 316

JO - Nature Biotechnology

JF - Nature Biotechnology

IS - 3

ER -