TY - JOUR
T1 - A human phenome-interactome network of protein complexes implicated in genetic disorders
AU - Hansen, Kasper Lage
AU - Karlberg, Erik, Olof, Linnart
AU - Størling, Zenia, Marian
AU - Ólason, Páll Ísólfur
AU - Pedersen, Anders Gorm
AU - Rigina, Olga
AU - Hinsby, Anders Mørkeberg
AU - Tumer, Zeynep
AU - Pociot, Flemming
AU - Tommerup, Niels
AU - Moreau, Yves
AU - Brunak, Søren
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 -