Concordance of gene expression in human protein complexes reveals tissue specificity and pathology
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Concordance of gene expression in human protein complexes reveals tissue specificity and pathology. / Börnigen, Daniela; Pers, Tune H; Thorrez, Lieven; Huttenhower, Curtis; Moreau, Yves; Brunak, Søren.
In: NUCLEIC ACIDS RES, Vol. 41, No. 18, 10.2013, p. e171.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Concordance of gene expression in human protein complexes reveals tissue specificity and pathology
AU - Börnigen, Daniela
AU - Pers, Tune H
AU - Thorrez, Lieven
AU - Huttenhower, Curtis
AU - Moreau, Yves
AU - Brunak, Søren
PY - 2013/10
Y1 - 2013/10
N2 - Disease-causing variants in human genes usually lead to phenotypes specific to only a few tissues. Here, we present a method for predicting tissue specificity based on quantitative deregulation of protein complexes. The underlying assumption is that the degree of coordinated expression among proteins in a complex within a given tissue may pinpoint tissues that will be affected by a mutation in the complex and coordinated expression may reveal the complex to be active in the tissue. We identified known disease genes and their protein complex partners in a high-quality human interactome. Each susceptibility gene's tissue involvement was ranked based on coordinated expression with its interaction partners in a non-disease global map of human tissue-specific expression. The approach demonstrated high overall area under the curve (0.78) and was very successfully benchmarked against a random model and an approach not using protein complexes. This was illustrated by correct tissue predictions for three case studies on leptin, insulin-like-growth-factor 2 and the inhibitor of NF-κB kinase subunit gamma that show high concordant expression in biologically relevant tissues. Our method identifies novel gene-phenotype associations in human diseases and predicts the tissues where associated phenotypic effects may arise.
AB - Disease-causing variants in human genes usually lead to phenotypes specific to only a few tissues. Here, we present a method for predicting tissue specificity based on quantitative deregulation of protein complexes. The underlying assumption is that the degree of coordinated expression among proteins in a complex within a given tissue may pinpoint tissues that will be affected by a mutation in the complex and coordinated expression may reveal the complex to be active in the tissue. We identified known disease genes and their protein complex partners in a high-quality human interactome. Each susceptibility gene's tissue involvement was ranked based on coordinated expression with its interaction partners in a non-disease global map of human tissue-specific expression. The approach demonstrated high overall area under the curve (0.78) and was very successfully benchmarked against a random model and an approach not using protein complexes. This was illustrated by correct tissue predictions for three case studies on leptin, insulin-like-growth-factor 2 and the inhibitor of NF-κB kinase subunit gamma that show high concordant expression in biologically relevant tissues. Our method identifies novel gene-phenotype associations in human diseases and predicts the tissues where associated phenotypic effects may arise.
KW - Disease
KW - Gene Expression
KW - Humans
KW - Lamin Type A
KW - Multiprotein Complexes
KW - Organ Specificity
KW - Phenotype
KW - Protein Interaction Mapping
KW - Journal Article
KW - Research Support, Non-U.S. Gov't
KW - Research Support, U.S. Gov't, Non-P.H.S.
U2 - 10.1093/nar/gkt661
DO - 10.1093/nar/gkt661
M3 - SCORING: Journal article
C2 - 23921638
VL - 41
SP - e171
JO - NUCLEIC ACIDS RES
JF - NUCLEIC ACIDS RES
SN - 0305-1048
IS - 18
ER -