Network-based prediction of polygenic disease genes involved in cell motility.
Ontology highlight
ABSTRACT: Background
Schizophrenia and autism are examples of polygenic diseases caused by a multitude of genetic variants, many of which are still poorly understood. Recently, both diseases have been associated with disrupted neuron motility and migration patterns, suggesting that aberrant cell motility is a phenotype for these neurological diseases.Results
We formulate the POLYGENIC DISEASE PHENOTYPE Problem which seeks to identify candidate disease genes that may be associated with a phenotype such as cell motility. We present a machine learning approach to solve this problem for schizophrenia and autism genes within a brain-specific functional interaction network. Our method outperforms peer semi-supervised learning approaches, achieving better cross-validation accuracy across different sets of gold-standard positives. We identify top candidates for both schizophrenia and autism, and select six genes labeled as schizophrenia positives that are predicted to be associated with cell motility for follow-up experiments.Conclusions
Candidate genes predicted by our method suggest testable hypotheses about these genes’ role in cell motility regulation, offering a framework for generating predictions for experimental validation.
SUBMITTER: Bern M
PROVIDER: S-EPMC6584515 | biostudies-literature | 2019 Jun
REPOSITORIES: biostudies-literature
Publications
Network-based prediction of polygenic disease genes involved in cell motility.
Bern Miriam M King Alexander A Applewhite Derek A DA Ritz Anna A
BMC bioinformatics 20190620 Suppl 12
<h4>Background</h4>Schizophrenia and autism are examples of polygenic diseases caused by a multitude of genetic variants, many of which are still poorly understood. Recently, both diseases have been associated with disrupted neuron motility and migration patterns, suggesting that aberrant cell motility is a phenotype for these neurological diseases.<h4>Results</h4>We formulate the POLYGENIC DISEASE PHENOTYPE Problem which seeks to identify candidate disease genes that may be associated with a ph ...[more]
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