ArticlePloS one2015
Network Modules of the Cross-Species Genotype-Phenotype Map Reflect the Clinical Severity of Human Diseases.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Network-based machine learning approach to predict immunotherapy response in cancer patients.Nature communications · 2022Article
- DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.PLoS computational biology · 2020Article
- Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients.Nature communications · 2020Article
- Human and mouse essentiality screens as a resource for disease gene discovery.Nature communications · 2020Article
- Link clustering explains non-central and contextually essential genes in protein interaction networks.Scientific reports · 2019Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in genome sequencing techniques have improved our understanding of the genotype-phenotype relationship between genetic variants and human diseases. However, genetic variations uncovered from patient populations do not provide enough information to understand the mechanisms underlying the progression and clinical severity of human diseases. Moreover, building a high-resolution genotype-phenotype map is difficult due to the diverse genetic backgrounds of the human population. We built a cross-species genotype-phenotype map to explain the clinical severity of human genetic diseases. We developed a data-integrative framework to investigate network modules composed of human diseases mapped with gene essentiality measured from a model organism. Essential and nonessential genes connect diseases of different types which form clusters in the human disease network. In a large patient population study, we found that disease classes enriched with essential genes tended to show a higher mortality rate than disease classes enriched with nonessential genes. Moreover, high disease mortality rates are explained by the multiple comorbid relationships and the high pleiotropy of disease genes found in the essential gene-enriched diseases. Our results reveal that the genotype-phenotype map of a model organism can facilitate the identification of human disease-gene associations and predict human disease progression.
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