Assessing human disease phenotype similarity based on ontology

2016 ◽  
Author(s):  
Duc-Hau Le ◽  
Anh-Minh Dao ◽  
Ba-Su Pham
Keyword(s):  
Human Disease ◽  
Disease Phenotype ◽  
Phenotype Similarity

scholarly journals Myopia disease mouse models: a missense point mutation (S673G) and a protein-truncating mutation of the Zfp644 mimic human disease phenotype

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Katarzyna I. Szczerkowska ◽  
Silvia Petrezselyova ◽  
Jiri Lindovsky ◽  
Marcela Palkova ◽  
Jan Dvorak ◽  
...  
Keyword(s):  
Point Mutation ◽  
Mouse Models ◽  
Human Disease ◽  
Disease Phenotype ◽  
Truncating Mutation

scholarly journals Mutations in the splicing regulator Prp31 lead to retinal degeneration in Drosophila

Biology Open ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. bio052332 ◽  
Author(s):  
Sarita Hebbar ◽  
Malte Lehmann ◽  
Sarah Behrens ◽  
Catrin Hälsig ◽  
Weihua Leng ◽  
...  
Keyword(s):  
Retinal Degeneration ◽  
Human Disease ◽  
Molecular Mechanisms ◽  
Autosomal Dominant ◽  
Light Stress ◽  
Mrna Levels ◽  
Disease Phenotype ◽  
Induced Mutations ◽  
Splicing Regulator ◽  
Splicing Machinery

ABSTRACTRetinitis pigmentosa (RP) is a clinically heterogeneous disease affecting 1.6 million people worldwide. The second-largest group of genes causing autosomal dominant RP in human encodes regulators of the splicing machinery. Yet, how defects in splicing factor genes are linked to the aetiology of the disease remains largely elusive. To explore possible mechanisms underlying retinal degeneration caused by mutations in regulators of the splicing machinery, we induced mutations in Drosophila Prp31, the orthologue of human PRPF31, mutations in which are associated with RP11. Flies heterozygous mutant for Prp31 are viable and develop normal eyes and retina. However, photoreceptors degenerate under light stress, thus resembling the human disease phenotype. Degeneration is associated with increased accumulation of the visual pigment rhodopsin 1 and increased mRNA levels of twinfilin, a gene associated with rhodopsin trafficking. Reducing rhodopsin levels by raising animals in a carotenoid-free medium not only attenuates rhodopsin accumulation, but also retinal degeneration. Given a similar importance of proper rhodopsin trafficking for photoreceptor homeostasis in human, results obtained in flies presented here will also contribute to further unravel molecular mechanisms underlying the human disease.This paper has an associated First Person interview with the co-first authors of the article.

scholarly journals Human-Disease Phenotype Map Derived from PheWAS across 38,682 Individuals

2019 ◽  
Vol 104 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Anurag Verma ◽  
Lisa Bang ◽  
Jason E. Miller ◽  
Yanfei Zhang ◽  
Ming Ta Michael Lee ◽  
...  
Keyword(s):  
Human Disease ◽  
Disease Phenotype

scholarly journals NETMAGE: a humaN-disEase phenoType MAp GEnerator for the Visualization of PheWAS

2020 ◽  
Author(s):  
Vivek Sriram ◽  
Manu Shivakumar ◽  
Sang-Hyuk Jung ◽  
Lisa Bang ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Human Disease ◽  
Supplementary Information ◽  
Phenotypic Traits ◽  
Test Case ◽  
Disease Phenotype ◽  
Genetic Associations ◽  
Link Type ◽  
Genetic Components ◽  
Phenotype Network ◽  
Shared Genetic

AbstractSummaryGiven genetic associations from a PheWAS, a disease-disease network can be constructed where nodes represent phenotypes and edges represent shared genetic associations between phenotypes. To improve the accessibility of the visualization of shared genetic components across phenotypes, we developed the humaN-disEase phenoType MAp GEnerator (NETMAGE), a web-based tool that produces interactive phenotype network visualizations from summarized PheWAS results. Users can search the map by a variety of attributes, and they can select nodes to view information such as related phenotypes, associated SNPs, and other network statistics. As a test case, we constructed a network using UK BioBank PheWAS summary data. By examining the associations between phenotypes in our map, we can potentially identify novel instances of pleiotropy, where loci influence multiple phenotypic traits. Thus, our tool provides researchers with a means to identify prospective genetic targets for drug design, contributing to the exploration of personalized medicine.Availability and implementationOur service runs at https://hdpm.biomedinfolab.com. Source code can be downloaded at https://github.com/dokyoonkimlab/[email protected] informationSupplementary data and user guide are available at Bioinformatics online.

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