IPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases. Issue 12 (19th October 2017)

• Record Type: Journal Article
• Authors: Hollingsworth, Ethan W; Vaughn, Jacob E; Orack, Josh C; Skinner, Chelsea; Khouri, Jamil; Lizarraga, Sofia B; Hester, Mark E; Watanabe, Fumihiro; Kosik, Kenneth S; Imitola, Jaime
• Is Part Of: EMBO molecular medicine. Volume 9:Issue 12(2017)
• Page Start: 1742
• Page End: 1762
• Publication Date: 2017-10-19
• Subjects: Alzheimer's disease -- iPSCs -- neurogenetics -- neurological diseases -- phenogenetics; Molecular biology -- Periodicals; Medical genetics -- Periodicals; Pathology, Molecular -- Periodicals; 616.04205
• DOI: 10.15252/emmm.201708191
• Languages: English
• ISSNs: 1757-4676

Abstract

Abstract: Disease modeling with induced pluripotent stem cells (iPSCs) is creating an abundance of phenotypic information that has become difficult to follow and interpret. Here, we report a systematic analysis of research practices and reporting bias in neurological disease models from 93 published articles. We find heterogeneity in current research practices and a reporting bias toward certain diseases. Moreover, we identified 663 CNS cell‐derived phenotypes from 243 patients and 214 controls, which varied by mutation type and developmental stage in vitro . We clustered these phenotypes into a taxonomy and characterized these phenotype–genotype relationships to generate a phenogenetic map that revealed novel correlations among previously unrelated genes. We also find that alterations in patient‐derived molecular profiles associated with cellular phenotypes, and dysregulated genes show predominant expression in brain regions with pathology. Last, we developed the iPS cell phenogenetic map project atlas (iPhemap), an open submission, online database to continually catalog disease phenotypes. Overall, our findings offer new insights into the phenogenetics of iPSC‐derived models while our web tool provides a platform for researchers to query and deposit phenotypic information of neurological diseases. Synopsis: The future translational utility of iPSC disease models relies on understanding the phenotype to genotype relationships of patient‐derived cells. A meta‐analysis of phenotypes generated thus far by iPSC neurological disease models highlights the strengths and limitations of current practices. There is great heterogeneity in the methodologies and a reporting bias toward neurodegenerative diseases. A novel taxonomy of in vitro CNS cell phenotypes was established from 243 patients and 214 controls. There are correlations between alterations in patient‐derived molecular profiles associated with cellular phenotypes, and dysregulated genes in vitro are differentially expressed in brain regions associated with pathology. Minimal information about iPSC neurological modeling experiments were proposed and all reported phenotypes cataloged into a continually updated, searchable database, iPhemap, as resources for the research community. Abstract : The future translational utility of iPSC disease models relies on understanding the phenotype to genotype relationships of patient‐derived cells. A meta‐analysis of phenotypes generated thus far by iPSC neurological disease models highlights the strengths and limitations of current practices.