4570
An Atlas of Phenotype to Genotype Relationships of Patient-Derived Neurons and Oligodendrocytes: Implications for White Matter Disorders
Objectives: Reprogramming adult human somatic cells to model neurological diseases is poised to provide unprecedented insights in complex neurological disorders; however, the wealth of information and the multiple phenotypes generated from these studies has become increasingly difficult to follow and interpret. Furthermore, current efforts to develop patient derived neurons or oligodendrocytes from MS patients and other white matter disorders are limited due to the lack of a comprehensive taxonomy of phenotypes that can serve as in vitro biomarkers for neurodegeneration in these models, therefore a systematic assessment of the accumulated knowledge of phenotypes observed in the field is necessary.
Methods: A system biology meta-analysis was performed from iPSC experiments from 77 studies. We used Circos plot and ideogram to correlate neuronal phenotypes with mutations from neurodevelopmental and neurodegenerative disease. We used cytoscape to build a map of all phenotypes and genes. We performed network analysis of gene expression from diseased derived cells and controls to generate molecular phenotypes.
Results: We catalogued 517 novel phenotypes from 55 different mutations in 25 adult and pediatric neurological disorders. We established a novel taxonomy to group all the neuronal phenotypes from iPSC experiments into nine distinct clusters mapped to the human genome. In addition, these phenotypic clusters mapped to distinct derived cells, we found that phenotypes clustered to neural cells depending on gene mutations. We characterized the resulting relationships between genes and phenotype into a phenogenetic map, revealing differential grouping of phenotypes. We found that these relationships follow a scale-free power law relationship, revealing novel correlations between genes and phenotypes. We performed pair-wise statistical comparison of functional annotations derived from well-established gene ontologies and our new phenotype ontology validating novel correlations. We designed a web platform, iphemap.org to make our data accessible to scientists studying the modeling of neurological diseases with pluripotent stem cells derived from patients.
Conclusions: Our findings provide new insights into in-the-dish models of neurological diseases and our database provide, for the first time, a field synopsis of iPSC phenotypes with implications for sporadic white matter disorders such as multiple sclerosis.