Widespread Genotype-Phenotype Correlations in Intellectual Disability

• Published in: Frontiers in psychiatry Vol. 9; p. 535
• Main Authors: Casanova, Emily L, Gerstner, Zachary, Sharp, Julia L, Casanova, Manuel F, Feltus, Frank Alex
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 29-10-2018
• Subjects: autism spectrum disorder; craniofacial abnormalities; epilepsy; genetic phenotype associations; infantile proteopathy; neurodegeneration; Psychiatry; epilepsy; neurodegeneration; craniofacial abnormalities; autism spectrum disorder; genetic phenotype associations; infantile proteopathy
• ISSN: 1664-0640; 1664-0640
• DOI: 10.3389/fpsyt.2018.00535

Linking genotype to phenotype is a major aim of genetics research, yet the underlying biochemical mechanisms of many complex conditions continue to remain elusive. Recent research provides evidence that relevant gene-phenotype associations are discoverable in the study of intellectual disability (ID). Here we expand on that work, identifying distinctive gene interaction modules with unique enrichment patterns reflective of associated clinical features in ID.
Two hundred twelve forms of monogenic ID were curated according to comorbidities with autism and epilepsy. These groups were further subdivided according to secondary clinical manifestations of complex vs. simple facial dysmorphia and neurodegenerative-like features due to their clinical prominence, modest symptom overlap, and probable etiological divergence. An aggregate gene interaction ID network for these phenotype subgroups was discovered via a public database of known gene interactions: protein-protein, genetic, and mRNA coexpression. Additional annotation resources (Gene Ontology, Human Phenotype Ontology, TRANSFAC/JASPAR, and KEGG/WikiPathways) were utilized to assess functional and phenotypic enrichment patterns within subgroups.
Phenotypic analysis revealed high rates of complex facial dysmorphia in ID with comorbid autism. In contrast, neurodegenerative-like features were overrepresented in ID with epilepsy. Network analysis subsequently showed that gene groups divided according to clinical features of interest resulted in distinctive interaction clusters, with unique functional enrichments according to gene set.
These data suggest that specific comorbid and secondary clinical features in ID are predictive of underlying genotype. In summary, ID form unique clusters, which are comprised of individual conditions with remarkable genotypic and phenotypic overlap.