@article {671, title = {Autism Linked to Increased Oncogene Mutations but Decreased Cancer Rate.}, journal = {PLoS One}, volume = {11}, year = {2016}, month = {2016}, pages = {e0149041}, abstract = {

Autism spectrum disorder (ASD) is one phenotypic aspect of many monogenic, hereditary cancer syndromes. Pleiotropic effects of cancer genes on the autism phenotype could lead to repurposing of oncology medications to treat this increasingly prevalent neurodevelopmental condition for which there is currently no treatment. To explore this hypothesis we sought to discover whether autistic patients more often have rare coding, single-nucleotide variants within tumor suppressor and oncogenes and whether autistic patients are more often diagnosed with neoplasms. Exome-sequencing data from the ARRA Autism Sequencing Collaboration was compared to that of a control cohort from the Exome Variant Server database revealing that rare, coding variants within oncogenes were enriched for in the ARRA ASD cohort (p<1.0 x 10(-8)). In contrast, variants were not significantly enriched in tumor suppressor genes. Phenotypically, children and adults with ASD exhibited a protective effect against cancer, with a frequency of 1.3\% vs. 3.9\% (p<0.001), but the protective effect decreased with age. The odds ratio of neoplasm for those with ASD relative to controls was 0.06 (95\% CI: 0.02, 0.19; p<0.0001) in the 0 to 14 age group; 0.35 (95\% CI: 0.14, 0.87; p = 0.024) in the 15 to 29 age group; 0.41 (95\% CI: 0.15, 1.17; p = 0.095) in the 30 to 54 age group; and 0.49 (95\% CI: 0.14, 1.74; p = 0.267) in those 55 and older. Both males and females demonstrated the protective effect. These findings suggest that defects in cellular proliferation, and potentially senescence, might influence both autism and neoplasm, and already approved drugs targeting oncogenic pathways might also have therapeutic value for treating autism.

}, keywords = {Adolescent, Adult, Autism Spectrum Disorder, Child, Child, Preschool, Female, Genes, Tumor Suppressor, Genetic Predisposition to Disease, Humans, Infant, Male, Middle Aged, Mutation, Neoplasms, Oncogenes, Prevalence, Young Adult}, issn = {1932-6203}, doi = {10.1371/journal.pone.0149041}, author = {Darbro, Benjamin W and Singh, Rohini and Zimmerman, M Bridget and Mahajan, Vinit B and Bassuk, Alexander G} } @article {781, title = {Automated discovery and quantification of image-based complex phenotypes: a twin study of drusen phenotypes in age-related macular degeneration.}, journal = {Invest Ophthalmol Vis Sci}, volume = {52}, year = {2011}, month = {2011 Nov 25}, pages = {9195-206}, abstract = {

PURPOSE: Determining the relationships between phenotype and genotype of many disorders can improve clinical diagnoses, identify disease mechanisms, and enhance therapy. Most genetic disorders result from interaction of many genes that obscure the discovery of such relationships. The hypothesis for this study was that image analysis has the potential to enable formalized discovery of new visible phenotypes. It was tested in twins affected with age-related macular degeneration (AMD).

METHODS: Fundus images from 43 monozygotic (MZ) and 32 dizygotic (DZ) twin pairs with AMD were examined. First, soft and hard drusen were segmented. Then newly defined phenotypes were identified by using drusen distribution statistics that significantly separate MZ from DZ twins. The ACE model was used to identify the contributions of additive genetic (A), common environmental (C), and nonshared environmental (E) effects on drusen distribution phenotypes.

RESULTS: Four drusen distribution characteristics significantly separated MZ from DZ twin pairs. One encoded the quantity, and the remaining three encoded the spatial distribution of drusen, achieving a zygosity prediction accuracy of 76\%, 74\%, 68\%, and 68\%. Three of the four phenotypes had a 55\% to 77\% genetic effect in an AE model, and the fourth phenotype showed a nonshared environmental effect (E model).

CONCLUSIONS: Computational discovery of genetically determined features can reveal quantifiable AMD phenotypes that are genetically determined without explicitly linking them to specific genes. In addition, it can identify phenotypes that appear to result predominantly from environmental exposure. The approach is rapid and unbiased, suitable for large datasets, and can be used to reveal unknown phenotype-genotype relationships.

}, keywords = {Aged, 80 and over, Diseases in Twins, Female, Genetic Predisposition to Disease, Genotype, Humans, Macular Degeneration, Male, Phenotype, Registries, Retinal Drusen, Twins, Dizygotic, Twins, Monozygotic}, issn = {1552-5783}, doi = {10.1167/iovs.10-6793}, author = {Quellec, Gw{\'e}nol{\'e} and Russell, Stephen R and Seddon, Johanna M and Reynolds, Robyn and Scheetz, Todd and Mahajan, Vinit B and Stone, Edwin M and Abr{\`a}moff, Michael D} }