Abstract
Early prediction of complex disorders (e.g., autism and other neurodevelopmental disorders) is one of the fundamental goals of precision medicine and personalized genomics. An early prediction of complex disorders can have a significant impact on increasing the effectiveness of interventions and treatments in improving the prognosis and, in many cases, enhancing the quality of life in the affected patients. Considering the genetic heritability of neurodevelopmental disorders, we are proposing a novel framework for utilizing rare coding variation for early prediction of these disorders. We provide a novel formulation for the Ultra-Accurate Disorder Prediction (UADP) problem and develop a novel combinatorial framework for solving this problem. The primary goal of this novel framework, denoted as Odin (Oracle for DIsorder predictioN), is to make an accurate prediction for a subset of affected cases while having virtually zero false positive predictions for unaffected samples. Note that in the Odin framework we will take advantage of the available functional information (e.g., pairwise coexpression of genes during brain development) to increase the prediction power beyond genes with recurrent variants. Application of our method accurately recovers an additional 8% of autism cases without known recurrent mutated genes in the training set and with a less than 0.5% false positive prediction based on our analysis of unaffected controls. Furthermore, Odin predicted a set of 391 genes that severe variants in these genes can cause autism or other developmental delay disorders. Odin is publicly available at https://github.com/HormozdiariLab/Odin †
