Prediction of XXXX by Translation and Immune/Inflammation Coexpressed Genes in Toddlers From Pediatric Community Practices.

@entity1 @entity10791 @entity72 @entity2438
Importance: The identification of genomic signatures that aid early identification of individuals at risk for @entity72 ( @entity72 ) in the toddler period remains a major challenge because of the genetic and phenotypic heterogeneity of the disorder. Generally, @entity72 is not diagnosed before the fourth to fifth birthday. Objective: To apply a functional genomic approach to identify a biologically relevant signature with promising performance in the diagnostic classification of @entity1 and toddlers with @entity72 . Design, Setting, and @entity1 : Proof-of-principle study of leukocyte RNA expression levels from 2 independent cohorts of @entity1 aged 1 to 4 years (142 discovery @entity1 and 73 replication @entity1 ) using Illumina microarrays. Coexpression analysis of differentially expressed genes between Discovery @entity72 and control toddlers were used to define gene modules and eigengenes used in a diagnostic classification analysis. Independent validation of the classifier performance was tested on the replication cohort. Pathway enrichment and protein-protein interaction analyses were used to confirm biological relevance of the functional networks in the classifier. @entity1 recruitment occurred in general pediatric clinics and community settings. Male @entity1 and toddlers (age range, 1-4 years) were enrolled in the study. Recruitment criteria followed the 1-Year Well-Baby Check-Up Approach. Diagnostic judgment followed DSM-IV-TR and @entity2438 Diagnostic Observation Schedule criteria for @entity2438 . @entity1 with @entity72 were compared with control groups composed of typically developing toddlers as well as toddlers with global developmental or @entity10791 . Main Outcomes and Measures: Logistic regression and receiver operating characteristic curve analysis were used in a classification test to establish the accuracy, specificity, and sensitivity of the module-based classifier. Results: Our signature of differentially coexpressed genes was enriched in translation and immune/inflammation functions and produced 83% accuracy. In an independent test with approximately half of the sample and a different microarray, the diagnostic classification of @entity72 vs control samples was 75% accurate. Consistent with its @entity72 specificity, our signature did not distinguish toddlers with global developmental or @entity10791 from typically developing toddlers (62% accuracy). Conclusions and Relevance: This proof-of-principle study demonstrated that genomic biomarkers with very good sensitivity and specificity for @entity1 with @entity72 in general pediatric settings can be identified. It also showed that a blood-based clinical test for at-risk male @entity1 and toddlers could be refined and routinely implemented in pediatric diagnostic settings.
