T Cell Transcriptome in Chromosome 22q11.2 Deletion Syndrome.

Phenotypic variations of chromosome 22q11.2 deletion syndrome (22qDS) have unclear explanations. T cell lymphopenia in 22qDS related to varying degrees of thymic hypoplasia contributes to the phenotypic heterogeneity. No phenotype correlation with genotype or deletion size is known for lymphopenia. We investigated gene expression in human T cells of participants with and without 22qDS and T cells of participants with 22qDS with low or normal T cells. Peripheral blood was collected from participants aged 5-8 y. Immune function was checked. RNA sequencing was completed on isolated T cells, and differential gene expression profiles of T cells between 22qDS and healthy control subjects were established. A total of 360 genes were differentially expressed (q < 0.05) between T cells of patients with 22qDS (n = 13) and healthy control subjects (n = 6) (log2 fold change range, -2.0747, 15.6724). We compared gene expression between participants with 22qDS with low (n = 7) and normal T cell counts (n = 6), finding 94 genes that were differentially expressed (q < 0.05) (log2 fold change range, -4.5445, 5.1297). Twenty-nine genes correlated with T cell counts and markers CD3, CD4, CD8, and CD45RA+CD4 (R ≥ 0.8). We found significantly differentially expressed genes in participants with 22qDS compared with healthy control subjects and in participants with 22qDS with low T cell counts compared with those with normal T cell counts. Several enriched pathways suggest a role of T cells in defective communication between T cells and the innate immune system in 22qDS. Among these, the liver X receptor/retinoid X receptor pathway was noted to show several differentially expressed genes affecting participants with 22qDS compared with healthy control subjects and more so those with low T cell counts than in those with normal T cell counts.

The Development of an Infrastructure to Facilitate the Use of Whole Genome Sequencing for Population Health.

The clinical use of genomic analysis has expanded rapidly resulting in an increased availability and utility of genomic information in clinical care. We have developed an infrastructure utilizing informatics tools and clinical processes to facilitate the use of whole genome sequencing data for population health management across the healthcare system. Our resulting framework scaled well to multiple clinical domains in both pediatric and adult care, although there were domain specific challenges that arose. Our infrastructure was complementary to existing clinical processes and well-received by care providers and patients. Informatics solutions were critical to the successful deployment and scaling of this program. Implementation of genomics at the scale of population health utilizes complicated technologies and processes that for many health systems are not supported by current information systems or in existing clinical workflows. To scale such a system requires a substantial clinical framework backed by informatics tools to facilitate the flow and management of data. Our work represents an early model that has been successful in scaling to 29 different genes with associated genetic conditions in four clinical domains. Work is ongoing to optimize informatics tools; and to identify best practices for translation to smaller healthcare systems.