Distal chromosome 16p11.2 duplications containing SH2B1 in patients with scoliosis.

INTRODUCTION: Adolescent idiopathic scoliosis (AIS) is a common musculoskeletal disorder with strong evidence for a genetic contribution. CNVs play an important role in congenital scoliosis, but their role in idiopathic scoliosis has been largely unexplored. METHODS: Exome sequence data from 1197 AIS cases and 1664 in-house controls was analysed using coverage data to identify rare CNVs. CNV calls were filtered to include only highly confident CNVs with >10 average reads per region and mean log-ratio of coverage consistent with single-copy duplication or deletion. The frequency of 55 common recurrent CNVs was determined and correlated with clinical characteristics. RESULTS: Distal chromosome 16p11.2 microduplications containing the gene SH2B1 were found in 0.7% of AIS cases (8/1197). We replicated this finding in two additional AIS cohorts (8/1097 and 2/433), resulting in 0.7% (18/2727) of all AIS cases harbouring a chromosome 16p11.2 microduplication, compared with 0.06% of local controls (1/1664) and 0.04% of published controls (8/19584) (p=2.28×10-11, OR=16.15). Furthermore, examination of electronic health records of 92 455 patients from the Geisinger health system showed scoliosis in 30% (20/66) patients with chromosome 16p11.2 microduplications containing SH2B1 compared with 7.6% (10/132) of controls (p=5.6×10-4, OR=3.9). CONCLUSIONS: Recurrent distal chromosome 16p11.2 duplications explain nearly 1% of AIS. Distal chromosome 16p11.2 duplications may contribute to scoliosis pathogenesis by directly impairing growth or by altering expression of nearby genes, such as TBX6. Individuals with distal chromosome 16p11.2 microduplications should be screened for scoliosis to facilitate early treatment.

User testing of a diagnostic decision support system with machine-assisted chart review to facilitate clinical genomic diagnosis.

OBJECTIVES: There is a need in clinical genomics for systems that assist in clinical diagnosis, analysis of genomic information and periodic reanalysis of results, and can use information from the electronic health record to do so. Such systems should be built using the concepts of human-centred design, fit within clinical workflows and provide solutions to priority problems. METHODS: We adapted a commercially available diagnostic decision support system (DDSS) to use extracted findings from a patient record and combine them with genomic variant information in the DDSS interface. Three representative patient cases were created in a simulated clinical environment for user testing. A semistructured interview guide was created to illuminate factors relevant to human factors in CDS design and organisational implementation. RESULTS: Six individuals completed the user testing process. Tester responses were positive and noted good fit with real-world clinical genetics workflow. Technical issues related to interface, interaction and design were minor and fixable. Testers suggested solving issues related to terminology and usability through training and infobuttons. Time savings was estimated at 30%-50% and additional uses such as in-house clinical variant analysis were suggested for increase fit with workflow and to further address priority problems. CONCLUSION: This study provides preliminary evidence for usability, workflow fit, acceptability and implementation potential of a modified DDSS that includes machine-assisted chart review. Continued development and testing using principles from human-centred design and implementation science are necessary to improve technical functionality and acceptability for multiple stakeholders and organisational implementation potential to improve the genomic diagnosis process.