Abstract
BACKGROUND
Genetic testing is often pursued in children with medical complexity (CMC), in an attempt to establish a unifying diagnosis, understand pathogenicity and disease progression, guide care and inform reproductive planning. CMC are defined by at least one chronic condition, technology dependence, multiple subspecialist involvement, and high healthcare utilization. Despite multiple efforts to confirm clinical suspicion of an underlying genetic condition, many remain undiagnosed.
Whole genome sequencing (WGS) is becoming increasingly available as an informative diagnostic tool. The application of genomic technology to this population has the potential to increase the proportion of CMC for whom diagnoses are established, in an effort to reduce time and emotional burden of the diagnostic process, and reduce health care system costs.
OBJECTIVES
The main purpose of this study was to optimize the clinical implementation of state-of-the-art genome diagnostics for CMC, in terms of diagnostic yield.
DESIGN/METHODS
We conducted a prospective study using patients followed by the Complex Care program at a large urban tertiary care center. Research ethics board approval was obtained. Of 435 patients screened, 114 were eligible for inclusion as an underlying genetic condition was clinically suspected but not established to date by conventional genetic testing. To date, 21 participants were evaluated through a clinical genetic assessment, previous genetic testing review and peripheral blood-derived DNA sequence.
A laboratory team identified candidate genetic variants associated with patients’ clinical symptoms, as well as other paediatric medically actionable variants. When found, these variants were validated as clinically significant by comparing the child’s DNA to his parents’. WGS diagnostic yield was then determined by calculating the proportion of cases for which a genetic diagnosis was established.
RESULTS
Of the 21 patients recruited, nine WGS analysis were completed thus far. Among these, four participants were diagnosed with established diseases, two of which were considered as novel diseases. One case was identified with a possible diagnosis, however, the interpretation of this clinical phenotype remains of unknown significance. The other four patients of the study remained undiagnosed.
Given these preliminary results, the diagnostic yield of WGS was predicted at 44% in CMC. This can be compared to a previous study performed at our center in which the diagnostic rate for chromosomal microarray alone was reported to be 8% and microarray plus targeted gene sequencing 13%.
CONCLUSION
This study has shown WGS to be feasible and achieve a higher diagnostic yield in our complex care population. As detection rates improve and laboratory costs decrease overtime, WGS will undoubtedly become a more informative diagnostic tool, particularly in this population. Optimizing the application of this increasingly sophisticated genomic technology warrants further consideration.