Higher scores on autonomic symptom scales in pediatric patients with neurodevelopmental disorders of known genetic etiology.

INTRODUCTION: Features of underlying autonomic dysfunction, including sleep disturbances, gastrointestinal problems, and atypical heart rate, have been reported in neurodevelopmental conditions, including autism spectrum disorder (ASD). The current cross-sectional, between-groups study aimed to quantify symptoms of autonomic dysfunction in a neurodevelopmental pediatric cohort characterized by clinical diagnoses as well as genetic etiology. METHOD: The Pediatric Autonomic Symptom Scales (PASS) questionnaire was used to assess autonomic features across a group of patients with clinical neurodevelopmental diagnoses (NPD; N = 90) and genetic etiologies. Patients were subdivided based on either having a clinical ASD diagnosis (NPD-ASD; n = 37) or other non-ASD neurodevelopmental diagnoses, such as intellectual disability without ASD, speech and language disorders, and/or attention deficit hyperactivity disorder (NPD-OTHER; n = 53). Analyses focused on characterizing differences between the NPD group compared to previously published reference samples, as well as differences between the two NPD subgroups (NPD-ASD and NPD-OTHER). RESULTS: Our results indicate higher PASS scores in our NPD cohort relative to children with and without ASD from a previously published cohort. However, we did not identify significant group differences between our NPD-ASD and NPD-OTHER subgroups. Furthermore, we find a significant relationship between quantitative ASD traits and symptoms of autonomic function. CONCLUSION: This work demonstrates the utility of capturing quantitative estimates of autonomic trait dimensions that may be significantly linked with psychosocial impairments and other core clinical features of ASD.

Chromosomal microarray impacts clinical management.

Chromosomal microarray analysis (CMA) is standard of care, first-tier clinical testing for detection of genomic copy number variation among patients with developmental disabilities. Although diagnostic yield is higher than traditional cytogenetic testing, management impact has not been well studied. We surveyed genetic services providers regarding CMA ordering practices and perceptions about reimbursement. Lack of insurance coverage because of perceived lack of clinical utility was cited among the most frequent reasons why CMA was not ordered when warranted. We compiled a list of genomic regions where haploinsufficiency or triplosensitivity cause genetic conditions with documented management recommendations, estimating that at least 146 conditions potentially diagnosable by CMA testing have published literature supporting specific clinical management implications. Comparison with an existing clinical CMA database to determine the proportion of cases involving these regions showed that CMA diagnoses associated with such recommendations are found in approximately 7% of all cases (n = 28,526). We conclude that CMA impacts clinical management at a rate similar to other genetic tests for which insurance coverage is more readily approved. The information presented here can be used to address barriers that continue to contribute to inequities in patient access and care in regard to CMA testing.

Towards an evidence-based process for the clinical interpretation of copy number variation.

The evidence-based review (EBR) process has been widely used to develop standards for medical decision-making and to explore complex clinical questions. This approach can be applied to genetic tests, such as chromosomal microarrays, in order to assist in the clinical interpretation of certain copy number variants (CNVs), particularly those that are rare, and guide array design for optimal clinical utility. To address these issues, the International Standards for Cytogenomic Arrays Consortium has established an EBR Work Group charged with building a framework to systematically assess the potential clinical relevance of CNVs throughout the genome. This group has developed a rating system enumerating the evidence supporting or refuting dosage sensitivity for individual genes and regions that considers the following criteria: number of causative mutations reported; patterns of inheritance; consistency of phenotype; evidence from large-scale case-control studies; mutational mechanisms; data from public genome variation databases; and expert consensus opinion. The system is designed to be dynamic in nature, with regions being reevaluated periodically to incorporate emerging evidence. The evidence collected will be displayed within a publically available database, and can be used in part to inform clinical laboratory CNV interpretations as well as to guide array design.