Genomic Answers for Kids: Toward more equitable access to genomic testing for rare diseases in rural populations.

Next-generation sequencing has revolutionized the speed of rare disease (RD) diagnoses. While clinical exome and genome sequencing represent an effective tool for many RD diagnoses, there is room to further improve the diagnostic odyssey of many RD patients. One recognizable intervention lies in increasing equitable access to genomic testing. Rural communities represent a significant portion of underserved and underrepresented individuals facing additional barriers to diagnosis and treatment. Primary care providers (PCPs) at local clinics, though sometimes suspicious of a potential benefit of genetic testing for their patients, have significant constraints in pursuing it themselves and rely on referrals to specialists. Yet, these referrals are typically followed by long waitlists and significant delays in clinical assessment, insurance clearance, testing, and initiation of diagnosis-informed care management. Not only is this process time intensive, but it also often requires multiple visits to urban medical centers for which distance may be a significant barrier to rural families. Therefore, providing early, "direct-to-provider" (DTP) local access to unrestrictive genomic testing is likely to help speed up diagnostic times and access to care for RD patients in rural communities. In a pilot study with a PCP clinic in rural Kansas, we observed a minimum 5.5 months shortening of time to diagnosis through the DTP exome sequencing program as compared to rural patients receiving genetic testing through the "traditional" PCP-referral-to-specialist scheme. We share our experience to encourage future partnerships beyond our center. Our efforts represent just one step in fostering greater diversity and equity in genomic studies.

Insurance denials and diagnostic rates in a pediatric genomic research cohort.

PURPOSE: This study aimed to assess the amount and types of clinical genetic testing denied by insurance and the rate of diagnostic and candidate genetic findings identified through research in patients who faced insurance denials. METHODS: Analysis consisted of review of insurance denials in 801 patients enrolled in a pediatric genomic research repository with either no previous genetic testing or previous negative genetic testing result identified through cross-referencing with insurance prior-authorizations in patient medical records. Patients and denials were also categorized by type of insurance coverage. Diagnostic findings and candidate genetic findings in these groups were determined through review of our internal variant database and patient charts. RESULTS: Of the 801 patients analyzed, 147 had insurance prior-authorization denials on record (18.3%). Exome sequencing and microarray were the most frequently denied genetic tests. Private insurance was significantly more likely to deny testing than public insurance (odds ratio = 2.03 [95% CI = 1.38-2.99] P = .0003). Of the 147 patients with insurance denials, 53.7% had at least 1 diagnostic or candidate finding and 10.9% specifically had a clinically diagnostic finding. Fifty percent of patients with clinically diagnostic results had immediate medical management changes (5.4% of all patients experiencing denials). CONCLUSION: Many patients face a major barrier to genetic testing in the form of lack of insurance coverage. A number of these patients have clinically diagnostic findings with medical management implications that would not have been identified without access to research testing. These findings support re-evaluation of insurance carriers' coverage policies.

Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes.

PURPOSE: This study aimed to provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids program. METHODS: Extensive analyses of 960 families with suspected genetic disorders included short-read exome sequencing and short-read genome sequencing (srGS); PacBio HiFi long-read genome sequencing (HiFi-GS); variant calling for single nucleotide variants (SNV), structural variant (SV), and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants, and pedigrees were stored in PhenoTips database, with data sharing through controlled access the database of Genotypes and Phenotypes. RESULTS: Diagnostic rates ranged from 11% in patients with prior negative genetic testing to 34.5% in naive patients. Incorporating SVs from genome sequencing added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with >4-fold more rare coding SVs compared with srGS. Variants and genes of unknown significance remain the most common finding (58% of nondiagnostic cases). CONCLUSION: Computational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated using HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation and by providing HiFi variant (SNV/SV) resources from >1000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.

High Levels of Interest in Reproductive Genetic Information in Parents of Children and Adults With Hirschsprung Disease.

OBJECTIVES: Families affected by Hirschsprung disease (HSCR) have opportunities to learn recurrence risks to their children from statistical genetic and empiric studies and, in some cases, prenatal genetic testing or preimplantation genetic diagnosis (PGD). This study aimed to assess interest in reproductive genetic information for HSCR and factors that predict this interest in 2 groups with elevated risk of having a child with HSCR. METHODS: Adult patients with HSCR and parents of children with HSCR were surveyed about their interest in learning reproductive genetic information regarding HSCR through genetic counseling, prenatal testing, and PGD. Covariates assessed in this cross-sectional study included quality of life, illness perceptions, depressive symptoms, and adaptation to the condition. Bivariate analyses assessed differences between affected adults and parents. Logistic modeling was used to identify predictors of interest in reproductive genetic information. RESULTS: Study participants (n = 368) reported high interest in reproductive genetic information through genetic counseling (yes = 60%/unsure = 16%), prenatal testing (yes = 59%/unsure = 16%), and PGD (yes = 43%/unsure = 18%). Illness perceptions differed between affected adults and parents, but perceived severity of HSCR was high among all participants (µâ€Š= 3.42, SD = 0.67, 4-point scale). Interest in reproductive information was associated with being an affected adult, not having a family history of HSCR, negative emotional representations, and adaptation to the condition. CONCLUSIONS: Findings from this study support a desire among the surveyed HSCR patient groups to attend genetic counseling and be offered testing when available. Exploration of perceptions and experiences with the condition should be incorporated into the counseling to insure informed preference-based decision making.

Using the diffusion of innovations model to guide participant engagement in the genomics era.

Exome and genome sequencing (EGS) are increasingly the genetic testing modalities of choice among researchers owing to their ready availability, low cost, and large data output. Recruitment of larger, more diverse cohorts into long-term studies with extensive data collection is fundamental to the success of EGS research and to the widespread benefit of genomic medicine to various populations. Effective engagement will be critical to meeting this demand. The Diffusion of Innovation (DOI) model provides a framework for how new technologies are adopted in communities, including antecedents of an individual's decision to adopt the technology, how the technology's attributes influence its acceptability, the predictors of sustained use of that technology, and its diffusion through society. We apply the DOI model to frame participant engagement in EGS research and to guide the proposal of potential strategies that aim to overcome forecasted challenges. Finally, we suggest a variety of ways genetic counselors can apply their skills and training to the development and implementation of these strategies.