ABSTRACT
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.
Subject(s)
Genetic Testing , Genomics , Health Services Accessibility , Rare Diseases , Rural Population , Humans , Genetic Testing/methods , Rare Diseases/genetics , Rare Diseases/diagnosis , Genomics/methods , Child , Male , High-Throughput Nucleotide Sequencing , FemaleABSTRACT
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.
Subject(s)
Genomics , Insurance Coverage , Child , HumansABSTRACT
Long-read HiFi genome sequencing allows for accurate detection and direct phasing of single nucleotide variants, indels, and structural variants. Recent algorithmic development enables simultaneous detection of CpG methylation for analysis of regulatory element activity directly in HiFi reads. We present a comprehensive haplotype resolved 5-base HiFi genome sequencing dataset from a rare disease cohort of 276 samples in 152 families to identify rare (~0.5%) hypermethylation events. We find that 80% of these events are allele-specific and predicted to cause loss of regulatory element activity. We demonstrate heritability of extreme hypermethylation including rare cis variants associated with short (~200 bp) and large hypermethylation events (>1 kb), respectively. We identify repeat expansions in proximal promoters predicting allelic gene silencing via hypermethylation and demonstrate allelic transcriptional events downstream. On average 30-40 rare hypermethylation tiles overlap rare disease genes per patient, providing indications for variation prioritization including a previously undiagnosed pathogenic allele in DIP2B causing global developmental delay. We propose that use of HiFi genome sequencing in unsolved rare disease cases will allow detection of unconventional diseases alleles due to loss of regulatory element activity.
Subject(s)
DNA Methylation , Rare Diseases , Humans , Haplotypes , Rare Diseases/genetics , DNA Methylation/genetics , Sequence Analysis, DNA , Base Sequence , High-Throughput Nucleotide Sequencing , Nerve Tissue Proteins/geneticsABSTRACT
BACKGROUND: Advances in sequencing technology have led to expanded use of multi-gene panel tests (MGPTs) for clinical diagnostics. Well-designed MGPTs must balance increased detection of clinically significant findings while mitigating the increase in variants of uncertain significance (VUS). To maximize clinical utililty, design of such panels should include comprehensive gene vetting using a standardized clinical validity (CV) scoring system. METHODS: To assess the impact of CV-based gene vetting on MGPT results, data from MGPTs for cardiovascular indications were retrospectively analyzed. Using our CV scoring system, genes were categorized as having definitive, strong, moderate, or limited evidence. The rates of reported pathogenic or likely pathogenic variants and VUS were then determined for each CV category. RESULTS: Of 106 total genes, 42% had definitive, 17% had strong, 29% had moderate, and 12% had limited CV. The detection rate of variants classified as pathogenic or likely pathogenic was higher for genes with greater CV, while the VUS rate showed an inverse relationship with CV score. No pathogenic or likely pathogenic findings were observed in genes with a limited CV. CONCLUSION: These results demonstrate the importance of a standardized, evidence-based vetting process to establish CV for genes on MGPTs. Using our proposed system may help to increase the detection rate while mitigating higher VUS rates.