Access to clinically indicated genetic tests for pediatric patients with Medicaid: Evidence from outpatient genetics clinics in Texas.

PURPOSE: Little is known about how Medicaid coverage policies affect access to genetic tests for pediatric patients. Building upon and extending a previous analysis of prior authorization requests (PARs), we describe expected coverage of genetic tests submitted to Texas Medicaid and the PAR and diagnostic outcomes of those tests. METHODS: We retrospectively reviewed genetic tests ordered at 3 pediatric outpatient genetics clinics in Texas. We compared Current Procedural Terminology (CPT) codes with the Texas Medicaid fee-for-service schedule (FFSS) to determine whether tests were expected to be covered by Medicaid. We assessed completion and diagnostic yield of commonly ordered tests. RESULTS: Among the 3388 total tests submitted to Texas Medicaid, 68.9% (n = 2336) used at least 1 CPT code that was not on the FFSS and 80.7% (n = 2735) received a favorable PAR outcome. Of the tests with a CPT code not on the FFSS, 60.0% (n = 1400) received a favorable PAR outcome and were completed and 20.5% (n = 287) were diagnostic. The diagnostic yield of all tests with a favorable PAR outcome that were completed was 18.7% (n = 380/2029). CONCLUSION: Most PARs submitted to Texas Medicaid used a CPT code for which reimbursement from Texas Medicaid was not guaranteed. The frequency with which clinically indicated genetic tests were not listed on the Texas Medicaid FFSS suggests misalignment between genetic testing needs and coverage policies. Our findings can inform updates to Medicaid policies to reduce coverage uncertainty and expand access to genetic tests with high diagnostic utility.

Clinical, biochemical and genetic characteristics of MOGS-CDG: a rare congenital disorder of glycosylation.

PURPOSE: To summarise the clinical, molecular and biochemical phenotype of mannosyl-oligosaccharide glucosidase-related congenital disorders of glycosylation (MOGS-CDG), which presents with variable clinical manifestations, and to analyse which clinical biochemical assay consistently supports diagnosis in individuals with bi-allelic variants in MOGS. METHODS: Phenotypic characterisation was performed through an international and multicentre collaboration. Genetic testing was done by exome sequencing and targeted arrays. Biochemical assays on serum and urine were performed to delineate the biochemical signature of MOGS-CDG. RESULTS: Clinical phenotyping revealed heterogeneity in MOGS-CDG, including neurological, immunological and skeletal phenotypes. Bi-allelic variants in MOGS were identified in 12 individuals from 11 families. The severity in each organ system was variable, without definite genotype correlation. Urine oligosaccharide analysis was consistently abnormal for all affected probands, whereas other biochemical analyses such as serum transferrin analysis was not consistently abnormal. CONCLUSION: The clinical phenotype of MOGS-CDG includes multisystemic involvement with variable severity. Molecular analysis, combined with biochemical testing, is important for diagnosis. In MOGS-CDG, urine oligosaccharide analysis via matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry can be used as a reliable biochemical test for screening and confirmation of disease.

Second instance of co-occurring 22q11.2 deletion syndrome and Williams syndrome.

We present an 18-month-old male with Tetralogy of Fallot, retrognathia, short stature, global developmental delay, and dysmorphic features who was found to have dual diagnoses of both Williams syndrome and 22q11.2 deletion syndrome (22q11.2DS). To our knowledge, this is the second case of such a co-occurrence documented in the medical literature. Our patient presents with a blended physical phenotype of these two conditions and a behavioral phenotype that is distinct from what is typically observed in either disorder alone. We compare our patient's phenotype to the previously reported case and to the typical phenotypes for each individual condition. Additionally, we discuss why the occurrence of these two disorders together seems to be so rare, and the benefit of a genetics evaluation to an inpatient service team and the patient.

Clinical Exome Studies Have Inconsistent Coverage.

BACKGROUND: Exome sequencing has become a commonly used clinical diagnostic test. Multiple studies have examined the diagnostic utility and individual laboratory performance of exome testing; however, no previous study has surveyed and compared the data quality from multiple clinical laboratories. METHODS: We examined sequencing data from 36 clinical exome tests from 3 clinical laboratories. Exome data were compared in terms of overall characteristics and coverage of specific genes and nucleotide positions. The sets of genes examined included genes in Consensus Coding Sequence (CCDS) (n = 17723), a subset of genes clinically relevant to epilepsy (n = 108), and genes that are recommended for reporting of secondary findings (n = 57; excludes X-linked genes). RESULTS: The average exome nucleotide coverage (≥20×) of each laboratory varied at 96.49% (CV = 3%), 96.54% (CV = 1%), and 91.68% (CV = 4%), for laboratories A, B, and C, respectively. For CCDS genes, the average number of completely covered genes varied at 12184 (CV = 29%), 11687 (CV = 13%), and 5989 (CV = 37%), for laboratories A, B, and C, respectively. With smaller subsets of genes related to epilepsy and secondary findings, the CV revealed low consistency, with a maximum CV seen in laboratory C for both epilepsy genes (CV = 60%) and secondary findings genes (CV = 71%). CONCLUSIONS: Poor consistency in complete gene coverage was seen in the clinical exome laboratories surveyed. The degree of consistency varied widely between the laboratories.