A guidelines-consistent carrier screening panel that supports equity across diverse populations.

PURPOSE: The American College of Obstetricians and Gynecologists (ACOG) and the American College of Medical Genetics and Genomics (ACMG) suggest carrier screening panel design criteria intended to ensure meaningful results. This study used a data-driven approach to interpret the criteria to identify guidelines-consistent panels. METHODS: Carrier frequencies in >460,000 individuals across 11 races/ethnicities were used to assess carrier frequency. Other criteria were interpreted on the basis of published data. A total of 176 conditions were then evaluated. Stringency thresholds were set as suggested by ACOG and/or ACMG or by evaluating conditions already recommended by ACOG and ACMG. RESULTS: Forty and 75 conditions had carrier frequencies of ≥1 in 100 and ≥1 in 200, respectively; 175 had a well-defined phenotype; and 165 met at least 1 severity criterion and had an onset early in life. Thirty-seven conditions met conservative thresholds, including a carrier frequency of ≥1 in 100, and 74 conditions met permissive thresholds, including a carrier frequency of ≥1 in 200; thus, both were identified as guidelines-consistent panels. CONCLUSION: Clear panel design criteria are needed to ensure quality and consistency among carrier screening panels. Evidence-based analyses of criteria resulted in the identification of guidelines-consistent panels of 37 and 74 conditions.

Genetic ancestry analysis on >93,000 individuals undergoing expanded carrier screening reveals limitations of ethnicity-based medical guidelines.

PURPOSE: Carrier status associates strongly with genetic ancestry, yet current carrier screening guidelines recommend testing for a limited set of conditions based on a patient's self-reported ethnicity. Ethnicity, which can reflect both genetic ancestry and cultural factors (e.g., religion), may be imperfectly known or communicated by patients. We sought to quantitatively assess the efficacy and equity with which ethnicity-based carrier screening captures recessive disease risk. METHODS: For 93,419 individuals undergoing a 96-gene expanded carrier screen (ECS), correspondence was assessed among carrier status, self-reported ethnicity, and a dual-component genetic ancestry (e.g., 75% African/25% European) calculated from sequencing data. RESULTS: Self-reported ethnicity was an imperfect indicator of genetic ancestry, with 9% of individuals having >50% genetic ancestry from a lineage inconsistent with self-reported ethnicity. Limitations of self-reported ethnicity led to missed carriers in at-risk populations: for 10 ECS conditions, patients with intermediate genetic ancestry backgrounds-who did not self-report the associated ethnicity-had significantly elevated carrier risk. Finally, for 7 of the 16 conditions included in current screening guidelines, most carriers were not from the population the guideline aimed to serve. CONCLUSION: Substantial and disproportionate risk for recessive disease is not detected when carrier screening is based on ethnicity, leading to inequitable reproductive care.

Screening for Tay-Sachs disease carriers by full-exon sequencing with novel variant interpretation outperforms enzyme testing in a pan-ethnic cohort.

BACKGROUND: Pathogenic variants in HEXA that impair ß-hexosaminidase A (Hex A) enzyme activity cause Tay-Sachs Disease (TSD), a severe autosomal-recessive neurodegenerative disorder. Hex A enzyme analysis demonstrates near-zero activity in patients affected with TSD and can also identify carriers, whose single functional copy of HEXA results in reduced enzyme activity relative to noncarriers. Although enzyme testing has been optimized and widely used for carrier screening in Ashkenazi Jewish (AJ) individuals, it has unproven sensitivity and specificity in a pan-ethnic population. The ability to detect HEXA variants via DNA analysis has evolved from limited targeting of a few ethnicity-specific variants to next-generation sequencing (NGS) of the entire coding region coupled with interpretation of any discovered novel variants. METHODS: We combined results of enzyme testing, retrospective computational analysis, and variant reclassification to estimate the respective clinical performance of TSD screening via enzyme analysis and NGS. We maximized NGS accuracy by reclassifying variants of uncertain significance and compared to the maximum performance of enzyme analysis estimated by calculating ethnicity-specific frequencies of variants known to yield false-positive or false-negative enzyme results (e.g., pseudodeficiency and B1 alleles). RESULTS: In both AJ and non-AJ populations, the estimated clinical sensitivity, specificity, and positive predictive value were higher by NGS than by enzyme testing. The differences were significant for all comparisons except for AJ clinical sensitivity, where NGS exceeded enzyme testing, but not significantly. CONCLUSIONS: Our results suggest that performance of an NGS-based TSD carrier screen that interrogates the entire coding region and employs novel variant interpretation exceeds that of Hex A enzyme testing, warranting a reconsideration of existing guidelines.

Inter-lab concordance of variant classifications establishes clinical validity of expanded carrier screening.

Expanded carrier screening (ECS) panels that use next-generation sequencing aim to identify pathogenic variants in coding and clinically relevant non-coding regions of hundreds of genes, each associated with a serious recessive condition. ECS has established analytical validity and clinical utility, meaning that variants are accurately identified and pathogenic variants tend to alter patients' clinical management, respectively. However, the clinical validity of ECS, that is, correct discernment of whether an identified variant is indeed pathogenic, has only been shown for single conditions, not for panels. Here, we evaluate the clinical validity of a >170-condition ECS panel by assessing concordance between >12 000 variant interpretations classified with guideline-based criteria to their corresponding per-variant combined classifications in ClinVar. We observe 99% concordance at the level of unique variants. A more clinically relevant frequency-weighted analysis reveals that fewer than 1 in 500 patients are expected to receive a report with a variant that has a discordant classification. Importantly, gene-level concordance is not diminished for rare ECS conditions, suggesting that large panels do not balloon the panel-wide false-positive rate. Finally, because ECS is intended to serve all reproductive-age couples, we show that classification of novel variants is feasible and scales predictably for a large population.