Implementation of pooled saliva tests for universal screening of cCMV infection.

Congenital cytomegalovirus (cCMV) is the most common intrauterine infection, leading to neurodevelopmental disabilities. Universal newborn infant screening of cCMV has been increasingly advocated. In the absence of a high-throughput screening test, which can identify all infected newborn infants, the development of an accurate and efficient testing strategy has remained an ongoing challenge. Here we assessed the implementation of pooled saliva polymerase chain reaction (PCR) tests for universal screening of cCMV, in two hospitals of Jerusalem from April 2022 through April 2023. During the 13-month study period, 15,805 infants (93.6% of all live newborn infants) were screened for cCMV using the pooled approach that has since become our routine screening method. The empirical efficiency of the pooling was six (number of tested newborn infants per test), thereby sparing 83% of the saliva tests. Only a minor 3.05 PCR cycle loss of sensitivity was observed for the pooled testing, in accordance with the theoretical prediction for an eight-sample pool. cCMV was identified in 54 newborn infants, with a birth prevalence of 3.4 per 1,000; 55.6% of infants identified with cCMV were asymptomatic at birth and would not have been otherwise targeted for screening. The study demonstrates the wide feasibility and benefits of pooled saliva testing as an efficient, cost-sparing and sensitive approach for universal screening of cCMV.

Unbiased phenotype and genotype matching maximizes gene discovery and diagnostic yield.

PURPOSE: Widespread application of next-generation sequencing, combined with data exchange platforms, has provided molecular diagnoses for countless families. To maximize diagnostic yield, we implemented an unbiased semi-automated genematching algorithm based on genotype and phenotype matching. METHODS: Rare homozygous variants identified in 2 or more affected individuals, but not in healthy individuals, were extracted from our local database of ∼12,000 exomes. Phenotype similarity scores (PSS), based on human phenotype ontology terms, were assigned to each pair of individuals matched at the genotype level using HPOsim. RESULTS: 33,792 genotype-matched pairs were discovered, representing variants in 7567 unique genes. There was an enrichment of PSS ≥0.1 among pathogenic/likely pathogenic variant-level pairs (94.3% in pathogenic/likely pathogenic variant-level matches vs 34.75% in all matches). We highlighted founder or region-specific variants as an internal positive control and proceeded to identify candidate disease genes. Variant-level matches were particularly helpful in cases involving inframe indels and splice region variants beyond the canonical splice sites, which may otherwise have been disregarded, allowing for detection of candidate disease genes, such as KAT2A, RPAIN, and LAMP3. CONCLUSION: Semi-automated genotype matching combined with PSS is a powerful tool to resolve variants of uncertain significance and to identify candidate disease genes.

Lessons from applied large-scale pooling of 133,816 SARS-CoV-2 RT-PCR tests.

Pooling multiple swab samples before RNA extraction and real-time reverse transcription polymerase chain reaction (RT-PCR) analysis has been proposed as a strategy to reduce costs and increase throughput of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests. However, reports on practical large-scale group testing for SARS-CoV-2 have been scant. Key open questions concern reduced sensitivity due to sample dilution, the rate of false positives, the actual efficiency (number of tests saved by pooling), and the impact of infection rate in the population on assay performance. Here, we report an analysis of 133,816 samples collected between April and September 2020 and tested by Dorfman pooling for the presence of SARS-CoV-2. We spared 76% of RNA extraction and RT-PCR tests, despite the frequently changing prevalence (0.5 to 6%). We observed pooling efficiency and sensitivity that exceeded theoretical predictions, which resulted from the nonrandom distribution of positive samples in pools. Overall, our findings support the use of pooling for efficient large-scale SARS-CoV-2 testing.