Association of SARS-CoV-2 Spike Protein Antibody Vaccine Response with Infection Severity in Patients with Cancer: A National COVID Cancer Cross-sectional Evaluation

Importance: Accurate identification of patient groups with the lowest level of protection following COVID-19 vaccination is important to better target resources and interventions for the most vulnerable populations. It is not known whether SARS-CoV-2 antibody testing has clinical utility for high-risk groups, such as people with cancer. Objective: To evaluate whether spike protein antibody vaccine response (COV-S) following COVID-19 vaccination is associated with the risk of SARS-CoV-2 breakthrough infection or hospitalization among patients with cancer. Design, Setting, and Participants: This was a population-based cross-sectional study of patients with cancer from the UK as part of the National COVID Cancer Antibody Survey. Adults with a known or reported cancer diagnosis who had completed their primary SARS-CoV-2 vaccination schedule were included. This analysis ran from September 1, 2021, to March 4, 2022, a period covering the expansion of the UK's third-dose vaccination booster program. Interventions: Anti-SARS-CoV-2 COV-S antibody test (Elecsys; Roche). Main Outcomes and Measures: Odds of SARS-CoV-2 breakthrough infection and COVID-19 hospitalization. Results: The evaluation comprised 4249 antibody test results from 3555 patients with cancer and 294230 test results from 225272 individuals in the noncancer population. The overall cohort of 228827 individuals (patients with cancer and the noncancer population) comprised 298479 antibody tests. The median age of the cohort was in the age band of 40 and 49 years and included 182741 test results (61.22%) from women and 115737 (38.78%) from men. There were 279721 tests (93.72%) taken by individuals identifying as White or White British. Patients with cancer were more likely to have undetectable anti-S antibody responses than the general population (199 of 4249 test results [4.68%] vs 376 of 294230 [0.13%]; P <.001). Patients with leukemia or lymphoma had the lowest antibody titers. In the cancer cohort, following multivariable correction, patients who had an undetectable antibody response were at much greater risk for SARS-CoV-2 breakthrough infection (odds ratio [OR], 3.05; 95% CI, 1.96-4.72; P <.001) and SARS-CoV-2-related hospitalization (OR, 6.48; 95% CI, 3.31-12.67; P <.001) than individuals who had a positive antibody response. Conclusions and Relevance: The findings of this cross-sectional study suggest that COV-S antibody testing allows the identification of patients with cancer who have the lowest level of antibody-derived protection from COVID-19. This study supports larger evaluations of SARS-CoV-2 antibody testing. Prevention of SARS-CoV-2 transmission to patients with cancer should be prioritized to minimize impact on cancer treatments and maximize quality of life for individuals with cancer during the ongoing pandemic.

Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders

The development of computational methods to assess pathogenicity of pre-messenger RNA splicing variants is critical for diagnosis of human disease. We assessed the capability of eight algorithms, and a consensus approach, to prioritize 249 variants of uncertain significance (VUSs) that underwent splicing functional analyses. The capability of algorithms to differentiate VUSs away from the immediate splice site as being ‘pathogenic’ or ‘benign’ is likely to have substantial impact on diagnostic testing. We show that SpliceAI is the best single strategy in this regard, but that combined usage of tools using a weighted approach can increase accuracy further. We incorporated prioritization strategies alongside diagnostic testing for rare disorders. We show that 15% of 2783 referred individuals carry rare variants expected to impact splicing that were not initially identified as ‘pathogenic’ or ‘likely pathogenic’; one in five of these cases could lead to new or refined diagnoses