Our study aims to analyze COVID-19 vaccine administration in California based on various racial demographics using data collected from the California Open Data Portal (“California Grants Portal,” n.d). This analysis will focus on the months following the CDC’s Emergency Use Authorization (EUA) for the COVID-19 vaccines, including Pfizer-BioNTech, Moderna (Spikevax), and Janssen (J&J). Our goal is to examine COVID-19 vaccine equity and accessibility for various racial demographic groups in California, including American Indians or Alaska Natives, Asians, Black people or African Americans, Latinos, Pacific Islanders or other Pacific Islanders, and Whites. In our research study, we found that Whites were administered all COVID-19 vaccines at a much higher rate in the early months of the CDC’s EUA in comparison to other racial demographic groups in California. In addition, another significant finding was how other racial demographic groups, including American Indian or Alaska Natives, Asians, Black or African Americans, and Native Hawaiians or other Pacific Islanders did not reach the same level of administered COVID-19 vaccines between December 2020 to December 2021, whereas Latinos did reach that same level but only after almost a year following the CDC’s EUA, approximately around Sepetember 2021 to December 2021. Furthermore, the results of our research suggest larger societal implications regarding vaccine equity and accessibility.

Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly-interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.

Although somatic mutations in Histone 3.3 (H3.3) are well-studied drivers of oncogenesis, the role of germline mutations remains unreported. We analyze 46 patients bearing de novo germline mutations in histone 3 family 3A (H3F3A) or H3F3B with progressive neurologic dysfunction and congenital anomalies without malignancies. Molecular modeling of all 37 variants demonstrated clear disruptions in interactions with DNA, other histones, and histone chaperone proteins. Patient histone posttranslational modifications (PTMs) analysis revealed notably aberrant local PTM patterns distinct from the somatic lysine mutations that cause global PTM dysregulation. RNA sequencing on patient cells demonstrated up-regulated gene expression related to mitosis and cell division, and cellular assays confirmed an increased proliferative capacity. A zebrafish model showed craniofacial anomalies and a defect in Foxd3-derived glia. These data suggest that the mechanism of germline mutations are distinct from cancer-associated somatic histone mutations but may converge on control of cell proliferation.

Background

The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.

Results

Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.

Conclusions

Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.