Evaluating Two Educational Interventions for Enhancing COVID-19 Knowledge and Attitudes in a Sample American Indian/Alaska Native Population.

BACKGROUND: The COVID-19 pandemic has exacerbated existing healthcare disparities among American Indian/Alaska Native (AI/AN) populations rooted in historical traumas and systemic marginalization. METHODS: This study conducted at a single Indian Health Service (IHS) clinic in central Michigan evaluates two educational interventions for enhancing COVID-19 knowledge and attitudes in a sample AI/AN population. Utilizing a pre/post-intervention prospective study design, participants received either a video or infographic educational intervention, followed by a survey assessing their COVID-19 knowledge and attitudes. RESULTS: The results indicate significant improvements in knowledge and attitudes post-intervention, with both modalities proving effective. However, specific factors such as gender, political affiliation, and place of residence influenced COVID-19 attitudes and knowledge, emphasizing the importance of tailored interventions. CONCLUSIONS: Despite limitations, this study highlights the critical role of educational interventions in addressing vaccine hesitancy and promoting health equity within AI/AN communities. Moving forward, comprehensive strategies involving increased Indian Health Service funding, culturally relevant interventions, and policy advocacy are crucial in mitigating healthcare disparities and promoting health equity within AI/AN communities.

High-throughput PRIME-editing screens identify functional DNA variants in the human genome.

Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and single-base resolution manner remains challenging. Here, we develop a pooled prime-editing screen method, PRIME, that can be applied to characterize thousands of coding and non-coding variants in a single experiment with high reproducibility. To showcase its applications, we first identified essential nucleotides for a 716 bp MYC enhancer via PRIME-mediated single-base resolution analysis. Next, we applied PRIME to functionally characterize 1,304 genome-wide association study (GWAS)-identified non-coding variants associated with breast cancer and 3,699 variants from ClinVar. We discovered that 103 non-coding variants and 156 variants of uncertain significance are functional via affecting cell fitness. Collectively, we demonstrate that PRIME is capable of characterizing genetic variants at single-base resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.

Sociodemographic Disparities in the Diagnosis and Prognosis of Patients With Cervical Cancer: An Analysis of the Surveillance, Epidemiology, and End Results Program.

Background While the incidence and mortality rates of cervical cancer are declining due to improved prevention, screening, and treatment, inequitable access to care may contribute to worse patient outcomes. Therefore, we sought to evaluate sociodemographic disparities in the diagnosis and prognosis of patients with cervical cancer. Methodology The Surveillance, Epidemiology, and End Results (SEER) database was queried for adult women diagnosed with cervical cancer from 2010 to 2015. Sociodemographic groups of interest included patient race/ethnicity (non-Hispanic White/Hispanic White/Black/Other), residential setting (rural/urban), and county median household income (<$45,000/$45,000-59,999/$60,000-74,999/≥$75,000). Outcomes of interest included stage at diagnosis, receipt of hysterectomy, and overall survival (OS). Outcomes were evaluated using Pearson's chi-square test, multivariable logistic regression, and multivariable Cox proportional hazards. Results A total of 5,726 patients were identified with an average age of 50.1 years (SD = 14.6). Significant differences in cancer stage at diagnosis were identified based on race/ethnicity (p < 0.001) and household income (p = 0.012). On adjusted analysis, Black patients were found to be significantly less likely to receive a hysterectomy compared to non-Hispanic White patients (odds ratio (OR) = 0.46; 95% confidence interval (CI) = 0.37-0.56). Lower household income was associated with poorer survival for stage I (<$45,000 vs. >$75,000: hazard ratio (HR) = 1.53; 95% interquartile range (IQR) = 1.00-2.33), II ($45,000-59,999 vs. >$75,000: HR = 1.67; 95% IQR = 1.19-2.35), and IV (<$45,000 vs. >$75,000: HR = 1.64; 95% IQR = 1.22-2.29) disease. Black race was associated with poorer OS for stage IV disease (HR = 1.29; 95% IQR = 1.06-1.56). Conclusions This study highlights significant disparities in disease progression at diagnosis and OS for cervical cancer patients based on race/ethnicity and household income. These findings may assist policymakers in developing strategies for mitigating these disparities.

High throughput PRIME editing screens identify functional DNA variants in the human genome.

Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and base-pair resolution manner remains challenging. Here, we develop a novel pooled prime editing screen method, PRIME, which can be applied to characterize thousands of coding and non-coding variants in a single experiment with high reproducibility. To showcase its applications, we first identified essential nucleotides for a 716 bp MYC enhancer via PRIME-mediated saturation mutagenesis. Next, we applied PRIME to functionally characterize 1,304 non-coding variants associated with breast cancer and 3,699 variants from ClinVar. We discovered that 103 non-coding variants and 156 variants of uncertain significance are functional via affecting cell fitness. Collectively, we demonstrate PRIME capable of characterizing genetic variants at base-pair resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.

COVID-19 Virus and Vaccination Attitudes among Healthcare Workers in Michigan: A Cross-Sectional Study.

BACKGROUND: Defining the characteristics of healthcare worker (HCW) attitudes toward the coronavirus disease 2019 (COVID-19) vaccine can provide insights into vaccine hesitancy. This study's goal is to determine HCWs' attitudes regarding the COVID-19 vaccination and reasons for vaccine hesitancy. METHODS: This cross-sectional study surveyed HCWs working in institutions in Saginaw, Sanilac, and Wayne counties in Michigan (N = 120) using tipping-scale questions. Analysis of variance and t-test were used to measure HCWs' attitudes toward the COVID-19 virus and vaccines. RESULTS: Most HCWs received (95.9%) and recommended (98.3%) a COVID-19 vaccine. The top three factors that HCWs cited for recommending a COVID-19 vaccine were: (1) efficacy of the vaccine, (2) current exposure to patients with active COVID-19 infection and risk of virus spread, and (3) safety of vaccine and long-term follow-up. Female HCWs or HCWs aged 25-54 years were more concerned about contracting COVID-19. Physicians or HCWs aged 55-64 were less concerned regarding the effectiveness and side effects of the vaccine. CONCLUSIONS: Gender, age, ethnicity, provider type, and medical specialty showed statistically significant differences among COVID-19 attitudes. Focusing educational efforts on HCW demographics who are more likely to have negative attitudes can potentially decrease vaccine hesitancy.

The impact of educational interventions on COVID-19 and vaccination attitudes among patients in Michigan: A prospective study.

Background: Mass vaccination serves as an effective strategy to combat the COVID-19 pandemic. Vaccine hesitancy is a recognized impediment to achieving a vaccination rate necessary to protect communities. However, solutions and interventions to address this issue are limited by a lack of prior research. Methods: Over 200 patients from 18 Michigan counties participated in this study. Each participant received an initial survey, including demographical questions and knowledge and opinion questions regarding COVID-19 and vaccines. Participants were randomly assigned an educational intervention in either video or infographic format. Patients received a post-survey to assess changes in knowledge and attitudes. Paired sample t-tests and ANOVA were used to measure the effectiveness of the educational interventions. Participants also elected to complete a 3-month follow-up survey. Results: Patients showed increased knowledge after the educational intervention in six out of seven COVID-19 topics (p < 0.005). There was increased vaccine acceptance after the intervention but no difference in the effectiveness between the two intervention modalities. Post-intervention, more patients believed in CDC recommendations (p = 0.005), trusted the vaccine (p = 0.001), believed the vaccines had adequate testing (p = 0.019), recognized prior mistreatment in the medical care system (p = 0.005), agreed that a source they trust told them to receive a vaccine (p = 0.015), and were worried about taking time off of work to get a vaccine (p = 0.023). Additionally, post-intervention, patients were less concerned about mild reactions of the virus (p = 0.005), the rapid development of the vaccines (p < 0.001), and vaccine side effects (p = 0.031). Data demonstrated that attitude and knowledge improved when comparing pre-educational intervention to follow-up but decreased from post-intervention to follow-up. Conclusion: The findings illustrate that educational interventions improved COVID-19 and vaccine knowledge among patients and that the knowledge was retained. Educational interventions serve as powerful tools to increase knowledge within communities and address negative views on vaccination. Interventions should be continually utilized to reinforce information within communities to improve vaccination rates.

Efficient bi-allelic tagging in human induced pluripotent stem cells using CRISPR.

Allelic tagging of endogenous genes enables studying gene function and transcriptional control in the native genomic context. Here, we present an efficient protocol for bi-allelic tagging of protein-coding genes with fluorescent reporters in human iPSCs using the CRISPR-Cas9-mediated homology-directed repair. We detail steps for design, cloning, electroporation, and single-cell clone isolation and validation. The tagging strategy described in this protocol is readily applicable for knockin of other reporters in diverse cell types for biomedical research.

Parallel characterization of cis-regulatory elements for multiple genes using CRISPRpath.

Current pooled CRISPR screens for cis-regulatory elements (CREs), based on transcriptional output changes, are typically limited to characterizing CREs of only one gene. Here, we describe CRISPRpath, a scalable screening strategy for parallelly characterizing CREs of genes linked to the same biological pathway and converging phenotypes. We demonstrate the ability of CRISPRpath for simultaneously identifying functional enhancers of six genes in the 6-thioguanine­induced DNA mismatch repair pathway using both CRISPR interference (CRISPRi) and CRISPR nuclease (CRISPRn) approaches. Sixty percent of the identified enhancers are known promoters with distinct epigenomic features compared to other active promoters, including increased chromatin accessibility and interactivity. Furthermore, by imposing different levels of selection pressure, CRISPRpath can distinguish enhancers exerting strong impact on gene expression from those exerting weak impact. Our results offer a nuanced view of cis-regulation and demonstrate that CRISPRpath can be leveraged for understanding the complex gene regulatory program beyond transcriptional output at scale.