Publications by authors named "Alexis Vest"
Accessing and utilizing clinical and genomic data from an electronic health record data warehouse.
Transl Med Commun
March 2023
Electronic health records (EHRs) and linked biobanks have tremendous potential to advance biomedical research and ultimately improve the health of future generations. Repurposing EHR data for research is not without challenges, however. In this paper, we describe the processes and considerations necessary to successfully access and utilize a data warehouse for research.
View Article and Find Full Text PDFBackground: Acetaminophen (APAP) is the most common cause liver injury following alcohol in US patients. Predicting liver injury and subsequent hepatic regeneration in patients taking therapeutic doses of APAP may be possible using new 'omic methods such as metabolomics and genomics. Multi'omic techniques increase our ability to find new mechanisms of injury and regeneration.
View Article and Find Full Text PDFArticle Synopsis
- Many states in the U.S. are moving towards marijuana legalization, and this study examines its impact on emergency department visits related to cannabis.
- Seventeen healthcare institutions across fifteen states collected data on cannabinoid test results and medical codes for emergency visits over several years, corresponding to different stages of legalization.
- Findings indicate that as marijuana legalization progresses, there is generally a rise in cannabis-related emergency department visits, but the extent varies between states, influenced by factors like local culture and law enforcement attitudes.
Introduction: Biorepositories lack diversity both demographically and with regard to the clinical complaints of patients enrolled. The Emergency Medicine Specimen Bank (EMSB) seeks to enroll a diverse cohort of patients for discovery research in acute care conditions. Our objective in this study was to determine the differences in demographics and clinical complaints between participants in the EMSB and the overall emergency department (ED) population.
View Article and Find Full Text PDFRT-PCR is the foremost clinical test for diagnosis of COVID-19. Unfortunately, PCR-based testing has limitations and may not result in a positive test early in the course of infection before symptoms develop. Enveloped RNA viruses, such as coronaviruses, alter peripheral blood methylation and DNA methylation signatures may characterize asymptomatic versus symptomatic infection.
View Article and Find Full Text PDFImmune mechanisms associated with sex-based differences in severe COVID-19 clinical outcomes.
Biol Sex Differ
March 2022
Background: Although biological males and females are equally likely to become infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), evidence has mounted that males experience higher severity and fatality compared to females. MAIN: The objective of this review is to examine the existing literature on biological mechanisms underlying sex-based differences that could contribute to SARS-CoV-2 infection clinical outcomes. Sex-based differences in immunologic response and hormonal expression help explain the differences in coronavirus disease 2019 (COVID-19) outcomes observed in biological males and females.
View Article and Find Full Text PDFArticle Synopsis
- The study explores how DNA methylation patterns in COVID-19 patients can differentiate them from healthy individuals and forecast disease severity.
- Customization of a specialized DNA methylation array allowed researchers to analyze blood samples, revealing thousands of significant methylation sites linked to immune response and viral activity.
- Machine learning models showed high accuracy in predicting patient outcomes, highlighting the potential of using these epigenetic markers for improved diagnosis and prognosis in COVID-19 cases.
Article Synopsis
- The study investigates DNA methylation as a potential biomarker for distinguishing between SARS-CoV-2 infected patients and uninfected controls, with implications for predicting disease severity.
- Using a customized Illumina methylation array, researchers analyzed blood samples from 164 COVID-19 patients and 296 controls, identifying over 13,000 significant methylation sites linked to immune response pathways.
- Machine learning models demonstrated high predictive accuracy for determining case status and likelihood of severe outcomes, highlighting the relevance of epigenetic signatures in diagnosing and forecasting COVID-19 progression.