David Mayer

Background: The 2024–2025 influenza season was the most severe in the United States (US) since 2017–2018, with co-circulation of both influenza A virus subtypes (H1N1 and H3N2). Influenza vaccine effectiveness (VE) has varied by season, setting, and patient characteristics. Methods: Using electronic healthcare encounter data from 7 VISION sites in 8 US states, we evaluated influenza VE against influenza-associated hospitalizations and emergency department or urgent care (ED/UC) encounters from October 2024 to April 2025 among children aged 6 months–17 years and adults aged ≥18 years. Using a test-negative, case-control design, we compared the odds of influenza vaccination between acute respiratory illness encounters with a positive (cases) versus negative (controls) test for influenza by molecular assay, adjusting for confounders. Results: Analyses included 108 618 encounters (5764 hospitalizations and 102 854 ED/UC encounters) among children and 309 483 encounters (76 072 hospitalizations and 233 411 ED/UC encounters) among adults. Among children across care settings, 17.0% (6097/35 765) of cases versus 29.4% (21 449/72 853) of controls were vaccinated. Among adults, 28.2% (21 832/77 477) of cases versus 44.2% (102 560/232 006) of controls were vaccinated. VE was 51% (95% confidence interval [95% CI]: 41%–60%) against influenza-associated hospitalizations and 54% (95% CI: 52%–55%) against influenza-associated ED/UC encounters among children. VE was 43% (95% CI: 41%–46%) against influenza-associated hospitalizations and 49% (95% CI: 47%–50%) against influenza-associated ED/UC encounters among adults. Conclusions: Influenza vaccination provided protection against influenza-associated hospitalizations and ED/UC encounters among children and adults in the US during the severe 2024–2025 influenza season. These findings support influenza vaccination as an important tool to reduce influenza.

Background: The 2024–25 influenza season was the most severe in the United States (US) since 2017–18, with co-circulation of both influenza A virus subtypes (H1N1 and H3N2). Influenza vaccine effectiveness (VE) has varied by season, setting, and patient characteristics. Methods: Using electronic healthcare encounter data from eight US states, we evaluated influenza vaccine effectiveness (VE) against influenza-associated hospitalizations and emergency department or urgent care (ED/UC) encounters from October 2024–April 2025 among children aged 6 months–17 years and adults aged ≥18 years. Using a test-negative, case-control design, we compared the odds of influenza vaccination between acute respiratory illness (ARI) encounters with a positive (cases) versus negative (controls) test for influenza by molecular assay, adjusting for confounders. Results: Analyses included 108,618 encounters (5,764 hospitalizations and 102,854 ED/UC encounters) among children and 309,483 encounters (76,072 hospitalizations and 233,411 ED/UC encounters) among adults. Among children across care settings, 17.0% (6,097/35,765) of cases versus 29.4% (21,449/72,853) of controls were vaccinated. Among adults, 28.2% (21,832/77,477) of cases versus 44.2% (102,560/232,006) of controls were vaccinated. VE was 51% (95% confidence interval [95% CI]: 41–60%) against influenza-associated hospitalizations and 54% (95% CI: 52–55%) against influenza-associated ED/UC encounters among children. VE was 43% (95% CI: 41–46%) against influenza-associated hospitalizations and 49% (95% CI: 47–50%) against influenza-associated ED/UC encounters among adults. Conclusions: Influenza vaccination provided protection against influenza-associated hospitalizations and ED/UC encounters among children and adults in the US during the severe 2024–25 influenza season. These findings support influenza vaccination as an important tool to reduce influenza-associated disease. Brief Summary: During the 2024–25 influenza season, influenza vaccination provided protection against influenza-associated hospitalizations (43–51%) and emergency department or urgent care encounters (49–54%) among children and adults in the United States.

Many complex traits in humans exhibit sex differences. Recent advances in understanding context-specific genetic effects underscore the imperative for sex-aware genetic analyses to assess the role of sex in the genetic basis of human phenotypes. Despite increasing recognition of the importance of sex as a biological variable, current computational tools for genome-wide association studies (GWAS) lack functionality for performing nuanced sex-aware quality control and analysis. In response, we present GXwasR, a comprehensive R package that implements statistical genetic models for performing both GWAS and X-Chromosome-Wide Association Studies (XWAS). Designed for both sex-combined and sex-stratified analyses, GXwasR can account for unique features of chromosome X, including X-chromosome inactivation. Beyond enabling association analysis and meta-analysis, the tool has functions to a) test for sex differences in SNP-level genetic effects and heritability, b) assess genetic correlation, c) compute sex-aware polygenic risk scores (PRS), and d) support enhanced quality control protocols expressly designed for these purposes. GXwasR thus serves as a computational resource to enable investigations into the role of sex in the genetic basis of complex human phenotypes.

Over 6.37 million people have died from COVID-19 worldwide, but factors influencing COVID-19-related mortality remain understudied. We aimed to describe and identify risk factors for COVID-19 mortality in the Colorado Center for Personalized Medicine (CCPM) Biobank using integrated data sources, including Electronic Health Records (EHRs). We calculated cause-specific mortality and case-fatality rates for COVID-19 and common pre-existing health conditions defined by diagnostic phecodes and encounters in EHRs. We performed multivariable logistic regression analyses of the association between each pre-existing condition and COVID-19 mortality. Of the 155,859 Biobank participants enrolled as of July 2022, 20,797 had been diagnosed with COVID-19. Of 5334 Biobank participants who had died, 190 were attributed to COVID-19. The case-fatality rate was 0.91% and the COVID-19 mortality rate was 122 per 100,000 persons. The odds of dying from COVID-19 were significantly increased among older men, and those with 14 of the 61 pre-existing conditions tested, including hypertensive chronic kidney disease (OR: 10.14, 95% CI: 5.48, 19.16) and type 2 diabetes with renal manifestations (OR: 5.59, 95% CI: 3.42, 8.97). Male patients who are older and have pre-existing kidney diseases may be at higher risk for death from COVID-19 and may require special care.

Background: Neutralizing monoclonal antibodies (mAbs) are highly effective in reducing hospitalization and mortality among early symptomatic COVID-19 patients in clinical trials and real-world data. While resistance to some mAbs has since emerged among new variants, characteristics associated with treatment failure of mAbs remain unknown.Methods: This multicenter, observational cohort study included patients with COVID-19 who received mAb treatment between November 20, 2020, and December 9, 2021. We utilized electronic health records from a statewide health system plus state-level vaccine and mortality data. The primary outcome was mAb treatment failure, defined as hospitalization or death within 28 days of a positive SARS-CoV-2 test.Results: COVID-19 mAb was administered to 7406 patients. Hospitalization within 28 days of positive SARS-CoV-2 test occurred in 258 (3.5%) of all patients who received mAb treatment. Ten patients (0.1%) died within 28 days, and all but one were hospitalized prior to death. Characteristics associated with treatment failure included having two or more comorbidities excluding obesity and immunocompromised status (adjusted odds ratio [OR] 3.71, 95% confidence interval [CI] 2.52–5.56), lack of SARS-CoV-2 vaccination (OR 2.73, 95% CI 2.01–3.77), non-Hispanic black race/ethnicity (OR 2.21, 95% CI 1.20–3.82), obesity (OR 1.79, 95% CI 1.36–2.34), one comorbidity (OR 1.68, 95% CI 1.11–2.57), age ≥ 65 years (OR 1.62, 95% CI 1.13–2.35), and male sex (OR 1.56, 95% CI 1.21–2.02). Immunocompromised status (none, mild, or moderate/severe), pandemic phase, and type of mAb received were not associated with treatment failure (all p > 0.05).Conclusions: Comorbidities, lack of prior SARS-CoV-2 vaccination, non-Hispanic black race/ethnicity, obesity, age ≥ 65 years, and male sex are associated with treatment failure of mAbs.

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the Biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has over 200,000 patients with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain Region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped patients across multiple disease domains. Finally, we describe our current efforts towards return of clinical genetic test results including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA and CLIA-certified environment.

Background: Characterizing the experience and impact of the COVID-19 pandemic among various populations remains challenging due to the limitations inherent in common data sources, such as electronic health records (EHRs) or cross-sectional surveys. Objective: This study aims to describe testing behaviors, symptoms, impact, vaccination status, and case ascertainment during the COVID-19 pandemic using integrated data sources. Methods: In summer 2020 and 2021, we surveyed participants enrolled in the Biobank at the Colorado Center for Personalized Medicine (CCPM; N=180,599) about their experience with COVID-19. The prevalence of testing, symptoms, and impacts of COVID-19 on employment, family life, and physical and mental health were calculated overall and by demographic categories. Survey respondents who reported receiving a positive COVID-19 test result were considered a “confirmed case” of COVID-19. Using EHRs, we compared COVID-19 case ascertainment and characteristics in EHRs versus the survey. Positive cases were identified in EHRs using the International Statistical Classification of Diseases, 10th revision (ICD-10) diagnosis codes, health care encounter types, and encounter primary diagnoses. Results: Of the 25,063 (13.9%) survey respondents, 10,661 (42.5%) had been tested for COVID-19, and of those, 1366 (12.8%) tested positive. Nearly half of those tested had symptoms or had been exposed to someone who was infected. Young adults (18-29 years) and Hispanics were more likely to have positive tests compared to older adults and persons of other racial/ethnic groups. Mental health (n=13,688, 54.6%) and family life (n=12,233, 48.8%) were most negatively affected by the pandemic and more so among younger groups and women; negative impacts on employment were more commonly reported among Black respondents. Of the 10,249 individuals who responded to vaccination questions from version 2 of the survey (summer 2021), 9770 (95.3%) had received the vaccine. After integration with EHR data up to the time of the survey completion, 1006 (4%) of the survey respondents had a discordant COVID-19 case status between EHRs and the survey. Using all longitudinal EHR and survey data, we identified 11,472 (6.4%) COVID-19-positive cases among Biobank participants. In comparison to COVID-19 cases identified through the survey, EHR-identified cases were younger and more likely to be Hispanic. Conclusions: We found that the COVID-19 pandemic has had far-reaching and varying effects among our Biobank participants. Integrated data assets, such as the Biobank at the CCPM, are key resources for population health monitoring in response to public health emergencies, such as the COVID-19 pandemic.

Background: It is not known whether sotrovimab, a neutralizing monoclonal antibody (mAb) treatment authorized for early symptomatic COVID-19 patients, is effective against the SARS-CoV-2 Delta variant to prevent progression to severe disease and mortality. Methods: Observational cohort study of non-hospitalized adult patients with SARS-CoV-2 infection from October 1 ^st 2021 - December 11 ^th 2021, using electronic health records from a statewide health system plus state-level vaccine and mortality data. We used propensity matching to select 3 patients not receiving mAbs for each patient who received outpatient sotrovimab treatment. The primary outcome was 28-day hospitalization; secondary outcomes included mortality and severity of hospitalization. Results: Of 10,036 patients with SARS-CoV-2 infection, 522 receiving sotrovimab were matched to 1,563 not receiving mAbs. Compared to mAb-untreated patients, sotrovimab treatment was associated with a 63% decrease in the odds of all-cause hospitalization (raw rate 2.1% versus 5.7%; adjusted OR 0.37, 95% CI 0.19-0.66) and an 89% decrease in the odds of all-cause 28-day mortality (raw rate 0% versus 1.0%; adjusted OR 0.11, 95% CI 0.0-0.79), and may reduce respiratory disease severity among those hospitalized. Conclusion: Real-world evidence demonstrated sotrovimab effectiveness in reducing hospitalization and all-cause 28-day mortality among COVID-19 outpatients during the Delta variant phase.

Studying proteins through the lens of evolution can reveal features such as conserved domains, lineage-specific variants, and co-occurring domain architectures in phylogenetic context across all superkingdoms. MolEvolvR enables researchers to conduct such evolution-focused studies to generate testable hypotheses about protein function and evolution. MolEvolvR is a novel web-app allowing researchers to visualize the molecular evolution of their proteins of interest in a phylogenetic context across the tree of life. It accepts multiple input formats — protein/domain sequences, homologous proteins, or domain scans — and, using a general-purpose computational workflow, returns detailed homolog data and dynamic graphical summaries (e.g., phylogenetic trees, multiple sequence alignments, domain architectures, domain proximity networks, phyletic spreads, co-occurrence patterns across lineages). MolEvolvR performs domain-centric searches to capture remote homologs that are missed by full-length searches, integrates domain architecture evolution with phyletic distribution analyses, and provides evolutionary context visualizations that reveal lineage-specific adaptations versus those that are broadly conserved. Thus, MolEvolvR is a powerful, easy-to-use web interface for computational protein characterization. The web-app can be accessed here: https://jravilab.org/molevolvr.