Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 26, 2024F1000ResearchOpen Access

UKB.COVID19: an R package for UK Biobank COVID-19 data processing and analysis

View Full Paper
Ask AI
Bookmark
Share

Authors

LWLongfei WangVJVictoria E. JacksonLFLiam G. Fearnley

Discussion

Loading...

Member takes

Overview

Computational analysis reveals demographic and genetic risk factors in UK Biobank participants, highlighting tools for rapid pandemic epidemiological surveillance.

Key Points

  • Positively associated factors for severe SARS-CoV-2 infection include elevated body mass index and older age, with male participants exhibiting increased risk of infection.
  • Analysis of updated health records enables automated genome-wide association studies, successfully replicating the 3p21.31 locus for COVID-19 susceptibility and severity.
  • Rapid data processing clarifies how genetic predisposition interacts with environmental exposure, though researchers must secure independent UK Biobank access approvals.

Cite This Study

Wang et al. (2024) studied this question.

synapsesocial.com/papers/68e5ee97b6db64358758386bhttps://doi.org/10.12688/f1000research.55370.3
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population2017 · 4,405 citations
  2. 2ApoE4: an emerging therapeutic target for Alzheimer’s disease2019 · 466 citations
  3. 3LZTFL1 Upregulated by All-Trans Retinoic Acid during CD4+ T Cell Activation Enhances IL-5 Production2015 · 40 citations
  4. 4Collider bias undermines our understanding of COVID-19 disease risk and severity2020 · 923 citations
  5. 5Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission2020 · 1,597 citations