We characterized the genetics of 35 biomarkers in UK Biobank. We performed the association and fine-mapping analysis to prioritize the causal variants, constructed the polygenic risk score (PRS) models, and evaluated their medical relevance with causal inference and PRS-PheWAS. We demonstrate a new approach, called multi-PRS, to improve PRS by combining PRSs across traits.

• GWAS summary statistics is available on GWAS catalog

We uploaded the supplementary data on figshare.

• GWAS summary statistics
  • Title: The meta-analyzed GWAS summary statistics for 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'
  • DOI: https://doi.org/10.35092/yhjc.12355382
• snpnet
  • Title: The snpnet polygenic risk score coefficients for 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'
  • DOI: https://doi.org/10.35092/yhjc.12298838
• multi-PRS
  • Title: The multi-PRS weights computed with the 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'
  • DOI: https://doi.org/10.35092/yhjc.12355424

• trait names
• plotting color (on Supplementary table ST4)

• covariate_correction: (for adjusting for statins and covariates)
• snakemake: (for running the GWAS)
  • filtration: (for filtering GWAS results)
    • meta: (meta-analysis of the GWAS from multiple populations)
      • meta_flipfix: (flipping alleles on the meta-analysis)
      • cascade: (plotting of the variant effects)
      • phewas: (testing against other traits)
• snpnet: (generation of polygenic risk scores)

• Phenotype file location
  • Residual: @@@@@@/projects/biomarkers/covariate_corrected/outputExtendedNoTDIreduced/phenotypes/combined.20190810.phe
• GWAS summary statistics
  • @@@@@@/projects/biomarkers_rivas/main/<population>/ukb24983_v2_hg19.<trait>.genotyped.glm.linear.gz
• M-A
  • @@@@@@/projects/biomarkers_rivas/meta_flipfixed/METAANALYSIS_<trait>_1.tbl.gz