Polygenic Score (PGS) ID: PGS004179

Predicted Trait
Reported Trait Asthma
Mapped Trait(s) asthma (MONDO_0004979)
Additional Trait Information UK Biobank codes: non-cancer codes: 1111; ICD9: 49300, 49309 ,49310 ,49319 ,49390 ,49399; ICD10: J450,J451,J458
Released in PGS Catalog: Dec. 15, 2023
Download Score FTP directory
Terms and Licenses
PGS obtained from the Catalog should be cited appropriately, and used in accordance with any licensing restrictions set by the authors. See EBI Terms of Use (https://www.ebi.ac.uk/about/terms-of-use/) for additional details.

Score Details

Score Construction
PGS Name asthma_4
Development Method
Name LASSO
Parameters To reduce the number of candidate SNPs to a computationally feasible set, a gwas was performed on the raw phenotype and the 50,000 snps with smallest p-value were retained. The raw phenotype was regressed on age, sex, and the top 20 UK Biobank PCs and a residual phenotype was then built. The LASSO model was trained using these 50k SNPs and the adjusted phenotype.
Variants
Original Genome Build GRCh37
Number of Variants 3,963
Effect Weight Type beta
PGS Source
PGS Catalog Publication (PGP) ID PGP000520
Citation (link to publication) Raben TG et al. Sci Rep (2023)
Ancestry Distribution
Score Development/Training
European: 100%
200,000 individuals (100%)

Development Samples

Score Development/Training
Study Identifiers Sample Numbers Sample Ancestry Cohort(s) Phenotype Definitions & Methods Age of Study Participants Participant Follow-up Time Additional Ancestry Description Additional Sample/Cohort Information
[
  • 48,612 cases
  • , 151,388 controls
]
,
45.7 % Male samples
European NR UK Biobank codes: non-cancer codes: 1111; ICD9: 49300, 49309 ,49310 ,49319 ,49390 ,49399; ICD10: J450,J451,J458 used UK self report 'white' category and then used an adjusted phenotype that includes a regression on the top 20 PCs

Performance Metrics

Disclaimer: The performance metrics are displayed as reported by the source studies. It is important to note that metrics are not necessarily comparable with each other. For example, metrics depend on the sample characteristics (described by the PGS Catalog Sample Set [PSS] ID), phenotyping, and statistical modelling. Please refer to the source publication for additional guidance on performance.

PGS Performance
Metric ID (PPM)
PGS Sample Set ID
(PSS)
Performance Source Trait PGS Effect Sizes
(per SD change)
Classification Metrics Other Metrics Covariates Included in the Model PGS Performance:
Other Relevant Information

Evaluated Samples

PGS Sample Set ID
(PSS)
Phenotype Definitions and Methods Participant Follow-up Time Sample Numbers Age of Study Participants Sample Ancestry Additional Ancestry Description Cohort(s) Additional Sample/Cohort Information