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 |
Score Construction | |
PGS Name | asthma_2 |
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 | 6,770 |
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%) |
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 |
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— | [ ,
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 | — |
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 |
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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 |
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