Publication Information (EuropePMC) | |
Title | Advancing our understanding of genetic risk factors and potential personalized strategies for pelvic organ prolapse. |
PubMed ID | 35739095(Europe PMC) |
doi | 10.1038/s41467-022-31188-5 |
Publication Date | June 23, 2022 |
Journal | Nat Commun |
Author(s) | Pujol-Gualdo N, Läll K, Lepamets M, Estonian Biobank Research Team, Rossi HR, Arffman RK, Piltonen TT, Mägi R, Laisk T. |
Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
---|---|---|---|---|---|---|
PGS002288 (PRS_POP) |
PGP000314 | Pujol-Gualdo N et al. Nat Commun (2022) |
Pelvic organ prolapse | pelvic organ prolapse | 3,242,959 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002288/ScoringFiles/PGS002288.txt.gz |
PGS Performance Metric ID (PPM) |
Evaluated Score |
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 |
---|---|---|---|---|---|---|---|---|---|
PPM012986 | PGS002288 (PRS_POP) |
PSS009640| European Ancestry| 98,656 individuals |
PGP000314 | Pujol-Gualdo N et al. Nat Commun (2022) |
Reported Trait: Incident pelvic organ prolapse cases | HR: 1.31 [1.25, 1.37] | C-index: 0.592 | — | 10 PCs, and seven batche indicators | — |
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 |
---|---|---|---|---|---|---|---|---|
PSS009640 | — | — | [ ,
0.0 % Male samples |
— | European | — | EB | — |