PGS Publication: PGP000415

Publication Information (EuropePMC)
Title Polygenic risk scores for prediction of breast cancer in Korean women.
PubMed ID 36343017(Europe PMC)
doi 10.1093/ije/dyac206
Publication Date Nov. 7, 2022
Journal Int J Epidemiol
Author(s) Jee YH, Ho WK, Park S, Easton DF, Teo SH, Jung KJ, Kraft P.
Released in PGS Catalog: Jan. 19, 2023

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported

PGS Developed By This Publication

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)
PGS003397
(PRS-42ASN)
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Breast cancer breast carcinoma 42
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003397/ScoringFiles/PGS003397.txt.gz
PGS003399
(PRS-209EUR)
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Breast cancer breast carcinoma 209
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003399/ScoringFiles/PGS003399.txt.gz
PGS003396
(PRS-11ASN)
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Breast cancer breast carcinoma 11
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003396/ScoringFiles/PGS003396.txt.gz
PGS003398
(PRS-136EUR)
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Breast cancer breast carcinoma 136
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003398/ScoringFiles/PGS003398.txt.gz

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) 		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
PPM016283 PGS003399
(PRS-209EUR)
 PSS010095|
East Asian Ancestry|
41,031 individuals
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Reported Trait: Occurrence of breast cancer HR: 1.54 [1.43, 1.66] AUROC: 0.62 [0.6, 0.64] — principal component —
PPM016281 PGS003397
(PRS-42ASN)
 PSS010095|
East Asian Ancestry|
41,031 individuals
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Reported Trait: Occurrence of breast cancer HR: 1.4 [1.3, 1.51] AUROC: 0.6 [0.58, 0.62] — principal component —
PPM016282 PGS003398
(PRS-136EUR)
 PSS010095|
East Asian Ancestry|
41,031 individuals
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Reported Trait: Occurrence of breast cancer HR: 1.55 [1.44, 1.66] AUROC: 0.62 [0.6, 0.64] — principal component —
PPM016280 PGS003396
(PRS-11ASN)
 PSS010095|
East Asian Ancestry|
41,031 individuals
 PGP000415 |
Jee YH et al. Int J Epidemiol (2022)
 Reported Trait: Occurrence of breast cancer HR: 1.35 [1.25, 1.45] AUROC: 0.58 [0.56, 0.61] — principal component —

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
PSS010095 — — 41,031 individuals,
0.0 % Male samples
 — East Asian
(Korean)		 — KCPS KPCS-II