PGS Publication: PGP000292

Publication Information (EuropePMC)
Title Genetic predisposition to cancer across people of different ancestries in Qatar: a population-based, cohort study.
PubMed ID 35150601(Europe PMC)
doi 10.1016/s1470-2045(21)00752-x
Publication Date Feb. 9, 2022
Journal Lancet Oncol
Author(s) Saad M, Mokrab Y, Halabi N, Shan J, Razali R, Kunji K, Syed N, Temanni R, Subramanian M, Ceccarelli M, Qatar Genome Programme Research Consortium, Rafii Tabrizi A, Bedognetti D, Chouchane L.
Released in PGS Catalog: March 16, 2022

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

External PGS Evaluated By This Publication

Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000370
(PRSWEB_PHECODE153_CRC-Huyghe_PT_UKB_20200608)
PGP000118 |
Fritsche LG et al. Am J Hum Genet (2020)
Colorectal cancer colorectal cancer 87
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000370/ScoringFiles/PGS000370.txt.gz
PGS000004
(PRS313_BC)
PGP000002 |
Mavaddat N et al. Am J Hum Genet (2018)
Breast Cancer breast carcinoma 313
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000004/ScoringFiles/PGS000004.txt.gz
PGS000030
(PrCa)
PGP000019 |
Schumacher FR et al. Nat Genet (2018)
Prostate cancer prostate carcinoma 147
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000030/ScoringFiles/PGS000030.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
PPM012885 PGS000004
(PRS313_BC)
PSS009592|
Ancestry Not Reported|
5,023 individuals
PGP000292 |
Saad M et al. Lancet Oncol (2022)
|Ext.
Reported Trait: Breast cancer OR: 1.432 [1.333, 1.538] AUROC: 0.6 [0.581, 0.62]
PPM012886 PGS000030
(PrCa)
PSS009594|
Ancestry Not Reported|
4,580 individuals
PGP000292 |
Saad M et al. Lancet Oncol (2022)
|Ext.
Reported Trait: Prostate cancer OR: 1.835 [1.664, 2.023] AUROC: 0.672 [0.645, 0.698]
PPM012887 PGS000370
(PRSWEB_PHECODE153_CRC-Huyghe_PT_UKB_20200608)
PSS009593|
Ancestry Not Reported|
9,666 individuals
PGP000292 |
Saad M et al. Lancet Oncol (2022)
|Ext.
Reported Trait: Colorectal cancer OR: 1.543 [1.411, 1.686] AUROC: 0.621 [0.597, 0.645]

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
PSS009592
[
  • 989 cases
  • , 4,034 controls
]
,
0.0 % Male samples
Not reported TCGA
PSS009593
[
  • 592 cases
  • , 9,074 controls
]
Not reported TCGA
PSS009594
[
  • 453 cases
  • , 4,127 controls
]
,
100.0 % Male samples
Not reported TCGA