PGS Publication: PGP000122

Publication Information (EuropePMC)
Title Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.
PubMed ID 33398198(Europe PMC)
doi 10.1038/s41588-020-00748-0
Publication Date Jan. 4, 2021
Journal Nat Genet
Author(s) Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, Schumacher FR, Olama AAA, Benlloch S, Dadaev T, Brook MN, Sahimi A, Hoffmann TJ, Takahashi A, Matsuda K, Momozawa Y, Fujita M, Muir K, Lophatananon A, Wan P, Le Marchand L, Wilkens LR, Stevens VL, Gapstur SM, Carter BD, Schleutker J, Tammela TLJ, Sipeky C, Auvinen A, Giles GG, Southey MC, MacInnis RJ, Cybulski C, Wokołorczyk D, Lubiński J, Neal DE, Donovan JL, Hamdy FC, Martin RM, Nordestgaard BG, Nielsen SF, Weischer M, Bojesen SE, Røder MA, Iversen P, Batra J, Chambers S, Moya L, Horvath L, Clements JA, Tilley W, Risbridger GP, Gronberg H, Aly M, Szulkin R, Eklund M, Nordström T, Pashayan N, Dunning AM, Ghoussaini M, Travis RC, Key TJ, Riboli E, Park JY, Sellers TA, Lin HY, Albanes D, Weinstein SJ, Mucci LA, Giovannucci E, Lindstrom S, Kraft P, Hunter DJ, Penney KL, Turman C, Tangen CM, Goodman PJ, Thompson IM, Hamilton RJ, Fleshner NE, Finelli A, Parent MÉ, Stanford JL, Ostrander EA, Geybels MS, Koutros S, Freeman LEB, Stampfer M, Wolk A, Håkansson N, Andriole GL, Hoover RN, Machiela MJ, Sørensen KD, Borre M, Blot WJ, Zheng W, Yeboah ED, Mensah JE, Lu YJ, Zhang HW, Feng N, Mao X, Wu Y, Zhao SC, Sun Z, Thibodeau SN, McDonnell SK, Schaid DJ, West CML, Burnet N, Barnett G, Maier C, Schnoeller T, Luedeke M, Kibel AS, Drake BF, Cussenot O, Cancel-Tassin G, Menegaux F, Truong T, Koudou YA, John EM, Grindedal EM, Maehle L, Khaw KT, Ingles SA, Stern MC, Vega A, Gómez-Caamaño A, Fachal L, Rosenstein BS, Kerns SL, Ostrer H, Teixeira MR, Paulo P, Brandão A, Watya S, Lubwama A, Bensen JT, Fontham ETH, Mohler J, Taylor JA, Kogevinas M, Llorca J, Castaño-Vinyals G, Cannon-Albright L, Teerlink CC, Huff CD, Strom SS, Multigner L, Blanchet P, Brureau L, Kaneva R, Slavov C, Mitev V, Leach RJ, Weaver B, Brenner H, Cuk K, Holleczek B, Saum KU, Klein EA, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Kim J, Neuhausen SL, Steele L, Ding YC, Isaacs WB, Nemesure B, Hennis AJM, Carpten J, Pandha H, Michael A, De Ruyck K, De Meerleer G, Ost P, Xu J, Razack A, Lim J, Teo SH, Newcomb LF, Lin DW, Fowke JH, Neslund-Dudas C, Rybicki BA, Gamulin M, Lessel D, Kulis T, Usmani N, Singhal S, Parliament M, Claessens F, Joniau S, Van den Broeck T, Gago-Dominguez M, Castelao JE, Martinez ME, Larkin S, Townsend PA, Aukim-Hastie C, Bush WS, Aldrich MC, Crawford DC, Srivastava S, Cullen JC, Petrovics G, Casey G, Roobol MJ, Jenster G, van Schaik RHN, Hu JJ, Sanderson M, Varma R, McKean-Cowdin R, Torres M, Mancuso N, Berndt SI, Van Den Eeden SK, Easton DF, Chanock SJ, Cook MB, Wiklund F, Nakagawa H, Witte JS, Eeles RA, Kote-Jarai Z, Haiman CA.
Released in PGS Catalog: Jan. 7, 2021

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 Scoring File (FTP Link)
PGS000662
(GRS.PCa.269)
PGP000122 |
Conti DV et al. Nat Genet (2021)
Prostate cancer prostate carcinoma 269
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000662/ScoringFiles/PGS000662.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
PPM001365 PGS000662
(GRS.PCa.269)
PSS000596|
European Ancestry|
199,969 individuals
PGP000122 |
Conti DV et al. Nat Genet (2021)
Reported Trait: Prostate Cancer AUROC: 0.833 Odds ratio (OR, top 10% versus 40-60% GRS): 4.17
Overall Net Reclassification Index (NRI [%]): 59.4
Age, 10 PCs
PPM001366 PGS000662
(GRS.PCa.269)
PSS000595|
African Ancestry|
2,633 individuals
PGP000122 |
Conti DV et al. Nat Genet (2021)
Reported Trait: Prostate Cancer AUROC: 0.679 Odds ratio (OR, top 10% versus 40-60% GRS): 3.53 Age, 10 PCs, study

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
PSS000595
[
  • 1,586 cases
  • , 1,047 controls
]
,
100.0 % Male samples
African unspecified CAUG
PSS000596
[
  • 6,852 cases
  • , 193,117 controls
]
,
100.0 % Male samples
European UKB