| 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. |
| Polygenic Score (PGS) ID | PGS Name | PGS Publication (PGP) ID | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants | PGS Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000662 | GRS.PCa.269 | PGP000122 Conti DV et al. Nat Genet (2021) | Prostate Cancer | prostate carcinoma | 269 | http://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000662/ScoringFiles/PGS000662.txt.gz |
|
PGS Performance Metric ID (PPM ID) |
Evaluated Score |
PGS Sample Set ID (PSS ID) |
Performance Source | Trait |
PGS Effect Sizes (per SD change) |
PGS Classification Metrics | Other Metrics | Covariates Included in the Model | PGS Performance: Other Relevant Information |
|---|---|---|---|---|---|---|---|---|---|
| PPM001365 | PGS000662 (GRS.PCa.269) | PSS000596 | PGP000122 Conti DV et al. (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 | PGP000122 Conti DV et al. (2021) | Reported Trait: Prostate Cancer | — | AUROC: 0.679 | Odds ratio (OR, top 10% versus 40-60% GRS): 3.53 | Age, 10 PCs, study | — |
|
PGS Sample Set ID (PSS ID) |
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 | — | — | [ ,
100.0 % Male samples |
— | African unspecified | — | CAUG | — |
| PSS000596 | — | — | [ ,
100.0 % Male samples |
— | European | — | UKB | — |