Polygenic risk scores for the prediction of common cancers in East Asians: A population-based prospective cohort study.
To evaluate the utility of polygenic risk scores (PRSs) in identifying high-risk individuals, different publicly available PRSs for breast (n=85), prostate (n=37), colorectal (n=22), and lung cancers (n=11) were examined in a prospective study of 21,694 Chinese adults.
We constructed PRS using weights curated in the online PGS Catalog. PRS performance was evaluated by distribution, discrimination, predictive ability, and calibration. Hazard ratios (HR) and corresponding confidence intervals (CI) of the common cancers after 20 years of follow-up were estimated using Cox proportional hazard models for different levels of PRS.
A total of 495 breast, 308 prostate, 332 female-colorectal, 409 male-colorectal, 181 female-lung, and 381 male-lung incident cancers were identified. The area under receiver operating characteristic curve for the best-performing site-specific PRS were 0.61 (PGS000873, breast), 0.70 (PGS00662, prostate), 0.65 (PGS000055, female-colorectal), 0.60 (PGS000734, male-colorectal), 0.56 (PGS000721, female-lung), and 0.58 (PGS000070, male-lung), respectively. Compared to the middle quintile, individuals in the highest cancer-specific PRS quintile were 64% more likely to develop cancers of the breast, prostate, and colorectal. For lung cancer, the lowest cancer-specific PRS quintile was associated with 28-34% decreased risk compared to the middle quintile. In contrast, the HR observed for quintiles 4 (female-lung: 0.95 [0.61-1.47]; male-lung: 1.14 [0.82-1.57]) and 5 (female-lung: 0.95 [0.61-1.47]) were not significantly different from that for the middle quintile.
Site-specific PRSs can stratify the risk of developing breast, prostate, and colorectal cancers in this East Asian population. Appropriate correction factors may be required to improve calibration.
This work is supported by the National Research Foundation Singapore (NRF-NRFF2017-02), PRECISION Health Research, Singapore (PRECISE) and the Agency for Science, Technology and Research (A*STAR). WP Koh was supported by National Medical Research Council, Singapore (NMRC/CSA/0055/2013). CC Khor was supported by National Research Foundation Singapore (NRF-NRFI2018-01). Rajkumar Dorajoo received a grant from the Agency for Science, Technology and Research Career Development Award (A*STAR CDA - 202D8090), and from Ministry of Health Healthy Longevity Catalyst Award (HLCA20Jan-0022).The Singapore Chinese Health Study was supported by grants from the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016) and the U.S. National Institutes of Health (NIH) (R01 CA144034 and UM1 CA182876).
Ho PJ
，Tan IB
，Chong DQ
，Khor CC
，Yuan JM
，Koh WP
，Dorajoo R
，Li J
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《eLife》
Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach.
Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.
Gao G
，Zhao F
，Ahearn TU
，Lunetta KL
，Troester MA
，Du Z
，Ogundiran TO
，Ojengbede O
，Blot W
，Nathanson KL
，Domchek SM
，Nemesure B
，Hennis A
，Ambs S
，McClellan J
，Nie M
，Bertrand K
，Zirpoli G
，Yao S
，Olshan AF
，Bensen JT
，Bandera EV
，Nyante S
，Conti DV
，Press MF
，Ingles SA
，John EM
，Bernstein L
，Hu JJ
，Deming-Halverson SL
，Chanock SJ
，Ziegler RG
，Rodriguez-Gil JL
，Sucheston-Campbell LE
，Sandler DP
，Taylor JA
，Kitahara CM
，O'Brien KM
，Bolla MK
，Dennis J
，Dunning AM
，Easton DF
，Michailidou K
，Pharoah PDP
，Wang Q
，Figueroa J
，Biritwum R
，Adjei E
，Wiafe S
，GBHS Study Team
，Ambrosone CB
，Zheng W
，Olopade OI
，García-Closas M
，Palmer JR
，Haiman CA
，Huo D
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《-》
Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.
Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
Mavaddat N
，Michailidou K
，Dennis J
，Lush M
，Fachal L
，Lee A
，Tyrer JP
，Chen TH
，Wang Q
，Bolla MK
，Yang X
，Adank MA
，Ahearn T
，Aittomäki K
，Allen J
，Andrulis IL
，Anton-Culver H
，Antonenkova NN
，Arndt V
，Aronson KJ
，Auer PL
，Auvinen P
，Barrdahl M
，Beane Freeman LE
，Beckmann MW
，Behrens S
，Benitez J
，Bermisheva M
，Bernstein L
，Blomqvist C
，Bogdanova NV
，Bojesen SE
，Bonanni B
，Børresen-Dale AL
，Brauch H
，Bremer M
，Brenner H
，Brentnall A
，Brock IW
，Brooks-Wilson A
，Brucker SY
，Brüning T
，Burwinkel B
，Campa D
，Carter BD
，Castelao JE
，Chanock SJ
，Chlebowski R
，Christiansen H
，Clarke CL
，Collée JM
，Cordina-Duverger E
，Cornelissen S
，Couch FJ
，Cox A
，Cross SS
，Czene K
，Daly MB
，Devilee P
，Dörk T
，Dos-Santos-Silva I
，Dumont M
，Durcan L
，Dwek M
，Eccles DM
，Ekici AB
，Eliassen AH
，Ellberg C
，Engel C
，Eriksson M
，Evans DG
，Fasching PA
，Figueroa J
，Fletcher O
，Flyger H
，Försti A
，Fritschi L
，Gabrielson M
，Gago-Dominguez M
，Gapstur SM
，García-Sáenz JA
，Gaudet MM
，Georgoulias V
，Giles GG
，Gilyazova IR
，Glendon G
，Goldberg MS
，Goldgar DE
，González-Neira A
，Grenaker Alnæs GI
，Grip M
，Gronwald J
，Grundy A
，Guénel P
，Haeberle L
，Hahnen E
，Haiman CA
，Håkansson N
，Hamann U
，Hankinson SE
，Harkness EF
，Hart SN
，He W
，Hein A
，Heyworth J
，Hillemanns P
，Hollestelle A
，Hooning MJ
，Hoover RN
，Hopper JL
，Howell A
，Huang G
，Humphreys K
，Hunter DJ
，Jakimovska M
，Jakubowska A
，Janni W
，John EM
，Johnson N
，Jones ME
，Jukkola-Vuorinen A
，Jung A
，Kaaks R
，Kaczmarek K
，Kataja V
，Keeman R
，Kerin MJ
，Khusnutdinova E
，Kiiski JI
，Knight JA
，Ko YD
，Kosma VM
，Koutros S
，Kristensen VN
，Krüger U
，Kühl T
，Lambrechts D
，Le Marchand L
，Lee E
，Lejbkowicz F
，Lilyquist J
，Lindblom A
，Lindström S
，Lissowska J
，Lo WY
，Loibl S
，Long J
，Lubiński J
，Lux MP
，MacInnis RJ
，Maishman T
，Makalic E
，Maleva Kostovska I
，Mannermaa A
，Manoukian S
，Margolin S
，Martens JWM
，Martinez ME
，Mavroudis D
，McLean C
，Meindl A
，Menon U
，Middha P
，Miller N
，Moreno F
，Mulligan AM
，Mulot C
，Muñoz-Garzon VM
，Neuhausen SL
，Nevanlinna H
，Neven P
，Newman WG
，Nielsen SF
，Nordestgaard BG
，Norman A
，Offit K
，Olson JE
，Olsson H
，Orr N
，Pankratz VS
，Park-Simon TW
，Perez JIA
，Pérez-Barrios C
，Peterlongo P
，Peto J
，Pinchev M
，Plaseska-Karanfilska D
，Polley EC
，Prentice R
，Presneau N
，Prokofyeva D
，Purrington K
，Pylkäs K
，Rack B
，Radice P
，Rau-Murthy R
，Rennert G
，Rennert HS
，Rhenius V
，Robson M
，Romero A
，Ruddy KJ
，Ruebner M
，Saloustros E
，Sandler DP
，Sawyer EJ
，Schmidt DF
，Schmutzler RK
，Schneeweiss A
，Schoemaker MJ
，Schumacher F
，Schürmann P
，Schwentner L
，Scott C
，Scott RJ
，Seynaeve C
，Shah M
，Sherman ME
，Shrubsole MJ
，Shu XO
，Slager S
，Smeets A
，Sohn C
，Soucy P
，Southey MC
，Spinelli JJ
，Stegmaier C
，Stone J
，Swerdlow AJ
，Tamimi RM
，Tapper WJ
，Taylor JA
，Terry MB
，Thöne K
，Tollenaar RAEM
，Tomlinson I
，Truong T
，Tzardi M
，Ulmer HU
，Untch M
，Vachon CM
，van Veen EM
，Vijai J
，Weinberg CR
，Wendt C
，Whittemore AS
，Wildiers H
，Willett W
，Winqvist R
，Wolk A
，Yang XR
，Yannoukakos D
，Zhang Y
，Zheng W
，Ziogas A
，ABCTB Investigators
，kConFab/AOCS Investigators
，NBCS Collaborators
，Dunning AM
，Thompson DJ
，Chenevix-Trench G
，Chang-Claude J
，Schmidt MK
，Hall P
，Milne RL
，Pharoah PDP
，Antoniou AC
，Chatterjee N
，Kraft P
，García-Closas M
，Simard J
，Easton DF
... -
《-》
Development and validation of genome-wide polygenic risk scores for predicting breast cancer incidence in Japanese females: a population-based case-cohort study.
This study aimed to develop an ancestry-specific polygenic risk scores (PRSs) for the prediction of breast cancer events in Japanese females and validate it in a longitudinal cohort study.
Using publicly available summary statistics of female breast cancer genome-wide association study (GWAS) of Japanese and European ancestries, we, respectively, developed 31 candidate genome-wide PRSs using pruning and thresholding (P + T) and LDpred methods with varying parameters. Among the candidate PRS models, the best model was selected using a case-cohort dataset (63 breast cancer cases and 2213 sub-cohorts of Japanese females during a median follow-up of 11.9 years) according to the maximal predictive ability by Harrell's C-statistics. The best-performing PRS for each derivation GWAS was evaluated in another independent case-cohort dataset (260 breast cancer cases and 7845 sub-cohorts of Japanese females during a median follow-up of 16.9 years).
For the best PRS model involving 46,861 single nucleotide polymorphisms (SNPs; P + T method with PT = 0.05 and R2 = 0.2) derived from Japanese-ancestry GWAS, the Harrell's C-statistic was 0.598 ± 0.018 in the evaluation dataset. The age-adjusted hazard ratio for breast cancer in females with the highest PRS quintile compared with those in the lowest PRS quintile was 2.47 (95% confidence intervals, 1.64-3.70). The PRS constructed using Japanese-ancestry GWAS demonstrated better predictive performance for breast cancer in Japanese females than that using European-ancestry GWAS (Harrell's C-statistics 0.598 versus 0.586).
This study developed a breast cancer PRS for Japanese females and demonstrated the usefulness of the PRS for breast cancer risk stratification.
Ohbe H
，Hachiya T
，Yamaji T
，Nakano S
，Miyamoto Y
，Sutoh Y
，Otsuka-Yamasaki Y
，Shimizu A
，Yasunaga H
，Sawada N
，Inoue M
，Tsugane S
，Iwasaki M
，Japan Public Health Center-based Prospective Study Group
... -
《-》
ResearchGate
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钛学术
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