Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

Daniel R Barnes; Jonathan P Tyrer; Joe Dennis; Goska Leslie; Manjeet K Bolla; Michael Lush; Amber M Aeilts; Kristiina Aittomäki; Nadine Andrieu; Irene L Andrulis; Hoda Anton-Culver; Adalgeir Arason; Banu K Arun; Judith Balmaña; Elisa V Bandera; Rosa B Barkardottir; Lieke P V Berger; Amy Berrington de Gonzalez; Pascaline Berthet; Katarzyna Bialkowska; Line Bjørge; Amie M Blanco; Marinus J Blok; Kristie A Bobolis; Natalia V Bogdanova; James D Brenton; Henriett Butz; Saundra S Buys; Maria A Caligo; Ian Campbell; Carmen Castillo; Kathleen B M Claes; Sarah V Colonna; Linda S Cook; Mary B Daly; Agnieszka Dansonka-Mieszkowska; Miguel de la Hoya; Anna deFazio; Allison DePersia; Yuan Chun Ding; Susan M Domchek; Thilo Dörk; Zakaria Einbeigi; Christoph Engel; D Gareth Evans; Lenka Foretova; Renée T Fortner; Florentia Fostira; GEMO Study Collaborators; EMBRACE Collaborators; KConFab Investigators

doi:10.1101/2024.02.29.24303243

Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

Daniel R Barnes^*, Jonathan P Tyrer, Joe Dennis, Goska Leslie, Manjeet K Bolla, Michael Lush, Amber M Aeilts, Kristiina Aittomäki, Nadine Andrieu, Irene L Andrulis, Hoda Anton-Culver, Adalgeir Arason, Banu K Arun, Judith Balmaña, Elisa V Bandera, Rosa B Barkardottir, Lieke P V Berger, Amy Berrington de Gonzalez, Pascaline Berthet, Katarzyna BialkowskaLine Bjørge, Amie M Blanco, Marinus J Blok, Kristie A Bobolis, Natalia V Bogdanova, James D Brenton, Henriett Butz, Saundra S Buys, Maria A Caligo, Ian Campbell, Carmen Castillo, Kathleen B M Claes, Sarah V Colonna, Linda S Cook, Mary B Daly, Agnieszka Dansonka-Mieszkowska, Miguel de la Hoya, Anna deFazio, Allison DePersia, Yuan Chun Ding, Susan M Domchek, Thilo Dörk, Zakaria Einbeigi, Christoph Engel, D Gareth Evans, Lenka Foretova, Renée T Fortner, Florentia Fostira, GEMO Study Collaborators, EMBRACE Collaborators, KConFab Investigators

^*Corresponding author for this work

Research output: Working paper / Preprint › Preprint

Abstract

BACKGROUND: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). METHODS: We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. RESULTS: Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10 ). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). CONCLUSIONS: This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.

Original language	English
Publisher	MedRxiv
DOIs	https://doi.org/10.1101/2024.02.29.24303243
Publication status	Published - 4 Mar 2024

Access to Document

10.1101/2024.02.29.24303243

Cite this

Barnes, D. R., Tyrer, J. P., Dennis, J., Leslie, G., Bolla, M. K., Lush, M., Aeilts, A. M., Aittomäki, K., Andrieu, N., Andrulis, I. L., Anton-Culver, H., Arason, A., Arun, B. K., Balmaña, J., Bandera, E. V., Barkardottir, R. B., Berger, L. P. V., de Gonzalez, A. B., Berthet, P., ... KConFab Investigators (2024). Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk. MedRxiv . https://doi.org/10.1101/2024.02.29.24303243

@techreport{99d2f17401cb4ba8b03b0faa2006d2d3,

title = "Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk",

abstract = "BACKGROUND: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). METHODS: We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. RESULTS: Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10 ). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). CONCLUSIONS: This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.",

author = "Barnes, {Daniel R} and Tyrer, {Jonathan P} and Joe Dennis and Goska Leslie and Bolla, {Manjeet K} and Michael Lush and Aeilts, {Amber M} and Kristiina Aittom{\"a}ki and Nadine Andrieu and Andrulis, {Irene L} and Hoda Anton-Culver and Adalgeir Arason and Arun, {Banu K} and Judith Balma{\~n}a and Bandera, {Elisa V} and Barkardottir, {Rosa B} and Berger, {Lieke P V} and {de Gonzalez}, {Amy Berrington} and Pascaline Berthet and Katarzyna Bialkowska and Line Bj{\o}rge and Blanco, {Amie M} and Blok, {Marinus J} and Bobolis, {Kristie A} and Bogdanova, {Natalia V} and Brenton, {James D} and Henriett Butz and Buys, {Saundra S} and Caligo, {Maria A} and Ian Campbell and Carmen Castillo and Claes, {Kathleen B M} and Colonna, {Sarah V} and Cook, {Linda S} and Daly, {Mary B} and Agnieszka Dansonka-Mieszkowska and {de la Hoya}, Miguel and Anna deFazio and Allison DePersia and Ding, {Yuan Chun} and Domchek, {Susan M} and Thilo D{\"o}rk and Zakaria Einbeigi and Christoph Engel and Evans, {D Gareth} and Lenka Foretova and Fortner, {Ren{\'e}e T} and Florentia Fostira and {GEMO Study Collaborators} and {EMBRACE Collaborators} and {KConFab Investigators}",

year = "2024",

month = mar,

day = "4",

doi = "10.1101/2024.02.29.24303243",

language = "English",

publisher = "MedRxiv ",

address = "United States",

type = "WorkingPaper",

institution = "MedRxiv ",

}

Barnes, DR, Tyrer, JP, Dennis, J, Leslie, G, Bolla, MK, Lush, M, Aeilts, AM, Aittomäki, K, Andrieu, N, Andrulis, IL, Anton-Culver, H, Arason, A, Arun, BK, Balmaña, J, Bandera, EV, Barkardottir, RB, Berger, LPV, de Gonzalez, AB, Berthet, P, Bialkowska, K, Bjørge, L, Blanco, AM, Blok, MJ, Bobolis, KA, Bogdanova, NV, Brenton, JD, Butz, H, Buys, SS, Caligo, MA, Campbell, I, Castillo, C, Claes, KBM, Colonna, SV, Cook, LS, Daly, MB, Dansonka-Mieszkowska, A, de la Hoya, M, deFazio, A, DePersia, A, Ding, YC, Domchek, SM, Dörk, T, Einbeigi, Z, Engel, C, Evans, DG, Foretova, L, Fortner, RT, Fostira, F, GEMO Study Collaborators, EMBRACE Collaborators & KConFab Investigators 2024 'Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk' MedRxiv . https://doi.org/10.1101/2024.02.29.24303243

TY - UNPB

T1 - Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

AU - Barnes, Daniel R

AU - Tyrer, Jonathan P

AU - Dennis, Joe

AU - Leslie, Goska

AU - Bolla, Manjeet K

AU - Lush, Michael

AU - Aeilts, Amber M

AU - Aittomäki, Kristiina

AU - Andrieu, Nadine

AU - Andrulis, Irene L

AU - Anton-Culver, Hoda

AU - Arason, Adalgeir

AU - Arun, Banu K

AU - Balmaña, Judith

AU - Bandera, Elisa V

AU - Barkardottir, Rosa B

AU - Berger, Lieke P V

AU - de Gonzalez, Amy Berrington

AU - Berthet, Pascaline

AU - Bialkowska, Katarzyna

AU - Bjørge, Line

AU - Blanco, Amie M

AU - Blok, Marinus J

AU - Bobolis, Kristie A

AU - Bogdanova, Natalia V

AU - Brenton, James D

AU - Butz, Henriett

AU - Buys, Saundra S

AU - Caligo, Maria A

AU - Campbell, Ian

AU - Castillo, Carmen

AU - Claes, Kathleen B M

AU - Colonna, Sarah V

AU - Cook, Linda S

AU - Daly, Mary B

AU - Dansonka-Mieszkowska, Agnieszka

AU - de la Hoya, Miguel

AU - deFazio, Anna

AU - DePersia, Allison

AU - Ding, Yuan Chun

AU - Domchek, Susan M

AU - Dörk, Thilo

AU - Einbeigi, Zakaria

AU - Engel, Christoph

AU - Evans, D Gareth

AU - Foretova, Lenka

AU - Fortner, Renée T

AU - Fostira, Florentia

AU - GEMO Study Collaborators

AU - EMBRACE Collaborators

AU - KConFab Investigators

PY - 2024/3/4

Y1 - 2024/3/4

N2 - BACKGROUND: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). METHODS: We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. RESULTS: Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10 ). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). CONCLUSIONS: This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.

AB - BACKGROUND: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). METHODS: We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. RESULTS: Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10 ). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). CONCLUSIONS: This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.

U2 - 10.1101/2024.02.29.24303243

DO - 10.1101/2024.02.29.24303243

M3 - Preprint

BT - Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

PB - MedRxiv

ER -

Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk

Abstract

Access to Document

Fingerprint

Cite this