Characterizing the Relationship between Expression Quantitative Trait Loci (eQTLs), DNA Methylation Quantitative Trait Loci (mQTLs), and Breast Cancer Risk Variants

Peh Joo Ho; Alexis Khng; Benita Kiat-Tee Tan; Chiea Chuen Khor; Ern Yu Tan; Geok Hoon Lim; Jian-Min Yuan; Su-Ming Tan; Xuling Chang; Veronique Kiak Mien Tan; Xueling Sim; Rajkumar Dorajoo; Woon-Puay Koh; Mikael Hartman; Jingmei Li

doi:10.3390/cancers16112072

Characterizing the Relationship between Expression Quantitative Trait Loci (eQTLs), DNA Methylation Quantitative Trait Loci (mQTLs), and Breast Cancer Risk Variants

Cancers (Basel). 2024 May 30;16(11):2072. doi: 10.3390/cancers16112072.

Authors

Peh Joo Ho^{1

2

3}, Alexis Khng¹, Benita Kiat-Tee Tan^{4

5

6}, Chiea Chuen Khor^{1

7}, Ern Yu Tan^{8

9

10}, Geok Hoon Lim¹¹, Jian-Min Yuan^{12

13}, Su-Ming Tan¹⁴, Xuling Chang^{15

16

17}, Veronique Kiak Mien Tan^{5

6}, Xueling Sim³, Rajkumar Dorajoo^{1

15}, Woon-Puay Koh^{18

19}, Mikael Hartman^{2

3

20}, Jingmei Li^{1

2}

Affiliations

¹ Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore 138672, Singapore.
² Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore.
³ Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117549, Singapore.
⁴ Department of General Surgery, Sengkang General Hospital, Singapore 544886, Singapore.
⁵ Department of Breast Surgery, Singapore General Hospital, Singapore 544886, Singapore.
⁶ Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, Singapore 168583, Singapore.
⁷ Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore.
⁸ Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore.
⁹ Lee Kong Chian School of Medicine, Nanyang Technology University, Singapore 639798, Singapore.
¹⁰ Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), 61 Biopolis Street, Singapore 138673, Singapore.
¹¹ KK Breast Department, KK Women's and Children's Hospital, Singapore 229899, Singapore.
¹² Cancer Epidemiology and Prevention Program, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA 15232, USA.
¹³ Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.
¹⁴ Division of Breast Surgery, Changi General Hospital, Singapore 529889, Singapore.
¹⁵ Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore.
¹⁶ Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore 119074, Singapore.
¹⁷ Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia.
¹⁸ Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117545, Singapore.
¹⁹ Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore 117609, Singapore.
²⁰ Department of Surgery, University Surgical Cluster, National University Hospital, Singapore 119074, Singapore.

Abstract

Purpose: To assess the association of a polygenic risk score (PRS) for functional genetic variants with the risk of developing breast cancer.

Methods: Summary data-based Mendelian randomization (SMR) and heterogeneity in dependent instruments (HEIDI) were used to identify breast cancer risk variants associated with gene expression and DNA methylation levels. A new SMR-based PRS was computed from the identified variants (functional PRS) and compared to an established 313-variant breast cancer PRS (GWAS PRS). The two scores were evaluated in 3560 breast cancer cases and 3383 non-cancer controls and also in a prospective study (n = 10,213) comprising 418 cases.

Results: We identified 149 variants showing pleiotropic association with breast cancer risk (eQTL_HEIDI > 0.05 = 9, mQTL_HEIDI > 0.05 = 165). The discriminatory ability of the functional PRS (AUC_continuous [95% CI]: 0.540 [0.526 to 0.553]) was found to be lower than that of the GWAS PRS (AUC_continuous [95% CI]: 0.609 [0.596 to 0.622]). Even when utilizing 457 distinct variants from both the functional and GWAS PRS, the combined discriminatory performance remained below that of the GWAS PRS (AUC_continuous, combined [95% CI]: 0.561 [0.548 to 0.575]). A binary high/low-risk classification based on the 80th centile PRS in controls revealed a 6% increase in cases using the GWAS PRS compared to the functional PRS. The functional PRS identified an additional 12% of high-risk cases but also led to a 13% increase in high-risk classification among controls. Similar findings were observed in the SCHS prospective cohort, where the GWAS PRS outperformed the functional PRS, and the highest-performing PRS, a combined model, did not significantly improve over the GWAS PRS.

Conclusions: While this study identified potentially functional variants associated with breast cancer risk, their inclusion did not substantially enhance the predictive accuracy of the GWAS PRS.

Keywords: KCNN4; SMR; breast cancer risk; eQTL; genetic risk score; mQTL; methylation.

Grants and funding

This work was supported by the Agency for Science, Technology and Research (A*STAR) and PRECISION Health Research, Singapore (PRECISE). W.-P.K. was supported by the National Medical Research Council, Singapore [CSA-SI (MOH-000434)]. R.D. received a grant from the Agency for Science, Technology and Research Career Development Award (A*STAR CDA—202D8090) and from the Ministry of Health Healthy Longevity Catalyst Award (HLCA20Jan-0022). The breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710), and The European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935). All studies and funders are listed in Michailidou et al. (Nature, 2017). SGBCC is funded by National Research Foundation Singapore [NRF-NRFF2017-02], NUS start-up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant [NMRC/CG/NCIS/2010, NMRC/CG/012/2013, CGAug16M005], Breast Cancer Prevention Programme (SSHSPH-Res-Prog), Asian Breast Cancer Research Fund, and the NMRC Clinician Scientist Award (SI Category) [NMRC/CSA-SI/0015/2017]. The Multi-Ethnic Phase 2 study is supported by the Singapore Ministry of Health, National University of Singapore (Population Health Metrics and Analytics funding) and National University Health System, Singapore. The Singapore Chinese Health Study was supported by the National Institutes of Health (NIH) of the United States (grants # R01 CA144034 and UM1 CA182876) and the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016).