Genome‐wide exploration of genetic interactions for bladder cancer risk

Author:

Yu Evan Yi‐Wen123ORCID,Tang Qiu‐Yi4,Chen Ya‐Ting12,Zhang Yan‐Xi12,Dai Ya‐Nan3,Wu Yu‐Xuan12,Li Wen‐Chao5,Mehrkanoon Siamak6,Wang Shi‐Zhi7,Zeegers Maurice P.3,Wesselius Anke3ORCID

Affiliation:

1. Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, School of Public Health Southeast University Nanjing China

2. Department of Epidemiology & Biostatistics, School of Public Health Southeast University Nanjing China

3. Department of Epidemiology, CAPHRI Care and Public Health Research Institute, School of Nutrition and Translational Research in Metabolism Maastricht University Maastricht the Netherlands

4. Medical School of Southeast University Nanjing China

5. Department of Urology Affiliated Zhongda Hospital of Southeast University Nanjing China

6. Information and Computing Sciences Utrecht University Utrecht Netherlands

7. Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health Southeast University Nanjing China

Abstract

AbstractAlthough GWASs have been conducted to investigate genetic variation of bladder tumorigenesis, little is known about genetic interactions that may influence bladder cancer (BC) risk. By leveraging large‐scale participants from UK Biobank, we established a discovery database with 4000 Caucasian participants (2000 cases vs 2000 non‐cases), a database with 1648 Caucasian participants (824 cases vs 824 non‐cases) and 856 non‐Caucasian participants (428 cases vs 428 non‐cases) as validation. We then performed a genome‐wide SNP‐SNP interaction investigation related to BC risk based a machine learning approach (ie, GenEpi). Moreover, we used the selected interactions to build a BC screening model with an integrated interaction‐empowered polygenic risk score (iPRS) based on Cox proportional hazard model. With Bonferroni correction, we identified 10 statistically significant pairs of SNPs, which located in 17 chromosomes. Of these, four SNP‐SNP interactions were found to be positively associated with BC risk among Caucasian participants (ORs 1.57‐2.03), while six SNP‐SNP interactions showed negatively associated with BC risk (ORs 0.54‐0.65). Only four of the SNP‐SNP interactions were consistently identified in non‐Caucasian participants located in ST7LADSS2, FHITCHDH, LARP4BLHPP and RBFOX3MPRIP. In addition, the iPRS showed a HR of 1.81 (95% CI: 1.46‐2.09) compared the highest tertile to the lowest tertile, with an enhanced AUC (0.91; 95% CI:0.85‐0.97) than PRS (AUC: 0.86; 95% CI:0.76‐0.95; PDeLong test = 2.2 × 10−4). In summary, this study identified several important SNP‐SNP interactions for BC risk, and developed an iPRS model for BC screening, which may help to identify the people at high‐risk state of BC before early manifestation.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

Cancer Research,Oncology

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