A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians

Abstract

Introduction: Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).

Methods: Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.

Results: With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828_C6orf10 and rs204999_PRRT1, OR_interaction = 1.17, p = 6.57 × 10^-13; rs3135369_BTNL2 and rs2858859_HLA-DQA1, OR_interaction = 1.17, p = 2.43 × 10^-13; rs2858859_HLA-DQA1 and rs9275572_HLA-DQA2, OR_interaction = 1.15, p = 2.84 × 10^-13; rs2853668_TERT and rs62329694_CLPTM1L, OR_interaction = 0.73, p = 2.70 × 10^-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828_C6orf10 and rs204999_PRRT1, OR_interaction = 1.13, p = 0.008; rs3135369_BTNL2 and rs2858859_HLA-DQA1, OR_interaction = 1.11, p = 5.23 × 10^-4; rs3135369_BTNL2 and rs9271300_HLA-DQA1, OR_interaction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.

Conclusions: Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.

Keywords: Cancer risk; GWAS; Gene-gene interaction; Genetic screening model; Lung cancer; Single nucleotide polymorphism.

Figure 1.

The workflow diagram of this study. We adopt a two-phase design in genome-wide G × G interaction study. In the discovery phase, a two-step strategy, Screening before Testing, was used for high-dimensionality reduction using European-ancestry participants from ILCCO-OncoArray and TRICL. In the validation phase, Bonferroni-corrected significant G × G interactions were further confirmed in the UK Biobank. Meanwhile, meta-analysis of ILCCO-OncoArray, TRICL, and UK Biobank and stratified analysis were performed to identify weak effect G × G signals. Trans-ethnic validation of G × G interactions was conducted using Asian participants from NJMU-GSA. An improved lung cancer screening model incorporating polygenetic risk score and G × G interaction score was also developed. eQTL, expression quantitative trait loci; ILCCO-OncoArray, International Lung Cancer Consortium OncoArray project; KEGG, Kyoto Encyclopedia of Genes and Genomes; LUAD, lung adenocarcinoma; LUSC, lung squamous carcinoma; NJMU-GSA, Nanjing Medical University-Global Screening Array; TRICL, Transdisciplinary Research in Cancer of the Lung.

Figure 2.

Forest plot of G × G interactions for (A) rs204999 × rs521828 and (B) rs2853668 × rs62329694 using the European-ancestry participants from ILCCO-OncoArray, TRICL, and UK Biobank. The three-dimensional G × G interaction signal map for association results of all epistatic pairs upstream and downstream of the identified G × G interaction using imputed data in (C) 6p21.32 and (D) 5p15.33 regions. The p values were derived from the logistic regresssion model adjusted for covariates and pooled by meta-analysis of ILCCO-OncoArray, TRICL, and UK Biobank. p values were plotted on a negative log₁₀-transformed scale. CI, confidence interval; ILCCO-OncoArray, International Lung Cancer Consortium OncoArray project; TRICL, Transdisciplinary Research in Cancer of the Lung.

Figure 3.

The comparison of G × G interaction association results and effect of allele frequency between Europeans and Asians. Star symbol (*) indicates that G × G interaction is significant in both Europeans and Asians. CI, confidence interval; EAF, effect allele frequency; LUAD, lung adenocarcinoma.

Figure 4.

Participants in the UK Biobank were divided into 10 equal groups according to the PRS and iPRS, respectively. HR and 95% CI of each group were derived from Cox proportional hazards model adjusted for covariates by setting the lowest group as reference for never (A) and ever smokers (B). Cumulative lung cancer incidence curves were illustrated for subjects at different overall risk score groups calculated from demographic variables (age, sex, and pack-years) and iPRS for never (C) and ever smokers (D). HR and 95% CI were derived from proportional hazards model adjusted for covariates by setting the lowest group as reference. The absolute lung cancer incidence rates were presented for subjects at different iPRS, pack-years, and age groups (E). CI, confidence interval; HR, hazard ratio; iPRS, interaction-empowered polygenetic risk score; PRS, polygenetic risk score; Ref, reference group.