Abstract 1314: Trans-ethnic HLA fine-mapping of the MHC region identified several independent variants influencing susceptibility to lung cancer
Bibliographic record
Abstract
Abstract Background: Genetic variants within the major histocompatibility complex (MHC) are associated with lung cancer. However, debate persists about the identity of the true causal variants, in part due to the broad linkage disequilibrium (LD) characteristic of the MHC and to the complexity and cost of complete HLA genotyping. Here, we assessed the role of the MHC in modulating lung cancer risk in Asians and Europeans using a broad set of HLA variants to detect the main alleles and the presence of independent effects elsewhere in this genomic region. Material and methods: Association between the HLA variants and risk of lung cancer was examined in two collections of samples of different ethnicity (18,686 cases / 15,190 controls and 2,324 cases / 1,646 controls of European and Asian ancestry, respectively). Using existing genome-wide SNP data from the lung cancer OncoArray study, we imputed and tested classical alleles and amino acid polymorphisms in HLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1, HLA-DRB1, HLA-DPA1 and HLA-DPB1, as well as 7,258 SNPs across the MHC. All the analyses were performed assuming an additive genetic model adjusted for sex and principal components as covariates. The study-wide significant threshold was p=6.03 x 10-6. Results: Conditional, haplotype and stratified analyses identified two independent HLA allele effects associated with lung cancer squamous cell carcinoma in Europeans. One is HLA-DQB1*06 that showed a significant protective effect (OR=0.85, 95%CI 0.80-0.90, p=3.05 x10-8). The other effect is attributed to the long ancestral 8.1 haplotype (OR=1.30, 95%CI 1.18-1.42, p=4.78 x10-8), which contains class I and class II HLA alleles (A*0101 - B*0801 - C*0701 - DRB1*0301 - DQB1*0201 - DQA1*0501). In addition, single-amino-acid polymorphisms in HLA-B (at positions 9, 156, 163 and 178) and HLA-DRB1 (at positions 26, 71 and 74) located in peptide-binding grooves, suggest these proteins as possible functional contributors within the haplotype. In Asians, we observed two independent HLA allele effects associated with lung adenocarcinoma : HLA-DQB1*0401 (OR=1.67, 95% CI 1.35-2.05, p=1.59 x10-6), and HLA-DRB1*0701(OR=1.62, 95% CI 1.31-2.01, p=5.48 x10-6) as well as an intronic SNP in HLA-A (rs2256919) (OR=0.75, 95% CI 0.67-0.83, p=1.75 x10-7). Conclusions: We established an association between HLA haplotype 8.1 and squamous lung cancer risk in Europeans. In contrast, in Asians we observed associations only with class II HLA alleles and risk of lung adenocarcinoma. We did not observed shared HLA alleles effects between populations. This ethnic heterogeneity in classical HLA allelic associations with lung cancer may be explained by allele frequency differences between populations and also different exposures that interact with HLA. Furthermore, our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC. Citation Format: Aida Ferreiro-Iglesias, Corina Lesseur, James McKay, Rayjean J. Hung, Christopher I. Amos, Paul Brennan, on behalf of OncoArray consortium. Trans-ethnic HLA fine-mapping of the MHC region identified several independent variants influencing susceptibility to lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1314. doi:10.1158/1538-7445.AM2017-1314
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".