The immunogenetics of viral antigen response is associated with subtype-specific glioma risk and survival

Affiliations

¹ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA. Electronic address: geno.guerra@ucsf.edu.
² Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
³ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
⁴ Department of Pediatrics, University of California, San Francisco, Oakland, CA, USA.
⁵ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
⁶ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA; Institute of Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
⁷ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, USA.
⁸ Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
⁹ Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
¹⁰ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Institute of Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
¹¹ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, USA. Electronic address: stephen.francis@ucsf.edu.

PMID: 35550063
PMCID: PMC9247888
DOI: 10.1016/j.ajhg.2022.04.011

The immunogenetics of viral antigen response is associated with subtype-specific glioma risk and survival

Geno Guerra et al. Am J Hum Genet. 2022.

. 2022 Jun 2;109(6):1105-1116.

doi: 10.1016/j.ajhg.2022.04.011. Epub 2022 May 11.

Authors

Affiliations

¹ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA. Electronic address: geno.guerra@ucsf.edu.
² Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
³ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
⁴ Department of Pediatrics, University of California, San Francisco, Oakland, CA, USA.
⁵ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
⁶ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA; Institute of Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
⁷ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, USA.
⁸ Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
⁹ Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
¹⁰ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Institute of Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
¹¹ Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, USA. Electronic address: stephen.francis@ucsf.edu.

PMID: 35550063
PMCID: PMC9247888
DOI: 10.1016/j.ajhg.2022.04.011

Abstract

Glioma is a highly fatal cancer with prognostically significant molecular subtypes and few known risk factors. Multiple studies have implicated infections in glioma susceptibility, but evidence remains inconsistent. Genetic variants in the human leukocyte antigen (HLA) region modulate host response to infection and have been linked to glioma risk. In this study, we leveraged genetic predictors of antibody response to 12 viral antigens to investigate the relationship with glioma risk and survival. Genetic reactivity scores (GRSs) for each antigen were derived from genome-wide-significant (p < 5 × 10^-8) variants associated with immunoglobulin G antibody response in the UK Biobank cohort. We conducted parallel analyses of glioma risk and survival for each GRS and HLA alleles imputed at two-field resolution by using data from 3,418 glioma-affected individuals subtyped by somatic mutations and 8,156 controls. Genetic reactivity scores to Epstein-Barr virus (EBV) ZEBRA and EBNA antigens and Merkel cell polyomavirus (MCV) VP1 antigen were associated with glioma risk and survival (Bonferroni-corrected p < 0.01). GRS_ZEBRA and GRS_MCV were associated in opposite directions with risk of IDH wild-type gliomas (OR_ZEBRA = 0.91, p = 0.0099/OR_MCV = 1.11, p = 0.0054). GRS_EBNA was associated with both increased risk for IDH mutated gliomas (OR = 1.09, p = 0.040) and improved survival (HR = 0.86, p = 0.010). HLA-DQA1^∗03:01 was significantly associated with decreased risk of glioma overall (OR = 0.85, p = 3.96 × 10^-4) after multiple testing adjustment. This systematic investigation of the role of genetic determinants of viral antigen reactivity in glioma risk and survival provides insight into complex immunogenomic mechanisms of glioma pathogenesis. These results may inform applications of antiviral-based therapies in glioma treatment.

Keywords: Epstein-Barr virus; Merkel cell polyomavirus; glioma; human leukocyte antigen; polygenic risk score.

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Conflict of interest statement

Declaration of interests The authors declare no competing interests.

Figures

**Figure 1**
Summary of data processing and analysis Our analysis consisted of three glioma case-control datasets. The first dataset (purple) included 786 glioma cases from The Cancer Genome Atlas (TCGA) genotyped on the Affymetrix 6.0 array and cancer-free controls assembled from two Wellcome Trust Case Control Consortium (WTCCC) studies genotyped with the Affymetrix 6.0 array: 2,917 controls from the 1958 British Birth cohort and 2,794 controls from the UK Blood Service control group. The second dataset (yellow) included 659 cases and 586 controls from the University of California, San Francisco (UCSF) Adult Glioma Study (AGS) genotyped on the Illumina HumanHap370duo panel. The third set (blue) included 1,973 cases from the Mayo Clinic and UCSF AGS and 1,859 controls from the Glioma International Case-Control Study (GICC) who were genotyped on the Illumina OncoArray, as previously described.^,, , , The three resulting case-control datasets were processed through quality controls as described in the main text and imputed with the TOPMed imputation server. SNP2HLA was used to impute HLA alleles from SNP data. Risk and survival analyses were performed separately on each study's imputed HLA alleles, on multiple glioma molecular subtypes, and a fixed-effects meta-analysis was performed to aggregate results. Separately, genetic reactivity scores to five viral antigens were created with previously published GWAS data. For cases and controls across the three studies, a genetic reactivity score (GRS) for antibody response to each of the five antigens was calculated for each individual with the available sequencing data. Risk and survival analyses were performed separately on each study with each GRS as a predictor, with results aggregated via a fixed effects inverse-variance-weighted meta-analysis for each subset of glioma patients and controls based on molecular subtype.

**Figure 2**
GRS correlations within the UCSF-Mayo cases and controls Pearson correlations between genetically predicted antigen responses (via GRS) as computed in the UCSF-Mayo glioma cases and controls. Values were printed in each block if and only if the associated correlation test p value was less than 0.01.

**Figure 3**
Significant GRS-glioma subtype risk association meta-analysis forest plots Forest plot meta-analysis results of GRS-glioma risk associations that were at least nominally statistically significant (p < 0.05). Response to antigens EBV ZEBRA, MCV, and EBV EBNA had associations that reached this threshold. Results are reported as odds ratios along with 95% confidence intervals. Briefly, each header indicates the studied viral antigen GRS, within are its association with molecular glioma subtypes reported with p < 0.05 and the 95% confidence interval of each study-specific effect. The diamond visualizes the 95% confidence interval for the fixed effect (FE) meta-analysis across all three studies. Each meta-analysis was tested for between-study heterogeneity (Q statistic), and p < 0.05 indicates evidence of study-specific associations.

**Figure 4**
Nominal GRS-glioma subtype survival association meta-analysis forest plots Forest plot meta-analysis results of GRS-glioma survival associations that were at least nominally statistically significant (p < 0.05). Genetically inferred response to antigens EBV ZEBRA, MCV, and EBV EBNA had associations that reached this threshold. Results are reported as hazard ratios along with 95% confidence intervals. Briefly, each header indicates the studied viral antigen GRS, within are its association with molecular glioma subtypes reported with p < 0.05 and the 95% confidence interval of each study-specific effect. The diamond visualizes the 95% confidence interval for the fixed effect (FE) meta-analysis across included studies. Studies that had an insufficient number of cases/events in a subtype were not included in the meta-analysis. Each meta-analysis (where more than one study was included) was tested for between-study heterogeneity (Q statistic), and p < 0.05 indicates evidence of study-specific associations.

**Figure 5**
Kaplan Meier curves for significant GRS_EBNA-glioma molecular subtype associations Kaplan-Meier curves for subtypes where GRS_EBNA was nominally associated with subtype-specific glioma survival differences (p < 0.05 via Cox regression). The second and third plots are distinct partitions of the IDH-mutated subgroup. To visualize, unnormalized GRSs across the included studies were binned on the basis of the case-specific 80^th percentile score in the UCSF-Mayo dataset. p values included on each plot are results of a log-rank test for difference between the two curves. Below each set of curves provides the number of cases surviving beyond that time point for each of the two GRS groups. In all cases, the glioma cases with higher GRS for EBV EBNA had visually improved survival outcomes compared to the bottom 80%.

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The immunogenetics of viral antigen response is associated with subtype-specific glioma risk and survival

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The immunogenetics of viral antigen response is associated with subtype-specific glioma risk and survival

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