English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

BACKGROUND Prior epidemiological studies in glioma have identified 25 germline risk variants, as well as risk associations with exposure to ionizing radiation (which increases risk) and history of allergies and aspirin use (which decrease risk). In this analysis we LDscore regression, which leverages single SNP associations and known patterns of linkage disequilibrium (LD) to estimate the genetic correlation between phenotypes, to confirm prior associations as well as attempt to identify novel phenotype associations for traits not previously assessed that may improve genetic prediction for glioma. METHODS Summary statistics for all glioma, GBM, and non-GBM were obtained from a prior meta-analysis conducted by Melin, et al. Summary statistics for 13 immune- and atopy-related traits were obtained from the prior case-control studies and the UK biobank. Data were filtered to include only SNPs with imputation INFO value &gt;0.7, and minor allele frequency &gt;0.01, excluding SNPs within the HLA region. Pairwise genetic correlation between these traits was generated using LDSC. Associations were considered significant at p&lt; 0.05 RESULTS Significant negative correlations were identified between glioma and ulcerative colitis (rg= -0.4039, p=4.91x10-10), celiac disease (rg= -0.2028, p=1.18x10-4), lupus (rg= -0.0956, p=0.0083), and multiple sclerosis (rg= -0.5755, p=4.46x10-9). These associations were generally consistent in both GBM and non-GBM. There was a significant correlation between both self-reported (rg= -0.102, p=0.0233) and doctor diagnosed (rg= -0.116, p=0.0305) hayfever/allergic rhinitis and GBM only. CONCLUSIONS This analysis demonstrates a genetic basis for previously identified protective effect of allergic rhinitis on GBM, and identifies novel associations between multiple auto-immune traits and glioma. Further studies are necessary in order to confirm these associations and identify the mechanism through which increased immune activity may lower risk of glioma.

GENE-11. LDSCORE REGRESSION IDENTIFIES NOVEL ASSOCIATIONS BETWEEN GLIOMA AND AUTO-IMMUNE CONDITIONS