Prevalence of BRAFV600 in glioma and use of BRAF Inhibitors in patients with BRAFV600 mutation-positive glioma: systematic review. Neuro-oncology, [noab247].
Background
The burden of chronic hepatitis B virus (HBV) varies across the European Union (EU) and European Economic Area (EEA).
Aim
We aimed to update the 2017 HBV prevalence estimates in EU/EEA countries and the United Kingdom for 2018 to 2021.
Methods
We undertook a systematic review, adding to HBV prevalence estimates from an existing (2005–2017) database. Databases were searched for original English-language research articles including HBV surface antigen prevalence estimates among the general population, pregnant women, first-time blood donors (FTB), men who have sex with men (MSM), migrants and people in prison. Country experts contributed grey literature data. Risk of bias was assessed using a quality assessment framework.
Findings
The update provided 147 new prevalence estimates across the region (updated total n = 579). Median HBV prevalence in the general population was 0.5% and the highest was 3.8% (Greece). Among FTB, the highest prevalence was 0.8% (Lithuania). Estimates among pregnant women were highest in Romania and Italy (5.1%). Among migrants, the highest estimate was 31.7% (Spain). Relative to 2017 estimates, median prevalence among pregnant women decreased by 0.5% (to 0.3%) and increased by 0.9% (to 5.8%) among migrants. Among MSM, the highest estimate was 3.4% (Croatia). Prevalence among people in prison was highest in Greece (8.3%) and the median prevalence increased by 0.6% (to 2.1%).
Conclusions
The HBV prevalence is low in the general population and confined to risk populations in most European countries with some exceptions. Screening and treatment should be targeted to people in prison and migrants.
AIMS
To use two-sample Mendelian Randomisation to prioritise novel genes for drug targeting in glioma risk using expression, protein and splicing quantitative trait loci (eQTLs, pQTLs and sQTLs, respectively).
METHOD
We used genetic variants from GWAS to compare the effects of eQTLs, pQTLs and sQTLs on genetic liability to glioma risk (n=12,496). eQTL data was retrieved from the MetaBrain study of five different brain tissues (n=108 to 2,970). pQTL data was retrieved from the BrainQTL study of dorsolateral prefrontal cortex tissue (n = 330), and sQTL data was retrieved from Genotype-Tissue Expression (GTEx) Project (v8) of 13 brain tissues (n=114 to 209). SNPs which were trans-QTLs (>1 Mb) due to risk of horizontal pleiotropy, and greater than GWAS significance (P > 5 × 10-8) were excluded. Instruments were constructed using independent SNPs (r2 < 0.001). Results underwent relevant sensitivity analysis; colocalisation and Steiger filtering.
RESULTS
We found 123 MR associations for 28 genes with genetically predicted altered expression, protein or splicing levels affected risk of glioma. These included genes recurrently associated with glioma risk such as TERT, RTEL1, CDKN2A/B and EGFR, and novel putative genes; BTN3A2, GALNT6, GMPPB and FAIM. Following sensitivity analyses, we found that 58 MR associations for 25 genes had robust evidence.
CONCLUSION
We identified four novel associations not previously found in GWAS; BTN3A2 (6p22.2), FAIM (3q22.3), GALNT6 (12q13.13) and GMPPB (3p21.31) are implicated in glioma risk and are also not located on a known glioma risk locus. Further analysis is required to identify the suitability of these genes for drug targeting in glioma.
Genetically predicted changes in molecular traits are associated with genetic liability to glioma risk. We sought to identify and provide evidence for the prioritisation of these traits using a combined two-sample Mendelian randomisation and colocalisation pipeline.We used genetic variants from genome-wide association studies (GWAS) to compare the effects of gene expression, protein abundance and splicing variation on genetic liability to glioma risk.We performed analysis of quantitative trait loci (QTL) (expression QTL [MetaBrain, n=4,119,012]; protein QTL [BrainQTL, n=786,632] and splicing QTL [GTEx, n=166,721]) derived from 15 different brain tissues and summary-level data from eight glioma GWAS (12,496 cases and 18,190 controls).We found robust evidence linking QTL for 25 genes in 15 loci with risk of glioma following relevant sensitivity analysis. We identified four novel genes putatively implicated in glioma risk: BTN3A2 (6p22.2), FAIM (3q22.3), GALNT6 (12q13.13) and GMPPB (3p21.31). Identification of these novel genes may improve understanding in pathogenic mechanisms underlying gliomagenesis and should be followed up in further studies, which may inform novel prevention studies following future clinical trials.
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