A Meta-Analysis of Association Between Pesticides Exposure and Glioma Risk in Adults

Role of DNA methylation in the relationship between glioma risk factors and glioma incidence: a two-step Mendelian randomization study

Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region (HEATR3) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy.

Pesticide Residue Intake From Fruit and Vegetable Consumption and Risk of Glioma

We aimed to determine whether intake of pesticide residues from fruits and vegetables was associated with glioma. Within 3 prospective cohorts from 1998-2016-the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study-we computed multivariable-adjusted hazard ratios (MVHRs) and 95% confidence intervals (CI) for glioma by quintiles of intake of low- and high-pesticide-residue fruits and vegetables using Cox proportional hazards regression. Fruits and vegetables were categorized as high or low residue using a validated method based on pesticide surveillance data. We confirmed 275 glioma cases across 2,745,862 person-years. A significant association was observed between intake of high-residue fruits and vegetables and glioma in NHS (MVHR = 2.99, 95% CI: 1.38, 6.44 comparing highest with lowest quintile, P for trend = 0.02). This was not identified in NHSII (MVHR = 0.52, 95% CI: 0.19, 1.45, P for trend = 0.20) or Health Professionals Follow-up Study (MVHR = 1.01, 95% CI: 0.42, 2.45, P for trend = 0.39). No significant associations were observed by intake of low-residue fruits and vegetables; overall intake was not significantly associated with glioma in any cohort. We found no evidence for an inverse relationship of fruit and vegetable intake with glioma. Although limited in power, this study suggests a possible association between fruit-and-vegetable pesticide residue intake and risk of glioma that merits further study.

Brain Disorders and Chemical Pollutants: A Gap Junction Link?

The incidence of brain pathologies has increased during last decades. Better diagnosis (autism spectrum disorders) and longer life expectancy (Parkinson's disease, Alzheimer's disease) partly explain this increase, while emerging data suggest pollutant exposures as a possible but still underestimated cause of major brain disorders. Taking into account that the brain parenchyma is rich in gap junctions and that most pollutants inhibit their function; brain disorders might be the consequence of gap-junctional alterations due to long-term exposures to pollutants. In this article, this hypothesis is addressed through three complementary aspects: (1) the gap-junctional organization and connexin expression in brain parenchyma and their function; (2) the effect of major pollutants (pesticides, bisphenol A, phthalates, heavy metals, airborne particles, etc.) on gap-junctional and connexin functions; (3) a description of the major brain disorders categorized as neurodevelopmental (autism spectrum disorders, attention deficit hyperactivity disorders, epilepsy), neurobehavioral (migraines, major depressive disorders), neurodegenerative (Parkinson's and Alzheimer's diseases) and cancers (glioma), in which both connexin dysfunction and pollutant involvement have been described. Based on these different aspects, the possible involvement of pollutant-inhibited gap junctions in brain disorders is discussed for prenatal and postnatal exposures.

Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study

BACKGROUND

Whilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a causal relationship.

METHODS

We performed a systematic search of MEDLINE from inception to October 2018 to identify candidate risk factors and conducted a meta-analysis of two glioma genome-wide association studies (5739 cases and 5501 controls) to form our exposure and outcome datasets. MR analyses were performed using genetic variants to proxy for candidate risk factors. We investigated whether risk factors differed by subtype diagnosis (either glioblastoma (n = 3112) or non-glioblastoma (n = 2411)). MR estimates for each risk factor were determined using multiplicative random effects inverse-variance weighting (IVW). Sensitivity analyses investigated potential pleiotropy using MR-Egger regression, the weighted median estimator, and the mode-based estimator. To increase power, trait-specific polygenic risk scores were used to test the association of a genetically predicated increase in each risk factor with glioma onset.

RESULTS

Our systematic search identified 36 risk factors that could be proxied using genetic variants. Using MR, we found evidence that four genetically predicted traits increased risk of glioma, glioblastoma or non-glioblastoma: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption and liability to childhood extreme obesity (> 3 standard deviations from the mean). Two traits decreased risk of non-glioblastoma cancers: increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels. Our findings were similar across sensitivity analyses that made allowance for pleiotropy (genetic confounding).

CONCLUSIONS

Our comprehensive investigation provides evidence of a causal link between both genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, and LDLc and triglyceride levels, and glioma. The findings from our study warrant further research to uncover mechanisms that implicate these traits in glioma onset.

Diuron exposure and Akt overexpression promote glioma formation through DNA hypomethylation

BACKGROUND

Diuron is an environmental component listed as a likely human carcinogen. Several other studies report that diuron can be oncogenic for bladder, urothelial, skin, and mammary cells. No study mentions the putative effect of diuron on the glioma occurrence.

OBJECTIVES

We here wanted to investigate the effects of diuron exposure on the glioma occurrence while wishing to incriminate a putative implication of DNA methylation modulation in this process.

METHODS

In in vivo model of glioma, diuron exposure was firstly compared or combined with oncogenic overexpressions already known to promote gliomagenesis. ELISA quantifying the 5-methylcytosine level on DNA was performed to examine the global DNA methylation level. Quantitative real-time polymerase chain reaction and proximity ligation in situ assay were performed to identify the molecular causes of the diuron-induced changes of DNA methylation. The signatures diuron-induced changes of DNA methylation were analyzed in a cohort of 23 GBM patients.

RESULTS

Diuron exposure is not sufficient to promote glioma, such as the oncogenic overexpression of Akt or Ras. However, the combination of diuron exposure and Akt overexpression promotes glioma. We observed that the diuron/Akt-induced glioma is characterized by three phenotypic signatures characterizing cancer cells: a global DNA hypomethylation, a loss of sensitivity to cell death induction, and a gain of signals of immune escape. Our data associated these phenotypes with three aberrant DNA methylation signatures: the LLT1, PD-L1, and Bcl-w hypomethylations. Strikingly, we observed that these three concomitant hypomethylations were only observed in GBM patients having a potential exposure to diuron via their professional activity.

CONCLUSIONS

As single player, diuron is not an oncogenic of glioma, but it can participate to the glioma formation in association with other events (also devoid of oncogenic property as single player) such as Akt overexpression.

Genetic and molecular epidemiology of adult diffuse glioma

The WHO 2007 glioma classification system (based primarily on tumour histology) resulted in considerable interobserver variability and substantial variation in patient survival within grades. Furthermore, few risk factors for glioma were known. Discoveries over the past decade have deepened our understanding of the molecular alterations underlying glioma and have led to the identification of numerous genetic risk factors. The advances in molecular characterization of glioma have reframed our understanding of its biology and led to the development of a new classification system for glioma. The WHO 2016 classification system comprises five glioma subtypes, categorized by both tumour morphology and molecular genetic information, which led to reduced misclassification and improved consistency of outcomes within glioma subtypes. To date, 25 risk loci for glioma have been identified and several rare inherited mutations that might cause glioma in some families have been discovered. This Review focuses on the two dominant trends in glioma science: the characterization of diagnostic and prognostic tumour markers and the identification of genetic and other risk factors. An overview of the many challenges still facing glioma researchers is also included.

Use of Mendelian andomization for dentifying isk actors for rain umors

Gliomas are a group of primary brain tumors, the most common and aggressive subtype of which is glioblastoma. Glioblastoma has a median survival of just 15 months after diagnosis. Only previous exposure to ionizing radiation and particular inherited genetic syndromes are accepted risk factors for glioma; the vast majority of cases are thought to occur spontaneously. Previous observational studies have described associations between several risk factors and glioma, but studies are often conflicting and whether these associations reflect true casual relationships is unclear because observational studies may be susceptible to confounding, measurement error and reverse causation. Mendelian randomization (MR) is a form of instrumental variable analysis that can be used to provide supporting evidence for causal relationships between exposures (e.g., risk factors) and outcomes (e.g., disease onset). MR utilizes genetic variants, such as single nucleotide polymorphisms (SNPs), that are robustly associated with an exposure to determine whether there is a causal effect of the exposure on the outcome. MR is less susceptible to confounding, reverse causation and measurement errors as it is based on the random inheritance during conception of genetic variants that can be relatively accurately measured. In previous studies, MR has implicated a genetically predicted increase in telomere length with an increased risk of glioma, and found little evidence that obesity related factors, vitamin D or atopy are causal in glioma risk. In this review, we describe MR and its potential use to discover and validate novel risk factors, mechanistic factors, and therapeutic targets in glioma.

Cigarette smoking and risk of adult glioma: a meta-analysis of 24 observational studies involving more than 2.3 million individuals

Background

Cigarette smoking has been shown to be a risk factor for adult glioma by some but not all studies. We conducted a meta-analysis to systematically assess the potential association.

Methods

PubMed and EMBASE were searched from the date of their inception to October 1, 2015, to identify relevant articles. Reference lists from these articles were reviewed to identify additional studies. Both cohort and case–control studies were included. Fixed-effects models were used to calculate the overall relative risk (RR) with corresponding 95% confidence intervals (CIs).

Results

The final analysis included 24 studies (seven cohort and 17 case–control studies), involving more than 2.3 million individuals. The combined RR was 1.04 (95% CI: 1.00, 1.09; P=0.073) for ever-smokers, 0.97 (95% CI: 0.88, 1.07; P=0.574) for current-smokers, and 1.07 (95% CI: 0.98, 1.16; P=0.130) for past smokers, with little evidence of heterogeneity. Omission of any single study from the analysis had little effect on the result. No evidence of publication bias was found. A small but statistically significant increase was found in past smokers in females (RR: 1.13, 95% CI: 1.00, 1.28; P=0.046) but not in males.

Conclusion

In general, there was no association between cigarette smoking and adult glioma. The small but statistically significant association in females requires further investigation.