Study designs may influence results: the problems with questionnaire-based case-control studies on the epidemiology of glioma

AllergoOncology: Biomarkers and refined classification for research in the allergy and glioma nexus-A joint EAACI-EANO position paper

Epidemiological studies have explored the relationship between allergic diseases and cancer risk or prognosis in AllergoOncology. Some studies suggest an inverse association, but uncertainties remain, including in IgE-mediated diseases and glioma. Allergic disease stems from a Th2-biased immune response to allergens in predisposed atopic individuals. Allergic disorders vary in phenotype, genotype and endotype, affecting their pathophysiology. Beyond clinical manifestation and commonly used clinical markers, there is ongoing research to identify novel biomarkers for allergy diagnosis, monitoring, severity assessment and treatment. Gliomas, the most common and diverse brain tumours, have in parallel undergone changes in classification over time, with specific molecular biomarkers defining glioma subtypes. Gliomas exhibit a complex tumour-immune interphase and distinct immune microenvironment features. Immunotherapy and targeted therapy hold promise for primary brain tumour treatment, but require more specific and effective approaches. Animal studies indicate allergic airway inflammation may delay glioma progression. This collaborative European Academy of Allergy and Clinical Immunology (EAACI) and European Association of Neuro-Oncology (EANO) Position Paper summarizes recent advances and emerging biomarkers for refined allergy and adult-type diffuse glioma classification to inform future epidemiological and clinical studies. Future research is needed to enhance our understanding of immune-glioma interactions to ultimately improve patient prognosis and survival.

Time trends in mobile phone use and glioma incidence among males in the Nordic Countries, 1979-2016

INTRODUCTION

In the Nordic countries, the use of mobile phones increased sharply in the mid-1990s especially among middle-aged men. We investigated time trends in glioma incidence rates (IR) with the perspective to inform about the plausibility of brain tumour risks from mobile phone use reported in some case-control studies.

METHODS

We analysed IR of glioma in Denmark, Finland, Norway, and Sweden among men aged 40-69 years, using data from national cancer registries and population statistics during 1979-2016, using log-linear joinpoint analysis. Information on regular mobile phone use and amount of call-time was obtained from major studies of mobile phones in these countries. We compared annual observed incidence with that expected under various risk scenarios to assess which of the reported effect sizes are compatible with the observed IR. The expected numbers of cases were computed accounting for an impact of other factors besides mobile phone use, such as improved cancer registration.

RESULTS

Based on 18,232 glioma cases, IR increased slightly but steadily with a change of 0.1% (95 %CI 0.0%; 0.3%) per year during 1979-2016 among 40-59-year-old men and for ages 60-69, by 0.6 % (95 %CI 0.4; 0.9) annually. The observed IR trends among men aged 40-59 years were incompatible with risk ratios (RR) 1.08 or higher with a 10-year lag, RR ≥ 1.2 with 15-year lag and RR ≥ 1.5 with 20-year lag. For the age group 60-69 years, corresponding effect sizes RR ≥ 1.4, ≥2 and ≥ 2.5 could be rejected for lag times 10, 15 and 20 years.

DISCUSSION

This study confirms and reinforces the conclusions that no changes in glioma incidence in the Nordic countries have occurred that are consistent with a substantial risk attributable to mobile phone use. This particularly applies to virtually all reported risk increases reported by previous case-control studies with positive findings.

Association of a novel antisense lncRNA TP73-AS1 polymorphisms and expression with colorectal cancer susceptibility and prognosis

BACKGROUND

TP73-AS1 is a novel antisense long noncoding RNA and plays an important role in cell proliferation and cancer development. However, the link between TP73-AS1 and colorectal cancer (CRC) has not yet been reported.

OBJECTIVE

To explore the association of genetic variants in TP73-AS1 and its expression with CRC susceptibility and prognosis.

METHODS

A case-control study (including 507 CRC cases and 503 controls) and bioinformatics analysis were conducted.

RESULTS

rs9800 polymorphism was significantly related to higher risk in CRC [adjusted odds ratio (AOR) = 1.33, 95% confidence interval (CI) = 1.02-1.75, P = 0.034 in heterozygote codominant model]. There was no difference between TP73-AS1 polymorphisms and different tumor node metastasis (TNM) stages in the adjusted model. Moreover, TP73-AS1 expression level was positively related to different TNM stages. After adjusted for age, gender and TNM, higher TP73-AS1 expression levels were related to shorter recurrence-free survival time [hazard ratio (HR) = 1.66, 95% CI = 1.02-2.71, P = 0.043].

CONCLUSION

TP73-AS1 polymorphisms and expression may be associated with susceptibility and prognosis of CRC.

Partitioned glioma heritability shows subtype-specific enrichment in immune cells

BACKGROUND

Epidemiological studies of adult glioma have identified genetic syndromes and 25 heritable risk loci that modify individual risk for glioma, as well increased risk in association with exposure to ionizing radiation and decreased risk in association with allergies. In this analysis, we assess whether there is a shared genome-wide genetic architecture between glioma and atopic/autoimmune diseases.

METHODS

Using summary statistics from a glioma genome-wide association studies (GWAS) meta-analysis, we identified significant enrichment for risk variants associated with gene expression changes in immune cell populations. We also estimated genetic correlations between glioma and autoimmune, atopic, and hematologic traits using linkage disequilibrium score regression (LDSC), which leverages genome-wide single-nucleotide polymorphism (SNP) associations and patterns of linkage disequilibrium.

RESULTS

Nominally significant negative correlations were observed for glioblastoma (GB) and primary biliary cirrhosis (rg = -0.26, P = .0228), and for non-GB gliomas and celiac disease (rg = -0.32, P = .0109). Our analyses implicate dendritic cells (GB pHM = 0.0306 and non-GB pHM = 0.0186) in mediating both GB and non-GB genetic predisposition, with GB-specific associations identified in natural killer (NK) cells (pHM = 0.0201) and stem cells (pHM = 0.0265).

CONCLUSIONS

This analysis identifies putative new associations between glioma and autoimmune conditions with genomic architecture that is inversely correlated with that of glioma and that T cells, NK cells, and myeloid cells are involved in mediating glioma predisposition. This provides further evidence that increased activation of the acquired immune system may modify individual susceptibility to glioma.

Lack of association between modifiable exposures and glioma risk: a Mendelian randomization analysis

Background

The etiological basis of glioma is poorly understood. We have used genetic markers in a Mendelian randomization (MR) framework to examine if lifestyle, cardiometabolic, and inflammatory factors influence the risk of glioma. This methodology reduces bias from confounding and is not affected by reverse causation.

Methods

We identified genetic instruments for 37 potentially modifiable risk factors and evaluated their association with glioma risk using data from a genome-wide association study of 12 488 glioma patients and 18 169 controls. We used the estimated odds ratio of glioma associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures:

Lifestyle and dietary factors—height, plasma insulin-like growth factor 1, blood carnitine, blood methionine, blood selenium, blood zinc, circulating adiponectin, circulating carotenoids, iron status, serum calcium, vitamins (A1, B12, B6, E, and 25-hydroxyvitamin D), fatty acid levels (monounsaturated, omega-3, and omega-6) and circulating fetuin-A;

Cardiometabolic factors—birth weight, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, total triglycerides, basal metabolic rate, body fat percentage, body mass index, fasting glucose, fasting proinsulin, glycated hemoglobin levels, diastolic and systolic blood pressure, waist circumference, waist-to-hip ratio; and

Inflammatory factors— C-reactive protein, plasma interleukin-6 receptor subunit alpha and serum immunoglobulin E.

Results

After correction for the testing of multiple potential risk factors and excluding associations driven by one single nucleotide polymorphism, no significant association with glioma risk was observed (ie, P_Corrected > 0.05).

Conclusions

This study did not provide evidence supporting any of the 37 factors examined as having a significant influence on glioma risk.

Searching for causal relationships of glioma: a phenome-wide Mendelian randomisation study

BACKGROUND

The aetiology of glioma is poorly understood. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to search for glioma risk factors.

METHODS

We performed an MR-PheWAS analysing 316 phenotypes, proxied by 8387 genetic variants, and summary genetic data from a GWAS of 12,488 glioma cases and 18,169 controls. Causal effects were estimated under a random-effects inverse-variance-weighted (IVW-RE) model, with robust adjusted profile score (MR-RAPS), weighted median and mode-based estimates computed to assess the robustness of findings. Odds ratios per one standard deviation increase in each phenotype were calculated for all glioma, glioblastoma (GBM) and non-GBM tumours.

RESULTS

No significant associations (P < 1.58 × 10-4) were observed between phenotypes and glioma under the IVW-RE model. Suggestive associations (1.58 × 10-4 < P < 0.05) were observed between leukocyte telomere length (LTL) with all glioma (ORSD = 3.91, P = 9.24 × 10-3) and GBM (ORSD = 4.86, P = 3.23 × 10-2), but the association was primarily driven by the TERT variant rs2736100. Serum low-density lipoprotein cholesterol and plasma HbA1C showed suggestive associations with glioma (ORSD = 1.11, P = 1.39 × 10-2 and ORSD = 1.28, P = 1.73 × 10-2, respectively), both associations being reliant on single genetic variants.

CONCLUSIONS

Our study provides further insight into the aetiological basis of glioma for which published data have been mixed.

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.

Risk factors for childhood and adult primary brain tumors

Primary brain tumors account for ~1% of new cancer cases and ~2% of cancer deaths in the United States; however, they are the most commonly occurring solid tumors in children. These tumors are very heterogeneous and can be broadly classified into malignant and benign (or non-malignant), and specific histologies vary in frequency by age, sex, and race/ethnicity. Epidemiological studies have explored numerous potential risk factors, and thus far the only validated associations for brain tumors are ionizing radiation (which increases risk in both adults and children) and history of allergies (which decreases risk in adults). Studies of genetic risk factors have identified 32 germline variants associated with increased risk for these tumors in adults (25 in glioma, 2 in meningioma, 3 in pituitary adenoma, and 2 in primary CNS lymphoma), and further studies are currently under way for other histologic subtypes, as well as for various childhood brain tumors. While identifying risk factors for these tumors is difficult due to their rarity, many existing datasets can be leveraged for future discoveries in multi-institutional collaborations. Many institutions are continuing to develop large clinical databases including pre-diagnostic risk factor data, and developments in molecular characterization of tumor subtypes continue to allow for investigation of more refined phenotypes. Key Point 1. Brain tumors are a heterogeneous group of tumors that vary significantly in incidence by age, sex, and race/ethnicity.2. The only well-validated risk factors for brain tumors are ionizing radiation (which increases risk in adults and children) and history of allergies (which decreases risk).3. Genome-wide association studies have identified 32 histology-specific inherited genetic variants associated with increased risk of these tumors.

Epidemiology of Brain Tumors

Incidence, prevalence, and survival for brain tumors varies by histologic type, age at diagnosis, sex, and race/ethnicity. Significant progress has been made in identifying potential risk factors for brain tumors, although more research is warranted. The strongest risk factors that have been identified thus far include allergies/atopic disease, ionizing radiation, and heritable genetic factors. Further analysis of large, multicenter, epidemiologic studies, as well as well annotated omic datasets (including genomic, epigenomic, transcriptomic, proteomic, or metabolomics data) can potentially lead to further understanding of the relationship between gene and environment in the process of brain tumor development.

Does stress increase risk of breast cancer? A 15-year prospective study

OBJECTIVE

The possible impact of stress on cancer incidence remains controversial. We prospectively evaluated associations between life event stressors, social support, personality characteristics (optimism, anger control, antiemotionality), and risk of developing primary breast cancer (BCa), in women at increased familial risk of BCa.

METHODS

A prospective cohort, repeated measures design was used. Recruitment was through the Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer, which collects genetic, epidemiological, and clinical data from Australasian families with multiple BCa cases. Acute and chronic stressors for the prior 3 years and psychosocial, clinical, and epidemiological variables were measured at cohort entry and at 3-yearly intervals. Cox proportional hazard regression analysis controlling for BCa risk factors and familial clustering was undertaken. The primary outcome was histopathologically confirmed BCa (invasive or ductal carcinoma in situ, including occult cases diagnosed during risk-reducing mastectomy).

RESULTS

Of 3595 consecutive women invited to participate, 3054 (85.0%) consented. Of these, 2739 (89.7%) from 990 families (range 1-16 per family) completed at least 1 assessment point. During the study, 103 women were diagnosed with BCa. No stressor or psychosocial variable or interaction between them was significantly associated with BCa in unadjusted or adjusted models (total acute stressors HR = 1.03 [0.99-1.08], P = .19; total chronic stressors HR = 1.0 [0.90-1.11], P = .98).

CONCLUSIONS

This study did not demonstrate an association between acute and chronic stressors, social support, optimism, antiemotionality or anger control, and BCa risk. Women should focus on proven methods of BCa risk reduction.

Impact of atopy on risk of glioma: a Mendelian randomisation study

BACKGROUND

An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations.

METHODS

Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis.

RESULTS

Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194).

CONCLUSIONS

Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.