Smoking and Glioma Risk: Evidence From a Meta-Analysis of 25 Observational Studies

Analysis and prediction of central nervous system tumor burden in China during 1990-2030

Central nervous system (CNS) tumors, due to their unique locations, pose a serious threat to human health and present challenges to modern medicine. These tumors exhibit notable epidemiological characteristics across various ethnicities, regions, and age groups. This study investigated the trend of disease burden of CNS tumors in China from 1990-2019 and predicted the incidence and death rate from 2020-2030. Employing data from the 2019 Global Burden of Disease (GBD) database, we utilized key indicators to scrutinize the disease burden associated with CNS tumors in China. The analysis employed the Joinpoint model to track the trend in disease burden, calculating both the annual percentage change (APC) and average annual percentage change (AAPC). Additionally, the Matlab software facilitated the creation of a gray model to forecast the incidence and death rate of CNS tumors in China spanning from 2020 to 2030." In 2019, the age-standardized incidence rate, prevalence rate, death rate, and disability-adjusted life years (DALYs) associated with CNS tumors in China were among the high level in the world. The standardized prevalence rate and DALYs of CNS tumors in China residents showed a stable fluctuation trend with age; however, age-standardized death and incidence rate demonstrated a generally upward trend with age. In China, the age-standardized prevalence and incidence rate of males were lower than those for female residents, while the age-standardized death rate and DALYs among males surpassed those of females. From 1990-2019, the age-standardized prevalence and incidence rate of CNS tumors in China exhibited an increasing trend. The age-standardized death rate and DALYs showed a contrasting trend. According to the gray model's prediction, incidence rate of CNS tumors would continue rising while the death rate is expected to decline in China from 2020-2023. The burden of CNS tumors in China has shown an upward trajectory, posing significant challenges to their treatment. It is necessary to pay attention to tertiary prevention, start from the perspective of high-risk groups and high-risk factors to reduce the burden of disease, and achieve "early detection, early diagnosis, and early treatment".

Integrated machine learning survival framework develops a prognostic model based on inter-crosstalk definition of mitochondrial function and cell death patterns in a large multicenter cohort for lower-grade glioma

BACKGROUND

Lower-grade glioma (LGG) is a highly heterogeneous disease that presents challenges in accurately predicting patient prognosis. Mitochondria play a central role in the energy metabolism of eukaryotic cells and can influence cell death mechanisms, which are critical in tumorigenesis and progression. However, the prognostic significance of the interplay between mitochondrial function and cell death in LGG requires further investigation.

METHODS

We employed a robust computational framework to investigate the relationship between mitochondrial function and 18 cell death patterns in a cohort of 1467 LGG patients from six multicenter cohorts worldwide. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations. Ultimately, we devised the mitochondria-associated programmed cell death index (mtPCDI) using machine learning models that exhibited optimal performance.

RESULTS

The mtPCDI, generated by combining 18 highly influential genes, demonstrated strong predictive performance for prognosis in LGG patients. Biologically, mtPCDI exhibited a significant correlation with immune and metabolic signatures. The high mtPCDI group exhibited enriched metabolic pathways and a heightened immune activity profile. Of particular importance, our mtPCDI maintains its status as the most potent prognostic indicator even following adjustment for potential confounding factors, surpassing established clinical models in predictive strength.

CONCLUSION

Our utilization of a robust machine learning framework highlights the significant potential of mtPCDI in providing personalized risk assessment and tailored recommendations for metabolic and immunotherapy interventions for individuals diagnosed with LGG. Of particular significance, the signature features highly influential genes that present further prospects for future investigations into the role of PCD within mitochondrial function.

The Epidemiology of Central Nervous System Tumors

This article reviews the current epidemiology of central nervous system tumors. Population-level basic epidemiology, nationally and internationally, and current understanding of germline genetic risk are discussed, with a focus on known and well-studied risk factors related to the etiology of central nervous system tumors.

α9-Containing Nicotinic Receptors in Cancer

Neuronal nicotinic acetylcholine receptors containing the α9 or the α9 and α10 subunits are expressed in various extra-neuronal tissues. Moreover, most cancer cells and tissues highly express α9-containing receptors, and a number of studies have shown that they are powerful regulators of responses that stimulate cancer processes such as proliferation, inhibition of apoptosis, and metastasis. It has also emerged that their modulation is a promising target for drug development. The aim of this review is to summarize recent data showing the involvement of these receptors in controlling the downstream signaling cascades involved in the promotion of cancer.

A combined healthy lifestyle score in relation to glioma: a case-control study

Background

The evidence on the association between adherence to a healthy lifestyle and risk of glioma are scarce. This is particularly relevant to Middle Eastern countries where lifestyle factors including dietary intakes, physical activity and environmental contributors are different from other parts of the world. The aim of this case-control study was, therefore, investigating the association between adherence to a healthy lifestyle and odds of glioma among adults.

Methods

Totally, 128 newly diagnosed glioma cases and 256 age- and sex-matched controls were recruited in this hospital-based case-control study. Dietary intakes were examined by the use of a 126-item validated FFQ. International Physical Activity Questionnaire (IPAQ) was used for measuring physical activity of participants. To construct a healthy lifestyle score (HLS), data from dietary intakes, physical activity and BMI were used. Subjects in the low risk categories of the mentioned components received the score of 1, otherwise they received the score of 0. The final HLS was computed through summing up the scores of components.

Results

After adjustment for age and sex, we found that individuals with the highest HLS score were 55% less likely to have glioma compared with those with the lowest score (OR: 0.45; 95% CI: 0.22, 0.92). Additional controlling for other potential confounders made the association stronger (OR: 0.28; 95%CI: 0.12, 0.66). In terms of individual components of healthy lifestyle score, subjects with a healthy diet had 54% lower odds of glioma than those with a non-healthy diet (OR: 0.46; 95%CI: 0.26, 0.80). No significant associations were seen between physical activity level or BMI status and glioma.

Conclusion

We found evidence indicating that adherence to a healthy lifestyle, in particular a healthy diet, was associated with a lower odds of glioma. Prospective cohort studies are needed to confirm these findings.

Choline and nicotine increase glioblastoma cell proliferation by binding and activating α7- and α9- containing nicotinic receptors

Glioblastomas (GBMs), the most frequent and aggressive human primary brain tumours, have altered cell metabolism, and one of the strongest indicators of malignancy is an increase in choline compounds. Choline is also a selective agonist of some neuronal nicotinic acetylcholine receptor (nAChR) subtypes. As little is known concerning the expression of nAChR in glioblastoma cells, we analysed in U87MG human grade-IV astrocytoma cell line and GBM5 temozolomide-resistant glioblastoma cells selected from a cancer stem cell-enriched culture, molecularly, pharmacologically and functionally which nAChR subtypes are expressed and,whether choline and nicotine can affect GBM cell proliferation. We found that U87MG and GBM5 cells express similar nAChR subtypes, and choline and nicotine increase their proliferation rate and activate the anti-apoptotic AKT and pro-proliferative ERK pathways. These effects are blocked by the presence of non-cell-permeable peptide antagonists selective for α7- and α9-containing nicotinic receptors. siRNA-mediated silencing of α7 or α9 subunit expression also selectively prevents the effects of nicotine and choline on GBM cell proliferation. Our findings indicate that nicotine and choline activate the signalling pathways involved in the proliferation of GBM cells, and that these effects are mediated by α7 and α9-containing nAChRs. This suggests that these nicotinic receptors may contribute to the aggressive behaviour of this tumor and may indicate new therapeutic strategies against high-grade human brain tumours.

Cigarette Smoking Is Associated with Increased Risk of Malignant Gliomas: A Nationwide Population-Based Cohort Study

The association between cigarette smoking and the risk of developing malignant glioma (MG) remains unclear. We aimed to evaluate this potential association in a large general population, using a well-established and validated longitudinal nationwide database. Using data from the Korean National Health Insurance System cohort, 9,811,768 people over 20 years old without any cancer history in 2009 were followed until the end of 2017. We documented 6100 MG cases (ICD-10 code C71) during the median follow-up period of 7.31 years. Current smokers had a higher risk of developing MG (HR = 1.22, CI: 1.13–1.32) compared with never-smokers, after adjusting for confounders. This association was stronger for those who smoked ≥ 20 cigarettes daily (HR = 1.50, CI: 1.36–1.64). Furthermore, having 30 or more pack-years of smoking over the course of one’s lifetime was associated with an increased risk of developing MG in a dose-dependent manner, compared with never-smokers (HR = 1.31, CI: 1.16–1.48 for 30–39 pack-years of smoking; HR = 1.36, CI: 1.17–1.59 for 40–49 pack-years of smoking; HR = 1.68; CI: 1.44–1.95 for ≥ 50 pack-years of smoking). These results suggest that cigarette smoking may be associated with developing MG. Further prospective studies could help elucidate this association.

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.

Socioeconomic status and mortality among dialysis patients: a systematic review and meta-analysis

BACKGROUND

The reported association between individual indicators of socioeconomic status (SES) and mortality in dialysis patients was inconsistent in previous studies. We performed a meta-analysis to identify the association between SES and mortality of dialysis population.

METHODS

The meta-analysis was conducted in accordance with MOOSE guidelines. Cohorts evaluating the association between SES indicators (income, education and occupation) and mortality in dialysis patients were included. Random-effects models were used to pool the adjusted relative risk (RR) from individual studies. Heterogeneity was assessed by Cochrane's Q and the I² statistic. Subgroup analyses and sensitivity analyses were performed to identify sources of heterogeneity and to evaluate the robustness of findings.

RESULTS

Fourteen studies were finally included. In hemodialysis patients, increased mortality was associated with lower level of income (RR = 1.08, 95%CI [1.01-1.16], P = 0.035; I² = 87.9%, P < 0.001) and occupation (RR = 1.63, 95%CI [1.11-2.38], P = 0.013; I² = 0.0%, P = 0.601). However, no significant association was identified for education (RR = 1.43, 95%CI [0.92-2.25]; P = 0.112; I² = 68.3%,P = 0.001). In patients receiving peritoneal dialysis, lower level of income (RR = 1.80, 95%CI [1.12-2.88],P = 0.015; I² = 75.9%, P = 0.042), education (RR = 1.27, 95%CI [1.13-1.43], P < 0.001; I² = 0.0%, P = 0.684), and occupation (RR = 3.42, 95% CI [1.35-8.70], P = 0.010) were risk factors for increased mortality. Subgroup analysis showed the association between SES indicators and mortality in hemodialysis differed according to geographic locations and study designs.

CONCLUSION

Lower SES (measured by income, education, and occupation) tends to be associated with higher mortality in patients receiving maintenance dialysis. But the magnitude of the associations varied for different individual indicators of SES.

Demographic Variation in the Frequency of Gliomas in Florida

Background and objectives: Glial brain cancers affect nearly 20,000 individuals in the United States (USA) annually. SEER database data exploring the relationship between race and gliomas is now available and have shown that cerebral gliomas occur at a higher frequency in Caucasian men. However, such analyses did not include demographic data specific to the state of Florida. This study assessed the association between race and glial vs. non-glial Central Nervous System (CNS) cancers in Florida, USA. Materials and Methods: This case-control study utilized the Florida Cancer Data Registry (FCDS), in which race was considered the exposure and development of glioma as the measured outcome. The sample was comprised of patients in Florida diagnosed with brain tumors from 1981 to 2013. Relative racial frequencies were compared between patients with glial brain tumors and those with other CNS tumors. Data was analyzed using logistic regression in order to determine any associations between race and frequency of diagnosis adjusting for several confounders (age, sex, smoking status, year of diagnosis, and insurance status). Results: Between 1981 and 2013 a total of 14,092 patients meeting the inclusion and exclusion criteria were diagnosed in Florida with a primary brain tumor. Being of non-white race was associated with 60% decreased odds of glioma diagnosis compared to the reference white population (adjusted OR 0.4, 95% CI 0.34⁻0.47). Secondary findings include associations between increasing age and male sex with increased odds of glioma diagnosis. Decreased adjusted odds of glioma diagnosis were found with former smoking status (reference non-smokers), diagnosis between 2001 and 2010 (reference 1981⁻1990), and Medicaid or Medicare insurance (reference private insurance). Hispanic ethnicity, current smoking status, no insurance/self-pay, and geographical location (urban vs. rural) all had no association with glioma diagnosis. Conclusions: These findings are consistent with and help reinforce previous studies utilizing national databases (SEER) which also showed increasing odds of glioma diagnosis in older white males. Various potential explanations for these findings include genetic predisposition, lifestyle and behavioral factors, and socioeconomic status, including access to healthcare. Future research aims at identifying potential genetic etiologies.

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.

Nut intake and stroke risk: A dose-response meta-analysis of prospective cohort studies

We aim to quantify the effects of nut intake on risk of stroke by a dose-response meta-analysis with a random-effects model. Two databases (PubMed and Emabse) were searched for prospective cohort studies regarding nut intake and stroke risk. Studies were included if they fulfilled the predefined criteria. Eleven articles encompassing fourteen cohort studies were included in final analysis. The pooled relative risk (RR) of stroke for the highest versus (vs.) lowest category of nut intake was 0.88 (95% confidence interval [CI] 0.80-0.97). The power to detect a RR of 0.88 for the highest versus vs. lowest category of nut intake was 86.2%. In multiple subset analyses by gender, location, and stroke subtype, the inverse association was only found in women (RR = 0.84, 95% CI 0.73–0.96) and Asia (RR = 0.79, 95% CI 0.67–0.93). In the dose-response meta-analysis, evidence for a nonlinear association between nut intake and stroke risk was observed and a RR of 0.86 was conferred for 12 g/day. Based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system, the quality of evidence was moderate. In conclusions, finding from current meta-analysis of fourteen cohort studies indicates that nut intake may be related to decreased risk of stroke.