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Key features: 

• The Northern Sweden Health and Disease Study (NSHDS) was initiated in the mid-1980s. The NSHDS is a population-based prospective longitudinal cohort comprising >140 000 participants in the two northernmost regions in Sweden, Norrbotten and Västerbotten, with >240 000 blood samples and 1.5 million person-years of follow-up.
• The NSHDS includes three sub-cohorts: the Västerbotten Intervention Programme (VIP), the expanded Northern Sweden Monitoring of Trends and Determinants of Cardiovascular Disease (MONICA) Study, and the Mammography Screening Project (MSP). The VIP is both a community-based cardiometabolic intervention programme encouraging healthy lifestyle (targeting individuals 40, 50, and 60 years of age), and a corresponding research cohort. The MONICA is an observational study focusing on cardiovascular disease and its associated risk factors, recruiting individuals aged 25–74 years. The MSP recruited women attending mammography during 1995–2006. The NSHDS median participation age is 50 years (53% women).
• Most participants contribute data on health, lifestyle, anthropometric measures, blood pressure, blood lipids, and glucose tolerance, along with research blood samples that are fractionated, frozen within an hour of collection, and stored at –80°C. Linkage to registries, clinical cohorts, and biological tissue archives facilitates studies of well-characterized participants (often combined with intervention studies).
• Collaborations are encouraged. Additional information can be found at: info.brs@umu.se; https://www.umu.se/en/biobank

Purpose: Although sociodemographic factors such as socioeconomic status (SES), travel time to health care, cohabitation status, and region of residence are observed to influence incidence and survival for several types of cancers, it is unclear whether similar effects have been observed in patients with glioma. This study investigates whether these factors affect survival for glioma patients.

Methods: In this retrospective study, the Swedish National Quality Registry for Brain Tumors was used to identify 1,276 patients with glioma WHO grade I–IV for whom data were deposited between 2009 and 2013. The RISK North database, which links data from the National Cancer Quality Register with citizen demographic data from the Longitudinal Integration Database for Health Insurance and Labor Market Studies (LISA), the Total Population Registry (TPR), and the Geography Database (GD), was utilized to assess survival in patients with glioma in relation to education level, cohabitation status, travel time to regional hospitals, and region of residence.

Results: In the multivariable analysis, longer survival was observed among WHO grade III-IV glioma patients with higher education level (middle school (ref) HR: 1, high school HR: 0.81 CI [0.67–0.98], p = 0.033; university/college HR: 0.81 CI [0.66–1.00], p = 0.048). Survival was not associated with travel time, cohabitation status, or region of residence in the multivariable survival analysis.

Conclusion: Low education level was associated with reduced survival for patients with glioma WHO grade III and IV in multivariable survival analyses, but no differences in survival were found in relation to travel time, cohabitation status, or region of residence.

The aim of the present study was to investigate if use of antidepressants is related to the risk of developing lower (WHO grade 2-3) and higher grade (WHO grade 4) glioma. A registry based case-control study was performed using 1283 glioma cases and 6400 age-, sex- and geographically matched controls, diagnosed in Sweden 2009-2013. Conditional logistic regression was used to analyze whether Selective Serotonin Reuptake Inhibitors (SSRIs) or non-SSRIs were associated with the risk of developing lower- or higher-grade glioma in the study population. Our results show that use of antidepressant medication was not associated with the risk of developing glioma. We also performed a meta-analysis in which the dataset from the present study was combined with results from two previous epidemiological studies to answer the same questions. The meta-analysis showed a modest risk reduction of developing glioma in relation to antidepressant treatment (OR 0.90 [95% CI 0.83-0.97]), when all glioma subgroups and all forms of antidepressant medications were combined. In conclusion, it remains possible that antidepressants may have common monoaminergic mechanism(s) that reduce the risk of developing glioma.

Background: Depression and treatment with antidepressant medication is common in patients with malignant glioma. However, the extent to which antidepressants may affect the disease is not fully understood. Therefore, the purpose of the present study was to investigate possible associations between treatment with antidepressant medication and survival in glioma patients.

Methods: We performed a registry-based cohort study including 1231 patients with malignant glioma (WHO grade 2, 3 and 4) having undergone surgery, and 6400 matched controls without glioma. All data was extracted from the RISK North database, which contains information from multiple national population-based registries in Sweden.

Results: Treatment with antidepressants is more common in patients with malignant glioma (27%), compared to controls (16%), p<.001. Treatment with antidepressants after surgery for glioma was significantly associated with poorer survival. These effects were observed both for selective serotonin reuptake inhibitors (SSRIs) and non-SSRIs. In grade 4 glioma, SSRI treatment was associated with a HR of 3.32 (95% CI 2.69–4.10, p<.001), and non-SSRI treatment a HR of 3.54 (95% CI 2.52–4.99, p<.001), compared to glioma patients without antidepressants. In grade 2-3 glioma, the HR for SSRI treatment was 3.26 (95% CI 2.19–4.85, p<.001), and for non-SSRI treatment 7.71 (95% CI 4.22-14.12, p<.001).

Conclusions: Our results demonstrate a negative association between antidepressant medication and survival in glioma. Further research will be needed to clarify causation.

Gliomas are highly complex and metabolically active brain tumors associated with poor prognosis. Recent reports have found altered levels of blood metabolites during early tumor development, suggesting that tumor development could be detected several years before clinical manifestation. In this study, we performed metabolite analyses of blood samples collected from healthy controls and future glioma patients, up to eight years before glioma diagnosis, and on the day of glioma surgery. We discovered that metabolites related to early glioma development were associated with an increased energy turnover, as highlighted by elevated levels of TCA-related metabolites such as fumarate, malate, lactate and pyruvate in pre-diagnostic cases. We also found that metabolites related to glioma progression at surgery were primarily high levels of amino acids and metabolites of amino acid catabolism, with elevated levels of 11 amino acids and two branched-chain alpha-ketoacids, ketoleucine and ketoisoleucine. High amino acid turnover in glioma tumor tissue is currently utilized for PET imaging, diagnosis and delineation of tumor margins. By examining blood-based metabolic progression patterns towards disease onset, we demonstrate that this high amino acid turnover is also detectable in a simple blood sample. These findings provide additional insight of metabolic alterations during glioma development and progression.

Background: Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to efficiently capture genetic risk using available data.

Methods: We applied a method based on continuous shrinkage priors (PRS-CS) to model the joint effects of over 1 million common variants on disease risk and compared this to an approach (PRS-CT) that only selects a limited set of independent variants that reach genome-wide significance (P < 5 x 10(-8)). PRS models were trained using GWAS stratified by histological (10 346 cases and 14 687 controls) and molecular subtype (2632 cases and 2445 controls), and validated in 2 independent cohorts.

Results: PRS-CS was generally more predictive than PRS-CT with a median increase in explained variance (R-2) of 24% (interquartile range = 11-30%) across glioma subtypes. Improvements were pronounced for glioblastoma (GBM), with PRS-CS yielding larger odds ratios (OR) per standard deviation (SD) (OR = 1.93, P = 2.0 x 10(-54) vs. OR = 1.83, P = 9.4 x 10(-50)) and higher explained variance (R-2 = 2.82% vs. R-2 = 2.56%). Individuals in the 80th percentile of the PRS-CS distribution had a significantly higher risk of GBM (0.107%) at age 60 compared to those with average PRS (0.046%, P = 2.4 x 10(-12)). Lifetime absolute risk reached 1.18% for glioma and 0.76% for IDH wildtype tumors for individuals in the 95th PRS percentile. PRS-CS augmented the classification of IDH mutation status in cases when added to demographic factors (AUC = 0.839 vs. AUC = 0.895, P-Delta AUC = 6.8 x 10(-9)).

Conclusions: Genome-wide PRS has the potential to enhance the detection of high-risk individuals and help distinguish between prognostic glioma subtypes.

The serine/glycine (ser/gly) synthesis pathway branches from glycolysis and is hyperactivated in approximately 30% of cancers. In ~13% of glioblastoma cases, we observed frequent amplifications and rare mutations in the gene encoding the enzyme PSPH, which catalyzes the last step in the synthesis of serine. This urged us to unveil the relevance of PSPH genetic alterations and subsequent ser/gly metabolism deregulation in the pathogenesis of glioblastoma. Primary glioblastoma cells overexpressing PSPH and PSPHV116I showed an increased clonogenic capacity, cell proliferation, and migration, supported by elevated nucleotide synthesis and utilization of reductive NAD(P). We previously identified sertraline as an inhibitor of ser/gly synthesis and explored its efficacy at suboptimal dosages in combination with the clinically pretested chloroquine to target ser/glyhigh glioblastoma models. Interestingly, ser/glyhigh glioblastomas, including PSPHamp and PSPHV116I, displayed selective synergistic inhibition of proliferation in response to combination therapy. PSPH knockdown severely affected ser/glyhigh glioblastoma clonogenicity and proliferation, while simultaneously increasing its sensitivity to chloroquine treatment. Metabolite landscaping revealed that sertraline/chloroquine combination treatment blocks NADH and ATP generation and restricts nucleotide synthesis, thereby inhibiting glioblastoma proliferation. Our previous studies highlight ser/glyhigh cancer cell modulation of its microenvironment at the level of immune suppression. To this end, high PSPH expression predicts poor immune checkpoint therapy responses in glioblastoma patients. Interestingly, we show that PSPH amplifications in glioblastoma facilitate the expression of immune suppressor galectin-1, which can be inhibited by sertraline treatment. Collectively, we revealed that ser/glyhigh glioblastomas are characterized by enhanced clonogenicity, migration, and suppression of the immune system, which could be tackled using combined sertraline/chloroquine treatment, revealing novel therapeutic opportunities for this subgroup of GBM patients.

Genetic and metabolic changes in tissue and blood are reported to occur several years before glioma diagnosis. Since gliomas are currently detected late, a liquid biopsy for early detection could affect the quality of life and prognosis of patients. Here, we present a nested case-control study of 550 prediagnostic glioma cases and 550 healthy controls from the Northern Sweden Health and Disease study (NSHDS) and the European Prospective Investigation into Cancer and Nutrition (EPIC) study. We identified 93 significantly altered metabolites related to glioma development up to 8 years before diagnosis. Out of these metabolites, a panel of 20 selected metabolites showed strong disease correlation and a consistent progression pattern toward diagnosis in both the NSHDS and EPIC cohorts, and they separated future cases from controls independently of biological sex. The blood metabolite panel also successfully separated both lower-grade glioma and glioblastoma cases from controls, up to 8 years before diagnosis in patients within the NSHDS cohort and up to 2 years before diagnosis in EPIC. Pathway enrichment analysis detected metabolites related to the TCA cycle, Warburg effect, gluconeogenesis, and cysteine, pyruvate, and tyrosine metabolism as the most affected.

The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.