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BACKGROUND: The Northern Sweden Health and Disease Study is a unique population-based biobank linked to the clinical data registries. The samples originate from over 133 000 individuals living in the northern part of Sweden, and primarily collected during health checkups from the age of 40 years. Our project aims to investigate alterations in metabolite signatures in blood plasma of healthy blood donors that later in life developed a tumor. Brain tumors, especially glioblastoma is associated with poor prognosis. To explore early events of metabolic reprograming linked to future diagnosis, we investigated alterations in metabolite concentrations in plasma collected several years before diagnosis with matched healthy controls.

MATERIALS AND METHODS: In total 392 analytical samples (256 repeated timepoint and 136 single timepoint, case-control samples) were analyzed using GCTOFMS. Constrained randomization of run order was utilized to maximize information output and minimize the false discovery rate. By use of reference databases, we could with high confidence quantify and identify 150 plasma metabolites. We detected metabolites with significant alterations in concertation between pre-clinical glioma cases and healthy controls by the effect projection approach based on orthogonal partial least squares (OPLSEP).

RESULTS AND CONCLUSIONS: For the repeated blood samples, we designed and applied a novel multivariate strategy for high resolution biomarker pattern discovery. We utilize the fact that we have available samples from two repeated time points prior to diagnosis for each future glioma case and their matched controls to construct a small design of experiment (DoE) of four samples for each match pair. The data for each individual DoE was evaluated by OPLS-EP to determine the effect of each individual metabolite in relation to control-case, time and their interaction. Finally, latent significance calculations by means of OPLS were used to extract and evaluate the correct latent biomarker and highlight true significance of individual metabolites. Our study presents an approach to minimize confounding effects due to systematic noise from sampling, the analytical method, as well as take into account personalized metabolic levels over time, enabling biomarker detection within a smaller sample group. We will present and discuss the latest results and biomarkers from this exploratory metabolomics study at the meeting

PCBs are classified as xenoestrogens and carcinogens and their health risks may be sex-specific. To identify potential sex-specific responses to PCB-exposure we established gene expression profiles in a population study subdivided into females and males. Gene expression profiles were determined in a study population consisting of 512 subjects from the EnviroGenomarkers project, 217 subjects who developed lymphoma and 295 controls were selected in later life. We ran linear mixed models in order to find associations between gene expression and exposure to PCBs, while correcting for confounders, in particular distribution of white blood cells (WBC), as well as random effects. The analysis was subdivided according to sex and development of lymphoma in later life. The changes in gene expression as a result of exposure to the six studied PCB congeners were sex- and WBC type specific. The relatively large number of genes that are significantly associated with PCB-exposure in the female subpopulation already indicates different biological response mechanisms to PCBs between the two sexes. The interaction analysis between different PCBs and WBCs provides only a small overlap between sexes. In males, cancer-related pathways and in females immune system-related pathways are identified in association with PCBs and WBCs. Future lymphoma cases and controls for both sexes show different responses to the interaction of PCBs with WBCs, suggesting a role of the immune system in PCB-related cancer development.

OBJECTIVES: To characterize the impact of PCB exposure on DNA methylation in peripheral blood leucocytes and to evaluate the corresponding changes in relation to possible health effects, with a focus on B-cell lymphoma.

METHODS: We conducted an epigenome-wide association study on 611 adults free of diagnosed disease, living in Italy and Sweden, in whom we also measured plasma concentrations of 6 PCB congeners, DDE and hexachlorobenzene.

RESULTS: We identified 650 CpG sites whose methylation correlates strongly (FDR < 0.01) with plasma concentrations of at least one PCB congener. Stronger effects were observed in males and in Sweden. This epigenetic exposure profile shows extensive and highly statistically significant overlaps with published profiles associated with the risk of future B-cell chronic lymphocytic leukemia (CLL) as well as with clinical CLL (38 and 28 CpG sites, respectively). For all these sites, the methylation changes were in the same direction for increasing exposure and for higher disease risk or clinical disease status, suggesting an etiological link between exposure and CLL. Mediation analysis reinforced the suggestion of a causal link between exposure, changes in DNA methylation and disease. Disease connectivity analysis identified multiple additional diseases associated with differentially methylated genes, including melanoma for which an etiological link with PCB exposure is established, as well as developmental and neurological diseases for which there is corresponding epidemiological evidence. Differentially methylated genes include many homeobox genes, suggesting that PCBs target stem cells. Furthermore, numerous polycomb protein target genes were hypermethylated with increasing exposure, an effect known to constitute an early marker of carcinogenesis.

CONCLUSIONS: This study provides mechanistic evidence in support of a link between exposure to PCBs and the etiology of CLL and underlines the utility of omic profiling in the evaluation of the potential toxicity of environmental chemicals.

BACKGROUND: B-cell chronic lymphocytic leukemia (CLL) is a common type of adult leukemia. It often follows an indolent course and is preceded by monoclonal B-cell lymphocytosis, an asymptomatic condition, however it is not known what causes subjects with this condition to progress to CLL. Hence the discovery of prediagnostic markers has the potential to improve the identification of subjects likely to develop CLL and may also provide insights into the pathogenesis of the disease of potential clinical relevance.

RESULTS: We employed peripheral blood buffy coats of 347 apparently healthy subjects, of whom 28 were diagnosed with CLL 2.0-15.7 years after enrollment, to derive for the first time genome-wide DNA methylation, as well as gene and miRNA expression, profiles associated with the risk of future disease. After adjustment for white blood cell composition, we identified 722 differentially methylated CpG sites and 15 differentially expressed genes (Bonferroni-corrected p < 0.05) as well as 2 miRNAs (FDR < 0.05) which were associated with the risk of future CLL. The majority of these signals have also been observed in clinical CLL, suggesting the presence in prediagnostic blood of CLL-like cells. Future CLL cases who, at enrollment, had a relatively low B-cell fraction (<10%), and were therefore less likely to have been suffering from undiagnosed CLL or a precursor condition, showed profiles involving smaller numbers of the same differential signals with intensities, after adjusting for B-cell content, generally smaller than those observed in the full set of cases. A similar picture was obtained when the differential profiles of cases with time-to-diagnosis above the overall median period of 7.4 years were compared with those with shorted time-to-disease. Differentially methylated genes of major functional significance include numerous genes that encode for transcription factors, especially members of the homeobox family, while differentially expressed genes include, among others, multiple genes related to WNT signaling as well as the miRNAs miR-150-5p and miR-155-5p.

CONCLUSIONS: Our findings demonstrate the presence in prediagnostic blood of future CLL patients, more than 10 years before diagnosis, of CLL-like cells which evolve as preclinical disease progresses, and point to early molecular alterations with a pathogenetic potential.

Pre-diagnostic serum/plasma concentrations of B-cell activation markers have been associated with future risk of B-cell lymphomas (BCL) in HIV-infected patients and in the general population. Current evidence for the general population is however limited and relies on relatively small numbers of observations, especially for specific histologies. We carried out a nested case-control study, including 218 BCL and 218 matched controls, within two prospective cohorts, to investigate the association between plasma levels of soluble (s)CD27 and sCD30 and future risk of BCL, and main histologic subtypes separately. To expand the evidence further, we performed meta-analyses of the published data on these associations from prospective studies among the general population. Our study revealed a significant relationship between sCD30 concentration and BCL risk (OR=0.86, 1.53, 1.76, for the 2(nd) -4(th) quartiles respectively, P-trend=0.01). Similar increased risks were observed for diffuse large B-cell lymphoma and follicular lymphoma. Analyses of sCD27 blood concentrations did not show significant associations with BCL, (OR=0.90, 1.26, 1.65 for the 2(nd) -4(th) quartiles, respectively, P-trend=0.17), but significant associations were observed for chronic lymphocytic leukaemia and for the group of 'other BCL' subtypes. Our findings involving sCD30 were confirmed within our meta-analyses of five prospective cohorts, while results were more heterogeneous for sCD27 with the exception of CLL which was found consistently in all studies. Data to date suggest that chronic B-cell stimulation might be an important mechanism involved in B-cell lymphomagenesis both in HIV-infected and in the general population.

Simple Summary: Reprogramming of cellular metabolism is a major hallmark of cancer cells, and play an important role in tumor initiation and progression. The aim of our study is to discover circulating early metabolic markers of brain tumors, as discovery and development of reliable predictive molecular markers are needed for precision oncology applications. We use a study design tailored to minimize confounding factors and a novel machine learning and visualization approach (SMART) to identify a panel of 15 interlinked metabolites related to glioma development. The presented SMART strategy facilitates early molecular marker discovery and can be used for many types of molecular data.

Abstract: Here, we present a strategy for early molecular marker pattern detection-Subset analysis of Matched Repeated Time points (SMART)-used in a mass-spectrometry-based metabolomics study of repeated blood samples from future glioma patients and their matched controls. The outcome from SMART is a predictive time span when disease-related changes are detectable, defined by time to diagnosis and time between longitudinal sampling, and visualization of molecular marker patterns related to future disease. For glioma, we detect significant changes in metabolite levels as early as eight years before diagnosis, with longitudinal follow up within seven years. Elevated blood plasma levels of myo-inositol, cysteine, N-acetylglucosamine, creatinine, glycine, proline, erythronic-, 4-hydroxyphenylacetic-, uric-, and aceturic acid were particularly evident in glioma cases. We use data simulation to ensure non-random events and a separate data set for biomarker validation. The latent biomarker, consisting of 15 interlinked and significantly altered metabolites, shows a strong correlation to oxidative metabolism, glutathione biosynthesis and monosaccharide metabolism, linked to known early events in tumor development. This study highlights the benefits of progression pattern analysis and provide a tool for the discovery of early markers of disease.

Persistent organic pollutants (POPs) are synthetic chemical substances that accumulate in our environment. POPs such as polychlorinated biphenyls (PCBs), hexachlorobenzene (HCB) and dichlorodiphenyltrichloroethane (DDT) have been classified as carcinogenic to humans and animals. Due to their resistance to biodegradation humans are still exposed to these compounds worldwide. We aim to evaluate the miRNA and transcriptomic response of a human population exposed to POPs. The miRNA and transcriptomic response was measured in blood of healthy subjects by microarray technology and associated with the serum concentrations of six PCB congeners, DDE (a common DDT metabolite), and HCB. A total of 93 miRNA levels appeared significantly associated with the POP-exposure (FDR < 0.05). The miRNA profile includes four tumor suppressor miRNAs, namely miR-193a-3p, miR-152, miR-31-5p and miR-34a-5p. Integration of the miRNA profile with the transcriptome profile suggests an interaction with oncogenes such as MYC, CCND1, BCL2 and VEGFA. We have shown that exposure to POPs is associated with human miRNA and transcriptomic responses. The identified miRNAs and target genes are related to various types of cancer and involved in relevant signaling pathways like wnt and p53. Therefore, these miRNAs may have great potential to contribute to biomarker-based environmental health risk assessment.

Limited evidence exists on the role of modifiable lifestyle factors on the risk of lymphoma. In this rk, the associations between adherence to healthy lifestyles and risks of Hodgkin lymphoma (HL) and n-Hodgkin lymphoma (NHL) were evaluated in a large-scale European prospective cohort. Within the ropean Prospective Investigation into Cancer and Nutrition (EPIC), 2,999 incident lymphoma cases 32 HL and 2,746 NHL) were diagnosed among 453,808 participants after 15 years (median) of follow- . The healthy lifestyle index (HLI) score combined information on smoking, alcohol intake, diet, ysical activity and BMI, with large values of HLI expressing adherence to healthy behavior. Cox oportional hazards models were used to estimate lymphoma hazard ratios (HR) and 95% confidence terval (CI). Sensitivity analyses were conducted by excluding, in turn, each lifestyle factor from the HLI ore. The HLI was inversely associated with HL, with HR for a 1-standard deviation (SD) increment in the ore equal to 0.78 (95% CI: 0.66, 0.94). Sensitivity analyses showed that the association was mainly iven by smoking and marginally by diet. NHL risk was not associated with the HLI, with HRs for a 1-SD crement equal to 0.99 (0.95, 1.03), with no evidence for heterogeneity in the association across NHL btypes. In the EPIC study, adherence to healthy lifestyles was not associated with overall lymphoma or NHL risk, while an inverse association was observed for HL, although this was largely attributable to smoking. These findings suggest a limited role of lifestyle factors in the etiology of lymphoma subtypes.

Previous epidemiological studies suggest an inverse association between allergies, marked by elevated immunoglobulin (Ig) E levels, and non-Hodgkin lymphoma (NHL) risk. The evidence, however, is inconsistent and prospective data are sparse. We examined the association between prediagnostic total (low: < 20; intermediate: 20-100; high > 100 kU/l) and specific IgE (negative: < 0.35; positive >= 0.35 kU/I) concentrations against inhalant antigens and lymphoma risk in a study nested within the European Prospective Investigation into Cancer and Nutrition cohort. A total of 1021 incident cases and matched controls of NHL, multiple myeloma (MM) and Hodgkin lymphoma with a mean follow-up time of 7 years were investigated. Multivariate-adjusted odds ratios (ORs) with 95% confidence intervals (CI) were calculated by conditional logistic regression. Specific IgE was not associated with the risk of MM, B-cell NHL and B-cell NHL subtypes. In contrast, total IgE levels were inversely associated with the risk of MM [high level: OR = 0.40 (95% CI = 0.21-0.79)] and B-cell NHL [intermediate level: OR = 0.68 (95% CI = 0.53-0.88); high level: OR = 0.62 (95% CI = 0.44-0.86)], largely on the basis of a strong inverse association with chronic lymphocytic leukemia [CLL; intermediate level: OR = 0.49 (95% CI = 0.30-0.80); high level: OR = 0.13 (95% CI = 0.05-0.35)] risk. The inverse relationship for CLL remained significant for those diagnosed 5 years after baseline. The findings of this large prospective study demonstrated significantly lower prediagnostic total IgE levels among CLL and MM cases compared with matched controls. This corresponds to the clinical immunodeficiency state often observed in CLL patients prior to diagnosis. No support for an inverse association between prediagnostic levels of specific IgE and NHL risk was found.

To better understand the role of individual and lifestyle factors in human disease, an exposome-wide association study was performed to investigate within a single-study anthropometry measures and lifestyle factors previously associated with B-cell lymphoma (BCL). Within the European Prospective Investigation into Cancer and nutrition study, 2402 incident BCL cases were diagnosed from 475 426 participants that were followed-up on average 14 years. Standard and penalized Cox regression models as well as principal component analysis (PCA) were used to evaluate 84 exposures in relation to BCL risk. Standard and penalized Cox regression models showed a positive association between anthropometric measures and BCL and multiple myeloma/plasma cell neoplasm (MM). The penalized Cox models additionally showed the association between several exposures from categories of physical activity, smoking status, medical history, socioeconomic position, diet and BCL and/or the subtypes. PCAs confirmed the individual associations but also showed additional observations. The PC5 including anthropometry, was positively associated with BCL, diffuse large B-cell lymphoma (DLBCL) and MM. There was a significant positive association between consumption of sugar and confectionary (PC11) and follicular lymphoma risk, and an inverse association between fish and shellfish and Vitamin D (PC15) and DLBCL risk. The PC1 including features of the Mediterranean diet and diet with lower inflammatory score showed an inverse association with BCL risk, while the PC7, including dairy, was positively associated with BCL and DLBCL risk. Physical activity (PC10) was positively associated with DLBCL risk among women. This study provided informative insights on the etiology of BCL.

Introduction: Chronic inflammation plays a critical role in lymphomagenesis and several dietary factors seem to be involved its regulation. The aim of the current study was to assess the association between the inflammatory potential of the diet and the risk of lymphoma and its subtypes in the European Investigation into Cancer and Nutrition (EPIC) study.

Methods: The analysis included 476,160 subjects with an average follow-up of 13.9 years, during which 3,136 lymphomas (135 Hodgkin lymphoma (HL), 2606 non-Hodgkin lymphoma (NHL) and 395 NOS) were identified. The dietary inflammatory potential was assessed by means of an inflammatory score of the diet (ISD), calculated using 28 dietary components and their corresponding inflammatory weights. The association between the ISD and lymphoma risk was estimated by hazard ratios (HR) and 95% confidence intervals (CI) calculated by multivariable Cox regression models adjusted for potential confounders.

Results: The ISD was not associated with overall lymphoma risk. Among lymphoma subtypes, a positive association between the ISD and mature B-cell NHL (HR for a 1-SD increase: 1.07 (95% CI 1.01; 1.14), p trend = 0.03) was observed. No statistically significant association was found among other subtypes. However, albeit with smaller number of cases, a suggestive association was observed for HL (HR for a 1-SD increase = 1.22 (95% CI 0.94; 1.57), p trend 0.13).

Conclusions: Our findings suggested that a high ISD score, reflecting a pro-inflammatory diet, was modestly positively associated with the risk of B-cell lymphoma subtypes. Further large prospective studies on low-grade inflammation induced by diet are warranted to confirm these findings.

There is a growing evidence of the protective role of the Mediterranean diet (MD) on cancer. However, no prospective study has yet investigated its influence on lymphoma. We evaluated the association between adherence to the MD and risk of lymphoma and its subtypes in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The analysis included 476,160 participants, recruited from 10 European countries between 1991 and 2001. Adherence to the MD was estimated through the adapted relative MD (arMED) score excluding alcohol. Cox proportional hazards regression models were used while adjusting for potential confounders. During an average follow-up of 13.9 years, 3,136 lymphomas (135 Hodgkin lymphoma [HL], 2,606 non-HL and 395 lymphoma not otherwise specified) were identified. Overall, a 1-unit increase in the arMED score was associated with a 2% lower risk of lymphoma (95% CI: 0.97; 1.00, p-trend = 0.03) while a statistically nonsignificant inverse association between a high versus low arMED score and risk of lymphoma was observed (hazard ratio [HR]: 0.91 [95% CI 0.80; 1.03], p-trend = 0.12). Analyses by lymphoma subtype did not reveal any statistically significant associations. Albeit with small numbers of cases (N = 135), a suggestive inverse association was found for HL (HR 1-unit increase = 0.93 [95% CI: 0.86; 1.01], p-trend = 0.07). However, the study may have lacked statistical power to detect small effect sizes for lymphoma subtype. Our findings suggest that an increasing arMED score was inversely related to the risk of overall lymphoma in EPIC but not by subtypes. Further large prospective studies are warranted to confirm these findings.

BACKGROUND: Nested case-control studies aim to link molecular markers with a certain outcome. Repeated prediagnostic samples may improve the evaluation of marker-disease associations. However, data regarding the benefit of repeated samples in such studies are sparse. We aimed to assess the relationship between blood levels of various proteins and risk of glioma, B cell lymphoma, and multiple myeloma to gain further understanding of disease etiology and to evaluate the clinical relevance of the studied markers. To this end, marker-disease associations were evaluated considering the natural history of the studied disease and the time between blood sample collection and diagnosis using both single (I-II) and repeated prediagnostic blood samples (III-IV).

PATIENTS AND METHODS: We conducted four nested case-control studies and one meta-analysis using samples from three prospective cohorts: the Janus Serum Bank, the Northern Sweden Health and Disease study, and the European Prospective Investigation into Cancer and Nutrition study. The following studied endpoints and relationships were included: I) glioma risk and the association with the receptor tyrosine kinases (soluble) sEGFR and sERBB2; II) B cell lymphoma risk and the association with the immune markers sCD27 and sCD30; III) B cell lymphoma risk and the association with immune markers (CXCL13, sTNF-R1, sCD23, sCD27, and sCD30) and their trends over time; and IV) multiple myeloma risk and the association  with ten immune markers and growth factors (MCP-3, MIP-1α, MIP-1β, VEGF, FGF-2, fractalkine, TGF-α, IL-13, TNF-α, and IL-10) and their trends over time.

RESULTS: Risk of developing I) glioma was weakly associated with high blood levels of sERBB2. In addition, high levels of both sEGFR and sERBB2 assessed 15 years before diagnosis were associated with glioblastoma risk.

Risk of II) B cell lymphoma was associated with high levels of sCD30, whereas high levels of sCD27 were particularly associated with risk of chronic lymphocytic leukemia. Meta-analyses showed consistent results for sCD30 across cohorts and lymphoma subtypes, whereas results for sCD27 were less consistent across cohorts and subtypes.

In addition, III) B cell lymphoma risk was associated with levels of CXCL13, sCD23, sCD27, and sCD30 assessed in samples collected 17 years before diagnosis. Marker levels increased in cases closer to diagnosis, particularly for indolent lymphoma with a marked association for chronic lymphocytic leukemia and sCD23. Increasing marker levels closer to diagnosis were also observed for CXCL13 in future diffuse large B cell lymphoma patients.

Risk of IV) multiple myeloma was associated with low levels of MCP-3, VEGF, FGF-2, fractalkine, and TGF-α. Levels of these markers decreased in myeloma cases over time, especially for TGF-α. TGF-α assessed at time of the prediagnostic repeated sample seemed to help predict progression to multiple myeloma.

CONCLUSIONS: Both the natural history of the studied disease and the time between sample collection and diagnosis are crucial for the evaluation of marker-disease associations. Using repeated blood samples improves the understanding of marker-disease associations and might help to identify useful biomarker candidates.

Genetic variants have been associated with the risk of developing glioma, but functional mechanisms on disease phenotypic traits remain to be investigated. One phenotypic trait of glioblastoma is the mutation and amplification of the epidermal growth factor receptor (EGFR) gene. We investigated associations between pre-diagnostic serum protein concentrations of EGFR and ErbB2, both members of the EGFR family, and future risk of glioma. Further, we studied if EGFR glioma risk variants were associated with EGFR and ErbB2 serum levels. We assessed the associations between genetic glioma risk variants and serum concentrations of EGFR and ErbB2, as measured in pre-diagnostic cohort serum samples of 593 glioma patients and 590 matched cancer-free controls. High serum EGFR and ErbB2 levels were associated with risk of developing glioblastoma (P = 0.008; OR = 1.58, 95 % CI = 1.13-2.22 and P = 0.017, OR = 1.63, 95 % CI = 1.09-2.44, respectively). High serum ErbB2 concentration was also associated with glioma risk overall (P = 0.049; OR = 1.39, 95 % CI = 1.00-1.93). Glioma risk variants were not associated with high serum protein abundance. In contrast, the EGFR risk variant rs4947986 (T) was correlated with decreased EGFR serum levels (study cohort P = 0.024 and controls P = 0.009). To our knowledge, this is the first study showing an association of EGFR and ErbB2 serum levels with glioma more than a decade before diagnosis, indicating that EGFR and ErbB2 serum proteins are important in early gliomagenesis. However, we did not find evidence that glioma risk variants were associated with high pre-diagnostic serum concentrations of EGFR and ErbB2.

Biomarkers reliably predicting progression to multiple myeloma (MM) are lacking. Myeloma risk has been associated with low blood levels of monocyte chemotactic protein-3 (MCP-3), macrophage inflammatory protein-1 alpha (MIP-1 alpha), vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), fractalkine, and transforming growth factor-alpha (TGF-alpha). In this study, we aimed to replicate these findings and study the individual dynamics of each marker in a prospective longitudinal cohort, thereby examining their potential as markers of myeloma progression. For this purpose, we identified 65 myeloma cases and 65 matched cancer-free controls each with two donated blood samples within the Northern Sweden Health and Disease Study. The first and repeated samples from myeloma cases were donated at a median 13 and 4 years, respectively, before the myeloma was diagnosed. Known risk factors for progression were determined by protein-, and immunofixation electrophoresis, and free light chain assays. We observed lower levels of MCP-3, VEGF, FGF-2, and TGF-alpha in myeloma patients than in controls, consistent with previous data. We also observed that these markers decreased among future myeloma patients while remaining stable in controls. Decreasing trajectories were noted for TGF-alpha (P=2.5 x 10(-4)) indicating progression to MM. Investigating this, we found that low levels of TGF-alpha assessed at the time of the repeated sample were independently associated with risk of progression in a multivariable model (hazard ratio = 3.5; P=0.003). TGF-alpha can potentially improve early detection of MM.

The B-cell activation markers CXCL13, sCD23, (S)CD27, and sCD30 are associated with future lymphoma risk. However, a lack of information about the individual dynamics of markerdisease association hampers interpretation. In this study, we identified 170 individuals who had donated two prediagnostic blood samples before B-cell lymphoma diagnosis, along with 170 matched cancer-free controls from the Northern Sweden Health and Disease Study. Lymphoma risk associations were investigated by subtype and marker levels measured at baseline, at the time of the repeated sample, and with the rate of change in the marker level. Notably, we observed strong associations between CXCL13, sCD23, sCD27, and sCD30 and lymphoma risk in blood samples collected 15 to 25 years before diagnosis. B-cell activation marker levels increased among future lympho-ma cases over time, while remaining stable among controls. Associations between slope and risk were strongest for indolent lymphoma subtypes. We noted a marked association of sCD23 with chronic lymphocytic leukemia (ORSlope - 28, Ptrend(-)7.279 x 10 (-10)). Among aggressive lymphomas, the association between diffuse large B-cell lymphoma risk and slope was restricted to CXCL13. B-cell activation seemed to play a role in B-cell lymphoma development at early stages across different subtypes. Furthermore, B-cell activation presented differential trajectories in future lymphoma patients, mainly driven by indolent subtypes. Our results suggest a utility of these markers in predicting the presence of early occult disease and/or the screening and monitoring of indolent lymphoma in individual patients. 

Background: Changes in immune marker levels in the blood could be used to improve the early detection of tumor-associated inflammatory processes. To increase predictiveness and utility in cancer detection, intraindividual long-term stability in cancer-free individuals is critical for biomarker candidates as to facilitate the detection of deviation from the norm.

Methods: We assessed intraindividual long-term stability for 19 immune markers (IL10, IL13, TNFa, CXCL13, MCP-3, MIP-1a, MIP-1b, fractalkine, VEGF, FGF-2, TGFa, sIL2Ra, sIL6R, sVEGF-R2, sTNF-R1, sTNF-R2, sCD23, sCD27, and sCD30) in 304 cancer-free individuals. Repeated blood samples were collected up to 20 years apart. Intraindividual reproducibility was assessed by calculating intraclass correlation coefficients (ICC) using a linear mixed model.

Results: ICCs indicated fair to good reproducibility (ICCs ≥ 0.40 and < 0.75) for 17 of 19 investigated immune markers, including IL10, IL13, TNFa, CXCL13, MCP-3, MIP-1a, MIP-1b, fractalkine, VEGF, FGF-2, TGFa, sIL2Ra, sIL6R, sTNF-R1, sTNF-R2, sCD27, and sCD30. Reproducibility was strong (ICC ≥ 0.75) for sCD23, while reproducibility was poor (ICC < 0.40) for sVEGF-R2. Using a more stringent criterion for reproducibility (ICC ≥ 0.55), we observed either acceptable or better reproducibility for IL10, IL13, CXCL13, MCP-3, MIP-1a, MIP-1b, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30.

Conclusions: IL10, IL13, CXCL13, MCP-3, MIP-1a, MIP-1b, VEGF, FGF-2, sTNF-R1, sCD23, sCD27, and sCD30 displayed ICCs consistent with intraindividual long-term stability in cancer-free individuals. Impact: Our data support using these markers in prospective longitudinal studies seeking early cancer detection biomarkers.

Follow-up of low-risk monoclonal gammopathy of undetermined significance (MGUS) is debated as multiple myeloma (MM) progression risk is low. Worse MM outcome was reported for patients followed for low-risk MGUS, possibly due to less optimal follow-up. However, it is unknown whether progressing low-risk MGUS is associated with aggressive tumor behavior. Understanding these patterns is crucial for MGUS management. Here, we investigated whether progression from low-risk MGUS is associated with worse MM outcome in patients who had no MGUS follow-up before myeloma diagnosis. We retrospectively determined the MGUS status in repeated pre-diagnostic blood samples prospectively collected from 42 myeloma patients in median 11.6 years (first sample) and 3.3 years (repeated sample) before myeloma diagnosis. At first pre-diagnostic blood draw, 12 had low-risk (defined by an immunoglobulin [Ig] G monoclonal [M] spike < 15 g/L and a normal free light-chain ratio) and 30 had MGUS of other risk. MM bone disease was more common in patients with low-risk MGUS at first blood draw (67% vs. 30%, P = 0.041). Median survival since myeloma diagnosis was worse in low-risk than other MGUS at first blood draw (2.3 vs. 7.5 years, P = 0.004). Modest progression was observed between first and repeated blood draw for the majority of low-risk MGUS as 67% remained as low- or low-intermediate-risk MGUS at repeated blood draw. Our study, albeit limited by its small size, indicates that progression from low-risk MGUS is associated with worse MM outcome regardless of MGUS follow-up. Although further investigation is needed, progressing low-risk MGUS could belong to a group of aggressive tumors with progression that is difficult to predict.

Genome-wide association studies (GWASs) based on common single nucleotide polymorphisms (SNPs) have identified several loci associated with the risk of monoclonal gammopathy of unknown significance (MGUS), a precursor condition for multiple myeloma (MM). We hypothesized that analyzing haplotypes might be more useful than analyzing individual SNPs, as it could identify functional chromosomal units that collectively contribute to MGUS risk. To test this hypothesis, we used data from our previous GWAS on 992 MGUS cases and 2910 controls from three European populations. We identified 23 haplotypes that were associated with the risk of MGUS at the genome-wide significance level (p < 5 × 10−8) and showed consistent results among all three populations. In 10 genomic regions, strong promoter, enhancer and regulatory element-related histone marks and their connections to target genes as well as genome segmentation data supported the importance of these regions in MGUS susceptibility. Several associated haplotypes affected pathways important for MM cell survival such as ubiquitin-proteasome system (RNF186, OTUD3), PI3K/AKT/mTOR (HINT3), innate immunity (SEC14L1, ZBP1), cell death regulation (BID) and NOTCH signaling (RBPJ). These pathways are important current therapeutic targets for MM, which may highlight the advantage of the haplotype approach homing to functional units.

Multiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development.

One obstacle to developing new treatments for glioma is the generally poor understanding of glioma aetiology. The only generally accepted environmental risk factor or glioma is ionizing radiation. Glioma aetiology has also been shown to contain a genetic component, in part through observations that individuals in families with a history of glioma have an elevated risk of developing glioma themselves. The genetic component in glioma aetiology has been further substantiated through genome wide association studies (GWAS). These studies have identified associations between a number of common genetic variants and an increased glioma risk. However, the studies have all been of case-control design (i.e. including cases at diagnosis), and as such they presumably suffer from a degree of survival bias. Survival bias risks being introduced in a study when rapidly fatal cases are not included. This is an inherent risk of case-control designs, which is particularly pronounced when studying a disease with very poor prognosis, such as glioma. Ultimately, survival bias may result in erroneous conclusions, as it is impossible to separate associations with prognosis from associations with risk of disease. To accurately confirm previously identified glioma risk variants, and ascertain whether they are associated with risk or with prolonged survival, we investigated these variants in a set of pre-diagnostic serum samples (594 cases and 591 matched controls). Analyses of population based, pre-diagnostic samples eliminates the risk of survival bias, and enables distinction between genetic variants associated with glioma risk (i.e. aetiology) and genetic variants associated with prognosis. The serum samples were acquired through The Janus Serum Bank, a Norwegian population based biobank reserved for cancer research. Variant detection was achieved by means of cycling temperature capillary electrophoresis. Our investigation confirmed the association with glioma risk for the investigated variants within five genomic regions; 8q24.21 (CCDC26), 9p21.3 (CDKN2B-AS1), 11q23.3 (PHLDB1), 17p13.1 (TP53), and 20q13.33 (RTEL1). This is indicative of these variants being truly associated with glioma risk, and thus may impact gliomagenesis. However, previously identified risk variants within the 5p15.33 (TERT) and 7p11.2 (EGFR) could not be positively confirmed by this study. The lack of positive confirmation raises the question whether EGFR and TERT genetic variants are linked with prolonged survival, rather than with glioma aetiology.

Background: Although glioma etiology is poorly understood in general, growing evidence indicates a genetic component. Four large genome-wide association studies (GWAS) have linked common genetic variants with an increased glioma risk. However, to date, these studies are based largely on a case-control design, where cases have been recruited at the time of or after diagnosis. They may therefore suffer from a degree of survival bias, introduced when rapidly fatal cases are not included.

Methods: To confirm glioma risk variants in a prospective setting, we have analyzed 11 previously identified risk variants in a set of prediagnostic serum samples with 598 cases and 595 matched controls. Serum samples were acquired from The Janus Serum Bank, a Norwegian population-based biobank reserved for cancer research.

Results: We confirmed the association with glioma risk for variants within five genomic regions: 8q24.21 (CCDC26), 9p21.3 (CDKN2B-AS1), 11q23.3 (PHLDB1), 17p13.1 (TP53), and 20q13.33 (RTEL1). However, previously identified risk variants within the 7p11.2 (EGFR) region were not confirmed by this study.

Conclusions: Our results indicate that the risk variants that were confirmed by this study are truly associated with glioma risk and may, consequently, affect gliomagenesis. Though the lack of positive confirmation of EGFR risk variants may be attributable to relatively limited statistical power, it nevertheless raises the question whether they truly are risk variants or markers for glioma prognosis.

Impact: Our findings indicate the need for further studies to clarify the role of glioma risk loci with respect to prolonged survival versus etiology.

No strong aetiological factors have been established for glioma aside from genetic mutations and variants, ionising radiation and an inverse relationship with asthmas and allergies. Our aim was to investigate the association between pre-diagnostic immune protein levels and glioma risk. We conducted a case–control study nested in the Northern Sweden Health and Disease Study cohort. We analysed 133 glioma cases and 133 control subjects matched by age, sex and date of blood donation. ELISA or Luminex bead-based multiplex assays were used to measure plasma levels of 19 proteins. Conditional logistic regression models were used to estimate the odds ratios and 95% CIs. To further model the protein trajectories over time, the linear mixed-effects models were conducted. We found that the levels of sVEGFR2, sTNFR2, sIL-2Rα and sIL-6R were associated with glioma risk. After adjusting for the time between blood sample collection and glioma diagnosis, the odds ratios were 1.72 (95% CI = 1.01–2.93), 1.48 (95% CI = 1.01–2.16) and 1.90 (95% CI = 1.14–3.17) for sTNFR2, sIL-2Rα and sIL-6R, respectively. The trajectory of sVEGFR2 concentrations over time was different between cases and controls (p-value = 0.031), increasing for cases (0.8% per year) and constant for controls. Our findings suggest these proteins play important roles in gliomagenesis.