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Purpose: The roles of folate and vitamin B12 in prostate cancer (PCa) or breast cancer (BC) development are unclear. We investigated their roles using the prospective Swedish Apolipoprotein MOrtality RISk (AMORIS) study.Methods: 8,783 men and 19,775 women with vitamin B12 and folate serum measurements were included. Their associations with PCa and BC risk categories were evaluated using Cox proportional hazards regression.Results: During mean follow-up of 13 years, 703 men developed PCa. There was an inverse association between folate > 32 nmol/L and high-risk PCa [hazard ratio (HR) 0.12, 95% confidence interval (CI) 0.02-0.90], and a positive association between folate < 5 nmol/L and metastatic PCa (HR 5.25, 95% CI 1.29-21.41), compared with folate 5-32 nmol/L. No associations with vitamin B12 were found. 795 women developed BC during mean follow-up of 14 years. When restricting to the fasting population, there was a positive association between folate > 32 nmol/L and BC (HR 1.47, 95% CI 1.06-2.04).Conclusion: High folate levels may protect against PCa and low folate levels may increase risk of metastatic PCa. High fasting folate levels may be associated with an increased BC risk. Vitamin B12 was not found to be linked with risk of PCa or BC. Longitudinal studies with serum and dietary information could help define new prevention targets and add information on the role of folate fortification. [ABSTRACT FROM AUTHOR]

Background: Although the onset of inflammatory cascades may profoundly influence the nature of antibody responses, the interplay between inflammatory and humoral (antibody) immune markers remains unclear. Thus, we explored the reciprocity between the humoral immune system and inflammation and assessed how external socio-demographic factors may influence these interactions. From the AMORIS cohort, 5513 individuals were identified with baseline measurements of serum humoral immune [immunoglobulin G, A & M (IgG, IgA, IgM)] and inflammation (C-reactive protein (CRP), albumin, haptoglobin, white blood cells (WBC), iron and total iron-binding capacity) markers measured on the same day. Correlation analysis, principal component analysis and hierarchical clustering were used to evaluate biomarkers correlation, variation and associations. Multivariate analysis of variance was used to assess associations between biomarkers and educational level, socio-economic status, sex and age., Results: Frequently used serum markers for inflammation, CRP, haptoglobin and white blood cells, correlated together. Hierarchical clustering and principal component analysis confirmed the interaction between these main biological responses, showing an acute response component (CRP, Haptoglobin, WBC, IgM) and adaptive response component (Albumin, Iron, TIBC, IgA, IgG). A socioeconomic gradient associated with worse health outcomes was observed, specifically low educational level, older age and male sex were associated with serum levels that indicated infection and inflammation., Conclusions: These findings indicate that serum markers of the humoral immune system and inflammation closely interact in response to infection or inflammation. Clustering analysis presented two main immune response components: an acute and an adaptive response, comprising markers of both biological pathways. Future studies should shift from single internal marker assessment to multiple humoral and inflammation serum markers combined, when assessing risk of clinical outcomes such as cancer., (© 2021. The Author(s).)

Background: Metabolites are genetically and environmentally determined. Consequently, they can be used to characterize environmental exposures and reveal biochemical mechanisms that link exposure to disease. To explore disease susceptibility and improve population risk stratification, we aimed to identify metabolic profiles linked to carcinogenesis and mortality and their intrinsic associations by characterizing subgroups of individuals based on serum biomarker measurements. We included 13,615 participants from the Swedish Apolipoprotein MOrtality RISk Study who had measurements for 19 biomarkers representative of central metabolic pathways. Latent Class Analysis (LCA) was applied to characterise individuals based on their biomarker values (according to medical cut-offs), which were then examined as predictors of cancer and death using multivariable Cox proportional hazards models., Results: LCA identified four metabolic profiles within the population: (1) normal values for all markers (63% of population); (2) abnormal values for lipids (22%); (3) abnormal values for liver functioning (9%); (4) abnormal values for iron and inflammation metabolism (6%). All metabolic profiles (classes 2-4) increased risk of cancer and mortality, compared to class 1 (e.g. HR for overall death was 1.26 (95% CI: 1.16-1.37), 1.67 (95% CI: 1.47-1.90), and 1.21 (95% CI: 1.05-1.41) for class 2, 3, and 4, respectively)., Conclusion: We present an innovative approach to risk stratify a well-defined population based on LCA metabolic-defined subgroups for cancer and mortality. Our results indicate that standard of care baseline serum markers, when assembled into meaningful metabolic profiles, could help assess long term risk of disease and provide insight in disease susceptibility and etiology.