SERMs Promote Anti-Inflammatory Signaling and Phenotype of CD14+ Cells

Signaling via estrogen receptors (ER) is recognized as an essential part of the immune regulation, and ER-mediated signaling is involved in autoimmune reactions. Especially ERα activation in immune cells has been suggested to skew cytokine production toward Th2/M2-type mediators, which can have protective effect on inflammatory diseases and reduce Th1 and Th17 responses. These effects are caused by increased alternative activation of macrophages and changes in the activation of different T cell populations. In humans, hormonal status has been shown to have a major impact on several inflammatory diseases. Selective estrogen receptor modulators (SERMs) are ER ligands that regulate ER actions in a tissue-specific manner mostly lacking the adverse effects of steroid hormones. The impact of SERMs on the immune system is less studied, but it is suggested that certain SERMs may also produce immunoprotective effects. Here, we show that two novel SERMs and raloxifene affect immune cells by promoting M2 macrophage phenotype, alleviating NFκB activity, inhibiting T cell proliferation, and stimulating the production of anti-inflammatory compounds such as IL10 and IL1 receptor antagonist. Thus, these compounds have high potency as drug candidates against autoimmune diseases.     

High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis

Aims High-throughput metabolite quantification holds promise for cardiovascular risk assessment. Here, we evaluated whether metabolite quantification by nuclear magnetic resonance (NMR) improves prediction of subclinical atherosclerosis in comparison to conventional lipid testing. Methods and results Circulating lipids, lipoprotein subclasses, and small molecules were assayed by NMR for 1595 individuals aged 24-39 years from the population-based Cardiovascular Risk in Young Finns Study. Carotid intima-media thickness (IMT), a marker of subclinical atherosclerosis, was measured in 2001 and 2007. Baseline conventional risk factors and systemic metabolites were used to predict 6-year incidence of high IMT (≥90th percentile) or plaque. The best prediction of high intima-media thickness was achieved when total and HDL cholesterol were replaced by NMR-determined LDL cholesterol and medium HDL, docosahexaenoic acid, and tyrosine in prediction models with risk factors from the Framingham risk score. The extended prediction model improved risk stratification beyond established risk factors alone; area under the receiver operating characteristic curve 0.764 vs. 0.737, P =0.02, and net reclassification index 17.6%, P =0.0008. Higher docosahexaenoic acid levels were associated with decreased risk for incident high IMT (odds ratio: 0.74; 95% confidence interval: 0.67-0.98; P = 0.007). Tyrosine (1.33; 1.10-1.60; P = 0.003) and glutamine (1.38; 1.13-1.68; P = 0.001) levels were associated with 6-year incident high IMT independent of lipid measures. Furthermore, these amino acids were cross-sectionally associated with carotid IMT and the presence of angiographically ascertained coronary artery disease in independent populations. Conclusion High-throughput metabolite quantification, with new systemic biomarkers, improved risk stratification for subclinical atherosclerosis in comparison to conventional lipids and could potentially be useful for early cardiovascular risk assessment.     

Grading of Neuroendocrine Tumors With Ki-67 Requires High-quality Assessment Practices

Gastrointestinal and pancreatic neuroendocrine tumors (NETs) arise from disseminated neuroendocrine cells, expressing general and specific neuroendocrine markers. The World Health Organization 2010 classification of NETs is based on grading them according to the proliferation index (PI), which is determined by immunohistochemical staining of the nuclear antigen Ki-67. The classification introduces Ki-67 as the most important criterion for tumor grading, influencing patients' prognoses and the choice of treatment. The aim of this study was to evaluate the assessment of PI value in NETs and its influence on tumor grading. The tumor material consisted of 51 NETs from the pancreas (n=31) and ileum (n=20). The slides were stained with the Ki-67 antibody and visualized using a polymer kit. PI was assessed visually by microscope oculars and using a public domain image analysis software, ImmunoRatio. The PI was measured from the most proliferative areas of the tumor. The PI values and tumor grade by ImmunoRatio were highly reproducible as compared with conventional assessment, which suffered from variation especially if ascertained by different observers. Computer-aided assessments had almost perfect correlation (r=0.985, r=0.987, and r=0.995) (P=0.000) and reproducibility (κ=0.886, κ=0.886, and κ=1.000) (P=0.000) in PI values and tumor grades, respectively. The PI values and tumor grade between conventional and ImmunoRatio assessments by a qualified observer were in good agreement. ImmunoRatio is a qualified diagnostic aid to more objectively analyze Ki-67 PI-based tumor grade in NETs.     

Metabolic signatures of insulin resistance in 7,098 young adults

Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.     

When and how to start prevention of atherosclerosis? Lessons from the Cardiovascular Risk in the Young Finns Study and the Special Turku Coronary Risk Factor Intervention Project

This review provides an up-to-date summary of findings from two ongoing population-based, prospective studies conducted in Finland: The Cardiovascular Risk in Young Finns Study, and the Special Turku Coronary Risk Factor Intervention Project (STRIP), which have contributed significantly to the scientific literature concerning the childhood origin of cardiovascular disease, and whether prevention efforts in adults can be expanded to young people. From the Young Finns Study, we summarize evidence demonstrating childhood risk factors to be associated with both risk factors and preclinical markers of atherosclerosis in adulthood, and from STRIP, we summarize evidence showing that supervised dietary counseling of a low saturated fat diet effectively decreases exposure to cardiovascular risk factors without affecting growth and development of healthy children and adolescents. The evidence available from these studies supports that the ability to prevent or delay the risk of premature atherosclerosis and its clinical sequelae later in life lies in maintaining a low lifetime risk by preventing the development of risk factors in early life.