Increased Numbers of IL-7 Receptor Molecules on CD4+CD25−CD107a+ T-Cells in Patients with Autoimmune Diseases Affecting the Central Nervous System

BACKGROUND: High content immune profiling in peripheral blood may reflect immune aberrations associated with inflammation in multiple sclerosis (MS) and other autoimmune diseases affecting the central nervous system. METHODS AND FINDINGS: Peripheral blood mononuclear cells from 46 patients with multiple sclerosis (MS), 9 patients diagnosed with relapsing remitting MS (RRMS), 13 with secondary progressive multiple sclerosis (SPMS), 9 with other neurological diseases (OND) and well as 15 healthy donors (HD) were analyzed by 12 color flow cytometry (TCRalphabeta, TCRgammadelta, CD4, CD8alpha, CD8beta, CD45RA, CCR7, CD27, CD28, CD107a, CD127, CD14) in a cross-sectional study to identify variables significantly different between controls (HD) and patients (OND, RRMS, SPMS). We analyzed 187 individual immune cell subsets (percentages) and the density of the IL-7 receptor alpha chain (CD127) on 59 individual immune phenotypes using a monoclonal anti-IL-7R antibody (clone R34.34) coupled to a single APC molecule in combination with an APC-bead array. A non-parametric analysis of variance (Kruskal-Wallis test) was conducted in order to test for differences among the groups in each of the variables. To correct for the multiplicity problem, the FDR correction was applied on the p-values. We identified 19 variables for immune cell subsets (percentages) which allowed to segregate healthy individuals and individuals with CNS disorders. We did not observe differences in the relative percentage of IL-7R-positive immune cells in PBMCs. In contrast, we identified significant differences in IL-7 density, measured on a single cell level, in 2/59 variables: increased numbers of CD127 molecules on TCRalphabeta+CD4+CD25 (intermed) T-cells and on TCRalphabeta+CD4+CD25-CD107a+ T-cells (mean: 28376 Il-7R binding sites on cells from HD, 48515 in patients with RRMS, 38195 in patients with SPMS and 33692 IL-7 receptor binding sites on cells from patients with OND). CONCLUSION: These data show that immunophenotyping represents a powerful tool to differentiate healthy individuals from individuals suffering from neurological diseases and that the number of IL-7 receptor molecules on differentiated TCRalphabeta+CD4+CD25-CD107a+ T-cells, but not the percentage of IL-7R-positive cells, segregates healthy individuals from patients with neurological disorders

Bioaccumulation and Toxicity of Organic Chemicals in Terrestrial Invertebrates

Terrestrial invertebrates are key components in ecosystems, with crucial roles in soil structure, functioning, and ecosystem services. The present chapter covers how terrestrial invertebrates are impacted by organic chemicals, focusing on up-to-date information regarding bioavailability, exposure routes and general concepts on bioaccumulation, toxicity, and existing models. Terrestrial invertebrates are exposed to organic chemicals through different routes, which are dependent on both the organismal traits and nature of exposure, including chemical properties and media characteristics. Bioaccumulation and toxicity data for several groups of organic chemicals are presented and discussed, attempting to cover plant protection products (herbicides, insecticides, fungicides, and molluscicides), veterinary and human pharmaceuticals, polycyclic aromatic compounds, polychlorinated biphenyls, flame retardants, and personal care products. Chemical mixtures are also discussed bearing in mind that chemicals appear simultaneously in the environment. The biomagnification of organic chemicals is considered in light of the consumption of terrestrial invertebrates as novel feed and food sources. This chapter highlights how science has contributed with data from the last 5 years, providing evidence on bioavailability, bioaccumulation, and toxicity derived from exposure to organic chemicals, including insights into the main challenges and shortcomings to extrapolate results to real exposure scenarios

Mammary Involution and Breast Cancer Risk: Transgenic Models and Clinical Studies

Postlactational involution is the process following weaning during which the mammary gland undergoes massive cell death and tissue remodeling as it returns to the pre-pregnant state. Lobular involution is the process by which the breast epithelial tissue is gradually lost with aging of the mammary gland. While postlactational involution and lobular involution are distinct processes, recent studies have indicated that both are related to breast cancer development. Experiments using a variety of rodent models, as well as observations in human populations, suggest that deregulation of postlactational involution may act to facilitate tumor formation. By contrast, new human studies show that completion of lobular involution protects against subsequent breast cancer incidence

Genome-wide association studies of cancer: current insights and future perspectives.

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries