Regulated Expression of Human Histocompatibility Leukocyte Antigen (HLA)-DO During Antigen-dependent and Antigen-independent Phases of B Cell Development

Human histocompatibility leukocyte antigen (HLA)-DO, a lysosomal resident major histocompatibility complex class II molecule expressed in B cells, has previously been shown to be a negative regulator of HLA-DM peptide loading function. We analyze the expression of DO in human peripheral blood, lymph node, tonsil, and bone marrow to determine if DO expression is modulated in the physiological setting. B cells, but not monocytes or monocyte-derived dendritic cells, are observed to express this protein. Preclearing experiments demonstrate that ∼50% of HLA-DM is bound to DO in peripheral blood B cells. HLA-DM and HLA-DR expression is demonstrated early in B cell development, beginning at the pro-B stage in adult human bone marrow. In contrast, DO expression is initiated only after B cell development is complete. In all situations, there is a striking correlation between intracellular DO expression and cell surface class II–associated invariant chain peptide expression, which suggests that DO substantially inhibits DM function in primary human B cells. We report that the expression of DO is markedly downmodulated in human germinal center B cells. Modulation of DO expression may provide a mechanism to regulate peptide loading activity and antigen presentation by B cells during the development of humoral immune responses

Breast cancer risk and prevention in 2024: An overview from the Breast Cancer UK ‐ Breast Cancer Prevention Conference

The Breast Cancer UK—Breast Cancer Prevention Conference addressed risk from environmental pollutants and health behaviour‐related breast‐cancer risk. Epidemiological studies examining individual chemicals and breast cancer risk have produced inconclusive results including endocrine disrupting chemicals (EDCs) Bisphenol A, per‐ and polyfluorinated alkyl substances as well as aluminium. However, laboratory studies have shown that multiple EDCs, can work together to exhibit effects, even when combined at levels that alone are ineffective. The TEXB‐α/β assay measures total estrogenic load, and studies have provided evidence of a link between multiple‐chemical exposures and breast cancer. However, prospective studies using TEXB‐α/β are needed to establish a causative link. There is also a need to assess real‐life exposure to environmental‐chemical mixtures during pregnancy, and their potential involvement in programming adverse foetal health outcomes in later life. Higher rates of breast cancer have occurred alongside increases in potentially‐modifiable risk factors such as obesity. Increasing body‐mass index is associated with increased risk of developing postmenopausal breast cancer, but with decreased risk of premenopausal breast cancer. In contrast, lower rates of breast cancer in Asian compared to Western populations have been linked to soya/isoflavone consumption. Risk is decreased by breastfeeding, which is in addition to the decrease in risk observed for each birth and a young first‐birth. Risk is lower in those with higher levels of self‐reported physical activity. Current evidence suggests breast‐cancer survivors should also avoid weight gain, be physically active, and eat a healthy diet for overall health. A broad scientific perspective on breast cancer risk requires focus on both environmental exposure to chemicals and health behaviour‐related risk. Research into chemical exposure needs to focus on chemical mixtures and prospective epidemiological studies in order to test the effects on breast cancer risk. Behaviour‐related research needs to focus on implementation as well as deeper understanding of the mechanisms of cancer prevention

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

Genome-wide association study identifies 74 loci associated with educational attainment

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases

The Intestinal Eukaryotic Virome in Healthy and Diarrhoeic Neonatal Piglets.

Neonatal porcine diarrhoea of uncertain aetiology has been reported from a number of European countries. The aim of the present study was to use viral metagenomics to examine a potential viral involvement in this diarrhoea and to describe the intestinal virome with focus on eukaryotic viruses. Samples from the distal jejunum of 50 diarrhoeic and 19 healthy piglets from 10 affected herds were analysed. The viral fraction of the samples was isolated and nucleic acids (RNA and DNA fractions) were subjected to sequence independent amplification. Samples from diarrhoeic piglets from the same herds were pooled whereas samples from healthy piglets were analysed individually. In total, 29 clinical samples, plus two negative controls and one positive control consisting of a mock metagenome were sequenced using the Ion Torrent platform. The resulting sequence data was subjected to taxonomic classification using Kraken, Diamond and HMMER. In the healthy specimens, eight different mammalian virus families were detected (Adenoviridae, Anelloviridae, Astroviridae, Caliciviridae, Circoviridae, Parvoviridae, Picornaviridae, and Reoviridae) compared to four in the pooled diarrhoeic samples (Anelloviridae, Circoviridae, Picornaviridae, and Reoviridae). It was not possible to associate a particular virus family with the investigated diarrhoea. In conclusion, this study does not support the hypothesis that the investigated diarrhoea was caused by known mammalian viruses. The results do, however, indicate that known mammalian viruses were present in the intestine as early as 24-48 hours after birth, indicating immediate infection post-partum or possibly transplacental infection

MetLab: An In Silico Experimental Design, Simulation and Analysis Tool for Viral Metagenomics Studies.

Metagenomics, the sequence characterization of all genomes within a sample, is widely used as a virus discovery tool as well as a tool to study viral diversity of animals. Metagenomics can be considered to have three main steps; sample collection and preparation, sequencing and finally bioinformatics. Bioinformatic analysis of metagenomic datasets is in itself a complex process, involving few standardized methodologies, thereby hampering comparison of metagenomics studies between research groups. In this publication the new bioinformatics framework MetLab is presented, aimed at providing scientists with an integrated tool for experimental design and analysis of viral metagenomes. MetLab provides support in designing the metagenomics experiment by estimating the sequencing depth needed for the complete coverage of a species. This is achieved by applying a methodology to calculate the probability of coverage using an adaptation of Stevens' theorem. It also provides scientists with several pipelines aimed at simplifying the analysis of viral metagenomes, including; quality control, assembly and taxonomic binning. We also implement a tool for simulating metagenomics datasets from several sequencing platforms. The overall aim is to provide virologists with an easy to use tool for designing, simulating and analyzing viral metagenomes. The results presented here include a benchmark towards other existing software, with emphasis on detection of viruses as well as speed of applications. This is packaged, as comprehensive software, readily available for Linux and OSX users at https://github.com/norling/metlab

Cross-Sectional Variations in Structure and Function of Coral Reef Microbiome With Local Anthropogenic Impacts on the Kenyan Coast of the Indian Ocean

Coral reefs face an increased number of environmental threats from anthropomorphic climate change and pollution from agriculture, industries and sewage. Because environmental changes lead to their compositional and functional shifts, coral reef microbial communities can serve as indicators of ecosystem impacts through development of rapid and inexpensive molecular monitoring tools. Little is known about coral reef microbial communities of the Western Indian Ocean (WIO). We compared taxonomic and functional diversity of microbial communities inhabiting near-coral seawater and sediments from Kenyan reefs exposed to varying impacts of human activities. Over 19,000 species (bacterial, viral and archaeal combined) and 4,500 clusters of orthologous groups of proteins (COGs) were annotated. The coral reefs showed variations in the relative abundances of ecologically significant taxa, especially copiotrophic bacteria and coliphages, corresponding to the magnitude of the neighboring human impacts in the respective sites. Furthermore, the near-coral seawater and sediment metagenomes had an overrepresentation of COGs for functions related to adaptation to diverse environments. Malindi and Mombasa marine parks, the coral reef sites closest to densely populated settlements were significantly enriched with genes for functions suggestive of mitigation of environment perturbations including the capacity to reduce intracellular levels of environmental contaminants and repair of DNA damage. Our study is the first metagenomic assessment of WIO coral reef microbial diversity which provides a much-needed baseline for the region, and points to a potential area for future research toward establishing indicators of environmental perturbations

Number of samples from healthy piglets (n = 19) and pooled diarrhoeic samples (n = 10) positive for virus families known to infect mammals.

<p>Number of samples from healthy piglets (n = 19) and pooled diarrhoeic samples (n = 10) positive for virus families known to infect mammals.</p

Descriptive data on selected herds (n = 10, A-J) and piglets (n = 69).

<p>Descriptive data on selected herds (n = 10, A-J) and piglets (n = 69).</p