Comparisons of PNEC derivation logic flows under example regulatory schemes and implications for ecoTTC.

Derivation of Predicted No Effect Concentrations (PNECs) for aquatic systems is the primary deterministic form of hazard extrapolation used in environmental risk assessment. Depending on the data availability, different regulatory jurisdictions apply application factors (AFs) to the most sensitive measured endpoint to derive the PNEC for a chemical. To assess differences in estimated PNEC values, two PNEC determination methodologies were applied to a curated public database using the EnviroTox Platform (www.EnviroToxdatabase.org). PNECs were derived for 3647 compounds using derivation procedures based on example US EPA and a modified European Union chemical registration procedure to allow for comparisons. Ranked probability distributions of PNEC values were developed and 5th percentile values were calculated for the entire dataset and scenarios where full acute or full chronic data sets were available. The lowest PNEC values indicated categorization based on chemical attributes and modes of action would lead to improved extrapolations. Full acute or chronic datasets gave measurably higher 5th percentile PNEC values. Algae were under-represented in available ecotoxicity data but drove PNECs disproportionately. Including algal inhibition studies will be important in understanding chemical hazards. The PNEC derivation logic flows are embedded in the EnviroTox Platform providing transparent and consistent PNEC derivations and PNEC distribution calculations.

Mode of Action (MOA) Assignment Classifications for Ecotoxicology: An Evaluation of Approaches.

The mode of toxic action (MOA) is recognized as a key determinant of chemical toxicity and as an alternative to chemical class-based predictive toxicity modeling. However, MOA classification has never been standardized in ecotoxicology, and a comprehensive comparison of classification tools and approaches has never been reported. Here we critically evaluate three MOA classification methodologies using an aquatic toxicity data set of 3448 chemicals, compare the approaches, and assess utility and limitations in screening and early tier assessments. The comparisons focused on three commonly used tools: Verhaar prediction of toxicity MOA, the U.S. Environmental Protection Agency (EPA) ASsessment Tool for Evaluating Risk (ASTER) QSAR (quantitative structure activity relationship) application, and the EPA Mode of Action and Toxicity (MOAtox) database. Of the 3448 MOAs predicted using the Verhaar scheme, 1165 were classified by ASTER, and 802 were available in MOAtox. Of the subset of 432 chemicals with MOA assignments for each of the three schemes, 42% had complete concordance in MOA classification, and there was no agreement for 7% of the chemicals. The research shows the potential for large differences in MOA classification between the five broad groups of the Verhaar scheme and the more mechanism-based assignments of ASTER and MOAtox. Harmonization of classification schemes is needed to use MOA classification in chemical hazard and risk assessment more broadly.

The role of genomics in common variable immunodeficiency disorders.

The advent of next-generation sequencing (NGS) and 'omic' technologies has revolutionized the field of genetics, and its implementation in health care has the potential to realize precision medicine. Primary immunodeficiencies (PID) are a group of rare diseases which have benefited from NGS, with a massive increase in causative genes identified in the past few years. Common variable immunodeficiency disorders (CVID) are a heterogeneous form of PID and the most common form of antibody failure in children and adults. While a monogenic cause of disease has been identified in a small subset of CVID patients, a genomewide association study and whole genome sequencing have found that, in the majority, a polygenic cause is likely. Other NGS technologies such as RNA sequencing and epigenetic studies have contributed further to our understanding of the contribution of altered gene expression in CVID pathogenesis. We believe that to unravel further the complexities of CVID, a multi-omic approach, combining DNA sequencing with gene expression, methylation, proteomic and metabolomics data, will be essential to identify novel disease-associated pathways and therapeutic targets.

A mutation in X-linked inhibitor of apoptosis (G466X) leads to memory inflation of Epstein-Barr virus-specific T cells.

Mutations in the X-linked inhibitor of apoptosis (XIAP) gene have been associated with XLP-like disease, including recurrent Epstein-Barr virus (EBV)-related haemophagocytic lymphohystiocytosis (HLH), but the immunopathogenic bases of EBV-related disease in XIAP deficiency is unknown. We present the first analysis of EBV-specific T cell responses in functional XIAP deficiency. In a family of patients with a novel mutation in XIAP (G466X) leading to a late-truncated protein and varying clinical features, we identified gradual hypogammaglobulinaemia and large expansions of T cell subsets, including a prominent CD4(+) CD8(+) population. Extensive ex-vivo analyses showed that the expanded T cell subsets were dominated by EBV-specific cells with conserved cytotoxic, proliferative and interferon (IFN)-γ secretion capacity. The EBV load in blood fluctuated and was occasionally very high, indicating that the XIAP(G466X) mutation could impact upon EBV latency. XIAP deficiency may unravel a new immunopathogenic mechanism in EBV-associated disease.