Lineage-dependent effects of aryl hydrocarbon receptor agonists contribute to liver tumorigenesis

Rodent cancer bioassays indicate that the aryl hydrocarbon receptor (AHR) agonist, 2,3,7,8-tetracholorodibenzo-p-dioxin (TCDD), causes increases in both hepatocytic and cholangiocytic tumors. Effects of AHR activation have been evaluated on rodent hepatic stem cells (rHpSCs) versus their descendants, hepatoblasts (rHBs), two lineage stages of multipotent, hepatic precursors with overlapping but also distinct phenotypic traits. This was made possible by defining the first successful culture conditions for ex vivo maintenance of rHpScs consisting of a substratum of hyaluronans and Kubota's medium (KM), a serum-free medium designed for endodermal stem/progenitor cells. Supplementation of KM with leukemia inhibitory factor elicited lineage restriction to rHBs. Cultures were treated with various AHR agonists including TCDD, 6-formylindolo-[3,2-b]carbazole (FICZ), and 3-3'-diindolylmethane (DIM) and then analyzed with a combination of immunocytochemistry, gene expression, and high-content image analysis. The AHR agonists increased proliferation of rHpSCs at concentrations producing a persistent AHR activation as indicated by induction of Cyp1a1. By contrast, treatment with TCDD resulted in a rapid loss of viability of rHBs, even though the culture conditions, in the absence of the agonists, were permissive for survival and expansion of rHBs. The effects were not observed with FICZ and at lower concentrations of DIM. Conclusion: Our findings are consistent with a lineage-dependent mode of action for AHR agonists in rodent liver tumorigenesis through selective expansion of rHpSCs in combination with a toxicity-induced loss of viability of rHBs. These lineage-dependent effects correlate with increased frequency of liver tumors. (Hepatology 2015;61:548-560

An epigenetic clock for human skeletal muscle.

BACKGROUND: Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue. METHODS: To address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study of age-associated DNA methylation patterns in skeletal muscle. RESULTS: The newly developed clock uses 200 cytosine-phosphate-guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine-phosphate-guanine dinucleotides of the pan-tissue clock. The muscle clock outperformed the pan-tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan-tissue clock, P < 0.0001) and an average correlation of ρ = 0.62 between actual and predicted age across datasets (vs. ρ = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies. CONCLUSIONS: We have developed a muscle-specific epigenetic clock that predicts age with better accuracy than the pan-tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle-specific biological ageing processes

Changes in body composition and performance with supplemental HMB-FA+ATP (Manuscript Clarification)

Additional co-authors: Matthew D. Vukovich, Colin Wilborn, and Darryn S. Willoughb

Incorporating New Technologies Into Toxicity Testing and Risk Assessment: Moving From 21st Century Vision to a Data-Driven Framework

Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency

The short-term effect of high versus moderate protein intake on recovery after strength training in resistance-trained individuals

Background: Dietary protein intakes up to 2.9 g.kg-1.d-1 and protein consumption before and after resistance training may enhance recovery, resulting in hypertrophy and strength gains. However, it remains unclear whether protein quantity or nutrient timing is central to positive adaptations. This study investigated the effect of total dietary protein content, whilst controlling for protein timing, on recovery in resistance trainees. Methods: Fourteen resistance-trained individuals underwent two 10-day isocaloric dietary regimes with a protein content of 1.8 g.kg-1.d-1 (PROMOD) or 2.9 g.kg-1.d-1 (PROHIGH) in a randomised, counterbalanced, crossover design. On days 8-10 (T1-T3), participants undertook resistance exercise under controlled conditions, performing 3 sets of squat, bench press and bent-over rows at 80% 1 repetition maximum until volitional exhaustion. Additionally, participants consumed a 0.4 g.kg-1 whey protein concentrate/isolate mix 30 minutes before and after exercise sessions to standardise protein timing specific to training. Recovery was assessed via daily repetition performance, muscle soreness, bioelectrical impedance phase angle, plasma creatine kinase (CK) and tumor necrosis factor-α (TNF-α). Results: No significant differences were reported between conditions for any of the performance repetition count variables (p>0.05). However, within PROMOD only, squat performance total repetition count was significantly lower at T3 (19.7 ± 6.8) compared to T1 (23.0 ± 7.5; p=0.006). Pre and post-exercise CK concentrations significantly increased across test days (p≤0.003), although no differences were reported between conditions. No differences for TNF-α or muscle soreness were reported between dietary conditions. Phase angle was significantly greater at T3 for PROHIGH (8.26 ± 0.82°) compared with PROMOD (8.08 ± 0.80°; p=0.012). Conclusions: When energy intake and peri-exercise protein intake was controlled for, a short term PROHIGH diet did not improve markers of muscle damage or soreness in comparison to a PROMOD approach following repeated days of intensive training. Whilst it is therefore likely that protein intakes (1.8g.kg-1.d-1) may be sufficient for resistance-trained individuals, it is noteworthy that both lower body exercise performance and bioelectrical phase angle were maintained with PROHIGH. Longer term interventions are warranted to determine whether PROMOD intakes are sufficient during prolonged training periods or when extensive exercise (e.g. training twice daily) is undertaken

Resistance to pirimiphos-methyl in West African Anopheles is spreading via duplication and introgression of the Ace1 locus

Vector population control using insecticides is a key element of current strategies to prevent malaria transmission in Africa. The introduction of effective insecticides, such as the organophosphate pirimiphos-methyl, is essential to overcome the recurrent emergence of resistance driven by the highly diverse Anopheles genomes. Here, we use a population genomic approach to investigate the basis of pirimiphos-methyl resistance in the major malaria vectors Anopheles gambiae and A. coluzzii. A combination of copy number variation and a single non-synonymous substitution in the acetylcholinesterase gene, Ace1, provides the key resistance diagnostic in an A. coluzzii population from Coˆte d’Ivoire that we used for sequence-based association mapping, with replication in other West African populations. The Ace1 substitution and duplications occur on a unique resistance haplotype that evolved in A. gambiae and introgressed into A. coluzzii, and is now common in West Africa primarily due to selection imposed by other organophosphate or carbamate insecticides. Our findings highlight the predictive value of this complex resistance haplotype for phenotypic resistance and clarify its evolutionary history, providing tools to for molecular surveillance of the current and future effectiveness of pirimiphos-methyl based interventions

Double-stranded RNA-activated protein kinase PKR of fishes and amphibians: Varying the number of double-stranded RNA binding domains and lineage-specific duplications

BackgroundDouble-stranded (ds) RNA, generated during viral infection, binds and activates the mammalian anti-viral protein kinase PKR, which phosphorylates the translation initiation factor eIF2alpha leading to the general inhibition of protein synthesis. Although PKR-like activity has been described in fish cells, the responsible enzymes eluded molecular characterization until the recent discovery of goldfish and zebrafish PKZ, which contain Z-DNA-binding domains instead of dsRNA-binding domains (dsRBDs). Fish and amphibian PKR genes have not been described so far.ResultsHere we report the cloning and identification of 13 PKR genes from 8 teleost fish and amphibian species, including zebrafish, demonstrating the coexistence of PKR and PKZ in this latter species. Analyses of their genomic organization revealed up to three tandemly arrayed PKR genes, which are arranged in head-to-tail orientation. At least five duplications occurred independently in fish and amphibian lineages. Phylogenetic analyses reveal that the kinase domains of fish PKR genes are more closely related to those of fish PKZ than to the PKR kinase domains of other vertebrate species. The duplication leading to fish PKR and PKZ genes occurred early during teleost fish evolution after the divergence of the tetrapod lineage. While two dsRBDs are found in mammalian and amphibian PKR, one, two or three dsRBDs are present in fish PKR. In zebrafish, both PKR and PKZ were strongly upregulated after immunostimulation with some tissue-specific expression differences. Using genetic and biochemical assays we demonstrate that both zebrafish PKR and PKZ can phosphorylate eIF2alpha in yeast.ConclusionConsidering the important role for PKR in host defense against viruses, the independent duplication and fixation of PKR genes in different lineages probably provided selective advantages by leading to the recognition of an extended spectrum of viral nucleic acid structures, including both dsRNA and Z-DNA/RNA, and perhaps by altering sensitivity to viral PKR inhibitors. Further implications of our findings for the evolution of the PKR family and for studying PKR/PKZ interactions with viral gene products and their roles in viral infections are discussed

Incidence of Schizophrenia and Other Psychoses in England, 1950–2009: A Systematic Review and Meta-Analyses

Background We conducted a systematic review of incidence rates in England over a sixty-year period to determine the extent to which rates varied along accepted (age, sex) and less-accepted epidemiological gradients (ethnicity, migration and place of birth and upbringing, time). Objectives To determine variation in incidence of several psychotic disorders as above. Data Sources Published and grey literature searches (MEDLINE, PSycINFO, EMBASE, CINAHL, ASSIA, HMIC), and identification of unpublished data through bibliographic searches and author communication. Study Eligibility Criteria Published 1950–2009; conducted wholly or partially in England; original data on incidence of non-organic adult-onset psychosis or one or more factor(s) pertaining to incidence. Participants People, 16–64 years, with first -onset psychosis, including non-affective psychoses, schizophrenia, bipolar disorder, psychotic depression and substance-induced psychosis. Study Appraisal and Synthesis Methods Title, abstract and full-text review by two independent raters to identify suitable citations. Data were extracted to a standardized extraction form. Descriptive appraisals of variation in rates, including tables and forest plots, and where suitable, random-effects meta-analyses and meta-regressions to test specific hypotheses; rate heterogeneity was assessed by the I2-statistic. Results 83 citations met inclusion. Pooled incidence of all psychoses (N = 9) was 31.7 per 100,000 person-years (95%CI: 24.6–40.9), 23.2 (95%CI: 18.3–29.5) for non-affective psychoses (N = 8), 15.2 (95%CI: 11.9–19.5) for schizophrenia (N = 15) and 12.4 (95%CI: 9.0–17.1) for affective psychoses (N = 7). This masked rate heterogeneity (I2: 0.54–0.97), possibly explained by socio-environmental factors; our review confirmed (via meta-regression) the typical age-sex interaction in psychosis risk, including secondary peak onset in women after 45 years. Rates of most disorders were elevated in several ethnic minority groups compared with the white (British) population. For example, for schizophrenia: black Caribbean (pooled RR: 5.6; 95%CI: 3.4–9.2; N = 5), black African (pooled RR: 4.7; 95%CI: 3.3–6.8; N = 5) and South Asian groups in England (pooled RR: 2.4; 95%CI: 1.3–4.5; N = 3). We found no evidence to support an overall change in the incidence of psychotic disorder over time, though diagnostic shifts (away from schizophrenia) were reported. Limitations Incidence studies were predominantly cross-sectional, limiting causal inference. Heterogeneity, while evidencing important variation, suggested pooled estimates require interpretation alongside our descriptive systematic results. Conclusions and Implications of Key Findings Incidence of psychotic disorders varied markedly by age, sex, place and migration status/ethnicity. Stable incidence over time, together with a robust socio-environmental epidemiology, provides a platform for developing prediction models for health service planning

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495