A UK framework for the assessment and integration of different scientific evidence streams in chemical risk assessment.

BACKGROUND: Few methods are available for transparently combining different evidence streams for chemical risk assessment to reach an integrated conclusion on the probability of causation. Hence, the UK Committees on Toxicity (COT) and on Carcinogenicity (COC) have reviewed current practice and developed guidance on how to achieve this in a transparent manner, using graphical visualisation. METHODS/APPROACH: All lines of evidence, including toxicological, epidemiological, new approach methodologies, and mode of action should be considered, taking account of their strengths/weaknesses in their relative weighting towards a conclusion on the probability of causation. A qualitative estimate of the probability of causation is plotted for each line of evidence and a combined estimate provided. DISCUSSION/CONCLUSIONS: Guidance is provided on integration of multiple lines of evidence for causation, based on current best practice. Qualitative estimates of probability for each line of evidence are plotted graphically. This ensures a deliberative, consensus conclusion on likelihood of causation is reached. It also ensures clear communication of the influence of the different lines of evidence on the overall conclusion on causality. Issues on which advice from the respective Committees is sought varies considerably, hence the guidance is designed to be sufficiently flexible to meet this need.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT).

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Interpretation of in vitro concentration-response data for risk assessment and regulatory decision-making: Report from the 2022 IWGT quantitative analysis expert working group meeting.

Quantitative risk assessments of chemicals are routinely performed using in vivo data from rodents; however, there is growing recognition that non-animal approaches can be human-relevant alternatives. There is an urgent need to build confidence in non-animal alternatives given the international support to reduce the use of animals in toxicity testing where possible. In order for scientists and risk assessors to prepare for this paradigm shift in toxicity assessment, standardization and consensus on in vitro testing strategies and data interpretation will need to be established. To address this issue, an Expert Working Group (EWG) of the 8th International Workshop on Genotoxicity Testing (IWGT) evaluated the utility of quantitative in vitro genotoxicity concentration-response data for risk assessment. The EWG first evaluated available in vitro methodologies and then examined the variability and maximal response of in vitro tests to estimate biologically relevant values for the critical effect sizes considered adverse or unacceptable. Next, the EWG reviewed the approaches and computational models employed to provide human-relevant dose context to in vitro data. Lastly, the EWG evaluated risk assessment applications for which in vitro data are ready for use and applications where further work is required. The EWG concluded that in vitro genotoxicity concentration-response data can be interpreted in a risk assessment context. However, prior to routine use in regulatory settings, further research will be required to address the remaining uncertainties and limitations.

Performance of tumour microenvironment deconvolution methods in breast cancer using single-cell simulated bulk mixtures.

Cells within the tumour microenvironment (TME) can impact tumour development and influence treatment response. Computational approaches have been developed to deconvolve the TME from bulk RNA-seq. Using scRNA-seq profiling from breast tumours we simulate thousands of bulk mixtures, representing tumour purities and cell lineages, to compare the performance of nine TME deconvolution methods (BayesPrism, Scaden, CIBERSORTx, MuSiC, DWLS, hspe, CPM, Bisque, and EPIC). Some methods are more robust in deconvolving mixtures with high tumour purity levels. Most methods tend to mis-predict normal epithelial for cancer epithelial as tumour purity increases, a finding that is validated in two independent datasets. The breast cancer molecular subtype influences this mis-prediction. BayesPrism and DWLS have the lowest combined numbers of false positives and false negatives, and have the best performance when deconvolving granular immune lineages. Our findings highlight the need for more single-cell characterisation of rarer cell types, and suggest that tumour cell compositions should be considered when deconvolving the TME.

Assessing the quality and making appropriate use of historical negative control data: A report of the International Workshop on Genotoxicity Testing (IWGT).

Historical negative control data (HCD) have played an increasingly important role in interpreting the results of genotoxicity tests. In particular, Organisation for Economic Co-operation and Development (OECD) genetic toxicology test guidelines recommend comparing responses produced by exposure to test substances with the distribution of HCD as one of three criteria for evaluating and interpreting study results (referred to herein as "Criterion C"). Because of the potential for inconsistency in how HCD are acquired, maintained, described, and used to interpret genotoxicity testing results, a workgroup of the International Workshops for Genotoxicity Testing was convened to provide recommendations on this crucial topic. The workgroup used example data sets from four in vivo tests, the Pig-a gene mutation assay, the erythrocyte-based micronucleus test, the transgenic rodent gene mutation assay, and the in vivo alkaline comet assay to illustrate how the quality of HCD can be evaluated. In addition, recommendations are offered on appropriate methods for evaluating HCD distributions. Recommendations of the workgroup are: When concurrent negative control data fulfill study acceptability criteria, they represent the most important comparator for judging whether a particular test substance induced a genotoxic effect. HCD can provide useful context for interpreting study results, but this requires supporting evidence that (i) HCD were generated appropriately, and (ii) their quality has been assessed and deemed sufficiently high for this purpose. HCD should be visualized before any study comparisons take place; graph(s) that show the degree to which HCD are stable over time are particularly useful. Qualitative and semi-quantitative assessments of HCD should also be supplemented with quantitative evaluations. Key factors in the assessment of HCD include: (i) the stability of HCD over time, and (ii) the degree to which inter-study variation explains the total variability observed. When animal-to-animal variation is the predominant source of variability, the relationship between responses in the study and an HCD-derived interval or upper bounds value (i.e., OECD Criterion C) can be used with a strong degree of confidence in contextualizing a particular study's results. When inter-study variation is the major source of variability, comparisons between study data and the HCD bounds are less useful, and consequentially, less emphasis should be placed on using HCD to contextualize a particular study's results. The workgroup findings add additional support for the use of HCD for data interpretation; but relative to most current OECD test guidelines, we recommend a more flexible application that takes into consideration HCD quality. The workgroup considered only commonly used in vivo tests, but it anticipates that the same principles will apply to other genotoxicity tests, including many in vitro tests.

Exploring technologies to better link physical evidence and digital information for disaster victim identification.

Disaster victim identification (DVI) entails a protracted process of evidence collection and data matching to reconcile physical remains with victim identity. Technology is critical to DVI by enabling the linkage of physical evidence to information. However, labelling physical remains and collecting data at the scene are dominated by low-technology paper-based practices. We ask, how can technology help us tag and track the victims of disaster? Our response to this question has two parts. First, we conducted a human-computer interaction led investigation into the systematic factors impacting DVI tagging and tracking processes. Through interviews with Australian DVI practitioners, we explored how technologies to improve linkage might fit with prevailing work practices and preferences; practical and social considerations; and existing systems and processes. We focused on tagging and tracking activities throughout the DVI process. Using insights from these interviews and relevant literature, we identified four critical themes: protocols and training; stress and stressors; the plurality of information capture and management systems; and practicalities and constraints. Second, these findings were iteratively discussed by the authors, who have combined expertise across electronics, data science, cybersecurity, human-computer interaction and forensic pathology. We applied the themes identified in the first part of the investigation to critically review technologies that could support DVI practitioners by enhancing DVI processes that link physical evidence to information. This resulted in an overview of candidate technologies matched with consideration of their key attributes. This study recognises the importance of considering human factors that can affect technology adoption into existing practices. Consequently, we provide a searchable table (as Supplementary information) that relates technologies to the key considerations and attributes relevant to DVI practice, for readers to apply to their own context. While this research directly contributes to DVI, it also has applications to other domains in which a physical/digital linkage is required, and particularly within high stress environments with little room for error.Key points:Disaster victim identification (DVI) processes require us to link physical evidence and digital information. While technology could improve this linkage, experience shows that technological "solutions" are not always adopted in practice.Our study of the practices, preferences and contexts of Australian DVI practitioners suggests 10 critical considerations for these technologies.We review and evaluate 44 candidate technologies against these considerations and highlight the role of human factors in adoption.

A comparison of the lowest effective concentration in culture media for detection of chromosomal damage in vitro and in blood or plasma for detection of micronuclei in vivo.

It is often assumed that genotoxic substances will be detected more easily by using in vitro rather than in vivo genotoxicity tests since higher concentrations, more cytotoxicity and static exposures can be achieved. However, there is a paucity of data demonstrating whether genotoxic substances are detected at lower concentrations in cell culture in vitro than can be reached in the blood of animals treated in vivo. To investigate this issue, we compared the lowest concentration required for induction of chromosomal damage in vitro (lowest observed effective concentration, or LOEC) with the concentration of the test substance in blood at the lowest dose required for biologically relevant induction of micronuclei in vivo (lowest observed effective dose, or LOED). In total, 83 substances were found for which the LOED could be identified or estimated, where concentrations in blood and micronucleus data were available via the same route of administration in the same species, and in vitro chromosomal damage data were available. 39.8 % of substances were positive in vivo at blood concentrations that were lower than the LOEC in vitro, 22.9 % were positive at similar concentrations, and 37.3 % of substances were positive in vivo at higher concentrations. Distribution analysis showed a very wide scatter of > 6 orders of magnitude across these 3 categories. When mode of action was evaluated, the distribution of clastogens and aneugens across the 3 categories was very similar. Thus, the ability to detect induction of micronuclei in bone marrow in vivo regardless of the mechanism for micronucleus induction, is clearly not solely determined by the concentration of test substance which induced chromosomal damage in vitro.

Commentary: statistical analysis of 2 × 2 tables in biomarker studies 2) study design and statistical tests.

In this article the importance of study design will be emphasized, statistical methods for analysing the data are described and some of the implications of these method are discussed. How these issues relate to the use of SpIN and SnOUT rules are reviewed.

Commentary: statistical analysis of 2 × 2 tables in biomarker studies 3) design, interpretation and guidelines.

This article discusses issues associated with the design and interpretation of biomarker studies, points to various guidelines and lists points to look out for in assessing studies.

Commentary: statistical analysis of 2 × 2 tables in biomarker studies 1) the four 'indices of test validity'.

Diagnostic statistics such as sensitivity and specificity are widely used in the assessment of biomarkers. Interpretation of these and other statistics derived from a 2 × 2 table can be complex. The properties of the commonly used statistics are discussed. The object is to provide help in their interpretation for authors designing studies and the subsequent reporting of results and to referees and others who assess such papers.

Metagenomic Geolocation Using Read Signatures.

We present a novel approach to the Metagenomic Geolocation Challenge based on random projection of the sample reads from each location. This approach explores the direct use of k-mer composition to characterise samples so that we can avoid the computationally demanding step of aligning reads to available microbial reference sequences. Each variable-length read is converted into a fixed-length, k-mer-based read signature. Read signatures are then clustered into location signatures which provide a more compact characterisation of the reads at each location. Classification is then treated as a problem in ranked retrieval of locations, where signature similarity is used as a measure of similarity in microbial composition. We evaluate our approach using the CAMDA 2020 Challenge dataset and obtain promising results based on nearest neighbour classification. The main findings of this study are that k-mer representations carry sufficient information to reveal the origin of many of the CAMDA 2020 Challenge metagenomic samples, and that this reference-free approach can be achieved with much less computation than methods that need reads to be assigned to operational taxonomic units-advantages which become clear through comparison to previously published work on the CAMDA 2019 Challenge data.

Recommendations for conducting the rodent erythrocyte Pig-a assay: A report from the HESI GTTC Pig-a Workgroup.

The rodent Pig-a assay is a flow cytometric, phenotype-based method used to measure in vivo somatic cell mutation. An Organization for Economic Co-operation and Development (OECD) test guideline is currently being developed to support routine use of the assay for regulatory purposes (OECD project number 4.93). This article provides advice on best practices for designing and conducting rodent Pig-a studies in support of evaluating test substance safety, with a focus on the rat model. Various aspects of assay conduct, including laboratory proficiency, minimum number of animals per dose group, preferred treatment and blood sampling schedule, and statistical analysis are described.

Assessment of systemic genetic damage in pediatric inflammatory bowel disease.

The etiology of distal site cancers in inflammatory bowel disease (IBD) is not well understood and requires further study. We investigated whether pediatric IBD patients' blood cells exhibit elevated levels of genomic damage by measuring the frequency of mutant phenotype (CD59-/CD55-) reticulocytes (MUT RET) as a reporter of PIG-A mutation, and the frequency of micronucleated reticulocytes (MN-RET) as an indicator of chromosomal damage. IBD patients (n = 18 new-onset disease, 46 established disease) were compared to age-matched controls (constipation or irritable bowel syndrome patients from the same clinic, n = 30) and young healthy adults age 19-24 (n = 25). IBD patients showed no indication of elevated MUT RET relative to controls (mean ± SD = 3.1 ± 2.3 × 10-6 vs. 3.6 ± 5.6 x 10-6 , respectively). In contrast, 59 IBD patients where %MN-RET measurements were obtained, 10 exceeded the upper bound 90% tolerance interval derived from control subjects (i.e., 0.42%). Furthermore, each of the 10 IBD patients with elevated MN-RET had established disease (10/42), none were new-onset (0/17) (p = .049). Interestingly, each of the subjects with increased chromosomal damage was receiving anti-TNF based monotherapy at the time blood was collected (10/10, 100%), whereas this therapy was less common (20/32, 63%) among patients that exhibited ≤0.42% MN-RET (p = .040). The results clearly indicate the need for further work to understand whether the results presented herein are reproducible and if so, to elucidate the causative factor(s) responsible for elevated MN-RET frequencies in some IBD patients.

Human blood PIG-A mutation and micronucleated reticulocyte flow cytometric assays: Method optimization and evaluation of intra- and inter-subject variation.

We previously described flow cytometry-based methods for scoring the incidence of micronucleated reticulocytes (MN-RET) and PIG-A mutant phenotype reticulocytes (MUT RET) in rodent and human blood samples. The current report describes important methodological improvements for human blood analyses, including immunomagnetic enrichment of CD71-positive reticulocytes prior to MN-RET scoring, and procedures for storing frozen blood for later PIG-A analysis. Technical replicate variability in MN-RET and MUT RET frequencies based on blood specimens from 14 subjects, intra-subject variability based on serial blood draws from 6 subjects, and inter-subject variation based on up to 344 subjects age 0 to 73 years were quantified. Inter-subject variation explained most of the variability observed for both endpoints (≥77%), with much lower intra-subject and technical replicate variability. The relatively large degree of inter-subject variation is apparent from mean and standard deviation values for MN-RET (0.15 ± 0.10%) and MUT RET (4.7 ± 5.0 per million, after omission of two extreme outliers). The influences of age and sex on inter-subject variation were investigated, and neither factor affected MN-RET whereas both influenced MUT RET frequency. The lowest MUT RET values were observed for subjects <11 years old, and males had moderately higher frequencies than females. These results indicate that MN-RET and MUT RET are automation-compatible biomarkers of genotoxicity that bridge species of toxicological interest to include human populations. These data will be useful for appropriately designing future human studies that include these biomarkers of genotoxicity, and highlight the need for additional work aimed at identifying the sources of inter-individual variability reported herein.

Psychological Distress in Solitary Confinement: Symptoms, Severity, and Prevalence in the United States, 2017-2018.

Objectives. To specify symptoms and measure prevalence of psychological distress among incarcerated people in long-term solitary confinement.Methods. We gathered data via semistructured, in-depth interviews; Brief Psychiatric Rating Scale (BPRS) assessments; and systematic reviews of medical and disciplinary files for 106 randomly selected people in solitary confinement in the Washington State Department of Corrections in 2017. We performed 1-year follow-up interviews and BPRS assessments with 80 of these incarcerated people, and we present the results of our qualitative content analysis and descriptive statistics.Results. BPRS results showed clinically significant symptoms of depression, anxiety, or guilt among half of our research sample. Administrative data showed disproportionately high rates of serious mental illness and self-harming behavior compared with general prison populations. Interview content analysis revealed additional symptoms, including social isolation, loss of identity, and sensory hypersensitivity.Conclusions. Our coordinated study of rating scale, interview, and administrative data illustrates the public health crisis of solitary confinement. Because 95% or more of all incarcerated people, including those who experienced solitary confinement, are eventually released, understanding disproportionate psychopathology matters for developing prevention policies and addressing the unique needs of people who have experienced solitary confinement, an extreme element of mass incarceration.

Null hypothesis significance testing and effect sizes: can we 'effect' everything or anything?

The Null Hypothesis Significance Testing (NHST) paradigm is increasingly criticized. Estimation approaches such as point estimates and confidence intervals, while having limitations, provide better descriptions of results than P-values and statements about significance levels. Their use is supported by many statisticians. The effect size approach is an important part of power and sample size calculations at the experimental design stage and in meta-analysis and in the interpretation of the biological importance of study results. Care is needed, however, to ensure that such effect sizes are relevant for the endpoint. Effect sizes should not be used to interpret results without accompanying limits, such as confidence intervals. New methods, especially Bayesian approaches, are being developed; however, no single method provides a simple answer. Rather there is a need to improve researchers understanding of the complex issues underlying experimental design, statistical analysis and interpretation of results.

Counts: an outstanding challenge for log-ratio analysis of compositional data in the molecular biosciences.

Thanks to sequencing technology, modern molecular bioscience datasets are often compositions of counts, e.g. counts of amplicons, mRNAs, etc. While there is growing appreciation that compositional data need special analysis and interpretation, less well understood is the discrete nature of these count compositions (or, as we call them, lattice compositions) and the impact this has on statistical analysis, particularly log-ratio analysis (LRA) of pairwise association. While LRA methods are scale-invariant, count compositional data are not; consequently, the conclusions we draw from LRA of lattice compositions depend on the scale of counts involved. We know that additive variation affects the relative abundance of small counts more than large counts; here we show that additive (quantization) variation comes from the discrete nature of count data itself, as well as (biological) variation in the system under study and (technical) variation from measurement and analysis processes. Variation due to quantization is inevitable, but its impact on conclusions depends on the underlying scale and distribution of counts. We illustrate the different distributions of real molecular bioscience data from different experimental settings to show why it is vital to understand the distributional characteristics of count data before applying and drawing conclusions from compositional data analysis methods.

In vivo genotoxicity testing strategies: Report from the 7th International workshop on genotoxicity testing (IWGT).

The working group reached complete or majority agreement on many issues. Results from TGR and in vivo comet assays for 91 chemicals showed they have similar ability to detect in vivo genotoxicity per se with bacterial mutagens and Ames-positive carcinogens. TGR and comet assay results were not significantly different when compared with IARC Group 1, 2 A, and unclassified carcinogens. There were significantly more comet assay positive responses for Group 2B chemicals, and for IARC classified and unclassified carcinogens combined, which may be expected since mutation is a sub-set of genotoxicity. A liver comet assay combined with the bone marrow/blood micronucleus (MNviv) test would detect in vivo genotoxins that do not exhibit tissue-specific or site-of-contact effects, and is appropriate for routine in vivo genotoxicity testing. Generally for orally administered substances, a comet assay at only one site-of-contact GI tract tissue (stomach or duodenum/jejunum) is required. In MNviv tests, evidence of target tissue exposure can be obtained in a number of different ways, as recommended by ICH S2(R1) and EFSA (Hardy et al., 2017). Except for special cases the i.p. route is inappropriate for in vivo testing; for risk evaluations more weight should be given to data from a physiologically relevant administration route. The liver MN test is sufficiently validated for the development of an OECD guideline. However, the impact of dosing animals >6 weeks of age needs to be evaluated. The GI tract MN test shows promise but needs more validation for an OECD guideline. The Pig-a assay detects systemically available mutagens and is a valuable follow-up to in vitro positive results. A new freeze-thaw protocol provides more flexibility. Mutant reticulocyte and erythrocyte frequencies should both be determined. Preliminary data are available for the Pig-a assay in male rat germ cells which require validation including germ cell DNA mutation origin.

A comparison of transgenic rodent mutation and in vivo comet assay responses for 91 chemicals.

A database of 91 chemicals with published data from both transgenic rodent mutation (TGR) and rodent comet assays has been compiled. The objective was to compare the sensitivity of the two assays for detecting genotoxicity. Critical aspects of study design and results were tabulated for each dataset. There were fewer datasets from rats than mice, particularly for the TGR assay, and therefore, results from both species were combined for further analysis. TGR and comet responses were compared in liver and bone marrow (the most commonly studied tissues), and in stomach and colon evaluated either separately or in combination with other GI tract segments. Overall positive, negative, or equivocal test results were assessed for each chemical across the tissues examined in the TGR and comet assays using two approaches: 1) overall calls based on weight of evidence (WoE) and expert judgement, and 2) curation of the data based on a priori acceptability criteria prior to deriving final tissue specific calls. Since the database contains a high prevalence of positive results, overall agreement between the assays was determined using statistics adjusted for prevalence (using AC1 and PABAK). These coefficients showed fair or moderate to good agreement for liver and the GI tract (predominantly stomach and colon data) using WoE, reduced agreement for stomach and colon evaluated separately using data curation, and poor or no agreement for bone marrow using both the WoE and data curation approaches. Confidence in these results is higher for liver than for the other tissues, for which there were less data. Our analysis finds that comet and TGR generally identify the same compounds (mainly potent mutagens) as genotoxic in liver, stomach and colon, but not in bone marrow. However, the current database content precluded drawing assay concordance conclusions for weak mutagens and non-DNA reactive chemicals.

Analysis of historical negative control group data from the in vitro micronucleus assay using human lymphocytes.

A database of the micronuclei counts was built up for historical negative control data from human lymphocyte in vitro micronuclei tests (MnVit) carried out in 8 laboratories with experience of the method. The mean incidence of micronucleated cells (mnt)/1000 cells ranged from 2.2/1000 to 15.9/1000. There were no large differences in incidence between the presence or absence of S9 mix or between different treatment lengths. There was also little evidence that different solvents affected the numbers of micronuclei appreciably. A number of laboratories did show significant inter-experiment variability, indicating that there remained unidentified factors affecting frequencies. Donor variance may be one such factor. Inter-individual variability may explain some of these differences. The approximate 7.5-fold difference in mnt/1000 scores in a relatively small group of experienced laboratories illustrates the potential complications that can arise if a metric like a fold increase was considered the only biologically important finding. Although there is inherent variability between experiments, it was evident that within a laboratory the overall laboratory mean remains constant over time. It is believed that these findings will provide help to laboratories conducting studies using human lymphocytes in the MnVit and to those involved in the assessment of MnVit results.