Progress with Structure-Activity Relationship modelling of occupational chemical respiratory sensitizers

Airway Diseases Related to the Use of Cleaning Agents in Occupational Settings

Exposure to disinfectants and cleaning products (DCPs) is now a well-established risk factor for work-related asthma (WRA). However, questions remain on the specific causal agents and pathophysiological mechanisms. Few studies have also reported an association between DCPs and rhinitis or chronic obstructive pulmonary disease. This review discusses the recent evidence pertaining to airway diseases attributable to occupational exposure to DCPs. In contrast to other agents, the incidence of WRA due to DCPs has increased over time. The use of DCPs in spray form has clearly been identified as an added risk factor. The mechanisms for WRA associated with DCPs remain poorly studied; however, both allergic and nonallergic responses have been described, with irritant mechanisms thought to play a major role. An early diagnostic workup based on clinical assessment accompanied by evaluation of lung function and immunological and airway inflammatory markers is important to guide optimal care and exposure avoidance to the implicated agent. Future research should focus on the effects of "green" products, pathophysiological mechanisms, and quantitative exposure assessment including the use of barcode-based methods to identify specific agents. There is an urgent need to strengthen preventive measures and interventions to reduce the burden of airway diseases associated with DCPs.

Comparison of high- and low-molecular-weight sensitizing agents causing occupational asthma: an evidence-based insight

INTRODUCTION

The many substances used at the workplace that can cause sensitizer-induced occupational asthma are conventionally categorized into high-molecular-weight (HMW) agents and low-molecular-weight (LMW) agents, implying implicitly that these two categories of agents are associated with distinct phenotypic profiles and pathophysiological mechanisms.

AREAS COVERED

The authors conducted an evidence-based review of available data in order to identify the similarities and differences between HMW and LMW sensitizing agents.

EXPERT OPINION

Compared with LMW agents, HMW agents are associated with a few distinct clinical features (i.e. concomitant work-related rhinitis, incidence of immediate asthmatic reactions and increase in fractional exhaled nitric oxide upon exposure) and risk factors (i.e. atopy and smoking). However, some LMW agents may exhibit 'HMW-like' phenotypic characteristics, indicating that LMW agents are a heterogeneous group of agents and that pooling them into a single group may be misleading. Regardless of the presence of detectable specific IgE antibodies, both HMW and LMW agents are associated with a mixed Th1/Th2 immune response and a predominantly eosinophilic pattern of airway inflammation. Large-scale multicenter studies are needed that use objective diagnostic criteria and assessment of airway inflammatory biomarkers to identify the pathobiological pathways involved in OA caused by the various non-protein agents.

Identification of true chemical respiratory allergens: Current status, limitations and recommendations

Asthma in the workplace is an important occupational health issue. It comprises various subtypes: occupational asthma (OA; both allergic asthma and irritant-induced asthma) and work-exacerbated asthma (WEA). Current regulatory paradigms for the management of OA are not fit for purpose. There is therefore an important unmet need, for the purposes of both effective human health protection and appropriate and proportionate regulation, that sub-types of work-related asthma can be accurately identified and classified, and that chemical respiratory allergens that drive allergic asthma can be differentiated according to potency. In this article presently available strategies for the diagnosis and characterisation of asthma in the workplace are described and critically evaluated. These include human health studies, clinical investigations and experimental approaches (structure-activity relationships, assessments of chemical reactivity, experimental animal studies and in vitro methods). Each of these approaches has limitations with respect to providing a clear discrimination between OA and WEA, and between allergen-induced and irritant-induced asthma. Against this background the needs for improved characterisation of work-related asthma, in the context of more appropriate regulation is discussed.

High-Resolution Computed Tomography of Fibrotic Interstitial Lung Disease

While radiography is the first-line imaging technique for evaluation of pulmonary disease, high-resolution computed tomography (HRCT) provides detailed assessment of the lung parenchyma and interstitium, allowing normal anatomy to be differentiated from superimposed abnormal findings. The fibrotic interstitial lung diseases have HRCT features that include reticulation, traction bronchiectasis and bronchiolectasis, honeycombing, architectural distortion, and volume loss. The characterization and distribution of these features result in distinctive CT patterns. The CT pattern and its progression over time can be combined with clinical, serologic, and pathologic data during multidisciplinary discussion to establish a clinical diagnosis. Serial examinations identify progression, treatment response, complications, and can assist in determining prognosis. This article will describe the technique used to perform HRCT, the normal and abnormal appearance of the lung on HRCT, and the CT patterns identified in common fibrotic lung diseases.

An Explainable Supervised Machine Learning Model for Predicting Respiratory Toxicity of Chemicals Using Optimal Molecular Descriptors

Respiratory toxicity is a serious public health concern caused by the adverse effects of drugs or chemicals, so the pharmaceutical and chemical industries demand reliable and precise computational tools to assess the respiratory toxicity of compounds. The purpose of this study is to develop quantitative structure-activity relationship models for a large dataset of chemical compounds associated with respiratory system toxicity. First, several feature selection techniques are explored to find the optimal subset of molecular descriptors for efficient modeling. Then, eight different machine learning algorithms are utilized to construct respiratory toxicity prediction models. The support vector machine classifier outperforms all other optimized models in 10-fold cross-validation. Additionally, it outperforms the prior study by 2% in prediction accuracy and 4% in MCC. The best SVM model achieves a prediction accuracy of 86.2% and a MCC of 0.722 on the test set. The proposed SVM model predictions are explained using the SHapley Additive exPlanations approach, which prioritizes the relevance of key modeling descriptors influencing the prediction of respiratory toxicity. Thus, our proposed model would be incredibly beneficial in the early stages of drug development for predicting and understanding potential respiratory toxic compounds.

In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities

The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.

Occupational Asthma Caused by Quaternary Ammonium Compounds: A Multicenter Cohort Study

BACKGROUND

Quaternary ammonium compounds (QACs) are used extensively for cleaning and disinfection and have been documented in scattered reports as a cause of occupational asthma (OA) through bronchoprovocation tests (BPTs).

OBJECTIVE

To examine the clinical, functional, and inflammatory profile of QAC-induced OA compared with OA caused by other low-molecular weight (LMW) agents.

METHODS

The study was conducted in a retrospective multicenter cohort of 871 subjects with OA ascertained by a positive BPT. Subjects with QAC-induced OA (n = 22) were identified based on a positive BPT to QACs after exclusion of those challenged with cleaning products or disinfectants that contained other potential respiratory sensitizers. They were compared with 289 subjects with OA caused by other LMW agents.

RESULTS

Most subjects with QAC-induced OA were working in the health care sector (n = 14). A twofold or greater increase in the postchallenge level of nonspecific bronchial hyperresponsiveness was recorded in eight of 11 subjects with QAC-induced OA (72.7%) and in 49.7% of those with OA caused by other LMW agents. Although sputum assessment was available in only eight subjects with QAC-induced OA, they showed a significantly greater median (interquartile) increase in sputum eosinophils (18.1% [range, 12.1% to 21.1%]) compared with those with OA caused by other LMW agents (2.0% [range, 0% to 5.2%]; P < .001).

CONCLUSIONS

This study indicates that QAC-induced OA is associated with a highly eosinophilic pattern of airway response and provides further evidence supporting the sensitizing potential of QACs. The findings highlight the heterogeneous nature of the pathobiologic pathways involved in OA caused by LMW agents.

Diagnosis of Hypersensitivity Pneumonitis in Adults. An Official ATS/JRS/ALAT Clinical Practice Guideline

Background: This guideline addresses the diagnosis of hypersensitivity pneumonitis (HP). It represents a collaborative effort among the American Thoracic Society, Japanese Respiratory Society, and Asociación Latinoamericana del Tórax.Methods: Systematic reviews were performed for six questions. The evidence was discussed, and then recommendations were formulated by a multidisciplinary committee of experts in the field of interstitial lung disease and HP using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach.Results: The guideline committee defined HP, and clinical, radiographic, and pathological features were described. HP was classified into nonfibrotic and fibrotic phenotypes. There was limited evidence that was directly applicable to all questions. The need for a thorough history and a validated questionnaire to identify potential exposures was agreed on. Serum IgG testing against potential antigens associated with HP was suggested to identify potential exposures. For patients with nonfibrotic HP, a recommendation was made in favor of obtaining bronchoalveolar lavage (BAL) fluid for lymphocyte cellular analysis, and suggestions for transbronchial lung biopsy and surgical lung biopsy were also made. For patients with fibrotic HP, suggestions were made in favor of obtaining BAL for lymphocyte cellular analysis, transbronchial lung cryobiopsy, and surgical lung biopsy. Diagnostic criteria were established, and a diagnostic algorithm was created by expert consensus. Knowledge gaps were identified as future research directions.Conclusions: The guideline committee developed a systematic approach to the diagnosis of HP. The approach should be reevaluated as new evidence accumulates.

Occupational Rhinitis

There is convincing evidence that tight relationships between the upper and lower airways also apply to the workplace context. Most patients with occupational asthma (OA) also suffer from occupational rhinitis (OR), although OR is 2 to 3 times more common than OA. OR most often precedes the development of OA, especially when high-molecular-weight protein agents are involved, and longitudinal cohort studies have confirmed that OR is associated with an increased risk for the development of OA. The level of exposure to sensitizing agents at the workplace is the most important determinant for the development of IgE-mediated sensitization and OR. Atopy is a risk factor for the development of IgE-mediated sensitization only to high-molecular-weight agents. In workers with work-related rhinitis symptoms, documentation of IgE-mediated sensitization to a workplace agent via skin prick testing or serum specific IgE confirms a diagnosis of probable OR, whereas specific nasal provocation testing in the laboratory remains the reference method to establish a definite diagnosis of OR. Complete avoidance of exposure to the causal agent is the most effective therapeutic option for controlling work-related nasal symptoms and preventing the development of OA. If complete elimination of exposure is expected to induce meaningful adverse socioeconomic consequences, reduction of exposure can be considered as an alternative approach, but it is important to consider the individual risk factors for the development of OA to implement a more personalized management of OR.

Occupational Exposure to Metals and Solvents: Allergy and Airway Diseases

PURPOSE OF REVIEW

Occupational allergic diseases (OAD) such as occupational contact dermatitis (OCD), occupational asthma (OA), and occupational rhinitis (OR) are the most prevalent occupational diseases in industrialized countries. The purpose of this review is to provide an update about the main occupational metal and solvent exposures related to allergy and airway diseases and to discuss newly defined causative agents and industries in this field.

RECENT FINDINGS

Currently for over 400 causative agents for OA and OCD, several hundreds of agents for OR have been identified. Although many studies have reported an overall decline in OAD related to known agents after implementation of efficient and effective workplace preventive measures, the constant development of new products continuously introduces to the market potential unknown respiratory hazards. Workplace allergens are often high molecular weight (HMW) agents that are > 10 kDa molecular weight and capable of eliciting IgE sensitization. Sensitizing low molecular weight (LMW) agents are often reactive chemicals. Metals and solvents are two large causative agent groups related to OADs that mainly behave as LMW (< 10 kDa) sensitizers and/or irritants. Avoidance of causative exposures through control strategies is the primary prevention approach for OADs. These strategies must be applied and covered for all known and newly defined causative agents. This review aims to summarize current status of known occupational metal and solvent exposures related to allergy and airway diseases and to discuss newly defined causative agents and industries in this field.

Modeling and insights into molecular basis of low molecular weight respiratory sensitizers

Respiratory sensitization has been considered an important toxicological endpoint, because of the severe risk to human health. A great part of sensitization events were caused by low molecular weight (< 1000) respiratory sensitizers in the past decades. However, there is currently no widely accepted test method that can identify prospective low molecular weight respiratory sensitisers. Herein, we performed the study of modeling and insights into molecular basis of low molecular weight respiratory sensitizers with a high-quality data set containing 136 respiratory sensitizers and 518 nonsensitizers. We built a number of classification models by using OCHEM tools, and a consensus model was developed based on the ten best individual models. The consensus model showed good predictive ability with a balanced accuracy of 0.78 and 0.85 on fivefold cross-validation and external validation, respectively. The readers can predict the respiratory sensitization of organic compounds via https://ochem.eu/article/114857 . The effect of several molecular properties on respiratory sensitization was also evaluated. The results indicated that these properties differ significantly between respiratory sensitizers and nonsensitizers. Furthermore, 14 privileged substructures responsible for respiratory sensitization were identified. We hope the models and the findings could provide useful help for environmental risk assessment.

In silico prediction of toxicity and its applications for chemicals at work

OBJECTIVE AND METHODS

This study reviewed the concept of in silico prediction of chemical toxicity for prevention of occupational cancer and future prospects in workers' health. In this review, a new approach to determine the credibility of in silico predictions with raw data is explored, and the method of determining the confidence level of evaluation based on the credibility of data is discussed. I searched various papers and books related to the in silico prediction of chemical toxicity and carcinogenicity. The intention was to utilize the most recent reports after 2015 regarding in silico prediction.

RESULTS AND CONCLUSION

The application of in silico methods is increasing with the prediction of toxic risks to human and the environment. The various toxic effects of industrial chemicals have triggered the recognition of the importance of using a combination of in silico models in the risk assessments. In silico occupational exposure models, industrial accidents, and occupational cancers are effectively managed and chemicals evaluated. It is important to identify and manage hazardous substances proactively through the rigorous evaluation of chemicals.

Skin and respiratory chemical allergy: confluence and divergence in a hybrid adverse outcome pathway

Sensitisation of the respiratory tract to chemicals resulting in respiratory allergy and allergic asthma is an important occupational health problem, and presents toxicologists with no shortage of challenges. A major issue is that there are no validated or, even widely recognised, methods available for the identification and characterisation of chemical respiratory allergens, or for distinguishing respiratory allergens from contact allergens. The first objective here has been review what is known (and what is not known) of the mechanisms through which chemicals induce sensitisation of the respiratory tract, and to use this information to construct a hybrid Adverse Outcome Pathway (AOP) that combines consideration of both skin and respiratory sensitisation. The intention then has been to use the construction of this hybrid AOP to identify areas of commonality/confluence, and areas of departure/divergence, between skin sensitisation and sensitisation of the respiratory tract. The hybrid AOP not only provides a mechanistic understanding of how the processes of skin and respiratory sensitisation differ, buy also a means of identifying areas of uncertainty about chemical respiratory allergy that benefit from a further investment in research.

In silico toxicology protocols

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

ADMET Evaluation in Drug Discovery. Part 17: Development of Quantitative and Qualitative Prediction Models for Chemical-Induced Respiratory Toxicity

As a dangerous end point, respiratory toxicity can cause serious adverse health effects and even death. Meanwhile, it is a common and traditional issue in occupational and environmental protection. Pharmaceutical and chemical industries have a strong urge to develop precise and convenient computational tools to evaluate the respiratory toxicity of compounds as early as possible. Most of the reported theoretical models were developed based on the respiratory toxicity data sets with one single symptom, such as respiratory sensitization, and therefore these models may not afford reliable predictions for toxic compounds with other respiratory symptoms, such as pneumonia or rhinitis. Here, based on a diverse data set of mouse intraperitoneal respiratory toxicity characterized by multiple symptoms, a number of quantitative and qualitative predictions models with high reliability were developed by machine learning approaches. First, a four-tier dimension reduction strategy was employed to find an optimal set of 20 molecular descriptors for model building. Then, six machine learning approaches were used to develop the prediction models, including relevance vector machine (RVM), support vector machine (SVM), regularized random forest (RRF), extreme gradient boosting (XGBoost), naïve Bayes (NB), and linear discriminant analysis (LDA). Among all of the models, the SVM regression model shows the most accurate quantitative predictions for the test set (q²_ext = 0.707), and the XGBoost classification model achieves the most accurate qualitative predictions for the test set (MCC of 0.644, AUC of 0.893, and global accuracy of 82.62%). The application domains were analyzed, and all of the tested compounds fall within the application domain coverage. We also examined the structural features of the compounds and important fragments with large prediction errors. In conclusion, the SVM regression model and the XGBoost classification model can be employed as accurate prediction tools for respiratory toxicity.