Occupational and non-occupational allergic contact dermatitis: a follow-up study

Increased loss-of-function filaggrin gene mutation prevalence in atopic dermatitis patients across northern latitudes indicates genetic fitness: A systematic review and meta-analysis

Loss-of-function (LoF) mutations in the filaggrin gene (FLG) constitute the strongest genetic risk for atopic dermatitis (AD). A latitude-dependent difference in the prevalence of LoF FLG mutations was systematically evaluated. A systematic review and meta-analysis were performed to estimate the prevalence of LoF FLG mutations in AD patients and the general population by geography and ethnicity. Risk of bias was assessed by Newcastle-Ottawa Scale and Jadad score. StatsDirect, version 3 software was used to calculate all outcomes. PubMed and EMBASE were searched until 9th December 2021. Studies were included if they contained data on the prevalence of LoF FLG mutations in AD patients or from the general population or associations between AD and LoF FLG mutations and were authored in English. Overall, 248 studies and 229 310 AD patients and individuals of the general population were included in the quantitative analysis. The prevalence of LoF FLG mutations was 19.1% (95% CI, 17.3-21.0) in AD patients and 5.8% (95% CI, 5.3-6.2) in the general population. There was a significant positive association between AD and LoF FLG mutations in all latitudes in the Northern hemisphere, but not in all ethnicities. The prevalence of LoF FLG mutations became gradually more prevalent in populations residing farther north of the Equator but was negligible in Middle Easterners and absent in most African populations. FLG LoF mutations are common and tend to increase with northern latitude, suggesting potential clinical implications for future AD management. The existence of possible genetic fitness from FLG LoF mutations remains unknown.

Occupational contact allergy: The European perspective-Analysis of patch test data from ESSCA between 2011 and 2020

BACKGROUND

Occupational skin diseases have led the occupational disease statistics in Europe for many years. Especially occupational allergic contact dermatitis is associated with a poor prognosis and low healing rates leading to an enormous burden for the affected individual and for society.

OBJECTIVES

To present the sensitization frequencies to the most relevant allergens of the European baseline series in patients with occupational contact dermatitis (OCD) and to compare sensitization profiles of different occupations.

METHODS

The data of 16 022 patients considered having OCD after patch testing within the European Surveillance System on Contact Allergies (ESSCA) network between January 2011 and December 2020 were evaluated. Patients (n = 46 652) in whom an occupational causation was refuted served as comparison group.

RESULTS

The highest percentages of OCD were found among patients working in agriculture, fishery and related workers, metal industry, chemical industry, followed by building and construction industry, health care, food and service industry. Sensitizations to rubber chemicals (thiurams, carbamates, benzothiazoles) and epoxy resins were associated with at least a doubled risk of OCD. After a decline from 2014 onwards, the risks to acquire an occupation-related sensitization to methyl(chloro)isothiazolinone (MCI/MI) and especially to methylisothiazolinone (MI) seem to increase again. Sensitization rates to formaldehyde were stable, and to methyldibromo glutaronitrile (MDBGN) slightly decreasing over time.

CONCLUSIONS

Among allergens in the European Baseline Series, occupational relevance is most frequently attributed to rubber accelerators, epoxy resins and preservatives.

Prediction of skin sensitization potency using machine learning approaches

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd.

QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

Skin sensitization is a major environmental and occupational health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. We have compiled, curated, analyzed, and compared the available human and LLNA data. Using these data, we have developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher CCR of 82% but at the expense of the reduced external dataset coverage (52%). We used the developed QSAR models for virtual screening of CosIng database and identified 1061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential.

[Contact allergies in the German workforce : Data of the IVDK network from 2003-2013]

BACKGROUND

In Germany, occupational skin diseases rank first in the occupational skin disease statistics for many years. Especially, occupationally acquired contact allergies as well as multi-sensitization are the most important predictors for a poor prognosis and persistent eczema.

OBJECTIVES

To update the spectrum and sensitization frequencies of most frequent allergens from the standard series in Germany in patients with occupationally acquired type IV sensitizations in general and within different occupational groups.

METHODS

Data of all employed patients (age range: 16-68 years, n = 14234) patch tested between 2003 and 2013 in the German Departments of the Information Network of Departments of Dermatology (IVDK) and diagnosed occupationally acquired contact dermatitis after patch testing were analyzed. The control group was composed of all other patients (n = 31706) within the same time frame, in which occupationally acquired allergic contact dermatitis was negated explicitly.

RESULTS

The prevalence Ratio (PR; indicating risk) was significantly increased for: Thiuram-mix (PR 5.63 95 %CI 4.97-6.4), zinkdiethyldithiocarbamate (PR 6.22 95 %CI 4.76-8.22), mercaptobenzothiazole (MBT) (PR 3.88 95 %CI 3.09-4.89), mercapto-mix without MBT (PR 3.23 95 %CI 2.59-4.03), N-isopropyl-N'-phenyl-p-phenylene diamine (IPPD) (PR 2.3195 %CI 1.87-2.86), epoxy resin (PR 2.82 95 %CI 2.45-3.25), chloromethylisothiazolinone/methylisothiazolinone (MCI/MI) (PR 2.19 95 %CI 1.97-2.42) and compositae mix II (PR 2.05 95 %CI 1.45-2.89). They were the predominant occupational allergens and were at least associated with a doubled risk (PR ≥ 2.0) for acquiring occupationally allergic contact dermatitis. The highest risk increase was identified in employees in the health services, in agriculture, metal industry, food and service industry as well as building trades

CONCLUSIONS

A limited number of occupationally relevant allergens cause the majority of sensitizations in the workforce, if standard series allergens are concerned. Data analysis of national and international contact allergy data bases provide valuable information on sensitization rates and profiles in skin risk occupations to implement targeted prevention strategies. To diagnose occupational allergic contact dermatitis in individual cases additional testing of occupation related patch test series as well as patients' own products is commonly inevitable.