Altered serum phospholipids in atopic dermatitis and association with clinical status

Immunoglobulin E autoantibodies in atopic dermatitis associate with Type-2 comorbidities and the atopic march

BACKGROUND

Autoreactive immunoglobulin E (IgE) antibodies to self-peptides within the epidermis have been identified in patients with atopic dermatitis (AD). Prevalence, concomitant diseases, patient characteristics, and risk factors of IgE autoantibody development remain elusive. We aimed to determine IgE autoantibodies in serum samples (n = 672) from well-characterized patients with AD and controls (1.2-88.9 years).

METHODS

Atopic dermatitis patients were sub-grouped in AD with comorbid Type-2 diseases ("AD + Type 2"; asthma, allergic rhinitis, food allergy, n = 431) or "solely AD" (n = 115). Also, subjects without AD but with Type-2 diseases ("atopic controls," n = 52) and non-atopic "healthy controls" (n = 74) were included. Total proteins from primary human keratinocytes were used for the immunoassay to detect IgE autoantibodies. Values were compared to already known positive and negative serum samples.

RESULTS

Immunoglobulin E autoantibodies were found in 15.0% (82/546) of all analyzed AD-patients. "AD + Type 2" showed a higher prevalence (16.4%) than "solely AD" (9.6%). "Atopic controls" (9.6%) were comparable with "solely AD" patients, while 2.7% of healthy controls showed IgE autoantibodies. Of those with high levels of IgE autoantibodies, 15 out of 16 were patients with "AD + Type 2". AD patients with IgE autoantibodies were younger than those without. Patients with IgE autoreactivity also displayed higher total serum IgE levels. Factors that affected IgE autoantibody development were as follows: birth between January and June, cesarean-section and diversity of domestic pets.

CONCLUSIONS

Immunoglobulin E autoantibodies in AD seem to associate with the presence of atopic comorbidities and environmental factors. The potential value of IgE autoantibodies as a predictive biomarker for the course of AD, including the atopic march, needs further exploration.

The Metabolic Footprint of Systemic Effects in the Blood Caused by Radiotherapy and Inflammatory Conditions: A Systematic Review

Response to radiotherapy (RT) includes tissue toxicity, which may involve inflammatory reactions. We aimed to compare changes in metabolic patterns induced at the systemic level by radiation and inflammation itself. Patients treated with RT due to head and neck cancer and patients with inflammation-related diseases located in the corresponding anatomical regions were selected. PubMed and Web of Science databases were searched from 1 January 2000 to 10 August 2023. Twenty-five relevant studies where serum/plasma metabolic profiles were analyzed using different metabolomics approaches were identified. The studies showed different metabolic patterns of acute and chronic inflammatory diseases, yet changes in metabolites linked to the urea cycle and metabolism of arginine and proline were common features of both conditions. Although the reviewed reports showed only a few specific metabolites common for early RT response and inflammatory diseases, partly due to differences in metabolomics approaches, several common metabolic pathways linked to metabolites affected by radiation and inflammation were revealed. They included pathways involved in energy metabolism (e.g., metabolism of ketone bodies, mitochondrial electron transport chain, Warburg effect, citric acid cycle, urea cycle) and metabolism of certain amino acids (Arg, Pro, Gly, Ser, Met, Ala, Glu) and lipids (glycerolipids, branched-chain fatty acids). However, metabolites common for RT and inflammation-related diseases could show opposite patterns of changes. This could be exemplified by the lysophosphatidylcholine to phosphatidylcholine ratio (LPC/PC) that increased during chronic inflammation and decreased during the early phase of response to RT. One should be aware of dynamic metabolic changes during different phases of response to radiation, which involve increased levels of LPC in later phases. Hence, metabolomics studies that would address molecular features of both types of biological responses using comparable analytical and clinical approaches are needed to unravel the complexities of these phenomena, ultimately contributing to a deeper understanding of their impact on biological systems.

Exposure to isocyanates predicts atopic dermatitis prevalence and disrupts therapeutic pathways in commensal bacteria

Atopic dermatitis (AD) is a chronic inflammatory skin condition increasing in industrial nations at a pace that suggests environmental drivers. We hypothesize that the dysbiosis associated with AD may signal microbial adaptations to modern pollutants. Having previously modeled the benefits of health-associated Roseomonas mucosa, we now show that R. mucosa fixes nitrogen in the production of protective glycerolipids and their ceramide by-products. Screening EPA databases against the clinical visit rates identified diisocyanates as the strongest predictor of AD. Diisocyanates disrupted the production of beneficial lipids and therapeutic modeling for isolates of R. mucosa as well as commensal Staphylococcus. Last, while topical R. mucosa failed to meet commercial end points in a placebo-controlled trial, the subgroup who completed the full protocol demonstrated sustained, clinically modest, but statistically significant clinical improvements that differed by study site diisocyanate levels. Therefore, diisocyanates show temporospatial and epidemiological association with AD while also inducing eczematous dysbiosis.

Integrated metabolomics and lipidomics study of patients with atopic dermatitis in response to dupilumab

BACKGROUND

Atopic dermatitis (AD) is one of the most common chronic inflammatory skin diseases. Dupilumab, a monoclonal antibody that targets the interleukin (IL)-4 and IL-13 receptors, has been widely used in AD because of its efficacy. However, metabolic changes occurring in patients with AD in response to dupilumab remains unknown. In this study, we integrated metabolomics and lipidomics analyses with clinical data to explore potential metabolic alterations associated with dupilumab therapeutic efficacy. In addition, we investigated whether the development of treatment side effects was linked to the dysregulation of metabolic pathways.

METHODS

A total of 33 patients with AD were included in the current study, with serum samples collected before and after treatment with dupilumab. Comprehensive metabolomic and lipidomic analyses have previously been developed to identify serum metabolites (including lipids) that vary among treatment groups. An orthogonal partial least squares discriminant analysis model was established to screen for differential metabolites and metabolites with variable importance in projection > 1 and p < 0.05 were considered potential metabolic biomarkers. MetaboAnalyst 5.0 was used to identify related metabolic pathways. Patients were further classified into two groups, well responders (n = 19) and poor responders (n = 14), to identify differential metabolites between the two groups.

RESULTS

The results revealed significant changes in serum metabolites before and after 16 weeks of dupilumab treatment. Variations in the metabolic profile were more significant in the well-responder group than in the poor-responder group. Pathway enrichment analysis revealed that differential metabolites derived from the well-responder group were mainly involved in glycerophospholipid metabolism, valine, leucine and isoleucine biosynthesis, the citrate cycle, arachidonic acid metabolism, pyrimidine metabolism, and sphingolipid metabolism.

CONCLUSION

Serum metabolic profiles of patients with AD varied significantly after treatment with dupilumab. Differential metabolites and their related metabolic pathways may provide clues for understanding the effects of dupilumab on patient metabolism.