Blue-Light Irradiation Regulates Proliferation and Differentiation in Human Skin Cells

Sunlight influences the physiology of the human skin in beneficial as well as harmful ways, as has been shown for UV light. However, little is known about the effects of other wavelengths of solar irradiation. In this study we irradiated human keratinocytes and skin-derived endothelial cells with light-emitting-diode devices of distinct wavelengths to study the effects on cell physiology. We found that light at wavelengths of 632–940nm has no effect, but irradiation with blue light at 412–426nm exerts toxic effects at high fluences. Light at 453nm is nontoxic up to a fluence of 500J/cm2. At nontoxic fluences, blue light reduces proliferation dose dependently by up to 50%, which is attributable to differentiation induction as shown by an increase of differentiation markers. Experiments with BSA demonstrate that blue-light irradiation up to 453nm photolytically generates nitric oxide (NO) from nitrosated proteins, which is known to initiate differentiation in skin cells. Our data provide evidence for a molecular mechanism by which blue light may be effective in treating hyperproliferative skin conditions by reducing proliferation due to the induction of differentiation. We observed a photolytic release of NO from nitrosated proteins, indicating that they are light acceptors and signal transducers up to a wavelength of 453nm

Human Skin Endothelial Cells Can Express All 10 TLR Genes and Respond to Respective Ligands▿

Breakdown of the skin barrier requires the recognition of and rapid responses to invading pathogens. Since wounding usually also affects endothelial intactness, the expression of receptors of the Toll-like family involved in pathogen recognition in human skin vessel endothelia was examined. We found that human skin-derived microvascular endothelial cells can express all 10 Toll-like receptors (TLRs) currently known and will respond to respective ligands. Using immortalized skin-derived (HMEC-1) and primary dermal endothelial cells (HDMEC), we screened for TLR expression by real-time PCR. Endothelial cells express 7 (for HDMEC) and 8 (for HMEC-1) of the 10 known human TLRs under resting conditions but can express all 10 receptors in proinflammatory conditions. To provide evidence of TLR functionality, endothelial cells were challenged with TLR ligands, and after the TLR downstream signaling, MyD88 recruitment as well as early (interleukin-8 [IL-8] release) and late immune markers (inducible nitric oxide synthase mRNA expression) were monitored. Surprisingly, the responses observed were not uniform but were highly specific depending on the respective TLR ligand. For instance, lipopolysaccharides highly increased IL-8 release, but CpG DNA induced significant suppression. Additionally, TLR-specific responses were found to differ between resting and activated endothelial cells. These results show that human skin-derived endothelial cells can function as an important part of the innate immune response, can actively sense pathogen-associated molecular patterns, and can mount an increased or reduced inflammatory signal upon exposure to any of the currently known TLR ligands. Moreover, we also show here that proinflammatory conditions may affect TLR expression in a specific and nonuniform pattern

Blue light exposure decreases systolic blood pressure, arterial stiffness, and improves endothelial function in humans

Aims: Previous studies have shown that ultraviolet light can lead to release of nitric oxide (NO) from the skin and decrease blood pressure. In contrast to visible light local application of UV light bears a cancerogenic risk. Here, we investigated whether whole body exposure to visible blue light can also decrease blood pressure and increase endothelial function in healthy subjects. Methods: In a randomized cross-over study, 14 healthy male subjects were exposed on 2 days to monochromatic blue light or blue light with a filter foil (control light) over 30 min. We measured blood pressure (primary endpoint), heart rate, forearm vascular resistance, forearm-blood-flow, endothelial function (flow-mediated dilation), pulse wave velocity, and plasma NO species (NOx), nitrite, and nitroso compounds (RXNO) (secondary endpoints) during and up to 2 hours after exposure. Results: Blue light exposure significantly decreased systolic blood pressure and increased heart rate as compared to control. In parallel, blue light significantly increased forearm-blood-flow, flow-mediated dilation, circulating NOx and RXNO while it decreased forearm vascular resistance and pulse wave velocity. Conclusion: Whole body irradiation with visible blue light at real world doses improves blood pressure, endothelial function, and arterial stiffness by NO released from photolabile intracutanous NO metabolites into circulating blood.</p

Characterization of disease-specific cellular abundance profiles of chronic inflammatory skin conditions from deconvolution of biopsy samples

Background: Psoriasis and atopic dermatitis are two inflammatory skin diseases with a high prevalence and a significant burden on the patients. Underlying molecular mechanisms include chronic inflammation and abnormal proliferation. However, the cell types contributing to these molecular mechanisms are much less understood. Recently, deconvolution methodologies have allowed the digital quantification of cell types in bulk tissue based on mRNA expression data from biopsies. Using these methods to study the cellular composition of the skin enables the rapid enumeration of multiple cell types, providing insight into the numerical changes of cell types associated with chronic inflammatory skin conditions. Here, we use deconvolution to enumerate the cellular composition of the skin and estimate changes related to onset, progress, and treatment of these skin diseases. Methods: A novel signature matrix, i.e. DerM22, containing expression data from 22 reference cell types, is used, in combination with the CIBERSORT algorithm, to identify and quantify the cellular subsets within whole skin biopsy samples. We apply the approach to public microarray mRNA expression data from the skin layers and 648 samples from healthy subjects and patients with psoriasis or atopic dermatitis. The methodology is validated by comparison to experimental results from flow cytometry and immunohistochemistry studies, and the deconvolution of independent data from isolated cell types. Results: We derived the relative abundance of cell types from healthy, lesional, and non-lesional skin and observed a marked increase in the abundance of keratinocytes and leukocytes in the lesions of both inflammatory dermatological conditions. The relative fraction of these cells varied from healthy to diseased skin and from non-lesional to lesional skin. We show that changes in the relative abundance of skin-related cell types can be used to distinguish between mild and severe cases of psoriasis and atopic dermatitis, and trace the effect of treatment. Conclusions: Our analysis demonstrates the value of this new resource in interpreting skin-derived transcriptomics data by enabling the direct quantification of cell types in a skin sample and the characterization of pathological changes in tissue composition

Treatment of Atopic Dermatitis Using a Full-Body Blue Light Device (AD-Blue): Protocol of a Randomized Controlled Trial

Irradiation with visible blue light (wavelength 400-495 nm) is a promising, effective, and safe new treatment option for chronic inflammatory skin diseases such as psoriasis and atopic dermatitis. We will perform a multicenter, placebo-controlled, double-blinded, 3-armed, prospective, randomized controlled trial to investigate the efficacy and safety of full-body blue light devices (wavelengths: 415 nm and 450 nm) compared with that of placebo irradiation for the treatment of atopic dermatitis

Full-body blue light irradiation as treatment for atopic dermatitis : a randomized sham-controlled clinical trial (AD-Blue)

Background: Visible blue light (wavelength 400-495 nm) is a promising new treatment option for both psoriasis and atopic dermatitis (AD). Whilst previous clinical trials featured various devices and blue light at a variety of wavelengths, none of these interventions were challenged in objective clinical criteria. Patients and methods: Eighty-seven patients diagnosed with AD were enrolled in AD-Blue, an international, prospective, double-blinded, three-armed (415 nm vs. 450 nm vs. sham control), randomized trial designed to investigate the safety and efficacy of prototype full-body blue light devices. Results: Full-body irradiation with 450 nm blue light but not 415 nm had a significant impact on itch (Itch-VAS, -1.6 ± 2.3; p = 0.023 vs. sham irradiation). PO-SCORAD values also decreased significantly in response to irradiation at 415 nm (-11.5 ± 18.4; p = 0.028 vs. sham irradiation). None of the other outcome measures (EASI, SCORAD, IGA, DLQI) changed significantly. No safety signals were observed. Evaluation of skin transcriptomes, cytokine levels in serum, and ELISpots from peripheral blood mononuclear cells isolated from a subset of patients revealed moderate decreases in IL-31 in response to irradiation with blue light. Conclusions: Despite its favorable safety profile and moderate reductions in itch and IL-31 levels, full-body blue light irradiation did not lead to an amelioration of any of the objective measures of AD.</p

Characterization of disease-specific cellular abundance profiles of chronic inflammatory skin conditions from deconvolution of biopsy samples

Abstract Background Psoriasis and atopic dermatitis are two inflammatory skin diseases with a high prevalence and a significant burden on the patients. Underlying molecular mechanisms include chronic inflammation and abnormal proliferation. However, the cell types contributing to these molecular mechanisms are much less understood. Recently, deconvolution methodologies have allowed the digital quantification of cell types in bulk tissue based on mRNA expression data from biopsies. Using these methods to study the cellular composition of the skin enables the rapid enumeration of multiple cell types, providing insight into the numerical changes of cell types associated with chronic inflammatory skin conditions. Here, we use deconvolution to enumerate the cellular composition of the skin and estimate changes related to onset, progress, and treatment of these skin diseases. Methods A novel signature matrix, i.e. DerM22, containing expression data from 22 reference cell types, is used, in combination with the CIBERSORT algorithm, to identify and quantify the cellular subsets within whole skin biopsy samples. We apply the approach to public microarray mRNA expression data from the skin layers and 648 samples from healthy subjects and patients with psoriasis or atopic dermatitis. The methodology is validated by comparison to experimental results from flow cytometry and immunohistochemistry studies, and the deconvolution of independent data from isolated cell types. Results We derived the relative abundance of cell types from healthy, lesional, and non-lesional skin and observed a marked increase in the abundance of keratinocytes and leukocytes in the lesions of both inflammatory dermatological conditions. The relative fraction of these cells varied from healthy to diseased skin and from non-lesional to lesional skin. We show that changes in the relative abundance of skin-related cell types can be used to distinguish between mild and severe cases of psoriasis and atopic dermatitis, and trace the effect of treatment. Conclusions Our analysis demonstrates the value of this new resource in interpreting skin-derived transcriptomics data by enabling the direct quantification of cell types in a skin sample and the characterization of pathological changes in tissue composition

Additional file 1: of Characterization of disease-specific cellular abundance profiles of chronic inflammatory skin conditions from deconvolution of biopsy samples

Table S2. Signature matrix DerM22. (XLSX 654 kb

Additional file 3: of Characterization of disease-specific cellular abundance profiles of chronic inflammatory skin conditions from deconvolution of biopsy samples

Table S3. Reference dataset for DerM22. (XLSX 17 kb