The Journal of investigative dermatology最新文献

Environmental factors play a role in onset of psoriasis. We investigated whether early childhood stress contributes to the development of psoriasis later in life. Questionnaires, answered by parents of children in the All Babies in Southeast Sweden prospective birth cohort (n = 16,145) follow-up at 1, 3, 5, and 8 years of the child, were used. Psoriasis cases were identified using the Swedish National Patient Register. Statistical analyses were conducted using the R programming language. The stress life factor "new family structure" (divorce/separation and/or new adult or new/step siblings) before the age of 1 year increased the risk of developing psoriasis (OR = 4.19, 95% confidence interval = 1.01-11.48, P = .048) in the univariate regression model and was also significant when adjusted for confounders. Integrating data from follow-up years 1, 3, 5, and 8, "new family structure" increased the risk of psoriasis-univariate (OR = 3.40, 95% confidence interval = 1.06-9.42, P = .04) but was not significant in the adjusted multivariable model, although the effect size was high (OR = 2.91, 95% confidence interval = 0.88-8.41). Children experiencing the psychological stress of a "new family structure" during the first 8 years of life have an increased risk of developing psoriasis later.

Although accumulating evidence implicates cellular senescence in acute wound healing, the precise roles of senescent cells within distinct cell lineages during this process remain elusive. To address this, we employed the p16-tdTomato reporter mouse model for labeling and isolating senescent cells from wound tissue. Longitudinal in vivo imaging monitoring revealed the temporal dynamics of tdTomato (tdTom) fluorescence, with signal detection as early as postoperative day 3, peaking by day 6. Utilizing an optimized tissue digestion protocol, we achieved high-viability FACS isolation of p16^INK4a-expressing cells (tdTom+), which exhibited characteristic senescent cell morphology and marker expression. Single-cell analysis demonstrated that tdTom+ wound cells enriched with p16 expression were primarily characterized as fibroblasts and displayed common features of senescence. These findings validate the p16-tdTomato reporter mouse as a reliable model for identifying and isolating senescent cells from the wound microenvironment at single-cell resolution.

Tightly regulated cell-cell and cell-niche intercommunications through intertwined signaling networks are involved in maintaining normal hair follicle (HF) homeostasis, cycling, and cell fate determination. However, knowledge of specific mechanisms through which hair loss takes place under pathological situations is needed. Using a keratinocyte-specific knockout mouse model, we uncover that the G-protein-coupled receptor kinase 2 signaling node plays a key role in HF homeostasis. Epidermal G-protein-coupled receptor kinase 2 ablation causes alterations during anagen induction, giving rise to abnormal cyst-like structures. HF-linked cysts display aberrant growth and differentiation patterns as well as lineage infidelity, displaying features of abortive HFs unable to fully acquire canonical hallmarks. Cysts triggered by G-protein-coupled receptor kinase 2 deletion displace the dermal papilla away from the bulge and promote irreversible changes in HF stem cell architecture, leading to bulge destruction and hair loss. Our data provide unforeseen roles of G-protein-coupled receptor kinase 2 in epidermal physiology and uncover the mechanisms linking dystrophic follicular cysts formation with hair loss, with potential connections to pathogenic processes operating in immune-mediated alopecias.

Melanoma is a highly aggressive cutaneous malignancy characterized by a strong propensity for metastasis and therapy resistance, with its progression being closely linked to metabolic reprogramming. This study integrated multiomics data (The Cancer Genome Atlas, Gene Expression Omnibus, European Nucleotide Archive) and advanced machine learning to develop prognostic and immunotherapy prediction models for melanoma, focusing on 114 metabolism-related pathways. Cox regression identified 70 genes linked to survival, with functional enrichment revealing key metabolic pathway alterations. A metabolism-related prognostic model (MRPM) was constructed using 101 combinations of machine learning algorithms, demonstrating superior predictive accuracy across 4 cohorts. High-risk patients showed worse survival and immunotherapy response in melanoma and other cancers. Tumor microenvironment analysis revealed MRPM's negative correlation with immune infiltration and positive association with tumor purity. Single-cell sequencing highlighted MRPM gene enrichment in melanocytes. Mechanistically, GYS1 (the key gene in MRPM) emerged as a pivotal prognostic gene that promotes melanoma proliferation and metastasis. Regulatory studies uncovered SP1's transcriptional control of GYS1- and PSMD14-mediated stabilization of SP1 through K48-linked ubiquitination removal. In vivo validation confirmed that PSMD14 knockdown suppressed tumor growth through SP1-GYS1 axis disruption. This work establishes MRPM as a robust predictive tool and elucidates the PSMD14-SP1-GYS1 regulatory network as a potential therapeutic target in melanoma metabolism.