Skin aging is a specific manifestation of the physiological aging process that occurs in virtually all organisms. In this study, we used data independent acquisition mass spectrometry to perform a comparative analysis of protein expression in volar forearm skin samples from of 20 healthy young and elderly Chinese individuals. Our quantitative proteomic analysis identified a total of 95 differentially expressed proteins (DEPs) in aged skin compared to young skin. Enrichment analyses of these DEPs (57 upregulated and 38 downregulated proteins) based on the GO, KEGG, and KOG databases revealed functional clusters associated with immunity and inflammation, oxidative stress, biosynthesis and metabolism, proteases, cell proliferation, cell differentiation, and apoptosis. We also found that GAPDH, which was downregulated in aged skin samples, was the top hub gene in a protein-protein interaction network analysis. Some of the DEPs identified herein had been previously correlated with aging of the skin and other organs, while others may represent novel age-related entities. Our non-invasive proteomics analysis of human epidermal proteins may guide future research on skin aging to help develop treatments for age-related skin conditions and rejuvenation.

Our group previously found that the transmembrane protein 232 (TMEM232) gene was associated with atopic dermatitis (AD) by Genome-wide association study and fine mapping study. However, its function is unclear so far. To investigate the roles and mechanisms of TMEM232 in AD. The expression of TMEM232 was investigated in skin lesions of AD patients, MC903-induced AD mouse model, human primary keratinocytes and HaCaT cells stimulated with different inflammatory factors. The role of TMEM232 in AD was analyzed in HaCaT cells and Tmem232 knockout (Tmem232^-/-) mice. Tmem232-specific small interfering RNA (siRNA) was used to evaluate its therapeutic potential in the AD mouse model. The expression of TMEM232 was significantly increased in skin lesions of AD patients，MC903-induced AD mouse model and human primary keratinocytes and HaCaT cells stimulated with different inflammatory factors compared to controls. In the presence of MC903, Tmem232^-/- mice exhibited significantly reduced dermatitis severity, mast cell infiltration in the back, and expression of Th1 and Th2-related inflammatory factors in skin tissue compared with WT mice. In vitro and in vivo experiments further showed that the upregulation of TMEM232 in AD exacerbated inflammation response through activating the pathway of nuclear factor-κB and signal transducer and activator of transcription (STAT) 3, and was regulated by IL4/STAT6 axis, which formed a self-amplifying loop. Finally, topical application of Tmem232-siRNA markedly ameliorated AD-like lesions in the AD model. The study first outlines the function of TMEM232. It is involved in regulating inflammation in AD and may be a potential target for AD treatment.

Forty-nine susceptible loci have been reported to be significantly associated with vitiligo by genome-wide association studies (GWASs) in European-derived whites. To date, some of these reported susceptibility loci have not yet been validated in the Chinese Han population. The purpose of this study was to examine whether the 16 reported susceptible loci in European-derived whites were associated with vitiligo in the Chinese Han population. Imputation was performed using our previous GWAS dataset by IMPUTE v2.2.2. The 16 imputed top single-nucleotide polymorphisms (SNPs) with suggestive signals, together with the reported SNPs, were genotyped in a total of 2581 patients and 2579 controls by the Sequenom MassARRAY system. PLINK 2.0 software was used to perform association analysis. The dbSNP database, HaploReg, and eQTL data were adopted to annotate the biological function of the SNPs. Finally, four SNPs from three loci were significantly associated with vitiligo, including rs3747517 (P = 1.29 × 10^–3, OR = 0.87) in 2q24.2, rs4807000 (P = 7.78 × 10^–24, OR = 0.66) and rs6510827 (P = 3.65 × 10^–5, OR = 1.19) in 19p13.3, and rs4822024 (P = 6.37 × 10^–10, OR = 0.67) in 22q13.2. According to the dbSNP database, rs3747517 is a missense variant of IFIH1, rs4807000 and rs6510827 are located in TICAM1, and rs4822024 is located 6 kb upstream of TEF. Further bioinformatics analysis by HaploReg and eQTL found that rs4807000, rs6510827, and rs4822024 are involved in regulating gene expression. Our study revealed the strong association of 2q24.2 (rs3747517), 19p13.3 (rs4807000, rs6510827), and 22q13.2 (rs4822024) with the risk of vitiligo in the Chinese Han population, which implicates common factors for vitiligo across different ethnicities, and helps expand the understanding of the genetic basis of this disease.

Introduction There is a lack of objective, accurate, and convenient methods for classification diagnostic hypopigmented dermatoses (HD) and severity evaluation of vitiligo. To achieve an accurate and intelligent classification diagnostic model of HD and severity evaluation model of vitiligo using a deep learning-based method. Methods A total of 11,483 images from 4744 patients with HD were included in this study. An optimal diagnostic model was constructed by merging the squeeze-and-excitation (SE) module with the candidate model, its diagnostic efficiency was compared with that of 98 dermatologists. An objective severity evaluation indicator was proposed through weighting method and combined with a segmentation model to form a severity evaluation model, which was then compared with the assessments conducted by three experienced dermatologists using the naked eye. Results The improved diagnosis model SE_ResNet-18 outperformed the other 11 classic models with an accuracy of 0.9389, macro-specificity of 0.9878, and macro-f1 score of 0.9395, and outperformed the different categories of 98 dermatologists (P < 0.001). The weighted Kappa test indicated medium consistency between the Indicator_v and the VASI_change (K = 0.567, P < 0.05). The optimal segmented model, HR-Net, had 0.8421 mIOU. The model-based severity evaluation results were not significantly different among the three experienced dermatologists. Conclusions This study proposes an objective, accurate, and convenient hybrid model for diagnosing HD and evaluating the severity of vitiligo, providing a method for dermatologists especially in grassroots hospitals, and provides a foundation for telemedicine.

Neurofibromatosis (NF) is an autosomal genetic disorder for which early and definite clinical diagnoses are difficult. To identify the diagnosis, five affected probands with suspected NF from unrelated families were included in this study. Molecular analysis was performed using multigene panel testing and Sanger sequencing. Ultradeep sequencing was used to analyze the mutation rate in the tissues from the proband with mosaic mutations. Three different pathogenic variants of theNF1gene were found in three probands who mainly complained of café-au-lait macules (CALMs), including one frameshift variant c.5072_5073insTATAACTGTAACTCCTGGGTCAGGGAGTACACCAA:p.Tyr1692Ilefs in exon 37, one missense variant c.3826C > T:p.Arg1276Ter in exon 28, and one splicing variant c.4110 + 1G > T at the first base downstream of the 3′-end of exon 30. OneNF1gene mosaic variant was found in a proband who complained of cutaneous neurofibroma with the frameshift variant c.495_498del:p.Thr165fs in exon 5, and ultradeep sequencing showed the highest mutation rate of 10.81% in cutaneous neurofibromas. A frameshift variant, c.36_39del:p.Ser12fs in exon 1 of theNF2gene, was found in a proband who presented with skin plaques and intracranial neurogenic tumors. All of these pathogenic variants were heterozygous, one was not reported, and one not in Chinese before. This study expands the pathogenic variant spectrum of NF and demonstrates the clinical diagnosis.