Frizzled-related proteins 4 (SFRP4) rs1802073G allele predicts the elevated serum lipid levels during acitretin treatment in psoriatic patients from Hunan, China

Background Acitretin is a second-generation synthetic retinoid, and is widely used for treating the severe psoriasis vulgaris. However, it should be chosen with caution for its cardiovascular risk, and it is reported that acitretin may increase the serum lipids. The purpose of this study is to investigate the relationship between the Frizzled-related proteins 4 (SFRP4) rs1802073 polymorphism and the changes of serum lipids in Chinese psoriatic patients during the treatment with acitretin. Methods In our study, 100 psoriatic patients were recruited systematically treated with acitretin (30 mg/day) for at least eight weeks. Data of the patients’ demographic and clinical characteristics and the results of serum triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were collected pre- and post-treatment. Results A total of 84 psoriatic patients were enrolled and divided into three groups by SFRP4 rs1802073 genotypes. The patients who carried with TT genotype had maintained levels of TG and LDL-C after acitretin treatment, while patients with GG/GT genotypes had significantly elevated levels of serum TG and LDL-C compared to the TT genotype (ΔTG%: 27.53 ± 59.13 vs −1.47 ± 37.79, p = 0.026, ΔLDL-C%: 10.62 ± 26.57 vs −1.29 ± 17.07, p = 0.042). The association of rs1802073 with TG and LDL-C profiles remained significant after adjusting for age, gender, and body mass index. Although without significance, the pre-post change in serum level of TC across rs1802073 GG/GT genotypes demonstrated a trend similar to TG and LDL, and the serum level of HDL-C demonstrated a trend opposite to TG, TC and LDL. Conclusions Our results demonstrated that SFRP4 rs1802073 polymorphism was found to be associated with elevated serum lipid levels after acitretin treatment, and it may serve as a genetic marker of safe and precise treatment for individual psoriatic patients

Whole Exome Sequencing in Psoriasis Patients Contributes to Studies of Acitretin Treatment Difference

Psoriasis vulgaris is an immune-mediated inflammatory skin disease. Although acitretin is a widely used synthetic retinoid for moderate to severe psoriasis, little is known about patients’ genetics in response to this drug. In this study, 179 patients were enrolled in either the discovery set (13 patients) or replication set (166 patients). The discovery set was sequenced by whole exome sequencing and sequential validation was conducted in the replication set by MassArray assays. Four SNPs (single nucleotide polymorphisms) (rs1105223T>C in CRB2, rs11086065A>G in ANKLE1, rs3821414T>C in ARHGEF3, rs1802073 T>G in SFRP4) were found to be significantly associated with acitretin response in either co-dominant or dominant models via multivariable logistic regression analysis, while CRB2 rs1105223CC (OR = 4.10, 95% CI = 1.46–11.5, p = 0.007) and ANKLE1 rs11086065AG/GG (OR = 2.76, 95% CI = 1.42–5.37, p = 0.003) were associated with no response to acitretin after 8-week treatment. Meanwhile, ARHGEF3 rs3821414CT/CC (OR = 0.25, 95% CI = 0.10–0.68, p = 0.006) and SFRP4 rs1802073GG/GT (OR = 2.40, 95% CI, 1.23–4.70, p = 0.011) were associated with a higher response rate. Four new genetic variations with potential influences on the response to acitretin were found in this study which may serve as genetic markers for acitretin in psoriasis patients

Risk-adapted Treatment Strategy For COVID-19 Patients

BACKGROUND: There are no clear expert consensus or guidelines on how to treat 2019 coronavirus disease (COVID-19). The objective of this study is to investigate the short-term effect of risk-adapted treatment strategy on patients with COVID-19. METHODS: We collected the medical records of 55 COVID-19 patients for analysis. We divided these patients into mild, moderate and severe groups, and risk-adapted treatment approaches were given according to the illness severity. RESULTS: Twelve patients were in mild group and 22 were in moderate group (non-severe group, n=34), and 21 patients were in severe group. At the end of the first two weeks after admission, clinical manifestations had completely despeared in 31(91.2%)patients in non-severe group, and 18(85.7%) patients in severe group (p=0.85). Both groups had a satisfied chest CT imaging recovery, which includes 22(64.7%) patients in non-severe group and 12(57.1%) patients in severe group recovered at least 50% of the whole leisions in the first week, and 28(82.4%) and 16(76.2%) recovered at least 75% in the second week, respectively. There were no significant differences in SARS-CoV-2 RNA clearance between two group (p=0.92). There were also no significant differences in the levels of SARS-CoV-2-IgM and IgG antibody production between the two groups (p=0.13, 0.62). There were 45 cases were discharged from the hospital, and no patients died at the time of this clinical analysis. CONCLUSIONS: Risk-adapted treatment strategy was associated with significant clinical manifestations alleviation and clinical imaging recovery. In severe COVID-19 patients, early and short-term use of low-dose methylprednisolone was beneficial and did not delay SARS-CoV-2 RNA clearance and influence IgG antibody production

Correction: Xingchen Zhou, et al. Whole Exome Sequencing in Psoriasis Patients Contributes to Studies of Acitretin Treatment Difference. Int. J. Mol. Sci. 2017, 18, 295

We would like to submit the following correction to the published paper [1], the reason for this action is that the data in Table 3 were reanalyzed by one more accurate statistic method: On page 12, the sentence of paragraph three “OR and 95% CI were calculated by limited backward-LR (likelihood ratio) logistic regression analysis with adjustment by clinical variables” should be corrected into “OR and 95% CI were calculated by limited enter logistic regression analysis with adjustment by clinical variables”.[...

Smart Identification of Psoriasis by Images Using Convolutional Neural Networks: A Case Study in China.

Psoriasis is a chronic inflammatory skin disease which holds a high incidence in China. However, professional dermatologists who can diagnose psoriasis early and correctly are insufficient in China, especially in the rural areas. A smart approach to identify psoriasis by pictures would be highly adaptable countrywide, and could play a useful role in early diagnosis and regular treatment of psoriasis. Design and evaluation of a smart psoriasis identification system based on clinical images (without relying on a dermatoscope) that works effectively similar to a dermatologist. A set of deep learning models using convolutional neural networks (CNNs) were explored and compared in the system for automatic identification of psoriasis. The work was carried out on a standardized dermatological dataset with 8021 clinical images of 9 common disorders including psoriasis along with full electronic medical records of patients built over the last 9 years in China. A two-stage deep neural network was designed and developed to identify psoriasis. In the first stage, a multi-label classifier was trained to learn the visual patterns for each individual skin disease. In the second stage, the output of the first stage were utilized to distinguish psoriasis from other skin diseases. The area under the curve (AUC) of the two-stage model reached 0.981±0.015, which outperforms a single-stage model. And the classifier showed superior performance (missed diagnosis rate: 0.04, misdiagnosis rate: 0.03) than 25 Chinese dermatologists (missed diagnosis rate: 0.09, misdiagnosis rate: 0.27) in the diagnosis of psoriasis on 100 clinical images. Using clinical images to identify psoriasis is feasible and effective based on CNNs, which also builds a solid technical base for smart care of skin diseases especially psoriasis using mobile/tablet applications for teledermatology in China. [Abstract copyright: © 2019 European Academy of Dermatology and Venereology.