Project description:The skin Microbiome stratifies Patients with CTCL into two subgroups. One subgroup has a balanced microbiome, while the other subgroups has a skin dybiosis with S. aureus outgrow. This is accompanied by impaired TCR repertoir and poor clinical outcome.
Project description:We surveyed the genotypes and DNA methylomes of 237 neonates and found 1423 punctate regions of the methylome that were highly variable across individuals, termed variably methylated regions (VMRs), against a backdrop of homogeneity. Although methQTLs were readily detected in neonatal methylomes, genotype alone did not explain the majority of the VMRs. We found that the best explanation for 75% of VMRs was the interaction of genotype with different in utero environments, including maternal smoking, maternal depression, maternal BMI, infant birth weight, gestational age and birth order. We surveyed the genotypes and DNA methylomes of 237 neonates and included 32 technical replicates
Project description:We surveyed the genotypes and DNA methylomes of 237 neonates and found 1423 punctate regions of the methylome that were highly variable across individuals, termed variably methylated regions (VMRs), against a backdrop of homogeneity. Although methQTLs were readily detected in neonatal methylomes, genotype alone did not explain the majority of the VMRs. We found that the best explanation for 75% of VMRs was the interaction of genotype with different in utero environments, including maternal smoking, maternal depression, maternal BMI, infant birth weight, gestational age and birth order. We surveyed the genotypes and DNA methylomes of 237 neonates
Project description:Spink5 constitituve knock-out mice mimic the disease features of Netherton syndrome but die within several hours after birth due to severe skin barrier defect. To characterize the skin barrier and skin inflammation phenotype of this mouse model at the molecular level, we collected back skin samples from mice shortly after their birth.
Project description:The role of the skin microbiome in UV-induced immune suppression has been overlooked. We addressed the question of microbial involvement in UV-induced immune suppression by using the standard model of contact hypersensitivity in the presence or absence of the microbiome (in germ-free [GF] and disinfected mice) and found that the microbiome inhibits UV-induced immune suppression. Furthermore, our transcriptome analysis (24 hours after irradiation) showed differential regulation of many genes in the presence or absence of the microbiome, including a predominance of pro-inflammatory cytokines versus immunosuppressive cytokines
Project description:We surveyed the genotypes and DNA methylomes of 237 neonates and found 1423 punctate regions of the methylome that were highly variable across individuals, termed variably methylated regions (VMRs), against a backdrop of homogeneity. Although methQTLs were readily detected in neonatal methylomes, genotype alone did not explain the majority of the VMRs. We found that the best explanation for 75% of VMRs was the interaction of genotype with different in utero environments, including maternal smoking, maternal depression, maternal BMI, infant birth weight, gestational age and birth order.
Project description:We surveyed the genotypes and DNA methylomes of 237 neonates and found 1423 punctate regions of the methylome that were highly variable across individuals, termed variably methylated regions (VMRs), against a backdrop of homogeneity. Although methQTLs were readily detected in neonatal methylomes, genotype alone did not explain the majority of the VMRs. We found that the best explanation for 75% of VMRs was the interaction of genotype with different in utero environments, including maternal smoking, maternal depression, maternal BMI, infant birth weight, gestational age and birth order.
Project description:In this study, we conducted an integrated analysis of skin measurements, clinical BSTI surveys, and the skin microbiome of 950 Korean subjects to examine the ideal skin microbiome-biophysical association. By utilizing four skin biophysical parameters, we identified four distinct Korean Skin Cutotypes (KSCs) and categorized the subjects into three aging groups based on their age distribution. We established strong connections between 15 core genera and the four KSC types within the three aging groups, revealing three prominent clusters of the facial skin microbiome. Together with skin microbiome variations, skin tone/elasticity distinguishes aging groups while oiliness/hydration distinguishes individual differences within aging groups. Our study provides prospective reality data for customized skin care based on the microbiome environment of each skin type.
