Ontology highlight
ABSTRACT:
PROVIDER: PRJNA750340 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Aging-related changes of facial skin microbiome in healthy women.
| PRJNA937708 | ENA
Project description:Studies in model organisms suggest that aged cells can be functionally rejuvenated, but whether this concept applies to human skin is unclear. Here we apply deep sequencing of RNA 3' ends ("3-seq") to discover the gene expression program associated with human photoaging and intrinsic skin aging (collectively termed "skin aging") and the impact of broadband light (BBL) treatment. We find that skin aging was associated with the significantly altered expression level of 2,265 coding and noncoding RNAs, of which 1,293 became "rejuvenated" after BBL treatment, i.e. more similar in expression level of youthful skin. Rejuvenated genes (RGs) included several known key regulators of organismal longevity and their proximal long non-coding RNAs. Skin aging is not associated with systematic changes in 3' end mRNA processing. Hence, BBL treatment can restore the gene expression pattern of photoaged and intrinsically aged human skin to resemble young skin. In addition, our data reveals a novel set of targets that may lead to new insights into the human skin aging process. Examination of broadband light treated and untreated human skin transcriptomes of 5 women aged 50 years or more. They were compared to the skin transcriptomes of 5 young women aged 30 years or less.
2012-07-30 | E-GEOD-39170 | biostudies-arrayexpress
Project description:Determining the Aging Clock for Chinese Women
| PRJNA1058230 | ENA
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.
| EGAS00001007334 | EGA