Courage in Decision Making: A Mixed-Methods Study of COVID-19 Vaccine Uptake in Women of Reproductive Age in the U.K.

COVID-19 vaccination rates are lower in women of reproductive age (WRA), including pregnant/postpartum women, despite their poorer COVID-19-related outcomes. We evaluated the vaccination experiences of 3568 U.K.

Sex differences in muscle protein expression and DNA methylation in response to exercise training.

Background: Exercise training elicits changes in muscle physiology, epigenomics, transcriptomics, and proteomics, with males and females exhibiting differing physiological responses to exercise training. However, the molecular mechanisms contributing to the differing adaptations between the sexes are poorly understood.

Methods: We performed a meta-analysis for sex differences in skeletal muscle DNA methylation following an endurance training intervention (Gene SMART cohort and E-MTAB-11282 cohort).

Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle.

Exercise training prevents age-related decline in muscle function. Targeting epigenetic aging is a promising actionable mechanism and late-life exercise mitigates epigenetic aging in rodent muscle. Whether exercise training can decelerate, or reverse epigenetic aging in humans is unknown.

Diagnosing sepsis in the ICU: Comparison of a gene expression signature to pre-existing biomarkers.

Purpose: We aimed to identify a gene signature that discriminates between sepsis and aseptic inflammation in patients administered antibiotics in the intensive care unit and compare it to commonly utilised sepsis biomarkers.

Methods: 91 patients commenced on antibiotics were retrospectively diagnosed as having: (i) blood culture positive sepsis; (ii) blood culture negative sepsis; or (iii) aseptic inflammation. Bloods were collected after <24 h of antibiotic commencement for both gene expression sequencing analysis and measurement of previously identified biomarkers.

Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism.

Nearly all human complex traits and diseases exhibit some degree of sex differences, with epigenetics being one of the main contributing factors. Various tissues display sex differences in DNA methylation; however, this has not yet been explored in skeletal muscle, despite skeletal muscle being among the tissues with the most transcriptomic sex differences. For the first time, we investigated the effect of sex on autosomal DNA methylation in human skeletal muscle across three independent cohorts (Gene SMART, FUSION, and GSE38291) using a meta-analysis approach, totalling 369 human muscle samples (222 males and 147 females), and integrated this with known sex-biased transcriptomics.

Meta-analysis of genome-wide DNA methylation and integrative omics of age in human skeletal muscle.

Background: Knowledge of age-related DNA methylation changes in skeletal muscle is limited, yet this tissue is severely affected by ageing in humans.

Methods: We conducted a large-scale epigenome-wide association study meta-analysis of age in human skeletal muscle from 10 studies (total n = 908 muscle methylomes from men and women aged 18-89 years old). We explored the genomic context of age-related DNA methylation changes in chromatin states, CpG islands, and transcription factor binding sites and performed gene set enrichment analysis.

Techniques for RNA extraction from cells cultured in starPEG-heparin hydrogels.

Three-dimensional (3D) cell culture models that provide a biologically relevant microenvironment are imperative to investigate cell-cell and cell-matrix interactions . Semi-synthetic star-shaped poly(ethylene glycol) (starPEG)-heparin hydrogels are widely used for 3D cell culture due to their highly tuneable biochemical and biomechanical properties. Changes in gene expression levels are commonly used as a measure of cellular responses.

An epigenetic clock for human skeletal muscle.

Background: Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue.

Methods: To address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC).