Nir Eynon

This study examines how NR supplementation and HIIT affect skeletal muscle epigenetic aging, finding opposing effects on epigenetic age acceleration across different clocks.

CpG Atlas integrates over 1.2 million CpG sites across multiple methylation arrays with 18 annotation layers and provides a query interface for epigenetic research.

This study identifies tissue-specific sex-biased DNA methylation changes across the lifespan, showing that age-related methylation changes are widespread but sex effects are rare and tissue-specific.

The paper develops Biolearn, an open-source framework for curating and evaluating aging biomarkers across datasets, finding that harmonization and standardization improve their performance and generalizability.

The paper creates a DNA methylation aging atlas across 17 human tissues, identifying conserved and tissue-specific aging signatures and potential therapeutic targets.

The paper develops cell-type specific DNA methylation clocks to estimate biological age at cell-type resolution and finds they show age acceleration in disease states.

This study finds that total testosterone is not linked to muscle mass or strength in pre-menopausal females, but bioavailable testosterone and nuclear-localized androgen receptor are associated with muscle hypertrophy.

This study integrates multi-OMIC data from 12 cohorts to identify exercise-specific molecular signatures and gene regulatory patterns in human skeletal muscle.

This study shows that ACTN3 genotype affects androgen response in skeletal muscle by altering AR expression and pathways related to muscle homeostasis.

This study identifies 48% differentially methylated positions and 37% variably methylated positions in blood methylomes across aging, revealing their roles in entropy and epigenetic clocks.

This paper uses DNA methylation data to analyze immune cell fractions across 25,629 blood samples, identifying associations with age, sex, health outcomes, and lifestyle factors.

This study shows exercise training reduces epigenetic and transcriptomic aging in human skeletal muscle, while muscle disuse accelerates transcriptomic aging.

This study integrates DNA methylation and proteomics data from human skeletal muscle to identify group and individual responses to high-intensity interval training.

The paper integrates skeletal muscle methylome and transcriptome data across three cohorts to identify sex differences in DNA methylation and gene expression, revealing functional links between epigenetic and transcriptional sex biases.

The paper identifies age-related DNA methylation changes in human skeletal muscle through a meta-analysis and integrates these with transcriptomic and proteomic data, revealing enriched age-related gene expression patterns.

The paper identifies nine nuclear-encoded SNPs associated with exercise response in the Gene SMART cohort using whole-mitochondrial genome sequencing and composite trait analysis.

The paper develops a muscle-specific epigenetic clock using DNA methylation data from skeletal muscle samples, achieving higher accuracy than a pan-tissue clock.