Jesse R. Poganik

This study shows ovarian aging can shift in both directions depending on the systemic environment through inter-organ communication and molecular changes.

This study shows that old white adipose tissue can rejuvenate in young hosts through thermogenic remodeling and pathway activation, reversing biological age markers.

DNA methylation clocks show heterochronic heart grafts shifting toward recipient age in syngeneic mice and 11 human recipients, while recipient mouse native heart, liver and blood show no consistent change.

The paper presents results from an open competition to develop aging biomarkers using DNA methylation data, showing improved predictive models for age, mortality, and multi-morbidity.

This study identifies aging genes in human blood by integrating epigenetic and transcriptomic data, finding genes enriched for immune functions that better replicate across populations and link to aging outcomes.

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.

This paper introduces LongReadAge, a probabilistic model for predicting epigenetic age at the cell-type level using long-read sequencing data.

The paper identifies compounds that extend mouse lifespan and healthspan using a biomarker-driven platform integrating gene expression, chemical screening, and lifespan studies.

MethylGPT is a transformer-based model trained on human DNA methylation data that accurately predicts methylation values and improves age and disease prediction.

This paper introduces Ageome, a framework to measure epigenetic age across molecular pathways in mice and humans, revealing pathway-specific aging patterns and heterogeneity in mortality prediction.

This study shows biological age can increase with stress and decrease with recovery, using epigenetic clocks in mice and humans.

The paper reanalyzes millions of molecular profiles to identify aging interventions using AI agents, finding over 500 interventions that reduce biological age and revealing patterns in aging modulation.

The paper identifies gastrulation in Xenopus laevis as the stage with the lowest epigenetic age and highest developmental disruption, suggesting it as the onset of aging.

Rapamycin treatment during early life extends lifespan and healthspan in mice and Daphnia magna by slowing development and delaying aging.

The paper introduces TIME-Seq, a low-cost method for epigenetic age prediction, and validates it on mouse and human samples, showing improved scalability and accuracy.