Alexander Tyshkovskiy

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.

The paper identifies resilience factors in aged mice using a genome-scale ORF screen, finding NKX2-5 variants that restore vision and reduce frailty.

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.

This paper introduces a computational framework to quantify transcriptomic damage across tissues and conditions, revealing age-associated increases and demonstrating that interventions can alter tDamAge.

This study identifies splicing degeneration as a hallmark of aging, showing it increases with age and is reversible with calorie restriction or rapamycin.

This study shows that SIRT6 Serine 10 mutations in mice affect DNA repair, LINE1 expression, and lifespan, with reduced LINE1 control having a stronger impact on lifespan than enhanced DNA repair.

This study shows that partial chemical reprogramming in aged mice increases lipid droplet formation, which may cause toxicity and hinder tissue rejuvenation.

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 identifies conserved master regulators that coordinate reprogramming-induced rejuvenation across different cell types and shows that perturbing these regulators can modulate transcriptomic age.

The paper introduces stAge, a framework to quantify localized transcriptomic age from spatial transcriptomics data, revealing spatial gradients and age acceleration in mouse and human aging.

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 uses iPSC-derived neurons from centenarians to identify resilience signatures associated with longevity, showing enhanced stress response and specific transcriptional programs.

OSK factors rejuvenate aged RPE cells by activating a Tet2-independent oxidative resilience pathway through GSTA4, restoring vision and reversing age-related degeneration.

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

This paper shows that MA-5 improves hearing loss and extends lifespan in mice by increasing NAD+ and SIRT1 through DNA-PK activation and mitochondrial function.

Regeneration in aging planarians reverses age-related physiological and molecular changes, restoring youthful gene expression and tissue composition.

This study shows that inducing a torpor-like state in mice slows blood epigenetic aging and improves healthspan by reducing core body temperature.

The paper identifies a compact panel of 21 plasma proteins that predict age-related diseases and organ health better than existing models and panels.

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 paper introduces P3GPT, a multimodal transformer model for aging research and drug discovery that performs multiple tasks across species, tissues, and omics data.

This study identifies transcriptomic biomarkers of mortality across species and models, revealing common aging mechanisms and rejuvenation signatures.

The paper investigates epigenetic aging by comparing single-cell DNA methylation changes across aging and development, revealing stochastic patterns and introducing a new algorithm for analyzing CpG clusters.

The paper identifies a Niemann-Pick type C mouse model with accelerated brain aging as a novel model for Alzheimer's disease research by analyzing transcriptomic data from congenital diseases.

The paper uses machine learning on plasma proteome data to develop organ-specific and conventional aging models, showing that age-related diseases reflect accelerated aging of specific organs and systems.

This study shows senolytic drugs reduce brain aging and COVID-19-related neuropathology by targeting senescent cells in human brain organoids and mice.

This study uses multi-omics analysis to show that chemical reprogramming reduces biological age in mouse fibroblasts by altering metabolism and mitochondrial function.

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.