detecting and targeting senescent cells through multiomics approaches

A continuum of chronic inflammation—from low‑grade in osteoarthritis (OA) to high‑grade in autoimmune diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc)—drives tissue stress, cellular senescence, and progressive organ damage via immune rewiring. Despite the major public health burden, there are no approved disease‑modifying therapiesthat directly target senescence in these conditions.

We and others have identified senescent cells (positive for p16INK4a, p15INK4b, p21CDKN1A) in joint and extra‑articular tissues from patients and disease models. A central challenge is to define which cell types become senescent, when, and how across disease stages and immune contexts, to enable specific senotherapies that recalibrate inflammation and promote regeneration.

Approach & Aims

1.      Map senescence in joint and immune subsets using high‑dimensional spectral cytometry, multiplex SASP/secretome profiling, and single‑cell multi‑omics integrated with machine learning to derive robust senescence signatures.

2.      Develop detection and clearance strategies leveraging two complementary models: (i) transgenic murine p16/p21‑ATTAC reporters for senescence detection/depletion; (ii) zebrafish p21:mCherry with inflammatory induction for rapid in vivo readouts.

3.      Translate biomarker‑guided interventions to restore joint and organ function within regenerative medicine pipelines.