Topical rapamycin reduces markers of senescence and aging in human skin: an exploratory, prospective, randomized trial

Chung CL, Lawrence I, Hoffman M, Elgindi D, Nadhan K, Potnis M, Jin A, Sershon C, Binnebose R, Lorenzini A, Sell C · 2019 · GeroScience · Atlas ID CHU2019

What this study shows

A small human trial testing whether rapamycin can slow aging in a tissue you can actually see and biopsy - skin. Topical rapamycin significantly lowered the senescence marker p16 and raised collagen VII, with visible improvement in skin appearance. Early, small-scale evidence (17 of 36 completed) that topical rapamycin can reduce a senescence marker in human skin.

Abstract

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Aging is a major risk factor for the majority of human diseases, and the development of interventions to reduce the intrinsic rate of aging is expected to reduce the risk for age-related diseases including cardiovascular disease, cancer, and dementia. In the skin, aging manifests itself in photodamage and dermal atrophy, with underlying tissue reduction and impaired barrier function.

Read the full abstract on PubMed →

At a glance

Evidence type	H Human study Marked H because it is direct evidence from a human clinical trial or human cohort; the code names the kind of study, not its quality -- a small, well-run trial is still H.
Study type	2 - Human Clinical Trial
Model system	Humans, RCT (skin, age >40; n=17 completed)
Journal	GeroScience
Year	2019
Peer reviewed	Yes
Record last updated	2026-10-01
Source	DOI 10.1007/s11357-019-00113-y · PMID 31761958 · Free full text (PMC6925069)

Extracted findings

These fields were extracted from the paper with AI assistance and have not been checked against the source. Read them as a pointer into the paper, not as curated claims; where they disagree with the curated summary above, the curated summary stands.

Intervention	Topical rapamycin
Target	mTORC1
Model	Human – RCT (skin, age >40, n=17 completed)
Effect	Topical rapamycin reduced senescence markers and signs of aging in human skin
Dose	Topical rapamycin 10 microM cream vs placebo (DMSO), applied to the hands; no detectable systemic rapamycin (LC/MS LOD 1 ng/ml).
Sample size	36 enrolled, 17 completed, 13 consented to biopsy, 8 samples analyzable (some analyses n=12).
Effect size	p16 protein reduced (P=0.008); collagen VII protein increased (P=0.0077). p21/tp53 trended down but not significant.
Limitations	Small sample size and high dropout; exploratory; some markers not significant; parametric+non-parametric testing used due to small n.

In the Atlas

Open questions that cite this study

Cited as supporting evidence for the open question How much of rapamycin's healthspan benefit runs through fewer senescent cells?.
Cited as supporting evidence for the open question A sensor/autophagy biomarker panel as a surrogate endpoint for human trials.

Cite this paper

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Chung, C. L., Lawrence, I., Hoffman, M., Elgindi, D., Nadhan, K., Potnis, M., Jin, A., Sershon, C., Binnebose, R., Lorenzini, A., & Sell, C. (2019). Topical rapamycin reduces markers of senescence and aging in human skin: an exploratory, prospective, randomized trial. GeroScience. https://doi.org/10.1007/s11357-019-00113-y

@article{CHU2019,
  author       = {Chung, C. L. and Lawrence, I. and Hoffman, M. and Elgindi, D. and Nadhan, K. and Potnis, M. and Jin, A. and Sershon, C. and Binnebose, R. and Lorenzini, A. and Sell, C.},
  title        = {{Topical rapamycin reduces markers of senescence and aging in human skin: an exploratory, prospective, randomized trial}},
  journal      = {GeroScience},
  year         = {2019},
  doi          = {10.1007/s11357-019-00113-y},
  note         = {PMID: 31761958},
}

Cite this Atlas record

The record is the Atlas's own work — the evidence label, the extracted findings and the links. It is cited as part of the dataset, not as the paper.

Barton, O. (2026). Oliver's mTOR Atlas (record CHU2019) [Data set]. https://mtor-atlas.org/study/CHU2019/ · Dataset DOI 10.5281/zenodo.22059963

@misc{atlas_CHU2019,
  author       = {Barton, Oliver},
  title        = {{Oliver's mTOR Atlas}, record CHU2019},
  howpublished = {Data set},
  year         = {2026},
  url          = {https://mtor-atlas.org/study/CHU2019/},
  doi          = {10.5281/zenodo.22059963}
}

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