A Yale School of Medicine study published April 4, 2025 in Science Immunology — supported in part by the Colton Center for Autoimmunity at Yale — offers a striking new hypothesis about why skin conditions like eczema are so frequently linked to food allergies: skin damage itself may directly trigger them.
The research, led by Dr. Anna Eisenstein and Dr. Andrew Wang, showed that in mice, various forms of skin injury — including lacerations, puncture wounds, and ultraviolet light damage — can induce new food allergies when a novel food protein is introduced to the gut within hours of the injury. Crucially, the connection operates at a distance: the allergen did not need to enter through the damaged skin, as animals exposed to the protein through their environment but not directly fed it did not develop allergies. The food also had to be genuinely new to the animal — previously eaten foods did not trigger the same response.
The findings represent a significant mindset shift. Before this work, it was not clear that immune events occurring in completely different parts of the body could be coordinated to trigger an allergy. The team identified several cytokines essential to this process and is now working to identify the specific immune cells responsible for relaying signals between the skin and gut.
While the findings are currently in mice, the implications are broad. Skin inflammation has already been linked to inflammatory bowel disease, rheumatoid arthritis, and heart disease — and this research adds food allergy to the list of systemic conditions that may originate in the skin.
Featured Experts

Katsuo Kurabayashi, PhD
Colton Consortium Member
Department Chair, Mechanical and Aerospace Engineering, NYU Tandon School of Engineering
Carla R. Nowosad, PhD
Colton Consortium Member
Assistant Professor, Department of Pathology, NYU Grossman School of Medicine / NYU Langone Health
Jun Wang, PhD
Colton Consortium Member
Associate Professor, Department of Pathology, NYU Grossman School of Medicine / NYU Langone HealthFeatured Projects

Developing a Multi-parameter Prognostic Prediction Model for Disability Ranks and Progression of Patients with Multiple Sclerosis at the Early Stages of the Disease
Integrating clinical, imaging, and biological data from large real-world MS cohorts, this project builds a machine learning model to predict disability progression early and enable personalized treatment decisions.

Immunotherapy-Related Adverse Effects as Models for Fragile Tolerance in Humans
Using cancer patients experiencing immunotherapy-triggered autoimmunity as a unique human model, this project uncovers the molecular and epigenetic mechanisms by which self-reactive T cells escape immune tolerance.
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Understanding the spectrum from preclinical psoriatic arthritis to early diagnosis of the disease
Vessel wall MRI in giant cell arteritis: standardized protocol and scoring approach developed by an international working group
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