Research approach

From Regulatory Programs to Tissue Inflammation

We study skin autoimmunity as a breakdown in how tissue components communicate. By combining clinical data, prospective human cohorts, ex vivo systems, and reductionist in vitro models, we ask how cytokine responses, chemokine gradients, stromal signals, immune states, and spatial context come together to produce disease.

Cell-cell communication network in skin across dendritic cells, keratinocytes, macrophages, melanocytes, and T cells, shown as a raw interaction graph and a clustered community view — An early map of dendritic cell, keratinocyte, macrophage, melanocyte, and T cell signaling in skin — a shared-neighbor graph (left) resolved into communities (right).

This current focus builds directly from the lab's earlier work in comparative genomics, gene regulation, and computational method development. Those tools let us compare diseases at their most elemental features and connect basic regulatory principles to complex clinical phenotypes. Our goal is to build systems immunology models that explain how molecular programs become coordinated cellular behaviors in human tissue.

Research focus

Skin as a human model of autoimmunity and autoinflammatory conditions

Inflammatory skin disease gives us access to the molecular, spatial, and clinical layers of autoimmunity. We use that access to connect cell state, tissue context, environmental exposure, and genetic variation.

Sample collection is minimally invasive: blister or punch biopsies and tape stripping are quick, low-risk procedures, and a growing set of assays can work from their small sample sizes. That combination makes skin a uniquely tractable system for studying autoimmunity directly in humans.

Spatial tissue panels comparing psoriasis, dermatomyositis, and cutaneous lupus samples

Comparative disease biology

Why compare across autoimmune skin diseases?

Inflammatory skin diseases often reuse overlapping cytokine pathways and immune-cell and tissue-cell states, but differ in where, when, and in which cells those programs are activated. This can produce overlapping clinical or histologic patterns—as in atopic dermatitis and allergic contact dermatitis, psoriasis and psoriasiform cutaneous lupus, or dermatomyositis and cutaneous lupus—even when triggers and treatment responses differ. Comparing diseases helps separate shared inflammatory circuits from disease-defining mechanisms.

Heatmap of gene expression responses to PBS, IFN-gamma, IFN-beta, and TNF-alpha stimulation

Cytokine response atlas

Which cells are responding, and to what signals?

We build a cell-type-specific response atlas by exposing primary human skin cells and ex vivo tissue to defined cytokines. We then use these reference programs to resolve disease signatures into their likely cellular and signaling components.

Response QTL plot showing genotype-dependent gene expression change from PBS to IFN-gamma stimulation

Genetics of cytokine response

Do genetic variants change how cells respond?

Many inflammatory and autoimmune skin diseases are polygenic. As part of the IGVF Consortium, we integrate genotyping with RNA-seq, ATAC-seq, and H3K27ac profiling to map response QTLs—variants whose regulatory effects emerge or change after cytokine stimulation. In melanocytes, this approach has implicated loci near ERAP2 and HLA-DRB5 in IFN-γ-induced antigen-presentation programs.IGVF Consortium

VIGOR study website landing page, 'Help Us Stop Vitiligo Before It Begins'

Prospective cohorts

How is autoimmunity initiated?

The VIGOR and CLuES studies follow people with vitiligo and cutaneous lupus, and their unaffected family members, over several years with fully remote at-home sampling — tracking genetic, environmental, and skin biomarker change before and during disease onset or progression.vigor.umassmed.edu

M2 macrophage marker heatmaps and diffusion maps tracing the CD14+ myeloid transition program

Myeloid cell role in inflammation

How does inflamed skin shape myeloid cell identity—and how do those states influence disease?

We study how CD14+ monocytes, macrophages, and dendritic cells are organized along continuous and branching transcriptional programs in skin. We focus on resident-like, inflammatory, and disease-associated states—and on the signals and functions that distinguish them.

Chemokine receptor expression across the CD14+ transition linked to spatial chemokine ligand trajectories across fibroblast, endothelial, and myeloid cell types

Tissue Immunology

What organizes inflammation in skin?

Using spatial transcriptomics and single-cell profiling, we reconstruct the cellular neighborhoods of diseased skin. We ask how local interactions among epithelial, stromal, and immune cells sustain—or restrain—inflammation.

Regulatory genomics

How do enhancers coordinate immune activation?

Our earlier work asked how dendritic cells and macrophages translate microbial signals into coordinated gene programs. We identified a conserved enhancer lexicon that helps encode response timing and used SIP—our immunoprecipitation-coupled extension of SPRITE—to show how multiway enhancer–promoter hubs shape the strength and cell-to-cell consistency of gene activation. This regulatory framework now guides our studies of diseased skin.

Current convergence

Macrophages, dendritic cells, and the regulatory logic of inflammation

Recent work points us toward a shared theme: myeloid and dendritic cells do not simply appear as fixed categories. They move through tissue-instructed programs that can be mapped, perturbed, and connected back to regulatory sequence and disease risk.

CD14+ myeloid cells expand in photosensitive disease.Resident-like and inflammatory states form a continuum.Fibroblast and keratinocyte signals shape tissue recruitment.CD14+ cells also expand in other disedases and show disease specific state and spatial transitions

Funding & consortia

Supported by

NIH Common Fund — IGVF ConsortiumImpact of Genomic Variation on Function. With the Weng lab: predictive modeling of the functional and phenotypic impact of genetic variants, including response QTLs in skin.

NIH Common Fund — SMaHT NetworkSomatic Mosaicism across Human Tissues. With the Fazzio lab: carCUT&Tag, a method for identifying and characterizing sequence variants in regulatory elements and genes.

NIH U01 — VIGOR / CLuESWith Harris and Rashighi: predictive drivers of new-onset, relapse, and progression of human autoimmunity in skin.

NIH P50 (Project II)With Richmond: cell-cell communication and tissue memory in vitiligo.

NIH R01With Divito: interrogating the clonal repertoire in drug hypersensitivity reactions.

LEO FoundationTo investigate the role of WARS1 as an alarmin that triggers CD14+ activation to initiate UV responses