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Decoding keloids links single-cell heterogeneity, adipocyte biology, biomarkers, and skin-of-color equity

A high-value JID review reframes keloids as a multi-compartment disease involving fibroblasts, inflammation, adipocytes, genetic risk, and skin-of-color biology.

keloidsingle-celladipocyteskin of color

Full Citation

Glass DA 2nd, Horsley V, Liu Y, Plikus MV, Jones L, Bayat A, Reichenberger EJ, Supp D. Decoding keloids: Single-cell heterogeneity, emerging role of adipocytes, molecular biomarkers, and therapeutic implications in skin of color. J Invest Dermatol. 2026 Feb 28:S0022-202X(26)00139-9.

Study typeAuthoritative narrative review synthesizing keloid genetics, multiomics, single-cell profiling, adipocyte-fibroblast crosstalk, epigenetics, vitamin D signaling, and therapeutic implications.
IdentifierPMID 41771398
DOI10.1016/j.jid.2026.01.044

Background and Question

Keloids are chronic wound-triggered fibroproliferative lesions that extend beyond the original injury, recur after excision, and disproportionately affect people with skin of color. The field has moved beyond a fibroblast-only model toward a multi-cellular, genetically influenced, inflammatory and metabolic disease model.

Research question

What do recent single-cell, multiomic, genetic, adipocyte, epigenetic, and vitamin D studies imply for a more precise model of keloid pathogenesis and therapy, especially in skin of color?

Methods and Evidence Chain

Evidence scope

Synthesized recent human and mechanistic literature on keloid pathogenesis rather than testing one new intervention.

Cellular axis

Emphasized single-cell heterogeneity and disease-associated fibroblast, immune, epidermal, and adipose-linked programs.

Molecular axis

Integrated biomarkers, heritable risk, microRNA regulation, vitamin D signaling, and adipocyte lipolysis.

Equity axis

Placed keloid biology in the clinical context of skin-of-color burden and translational underrepresentation.

1

Evidence scope

Synthesized recent human and mechanistic literature on keloid pathogenesis rather than testing one new intervention.

2

Cellular axis

Emphasized single-cell heterogeneity and disease-associated fibroblast, immune, epidermal, and adipose-linked programs.

3

Molecular axis

Integrated biomarkers, heritable risk, microRNA regulation, vitamin D signaling, and adipocyte lipolysis.

4

Equity axis

Placed keloid biology in the clinical context of skin-of-color burden and translational underrepresentation.

Key Results

Disease model

Keloids are presented as persistent inflammatory fibroproliferative lesions with excessive ECM and invasive growth.

Omics insight

Multiomic technologies identify disease-associated cell populations and signaling networks.

Adipocyte role

Adipocyte lipolysis and adipocyte-fibroblast communication are highlighted as emerging modulators of fibrosis.

Therapeutic direction

Biomarkers, vitamin D signaling, and epigenetic regulators create candidate paths for precision therapy.

Mechanism Interpretation

The review supports a niche-level mechanism: injury activates epidermal, immune, fibroblast, vascular, and adipose compartments; genetically susceptible skin maintains inflammatory and profibrotic signaling; adipocyte lipolysis and stromal crosstalk alter local metabolism; microRNAs and vitamin D-linked pathways tune repair responses; fibroblast subpopulations then sustain ECM accumulation and invasive scar expansion.

Mechanism / workflow schematic

Mermaid source is included so the website can render the diagram in supported browsers.

flowchart LR
  A[Skin injury in susceptible patient] --> B[Epidermal and immune activation]
  A --> C[Adipose niche response]
  C --> D[Adipocyte lipolysis and stromal crosstalk]
  B --> E[Inflammatory profibrotic signaling]
  D --> E
  F[Genetic risk and skin-of-color burden] --> E
  G[miRNA and vitamin D regulation] --> E
  E --> H[Activated fibroblast states]
  H --> I[Excess ECM and invasive keloid growth]

Clinical and Translational Relevance

Clinical relevance

The paper is clinically important because it connects molecular heterogeneity to the real population burden of keloids. It argues against one-size-fits-all treatment and supports stratifying lesions by ancestry-linked risk, anatomical site, recurrence history, inflammatory activity, and molecular phenotype.

Translational value

For a scar biology program, this review is a map for selecting biopsy panels and trial biomarkers. It suggests that fibroblast markers alone are insufficient; adipocyte state, immune tone, epithelial signals, vitamin D biology, and genetic susceptibility should be measured together.

Limitations and Critique

Review design

The paper synthesizes evidence and cannot itself prove causality for every proposed pathway.

Data unevenness

Skin-of-color populations remain underrepresented in many omics datasets despite bearing high disease burden.

Therapy gap

Emerging biomarkers do not automatically translate into validated treatment-selection tools.

Model mismatch

Animal and hypertrophic-scar models still incompletely reproduce true human keloid invasion and recurrence.

Reviewer-style critique

This is a useful review because it explicitly broadens keloid biology beyond fibroblast collagen production. The strongest critique is that the field still needs prospective, ancestry-aware, site-matched human tissue cohorts with treatment and recurrence outcomes, otherwise multiomic signals may remain descriptive.

Practical Next Research Actions

Action 1

Build a keloid cohort that records ancestry, Fitzpatrick type, body site, pain, itch, treatment history, and recurrence.

Action 2

Profile lesional edge, central keloid, adjacent normal skin, and subcutaneous adipose with scRNA-seq plus spatial transcriptomics.

Action 3

Add adipocyte lipolysis, vitamin D pathway, microRNA, IL6, TGF-beta, COL1A1, POSTN, and immune activation markers to validation panels.

Action 4

Design therapy studies that stratify by inflammatory versus matrix-dominant lesions rather than only by size.

Evidence-quality judgment

High-quality expert synthesis for hypothesis prioritization; direct therapeutic evidence remains pathway-specific and uneven.