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Deciphering the molecular basis of skin color variation through transcriptomics and machine learning
Elias Bou Samra1, Mickael Leclercq2, Juliette Sok1
1L'Oreal Research and Innovation, 93600, Aulnay-sous-Bois, France.
Scientific Reports
|December 19, 2025
Summary
This study reveals key genes and pathways influencing human skin color variation. Darker skin shows enhanced antioxidant defenses and altered lipid metabolism, with a 25-gene signature predicting skin tone.
Area of Science:
- Genetics and Genomics
- Dermatology
- Human Variation
Background:
- Human skin color is highly diverse, yet its genetic underpinnings are not fully understood.
- Constitutive skin pigmentation variation is influenced by complex genetic factors.
- Objective measurement of skin color is crucial for genetic studies.
Purpose of the Study:
- To investigate the genetic basis of constitutive skin pigmentation using the Individual Typology Angle (ITA).
- To identify genes and pathways associated with variations in skin color.
- To develop a predictive gene signature for skin pigmentation.
Main Methods:
- Comparative gene expression analysis between light and dark skin samples.
- Identification of significantly modulated genes and pathway enrichment analysis.
- Machine learning model development using a 25-gene signature to predict ITA.
Main Results:
- 265 significantly modulated genes were identified, clustering in pigmentation, antioxidant, lipid metabolism, and interferon-gamma signaling pathways.
- Darker skin exhibited upregulated pigmentation and antioxidant/detoxification genes (e.g., GSTM3, AKR1B10).
- A 25-gene signature, including novel candidates, was identified for predicting ITA, with potential roles for lipid metabolism and inhibited interferon-gamma signaling in darker skin.
Conclusions:
- This research provides novel insights into the genetic architecture of human skin pigmentation.
- Identified pathways suggest a role for enhanced antioxidant defense and specific lipid metabolism in darker skin.
- The findings lay the foundation for personalized skincare strategies based on genetic profiles.
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