Raman spectral fingerprinting links molecular and transcriptomic changes in mesenchymal stem cells during skeletal aging

Xuanyi Li; Jinyang Wang; Xinwei Zhou; Zhili Dong; Fan Yang; Lei Huang; Leyang Ji; Yongxi Lu; Ting Xiang; Tingting Ai; Yang Li; Dandan Ma; Chenshuang Li; Yang Yang; Xiaoxing Kou

doi:10.1016/j.dtrs.2025.100003

Dental Research ›› 2026, Vol. 1 ›› Issue (1) :2 -18. DOI: 10.1016/j.dtrs.2025.100003

RESEARCH

research-article

Raman spectral fingerprinting links molecular and transcriptomic changes in mesenchymal stem cells during skeletal aging

Xuanyi Li ^a^,^b^,^c^,¹
, Jinyang Wang ^a^,^b^,¹
, Xinwei Zhou ^a^,^b^,¹
, Zhili Dong ^a^,^b
, Fan Yang ^d
, Lei Huang ^a^,^b^,^c
, Leyang Ji ^a^,^b^,^c
, Yongxi Lu ^a^,^b^,^c
, Ting Xiang ^a^,^b^,^c
, Tingting Ai ^a^,^b
, Yang Li ^a^,^b
, Dandan Ma ^e
, Chenshuang Li ^f
, Yang Yang ^a^,^b^,^*
, Xiaoxing Kou ^a^,^b^,^c^,^*

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Abstract

The functional decline of bone marrow mesenchymal stem cells (BMMSCs) critically contributes to skeletal aging. However, rapid and label-free methods to assess this decline remain limited. Here, we establish a framework linking Raman spectroscopic fingerprints to the natural aging process in mice (young, middle-aged, and old), demonstrating age-related changes in molecular composition that corresponded with the loss of stem cell potency. Based on principal component analysis of spectral data, we developed an optimal convolutional neural network model that accurately predicts the age of BMMSCs. We identified a typical set of 20 spectral components that illustrate changes in proteins, lipids, and nucleic acids during aging. These spectral signatures correlate strongly with the cellular senescence marker and bone loss. Parallel single-cell RNA sequencing reveals transcriptomic reprogramming associated with inflammation, metabolism, and extracellular matrix remodeling, which covaries with spectral features. This spectral-transcriptomic association was successfully validated in independent cohorts. The typical spectral profiles accurately assessed the impact of inflammatory stimuli on stem cell and human tissues, and predicted bone loss in the ovariectomized mouse model. This integrative spectral fingerprinting approach offers a novel, label-free tool for diagnosing skeletal senescence and evaluating interventions targeting mesenchymal stem cells (MSCs) functionality.

Keywords

Raman Spectroscopy / Mesenchymal Stem Cells / Skeletal Aging / Transcriptomic Remodeling / Spectral Fingerprinting

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Xuanyi Li, Jinyang Wang, Xinwei Zhou, Zhili Dong, Fan Yang, Lei Huang, Leyang Ji, Yongxi Lu, Ting Xiang, Tingting Ai, Yang Li, Dandan Ma, Chenshuang Li, Yang Yang, Xiaoxing Kou. Raman spectral fingerprinting links molecular and transcriptomic changes in mesenchymal stem cells during skeletal aging. Dental Research, 2026, 1 (1) : 2-18 DOI:10.1016/j.dtrs.2025.100003

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