Integrating mass spectrometry imaging and data-driven segmentation for spatial metabolic mapping of diabetic eye disease

Shuohan Cheng; Shuo Wang; Tianfang Lan; Hongtao Jin; Zhou zhi; Zhonghua Wang; Zeper Abliz

doi:10.1016/j.jpha.2026.101596

Article Contents

Article Navigation > Journal of Pharmaceutical Analysis > 2026 > Accepted Manu

Shuohan Cheng, Shuo Wang, Tianfang Lan, Hongtao Jin, Zhou zhi, Zhonghua Wang, Zeper Abliz. Integrating mass spectrometry imaging and data-driven segmentation for spatial metabolic mapping of diabetic eye disease[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2026.101596

Citation:

Shuohan Cheng, Shuo Wang, Tianfang Lan, Hongtao Jin, Zhou zhi, Zhonghua Wang, Zeper Abliz. Integrating mass spectrometry imaging and data-driven segmentation for spatial metabolic mapping of diabetic eye disease[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2026.101596

Citation:

Shuohan Cheng, Shuo Wang, Tianfang Lan, Hongtao Jin, Zhou zhi, Zhonghua Wang, Zeper Abliz. Integrating mass spectrometry imaging and data-driven segmentation for spatial metabolic mapping of diabetic eye disease[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2026.101596

PDF( 34698 KB)

Integrating mass spectrometry imaging and data-driven segmentation for spatial metabolic mapping of diabetic eye disease

doi: 10.1016/j.jpha.2026.101596

Shuohan Cheng^1,2,
Shuo Wang^1,2,
Tianfang Lan^1,2,
Hongtao Jin³,
Zhou zhi^1,2,
Zhonghua Wang^{1,2
,
,},
Zeper Abliz^1,2,4

1. Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), National Ethnic Affairs Commission, Beijing, 100081, China;
2. Center for Imaging and Systems Biology, College of Life and Environmental Sciences, Minzu University of China, Beijing, 100081, China;
3. New Drug Safety Evaluation Center, Chinese Academy of Medical Sciences, Beijing 100050, China;
4. State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China

Funds:

This research was supported by the National Key Research and Development Program of China (Grant No.: 2023YFC3504401) and National Natural Science Foundation of China (Grant Nos.: 21927808 and 81803483).

Received Date: Sep. 24, 2025
Accepted Date: Mar. 01, 2026
Rev Recd Date: Feb. 28, 2026
Available Online: Mar. 12, 2026

Abstract

Abstract

Diabetic eye disease (DED) is a leading cause of vision impairment worldwide, yet the molecular mechanisms underlying its progression remain incompletely understood. In this study, we applied a dual-platform spatial metabolomics strategy integrating air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) and matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) to characterize spatial metabolic alterations in the eyes of diabetic rats. Data-driven segmentation of retinal micro-regions using SCiLS Lab software enabled fine-scale mapping of metabolic heterogeneity. Physiological, biochemical, and histopathological analyses were combined with spatial metabolite mapping to construct a metabolic atlas and evaluate the regulatory effects of ferulic acid. We established a comprehensive spatial metabolome atlas of the rat eye, identifying 135 annotated metabolites and revealing significant region-specific metabolic heterogeneity. Unsupervised k-means clustering was further applied to the high-resolution MALDI-MSI data, successfully delineating distinct functional micro-regions of the retina solely based on endogenous metabolic profiles, demonstrating the power of data-driven tissue segmentation. In diabetic eyes, 39 metabolites were significantly dysregulated, involving amino acid, glucose, lipid, and redox metabolism. Notably, lysine, arginine, carnitine, and GSH were depleted, while glucose-6-phosphate (G6P), glycerol-3-phosphate (G3P), and pro-inflammatory lipids were elevated, highlighting profound metabolic reprogramming across ocular compartments. Ferulic acid treatment restored nine key metabolites, alleviated oxidative stress, normalized lipid and glucose metabolism, and improved retinal structural integrity in a dose-dependent manner. This study shows that integrating mass spectrometry imaging with data-driven tissue segmentation reveals spatial metabolic reprogramming in DED and highlights ferulic acid as a promising therapeutic candidate.

FullText(HTML)

References(54)

References

[1]	A. Pollreisz, V. Gasser-Steiner, B. Gerendas, et al., Diagnosis, treatment and monitoring of diabetic eye disease (Update 2023), Wien. Klin. Wochenschr., 135 (2023) 195-200.
[2]	R. Cheloni, S.A. Gandolfi, C. Signorelli, et al., Global prevalence of diabetic retinopathy: protocol for a systematic review and meta-analysis, BMJ open, 9 (2019) e022188.
[3]	J.Q. Chen, C.Y. Yang, W.X. Zheng, et al., Global, regional, and national epidemiology of visual impairment in working-age individuals, 1990-2019, JAMA Ophthalmol., 142 (2024) 25-32.
[4]	D.S.J. Ting, C.S. Ho, R. Deshmukh, et al., Infectious keratitis: an update on epidemiology, causative microorganisms, risk factors, and antimicrobial resistance, Eye, 35 (2021) 1084-1101.
[5]	K.C. Shih, S.L. Lam, L. Tong, A systematic review on the impact of diabetes mellitus on the ocular surface, Nutr. Diabetes, 7 (2017) e251.
[6]	B. Giri, S. Dey, T. Das, et al., Chronic hyperglycemia mediated physiological alteration and metabolic distortion leads to organ dysfunction, infection, cancer progression and other pathophysiological consequences: An update on glucose toxicity, Biomed. Pharmacother., 107 (2018) 306-328.
[7]	M. Simmonds, A. Llewellyn, R. Walker, et al., Anti-VEGF drugs compared with laser photocoagulation for the treatment of diabetic retinopathy: a systematic review and meta-analysis, Health Technol. Assess, 29 (2024) 1-71.
[8]	F. Pelit, I. Erbas, N. Mert Ozupek, et al., A novel approach utilizing rapid thin-film microextraction method for salivary metabolomics studies in lung cancer diagnosis, Microchem. J., 207 (2024) 112069.
[9]	T. Recber, E. Nemutlu, K. Beksac, et al., Optimization and normalization strategies for long term untargeted HILIC-LC-qTOF-MS based metabolomics analysis: Early diagnosis of breast cancer, Microchem. J., 179 (2022) 107658.
[10]	M. Maulidiani, F. Abas, R. Rudiyanto, et al., Analysis of urinary metabolic alteration in type 2 diabetic rats treated with metformin using the metabolomics of quantitative spectral deconvolution 1H NMR spectroscopy, Microchem. J., 153 (2020) 104513.
[11]	S. Hosseinkhani, B. Arjmand, A. Dilmaghani-Marand, et al., Targeted metabolomics analysis of amino acids and acylcarnitines as risk markers for diabetes by LC-MS/MS technique, Sci. Rep., 12 (2022) 8418.
[12]	Y.H. Li, S.X. Liu, Y.S. Zhang, et al., Development of a dual-channel analytical approach for diabetic biomarker discovery in blood via integrative metabolomics and lipidomics, J. Chromatogr. A, 1760 (2025) 466323.
[13]	L.D. Hu, L.L. Yu, Z.K. Cao, et al., Integrating transcriptomics, metabolomics, and network pharmacology to investigate multi-target effects of sporoderm-broken spores of Ganoderma lucidum on improving HFD-induced diabetic nephropathy rats, J. Pharm. Anal., 14 (2024) 101105.
[14]	H. Zhang, K.H. Lu, M. Ebbini, et al., Mass spectrometry imaging for spatially resolved multi-omics molecular mapping, Npj Imaging, 2 (2024) 20.
[15]	X. Guo, X. Wang, C.Y. Tian, et al., Development of mass spectrometry imaging techniques and its latest applications, Talanta, 264 (2023) 124721.
[16]	D.M. Anderson, Z. Ablonczy, Y. Koutalos, et al., High resolution MALDI imaging mass spectrometry of retinal tissue lipids, J. Am. Soc. Mass Spectrom., 25 (2014) 1394-1403.
[17]	Y. Chen, J.V. Jester, D.M. Anderson, et al., Corneal haze phenotype in Aldh3a1-null mice: In vivo confocal microscopy and tissue imaging mass spectrometry, Chem.-Biol. Interact., 276 (2017) 9-14.
[18]	Y.H. Liu, X. Zhang, S. Yang, et al., Integrated mass spectrometry imaging reveals spatial-metabolic alteration in diabetic cardiomyopathy and the intervention effects of ferulic acid, J. Pharm. Anal., 13 (2023) 1496-1509.
[19]	S.H. Cheng, X.Y. Meng, Z.X. Wang, et al., Mass Spectrometry Imaging Reveals Spatial Metabolic Alterations and Salidroside's Effects in Diabetic Encephalopathy, Metabolites, 14 (2024) 670.
[20]	X.Y. Luo, S. Yang, S.H. Cheng, et al., Multimodal mass spectrometry imaging reveals spatial metabolic reprogramming in diabetic liver disease, Talanta, 291 (2025) 127891.
[21]	S.H. Cheng, W.B. Zhou, Y.H. Ren, et al., Spatial metabolic modulation in vascular dementia by Erigeron breviscapus injection using ambient mass spectrometry imaging, Phytomedicine, 138 (2025) 156412.
[22]	Z.Q. Pang, Y. Lu, G.Y. Zhou, et al., MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation, Nucleic Acids Res., 52 (2024) W398-W406.
[23]	R. Milne, S. Brownstein, Advanced glycation end products and diabetic retinopathy, Amino Acids, 44 (2013) 1397-1407.
[24]	K.S. Peters, E. Rivera, C. Warden, et al., Plasma Arginine and Citrulline are Elevated in Diabetic Retinopathy, Am. J. Ophthalmol., 235 (2022) 154-162.
[25]	J.L. Flanagan, P.A. Simmons, J. Vehige, et al., Role of carnitine in disease, Nutr. Metab., 7 (2010) 30.
[26]	A.O. Turgut, B. Kandil, E.K. Bilen, et al., The Negative Effects of Subclinical Pregnancy Toxaemia on Fetal Skeletal Muscle Development and Evaluation of the Protective Effects of Dietary l-Carnitine Supplementation in Sheep, Reprod. Domest. Anim., 60 (2025) e70088.
[27]	N. Longo, M. Frigeni, M. Pasquali, Carnitine transport and fatty acid oxidation, Biochim. Biophys. Acta, 1863 (2016) 2422-2435.
[28]	M. Yan, S.Z. Zhang, P.P. Liang, et al., Research Hotspots and Frontier Trends of Autophagy in Diabetic Cardiomyopathy From 2014 to 2024: A Bibliometric Analysis, J. Multidiscip. Healthc., (2025) 837-860.
[29]	H. Takashima, T. Maruyama, M. Abe, Significance of levocarnitine treatment in dialysis patients, Nutrients, 13 (2021) 1219.
[30]	G. Mingrone, Carnitine in type 2 diabetes, Ann. N. Y. Acad. Sci., 1033 (2004) 99-107.
[31]	F. Xiang, Z.M. Zhang, J.C. Xie, et al., Comprehensive review of the expanding roles of the carnitine pool in metabolic physiology: beyond fatty acid oxidation, J. Transl. Med., 23 (2025) 324.
[32]	S.P. Yang, R.Q. Liu, Z.Y. Xin, et al., Plasma Metabolomics identifies key metabolites and improves prediction of diabetic retinopathy: development and validation across multinational cohorts, Ophthalmol., 131 (2024) 1436-1446.
[33]	C. Peiro, T. Romacho, V. Azcutia, et al., Inflammation, glucose, and vascular cell damage: the role of the pentose phosphate pathway, Cardiovasc. Diabetol., 15 (2016) 82.
[34]	E. Possik, A. Al-Mass, M.-L. Peyot, et al., New mammalian glycerol-3-phosphate phosphatase: role in β-cell, liver and adipocyte metabolism, Front. Endocrinol., 12 (2021) 706607.
[35]	K. Tighanimine, J.A. Nabuco Leva Ferreira Freitas, I. Nemazanyy, et al., A homoeostatic switch causing glycerol-3-phosphate and phosphoethanolamine accumulation triggers senescence by rewiring lipid metabolism, Nat. Metab., 6 (2024) 323-342.
[36]	L.L. Li, P. Wang, X.D. Jiao, et al., Fatty acid esters of hydroxy fatty acids: A potential treatment for obesity-related diseases, Obes. Rev., 25 (2024) e13735.
[37]	A. Borsini, A. Nicolaou, D. Camacho-Munoz, et al., Omega-3 polyunsaturated fatty acids protect against inflammation through production of LOX and CYP450 lipid mediators: relevance for major depression and for human hippocampal neurogenesis, Mol. Psychiatry, 26 (2021) 6773-6788.
[38]	K. Brejchova, L. Balas, V. Paluchova, et al., Understanding FAHFAs: From structure to metabolic regulation, Prog. Lipid Res., 79 (2020) 101053.
[39]	S.L. Chen, H.D. Zou, Key Role of 12-Lipoxygenase and Its Metabolite 12-Hydroxyeicosatetraenoic Acid (12-HETE) in Diabetic Retinopathy, Curr. Eye Res., 47 (2022) 329-335.
[40]	Q.H. Xuan, Y. Ouyang, Y.F. Wang, et al., Multiplatform Metabolomics Reveals Novel Serum Metabolite Biomarkers in Diabetic Retinopathy Subjects, Adv. Sci., 7 (2020) 2001714.
[41]	C. Zhang, Y. Feng, X. Zhang, et al., Lipidomic Profiling Reveals HSD17B13 Deficiency-Associated Dysregulated Hepatic Phospholipid Metabolism in Aged Mice, Metabolites, 15 (2025) 353.
[42]	B. Du, K. Mu, M. Sun, et al., Biliary atresia and cholestasis plasma non-targeted metabolomics unravels perturbed metabolic pathways and unveils a diagnostic model for biliary atresia, Sci. Rep., 14 (2024) 15796.
[43]	J.V. Busik, W.J. Esselman, G.E. Reid, Examining the role of lipid mediators in diabetic retinopathy, Clin. Lipidol., 7 (2012) 661-675.
[44]	T.E. Fox, X. Han, S. Kelly, et al., Diabetes alters sphingolipid metabolism in the retina: a potential mechanism of cell death in diabetic retinopathy, Diabetes, 55 (2006) 3573-3580.
[45]	J.W. Jocken, G.H. Goossens, H. Boon, et al., Insulin-mediated suppression of lipolysis in adipose tissue and skeletal muscle of obese type 2 diabetic men and men with normal glucose tolerance, Diabetologia, 56 (2013) 2255-2265.
[46]	X. Wen, T.K. Ng, Q.P. Liu, et al., Azelaic acid and guanosine in tears improve discrimination of proliferative from non-proliferative diabetic retinopathy in type-2 diabetes patients: A tear metabolomics study, Heliyon, 9 (2023) e16109.
[47]	Y. Sun, Y.F. Zheng, C.X. Wang, et al., Glutathione depletion induces ferroptosis, autophagy, and premature cell senescence in retinal pigment epithelial cells, Cell Death Dis., 9 (2018) 753.
[48]	N.R. Haines, N. Manoharan, J.L. Olson, et al., Metabolomics analysis of human vitreous in diabetic retinopathy and rhegmatogenous retinal detachment, J. Proteome Res., 17 (2018) 2421-2427.
[49]	Y. Luo, H.P. Cui, Y. Liu, et al., Metabolomics and biomarkers in ocular matrix: beyond ocular diseases, Int. J. Ophthalmol., 13 (2020) 991.
[50]	C. Ding, N. Wang, Z.C. Wang, et al., Integrated analysis of metabolomics and lipidomics in plasma of T2DM patients with diabetic retinopathy, Pharm., 14 (2022) 2751.
[51]	M.S. Bhuia, R. Chowdhury, M.C. Shill, et al., Therapeutic Promises of Ferulic Acid and its Derivatives on Hepatic damage Related with Oxidative Stress and Inflammation: A Review with Mechanisms, Chem. Biodiversity, 21 (2024) e202400443.
[52]	L. Ye, P. Hu, L.P. Feng, et al., Protective Effects of Ferulic Acid on Metabolic Syndrome: A Comprehensive Review, Molecules, 28 (2022) 281.
[53]	Y. Li, W. Zhao, A.T. Sair, et al., Ferulic acid restores mitochondrial dynamics and autophagy via AMPK signaling pathway in a palmitate-induced hepatocyte model of metabolic syndrome, Sci. Rep., 14 (2024) 18970.
[54]	K.A. Khan, M.H. Saleem, S. Afzal, et al., Ferulic acid: therapeutic potential due to its antioxidant properties, role in plant growth, and stress tolerance, Plant Growth Regul., 104 (2024) 1329-1353.