Advancements and Challenges in Salivary Metabolomics for Early Detection and Monitoring of Systemic Diseases

Abstract

Salivary metabolomics is increasingly recognized as a powerful, noninvasive approach for studying human health and disease. Unlike blood or urine, saliva is easily accessible, minimally invasive, and suitable for repeated sampling. Advances in nuclear magnetic resonance, mass spectrometry, capillary electrophoresis, and bioinformatics have improved the sensitivity and reproducibility of salivary metabolite profiling, enabling its use across diverse systemic diseases such as cancer, cardiovascular disorders, diabetes, viral infections, autoimmune diseases, and neurodegenerative conditions. Despite this progress, clinical translation is limited by variability in sampling, lack of standardized protocols, and insufficient large-scale validation. This review synthesizes recent developments in human salivary metabolomics, emphasizing disease-specific biomarkers and key applications in systemic disease diagnosis and monitoring. We also examine methodological and biological factors that influence data reliability, including collection methods, storage conditions, circadian rhythms, age, and host–microbiome interactions. Furthermore, integration of multiomics strategies, machine learning, and clinical registry data is discussed as a means to enhance biomarker discovery and translational potential. By addressing these challenges, salivary metabolomics can evolve into a reliable platform for noninvasive diagnosis, longitudinal disease monitoring, and personalized medicine, providing a valuable complement to blood-based diagnostics in precision healthcare.

Keywords

biomarkers / metabolic profiling / noninvasive diagnosis / salivary metabolomics / systemic diseases

References

[1] C. B. Newgard, “Metabolomics and Metabolic Diseases: Where Do We Stand?,” Cell Metabolism 25, no. 1 (2017): 43-56.

[2] H. Huang, Y. Chen, W. Xu, et al., “Decoding Aging Clocks: New Insights From Metabolomics,” Cell Metabolism 37, no. 1 (2025): 34-58.

[3] L. Cui, H. Lu, and Y. H. Lee, “Challenges and Emergent Solutions for LC-MS/MS Based Untargeted Metabolomics in Diseases,” Mass Spectrometry Reviews 37, no. 6 (2018): 772-792.

[4] M. Pietzner, I. D. Stewart, J. Raffler, et al., “Plasma Metabolites to Profile Pathways in Noncommunicable Disease Multimorbidity,” Nature Medicine 27, no. 3 (2021): 471-479.

[5] D. Chen, W. Chan, S. Zhao, L. Li, and L. Li, “High-Coverage Quantitative Metabolomics of Human Urine: Effects of Freeze-Thaw Cycles on the Urine Metabolome and Biomarker Discovery,” Analytical Chemistry 94, no. 27 (2022): 9880-9887.

[6] Y. Li, Y. Feng, Z. Yang, Z. Zhou, D. Jiang, and J. Luo, “Untargeted Metabolomics of Saliva in Pregnant Women With and Without Gestational Diabetes Mellitus and Healthy Non-Pregnant Women,” Frontiers in Cellular and Infection Microbiology 13 (2023): 1206462.

[7] G. Baima, G. Iaderosa, F. Citterio, et al., “Salivary Metabolomics for the Diagnosis of Periodontal Diseases: A Systematic Review With Methodological Quality Assessment,” Metabolomics 17, no. 1 (2021): 1.

[8] S. Ishikawa, M. Sugimoto, K. Kitabatake, et al., “Identification of Salivary Metabolomic Biomarkers for Oral Cancer Screening,” Scientific Reports 6, no. 1 (2016): 31520.

[9] X. Zhao, X. Chen, Y. Lu, et al., “Saliva Metabolomics: A Non-Invasive Frontier for Diagnosing and Managing Oral Diseases,” Journal of Translational Medicine 23, no. 1 (2025): 582.

[10] Z. Huang, X. Yang, Y. Huang, et al., “Saliva—a New Opportunity for Fluid Biopsy,” Clinical Chemistry and Laboratory Medicine 61, no. 1 (2023): 4-32.

[11] C. Z. Zhang, X. Q. Cheng, J. Y. Li, et al., “Saliva in the Diagnosis of Diseases,” International Journal of Oral Science 8, no. 3 (2016): 133-137.

[12] Y. Zhou and Z. Liu, “Saliva Biomarkers in Oral Disease,” Clinica Chimica Acta 548 (2023): 117503.

[13] K. Okuyama and S. Yanamoto, “Saliva in Balancing Oral and Systemic Health, Oral Cancer, and Beyond: A Narrative Review,” Cancers 16, no. 24 (2024): 4276.

[14] M. Dodds, S. Roland, M. Edgar, and M. Thornhill, “Saliva a Review of Its Role in Maintaining Oral Health and Preventing Dental Disease,” BDJ Team 2, no. 1 (2015): 15123.

[15] J. Zheng, R. A. Dixon, and L. Li, “Development of Isotope Labeling LC-MS for human Salivary Metabolomics and Application to Profiling Metabolome Changes Associated With Mild Cognitive Impairment,” Analytical Chemistry 84, no. 24 (2012): 10802-10811.

[16] L. C. A. Bragard, M. R. C. Sete, L. B. Freitas-Fernandes, et al., “Salivary Metabolomic Profile in Adolescents With Juvenile Systemic Lupus Erythematosus,” Brazilian Oral Research 36 (2022): e0128.

[17] N. Kajiwara, M. Kakihana, J. Maeda, et al., “Salivary Metabolomic Biomarkers for Non-Invasive Lung Cancer Detection,” Cancer Science 115, no. 5 (2024): 1695-1705.

[18] V. Dosedělová, M. Laštovičková, Š. Konečný, J. Dolina, and P. Kubáň, “Optimization of Saliva Sampling Methods for Analysis of Bile Acids by UHPLC-MS,” Journal of Chromatography A 1736 (2024): 465354.

[19] L. d'Amone, G. Matzeu, and F. G. Omenetto, “Stabilization of Salivary Biomarkers,” ACS Biomaterials Science & Engineering 7, no. 12 (2021): 5451-5473.

[20] N. L. Kuehnbaum and P. Britz-McKibbin, “New Advances in Separation Science for Metabolomics: Resolving Chemical Diversity in a Post-Genomic Era,” Chemical Reviews 113, no. 4 (2013): 2437-2468.

[21] M. Breier, S. Wahl, C. Prehn, et al., “Targeted Metabolomics Identifies Reliable and Stable Metabolites in human Serum and Plasma Samples,” PLoS ONE 9, no. 2 (2014): e89728.

[22] S. C. Kalhan, L. Guo, J. Edmison, et al., “Plasma Metabolomic Profile in Nonalcoholic Fatty Liver Disease,” Metabolism 60, no. 3 (2011): 404-413.

[23] Y. Yuan, C. Wang, G. Wang, et al., “Airway Microbiome and Serum Metabolomics Analysis Identify Differential Candidate Biomarkers in Allergic Rhinitis,” Frontiers in Immunology 12 (2021): 771136.

[24] W. Wang, M. Huang, W. Ge, et al., “Identifying Serum Metabolite Biomarkers for Autoimmune Diseases: A Two-Sample Mendelian Randomization and Meta-Analysis,” Frontiers in Immunology 15 (2024): 1300457.

[25] M. Haid, C. Muschet, S. Wahl, et al., “Long-Term Stability of Human Plasma Metabolites During Storage at -80°C,” Journal of Proteome Research 17, no. 1 (2018): 203-211.

[26] V. M. Barnes, A. D. Kennedy, F. Panagakos, et al., “Global Metabolomic Analysis of human Saliva and Plasma From Healthy and Diabetic Subjects, With and Without Periodontal Disease,” PLoS ONE 9, no. 8 (2014): e105181.

[27] Y. Han, L. Jia, Y. Zheng, and W. Li, “Salivary Exosomes: Emerging Roles in Systemic Disease,” International Journal of Biological Sciences 14, no. 6 (2018): 633-643.

[28] E. Hyvärinen, B. Kashyap, and A. M. Kullaa, “Oral Sources of Salivary Metabolites,” Metabolites 13, no. 4 (2023): 498.

[29] S. Liu, S. Zhang, H. Chen, et al., “Changes in the Salivary Metabolome in Patients With Chronic Erosive Gastritis,” BMC Gastroenterology [Electronic Resource] 23, no. 1 (2023): 161.

[30] L. B. Freitas-Fernandes, T. K. S. Fidalgo, P. A. de Almeida, I. P. R. Souza, and A. P. Valente, “Salivary Metabolome of Children and Adolescents Under Peritoneal Dialysis,” Clinical Oral Investigations 25, no. 4 (2021): 2345-2351.

[31] D. Duarte, B. Castro, J. L. Pereira, J. F. Marques, A. L. Costa, and A. M. Gil, “Evaluation of Saliva Stability for NMR Metabolomics: Collection and Handling Protocols,” Metabolites 10, no. 12 (2020): 515.

[32] A. Sakanaka, M. Kuboniwa, N. Katakami, et al., “Saliva and Plasma Reflect Metabolism Altered by Diabetes and Periodontitis,” Frontiers in Molecular Biosciences 8 (2021): 742002.

[33] M. M. Abboud, F. A. Al-Rawashde, and E. M. Al-Zayadneh, “Alterations of Serum and Saliva Oxidative Markers in Patients With Bronchial Asthma,” Journal of Asthma 59, no. 11 (2022): 2154-2161.

[34] E. Ferrari, M. Gallo, A. Spisni, R. Antonelli, M. Meleti, and T. A. Pertinhez, “Human Serum and Salivary Metabolomes: Diversity and Closeness,” International Journal of Molecular Sciences 24, no. 23 (2023): 16603.

[35] G. A. Padilla, J. L. Calvi, M. K. Taylor, and D. A. Granger, “Saliva Collection, Handling, Transport, and Storage: Special Considerations and Best Practices for Interdisciplinary Salivary Bioscience Research,” in Salivary Bioscience: Foundations of Interdisciplinary Saliva Research and Applications, ed. D. A. Granger and M. K. Taylor (Springer International Publishing, 2020), 21-47.

[36] C. Liao, X. Chen, and Y. Fu, “Salivary Analysis: An Emerging Paradigm for Non-Invasive Healthcare Diagnosis and Monitoring,” Interdisciplinary Medicine 1, no. 3 (2023): e20230009.

[37] M. Elyashberg, “Identification and Structure Elucidation by NMR Spectroscopy,” TRAC Trends in Analytical Chemistry 69 (2015): 88-97.

[38] C. Zheng, S. Zhang, S. Ragg, D. Raftery, and O. Vitek, “Identification and Quantification of Metabolites in 1H NMR Spectra by Bayesian Model Selection,” Bioinformatics 27, no. 12 (2011): 1637-1644.

[39] G. Wider and L. Dreier, “Measuring Protein Concentrations by NMR Spectroscopy,” Journal of the American Chemical Society 128, no. 8 (2006): 2571-2576.

[40] L. S. Lloyd, R. W. Adams, M. Bernstein, et al., “Utilization of SABRE-Derived Hyperpolarization To Detect Low-Concentration Analytes via 1D and 2D NMR Methods,” Journal of the American Chemical Society 134, no. 31 (2012): 12904-12907.

[41] C. Lhoste, B. Lorandel, C. Praud, et al., “Ultrafast 2D NMR for the Analysis of Complex Mixtures,” Progress in Nuclear Magnetic Resonance Spectroscopy 130-131 (2022): 1-46.

[42] J. Debik, M. Sangermani, F. Wang, T. S. Madssen, and G. F. Giskeødegård, “Multivariate Analysis of NMR-Based Metabolomic Data,” NMR in Biomedicine 35, no. 2 (2022): e4638.

[43] P. Klukowski, R. Riek, and P. Güntert, “Machine Learning in NMR Spectroscopy,” Progress in Nuclear Magnetic Resonance Spectroscopy 148-149 (2025): 101575.

[44] Y. Luo, W. Chen, and Z. Su, “Deep Learning Network for NMR Spectra Reconstruction in Time-Frequency Domain and Quality Assessment,” Nature Communications 16, no. 1 (2025): 2342.

[45] D. Olivier-Jimenez, M. Chollet-Krugler, D. Rondeau, et al., “A Database of High-Resolution MS/MS Spectra for Lichen Metabolites,” Scientific Data 6, no. 1 (2019): 294.

[46] L. Jaitz, B. Mueller, G. Koellensperger, et al., “LC-MS Analysis of Low Molecular Weight Organic Acids Derived From Root Exudation,” Analytical and Bioanalytical Chemistry 400, no. 8 (2011): 2587-2596.

[47] L. He, X. Wei, X. Ma, et al., “Simultaneous Quantification of Nucleosides and Nucleotides From Biological Samples,” Journal of The American Society for Mass Spectrometry 30, no. 6 (2019): 987-1000.

[48] S. Alanazi, “Recent Advances in Liquid Chromatography-Mass Spectrometry (LC-MS) Applications in Biological and Applied Sciences,” Analytical Science Advances 6, no. 1 (2025): e70024.

[49] A. Jannasch, M. Sedlak, and J. Adamec, “Quantification of Pentose Phosphate Pathway (PPP) Metabolites by Liquid Chromatography-Mass Spectrometry (LC-MS),” Methods in Molecular Biology 708 (2011): 159-171.

[50] M. Israelsson, R. Brattsand, and G. Brattsand, “20α- and 20β-Dihydrocortisone May Interfere in LC-MS/MS Determination of Cortisol in Saliva and Urine,” Annals of Clinical Biochemistry 55, no. 3 (2018): 341-347.

[51] W. B. Dunn, D. Broadhurst, P. Begley, et al., “Procedures for Large-Scale Metabolic Profiling of Serum and Plasma Using Gas Chromatography and Liquid Chromatography Coupled to Mass Spectrometry,” Nature Protocols 6, no. 7 (2011): 1060-1083.

[52] S. Zhang, H. Wang, and M. J. Zhu, “A Sensitive GC/MS Detection Method for Analyzing Microbial Metabolites Short Chain Fatty Acids in Fecal and Serum Samples,” Talanta 196 (2019): 249-254.

[53] J. A. Custodio-Mendoza, C. Caamaño-Fernandez, M. A. Lage, P. J. Almeida, R. A. Lorenzo, and A. M. Carro, “GC-MS Determination of Malondialdehyde, Acrolein, and 4-Hydroxy-2-Nonenal by Ultrasound-Assisted Dispersive Liquid-Liquid Microextraction in Beverages,” Food Chemistry 384 (2022): 132530.

[54] H. G. Schmarr, W. Sang, and S. Ganss, “Analysis of Aldehydes via Headspace SPME With on-Fiber Derivatization to Their O-(2,3,4,5,6-Pentafluorobenzyl) Oxime Derivatives and Comprehensive 2D-GC-MS,” Journal of Separation Science 31, no. 19 (2008): 3458-3465.

[55] A. B. Fialkov, U. Steiner, S. J. Lehotay, and A. Amirav, “Sensitivity and Noise in GC-MS: Achieving Low Limits of Detection for Difficult Analytes,” International Journal of Mass Spectrometry 260, no. 1 (2007): 31-48.

[56] K. Tsutsui, M. Nemoto, M. Kono, et al., “GC-MS Analysis of Exhaled Gas for Fine Detection of Inflammatory Diseases,” Analytical Biochemistry 671 (2023): 115155.

[57] Y. Wang, Y. Huang, L. Song, et al., “The Characteristic VOCs of Different Parts of Artocarpus Heterophyllus Fruit Based on HS-SPME-GC-MS and PTR-TOF-MS,” Food Chemistry 459 (2024): 140431.

[58] S. C. Moldoveanu and V. David, “Derivatization Methods in GC and GC/MS,” in Gas Chromatography—Derivatization, Sample Preparation, Application, ed. P. Kusch (IntechOpen, 2018).

[59] C. Yu, L. Wang, J. Zheng, et al., “Nanoconfinement Effect Based in-Fiber Extraction and Derivatization Method for Ultrafast Analysis of Twenty Amines in human Urine by GC-MS: Application to Cancer Diagnosis Biomarkers' screening,” Analytica Chimica Acta 1217 (2022): 339985.

[60] J. M. Halket, D. Waterman, A. M. Przyborowska, R. K. Patel, P. D. Fraser, and P. M. Bramley, “Chemical Derivatization and Mass Spectral Libraries in Metabolic Profiling by GC/MS and LC/MS/MS,” Journal of Experimental Botany 56, no. 410 (2005): 219-243.

[61] A. Srinivasan, T. Maruthavanan, R. Mayildurai, and A. Ramasubbu, “GC-MS Investigations of VOCs in South Indian Honey Samples as Environmental Biomarkers,” Environmental Monitoring and Assessment 193, no. 8 (2021): 539.

[62] B. S. Seetha, S. Ganneru, R. Thati, and M. K. R. Mudiam, “Experimental Design of Non-Ionic Hydrophobic DES-DLLME Coupled With Injector Port Silylation-GC-MS/MS for the Quantitative Determination of 13 Bisphenols in Food Samples,” Food Chemistry 405, no. Pt A (2023): 134778.

[63] J. W. Tang, J. Y. Mou, J. Chen, et al., “Discrimination of Benign and Malignant Thyroid Nodules Through Comparative Analyses of Human Saliva Samples via Metabolomics and Deep-Learning-Guided Label-Free SERS,” ACS Applied Materials & Interfaces 17, no. 3 (2025): 5538-5549.

[64] V. L. Kouznetsova, J. Li, E. Romm, and I. F. Tsigelny, “Finding Distinctions Between Oral Cancer and Periodontitis Using Saliva Metabolites and Machine Learning,” Oral Diseases 27, no. 3 (2021): 484-493.

[65] T. Murata, T. Yanagisawa, T. Kurihara, et al., “Salivary Metabolomics With Alternative Decision Tree-Based Machine Learning Methods for Breast Cancer Discrimination,” Breast Cancer Research and Treatment 177, no. 3 (2019): 591-601.

[66] Y. Kobayashi, N. Fujiwara, Y. Murakami, et al., “Visualizing Fatigue Mechanisms in Non-Communicable Diseases: An Integrative Approach With Multi-Omics and Machine Learning,” BMC Medical Informatics and Decision Making 25, no. 1 (2025): 204.

[67] N. Peiffer-Smadja, T. M. Rawson, R. Ahmad, et al., “Machine Learning for Clinical Decision Support in Infectious Diseases: A Narrative Review of Current Applications,” Clinical Microbiology and Infection 26, no. 5 (2020): 584-595.

[68] C. Guan, A. Gong, Y. Zhao, et al., “Interpretable Machine Learning Model for New-Onset Atrial Fibrillation Prediction in Critically Ill Patients: A Multi-Center Study,” Critical Care (London, England) 28, no. 1 (2024): 349.

[69] K. Fuse, S. Uemura, S. Tamura, et al., “Patient-Based Prediction Algorithm of Relapse After Allo-HSCT for Acute Leukemia and Its Usefulness in the Decision-Making Process Using a Machine Learning Approach,” Cancer Medicine 8, no. 11 (2019): 5058-5067.

[70] G. Urbanski, F. Chabrun, E. Delattre, et al., “An Immuno-Lipidomic Signature Revealed by Metabolomic and Machine-Learning Approaches in Labial Salivary Gland to Diagnose Primary Sjögren's Syndrome,” Frontiers in Immunology 14 (2023): 1205616.

[71] H. Kuwabara, K. Katsumata, A. Iwabuchi, et al., “Salivary Metabolomics With Machine Learning for Colorectal Cancer Detection,” Cancer Science 113, no. 9 (2022): 3234-3243.

[72] A. Roi, L. C. Rusu, C. I. Roi, R. E. Luca, S. Boia, and R. I. Munteanu, “A New Approach for the Diagnosis of Systemic and Oral Diseases Based on Salivary Biomolecules,” Disease Markers 2019, no. 1 (2019): 8761860.

[73] M. Matsuoka, S. A. Soria, J. R. Pires, A. C. P. Sant'Ana, and M. Freire, “Natural and Induced Immune Responses in Oral Cavity and Saliva,” BMC Immunology 26, no. 1 (2025): 34.

[74] S. A. Ali, S. Habib, A. Ali, Moinuddin, and E. Haque, “Role of Salivary Markers for Diagnosis of Systemic Diseases,” in Toxicology and Human Health: Environmental Exposures and Biomarkers, ed. M. I. Ahmad, M. Mahamood, M. Javed, and S. S. Alhewairini (Springer Nature Singapore, 2023), 159-178.

[75] Z. T. Dame, F. Aziat, R. Mandal, et al., “The Human Saliva Metabolome,” Metabolomics 11, no. 6 (2015): 1864-1883.

[76] A. Gardner, G. Carpenter, and P. W. So, “Salivary Metabolomics: From Diagnostic Biomarker Discovery to Investigating Biological Function,” Metabolites 10, no. 2 (2020): 47.

[77] X. Peng, L. Cheng, Y. You, et al., “Oral Microbiota in human Systematic Diseases,” International Journal of Oral Science 14, no. 1 (2022): 14.

[78] P. Dongiovanni, M. Meroni, S. Casati, et al., “Salivary Biomarkers: Novel Noninvasive Tools to Diagnose Chronic Inflammation,” International Journal of Oral Science 15, no. 1 (2023): 27.

[79] S. Şenel, “An Overview of Physical, Microbiological and Immune Barriers of Oral Mucosa,” International Journal of Molecular Sciences 22, no. 15 (2021): 7821.

[80] R. Cueto, W. Shen, L. Liu, et al., “SAH Is a Major Metabolic Sensor Mediating Worsening Metabolic Crosstalk in Metabolic Syndrome,” Redox Biology 73 (2024): 103139.

[81] I. Lopes de Lima, A. Ap Rosini Silva, and C. Brites, “Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19,” International Journal of Molecular Sciences 25, no. 22 (2024): 11899.

[82] M. Spick, H. M. Lewis, C. F. Frampas, et al., “An Integrated Analysis and Comparison of Serum, Saliva and Sebum for COVID-19 Metabolomics,” Scientific Reports 12, no. 1 (2022): 11867.

[83] M. Bourgin, S. Durand, and G. Kroemer, “Diagnostic, Prognostic and Mechanistic Biomarkers of COVID-19 Identified by Mass Spectrometric Metabolomics,” Metabolites 13, no. 3 (2023): 342.

[84] K. Gilany, A. Mohamadkhani, S. Chashmniam, et al., “Metabolomics Analysis of the Saliva in Patients With Chronic hepatitis B Using Nuclear Magnetic Resonance: A Pilot Study,” Iranian Journal of Basic Medical Sciences 22, no. 9 (2019): 1044-1049.

[85] T. K. da Silva Fidalgo, L. B. Freitas-Fernandes, B. B. F. Marques, et al., “Salivary Metabolomic Analysis Reveals Amino Acid Metabolism Shift in SARS-CoV-2 Virus Activity and Post-Infection Condition,” Metabolites 13, no. 2 (2023): 263.

[86] C. Pozzi, R. Levi, D. Braga, et al., “A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019,” Gastro Hep Advances 1, no. 2 (2022): 194-209.

[87] F. Du, R. Li, R. He, et al., “Exploring Salivary Metabolome Alterations in People With HIV: Towards Early Diagnostic Markers,” Frontiers in Public Health 12 (2024): 1400332.

[88] G. Costa Dos Santos Junior, C. M. Pereira, T. Kelly da Silva Fidalgo, and A. P. Valente, “Saliva NMR-Based Metabolomics in the War against COVID-19,” Analytical Chemistry 92, no. 24 (2020): 15688-15692.

[89] L. T. Mendes, M. C. Gama-Almeida, D. L. Reis, et al., “Longitudinal (1)H NMR-Based Metabolomics in Saliva Unveils Signatures of Transition From Acute to Post-Acute Phase of SARS-CoV-2 Infection,” Viruses 16, no. 11 (2024): 1769.

[90] L. Machado, R. Prudente, E. Franco, et al., “Salivary Metabolomics in Patients With Long COVID-19 Infection,” Metabolites 14, no. 11 (2024): 598.

[91] N. Saheb Sharif-Askari, N. C. Soares, and H. A. Mohamed, “Saliva Metabolomic Profile of COVID-19 Patients Associates With Disease Severity,” Metabolomics 18, no. 11 (2022): 81.

[92] C. F. Frampas, K. Longman, M. Spick, et al., “Untargeted Saliva Metabolomics by Liquid Chromatography-Mass Spectrometry Reveals Markers of COVID-19 Severity,” PLoS ONE 17, no. 9 (2022): e0274967.

[93] B. Cotto, K. Natarajanseenivasan, and D. Langford, “HIV-1 Infection Alters Energy Metabolism in the Brain: Contributions to HIV-Associated Neurocognitive Disorders,” Progress in Neurobiology 181 (2019): 101616.

[94] C. Pretorius and L. Luies, “Characterising the Urinary Acylcarnitine and Amino Acid Profiles of HIV/TB Co-Infection, Using LC-MS Metabolomics,” Metabolomics 20, no. 5 (2024): 92.

[95] S. S. Mahalingam, S. Jayaraman, N. Bhaskaran, et al., “Polyamine Metabolism Impacts T Cell Dysfunction in the Oral Mucosa of People Living With HIV,” Nature Communications 14, no. 1 (2023): 399.

[96] F. Schulte, O. D. King, B. J. Paster, et al., “Salivary Metabolite Levels in Perinatally HIV-Infected Youth With Periodontal Disease,” Metabolomics 16, no. 9 (2020): 98.

[97] K. Nijakowski, J. Zdrojewski, M. Nowak, D. Gruszczynski, F. Knoll, and A. Surdacka, “Salivary Metabolomics for Systemic Cancer Diagnosis: A Systematic Review,” Metabolites 13, no. 1 (2022): 28.

[98] M. Sugimoto, D. T. Wong, A. Hirayama, T. Soga, and M. Tomita, “Capillary Electrophoresis Mass Spectrometry-Based Saliva Metabolomics Identified Oral, Breast and Pancreatic Cancer-Specific Profiles,” Metabolomics 6, no. 1 (2010): 78-95.

[99] X. Yan, M. Yang, J. Liu, et al., “Discovery and Validation of Potential Bacterial Biomarkers for Lung Cancer,” American Journal of Cancer Research 5, no. 10 (2015): 3111-3122.

[100] L. V. Bel'skaya, A. I. Loginova, and E. A. Sarf, “Pro-Inflammatory and Anti-Inflammatory Salivary Cytokines in Breast Cancer: Relationship With Clinicopathological Characteristics of the Tumor,” Current Issues in Molecular Biology 44, no. 10 (2022): 4676-4691.

[101] E. I. Dyachenko and L. V. Bel'skaya, “Salivary Transmembrane Mucins of the MUC1 Family (CA 15-3, CA 27.29, MCA) in Breast Cancer: The Effect of Human Epidermal Growth Factor Receptor 2 (HER2),” Cancers (Basel) 16, no. 20 (2024): 3461.

[102] T. Lan, L. Chen, and X. Wei, “Inflammatory Cytokines in Cancer: Comprehensive Understanding and Clinical Progress in Gene Therapy,” Cells 10, no. 1 (2021): 100.

[103] A. I. Makinen, V. Y. Pappalardo, M. J. Buijs, et al., “Salivary Microbiome Profiles of Oral Cancer Patients Analyzed Before and After Treatment,” Microbiome 11, no. 1 (2023): 171.

[104] Y. Ren, Q. Ma, X. Zeng, et al., “Saliva‑Microbiome‑Derived Signatures: Expected to Become a Potential Biomarker for Pulmonary Nodules (MCEPN-1),” BMC Microbiology 24, no. 1 (2024): 132.

[105] Z. Dong, Q. Chen, D. Zhao, et al., “Utilizing Saliva Metabolomics for Diagnosing Gastric Cancer and Exploring the Changes in Saliva Metabolites after Surgery,” OncoTargets and Therapy 17 (2024): 933-948.

[106] K. Nakane, K. Yagi, S. Yajima, S. Nomura, M. Sugimoto, and Y. Seto, “Salivary Metabolomic Biomarkers for Esophageal and Gastric Cancers by Liquid Chromatography-Mass Spectrometry,” Cancer Science 115, no. 9 (2024): 3089-3098.

[107] N. J. Daniels, C. E. Hershberger, M. Kerosky, et al., “Biomarker Discovery in Liver Disease Using Untargeted Metabolomics in Plasma and Saliva,” International Journal of Molecular Sciences 25, no. 18 (2024): 10144.

[108] C. E. Hershberger, R. Raj, and A. Mariam, “Characterization of Salivary and Plasma Metabolites as Biomarkers for HCC: A Pilot Study,” Cancers (Basel) 15, no. 18 (2023): 4527.

[109] C. E. Hershberger, A. I. Rodarte, S. Siddiqi, et al., “Salivary Metabolites Are Promising Non-Invasive Biomarkers of Hepatocellular Carcinoma and Chronic Liver Disease,” Liver Cancer International 2, no. 2 (2021): 33-44.

[110] X. Jiang, X. Chen, Z. Chen, J. Yu, H. Lou, and J. Wu, “High-Throughput Salivary Metabolite Profiling on an Ultralow Noise Tip-Enhanced Laser Desorption Ionization Mass Spectrometry Platform for Noninvasive Diagnosis of Early Lung Cancer,” Journal of Proteome Research 20, no. 9 (2021): 4346-4356.

[111] S. Shiraishi, M. Sugimoto, and K. Tokuuye, “Salivary Metabolites as Novel Independent Predictors of Radiation Pneumonitis,” Journal of Cancer Research and Clinical Oncology 149, no. 19 (2023): 17559-17566.

[112] T. Takayama, H. Tsutsui, I. Shimizu, et al., “Diagnostic Approach to Breast Cancer Patients Based on Target Metabolomics in Saliva by Liquid Chromatography With Tandem Mass Spectrometry,” Clinica Chimica Acta 452 (2016): 18-26.

[113] D. Xavier Assad, A. C. Acevedo, and E. Cançado Porto Mascarenhas, “Using an Untargeted Metabolomics Approach to Identify Salivary Metabolites in Women With Breast Cancer,” Metabolites 10, no. 12 (2020): 506.

[114] L. V. Bel'skaya, E. A. Sarf, and D. V. Solomatin, “Free Salivary Amino Acid Profile in Breast Cancer: Clinicopathological and Molecular Biological Features,” Current Issues in Molecular Biology 46, no. 6 (2024): 5614-5631.

[115] L. Zhong, F. Cheng, X. Lu, Y. Duan, and X. Wang, “Untargeted Saliva Metabonomics Study of Breast Cancer Based on Ultra Performance Liquid Chromatography Coupled to Mass Spectrometry With HILIC and RPLC Separations,” Talanta 158 (2016): 351-360.

[116] C. Cavaco, J. A. M. Pereira, K. Taunk, et al., “Screening of Salivary Volatiles for Putative Breast Cancer Discrimination: An Exploratory Study Involving Geographically Distant Populations,” Analytical and Bioanalytical Chemistry 410, no. 18 (2018): 4459-4468.

[117] J. Muller Bark, A. V. Karpe, J. D. Doecke, et al., “A Pilot Study: Metabolic Profiling of Plasma and Saliva Samples From Newly Diagnosed Glioblastoma Patients,” Cancer medicine 12, no. 10 (2023): 11427-11437.

[118] J. Zhang, X. Wen, Y. Li, et al., “Diagnostic Approach to Thyroid Cancer Based on Amino Acid Metabolomics in Saliva by Ultra-Performance Liquid Chromatography With High Resolution Mass Spectrometry,” Talanta 235 (2021): 122729.

[119] H. Hynne, E. M. Sandås, K. B. P. Elgstøen, et al., “Saliva Metabolomics in Dry Mouth Patients With Head and Neck Cancer or Sjögren's Syndrome,” Cells 11, no. 3 (2022): 323.

[120] G. Kageyama, J. Saegusa, Y. Irino, et al., “Metabolomics Analysis of Saliva From Patients With Primary Sjögren's Syndrome,” Clinical and Experimental Immunology 182, no. 2 (2015): 149-153.

[121] A. Bjork, J. Mofors, and M. Wahren-Herlenius, “Environmental Factors in the Pathogenesis of Primary Sjogren's Syndrome,” Journal of Internal Medicine 287, no. 5 (2020): 475-492.

[122] R. I. Fox, “Sjögren's Syndrome,” Lancet 366, no. 9482 (2005): 321-331.

[123] G. Piacenza Florezi, F. Pereira Barone, M. A. Izidoro, J. M. Soares-, C. M. Coutinho-Camillo, and S. V. Lourenço, “Targeted Saliva Metabolomics in Sjögren's Syndrome,” Clinics (Sao Paulo) 79 (2024): 100459.

[124] P. Bosman, V. Pichon, A. C. Acevedo, et al., “Identification of Potential Salivary Biomarkers for Sjögren's Syndrome With an Untargeted Metabolomic Approach,” Metabolomics 19, no. 9 (2023): 76.

[125] Z. Li, Y. Mu, C. Guo, et al., “Analysis of the Saliva Metabolic Signature in Patients With Primary Sjögren's Syndrome,” PLoS ONE 17, no. 6 (2022): e0269275.

[126] M. Herrala, J. J. W. Mikkonen, P. Pesonen, et al., “Variability of Salivary Metabolite Levels in Patients With Sjögren's Syndrome,” Journal of Oral Science 63, no. 1 (2020): 22-26.

[127] M. Herrala, S. Turunen, K. Hanhineva, et al., “Low-Dose Doxycycline Treatment Normalizes Levels of some Salivary Metabolites Associated With Oral Microbiota in Patients With Primary Sjögren's Syndrome,” Metabolites 11, no. 9 (2021): 595.

[128] A. Alt-Holland, X. Huang, T. Mendez, et al., “Identification of Salivary Metabolic Signatures Associated With Primary Sjögren's Disease,” Molecules (Basel, Switzerland) 28, no. 15 (2023): 5891.

[129] G. Setti, V. Righi, A. Mucci, et al., “Metabolic Profile of Whole Unstimulated Saliva in Patients With Sjögren's Syndrome,” Metabolites 13, no. 3 (2023): 348.

[130] L. The, “Diabetes: A Defining Disease of the 21st Century,” Lancet 401, no. 10394 (2023): 2087.

[131] M. Christ-Crain, D. G. Bichet, W. K. Fenske, et al., “Diabetes insipidus,” Nature Reviews Disease Primers 5, no. 1 (2019): 54.

[132] D. E. Haslam, L. Liang, K. Guo, et al., “Discovery and Validation of Plasma, Saliva and Multi-Fluid Plasma-Saliva Metabolomic Scores Predicting Insulin Resistance and Diabetes Progression or Regression Among Puerto Rican Adults,” Diabetologia 67, no. 9 (2024): 1838-1852.

[133] L. R. de Oliveira, C. Martins, T. K. Fidalgo, et al., “Salivary Metabolite Fingerprint of Type 1 Diabetes in Young Children,” Journal of Proteome Research 15, no. 8 (2016): 2491-2499.

[134] S. Bencharit, J. Carlson, W. C. Byrd, et al., “Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes,” International Journal of Dentistry 2022 (2022): 7544864.

[135] A. Alkahtani, M. Grootveld, M. Bhogadia, and A. Baysan, “Exploring Salivary Metabolic Alterations in Type 2 Diabetes: Implications for Dental Caries and Potential Influences of HbA1c and Vitamin D Levels,” Metabolites 14, no. 7 (2024): 372.

[136] A. Sakanaka, N. Katakami, M. Furuno, et al., “Salivary Metabolic Signatures of Carotid Atherosclerosis in Patients With Type 2 Diabetes Hospitalized for Treatment,” Frontiers in Molecular Biosciences 9 (2022): 1074285.

[137] Z. Wang, D. E. Haslam, C. M. Sawicki, et al., “Saliva, Plasma, and Multifluid Metabolomic Signatures of Periodontal Disease, Type 2 Diabetes Progression, and Markers of Glycemia and Dyslipidemia among Puerto Rican Adults with Overweight and Obesity,” Journal of the American Heart Association 13, no. 15 (2024): e033350.

[138] M. Cialie Rosso, F. Stilo, and S. Squara, “Exploring Extra Dimensions to Capture Saliva Metabolite Fingerprints From Metabolically Healthy and Unhealthy Obese Patients by Comprehensive Two-Dimensional Gas Chromatography Featuring Tandem Ionization Mass Spectrometry,” Analytical and Bioanalytical Chemistry 413, no. 2 (2021): 403-418.

[139] J. Troisi, F. Belmonte, A. Bisogno, et al., “Metabolomic Salivary Signature of Pediatric Obesity Related Liver Disease and Metabolic Syndrome,” Nutrients 11, no. 2 (2019): 274.

[140] P. Scheltens, B. De Strooper, M. Kivipelto, et al., “Alzheimer's Disease,” Lancet 397, no. 10284 (2021): 1577-1590.

[141] A. A. Rostagno, “Pathogenesis of Alzheimer's Disease,” International Journal of Molecular Sciences 24, no. 1 (2022): 107.

[142] D. S. Knopman, H. Amieva, R. C. Petersen, et al., “Alzheimer Disease,” Nature Reviews Disease Primers 7, no. 1 (2021): 33.

[143] Z. Breijyeh and R. Karaman, “Comprehensive Review on Alzheimer's Disease: Causes and Treatment,” Molecules (Basel, Switzerland) 25, no. 24 (2020): 5789.

[144] M. François, A. Karpe, J. W. Liu, et al., “Salivaomics as a Potential Tool for Predicting Alzheimer's Disease during the Early Stages of Neurodegeneration,” Journal of Alzheimer's Disease 82, no. 3 (2021): 1301-1313.

[145] T. Huan, T. Tran, J. Zheng, et al., “Metabolomics Analyses of Saliva Detect Novel Biomarkers of Alzheimer's Disease,” Journal of Alzheimer's Disease 65, no. 4 (2018): 1401-1416.

[146] J. Marksteiner, H. Oberacher, and C. Humpel, “Acyl-Alkyl-Phosphatidlycholines Are Decreased in Saliva of Patients With Alzheimer's Disease as Identified by Targeted Metabolomics,” Journal of Alzheimer's Disease 68, no. 2 (2019): 583-589.

[147] Y. Yang, J. Lv, H. Bai, et al., “Periodontal Status and Saliva Metabolic Signature in Patients With Alzheimer's Disease,” Journal of Alzheimer's Disease 95, no. 2 (2023): 603-613.

[148] J. Figueira, P. Jonsson, A. Nordin Adolfsson, R. Adolfsson, L. Nyberg, and A. Öhman, “NMR Analysis of the human Saliva Metabolome Distinguishes Dementia Patients From Matched Controls,” Molecular Biosystems 12, no. 8 (2016): 2562-2571.

[149] W. Poewe, K. Seppi, C. M. Tanner, et al., “Parkinson Disease,” Nature Reviews Disease Primers 3, no. 1 (2017): 17013.

[150] W. Dauer and S. Przedborski, “Parkinson's Disease: Mechanisms and Models,” Neuron 39, no. 6 (2003): 889-909.

[151] L. V. Kalia and A. E. Lang, “Parkinson's Disease,” Lancet 386, no. 9996 (2015): 896-912.

[152] S. Kumari, V. Goyal, S. S. Kumaran, S. N. Dwivedi, A. Srivastava, and N. R. Jagannathan, “Quantitative Metabolomics of Saliva Using Proton NMR Spectroscopy in Patients With Parkinson's Disease and Healthy Controls,” Neurological Sciences 41, no. 5 (2020): 1201-1210.

[153] J. Kim, S. An, and Y. Kim, “Surface Active Salivary Metabolites Indicate Oxidative Stress and Inflammation in Obstructive Sleep Apnea,” Allergy, Asthma & Immunology Research 15, no. 3 (2023): 316-335.

[154] X. Chen, Y. Chen, M. Feng, et al., “Altered Salivary Microbiota in Patients With Obstructive Sleep Apnea Comorbid Hypertension,” Nature and Science of Sleep 14 (2022): 593-607.

[155] S. M. Yu, H. C. Zheng, S. C. Wang, et al., “Salivary Metabolites Are Promising Noninvasive Biomarkers of Drug-Induced Liver Injury,” World Journal of Gastroenterology 30, no. 18 (2024): 2454-2466.

[156] L. Cui, J. Liu, X. Yan, and S. Hu, “Identification of Metabolite Biomarkers for Gout Using Capillary Ion Chromatography With Mass Spectrometry,” Analytical Chemistry 89, no. 21 (2017): 11737-11743.

[157] M. Siani-Rose, R. McKee, S. Cox, et al., “The Potential of Salivary Lipid-Based Cannabis-Responsive Biomarkers to Evaluate Medical Cannabis Treatment in Children With Autism Spectrum Disorder,” Cannabis and Cannabinoid Research 8, no. 4 (2023): 642-656.

[158] M. Caterino, R. Fedele, V. Carnovale, et al., “Lipidomic Alterations in human Saliva From Cystic Fibrosis Patients,” Scientific Reports 13, no. 1 (2023): 600.

[159] F. A. Fineide, B. Tashbayev, K. B. P. Elgstoen, et al., “Tear and Saliva Metabolomics in Evaporative Dry Eye Disease in Females,” Metabolites 13, no. 11 (2023): 1125.

[160] Y. Wu, L. Xing, L. Lu, et al., “Alterations in the Salivary Microbiome and Metabolism in Patients with Carotid Atherosclerosis From Rural Northeast China,” Journal of the American Heart Association 13, no. 15 (2024): e034014.

[161] L. Morgan, R. I. D. Birkler, S. Shaham-Niv, et al., “Saliva Metabolome Alterations After Acute Stress,” Scientific Reports 12, no. 1 (2022): 18470.

[162] M. Wei, G. An, and L. Fan, “Characteristics of Menstrual Cycle Disorder and Saliva Metabolomics of Young Women in a High-Temperature Environment,” Frontiers in Physiology 13 (2022): 994990.

[163] L. Lv, H. Jiang, X. Chen, et al., “The Salivary Microbiota of Patients with Primary Biliary Cholangitis Is Distinctive and Pathogenic,” Frontiers in Immunology 12 (2021): 713647.

[164] E. I. Dyachenko and L. V. Bel'skaya, “Salivary Metabolites in Breast Cancer and Fibroadenomas: Focus on Menopausal Status and BMI,” Metabolites 14, no. 10 (2024): 531.

[165] A. Ciurli, R. J. E. Derks, M. Liebl, C. Ammon, J. Neefjes, and M. Giera, “Spatially Resolved Sampling of the human Oral Cavity for Metabolic Profiling,” STAR Protocols 2, no. 4 (2021): 101002.

[166] A. Ciurli, Y. Mohammed, C. Ammon, et al., “Spatially and Temporally Resolved Metabolome of the human Oral Cavity,” iScience 27, no. 2 (2024): 108884.

[167] L. B. Freitas-Fernandes, G. P. Fontes, A. D. S. Letieri, A. P. Valente, I. P. R. Souza, and T. Fidalgo, “NMR-Based Metabolomics Demonstrates a Metabolic Change During Early Developmental Stages From Healthy Infants to Young Children,” Metabolites 13, no. 3 (2023): 445.

[168] E. Neyraud, C. Schwartz, H. Brignot, et al., “Longitudinal Analysis of the Salivary Metabolome of Breast-Fed and Formula-Fed Infants Over the First Year of Life,” Metabolomics 16, no. 3 (2020): 37.

[169] N. Tamura, K. Mizuno, R. Suzuki, et al., “Effect of Underwater Exercise on Salivary Metabolites of Older Persons with Disability,” In Vivo (Athens, Greece) 36, no. 6 (2022): 2678-2688.

[170] M. Bhogadia, M. Edgar, K. Hunwin, G. Page, and M. Grootveld, “Detection and Quantification of Ammonia as the Ammonium Cation in Human Saliva by (1)H NMR: A Promising Probe for Health Status Monitoring, With Special Reference to Cancer,” Metabolites 13, no. 7 (2023): 792.

[171] P. Bosman, V. Pichon, A. C. Acevedo, H. Chardin, and A. Combes, “Development of Analytical Methods to Study the Salivary Metabolome: Impact of the Sampling,” Analytical and Bioanalytical Chemistry 414, no. 23 (2022): 6899-6909.

[172] L. Fang, Q. Zhai, H. Zhang, P. Ji, C. Chen, and H. Zhang, “Comparisons of Different Extraction Methods and Solvents for Saliva Samples,” Metabolomics 20, no. 2 (2024): 38.

[173] E. Quartieri, E. Casali, E. Ferrari, et al., “Sample Optimization for Saliva (1)H-NMR Metabolic Profiling,” Analytical Biochemistry 640 (2022): 114412.

[174] M. Sugimoto, S. Ota, M. Kaneko, A. Enomoto, and T. Soga, “Quantification of Salivary Charged Metabolites Using Capillary Electrophoresis Time-of-Flight-Mass Spectrometry,” Bio-Protocol 10, no. 20 (2020): e3797.

[175] M. Nam, S. R. Jo, J. H. Park, and M. S. Kim, “Evaluation of Critical Factors in the Preparation of Saliva Sample From Healthy Subjects for Metabolomics,” Journal of Pharmaceutical and Biomedical Analysis 223 (2023): 115145.

[176] H. Mortazavi, A. A. Yousefi-Koma, and H. Yousefi-Koma, “Extensive Comparison of Salivary Collection, Transportation, Preparation, and Storage Methods: A Systematic Review,” BMC Oral Health 24, no. 1 (2024): 168.

[177] M. Scholz, A. E. Steuer, A. Dobay, H. P. Landolt, and T. Kraemer, “Assessing the Influence of Sleep and Sampling Time on Metabolites in Oral Fluid: Implications for Metabolomics Studies,” Metabolomics 20, no. 5 (2024): 97.

[178] Y. Maruyama, N. Fujii, R. Kawamata, et al., “Intra- and Inter-Day Variations in Oral Metabolites From Mouth-Rinsed Water Determined Using Capillary Electrophoresis-Mass Spectrometry Metabolomics,” Clinica Chimica Acta 565 (2025): 119965.

[179] N. Kawanishi, N. Hoshi, S. Masahiro, et al., “Effects of Inter-Day and Intra-Day Variation on Salivary Metabolomic Profiles,” Clinica Chimica Acta 489 (2019): 41-48.

[180] E. Dziurkowska and M. Wesolowski, “Effects of Age, Drug Dose, and Sampling Time on Salivary Levels of Olanzapine, Quetiapine, and Their Metabolites,” Journal of Clinical Medicine 9, no. 10 (2020): 3288.

[181] S. Daniele, G. Scarfò, L. Ceccarelli, et al., “The Mediterranean Diet Positively Affects Resting Metabolic Rate and Salivary Microbiota in Human Subjects: A Comparison With the Vegan Regimen,” Biology (Basel) 10, no. 12 (2021): 1292.

[182] D. Ercolini, R. Francavilla, L. Vannini, et al., “From an Imbalance to a New Imbalance: Italian-Style Gluten-Free Diet Alters the Salivary Microbiota and Metabolome of African Celiac Children,” Scientific Reports 5 (2015): 18571.

[183] M. Morzel, C. Truntzer, E. Neyraud, et al., “Associations Between Food Consumption Patterns and Saliva Composition: Specificities of Eating Difficulties Children,” Physiology & Behavior 173 (2017): 116-123.

[184] S. Sun, H. Zhang, L. Ye, et al., “Combined Analysis of the Microbiome and Metabolome to Reveal the Characteristics of Saliva From Different Diets: A Comparison Among Vegans, Seafood-Based Omnivores, and Red Meat (beef and lamb) Omnivores,” Frontiers in Microbiology 15 (2024): 1419686.

[185] F. De Filippis, L. Vannini, and A. La Storia, “The Same Microbiota and a Potentially Discriminant Metabolome in the Saliva of Omnivore, Ovo-Lacto-Vegetarian and Vegan Individuals,” PLoS ONE 9, no. 11 (2014): e112373.

[186] B. Karaahmet, L. Le, M. S. Mendes, A. K. Majewska, and M. K. O'Banion, “Repopulated Microglia Induce Expression of Cxcl13 With Differential Changes in Tau Phosphorylation but Do Not Impact Amyloid Pathology,” Journal of Neuroinflammation 19, no. 1 (2022): 173.

[187] Y. Saeki, A. Takenouchi, E. Otani, et al., “Long-Term Mastication Changed Salivary Metabolomic Profiles,” Metabolites 12, no. 7 (2022): 660.

[188] C. S. de Araujo, A. C. L. da Silva, L. B. Freitas-Fernandes, L. C. Maia, T. K. da Silva Fidalgo, and A. P. Valente, “Untargeted Stimulated and Unstimulated Salivary Metabolomics and Saliva Flow Rate in Children,” Clinical Oral Investigations 28, no. 9 (2024): 489.

[189] B. Carvalho, N. C. Faria, K. C. S. Silva, et al., “Salivary Metabolic Pathway Alterations in Brazilian E-Cigarette Users,” International Journal of Molecular Sciences 25, no. 21 (2024): 11750.

[190] J. N. McNeill, A. Roshandelpoor, M. Alotaibi, et al., “The Association of Eicosanoids and Eicosanoid-Related Metabolites With Pulmonary Hypertension,” European Respiratory Journal 62, no. 4 (2023): 2300561.

[191] K. Hildreth, S. D. Kodani, B. D. Hammock, and L. Zhao, “Cytochrome P450-Derived Linoleic Acid Metabolites EpOMEs and DiHOMEs: A Review of Recent Studies,” Journal of Nutritional Biochemistry 86 (2020): 108484.

[192] H. Liu, B. Nan, C. Yang, X. Li, H. Yan, and Y. Yuan, “Elaidic Acid Induced NLRP3 Inflammasome Activation via ERS-MAPK Signaling Pathways in Kupffer Cells,” Biochimica et Biophysica Acta: Molecular and Cell Biology Lipids 1867, no. 1 (2022): 159061.

[193] J. Joffre and J. Hellman, “Oxidative Stress and Endothelial Dysfunction in Sepsis and Acute Inflammation,” Antioxidants and Redox Signaling 35, no. 15 (2021): 1291-1307.

[194] I. Takeda, C. Stretch, P. Barnaby, et al., “Understanding the human Salivary Metabolome,” NMR in Biomedicine 22, no. 6 (2009): 577-584.

[195] A. Zhang, H. Sun, and X. Wang, “Saliva Metabolomics Opens Door to Biomarker Discovery, Disease Diagnosis, and Treatment,” Applied Biochemistry and Biotechnology 168, no. 6 (2012): 1718-1727.

[196] S. Squara, F. Manig, T. Henle, et al., “Extending the Breadth of Saliva Metabolome Fingerprinting by Smart Template Strategies and Effective Pattern Realignment on Comprehensive Two-Dimensional Gas Chromatographic Data,” Analytical and Bioanalytical Chemistry 415, no. 13 (2023): 2493-2509.

[197] K. Wijnant, L. Van Meulebroek, B. Pomian, et al., “Validated Ultra-High-Performance Liquid Chromatography Hybrid High-Resolution Mass Spectrometry and Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry for Salivary Metabolomics,” Analytical Chemistry 92, no. 7 (2020): 5116-5124.

[198] I. J. Miller, S. R. Peters, K. A. Overmyer, B. R. Paulson, M. S. Westphall, and J. J. Coon, “Real-Time Health Monitoring Through Urine Metabolomics,” npj Digital Medicine 2 (2019): 109.

[199] J. Wu and Y. Gao, “Physiological Conditions Can be Reflected in human Urine Proteome and Metabolome,” Expert Review of Proteomics 12, no. 6 (2015): 623-636.

[200] K. T. Do, G. Kastenmuller, D. O. Mook-Kanamori, et al., “Network-Based Approach for Analyzing Intra- and Interfluid Metabolite Associations in human Blood, Urine, and Saliva,” Journal of Proteome Research 14, no. 2 (2015): 1183-1194.

[201] E. Hyvarinen, M. Savolainen, J. J. W. Mikkonen, and A. M. Kullaa, “Salivary Metabolomics for Diagnosis and Monitoring Diseases: Challenges and Possibilities,” Metabolites 11, no. 9 (2021): 587.

[202] G. Pinto, M. Gelzo, G. Cernera, et al., “Molecular Fingerprint by Omics-Based Approaches in Saliva From Patients Affected by SARS-CoV-2 Infection,” Journal of Mass Spectrometry 59, no. 9 (2024): e5082.

[203] A.-H. Emwas, H. U. Zacharias, M. R. Alborghetti, et al., “Recommendations for Sample Selection, Collection and Preparation for NMR-Based Metabolomics Studies of Blood,” Metabolomics 21, no. 3 (2025): 66.

[204] M. Sud, E. Fahy, D. Cotter, et al., “Metabolomics Workbench: An International Repository for Metabolomics Data and Metadata, Metabolite Standards, Protocols, Tutorials and Training, and Analysis Tools,” Nucleic Acids Research 44, no. D1 (2016): D463-D470.

RIGHTS & PERMISSIONS

2025 The Author(s). MedComm published by Sichuan International Medical Exchange & Promotion Association (SCIMEA) and John Wiley & Sons Australia, Ltd.