Pathological pain subtypes can be classified as either neuropathic pain, caused by a somatosensory nervous system lesion or disease, or nociplastic pain, which develops without evidence of somatosensory system damage. Since there is no gold standard for the diagnosis of pathological pain subtypes, the proper classification of individual patients is currently an unmet challenge for clinicians. While the determination of specific biomarkers for each condition by current biochemical techniques is a complex task, the use of multimolecular techniques, such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), combined with artificial intelligence allows specific fingerprints for pathological pain-subtypes to be obtained, which may be useful for diagnosis. We analyzed whether the information provided by the mass spectra of serum samples of four experimental models of neuropathic and nociplastic pain combined with their functional pain outcomes could enable pathological pain subtype classification by artificial neural networks. As a result, a simple and innovative clinical decision support method has been developed that combines MALDI-TOF MS serum spectra and pain evaluation with its subsequent data analysis by artificial neural networks and allows the identification and classification of pathological pain subtypes in experimental models with a high level of specificity.

Department of Chemistry Analytical Chemistry Division Faculty of Sciences University of La Laguna 38204 San Cristóbal de La Laguna Tenerife Spain

Department of Chemistry Faculty of Science Masaryk University Kamenice 5 A14 625 00 Brno Czech Republic

Department of Chemistry Faculty of Science University of Girona 17071 Girona Catalonia Spain

Department of Histology and Embryology Faculty of Medicine Masaryk University 62500 Brno Czech Republic

International Clinical Research Center St Anne's University Hospital 656 91 Brno Czech Republic

Research Centre for Applied Molecular Oncology Masaryk Memorial Cancer Institute 62500 Brno Czech Republic

Research Group of Clinical Anatomy Embryology and Neuroscience Department of Medical Sciences University of Girona Girona Catalonia 17003 Spain

See more in PubMed

Debono D. J.; Hoeksema L. J.; Hobbs R. D. Caring for patients with chronic pain: pearls and pitfalls. J. Am. Osteopath. Assoc. 2013, 113, 620–627. 10.7556/jaoa.2013.023. PubMed DOI

Mäntyselkä P.; Kumpusalo E.; Ahonen R.; Kumpusalo A.; Kauhanen J.; Viinamäki H.; Halonen P.; Takala J. Pain as a reason to visit the doctor: a study in Finnish primary health care. Pain 2001, 89, 175–180. 10.1016/s0304-3959(00)00361-4. PubMed DOI

Goldberg D. S.; McGee S. J. Pain as a global public health priority. BMC Public Health 2011, 11, 770.10.1186/1471-2458-11-770. PubMed DOI PMC

Dorner T. E. Pain and chronic pain epidemiology: Implications for clinical and public health fields. Wien. Klin. Wochenschr. 2018, 130, 1–3. 10.1007/s00508-017-1301-0. PubMed DOI

Treede R. D.; Rief W.; Barke A.; Aziz Q.; Bennett M. I.; Benoliel R.; Cohen M.; Evers S.; Finnerup N. B.; First M. B.; et al. Chronic pain as a symptom or a disease: the IASP Classification of Chronic Pain for the International Classification of Diseases (ICD-11). Pain 2019, 160, 19–27. 10.1097/j.pain.0000000000001384. PubMed DOI

Grace P. M.; Hutchinson M. R.; Maier S. F.; Watkins L. R. Pathological pain and the neuroimmune interface. Nat. Rev. Immunol. 2014, 14, 217–231. 10.1038/nri3621. PubMed DOI PMC

Arnold L. M.; Bennett R. M.; Crofford L. J.; Dean L. E.; Clauw D. J.; Goldenberg D. L.; Fitzcharles M. A.; Paiva E. S.; Staud R.; Sarzi-Puttini P.; et al. AAPT Diagnostic Criteria for Fibromyalgia. J. Pain 2019, 20, 611–628. 10.1016/j.jpain.2018.10.008. PubMed DOI

Gilron I.; Baron R.; Jensen T. Neuropathic pain: principles of diagnosis and treatment. Mayo Clin. Proc. 2015, 90, 532–545. 10.1016/j.mayocp.2015.01.018. PubMed DOI

Walker J. Fibromyalgia: clinical features, diagnosis and management. Nurs. Stand. 2016, 31, 51–63. 10.7748/ns.2016.e10550. PubMed DOI

Häuser W.; Ablin J.; Fitzcharles M. A.; Littlejohn G.; Luciano J. V.; Usui C.; Walitt B. Fibromyalgia. Nat. Rev. Dis. Primers 2015, 1, 15022.10.1038/nrdp.2015.22. PubMed DOI

Jensen T. S.; Finnerup N. B. Allodynia and hyperalgesia in neuropathic pain: clinical manifestations and mechanisms. Lancet Neurol. 2014, 13, 924–935. 10.1016/S1474-4422(14)70102-4. PubMed DOI

Cohen S. P.; Mao J. Neuropathic pain: mechanisms and their clinical implications. BMJ 2014, 348, f7656.10.1136/bmj.f7656. PubMed DOI

Sluka K. A.; Clauw D. J. Neurobiology of fibromyalgia and chronic widespread pain. Neuroscience 2016, 338, 114–129. 10.1016/j.neuroscience.2016.06.006. PubMed DOI PMC

Ghavidel-Parsa B.; Bidari A.; Amir Maafi A.; Ghalebaghi B. The Iceberg Nature of Fibromyalgia Burden: The Clinical and Economic Aspects. Korean J. Pain 2015, 28, 169–176. 10.3344/kjp.2015.28.3.169. PubMed DOI PMC

Koroschetz J.; Rehm S. E.; Gockel U.; Brosz M.; Freynhagen R.; Tölle T. R.; Baron R. Fibromyalgia and neuropathic pain--differences and similarities. A comparison of 3057 patients with diabetic painful neuropathy and fibromyalgia. BMC Neurol. 2011, 11, 55.10.1186/1471-2377-11-55. PubMed DOI PMC

Velly A. M.; Mohit S. Epidemiology of pain and relation to psychiatric disorders. Prog. Neuropsychopharmacol. Biol. Psychiatry 2018, 87, 159–167. 10.1016/j.pnpbp.2017.05.012. PubMed DOI

Morlion B.; Coluzzi F.; Aldington D.; Kocot-Kepska M.; Pergolizzi J.; Mangas A. C.; Ahlbeck K.; Kalso E. Pain chronification: what should a non-pain medicine specialist know?. Curr. Med. Res. Opin. 2018, 34, 1169–1178. 10.1080/03007995.2018.1449738. PubMed DOI

Chae Y.; Park H. J.; Lee I. S. Pain modalities in the body and brain: Current knowledge and future perspectives. Neurosci. Biobehav. Rev. 2022, 139, 10474410.1016/j.neubiorev.2022.104744. PubMed DOI

Smith S. M.; Dworkin R. H.; Turk D. C.; Baron R.; Polydefkis M.; Tracey I.; Borsook D.; Edwards R. R.; Harris R. E.; Wager T. D.; et al. The Potential Role of Sensory Testing, Skin Biopsy, and Functional Brain Imaging as Biomarkers in Chronic Pain Clinical Trials: IMMPACT Considerations. J. Pain 2017, 18, 757–777. 10.1016/j.jpain.2017.02.429. PubMed DOI PMC

Liu Y.; Hüttenhain R.; Collins B.; Aebersold R. Mass spectrometric protein maps for biomarker discovery and clinical research. Expert Rev. Mol. Diagn. 2013, 13, 811–825. 10.1586/14737159.2013.845089. PubMed DOI PMC

Cross T. G.; Hornshaw M. P. Can LC and LC-MS ever replace immunoassays?. J. Appl. Bioanal. 2016, 2, 108–116. 10.17145/jab.16.015. DOI

Hoofnagle A. N.; Wener M. H. The fundamental flaws of immunoassays and potential solutions using tandem mass spectrometry. J. Immunol. Methods 2009, 347, 3–11. 10.1016/j.jim.2009.06.003. PubMed DOI PMC

Scherl A. Clinical protein mass spectrometry. Methods 2015, 81, 3–14. 10.1016/j.ymeth.2015.02.015. PubMed DOI

Bäckryd E.; Ghafouri B.; Carlsson A. K.; Olausson P.; Gerdle B. Multivariate proteomic analysis of the cerebrospinal fluid of patients with peripheral neuropathic pain and healthy controls - a hypothesis-generating pilot study. J. Pain Res. 2015, 8, 321–333. 10.2147/JPR.S82970. PubMed DOI PMC

Sisignano M.; Lötsch J.; Parnham M. J.; Geisslinger G. Potential biomarkers for persistent and neuropathic pain therapy. Pharmacol. Ther. 2019, 199, 16–29. 10.2147/JPR.S82970. PubMed DOI

Zhang G.; Annan R. S.; Carr S. A.; Neubert T. A.. Overview of peptide and protein analysis by mass spectrometry. Curr. Protoc. Protein Sci. 2010, Chapter 16:Unit16.1, 10.1002/0471140864.ps1601s62. PubMed DOI

Prabhu G. R. D.; Elpa D. P.; Chiu H. Y.; Urban P. L.. Clinical Analysis by Mass Spectrometry. In Encyclopedia of Analytical Science, Townshend; Worsfold P., Poole C., Eds.; M. Miró (Academic Press), 2018; pp 318–333.

Pusch W.; Kostrzewa M. Application of MALDI-TOF mass spectrometry in screening and diagnostic research. Curr. Pharm. Des. 2005, 11, 2577–2591. 10.2174/1381612054546932. PubMed DOI

Cho Y. T.; Su H.; Wu W. J.; Wu D. C.; Hou M. F.; Kuo C. H.; Shiea J. Biomarker Characterization by MALDI-TOF/MS. Adv. Clin. Chem. 2015, 69, 209–254. 10.1016/bs.acc.2015.01.001. PubMed DOI

Duncan M. W.; Nedelkov D.; Walsh R.; Hattan S. J. Applications of MALDI Mass Spectrometry in Clinical Chemistry. Clin. Chem. 2016, 62, 134–143. 10.1373/clinchem.2015.239491. PubMed DOI

Li R.; Zhou Y.; Liu C.; Pei C.; Shu W.; Zhang C.; Liu L.; Zhou L.; Wan J. Design of Multi-Shelled Hollow Cr2O3 Spheres for Metabolic Fingerprinting. Angew. Chem., Int. Ed. 2021, 60, 12504–12512. 10.1002/anie.202101007. PubMed DOI

Sun S.; Liu W.; Yang J.; Wang H.; Qian K. Nanoparticle-Assisted Cation Adduction and Fragmentation of Small Metabolites. Angew. Chem., Int. Ed. 2021, 60, 11310–11317. 10.1002/anie.202100734. PubMed DOI

Su H.; Li X.; Huang L.; Cao J.; Zhang M.; Vedarethinam V.; Di W.; Hu Z.; Qian K. Plasmonic Alloys Reveal a Distinct Metabolic Phenotype of Early Gastric Cancer. Adv. Mater. 2021, 33, e200797810.1002/adma.202007978. PubMed DOI

Zhang M.; Huang L.; Yang J.; Xu W.; Su H.; Cao J.; Wang Q.; Pu J.; Qian K. Ultra-Fast Label-Free Serum Metabolic Diagnosis of Coronary Heart Disease via a Deep Stabilizer. Adv. Sci. 2021, 8, e210133310.1002/advs.202101333. PubMed DOI PMC

Amato F.; López A.; Peña-Méndez E. M.; Vaňhara P.; Hampl A.; Havel J. Artificial neural networks in medical diagnosis. J. Appl. Biomed. 2013, 11, 47–58. 10.2478/v10136-012-0031-x. DOI

Houska J.; Peña-Méndez E. M.; Hernandez-Fernaud J. R.; Salido E.; Hampl A.; Havel J.; Vaňhara P. Tissue profiling by nanogold-mediated mass spectrometry and artificial neural networks in the mouse model of human primary hyperoxaluria 1. J. Appl. Biomed. 2014, 12, 119–125. 10.1016/j.jab.2013.12.001. DOI

Agatonovic-Kustrin S.; Beresford R. Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research. J. Pharm. Biomed. Anal. 2000, 22, 717–727. 10.1016/s0731-7085(99)00272-1. PubMed DOI

Basheer I. A.; Hajmeer M. Artificial neural networks: fundamentals, computing, design, and application. J. Microbiol. Methods 2000, 43, 3–31. 10.1016/s0167-7012(00)00201-3. PubMed DOI

Deulofeu M.; Kolářová L.; Salvadó V.; María Peña-Méndez E.; Almáši M.; Štork M.; Pour L.; Boadas-Vaello P.; Ševčíková S.; Havel J.; Vaňhara P. Rapid discrimination of multiple myeloma patients by artificial neural networks coupled with mass spectrometry of peripheral blood plasma. Sci. Rep. 2019, 9, 7975.10.1038/s41598-019-44215-1. PubMed DOI PMC

Deulofeu M.; García-Cuesta E.; Peña-Méndez E. M.; Conde J. E.; Jiménez-Romero O.; Verdú E.; Serrando M. T.; Salvadó V.; Boadas-Vaello P. Detection of SARS-CoV-2 Infection in Human Nasopharyngeal Samples by Combining MALDI-TOF MS and Artificial Intelligence. Front. Med. 2021, 8, 66135810.3389/fmed.2021.661358. PubMed DOI PMC

Zhang Y. G.; Jiang R. Q.; Guo T. M.; Wu S. X.; Ma W. J. MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain. BMC Musculoskelet. Disord. 2014, 15, 193.10.1186/1471-2474-15-193. PubMed DOI PMC

Sui P.; Watanabe H.; Artemenko K.; Sun W.; Bakalkin G.; Andersson M.; Bergquist J. Neuropeptide imaging in rat spinal cord with MALDI-TOF MS: Method development for the application in pain-related disease studies. Eur. J. Mass Spectrom. 2017, 23, 105–115. 10.1177/1469066717703272. PubMed DOI

Wåhlén K.; Ghafouri B.; Ghafouri N.; Gerdle B. Plasma Protein Pattern Correlates With Pain Intensity and Psychological Distress in Women With Chronic Widespread Pain. Front. Psychol. 2018, 9, 2400.10.3389/fpsyg.2018.02400. PubMed DOI PMC

Farajzadeh A.; Bathaie S. Z.; Arabkheradmand J.; Ghodsi S. M.; Faghihzadeh S. Different Pain States of Trigeminal Neuralgia Make Significant Changes in the Plasma Proteome and Some Biochemical Parameters: a Preliminary Cohort Study. J. Mol. Neurosci. 2018, 66, 524–534. 10.1007/s12031-018-1183-2. PubMed DOI

McCartney S.; Weltin M.; Burchiel K. J. Use of an artificial neural network for diagnosis of facial pain syndromes: an update. Stereotact. Funct. Neurosurg. 2014, 92, 44–52. 10.1159/000353188. PubMed DOI

Darvishi E.; Khotanlou H.; Khoubi J.; Giahi O.; Mahdavi N. Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers. J. Manipulative Physiol. Ther. 2017, 40, 486–493. 10.1016/j.jmpt.2017.03.012. PubMed DOI

Gudelis M.; Lacasta Garcia J. D.; Trujillano Cabello J. J. Diagnosis of pain in the right iliac fossa. A new diagnostic score based on Decision-Tree and Artificial Neural Network Methods. Cir. Esp. 2019, 97, 329–335. 10.1016/j.ciresp.2019.02.006. PubMed DOI

Gao X.; Xin X.; Li Z.; Zhang W. Predicting postoperative pain following root canal treatment by using artificial neural network evaluation. Sci. Rep. 2021, 11, 17243.10.1038/s41598-021-96777-8. PubMed DOI PMC

Kreiner M.; Viloria J. A novel artificial neural network for the diagnosis of orofacial pain and temporomandibular disorders. J. Oral Rehabil. 2022, 49, 884–889. 10.1111/joor.13350. PubMed DOI

Hao W.; Cong C.; Yuanfeng D.; Ding W.; Li J.; Yongfeng S.; Shijun W.; Wenhua Y. Multidata Analysis Based on an Artificial Neural Network Model for Long-Term Pain Outcome and Key Predictors of Microvascular Decompression in Trigeminal Neuralgia. World Neurosurg. 2022, 164, e271–e279. 10.1016/j.wneu.2022.04.089. PubMed DOI

Bosch-Mola M.; Homs J.; Álvarez-Pérez B.; Puig T.; Reina F.; Verdú E.; Boadas-Vaello P. (−)-Epigallocatechin-3-Gallate Antihyperalgesic Effect Associates With Reduced CX3CL1 Chemokine Expression in Spinal Cord. Phytother. Res. 2017, 31, 340–344. 10.1002/ptr.5753. PubMed DOI

Castany S.; Gris G.; Vela J. M.; Verdú E.; Boadas-Vaello P. Critical role of sigma-1 receptors in central neuropathic pain-related behaviours after mild spinal cord injury in mice. Sci. Rep. 2018, 8, 3873.10.1038/s41598-018-22217-9. PubMed DOI PMC

Bagó-Mas A.; Korimová A.; Deulofeu M.; Verdú E.; Fiol N.; Svobodová V.; Dubový P.; Boadas-Vaello P. Polyphenolic grape stalk and coffee extracts attenuate spinal cord injury-induced neuropathic pain development in ICR-CD1 female mice. Sci. Rep. 2022, 12, 14980.10.1038/s41598-022-19109-4. PubMed DOI PMC

Álvarez-Pérez B.; Deulofeu M.; Homs J.; Merlos M.; Vela J. M.; Verdú E.; Boadas-Vaello P. Long-lasting reflexive and nonreflexive pain responses in two mouse models of fibromyalgia-like condition. Sci. Rep. 2022, 12, 9719.10.1038/s41598-022-13968-7. PubMed DOI PMC

Morton D. B.; Griffiths P. H. Guidelines on the recognition of pain, distress and discomfort in experimental animals and an hypothesis for assessment. Vet. Rec. 1985, 116, 431–436. 10.1038/s41598-022-13968-7. PubMed DOI

Castany S.; Codony X.; Zamanillo D.; Merlos M.; Verdú E.; Boadas-Vaello P. Repeated Sigma-1 Receptor Antagonist MR309 Administration Modulates Central Neuropathic Pain Development After Spinal Cord Injury in Mice. Front. Pharmacol. 2019, 10, 222.10.3389/fphar.2019.00222. PubMed DOI PMC

Boccard J.; Rudaz S.. Mass Spectrometry Metabolomic Data Handling for Biomarker Discovery. In Proteomic and Metabolomic Approaches to Biomarker Discovery; Isaaq H., Veenstra T. D., Eds.; Academic Press, 2013; pp 425–445.

Kim S. J.; Kim S. H.; Kim J. H.; Hwang S.; Yoo H. J. Understanding Metabolomics in Biomedical Research. Endocrinol. Metab. 2016, 31, 7–16. 10.3803/EnM.2016.31.1.7. PubMed DOI PMC

Wagner R.; Heckman H. M.; Myers R. R. Wallerian degeneration and hyperalgesia after peripheral nerve injury are glutathione-dependent. Pain 1998, 77, 173–179. 10.1016/S0304-3959(98)00091-8. PubMed DOI

Kaur G.; Bedi O.; Sharma N.; Singh S.; Deshmukh R.; Kumar P. Anti-hyperalgesic and anti-nociceptive potentials of standardized grape seed proanthocyanidin extract against CCI-induced neuropathic pain in rats. J. Basic Clin. Physiol. Pharmacol. 2016, 27, 9–17. 10.1515/jbcpp-2015-0026. PubMed DOI

Wang Z.; Zhao W.; Shen X.; Wan H.; Yu J. M. The role of P2Y6 receptors in the maintenance of neuropathic pain and its improvement of oxidative stress in rats. J. Cell. Biochem. 2019, 120, 17123–17130. 10.1002/jcb.28972. PubMed DOI

Miyamoto K.; Ishikura K. I.; Kume K.; Ohsawa M. Astrocyte-neuron lactate shuttle sensitizes nociceptive transmission in the spinal cord. Glia 2019, 67, 27–36. 10.1002/glia.23474. PubMed DOI

Latremoliere A.; Costigan M. GCH1, BH4 and pain. Curr. Pharm. Biotechnol. 2011, 12, 1728–1741. 10.2174/138920111798357393. PubMed DOI PMC

Latremoliere A.; Latini A.; Andrews N.; Cronin S. J.; Fujita M.; Gorska K.; Hovius R.; Romero C.; Chuaiphichai S.; Painter M.; et al. Reduction of Neuropathic and Inflammatory Pain through Inhibition of the Tetrahydrobiopterin Pathway. Neuron 2015, 86, 1393–1406. 10.1016/j.neuron.2015.05.033. PubMed DOI PMC

Monakhova Y. B.; Goryacheva I. Y. Chemometric analysis of luminescent quantum dots systems: Long way to go but first steps taken. Trends Anal. Chem. 2016, 82, 164–174. 10.1016/j.trac.2016.05.017. DOI

Vaňhara P.; Moráň L.; Pečinka L.; Porokh V.; Pivetta T.; Masuri S.; Peña-Méndez E. M.; Conde-González J. E.; Hampl A.; Havel J.. Intact Cell Mass Spectrometry for Embryonic Stem Cell Biotyping. In Mitulović G., Eds.; Mass Spectrometry in Life Sciences and Clinical Laboratory; IntechOpen: London, 2021.

Grayston R.; Czanner G.; Elhadd K.; Goebel A.; Frank B.; Üçeyler N.; Malik R. A.; Alam U. A systematic review and meta-analysis of the prevalence of small fiber pathology in fibromyalgia: Implications for a new paradigm in fibromyalgia etiopathogenesis. Semin. Arthritis Rheum. 2019, 48, 933–940. 10.1016/j.semarthrit.2018.08.003. PubMed DOI

Sládková K.; Houska J.; Havel J. Laser desorption ionization of red phosphorus clusters and their use for mass calibration in time-of-flight mass spectrometry. Rapid Commun. Mass Spectrom. 2009, 23, 3114–3118. 10.1002/rcm.4230. PubMed DOI

Zimmermann M. Ethical guidelines for investigations of experimental pain in conscious animals. Pain 1983, 16, 109–110. 10.1016/0304-3959(83)90201-4. PubMed DOI

Bennett G. J.; Xie Y. K. A peripheral mononeuropathy in rat that produces disorders of pain sensation like those seen in man. Pain 1988, 33, 87–107. 10.1016/0304-3959(88)90209-6. PubMed DOI

Hargreaves K.; Dubner R.; Brown F.; Flores C.; Joris J. A new and sensitive method for measuring thermal nociception in cutaneous hyperalgesia. Pain 1988, 32, 77–88. 10.1016/0304-3959(88)90026-7. PubMed DOI

Chaplan S. R.; Bach F. W.; Pogrel J. W.; Chung J. M.; Yaksh T. L. Quantitative assessment of tactile allodynia in the rat paw. J. Neurosci. Methods 1994, 53, 55–63. 10.1016/0165-0270(94)90144-9. PubMed DOI

Norris J. L.; Cornett D. S.; Mobley J. A.; Andersson M.; Seeley E. H.; Chaurand P.; Caprioli R. M. Processing MALDI Mass Spectra to Improve Mass Spectral Direct Tissue Analysis. Int. J. Mass Spectrom. 2007, 260, 212–221. 10.1016/j.ijms.2006.10.005. PubMed DOI PMC