Novel Raman-based reagent-free diagnostics for arthritic diseases

The sensitivity and specificity of current serological biomarkers for arthritic diseases are limited often delaying the diagnosis and treatment.

Project information

Project duration


Project funder

Biocenter Oulu

Project coordinator

University of Oulu

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Project leader

Project description

Description of the scientific and societal objectives of the research: The sensitivity and specificity of current serological biomarkers for arthritic diseases are limited often delaying the diagnosis and treatment. Furthermore, they are unable to predict the disease course and treatment response. In this project, we will develop new Raman-based reagent-free diagnostics for arthritic diseases to tackle global challenges related to timeliness, sensitivity, and predictability of the conventional diagnostics in a sustainable manner.

Research methods: We utilize rapid and low-cost Raman spectroscopy along with advanced machine learning methods and next generation signal enhancement strategies (plasmonic nanopillars) to diagnose sub-types of rheumatoid arthritis (RA), osteoarthritis (OA), and juvenile idiopathic arthritis (JIA) from human biofluids (blood and synovial fluid) in a reagent-free way. Furthermore, the diagnostic performances of the developed methods will be compared in terms of sensitivity, specificity, and predictive value along with the cost-benefit involved per the developed methods.

Research data: We will measure human biofluids from RA, OA, and JIA patients, as well as healthy controls using both conventional and surface-enhanced Raman spectroscopy (SERS) in conjunction with gold standard techniques. In addition, clinical and cost parameters will be used for cost benefit analysis in patients with JIA.

Expected results and impact: This research is expected to provide instant outcomes for identifying and predicting the risk of arthritic diseases and related outcomes. Detected biochemical composition and prognostic factors of arthritic diseases will improve sustainability-related impact by guiding individualized treatment, improving health-related quality of life, decreasing stiffness and pain, and reducing unnecessary costs across the clinical pathway.

Key publications

Jansson MM, Kögler M, Hörkkö S, Ala-Kokko T, Rieppo L. Vibrational spectroscopy and its future applications in microbiology. Applied Spectroscopy Reviews 58:132-58, 2023.

Vesty G, Kokshagina O, Jansson M, Cheong F, Butler-Henderson K. Accounting, valuing and investing in healthcare: dealing with outdated accounting models. Meditari Accountancy Research 1:52–77, 2023.

Das Gupta S, Mäntynen V, Huan J, Saarakkala S, Jansson M. Surface-enhanced Raman spectroscopy for rapid identification of common pathogenic bacteria: a pilot study. Poster & Flash Presentation. The 12th International Conference on Clinical Spectroscopy (SPEC); conference proceeding 19–23.6.2022, Dublin, Ireland.

Heino H, Rieppo L, Männistö T, Sillanpää MJ, Mäntynen V, Saarakkala S. Diagnostic performance of attenuated total reflection Fourier-transform infrared spectroscopy for detecting COVID-19 from routine nasopharyngeal swab samples. Scientific Reports 12:20358, 2022.

Tiulpin A, Saarakkala S, Mathiessen A, Hammer HB, Furnes O, Nordsletten L, Englund M, Magnusson K. Predicting total knee arthroplasty from ultrasonography using machine learning. Osteoarthritis and Cartilage Open 4:100319, 2022.

Das Gupta S, Finnilä MAJ, Karhula SS, Kauppinen S, Joukainen A, Kröger H, Korhonen RK, Thambyah A, Rieppo L, Saarakkala S. Raman microspectroscopic analysis of the tissue-specific composition of the human osteochondral junction in osteoarthritis: A pilot study. Acta Biomaterialia 106:145-155, 2020.

Jansson MM, Harjumaa M, Puhto A-P, Pikkarainen M. Patients’ satisfaction and experiences during elective primary fast-track total hip and knee arthroplasty journey: A qualitative study. Journal of Clinical Nursing 29:567–82, 2020.

Tiulpin A, Klein S, Bierma-Zeinstra SMA, Thevenot J, Rahtu E, Meurs JV, Oei EHG, Saarakkala S. Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data. Scientific Reports 9:20038, 2019.

Jansson MM, Harjumaa M, Puhto A-P, Pikkarainen M. Healthcare professionals’ perceived problems in fast-track hip and knee arthroplasty: results of a qualitative interview study. Journal of Orthopaedic Surgery and Research 14:294, 2019.

Huang JA, Mousavi MZ, Zhao Y, Hubarevich A, Omeis F, Giovannini G, Schütte M, Garoli D, De Angelis F. SERS discrimination of single DNA bases in single oligonucleotides by electro-plasmonic trapping. Nature Communications 10:5321, 2019