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NCT Number: NCT07769619

Integrative AI-Based Multiomic and Neurophysiological Profiling of Chronic Pain in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease in which pain remains the most prominent and burdensome symptom from the patient's perspective. Although the introduction of biological and targeted synthetic disease-modifying antirheumatic drugs (bDMARDs and tsDMARDs) has significantly improved the control of inflammatory activity, an estimated 20-30% of patients continues to experience persistent moderate-to-severe pain despite achieving clinical remission. This discordance between objective inflammatory markers and subjective pain perception reflects an important unmet clinical need and suggests that chronic pain in RA may become partially or fully independent of peripheral inflammation, driven instead by central sensitization and nociplastic mechanisms. The RA-PAIN-AI study is a prospective, observational, case-control study integrating clinical assessment, patient-reported outcome measures, neurophysiological evaluation, and multiomic profiling, analyzed using artificial intelligence (AI)-based methods. Two groups of adult patients with RA are enrolled: a study group of patients with active disease qualifying for biological therapy under the Polish national drug program B.33, and a control group of patients in sustained clinical remission (at least 1.5 years) under biological therapy, without clinically significant chronic pain. All participants undergo clinical assessment, standardized questionnaires, peripheral blood collection at the baseline (Visit 1) and follow-up (Visit 2) visits. Electroencephalography (EEG) is offered as an optional procedure, at the discretion of the investigator. Biological samples are analyzed using advanced multiomic technologies, including whole genome sequencing (genomics), mRNA expression profiling (transcriptomics), and measurement of circulating proteins (secretomics). All clinical, biological, and neurophysiological data are then integrated using AI methods, including dimensionality reduction, clustering, and supervised machine learning, to identify distinct pain-related patient subtypes (endotypes). The primary objective of the study is to identify and characterize clinical, neurophysiological, and multiomic signatures associated with chronic pain in RA. Expected outcomes include identification of biomarkers predictive of chronic pain persistence despite effective anti-inflammatory treatment, improved differentiation between inflammation-driven pain and pain mediated by central nervous system changes, and support for the development of more personalized, mechanism-based treatment strategies in rheumatology. The study is non-interventional: no experimental therapeutic interventions are administered, and all participants continue to receive standard clinical care. All biological analyses are performed ex vivo.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

4th Military Clinical Hospital with Polyclinic (4WSzKzP SPZOZ)

Wroclaw, 50-981, Poland

Location status: Recruiting

Location contact

Mariusz Kiszka, Płk lek.

PRINCIPAL_INVESTIGATOR

Wojciech Tanski, gen. bryg. dr hab. n. med.

CONTACT

[email protected]

0048261 660 204

About this study

Background and rationale. Chronic pain in rheumatoid arthritis (RA) represents a complex, multidimensional clinical phenomenon extending beyond the traditional paradigm of inflammation-driven nociception. Despite significant therapeutic advances enabling effective control of peripheral inflammation with biological and targeted synthetic disease-modifying antirheumatic drugs (bDMARDs and tsDMARDs), an estimated 20-30% of patients continues to experience persistent moderate-to-severe pain, even after achieving clinical remission. This therapeutic gap highlights the evolution of pain mechanisms from peripheral nociception toward central sensitization and nociplastic pain. Evidence from quantitative sensory testing (QST) studies demonstrates widespread pressure pain threshold reduction at sites remote from inflamed joints, indicating generalized central sensitization. Conditioned pain modulation (CPM) protocols reveal impaired descending inhibitory pathways. Functional magnetic resonance imaging (fMRI) studies show pathological hyperconnectivity between the default mode network and the insula, correlating with pain centralization independently of inflammatory markers. At the molecular level, transcriptomic analyses of human dorsal root ganglia have revealed pathological remodeling of primary sensory neurons, including ectopic immunoglobulin signaling and neurogenesis. Metabolomic and lipidomic profiling demonstrates hypoxia-driven glycolytic reprogramming, lactate accumulation acting as an independent algogen through acid-sensing ion channels, and glycerophospholipid metabolism disruption impairing production of specialized pro-resolving mediators. Integrative multi-omic studies have further identified distinct immunometabolic signatures between ACPA-positive and ACPA-negative RA, suggesting serotype-dependent pain mechanisms.

Study design. The RA-PAIN-AI study is designed as a prospective, observational, case-control study integrating clinical, laboratory, neurophysiological, and multiomic data. Two main groups are enrolled: a study group of patients with confirmed RA in an active phase of the disease, qualified for biological therapy according to the Polish national drug program B.33, and a control group of patients with RA in long-term remission (≥1.5 years) under biological therapy, without clinically significant chronic pain.

Non-interventional nature. The study is non-interventional. No experimental therapeutic interventions are administered as part of this study, and all biological analyses are performed ex vivo. All participants continue to receive standard clinical care according to routine rheumatology practice; study procedures are aligned with routine clinical visits whenever possible. Participation is associated with minimal risk. The primary procedures involving participants include venous blood collection, questionnaire assessments, and, optionally (at the discretion of the investigator), electroencephalography (EEG). The risks associated with these procedures are comparable to those encountered in routine clinical practice.

Study procedures - Visit 1 (Baseline, Day 0). All participants undergo: verification of eligibility criteria; collection of informed consent; clinical assessment and medical history; completion of standardized questionnaires (EQ-5D-5L, PHQ-9, VAS, DN4, painDETECT, HAQ, SF-36, FAS, ISI, HADS, GAD-7, CSQ, RS-25); peripheral blood collection (approximately 30 mL total). EEG assessment is performed in selected participants, at the discretion of the investigator.

Study procedures - Visit 2 (Follow-up, 3-6 months after baseline). Participants undergo repeat peripheral blood collection (approximately 10 mL), completion of standardized questionnaires (EQ-5D-5L, PHQ-9, VAS, DN4, painDETECT, HAQ, SF-36, FAS, ISI, HADS, GAD-7, CSQ, RS-25) and, in participants who underwent EEG at Visit 1, repeat EEG assessment, at the discretion of the investigator.

Key assessment tools. The study integrates three complementary assessment domains: (i) patient-reported outcome measures (PROMs) covering pain intensity and character (VAS, DN4, painDETECT), functional status (HAQ), health-related quality of life (EQ-5D-5L, SF-36), psychological status (PHQ-9, HADS, GAD-7, CSQ, RS-25), and sleep quality (ISI), and fatigue (FAS); (ii)optional neurophysiological assessment by EEG (in selected participants, at the discretion of the investigator); and (iii) biological samples (peripheral blood) analyzed for multiomic and laboratory profiles, including whole genome sequencing (genomics), mRNA expression profiling (transcriptomics), and circulating protein measurement (secretomics).

Study setting. The study is conducted at the 4th Military Clinical Hospital with Polyclinic (4WSzKzP SPZOZ) in Wrocław, Poland, a tertiary referral center. Laboratory and multiomic analyses are conducted in collaboration with the Institute of Immunology and Experimental Therapy, Polish Academy of Sciences (IITD PAN; responsible for genomic and transcriptomic analyses) and the Biobank and Research Group at Łukasiewicz - PORT Polish Center for Technology Development (blood processing for genomic analysis and long-term biobanking). All procedures are conducted in accordance with Good Clinical Practice (GCP) guidelines and applicable national regulations.

Analysis framework. All clinical, biological, and neurophysiological data will be analyzed using both conventional statistical methods and artificial intelligence (AI)-based approaches. Statistical analyses will include descriptive statistics, between-group comparisons, correlation analyses, and multivariable analyses, as appropriate. In addition, AI methods, including dimensionality reduction, clustering, and supervised machine learning, will be used to identify distinct pain-related endotypes, develop predictive models for chronic pain persistence and treatment response, and support the transition from inflammation-centered management toward mechanism-based, personalized pain treatment in RA. The study also aims to create a structured, high-quality dataset and biobank resource to support future research in precision medicine and chronic pain in RA.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

- Study Group (Active RA)

  • Age ≥18 years.
  • Confirmed diagnosis of rheumatoid arthritis according to applicable classification criteria.
  • Active phase of the disease requiring initiation of biological therapy.
  • Qualification for treatment under the national drug program B.33: "Treatment of rheumatoid arthritis and juvenile idiopathic arthritis with aggressive course (ICD-10: M05, M06, M08)".
  • Ability to provide written informed consent.
  • Willingness to participate in clinical assessments, EEG, biological sample collection, and questionnaire-based evaluation.

Exclusion criteria

- Study Group

  • Contraindications to biological therapy as defined by the Polish Society of Rheumatology recommendations and the National Health Fund (NFZ) requirements under the B.33 drug program.
  • Inability to provide informed consent.
  • Any condition that, in the opinion of the investigator, may interfere with study participation or data interpretation.

Inclusion criteria

- Control Group (RA in Remission)

  • Age ≥18 years
  • Confirmed diagnosis of rheumatoid arthritis.
  • Ongoing biological therapy with sustained remission for at least 1.5 years and good tolerance of the treatment.
  • No current chronic pain reported in the clinical interview.
  • Ability to provide written informed consent.
  • Willingness to participate in study procedures, including biological sampling, EEG and questionnaire assessments.

Treatment and study plan

Primary outcomes

  1. Multiomic Profiles Associated With Chronic Pain in Rheumatoid Arthritis

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Genomic, transcriptomic, and secretomic profiles associated with chronic pain in rheumatoid arthritis.

  2. Integrated Differentiation Between Study Groups

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Integrated clinical, biological, and neurophysiological features differentiating participants with active rheumatoid arthritis and chronic pain from participants with rheumatoid arthritis in sustained remission without clinically significant chronic pain.

  3. AI-Based Classification of Pain-Related Endotypes

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Development of integrative artificial intelligence-based models for classification of pain-related endotypes using clinical, multiomic, and neurophysiological data.

Secondary outcomes

  1. Pain Intensity Assessed Using the Visual Analogue Scale.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Self-reported pain intensity will be assessed using the Visual Analogue Scale. Scores range from 0 to 100 mm, where 0 mm indicates no pain and 100 mm indicates the worst imaginable pain. Higher scores indicate greater pain intensity.

  2. Functional Status Assessed Using the Health Assessment Questionnaire.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Functional status will be assessed using the Health Assessment Questionnaire. Scores range from 0 to 3, where 0 indicates no disability and 3 indicates severe disability. Higher scores indicate worse functional status.

  3. Health-Related Quality of Life Assessed Using the EuroQol 5 Dimensions 5 Levels Index Value.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Health-related quality of life will be assessed using the EuroQol 5 Dimensions 5 Levels instrument. The EQ-5D-5L index value will be calculated according to the applicable value set. Index values generally range from values below 0 to 1, where 1 indicates full health, 0 indicates a health state equivalent to death, and values below 0 indicate health states valued as worse than death. Higher scores indicate better health-related quality of life.

  4. Health-Related Quality of Life Assessed Using the Short Form Health Survey.

    Time frame: Time Frame: Baseline, Day 0, and Visit 2, 3-6 months after baseline.

    Health-related quality of life will be assessed using the Short Form Health Survey. Domain scores are transformed to a 0 to 100 scale. Higher scores indicate better health status / better health-related quality of life.

  5. Depressive Symptoms Assessed Using the Patient Health Questionnaire-9.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Depressive symptoms will be assessed using the Patient Health Questionnaire-9. Total scores range from 0 to 27. Higher scores indicate greater depressive symptom severity.

  6. Sleep Quality Assessed Using the Insomnia Severity Index.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Sleep quality / insomnia severity will be assessed using the Insomnia Severity Index. Total scores range from 0 to 28. Higher scores indicate greater insomnia severity and worse sleep quality.

  7. Between-Group Comparison of Genomic Profiles.

    Time frame: Time Frame: Baseline, Day 0.

    Genomic profiles will be compared between participants with active rheumatoid arthritis and chronic pain and participants with rheumatoid arthritis in sustained remission without clinically significant chronic pain using whole genome sequencing. Results will be reported as genomic variants or genomic signatures associated with chronic pain status according to the Statistical Analysis Plan.

  8. Electroencephalography-Derived Markers of Altered Pain Processing.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    In participants who undergo optional exploratory electroencephalography, predefined electroencephalography-derived markers of altered pain processing will be assessed according to the Statistical Analysis Plan. Associations between each predefined electroencephalography-derived parameter and pain intensity and neuropathic pain features will be explored. Results will be reported separately for each predefined electroencephalography parameter.

  9. Predictive Performance of an Integrative Biomarker Model for Chronic Pain Persistence.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Predictive performance of an integrative biomarker model for chronic pain persistence at Visit 2 will be assessed using model performance metrics specified in the Statistical Analysis Plan, such as discrimination metrics for classification models. Higher discrimination values indicate better predictive performance.

  10. Number of Participants Assigned to Each Multidimensional Pain Phenotype Cluster.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Participants will be assigned to multidimensional pain phenotype clusters using an integrative analytical approach based on clinical, laboratory, patient-reported, neurophysiological, and multiomic variables, according to the Statistical Analysis Plan. The outcome will be reported as the number of participants assigned to each derived phenotype cluster.

  11. Neuropathic Pain Features Assessed Using the DN4 Neuropathic Pain Questionnaire.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Neuropathic pain features will be assessed using the DN4 Neuropathic Pain Questionnaire. Total scores range from 0 to 10. Higher scores indicate more neuropathic pain features / greater likelihood of neuropathic pain.

  12. Fatigue Assessed Using the Fatigue Assessment Scale.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Fatigue will be assessed using the Fatigue Assessment Scale. Total scores range from 10 to 50. Higher scores indicate greater fatigue severity.

  13. Pain Coping Strategies Assessed Using the Coping Strategies Questionnaire.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Pain coping strategies will be assessed using the Coping Strategies Questionnaire. Coping-strategy subscales will be reported separately according to the questionnaire scoring instructions. For each coping-strategy subscale, higher scores indicate greater use of the respective coping strategy.

  14. Psychological Resilience Assessed Using the Resilience Scale-25.

    Time frame: Baseline (Day 0) and Visit 2 (3-6 months after baseline)

    Psychological resilience will be assessed using the Resilience Scale-25. Total scores range from 25 to 175. Higher scores indicate greater psychological resilience.

  15. Anxiety Symptoms Assessed Using the Generalised Anxiety Disorder-7 Scale.

    Time frame: Time Frame: Baseline, Day 0, and Visit 2, 3-6 months after baseline.

    Anxiety symptoms will be assessed using the Generalised Anxiety Disorder-7 Scale. Total scores range from 0 to 21. Higher scores indicate greater anxiety symptom severity.

  16. Anxiety and Depression Symptoms Assessed Using the Hospital Anxiety and Depression Scale.

    Time frame: Time Frame: Baseline, Day 0, and Visit 2, 3-6 months after baseline.

    Anxiety and depression symptoms will be assessed using the Hospital Anxiety and Depression Scale. The instrument includes two subscales: Hospital Anxiety and Depression Scale-Anxiety and Hospital Anxiety and Depression Scale-Depression. Each subscale ranges from 0 to 21. Higher scores indicate greater anxiety or depression symptom severity.

  17. Between-Group Comparison of Transcriptomic Profiles.

    Time frame: Time Frame: Baseline, Day 0, and Visit 2, 3-6 months after baseline.

    Transcriptomic profiles will be compared between participants with active rheumatoid arthritis and chronic pain and participants with rheumatoid arthritis in sustained remission without clinically significant chronic pain using messenger RNA expression profiling. Results will be reported as differentially expressed transcripts or transcriptomic signatures associated with chronic pain status according to the Statistical Analysis Plan.

  18. Between-Group Comparison of Secretomic Profiles.

    Time frame: Time Frame: Baseline, Day 0, and Visit 2, 3-6 months after baseline.

    Secretomic profiles will be compared between participants with active rheumatoid arthritis and chronic pain and participants with rheumatoid arthritis in sustained remission without clinically significant chronic pain using quantitative measurement of circulating proteins. Results will be reported as differentially abundant circulating proteins or secretomic signatures associated with chronic pain status according to the Statistical Analysis Plan.

  19. Predictive Performance of an Integrative Biomarker Model for Response to Biological Therapy.

    Time frame: Time Frame: Baseline predictors; treatment response assessed at Visit 2, 3-6 months after baseline.

    Predictive performance of an integrative biomarker model for response to biological therapy at Visit 2 will be assessed using model performance metrics specified in the Statistical Analysis Plan, such as discrimination metrics for classification models. Higher discrimination values indicate better predictive performance.

Study contacts

Contact information is provided by the study sponsor or research team.

Anna Skotny, dr n. med.

CONTACT

[email protected]

Wojciech Tanski, gen. bryg. dr hab. n. med.

CONTACT

[email protected]

0048261 660 321

Sponsors and collaborators

Lead sponsor

4th Military Clinical Hospital with Polyclinic, Poland

Other

Collaborators

  • Institute of Immunology and Experimental Therapy of the Polish Academy of Sciences
  • Lukasiewicz - PORT Polish Center for Technology Development
  • Wrocław University of Science and Technology

Registry information

Acronym: RA-PAIN-AI

Important dates

Study start
2026
Primary completion
2028
Study completion
2029
First posted
Aug 18, 2026
Registry last updated
Aug 18, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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