---
title: "AI-driven multiomic and neurophysiological profiling of chronic pain in rheumatoid arthritis"
id: "bmj-open-10-integrative-ai-based-multiomic-and-neurophysiological-profiling-of-chronic-pain"
canonical_url: "https://medichelpline.com/clinical-feed/bmj-open-10-integrative-ai-based-multiomic-and-neurophysiological-profiling-of-chronic-pain"
content_type: "clinical_feed_article"
specialty: "Rheumatology"
source_name: "BMJ Open"
source_url: "http://bmjopen.bmj.com/cgi/content/short/16/9/e122024?rss=1"
published_at: "2026-09-24T12:27:02.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# AI-driven multiomic and neurophysiological profiling of chronic pain in rheumatoid arthritis
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/bmj-open-10-integrative-ai-based-multiomic-and-neurophysiological-profiling-of-chronic-pain
- **Specialty:** [Rheumatology](https://medichelpline.com/clinical-feed/rheumatology.md)
- **Primary Source:** BMJ Open
- **Source URL:** [Original Journal Publication](http://bmjopen.bmj.com/cgi/content/short/16/9/e122024?rss=1)
- **Published At:** 2026-09-24T12:27:02.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Rheumatoid arthritis (RA) remains dominated by **chronic pain**, which persists in an estimated 20–30% of patients despite inflammatory control with biologic and targeted synthetic DMARDs. - Persistent pain after remission is hypothesised to involve a shift from peripheral nociception to central sensitisation and **nociplastic pain**, motivating integrative stratification approaches. - The RA-PAIN-AI study is a prospective, observational, single-centre case–control study designed to identify clinical, neurophysiological and multiomic signatures associated with chronic pain in RA using integrative **artificial intelligence (AI)** methods. - Two adult RA groups will be enrolled: patients with active disease qualifying for biological therapy under the Polish national drug programme B.33, and patients on biological therapy in sustained clinical remission ≥1.5 years without clinically significant chronic pain. - Participants will undergo baseline clinical assessment, validated patient-reported outcome measures, and peripheral blood sampling; repeat questionnaires and blood collection will occur at 3–6 months with exact intervals recorded for longitudinal analyses. - Biological samples will be analysed by **whole genome sequencing (genomics)**, mRNA expression profiling (transcriptomics) and circulating protein measurement (secretomics). - **Electroencephalography (EEG)** will be performed only in a predefined exploratory subset based on feasibility, safety and eligibility criteria. - Minimum recruitment target is 50 participants per group. Given the exploratory, high-dimensional nature of the data, planned AI and machine-learning analyses will apply prespecified feature filtering, dimensionality reduction, regularisation and internal validation; all predictive models will require external validation in future cohorts. - The protocol received a favourable ethics opinion from the Bioethics Committee at the Hirszfeld Institute (Opinion No. KB-17/2025, dated 25 September 2025); written informed consent will be obtained and results disseminated via peer-reviewed publications, conferences and stakeholder communication. - Trial registration is provided as NCT07769619.
## Clinical Analysis & Structured Key Points
Introduction Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease in which pain remains the most prominent and burdensome symptom from the patient's perspective. Despite effective control of peripheral inflammation with biological and targeted synthetic disease-modifying antirheumatic drugs, an estimated 20 - 30% of patients continue to experience persistent moderate-to-severe pain after achieving clinical remission. This therapeutic gap reflects the evolution of pain mechanisms from peripheral nociception towards central sensitisation and nociplastic pain, creating a need for integrative approaches to patient stratification. The Rheumatoid Arthritis Pain Artificial Intelligence (RA-PAIN-AI) study aims to identify and characterise clinical, neurophysiological and multiomic signatures associated with chronic pain in patients with RA using integrative artificial intelligence (AI)-based analytical methods. Methods and analysis RA-PAIN-AI is a prospective, observational, single-centre case - control study integrating clinical laboratory neurophysiological and multiomic data. Two groups of adult patients with RA will be enrolled: patients with active RA qualifying for biological therapy under the Polish national drug programme B.33 and patients receiving biological therapy who are in sustained clinical remission for at least 1.5 years without clinically significant chronic pain. All participants will undergo clinical assessment, validated patient-reported outcome measures and peripheral blood collection at baseline, followed by repeat questionnaires and peripheral blood collection at 3 - 6 months. The exact interval between visits will be recorded and included in longitudinal analyses where appropriate. Electroencephalography will be performed only in an exploratory subset according to predefined feasibility, safety and eligibility criteria. Biological samples will be analysed using whole genome sequencing (genomics), messenger RNA expression profiling (transcriptomics) and measurement of circulating proteins (secretomics). A minimum of 50 participants per group will be recruited. Because the study is exploratory and high-dimensional, AI and machine-learning analyses will use prespecified feature filtering, dimensionality reduction, regularisation and internal validation procedures, and all predictive models will require external validation in future cohorts. Ethics and dissemination The protocol received a favourable opinion from the Bioethics Committee at the Hirszfeld Institute of Immunology and Experimental Therapy, Polish Academy of Sciences, Wroclaw, Poland (Opinion No. KB-17/2025, dated 25 September 2025). Written informed consent will be obtained from all participants before any study-related procedure. The results will be disseminated through peer-reviewed publications, conference presentations and communication with relevant scientific, clinical and patient communities. Trial registration number NCT07769619 .
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