Daily Pain Is Associated with Alterations in Functional Connectivity of the Brain on fMRI in Adults with Sickle Cell Disease
Bibliographic record
Abstract
Abstract Background:One-third of adults with sickle cell disease (SCD) have daily, chronic pain. Despite the high prevalence of chronic pain in adults with SCD, the mechanism of is not well defined. In other chronic pain disorders, functional MRI (fMRI) demonstrates a re-organization of the brain's connectivity, which may be maladaptive and contribute to the development of a chronic pain syndrome. We performed fMRI in adults with SCD as well as age-matched controls in order to test two hypotheses: 1) functional connectivity is different between adults with SCD and controls, and 2) differences in functional connectivity among adults with SCD are associated with a more severe pain phenotype. Methods:We performed resting-state fMRI in adults with SCD and age-matched controls. Functional connectivity was calculated using two approaches: 1) a seed-voxel approach with the seed being periaqueductal gray (PAG), an area of the brain known to inhibit pain sensation, and 2) an inter-network functional connectivity strength (FCS) analysis, in which seven brain functional networks were selected based on previous brain modularity analysis findings. To calculate the inter-network FCS between networks A and B, the summation of all functional connectivities between two networks are used. Thereafter, the networks that were significantly different in FCS between SCD and controls were used to determine the association between altered functional connectivity and pain phenotype within SCD subjects. Pain phenotype measurements in SCD subjects included a day-of-study pain score, a 15-day diary to document daily pain and opioid use, McGill pain and Pain DETECT questionnaires, and quantitative sensory testing in response to mechanical, cold, and heat stimuli. Statistical analyses were performed using FSL and Matlab software. Results: A total of 27 adults were examined, including 13 with SCD (9 HbSS, 4 HbSC) and 14 age-matched controls. Seed-based functional connectivity analyses revealed significantly decreased connectivity in SCD as compared to controls between PAG and the regions involved in pain, sensation, salience, emotion, learning, and memory (temporal gyrus, anterior/posterior insula, parahippocampal gyrus, fusiform gyrus, precunes, posterior cingulate gyrus, anterior cingulate, subcallosal gyrus, paracentral gyrus, inferior/superior parietal lobe, inferior frontal gyrus and superior temporal gyrus) (P<0.001, t-test with AlphaSim correction). Furthermore, inter-network analyses show significantly decreased FCS in SCD as compared to controls among networks involved in salience, emotion, learning, and memory (between the salience network and the striatum network, between the salience network and the temporal network, and within both the salience network and the hippocampus network) (P<0.001, t-test). When these inter-network differences in FCS between SCD subjects and controls were examined within SCD subjects to determine the association with clinical phenotype, significant associations were found with age (rs=0.63, P<0.024, Spearman correlation analysis), SCD genotype (SS vs SC) (r2=0.43, P<0.016, linear regression analysis), and number of diary days with pain score >5 (r2=0.5, P<0.011, linear regression analysis). Conclusions: In adults with SCD compared to controls, there were differences in inter-network FCS, including the salience, striatum, temporal, and hippocampus networks, which are crucial networks for salience, emotion, learning, and memory. When these inter-network FCS differences were examined within adults with SCD, significant associations were found with age, SCD genotype and number of pain days. Taken together, these data suggest that altered connectivity in the brain of adults with SCD contributes to the development of a chronic pain syndrome. These changes in functional connectivity on fMRI could be used as a biomarker to determine the efficacy of interventions targeted to decrease chronic pain. Disclosures Field: NKT Therapeutics: Research Funding; Astellas Pharmaceuticals: Research Funding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".