Histological Underpinnings of Grey Matter Changes in Fibromyalgia Investigated Using Multimodal Brain Imaging
Bibliographic record
Abstract
Chronic pain patients present with cortical gray matter alterations, observed with anatomical magnetic resonance (MR) imaging. Reduced regional gray matter volumes are often interpreted to reflect neurodegeneration, but studies investigating the cellular origin of gray matter changes are lacking. We used multimodal imaging to compare 26 postmenopausal women with fibromyalgia with 25 healthy controls (age range: 50–75 years) to test whether regional gray matter volume decreases in chronic pain are associated with compromised neuronal integrity. Regional gray matter decreases were largely explained by T1 relaxation times in gray matter, a surrogate measure of water content, and not to any substantial degree by GABA A receptor concentration, an indirect marker of neuronal integrity measured with [ 18 F] flumazenil PET. In addition, the MR spectroscopy marker of neuronal viability, N -acetylaspartate, did not differ between patients and controls. These findings suggest that decreased gray matter volumes are not explained by compromised neuronal integrity. Alternatively, a decrease in neuronal matter could be compensated for by an upregulation of GABA A receptors. The relation between regional gray matter and T1 relaxation times suggests decreased tissue water content underlying regional gray matter decreases. In contrast, regional gray matter increases were explained by GABA A receptor concentration in addition to T1 relaxation times, indicating perhaps increased neuronal matter or GABA A receptor upregulation and inflammatory edema. By providing information on the histological origins of cerebral gray matter alterations in fibromyalgia, this study advances the understanding of the neurobiology of chronic widespread pain. SIGNIFICANCE STATEMENT Regional gray matter alterations in chronic pain, as detected with voxel-based morphometry of anatomical magnetic resonance images, are commonly interpreted to reflect neurodegeneration, but this assumption has not been tested. We found decreased gray matter in fibromyalgia to be associated with T1 relaxation times, a surrogate marker of water content, but not with GABA A receptor concentration, a surrogate of neuronal integrity. In contrast, regional gray matter increases were partly explained by GABA A receptor concentration, indicating some form of neuronal plasticity. The study emphasizes that voxel-based morphometry is an exploratory measure, demonstrating the need to investigate the histological origin of gray matter alterations for every distinct clinical entity, and advances the understanding of the neurobiology of chronic (widespread) pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".