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Record W4394980113 · doi:10.1093/braincomms/fcae143

Systemic inflammation associates with and precedes cord atrophy in progressive multiple sclerosis

2024· article· en· W4394980113 on OpenAlexfundno aff
C Stuart, Aravinthan Varatharaj, Yukai Zou, Angela Darekar, Janine Domjan, Claudia A. M. Gandini Wheeler‐Kingshott, V. Hugh Perry, Ian Galea

Bibliographic record

VenueBrain Communications · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersMedical Research CouncilWessex Medical ResearchMedical Research Council CanadaUniversity of SouthamptonMultiple Sclerosis Society
KeywordsAtrophyMultiple sclerosisInflammationMedicinePathologyCordNeuroscienceImmunologyBiologySurgery

Abstract

fetched live from OpenAlex

Abstract In preclinical models of multiple sclerosis, systemic inflammation has an impact on the compartmentalized inflammatory process within the central nervous system and results in axonal loss. It remains to be shown whether this is the case in humans, specifically whether systemic inflammation contributes to spinal cord or brain atrophy in multiple sclerosis. Hence, an observational longitudinal study was conducted to delineate the relationship between systemic inflammation and atrophy using magnetic resonance imaging: the SIMS (Systemic Inflammation in Multiple Sclerosis) study. Systemic inflammation and progression were assessed in people with progressive multiple sclerosis (n = 50) over two and a half years. Eligibility criteria included: (i) primary or secondary progressive multiple sclerosis; (ii) age ≤ 70; and (iii) Expanded Disability Status Scale ≤ 6.5. First morning urine was collected weekly to quantify systemic inflammation by measuring the urinary neopterin-to-creatinine ratio using a validated ultra-performance liquid chromatography mass spectrometry technique. The urinary neopterin-to-creatinine ratio temporal profile was characterized by short-term responses overlaid on a background level of inflammation, so these two distinct processes were considered as separate variables: background inflammation and inflammatory response. Participants underwent MRI at the start and end of the study, to measure cervical spinal cord and brain atrophy. Brain and cervical cord atrophy occurred on the study, but the most striking change was seen in the cervical spinal cord, in keeping with the corticospinal tract involvement that is typical of progressive disease. Systemic inflammation predicted cervical cord atrophy. An association with brain atrophy was not observed in this cohort. A time lag between systemic inflammation and cord atrophy was evident, suggesting but not proving causation. The association of the inflammatory response with cord atrophy depended on the level of background inflammation, in keeping with experimental data in preclinical models where the effects of a systemic inflammatory challenge on tissue injury depended on prior exposure to inflammation. A higher inflammatory response was associated with accelerated cord atrophy in the presence of background systemic inflammation below the median for the study population. Higher background inflammation, while associated with cervical cord atrophy itself, subdued the association of the inflammatory response with cord atrophy. Findings were robust to sensitivity analyses adjusting for potential confounders and excluding cases with new lesion formation. In conclusion, systemic inflammation associates with, and precedes, multiple sclerosis progression. Further work is needed to prove causation since targeting systemic inflammation may offer novel treatment strategies for slowing neurodegeneration in multiple sclerosis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.092
GPT teacher head0.345
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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