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Inflammation in the Neurocircuitry of Obsessive-Compulsive Disorder

2017· article· en· W2654923513 on OpenAlexafffund
Sophia Attwells, Elaine Setiawan, Alan A. Wilson, Pablo Rusjan, Romina Mizrahi, Laura Miler, Cynthia Xu, Margaret A. Richter, Alan Kahn, Stephen J. Kish, Sylvain Houle, Lakshmi N. Ravindran, Jeffrey H. Meyer

Bibliographic record

VenueJAMA Psychiatry · 2017
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreCentre for Addiction and Mental HealthUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsTranslocator proteinPutamenOrbitofrontal cortexAnterior cingulate cortexBasal gangliaStriatumThalamusPsychologyNeuroinflammationNeurosciencePosterior cingulatePrecuneusVentral striatumCingulate cortexCortex (anatomy)MedicineInternal medicinePrefrontal cortexCentral nervous systemInflammationFunctional magnetic resonance imagingDopamineCognition

Abstract

fetched live from OpenAlex

Importance: For a small percentage of obsessive-compulsive disorder (OCD) cases exhibiting additional neuropsychiatric symptoms, it was proposed that neuroinflammation occurs in the basal ganglia as an autoimmune response to infections. However, it is possible that elevated neuroinflammation, inducible by a diverse range of mechanisms, is important throughout the cortico-striato-thalamo-cortical circuit of OCD. Identifying brain inflammation is possible with the recent advance in positron emission tomography (PET) radioligands that bind to the translocator protein (TSPO). Translocator protein density increases when microglia are activated during neuroinflammation and the TSPO distribution volume (VT) is an index of TSPO density. Objective: To determine whether TSPO VT is elevated in the dorsal caudate, orbitofrontal cortex, thalamus, ventral striatum, dorsal putamen, and anterior cingulate cortex in OCD. Design, Setting, and Participants: This case-control study was conducted at a tertiary care psychiatric hospital from May 1, 2010, to November 30, 2016. Participants with OCD (n = 20) and age-matched healthy control individuals (n = 20) underwent a fluorine F 18-labeled N-(2-(2-fluoroethoxy)benzyl)-N-(4-phenoxypyridin-3-yl)acetamide PET scan. It is a high-quality second-generation TSPO-binding PET radiotracer. All participants were drug and medication free, nonsmoking, and otherwise healthy. Main Outcomes and Measures: The TSPO VT was measured in the dorsal caudate, orbitofrontal cortex, thalamus, ventral striatum, dorsal putamen, and anterior cingulate cortex. Compulsions were assessed with the Yale-Brown Obsessive Compulsive Scale. Results: In the OCD and healthy groups, the mean (SD) ages were 27.4 (7.1) years and 27.6 (6.6) years, respectively, and 11 (55%) and 8 (40%) were women, respectively. In OCD, TSPO VT was significantly elevated in these brain regions (mean, 32%; range, 31%-36% except anterior cingulate cortex, 24%; analysis of variance, effect of diagnosis: P < .001 to P = .004). Slightly lower elevations in TSPO VT (22%-29%) were present in other gray matter regions. The Yale-Brown Obsessive Compulsive Scale measure of distress associated with preventing compulsive behaviors significantly correlated with TSPO VT in the orbitofrontal cortex (uncorrected Pearson correlation r = 0.62; P = .005). Conclusions and Relevance: To our knowledge, this is the first study demonstrating inflammation within the neurocircuitry of OCD. The regional distribution of elevated TSPO VT argues that the autoimmune/neuroinflammatory theories of OCD should extend beyond the basal ganglia to include the cortico-striato-thalamo-cortical circuit. Immunomodulatory therapies should be investigated in adult OCD, rather than solely childhood OCD, particularly in cases with prominent distress when preventing compulsions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.301
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), 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".

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Citations202
Published2017
Admission routes2
Has abstractyes

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