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Record W2132368680 · doi:10.1503/jpn.130283

Shared intermediate phenotypes for schizophrenia and bipolar disorder: neuroanatomical features of subtypes distinguished by executive dysfunction

2015· article· en· W2132368680 on OpenAlexvenueno aff
Alana M. Shepherd, Yann Quidé, Kristin R. Laurens, Nicole O’Reilly, Jesseca E. Rowland, Philip B. Mitchell, Vaughan J. Carr, Melissa J. Green

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2015
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research CouncilAustralian Schizophrenia Research BankRamsay Health CareNSW Ministry of HealthPratt FoundationKing's College LondonSylvia and Charles Viertel Charitable Foundation
KeywordsGrey matterBipolar disorderSchizophrenia (object-oriented programming)PsychologyPrecuneusWorking memoryWhite matterNeuroscienceNeuropsychologyAudiologyCardiologyInternal medicinePsychiatryMagnetic resonance imagingMedicineCognitionRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Shared genetic vulnerability for schizophrenia and bipolar disorder may be associated with common neuroanatomical features. In view of the evidence for working memory dysfunction as a candidate intermediate phenotype for both disorders, we explored neuroanatomical distinctions between subtypes defined according to working memory (n-back task) performance. METHODS: We analyzed T1-weighted MRI scans for patients with schizophrenia-spectrum disorder, bipolar-I disorder (BD-I) and healthy controls. The VBM8 toolbox was used to assess differences in grey and white matter volume across traditional diagnostic groups (schizophrenia v. BD-I). Subsequently, groups were defined as "executively spared" (ES) based on the achievement of greater than 50% accuracy in the 2-back task performance (comparable to performance in the control group) or "executively deficit" (ED) based on the achievement of less than 50% accuracy. RESULTS: Our study included 40 patients with schizophrenia-spectrum disorders, 30 patients with BD-I and 34 controls. Both the schizophrenia and BD-I groups showed grey matter volume reductions relative to the control group, but not relative to each other. The ED subtype (n = 32 [10 BD-I, 22 schizophrenia]) showed grey matter volume reductions in the bilateral superior and medial frontal gyri, right inferior opercular gyri and hippocampus relative to controls. The ES subtype (n = 38 [20 BD-I, 18 schizophrenia]) showed grey matter volume reductions in the right precuneus and left superior and medial orbital frontal gyri relative to controls. The ED subtype showed grey matter volume reduction in the right inferior frontal and precentral gyri relative to the ES subtype. There were no significant differences in white matter volume in any group comparisons. LIMITATIONS: This analysis was limited by small sample sizes. Further, insufficient numbers were available to assess a control-deficit comparison group. We were unable to assess the effects of mood stabilizer dose on brain structure. CONCLUSION: Neuroanatomical commonalities are evident among patients with schizophrenia-spectrum disorders and BD-I with working memory deficits. Reduced inferior frontal lobe volume may mediate cognitive deficits shared across the psychosis-mood spectrum.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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".

Quick stats

Citations38
Published2015
Admission routes1
Has abstractyes

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