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Record W6961461864 · doi:10.15154/aps3-0723

1/3 Brain Function and Genetics in Pediatric Obsessive-Compulsive Behaviors

2018· other· en· W6961461864 on OpenAlexaboutno aff

Bibliographic record

VenueNational Institutes of Health, National Institute of Mental Health (NIMH) Data Archive Repository · 2018
Typeother
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHeritabilityFunctional magnetic resonance imagingBrain Structure and FunctionTwin studyGenetic variantsImaging geneticsEndophenotypeMagnetic resonance imagingResting state fMRINeuroimaging

Abstract

fetched live from OpenAlex

Obsessive-compulsive behaviors (OCB) are common in children and adolescents. In addition to being the core features of obsessive-compulsive disorder (OCD), OCB are often associated in youth with tic, grooming, generalized anxiety, and autistic spectrum disorders. This competitive renewal application combines the unique clinical assessment, magnetic resonance imaging, and genetics expertise of three performance sites: Wayne State University (WSU), University of Michigan (UM), and the Hospital for Sick Children, affiliated with the University of Toronto (UT). The overall goal of this project - which extends prior and existing NIMH-funded research including Drs. Rosenberg and Diwadkar's neurodiagnostic imaging-genetic studies (K24MH02037; R01MH59299), Dr. Hanna's family, molecular genetic, and action monitoring studies (R01MH53876; R01MH59299; K20MH01065; R01MH101493) and Dr. Arnold and colleagues' extensive genetic studies in pediatric OCD (R01MH59299; R01MH101493) - is to exploit the emerging field of imaging genetics to 1) determine the relationship between alterations in functional connectivity of fronto-striatal-thalamic circuitry (FSTC) as measured by task and resting state functional magnetic resonance imaging (fMRI) and childhood OCB; 2) identify common, rare, and novel genetic variants associated with alterations in connectivity of FSTC as measured by fMRI; 3) clarify whether fMRI measured alterations in FSTC are potential intermediate phenotypes of OCB by determining whether they mediate the effects of genetic variants on OCB; and 4) combine structural MRI data from this study and our previous imaging genetics study to identify genetic variants associated with anterior cingulate volume and other FSTC structures in 1000 youth. The Child Behavior Checklist Obsessive-Compulsive Scale (CBCL-OCS) shows substantial heritability in pediatric twin studies. Heritability of structural and functional abnormalities in STC has also been demonstrated in OCD patients and their unaffected relatives. By using a research design consistent with the Research Domain Criteria (RDoC), targeted high field (3 Tesla) fMRI at WSU will be combined with comprehensive genomic assessment in 200 child psychiatric outpatients with CBCL-OCS scores = 5, 200 child psychiatric outpatients with CBL-OCS scores < 5, and 200 matched healthy controls aged 8-18 years. We will examine for common and rare genomic variants associated with FSTC dysregulation and conduct whole genome sequencing (WGS) in 60 subjects with FSTC dysregulation in the highest 10% of the distribution and compare to 60 subjects with FSTC dysregulation in the lowest 10% of the distribution to identify rare and novel variants of possible clinical significance. This unique study enacts the call for translational approaches to mental illness outlined in PAR- 14-165 by examining multiple genomic variants in FSTC in a spectrum of common, but understudied disorders in youth. Our work will provide a better understanding of the impact of genetic variants on FSTC dysregulation in the pathogenesis of OCB and lead to new diagnostic, treatment, and prevention strategies.

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: Dataset · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.048
GPT teacher head0.350
Teacher spread0.303 · 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
GenreDataset

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

Citations0
Published2018
Admission routes1
Has abstractyes

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