MétaCan
Menu
Back to cohort
Record W4402147613 · doi:10.1101/2024.08.02.24311302

Fetal Gene Regulatory Gene Deletions are Associated with Poor Cognition in Schizophrenia and Community-Based Samples

2024· preprint· en· W4402147613 on OpenAlexaff
Jennifer K. Forsyth, Jinhan Zhu, Ariana S. Chavannes, Zachary Trevorrow, Mahnoor Hyat, Sam A. Sievertsen, Sophie Ferreira-Ianone, Matthew P. Conomos, Keith H. Nuechterlein, Robert F. Asarnow, Michael F. Green, Katherine H. Karlsgodt, Diana O. Perkins, Tyrone D. Cannon, Jean Addington, K.S. Cadenhead, Barbara A. Cornblatt, Matcheri S. Keshavan, Daniel H. Mathalon, William S. Stone, Ming T. Tsuang, Elaine F. Walker, Scott W. Woods, Katherine L. Narr, Sarah McEwen, Charles Schleifer, Cindy M. Yee, Caroline Diehl, Anika Guha, Gregory A. Miller, Aaron Alexander‐Bloch, Jakob Seidlitz, Richard A. I. Bethlehem, Roel A. Ophoff, Carrie E. Bearden

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsUniversity of Calgary
FundersClinical and Translational Science Institute, University of California, Los AngelesNational Center for Advancing Translational SciencesNational Institute of Mental HealthShear Family FoundationNational Alliance for Research on Schizophrenia and Depression
KeywordsCopy-number variationNeurodevelopmental disorderSchizophrenia (object-oriented programming)PsychosisIntellectual disabilityPopulationGeneticsBiologyGenePsychologyMedicinePsychiatryGenome

Abstract

fetched live from OpenAlex

ABSTRACT Objective Schizophrenia is a neurodevelopmental disorder involving clinical and genetic heterogeneity. Multiple recurrent copy number variants (CNVs) increase risk for schizophrenia spectrum disorders (SSD). However, how known risk CNVs and broader genome-wide CNVs influence clinical variability is unclear. Furthermore, whether biological annotation of CNV scores can improve power for patient stratification is unknown. Methods This study examined associations between severe phenotypes in 617 SSD individuals, namely, child-onset psychosis or borderline intellectual functioning (IQ), and: 1) known risk CNVs; 2) genome-wide deletion burden scores; and 3) novel scores capturing deletion burden in 18 previously validated and mutually exclusive gene-sets, representing distinct aspects of neurodevelopment. Associations with borderline IQ were assessed for replicability in 233 SSD-relatives and 581 controls, and 9,930 youth from the Adolescent Brain Cognitive Development (ABCD) Study. Results Known SSD- (odds ratios (OR)=7.07, 95%CI[1.60,31.32]) and neurodevelopmental disorder (NDD)-risk CNVs (OR=4.56, 95%CI[1.48,14.10]) were associated with borderline IQ in SSD. Furthermore, beyond effects of known NDD-risk CNVs, deletion of genes involved in regulating gene expression during fetal brain development was associated with borderline IQ across SSD cases and non-cases (OR=2.57, 95%CI[1.44,4.60]), and in the ABCD cohort (OR=1.33, 95%CI[1.00,1.76]). Exploratory structural MRI-based analyses showed associations between fetal gene regulatory gene deletions and altered gray matter volume ( b =0.09, 95%CI[0.004,0.17]) and cortical thickness ( b =0.14, 95%CI[0.05,0.24]) across SSD cases and non-cases. Conclusions Results confirm contributions of known risk CNVs to severe phenotypes in SSD, implicate disrupted fetal brain development in poor cognition, and demonstrate the utility of a neurodevelopmental framework for identifying mechanisms underlying severe SSD-relevant phenotypes.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.226
Teacher spread0.207 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuemedRxivSame topicGenomic variations and chromosomal abnormalitiesFrench-language works237,207