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Record W4413341609 · doi:10.69667/rmj.25318

Cytogenetic Study of Autism: A Systematic Review

2025· article· en· W4413341609 on OpenAlexaboutno aff

Bibliographic record

VenueRazi Medical Journal · 2025
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsAutismPsychologySystematic reviewMedicineMEDLINEPsychiatryBiology

Abstract

fetched live from OpenAlex

Study of autism via a methodical search strategy predominantly through the Scopus database. The search employed terms including "autism," "autism spectrum disorder," "ASD," alongside "cytogenetics," "chromosome," "chromosomal abnormality," "copy number variation," "CNV," and "aneuploidy." The inquiry was confined to English, peer-reviewed publications without temporal limitations. The inclusion criteria emphasized original research, reviews, and case reports that elucidate cytogenetic or chromosomal investigations in persons with autism, encompassing classic karyotyping, aCGH, and SNP arrays, accompanied by explicit descriptions of findings and diagnoses. The exclusion criteria eliminated research focused on single-gene mutations lacking a cytogenetic component, non-English publications, editorials, and studies in which chromosomal mosaicism was a secondary observation. The findings indicated a vigorous scientific production in autism research, with annual publications continuously over 300 from 2021 to 2023; however, a decrease was observed in 2024 and 2025. The United States prominently led in publications, with over 600 documents, followed by Italy, the United Kingdom, China, and Canada. Prominent authors such as J.D. Buxbaum and A. Kolezvon significantly influenced research productivity. The review methodologically emphasized the growing integration of advanced genetic testing, such as Chromosomal Microarray Analysis (CMA), Whole Exome Sequencing (WES), and Whole Genome Sequencing (WGS), in conjunction with behavioral evaluations. Chromosomal Microarray Analysis (CMA) has become the recommended initial genetic assessment, detecting harmful copy number variations (CNVs) in 10-20% of autism spectrum disorder (ASD) cases, with elevated rates among individuals with intellectual disabilities. WES functioned as an ancillary instrument, providing diagnoses in 15-30% of ASD cohorts by identifying de novo pathogenic single-nucleotide variants (SNVs) and copy number variations (CNVs). Whole Genome Sequencing (WGS), albeit costly, provided the most thorough genomic perspective, detecting complex structural variants and copy number variations (CNVs) overlooked by alternative methods.

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)0.010
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.034
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0250.023
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.032
GPT teacher head0.369
Teacher spread0.337 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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