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Record W4406750752 · doi:10.1186/s13229-024-00633-1

Evolutionary constrained genes associated with autism spectrum disorder across 2,054 nonhuman primate genomes

2025· article· en· W4406750752 on OpenAlexaff
Yukiko Kikuchi, Mohammed Uddin, Joris A. Veltman, Sara Wells, Christopher Morris, Marc Woodbury‐Smith

Bibliographic record

VenueMolecular Autism · 2025
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsQueen's UniversityGenome Canada
FundersMedical Research CouncilNational Institutes of Health
KeywordsAutism spectrum disorderNonhuman primatePrimateGenomeBiologyNeuropsychologyGeneAutismEvolutionary biologyGeneticsComputational biologyPsychologyNeuroscienceDevelopmental psychologyCognition

Abstract

fetched live from OpenAlex

Abstract Background Significant progress has been made in elucidating the genetic underpinnings of Autism Spectrum Disorder (ASD). However, there are still significant gaps in our understanding of the link between genomics, neurobiology and clinical phenotype in scientific discovery. New models are therefore needed to address these gaps. Rhesus macaques ( Macaca mulatta ) have been extensively used for preclinical neurobiological research because of remarkable similarities to humans across biology and behaviour that cannot be captured by other experimental animals. Methods We used the macaque Genotype and Phenotype (mGAP) resource consisting of 2,054 macaque genomes to examine patterns of evolutionary constraint in known human neurodevelopmental genes. Residual variation intolerance scores (RVIS) were calculated for all annotated autosomal genes ( N = 18,168) and Gene Set Enrichment Analysis (GSEA) was used to examine patterns of constraint across ASD genes and related neurodevelopmental genes. Results We demonstrated that patterns of constraint across autosomal genes are correlated in humans and macaques, and that ASD-associated genes exhibit significant constraint in macaques ( p = 9.4 × 10 − 27 ). Among macaques, many key ASD-implicated genes were observed to harbour predicted damaging mutations. A small number of key ASD-implicated genes that are highly intolerant to mutation in humans, however, showed no evidence of similar intolerance in macaques ( CACNA1D , MBD5 , AUTS2 and NRXN1 ). Constraint was also observed across genes associated with intellectual disability ( p = 1.1 × 10 − 46 ), epilepsy ( p = 2.1 × 10 − 33 ) and schizophrenia ( p = 4.2 × 10 − 45 ), and for an overlapping neurodevelopmental gene set ( p = 4.0 × 10 − 10 ). Limitations The lack of behavioural phenotypes among the macaques whose genotypes were studied means that we are unable to further investigate whether genetic variants have similar phenotypic consequences among nonhuman primates. Conclusion The presence of pathological mutations in ASD genes among macaques, along with evidence of similar genetic constraints to those in humans, provides a strong rationale for further investigation of genotype-phenotype relationships in macaques. This highlights the importance of developing primate models of ASD to elucidate the neurobiological underpinnings and advance approaches for precision medicine and therapeutic interventions.

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)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.289
Teacher spread0.277 · 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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Citations2
Published2025
Admission routes1
Has abstractyes

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