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Record W4309899484 · doi:10.3389/fgene.2022.1041943

Do the diverse phenotypes of Prader-Willi syndrome reflect extremes of covariation in typical populations?

2022· article· en· W4309899484 on OpenAlexafffund
Iiro Salminen, Silven Read, Bernard J. Crespi

Bibliographic record

VenueFrontiers in Genetics · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsSimon Fraser University
FundersCommon FundNational Institute of Neurological Disorders and StrokeNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteNational Institute of Mental HealthCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNIH Office of the DirectorNatural Sciences and Engineering Research Council of CanadaNational Cancer InstituteNational Institutes of HealthNational Institute on Drug AbuseSimon Fraser UniversityUniversity of Alberta
KeywordsPhenotypeBiologyAutismAutism spectrum disorderMoodCognitionPhenotypic traitGeneticsGenomic imprintingPsychologyGeneDevelopmental psychologyNeuroscienceClinical psychologyDNA methylation

Abstract

fetched live from OpenAlex

The phenotypes of human imprinted neurogenetic disorders can be hypothesized as extreme alterations of typical human phenotypes. The imprinted neurogenetic disorder Prader-Willi syndrome (PWS) features covarying phenotypes that centrally involve altered social behaviors, attachment, mood, circadian rhythms, and eating habits, that can be traced to altered functioning of the hypothalamus. Here, we conducted analyses to investigate the extent to which the behavioral variation shown in typical human populations for a set of PWAS-associated traits including autism spectrum cognition, schizotypal cognition, mood, eating, and sleeping phenotypes shows covariability that recapitulates the covariation observed in individuals with PWS. To this end, we collected data from 296 typical individuals for this set of phenotypes, and showed, using principal components analysis, evidence of a major axis reflecting key covarying PWS traits. We also reviewed the literature regarding neurogenetic syndromes that overlap in their affected traits with PWS, to determine their prevalence and properties. These findings demonstrate that a notable suite of syndromes shows phenotypic overlap with PWS, implicating a large set of imprinted and non-imprinted genes, some of which interact, in the phenotypes of this disorder. Considered together, these findings link variation in and among neurogenetic disorders with variation in typical populations, especially with regard to pleiotropic effects mediated by the hypothalamus. This work also implicates effects of imprinted gene variation on cognition and behavior in typical human populations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.055
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.269
Teacher spread0.241 · 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 teacher head, 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

Citations2
Published2022
Admission routes2
Has abstractyes

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