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Record W3119908963 · doi:10.1101/2021.01.05.423827

Genome Wide Association Study in the New Haven Lexinome Project Identifies <i>GARRE1</i> as a Novel Gene for Reading Performance

2021· preprint· en· W3119908963 on OpenAlexaff
Andrew K. Adams, Emily L. Guertin, Dongnhu T. Truong, Elizabeth G. Atkinson, Mellissa M. C. DeMille, Joan Bosson‐Heenan, Jan C. Frijters, Jeffrey R. Gruen

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsBrock University
FundersManton Foundation
KeywordsGenome-wide association studyMinor allele frequencySingle-nucleotide polymorphismGeneticsBiologyGenetic associationExpression quantitative trait lociLocus (genetics)HeritabilityQuantitative trait locusAlleleDyslexiaGeneReading (process)Genotype

Abstract

fetched live from OpenAlex

Abstract Despite high prevalence and high heritability, few candidate genes have been identified for reading disability. To identify novel genetic variants we performed a genome-wide association study (GWAS) using high-depth whole genome sequencing and predicated on reading performance in 407 subjects enrolled in a longitudinal study of response-to-intervention, called the New Haven Lexinome Project. The primary GWAS identified a single peak of 31 SNPs on chromosome 19 that achieved the threshold for genome-wide significance (rs2599553 P =3.13×10 −8 ) located over an expression quantitative trait locus (eQTL) for GARRE1 (Granule Associated Rac And RHOG Effector 1). Little is known about the function of GARRE1 , except that it is highly and developmentally expressed in human cerebellum relative to cortex. Local ancestry regression showed the strongest association for the lead variant in African or Admixed American populations, who have been under-represented in previous genetic studies of reading. We replicated our chromosome 19 results in the Genes, Reading, and Dyslexia (GRaD) cohort and found a moderating effect of age with implications for the consideration of developmental effects in the design of future analyses. Growth curve modeling demonstrated that minor alleles of the lead SNP are related to reading longitudinally from Grade 1 to Grade 5, and that children with at least 1 minor allele of rs2599553 persistently underperformed relative to their peers by 0.33 to 0.5 standard deviations on standardized assessments of non-word decoding and reading fluency. Significance Statement To the best of our knowledge, this work represents the only GWAS predicated on longitudinal reading performance data. Starting with initial discovery, we replicate our association in a second cohort, address common causes of type I error, localize the signal to a single gene, implicate a region of the brain most likely to be affected by variation in our candidate, show a gene-by-age effect with implications for study design in this field, and demonstrate that minor alleles of our lead SNP are associated with significant and persistent clinical effects on reading development in children.

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)0.002
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.029
GPT teacher head0.282
Teacher spread0.254 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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