Mediational effects of reading-related intermediate phenotypes from polygenic scores to reading skills
Bibliographic record
Abstract
Reading is a fundamental human capacity that recruits and tunes brain circuitry subserving several neurocognitive skills. Individual differences in reading-related skills are largely influenced by genetic variation. However, the molecular basis of the heritability of reading-related skills remains narrowly replicated. Genome-wide association studies have enabled the computation of cumulative indices (polygenic scores-PGSs) aiming to capture individuals' genetic susceptibility for a given trait. By using a multiple-mediator framework, we investigated whether the associations between a reading-specific PGS (Reading-PGS) and reading decoding and comprehension could be explained by reading-related endophenotypes (i.e., phonological awareness-PA, phonological memory, rapid auditory processing, rapid bimodal temporal processing-RBTP, and rapid automatized naming) in a sample of 8-year-old French-speaking Canadian twins (N = 328 subjects (87 MZ and 241 DZ) from 208 twin pairs-one child per MZ pairs; males, N = 159). The association between Reading-PGS and reading performance is partially mediated by PA and RBTP. Furthermore, we supported the specificity of the direct and indirect effects between Reading-PGS and reading skills after controlling for the shared genetic variation with educational attainment and cognitive ability. Finally, we uncovered a sequence from Reading-PGS to behavior mediated through sensory processing and phonological skills, supporting one of the most robust theoretical hypothesis underlying reading acquisitions. PGSs specifically targeting reading skills are essential for improved prediction and understanding of the complex etiology through which reading skills unfold during childhood. This will facilitate the early identification of children with a genetic susceptibility for reading (dis)ability at a time when these phenotypes remain malleable to intervention.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".