The association between preschool musicality and school-age speech-related communication is partially accounted for by polygenic scores for rhythmicity¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2–r3 · q2 · i0 negligible
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i0 In a mediation-analogue SEM, the shared effect between preschool musicality and school-age speech factors captured by PGS rhythmicity is small but significant (β = 0.0051, SE = 0.0021, p = 0.015), within a total effect of β = 0.46 (p = 1.59×10−9). → Lucía de Hoyos 2025 q2 i? The PGS-rhythmicity-associated three-factor model fits well (CFI = 0.95), with modest musicality-speech (r = 0.42) and musicality-cognition (r = 0.31) factor correlations. → Lucía de Hoyos 2025 (2)

Evidence¶

Lucía de Hoyos 2025¶

Lucía de Hoyos, Ellen Verhoef, Aysu Okbay, Janne R. Vermeulen, Celeste Figaroa, Miriam Lense, Simon E. Fisher, Reyna L. Gordon & Beate St Pourcain. (2025). Preschool musicality is associated with school-age communication abilities through genes related to rhythmicity. npj Science of Learning 10:39. https://doi.org/10.1038/s41539-025-00329-y

q2 · i0 · associational · r2

Mediation-framework SEM on PGS-rhythmicity-associated ALSPAC measures (N = 5873) modelling directionality from preschool musicality to school-age communication; the article reports the total effect β = 0.46 and the shared effect "β = 0.0051 (SE = 0.0021), p = 0.015", a very small standardised coefficient, hence impact 0.

"the association between preschool musicality skills (Fmusicality) and school-age communication skills (Fspeech) (total effect:β =0 . 4 6( S E=0 . 0 4 7 ) ,p =1 . 5 9×1 0−9) is partially accounted for by PGSrhythmicity (shared effect: β = 0.0051 (SE = 0.0021), p = 0.015"

Lucía de Hoyos 2025 (2)¶

Lucía de Hoyos, Ellen Verhoef, Aysu Okbay, Janne R. Vermeulen, Celeste Figaroa, Miriam Lense, Simon E. Fisher, Reyna L. Gordon & Beate St Pourcain. (2025). Preschool musicality is associated with school-age communication abilities through genes related to rhythmicity. npj Science of Learning 10:39. https://doi.org/10.1038/s41539-025-00329-y

q2 · i? · associational · r3

Confirmatory factor analysis of PGS-rhythmicity-associated measures (N = 5873) identified a three-factor structure — Fmusicality, Fcognition, F*speech — with "a good model fit (CFI = 0.95, TLI = 0.93, RMSEA = 0.042, SRMR = 0.028"; factor loadings were virtually identical after adding PGS rhythmicity to the model.

"We identified a correlated three- factor model, which showed a good model fit (CFI = 0.95, TLI = 0.93, RMSEA = 0.042, SRMR = 0.028"

Discussion¶

Related Claims¶

• Latent musicality correlates moderately with speech-related communication (r = 0.50) and modestly with cognition (r = 0.33), but not with pragmatic or social-communication factors — a broader claim this one bears on
• Polygenic scores for rhythmicity associate with school-age speech-related communication and verbal-cognition outcomes, with two associations passing multiple-testing correction and four at the nominal level — related
• Genetic variation shared with rhythmicity does not account for the association between preschool musicality and school-age verbal cognition — related
• Polygenic scores for adult rhythmicity validate ALSPAC preschool and school-age musicality measures, extending genetic associations with rhythmicity to an earlier developmental window — related
• Phenotypic and genetic associations with musicality are robust to genetic confounding via educational attainment — related
• Preschool and school-age musicality measures predict school-age communication and social communication, explaining up to 6% of phenotypic variance, while infant nursery-rhyme measures explain less than 1%
• In latent difference score models of ability domains, nearly all PGS-to-change pathways are small and nonsignificant, while age consistently predicts pre-test level and change — related