Using a polygenic score in a family design to understand genetic influences on musicality

Abstract

To further our understanding of the genetics of musicality, we explored associations between a polygenic score for self-reported beat synchronization ability (PGSrhythm) and objectively measured rhythm discrimination, as well as other validated music skills and music-related traits. Using family data, we were able to further explore potential pathways of direct genetic, indirect genetic (through passive gene–environment correlation) and confounding effects (such as population structure and assortative mating). In 5648 Swedish twins, we found PGSrhythm to predict not only rhythm discrimination, but also melody and pitch discrimination (betas between 0.11 and 0.16, p < 0.001), as well as other music-related outcomes (p < 0.05). In contrast, PGSrhythm was not associated with control phenotypes not directly related to music. Associations did not deteriorate within families (N = 243), implying that indirect genetic or confounding effects did not inflate PGSrhythm effects. A correlation (r = 0.05, p < 0.001) between musical enrichment of the family childhood environment and individuals' PGSrhythm, suggests gene–environment correlation. We conclude that the PGSrhythm captures individuals' general genetic musical propensity, affecting musical behavior more likely direct than through indirect or confounding effects.

Synchrony to a beat predicts synchrony with other minds

“…Moreover, this ability is polygenic, underpinned by a genetic signature linked to several biological rhythms such as breathing, walking pace, and circadian chronotype. A large study of 5648 Swedish twins also found that selfreported beat synchronization runs in families (Wesseldijk et al, 2022). Further consistent with a stable, neurological basis, some neurological disorders affect synchrony.…”

Exploring the genetics of rhythmic perception and musical engagement in the Vanderbilt Online Musicality Study

“…Heritability estimates for rhythm perception and musical engagement were then calculated using GCTA, controlling for age, sex, and the first five ancestry‐based principal components (PCs). To improve the power for GREML, we replicated these heritability calculations in an independent sample of Swedish individuals, 43 then meta‐analyzed the resulting heritability estimates across the two independent datasets to obtain our final estimates. Swedish participants completed the exact same rhythm discrimination task administered in the Vanderbilt study (the SMDT; N = 2985) and one of the same self‐reported items on music engagement administered in the Vanderbilt study (i.e., “How engaged with music are you?,” N = 2929; see Supporting Material for more information on this sample).…”

A comprehensive investigation into the genetic relationship between music engagement and mental health

“…We also calculated PCs in the reduced sample with musical phenotypes available (N = 5,648), and including those as covariates in the association analyses did not change the results. For more details about the genetic data processing see Wesseldijk, Abdellaoui [25].…”

“…PGSs were calculated utilizing the most recent GWAS summary statistics available for MDD [35], bipolar disorder [36], schizophrenia [37], neuroticism, sensitivity to environmental stress (SESA) and depressive symptoms [38], and self-reported beat synchronization [24]. PGSs derived from the latter GWAS were shown to be a good proxy for genetic variation underlying general musicality in our recent validation study [25]. There was no overlap between the individuals in our current (target) sample and the discovery GWAS samples, which could lead to overestimation of the genetic predisposition of a trait [39].…”

“…Additionally, as control, we tested whether the polygenic scores are associated with general artistic achievements as established by Power, Steinberg [20], scientific achievements, as well as playing sports and the intensity of sport practice. We also examined whether a genetic predisposition for general musicality, including all aspects of human interaction with music, including music production skills and achievements as well as music engagement and listening [24,25] predicted receiving a clinical diagnosis of depression, anxiety, schizophrenia, bipolar disorder, stress-related disorders, or self-reported depressive symptoms, psychotic-like experiences or neuroticism. Lastly, to investigate gene-environment interaction, we tested whether the association between music engagement and mental health outcomes differed across levels of measured genetic risk for mental health problems.…”