Quantitative multidimensional phenotypes improve genetic analysis of laterality traits

Judith SCHMITZ; Mo ZHENG; Kelvin F. H. LUI; Catherine MCBRIDE; Connie S.-H. HO; Silvia PARACCHINI

doi:10.1038/s41398-022-01834-z

Quantitative multidimensional phenotypes improve genetic analysis of laterality traits

Judith SCHMITZ, Mo ZHENG, Kelvin F. H. LUI, Catherine MCBRIDE, Connie S.-H. HO, Silvia PARACCHINI^*

^*Corresponding author for this work

Wofoo Joseph Lee Consulting and Counselling Psychology Research Centre

Research output: Journal Publications › Journal Article (refereed) › peer-review

12 Citations (Scopus)

Abstract

Handedness is the most commonly investigated lateralised phenotype and is usually measured as a binary left/right category. Its links with psychiatric and neurodevelopmental disorders prompted studies aimed at understanding the underlying genetics, while other measures and side preferences have been less studied. We investigated the heritability of hand, as well as foot, and eye preference by assessing parental effects (n ≤ 5028 family trios) and SNP-based heritability (SNP-h2, n ≤ 5931 children) in the Avon Longitudinal Study of Parents and Children (ALSPAC). An independent twin cohort from Hong Kong (n = 358) was used to replicate results from structural equation modelling (SEM). Parental left-side preference increased the chance of an individual to be left-sided for the same trait, with stronger maternal than paternal effects for footedness. By regressing out the effects of sex, age, and ancestry, we transformed laterality categories into quantitative measures. The SNP-h2 for quantitative handedness and footedness was 0.21 and 0.23, respectively, which is higher than the SNP-h2 reported in larger genetic studies using binary handedness measures. The heritability of the quantitative measure of handedness increased (0.45) compared to a binary measure for writing hand (0.27) in the Hong Kong twins. Genomic and behavioural SEM identified a shared genetic factor contributing to handedness, footedness, and eyedness, but no independent effects on individual phenotypes. Our analysis demonstrates how quantitative multidimensional laterality phenotypes are better suited to capture the underlying genetics than binary traits.

Original language	English
Article number	68
Number of pages	8
Journal	Translational Psychiatry
Volume	12
Issue number	1
DOIs	https://doi.org/10.1038/s41398-022-01834-z
Publication status	Published - 19 Feb 2022

Bibliographical note

Funding

We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. We also thank Andrew P. Morris and Beate St Pourcain for advising on statistical analyses. The authors would also like to express their gratitude to Sarah Medland, Gabriel Cuellar Partida, and David Evans for providing the handedness GWAS summary statistics. The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and SP and JS will serve as guarantors for the analysis of the ALSPAC data presented in this paper. GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. Support to the genetic analysis was provided by the St Andrews Bioinformatics Unit funded by the Wellcome Trust [grant 105621/Z/14/Z]. The Hong Kong sample was funded through a Collaborative Research Fund from the Hong Kong Special Administrative Region Research Grants Council (CUHK8/CRF/13G, and C4054-17WF). JS is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 418445085) and supported by the Wellcome Trust [Institutional Strategic Support fund, Grant number 204821/Z/16/Z]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. SP is funded by the Royal Society (UF150663).

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Quantitative multidimensional phenotypes improve genetic analysis of laterality traits

Abstract

Bibliographical note

Funding

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