Bayesian polygenic risk estimation approach to nuclear families with discordant sib-pairs for myelomeningocele

Adolfo Aguayo-Gómez, Leonora Luna-Muñoz, Yevgeniya Svyryd, Luis Ángel Muñoz-Téllez and Osvaldo M Mutchinick

PLOS ONE, 2024, vol. 19, issue 12, 1-12

Abstract: Myelomeningocele (MMC) is the most severe and disabling form of spina bifida with chronic health multisystem complications and social and economic family and health systems burden. In the present study, we aimed to investigate the genetic risk estimate for MMC in a cohort of 203 Mexican nuclear families with discordant siblings for the defect. Utilizing a custom Illumina array, we analyzed 656 single nucleotide polymorphisms (SNPs) of 395 candidate genes to identify a polygenic risk profile for MMC. Through a family-based analysis employing the transmission disequilibrium test (TDT) and Bayesian analysis, we assessed risk alleles transmission and calculated conditional probabilities estimating a polygenic risk for MMC. Our findings reveal significant associations of six genes related to neural tube closure (PSMB4, ATIC, DKK2, PSEN2, C2CD3, and PLCB2), showing differences in risk allele transmission between affected and unaffected siblings. Bayesian analysis identified changes in the risk profile after initiating folic acid fortification in Mexico, showing an evident decline in the conditional risk from 1/156 to 1/304 respectively. Despite the decline, this represents a 5.84-fold increase in risk before fortification and a 2.99-fold increase post-fortification compared to the baseline risk level (1/910). Our study highlights the advantage of incorporating a Bayesian analytical methodology in families with discordant sib-pairs, offering insights into the polygenic risk estimate for MMC and, most probably, for other congenital malformations.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0316378

DOI: 10.1371/journal.pone.0316378

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