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Haplotype-based analysis distinguishes maternal-fetal genetic contribution to pregnancy-related outcomes

Author

Listed:
  • Amit K Srivastava
  • Julius Juodakis
  • Pol Sole-Navais
  • Jing Chen
  • Jonas Bacelis
  • Kari Teramo
  • Mikko Hallman
  • Pal R Njølstad
  • David M Evans
  • Bo Jacobsson
  • Louis J Muglia
  • Ge Zhang

Abstract

Genotype-based approaches for the estimation of SNP-based narrow-sense heritability (h^2) have limited utility in pregnancy-related outcomes due to confounding by the shared alleles between mother and child. Here, we propose a haplotype-based approach to estimate the genetic variance attributable to three haplotypes - maternal transmitted (h^m12), maternal non-transmitted (h^m22) and paternal transmitted (h^p12) in mother-child pairs. We show through extensive simulations that our haplotype-based approach outperforms the conventional and contemporary approaches for resolving the contribution of maternal and fetal effects, particularly when m1 and p1 have different effects in the offspring. We apply this approach to estimate the explicit and relative maternal-fetal genetic contribution to the phenotypic variance of gestational duration and gestational duration-adjusted fetal size measurements at birth in 10,375 mother-child pairs. The results reveal that variance of gestational duration is mainly attributable to m1 and m2 (h^m12=17.3%,S.E.=5.2%;h^m22=12.2%,S.E.=5.2%;h^p12=0.0%,S.E.=5.0%). In contrast, variance of fetal size measurements at birth are mainly attributable to m1 and p1 (h^m12=18.6−36.4%,h^m22=0.0−5.2% and h^p12=4.4−13.6%). Our results suggest that gestational duration and fetal size measurements are primarily genetically determined by the maternal and fetal genomes, respectively. In addition, a greater contribution of m1 as compared to m2 and p1 (h^m12−h^m22−h^p12>0) to birth length and head circumference suggests a substantial influence of correlated maternal-fetal genetic effects on these traits. Our newly developed approach provides a direct and robust alternative for resolving explicit maternal and fetal genetic contributions to the phenotypic variance of pregnancy-related outcomes.Author summary: Unlike other complex traits, pregnancy-related outcomes are influenced by both the maternal and fetal genotypes. Conventional genotype-based approaches considering individuals as an analytical unit, therefore, suffer from a bias due to confounding of the shared alleles between the mother and child. We present a unique haplotype-based approach considering mother-child pairs as a single analytical unit with maternal transmitted (m1), maternal non-transmitted (m2), and paternal transmitted (p1) haplotypes. Maternal transmitted haplotypes influence pregnancy-related outcomes through both the mother and child whereas maternal non-transmitted and paternal transmitted haplotypes influence pregnancy-related outcomes only through mother and child, respectively. Using extensive simulations, we show that our haplotype-based approach outperforms the conventional GCTA and contemporary M-GCTA approach for resolving maternal and fetal genetic contributions to pregnancy-related outcomes, particularly in the presence of parent-of-origin effects (POEs). We implement our newly developed approach to estimate the explicit and relative maternal-fetal genetic contributions to the phenotypic variance of gestational duration and gestational duration-adjusted fetal size measurements at birth in 10,375 mother-child pairs. Our results reveal that gestational duration and birth weight are primarily influenced by maternal and fetal genomes, respectively whereas birth length and head circumference have substantial influence of correlated maternal-fetal genetic effects or POEs.

Suggested Citation

  • Amit K Srivastava & Julius Juodakis & Pol Sole-Navais & Jing Chen & Jonas Bacelis & Kari Teramo & Mikko Hallman & Pal R Njølstad & David M Evans & Bo Jacobsson & Louis J Muglia & Ge Zhang, 2025. "Haplotype-based analysis distinguishes maternal-fetal genetic contribution to pregnancy-related outcomes," PLOS Genetics, Public Library of Science, vol. 21(3), pages 1-33, March.
  • Handle: RePEc:plo:pgen00:1011575
    DOI: 10.1371/journal.pgen.1011575
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