| Title: | Partitioning genetic effects on birthweight at classical human leukocyte antigen loci into maternal and fetal components, using structural equation modelling |
| Journal: | International Journal of Epidemiology |
| Published: | 13 Oct 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37831898/ |
| DOI: | https://doi.org/10.1093/ije/dyad142 |
| URL: | https://academic.oup.com/ije/advance-article-pdf/doi/10.1093/ije/dyad142/52089503/dyad142.pdf |
Publication 9383
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Abstract
BACKGROUND: Single nucleotide polymorphisms in the human leukocyte antigen (HLA) region in both maternal and fetal genomes have been robustly associated with birthweight (BW) in previous genetic association studies. However, no study to date has partitioned the association between BW and classical HLA alleles into maternal and fetal components.</p>
METHODS: We used structural equation modelling (SEM) to estimate the maternal and fetal effects of classical HLA alleles on BW. Our SEM leverages the data structure of the UK Biobank (UKB), which includes ∼270 000 participants' own BW and/or the BW of their firstborn child.</p>
RESULTS: We show via simulation that our model yields asymptotically unbiased estimates of the maternal and fetal allelic effects on BW and appropriate type I error rates, in contrast to simple regression models. Asymptotic power calculations show that we have sufficient power to detect moderate-sized maternal or fetal allelic effects of common HLA alleles on BW in the UKB. Applying our SEM to imputed classical HLA alleles and own and offspring BW from the UKB replicated the previously reported association at the HLA-C locus and revealed strong evidence for maternal (HLA-A*03:01, B*35:01, B*39:06, P <0.001) and fetal allelic effects (HLA-B*39:06, P <0.001) of non-HLA-C alleles on BW.</p>
CONCLUSIONS: Our model yields asymptotically unbiased estimates, appropriate type I error rates and appreciable power to estimate maternal and fetal effects on BW. These novel allelic associations between BW and classical HLA alleles provide insight into the immunogenetics of fetal growth in utero.</p>
3 Authors
- Geng Wang
- Nicole M Warrington
- David M Evans
1 Application
| Application ID | Title |
|---|---|
| 53641 | Determining the genetic and environmental aetiology of complex traits and diseases using existing and novel statistical methodologies |
Enabling scientific discoveries that improve human health