Abstract
Birth weight is a common measure of fetal growth that is associated with a range of health outcomes. It is directly affected by the fetal genome and indirectly by the maternal genome. We performed genome-wide association studies on birth weight in the genomes of the child and parents and further analyzed birth length and ponderal index, yielding a total of 243 fetal growth variants. We clustered those variants based on the effects of transmitted and nontransmitted alleles on birth weight. Out of 141 clustered variants, 22 were consistent with parent-of-origin-specific effects. We further used haplotype-specific polygenic risk scores to directly test the relationship between adult traits and birth weight. Our results indicate that the maternal genome contributes to increased birth weight through blood-glucose-raising alleles while blood-pressure-raising alleles reduce birth weight largely through the fetal genome.
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Data availability
The GWAS summary statistics from this study have been deposited at deCODE genetics (https://www.decode.com/summarydata/). Publicly available datasets used in this study were EGG Consortium datasets: http://mccarthy.well.ox.ac.uk/publications/2019/EggBirthWeight_NatureGenetics/Fetal_BW_European_meta.NG2019.txt.gz, http://mccarthy.well.ox.ac.uk/publications/2019/EggBirthWeight_NatureGenetics/Maternal_BW_European_meta.NG2019.txt.gz and https://egg-consortium.org/downloads/EGG-GWAS-BL.txt.gz. Other data generated or analyzed during this study are included in this article and Supplementary Tables 1–12.
Code availability
Custom code has been uploaded to the following GitHub repository: https://github.com/birthw/code.
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Acknowledgements
We thank the participants of this study and the investigators of the FinnGen study. Part of this work was conducted using the UKBB resource (application no. 56270).
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Contributions
T.J., V.S., H.H., D.F.G., G. Thorleifsson, U.T. and K.S. designed the study and interpreted the results. V.S., A.H., G. Thorgeirsson, R.B., E.L.S., D.O.A., T.S. and I.J. carried out participant ascertainment and recruitment. T.J., V.S., L.S., G.S., E.V.I., R.B.T., J.K.S., V.T., K.E.H., M.L.F., D.F.G. and G. Thorleifsson performed the statistical and bioinformatics analyses. T.J., V.S., U.T. and K.S. drafted the manuscript. All authors contributed to the final version of the manuscript.
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T.J., V.S., L.S., G.S., E.V.I., R.B.T., J.K.S., V.T., K.E.H., A.H., M.L.F., G. Thorgeirsson, D.O.A., I.J., H.H., D.F.G., G. Thorleifsson, U.T. and K.S. are affiliated with deCODE Genetics/Amgen and declare competing interests as employees. The other authors declare no competing interests.
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Peer review information Nature Genetics thanks Rachel Freathy and David Evans for their contribution to the peer review of this work.
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Extended data
Extended Data Fig. 1 Birth weight, offspring birth weight mothers and gestational age.
a,b, Effect estimates for fetal growth variants for gestational age vs. birth weight(adj for gestational age) in the Icelandic fetal (a) and maternal (b) GWAS analysis. Error bars shown for sequence variants with P < 5.1 × 10−4 in the corresponding birth weight analysis represent 95% CI. Effect estimates for gestational age were obtained by linear regression of gestational age against fetal growth variants in the Icelandic data. Effects are shown for the birth weight increasing allele based on the Icelandic fetal and maternal data, respectively. c,d, P-values for the fetal growth variants for the birth weight and birth weight mothers analysis with and without adjusting for gestational age. The log10 P-values of birth weight with and without adjusting for gestational age in the Icelandic fetal GWAS data (n = 125,541) (c). The log10 P-values of birth weight with and without adjusting for gestational age in the Icelandic maternal GWAS data (n = 59,735) (d). The name of the nearest gene is shown in black if P < 5 × 10−8. Note that for the COL27A1 variant the birth weight increasing allele in the Icelandic data differs from the one in the birth weight meta-analysis. The dashed grey line represents results from a simple linear regression using MAF (1 - MAF) as weights and the solid grey line indicates the reference line with slope = 1. GA, gestational age; BW, birth weight; OS, offspring.
Extended Data Fig. 2 Sequence variants associating with birth length and their effects on birth weight and birth length.
The figure shows effect estimates for birth weight and birth length, from linear regression of trait values on genotype counts, for sequence variants associating with birth length. Error bars, shown for sequence variants with P < 5.1 × 10−4, represent 95% confidence intervals for the estimates. Only one of the 10 birth length variants (within MTRMR11) does not also associate with birth weight. Effects are shown for the birth length increasing allele based on the birth length meta-analysis (n = 154,000). Variants are labelled with their nearest gene. The dashed grey line represents results from a simple linear regression using MAF (1 - MAF) as weights and the solid grey line indicates the reference line with slope = 1.
Extended Data Fig. 3 Discovery of 243 fetal growth variants in five fetal growth analyses.
Variants from the five sets of analyses (birth weight, birth length, ponderal index of the child’s genomes and offspring birth weight of the maternal and paternal genomes) were combined into one set of fetal growth variants. Variants were considered to belong to the same locus if they were within 500 kb apart and in linkage disequilibrium (LD) with r2 ≥ 0.1. Only one variant (near EPAS1) was identified in all five analyses, and one variant (near LINC00880) was identified in all sets apart from birth length.
Extended Data Fig. 4 Mode of action of rs10814916 in GLIS3.
The paternal transmitted allele is indicated in blue and non-transmitted paternal allele in cyan, and the maternal transmitted allele in red and maternal non-transmitted allele pink. The data is shown as effect of each allele on birth weight (in SD), with 95% CI, on the y-axes for the transmitted alleles and maternally non-transmitted allele. The effects are estimated jointly using maximum likelihood estimations on 104,920 parent-offspring trios. Effects are shown for rs10814916-A.
Extended Data Fig. 5 Heatmap displaying effects of variants associating with birth weight and cardiovascular traits arranged by mode of transmission clusters.
Variants associating with any of the three cardiovascular traits (SBP, hypertension or CAD) with P < 2.1 × 10−4 (0.05/number of independent variants (n = 243)) and a defined mode of transmission are shown. The effects, log(OR) or beta, were obtained from logistic or linear regression, respectively, of case/control status or trait values on genotype count of the sequence variant. The colors represent the effects of the 26 variants associating with the traits shown on the y-axis, with red indicative of a positive effect and blue of a negative effect. Effects are shown for the SBP increasing allele and variants are ordered first by their mode of transmission cluster classification and then by their effect on SBP. The effect is shown if the associating P-value is below 0.05. A filled circle represents P < 1 × 10−8 and an open circle P < 1 × 10−6. Transmission clusters: M, maternal effect; FM, fetal and maternal effect; FMN, no effect of the maternally transmitted allele; fM, fetal and maternal, with stronger maternal effect; Fm, fetal and maternal, with stronger fetal effect; PatT, paternally transmitted only effect; MatT, maternally transmitted only effect; F, fetal effect, independent of parent-of-origin. Birth weight (BW) phenotypes: BW mother and BW represent the corresponding meta-analyses, BWPT (paternally transmitted), BWMT (maternally transmitted) and BWMNT (maternally non-transmitted) are based on allele specific BW GWAS of Icelandic individuals and BWchild represents the Icelandic BW GWAS data. Abbreviations: SD, same direction; OD, opposite direction.
Extended Data Fig. 6 Heatmap displaying the effects of PRSs for adult cardio-metabolic traits on fetal growth traits by different transmission modes.
Effects are shown if P < 0.05, with positive associations represented in red and negative associations in blue. The P values and effects are from a linear regression of fetal trait values on PRS’s, adjusting for year of birth, gender and principal components. PRS for cardiovascular (CAD, hypertension and SBP), glycemic (T2D, HbA1c and glucose) and anthropometric (height, BMI and WHRadjBMI) traits were generated based on GWAS data from UK Biobank data for genotyped Icelandic individuals, and tested against the Icelandic fetal growth phenotypes. PRS for the transmitted and non-transmitted maternal (MT and MNT) and paternal (PT and PNT) alleles were tested separately using genotyped individuals only while Mother, Child and Father are based on the entire corresponding Icelandic GWAS data. The PRS were tested against birth weight, birth length, ponderal index, gestational age, as well as birth weight not adjusted for gestational age (BWunadjusted) and birth weight adjusted for birth length (BWadjBL).
Extended Data Fig. 7 Heatmap displaying effects of variants associating with birth weight and anthropometric traits arranged by mode of transmission clusters.
Variants associating with any of the three anthropometric traits (height, WHRadjBMI or BMI) with a P < 2.1 × 10−4 (0.05/number of independent variants (n = 243)) and a defined mode of transmission are shown. The effects, log(OR) or beta, were obtained from logistic or linear regression, respectively, of case/control status or trait values on genotype count of the sequence variant. The colors represent the effects of the 83 variants associating with the traits shown on the y-axis, with red indicative of a positive effect and blue of a negative effect. Effects are shown for the height increasing allele and variants are ordered first by their mode of transmission cluster classification and then by their effect on height. The effect is shown if the associating P-value is below 0.05. A filled circle represents P < 1 × 10−8 and an open circle P < 1 × 10−6. Transmission clusters: M, maternal effect; FM, fetal and maternal effect; FMN, no effect of the maternally transmitted allele; fM, fetal and maternal, with stronger maternal effect; Fm, fetal and maternal, with stronger fetal effect; PatT, paternally transmitted only effect; MatT, maternally transmitted only effect; F, fetal effect, independent of parent-of-origin. Birth weight (BW) phenotypes: BW mother and BW represent the corresponding meta-analyses, BWPT (paternally transmitted), BWMT (maternally transmitted) and BWMNT (maternally non-transmitted) are based on allele specific BW GWAS of Icelandic individuals and BWchild represents the Icelandic BW GWAS data. Abbreviations: SD, same direction; OD, opposite direction.
Extended Data Fig. 8 Cluster probability as a function of strength of association.
The figure shows the maximum probability that a sequence variant belongs to a specific cluster compared to the maximum Z-score for the association of the paternally and maternally transmitted and maternally non-transmitted alleles with birth weight.
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Juliusdottir, T., Steinthorsdottir, V., Stefansdottir, L. et al. Distinction between the effects of parental and fetal genomes on fetal growth. Nat Genet 53, 1135–1142 (2021). https://doi.org/10.1038/s41588-021-00896-x
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DOI: https://doi.org/10.1038/s41588-021-00896-x
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