Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Abstract

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Figure 1. Structural equation modelling (SEM)-adjusted fetal and maternal effects for the 193 lead SNPs that were identified in the GWAS of either own birth weight (left panel) or offspring birth weight (right panel) with minor allele frequency greater than 5%.

The SEM included 85,518 individuals from the UK Biobank with both their own and offspring’s birth weight, 178,980 and 93,842 individuals from the UK Biobank and the EGG consortium with only their own birth weight or offspring’s birth weight respectively. The colour of each point indicates the SEM-adjusted fetal effect on own birth weight association P-value and the shape of each point indicates the SEM-adjusted maternal effect on offspring birth weight association P-value. P-values for the fetal and maternal effect were calculated using a two-sided Wald test. SNPs which are labelled with the name of the closest gene are those which were identified in the GWAS of own birth weight but whose effects are mediated through the maternal genome (left panel) and SNPs that were identified in the GWAS of offspring birth weight but whose effects are mediated through the fetal genome (right panel). SNPs are aligned to the birth weight increasing allele from the GWAS.

Figure 2. Genome-wide genetic correlation between birth weight and a range of traits and diseases in later life.

Genetic correlation (r_g) and corresponding 95% confidence intervals between birth weight and the traits were estimated using linkage disequilibrium (LD) score regression in LD Hub. Genetic correlations were estimated from the summary statistics of the weighted linear model (WLM)-adjusted fetal genome-wide association study (GWAS; WLM-adjusted fetal effect on own birth weight) and the WLM-adjusted maternal GWAS (WLM-adjusted maternal effect on offspring birth weight). The total sample size included in the WLM-adjusted GWAS is 406,063 individuals with their own and/or their offspring’s birth weight. The genetic correlation estimates are colour coded according to their intensity and direction (red for positive correlation and blue for negative correlation). HOMA-B/IR, homeostasis model assessment of beta-cell function/insulin resistance; HbA1c, hemoglobin A1c; ADHD, attention deficit hyperactivity disorder. See Supplementary Table 10 for the references for each of the traits and diseases displayed and the genetic correlation results for other traits and diseases.

Figure 3. Mendelian randomization (MR) to assess the causal effect of maternal intrauterine exposures on offspring birth weight (adapted from Lawlor et al. 44)

a. Since maternal and fetal genotypes are correlated, it is essential to account for offspring genotype in this analysis. The continuous, thin arrow represents the relationship between the genetic instrument and intrauterine exposure. The dashed arrows represent potential confounding via maternal characteristics which, under MR assumptions, are not associated with the genetic instrument. The dotted arrows represent potential violation of MR assumptions via offspring genotype. The thick arrow represents the causal effect of interest. b. Higher offspring birth weight is caused by direct fetal genetic effects of height-raising alleles and indirect effects of maternal height-raising alleles. Maternal indirect effects of height-raising alleles may increase offspring birth weight by increasing the space available for growth, but we cannot rule out alternative explanations e.g. assortative mating. c. Higher maternal fasting glucose levels increase offspring birth weight. Conversely, direct fetal genetic effects of glucose-raising alleles reduce birth weight. This is likely due to their effects on insulin: variants that lower maternal insulin levels increase maternal glucose, which crosses the placenta and stimulates fetal insulin-mediated growth. However, the same variants in the fetus cause lower fetal insulin levels, and consequently, reduced fetal insulin-mediated growth. d. Higher maternal SBP is causally associated with lower offspring birth weight. After adjusting for maternal effects, there was no evidence of an effect of offspring’s own SBP genetic score on their own birth weight. SEP, socio-economic position; BW, birth weight; FPG, fasting plasma glucose; SBP, systolic blood pressure. 1 SD of BW = 484g,

Figure 4. Mendelian randomization (MR) to assess the causal effect of intrauterine growth on offspring adult outcomes, using maternal intrauterine exposures that influence fetal growth.

a. Maternal genotype should be associated with offspring birth weight independently of offspring genotype, so it is essential to adjust the analysis for offspring genotype. The continuous, thin, arrow represents the relationship between the genetic instrument and intrauterine exposure. The long-dashed arrows denote the (maternal and possibly fetal) genotype associations with birth weight; these arrows highlight the assumption that genetic variation influences offspring adult outcome via intrauterine growth, not birth weight. The short-dashed arrows represent potential confounding via maternal and offspring characteristics. The dotted arrow represents potential violation of assumptions of the MR analysis via offspring genotype. The thick arrow represents the causal effect of interest. We have not estimated the size of the causal effect as we do not have effect estimates for the SNP-maternal intrauterine exposures influencing fetal growth. However, we have used the presence/absence and direction of association in 3,886 mother-offspring pairs to indicate whether the intrauterine environment causes changes in adult offspring SBP (see Supplementary Table 18 for full results). b. Our results demonstrate that the observed negative correlation between birth weight and later SBP may be driven by the causal effect of higher maternal SBP on lower offspring birth weight (red arrow), in combination with the subsequent transmission of SBP-associated alleles to offspring (blue arrow), which then increase offspring SBP, rather than by long-term developmental compensations to adverse intrauterine conditions. SEP, socio-economic position; BW, birth weight; SBP, systolic blood pressure.