Observational epidemiological studies indicate that maternal height is associated with gestational age at birth and fetal growth measures (i.e., shorter mothers deliver infants at earlier gestational ages with lower birth weight and birth length). Different mechanisms have been postulated to explain these associations. This study aimed to investigate the casual relationships behind the strong association of maternal height with fetal growth measures (i.e., birth length and birth weight) and gestational age by a Mendelian randomization approach. We conducted a Mendelian randomization analysis using phenotype and genome-wide single nucleotide polymorphism (SNP) data of 3,485 mother/infant pairs from birth cohorts collected from three Nordic countries (Finland, Denmark, and Norway). We constructed a genetic score based on 697 SNPs known to be associated with adult height to index maternal height. To avoid confounding due to genetic sharing between mother and infant, we inferred parental transmission of the height-associated SNPs and utilized the haplotype genetic score derived from nontransmitted alleles as a valid genetic instrument for maternal height. In observational analysis, maternal height was significantly associated with birth length (p = 6.31 × 10⁻⁹), birth weight (p = 2.19 × 10⁻¹⁵), and gestational age (p = 1.51 × 10⁻⁷). Our parental-specific haplotype score association analysis revealed that birth length and birth weight were significantly associated with the maternal transmitted haplotype score as well as the paternal transmitted haplotype score. Their association with the maternal nontransmitted haplotype score was far less significant, indicating a major fetal genetic influence on these fetal growth measures. In contrast, gestational age was significantly associated with the nontransmitted haplotype score (p = 0.0424) and demonstrated a significant (p = 0.0234) causal effect of every 1 cm increase in maternal height resulting in ~0.4 more gestational d. Limitations of this study include potential influences in causal inference by biological pleiotropy, assortative mating, and the nonrandom sampling of study subjects. Our results demonstrate that the observed association between maternal height and fetal growth measures (i.e., birth length and birth weight) is mainly defined by fetal genetics. In contrast, the association between maternal height and gestational age is more likely to be causal. In addition, our approach that utilizes the genetic score derived from the nontransmitted maternal haplotype as a genetic instrument is a novel extension to the Mendelian randomization methodology in casual inference between parental phenotype (or exposure) and outcomes in offspring. Soon after the birth of a baby, doting parents send messages to friends and relatives or post information on social media sites to let everyone know when their new baby boy or girl was born. They may also post information about how heavy he/she was at birth and his/her length. These pregnancy outcomes, together with gestational age at birth (the length of time that a baby has spent developing in its mother’s womb), affect the baby’s immediate health and survival. Importantly, however, these pregnancy outcomes are also associated with the risk of long-term adverse health outcomes such as obesity, cardiometabolic disorders (heart disease and conditions such as diabetes that affect how the body makes energy from food), and neuropsychiatric conditions (mental disorders attributable to diseases of the nervous system, such as depression). For example, some studies have shown an association between low birth weight and an increased risk of type 2 diabetes later in life. Identification of the environmental and genetic factors that causally influence gestational age, length, and weight at birth would improve our understanding of why these pregnancy outcomes are associated with disease during adulthood and could help in the design of strategies to prevent these diseases. Epidemiological studies (investigations that examine disease patterns in populations) suggest that, compared to tall mothers, short mothers tend to deliver their babies at earlier gestational ages, with lower birth weights and lengths. Epidemiological studies cannot show, however, whether variations in maternal height cause variations in pregnancy outcomes. Other characteristics shared by tall mothers might actually determine the size and gestational age of their offspring (confounding). Here, the researchers use “Mendelian randomization” to assess the causal effect of maternal height on the size and gestational age at birth of babies. Because gene variants are inherited randomly, they are not prone to confounding. So, if maternal height actually affects gestational age and size at birth, genetic variants (instruments) that affect maternal height should be associated with differences in gestational age and size at birth, provided confounding due to the transmission of parental alleles (variant forms of genes; people have two alleles of every gene, one inherited from each parent) is avoided by adjusting for the baby’s genotype. The researchers used phenotype data (observable characteristics such as maternal height and birth weight of the baby) and single nucleotide polymorphism (SNP; a type of genetic variant) data obtained from 3,486 Nordic mother/baby pairs. Analysis of the phenotype data indicated that maternal height was significantly associated with length, weight, and gestational age at birth (a significant association is unlikely to have arisen by chance). For their Mendelian randomization analysis, the researchers constructed a genetic score based on 697 SNPs known to be associated with adult height. To avoid confounding due to genetic sharing between the mother and baby, they determined which of the height-associated alleles each baby had inherited from its mother and used the nontransmitted haplotype score as a genetic instrument for maternal height (a haplotype is a set of DNA variations that are inherited together). Birth length and weight were significantly associated with both the maternal and paternal transmitted haplotype scores but not with the maternal nontransmitted haplotype score. However, gestational age was significantly but modestly associated with the maternal nontransmitted haplotype score. The validity of the assumptions that underlie the Mendelian randomization approach and the design of the studies supplying the data for this analysis may affect the accuracy of the findings reported here. Nevertheless, these findings suggest that the observed association between maternal height and fetal growth measurements is mainly determined by the genetics of the baby. That is, differences in maternal height do not cause differences in birth weight or length. Rather, some of the gene variants that the baby inherits from its mother determine both its size and its mother’s height. These findings also provide weak evidence that the association between maternal height and gestational age is causal. Maternal height might, for example, causally influence gestational age by limiting the space available for the baby’s growth before birth. Finally, these findings introduce an extension to the Mendelian randomization approach that can be used to investigate causal associations between parental characteristics and offspring outcomes. 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Enhancing pregnancy health is known to improve the mother’s and offspring’s life-long well-being. The maternal environment, encompassing genetic factors, impacts of social determinants, the nutritional/metabolic milieu, and infections and inflammation, have immediate consequences for the in utero development of the fetus and long-term programming into childhood and adulthood. Moreover, adverse pregnancy outcomes such as preterm birth or preeclampsia, often attributed to the maternal environmental factors listed above, have been associated with poor maternal cardiometabolic health after pregnancy. In this BMC Medicine article collection, we explore a broad spectrum of maternal characteristics across pregnancy and postnatal phenotypes, anticipating substantial cross-fertilization of new understanding and shared mechanisms around diverse outcomes. Advances in the ability to leverage ‘omics across different platforms (genome, transcriptome, proteome, metabolome, microbiome, lipidome), large high-dimensional population databases, and unique cohorts are generating exciting new insights: The first articles in this collection highlight the role of placental biomarkers of preterm birth, metabolic influences on fetal and childhood growth, and the impact of common pre-existing maternal disorders, obesity and smoking on pregnancy outcomes, and the child’s health. As the collection grows, we look forward to seeing the connections emerge across maternal, fetal, and childhood outcomes that will foster new insights and preventative strategies for women.

Preterm birth (delivery at less than 37 weeks of gestation) is the leading cause of infant mortality worldwide. So far, the application of animal models to understand human birth timing has not substantially revealed mechanisms that could be used to prevent prematurity. However, with amassing data implicating an important role for genetics in the timing of the onset of human labor, the use of modern genomic approaches, such as genome-wide association studies, rare variant analyses using whole-exome or genome sequencing, and family-based designs, holds enormous potential. Although some progress has been made in the search for causative genes and variants associated with preterm birth, the major genetic determinants remain to be identified. Here, we review insights from and limitations of animal models for understanding the physiology of parturition, recent human genetic and genomic studies to identify genes involved in preterm birth, and emerging areas that are likely to be informative in future investigations. Further advances in understanding fundamental mechanisms, and the development of preventative measures, will depend upon the acquisition of greater numbers of carefully phenotyped pregnancies, large-scale informatics approaches combining genomic information with information on environmental exposures, and new conceptual models for studying the interaction between the maternal and fetal genomes to personalize therapies for mothers and infants. Information emerging from these advances will help us to identify new biomarkers for earlier detection of preterm labor, develop more effective therapeutic agents, and/or promote prophylactic measures even before conception.

The glucocorticoid receptor (GR) regulates hypothalamic-pituitary-adrenal (HPA) axis activity during the stress response. The paraventricular nucleus (PVN) is a major site of negative feedback to coordinate the degree of the HPA axis activity with the magnitude of the exposed stressor. To define the function of endogenous PVN GR, we used Cre-loxP technology to disrupt different GR exons in Sim1-expressing neurons of the hypothalamus. GR exon 2-deleted mice (Sim1Cre-GRe2Δ) demonstrated 43% loss of PVN GR compared with an 87% GR loss in exon 3-deleted mice (Sim1Cre-GRe3Δ). Sim1Cre-GRe3Δ mice display stunted growth at birth but develop obesity in adulthood and display impaired stress-induced glucose release. We observed elevated basal and stress-induced corticosterone levels in Sim1Cre-GRe3Δ mice, compared with control and Sim1Cre-GRe2Δ mice, and impaired dexamethasone suppression, indicating an inability to negatively regulate corticosterone secretion. Sim1Cre-GRe3Δ mice also showed increased CRH mRNA in the PVN, increased basal plasma ACTH levels, and reduced locomotor behavior. We observed no differences in Sim1Cre-GRe2Δ mice compared with control mice in any measure. Our behavioral data suggest that GR deletion in Sim1-expressing neurons has no effect on anxiety or despair-like behavior under basal conditions. We conclude that loss of PVN GR results in severe HPA axis hyperactivity and Cushing's syndrome-like phenotype but does not affect anxiety and despair-like behaviors.

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P = 3.96 × 10⁻¹⁴). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.