Preterm birth is a universal health problem that is one of the largest unmet medical needs contributing to the global burden of disease. Adding to its complexity is that there are no means to predict who is at risk when pregnancy begins or when women will actually deliver. Until these problems are addressed, there will be no interventions to reduce the risk because those who should be treated will not be known. Considerable evidence now exists that chronic life, generational or accumulated stress is a risk factor for preterm delivery in animal models and in women. This wear and tear on the body and mind is called allostatic load. This review explores the evidence that chronic stress contributes to preterm birth and other adverse pregnancy outcomes in animal and human studies. It explores how allostatic load can be used to, firstly, model stress and preterm birth in animal models and, secondly, how it can be used to develop a predictive model to assess relative risk among women in early pregnancy. Once care providers know who is in the highest risk group, interventions can be developed and applied to mitigate their risk.
Maternal smoking during pregnancy is associated with low birth weight. Common variation
at rs1051730 is robustly associated with smoking quantity and was recently shown to
influence smoking cessation during pregnancy, but its influence on birth weight is not
clear. We aimed to investigate the association between this variant and birth weight of
term, singleton offspring in a well-powered meta-analysis. We stratified 26 241 European
origin study participants by smoking status (women who smoked during pregnancy versus
women who did not smoke during pregnancy) and, in each stratum, analysed the association
between maternal rs1051730 genotype and offspring birth weight. There was evidence of
interaction between genotype and smoking (P = 0.007). In women who
smoked during pregnancy, each additional smoking-related T-allele was associated with a 20
g [95% confidence interval (95% CI): 4–36 g] lower birth weight
(P = 0.014). However, in women who did not smoke during
pregnancy, the effect size estimate was 5 g per T-allele (95% CI:
−4 to 14 g; P = 0.268). To conclude, smoking status
during pregnancy modifies the association between maternal rs1051730 genotype and
offspring birth weight. This strengthens the evidence that smoking during pregnancy is
causally related to lower offspring birth weight and suggests that population
interventions that effectively reduce smoking in pregnant women would result in a reduced
prevalence of low birth weight.
Longitudinal cohort studies are ideal for investigating how epigenetic patterns change over time and relate to changing exposure patterns and the development of disease. We highlight the challenges and opportunities in this approach.
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