The basic tenet of developmental origins of health and disease (DOHaD) research is that perinatal health behaviours of the mother and father, as well as those of the child in early life, can have a significant impact on the future health of the child and that of subsequent generations. Studies exploring DOHaD investigate how early life exposures increase susceptibility to later adverse health outcomes from medical and public health perspectives. This altered health risk appears to occur through reprogramming of physiological systems away from their normal developmental trajectories, and highlights the plasticity of organ systems in the perinatal periods.1 Recent research in this field has focused on the potential for these physiological changes to exert trans-generational effects, without the requirement for further exposures in subsequent generations.2 This appears to occur through genetic and environmental interactions, resulting in phenotypic changes that persist across generations.

The emergence of “-omics” biotechnologies (eg, genomics, proteomics and metabolomics) has revolutionised physiological research in the DOHaD field. From the genome to the epigenome, microbiome and metabolome, research investigating pathways leading to disease has never before had the technology to investigate physiology in such a high throughput, data-rich capacity. We summarise this emerging research capability and its application in DOHaD studies to explain how environmental and social factors, such as diet, stress and exposure to toxins, affect our physiology and become inherited, leaving a legacy of disease susceptibility for future generations.

The epigenome

The epigenome refers to changes made to the genome that result in altered transcriptional activity in the absence of DNA sequence alterations. This highly dynamic process, occurring in response to several external factors, is stably maintained and endures over multiple generations. Epigenetic mechanisms regulating gene expression, including DNA methylation, histone modifications and the actions of small non-coding RNAs, each contribute to tissue-specific gene expression and an altered cellular phenotype. The introduction of efficient sequencing and microarray techniques has facilitated the study of these epigenetic mechanisms.

The interaction between epigenetic inheritance and environmental exposures has been recognised as an important determinant of phenotypic outcomes for offspring.1 Exposures of the mother can result in epigenetic modifications in the developing fetus and the germline.3 Such transmission is not restricted to maternal exposures, and recent evidence shows that epigenetic modifications are also inheritable down the paternal line.4 Specifically, a murine model of paternal obesity has shown altered methylation and microRNA profiles,4 which highlights the role of the father’s contribution to inheritable disease susceptibility. Further, data from the Överkalix Swedish tri-generation population study have shown that the mortality risk ratio of grandchildren was associated with the food supply available to their same-sex paternal grandparent.5 Whether an epigenetic mode of inheritance can contribute to such human outcomes is as yet unknown, but is expected, given the strong parallels observed between animal and human trans-generational studies. Single-generation epigenetic effects have been seen in humans, eg, maternal depression in the third trimester of pregnancy is associated with increased methylation of the NR3C1 gene in cord blood mononuclear cells, in conjunction with altered stress responses in the infants at 3 months of age.6 Increased methylation of this same gene was found in the brain tissue of adolescents with a history of child abuse who later committed suicide,7 and in lymphocytes of 11–21-year-olds after childhood maltreatment, and is associated with poor psychological health.8 Together, these studies suggest that early epigenetic modifications may increase vulnerability to poor long-term health in humans. Recognition of epigenetic mechanisms that contribute to poor outcomes may contribute to interventions to reverse these effects. For example, rat offspring exposed to low maternal grooming behaviour have increased DNA methylation of the hippocampal glucocorticoid receptor gene, which is reversed by increased care provision in early postnatal life.9 Similar epiphenotypes are observed in infant saliva, when high tactile stimulation of the infant in the postnatal period normalises glucocorticoid receptor hypermethylation induced by maternal depression.10

The microbiome

The human microbiome is the collection of microorganisms that inhabit the human body, including commensal and symbiotic microbes. The study of the microbiome and its role in disease onset has been made possible by the introduction of large-scale sequencing techniques and gene expression arrays. These techniques have increased our ability to understand the contribution of the maternal microbiome to disease in subsequent generations. For example, altered bacterial colonisation of the alimentary tract of piglets, after antibiotic and stress exposure in early life, has been associated with immune development perturbations.11 This may have particular implications for preterm children, for whom exposure to antibiotics and stress is common in early life. Already, preliminary studies of the microbiome in preterm twins have shown that an altered pattern of microbial gut colonisation precedes the development of necrotising enterocolitis.12 In humans, obesity,13 smoking14 and different modes of delivery (eg, vaginal versus caesarean)15 are common potential prenatal factors that can influence maternal and neonatal microbiomes. An altered microbiome can also contribute to epigenetic changes.16

The metabolome

The metabolome is the complete set of metabolites (compounds of low molecular mass found in biological samples) that regulate cell and tissue growth, development, survival, maintenance and responses to the environment. The potential for metabolomic profiling to provide a phenotypic signature of pathophysiology has been recognised.17 Methods to assess the metabolome rely on high-resolution analytics, including mass spectrometry, nuclear magnetic resonance spectrometry and Fourier transform infrared spectroscopy. Unlike the epigenome and the microbiome, the metabolome can be highly dynamic and is able to change in short time frames, ranging from seconds to minutes. The choice of sampling material is therefore an important consideration and a challenge. The decision on sampling material will be specific to the research question and critical to the interpretation of results. For example, blood samples reflect highly dynamic responses, but hair samples reflect prolonged exposure and can therefore provide a more stable phenotype.18 The large volume of data generated by such techniques can provide insight into interactions between metabolites, genes, transcripts and proteins.19 These data can be highly informative about mechanisms leading to disease and the impact of environmental exposures on system physiology, such as the developmental impact of prenatal exposure to the endocrine disruptor, bisphenol A.20

The potential for metabolomics platforms to be used to identify biomarkers predicting pregnancy outcome is already becoming apparent. These platforms include observations of differences in the neonatal blood metabolome across gestational ages (differences that are dependent on postnatal age at sampling21) and specific pathology and illness severity;22 a study linking the maternal hair metabolome with fetal growth restriction;18 and an ongoing prospective study for early prediction of pre-eclampsia23 (trial NCT01891240).

Challenges to -omics approaches in DOHaD research

Use of these emerging biotechnological approaches in DOHaD research shows clear promise in expanding our current knowledge of mechanisms driving intergenerational transmission of disease and heightened disease susceptibility in individuals after specific exposures in early development. While such large volumes of biological data using these -omics approaches provides enormous opportunity, some challenges remain in their application and interpretation. The first challenge relates to identifying the appropriate time for tissue sampling, given the current limited use of these approaches in this field. Healthy ranges are also yet to be established, a limitation that occurs with any advance in technology and will be overcome through public sharing of data. To establish healthy ranges, sampling from multiple time points and multiple tissues will be necessary. This information will benefit the design of future studies, in which sampling can then occur at a single time point during tissue-specific sensitive periods to yield the most reliable, valid and interpretable data. The establishment of normative ranges will also help elucidate many other current unknowns in this area, including understanding what sample sizes are needed to identify meaningful effects; understanding and predicting the stability of -omics profiles; identifying the effects of a “second hit” or multiple exposures; understanding whether the duration or timing of each exposure is important in determining outcome; and understanding whether a genetic susceptibility is needed for the intergenerational transmission of poor outcomes or whether this is a highly conserved process.

Once we have identified biomarkers or signatures predictive of poor maternal, fetal or neonatal outcomes, the next critical step is to use this information to identify how to normalise these effects. This will necessitate an understanding of how postnatal factors normalise or exacerbate the -omics profile induced by the early life environment. Longitudinal studies of twins have provided some preliminary evidence of environmental influences, exploring the stability of the epigenome across the first 18 months of life and the degree of epigenetic discordance between siblings with a shared genetic and environmental background.24 Continued longitudinal assessments of these children will increase our understanding of the role of the environment on the epigenome through life. The impact of additional exposures in pregnancies of these subsequent generations has also yet to be identified, because few studies have assessed the potential for -omics profiles to be modified beyond the second generation.2

Recommendations for future studies

We highly recommend collaborative studies that integrate data derived from multiple platforms, collected from samples throughout early development and linked to clinical health outcomes. Analysis of samples from current and planned randomised controlled trials will allow the effects of standard care and interventions to be assessed concurrently. These studies will facilitate our understanding of disease susceptibility, onset and progression to a degree that has not previously been possible.

Implications for policy and practice

Effective interventions applied at critical periods of development can substantially reduce future disease burden. The potential for this research to be translated into tangible health benefits for child health and future generations is therefore enormous, aligning with the growing demands of national health regulatory bodies to focus efforts on preventative health care. The outcomes of this research could then potentially be used by health advocates to improve policy and practice, by clinicians and health workers to promote and support healthy perinatal behaviours, and be communicated to the wider community to optimise future child health.

Information on DOHaD and early life healthy behaviours is becoming more readily available, but it is unclear whether this is being effectively communicated to the health care providers who need it most, that is, those in direct contact with women who are pregnant or planning a pregnancy. For example, surveys of general practitioners reveal that they have limited knowledge of nutritional requirements in pregnancy, and also feel uncomfortable providing this information to women due to a lack of confidence.25 Knowledge gaps such as this must be urgently addressed to optimise the health of future populations. Similarly, while the internet is teeming with websites offering advice for pregnant and breastfeeding women, these often contain inaccurate or misleading advice and conflicting information. Evidence-based online resources to which women can be directed for accurate health information are needed.