Associations between body size, nutrition and socioeconomic position in early life and the epigenome: A systematic review

Background Body size, nutrition and socioeconomic position (SEP) in early life have been associated with a wide range of long-term health effects. Epigenetics is one possible mechanism through which these early life exposures can impact later life health. We conducted a systematic review examining the observational evidence for the impact of body size, nutrition and SEP in early life on the epigenome in humans. Methods This systematic review is registered with the PROSPERO database (registration number: CRD42016050193). Three datasets were simultaneously searched using Ovid and the resulting studies were evaluated by at least two independent reviewers. Studies measuring epigenetic markers either at the same time as, or after, the early life exposure and have a measure of body size, nutrition or SEP in early life (up to 12 years), written in English and from a community-dwelling participants were included. Results We identified 90 eligible studies. Seventeen of these papers examined more than one early life exposure of interest. Fifty six papers examined body size, 37 nutrition and 17 SEP. All of the included papers examined DNA methylation (DNAm) as the epigenetic marker. Overall there was no strong evidence for a consistent association between these early life variables in DNAm which may be due to the heterogeneous study designs, data collection methods and statistical analyses. Conclusions Despite these inconclusive results, the hypothesis that the early life environment can impact DNAm, potentially persisting into adult life, was supported by some studies and warrants further investigation. We provide recommendations for future studies.


Introduction
Substantial evidence from the field of life course epidemiology has supported a relationship between physical and social exposures across the entire life course and later life health [1]. Rapid growth and development that occurs in early life marks a sensitive period during which external factors can influence an individual's later life health [2][3][4] Evidence has accumulated for the importance of nutrition and growth in utero and early postnatal life on a wide range of health and ageing outcomes such as cardiometabolic and bone health [5]. Childhood socioeconomic position (SEP) has also been found to be associated with a wide range of later life health outcomes [6,7].
Exposures in early life must impact the organism in order for their effects to manifest after a long latency period. The biological, behavioural and psychosocial mechanisms linking these earlier life exposures with later life health are complex [1,3]. Epigenetics is one possible mechanism [3,[8][9][10]. Epigenetics refers to processes that regulate gene expression but do not change the underlying DNA sequence. These tissue and cell-specific processes include DNA methylation (DNAm), histone modification, other changes to chromatin structure, and posttranscriptional control [3]. Genetic variation, stochastic events as well as the environment have been shown to influence the epigenome [11]. Since these epigenetic processes can persist during mitosis, it is feasible that early life exposures influencing the epigenome may have a phenotypic manifestation in later life [9].
A number of early life exposures have been investigated in relation to epigenetics. Animal studies have made a convincing case for the role of nutrition during fetal and early neonatal growth on epigenetics [12,13]. DNA or histone methylation in offspring in these studies has been shown to be particularly susceptible to maternal dietary intake of folate, vitamin B6 (pyridoxine), vitamin B12 (cobalamin), vitamin B2 (riboflavin), choline and methionine. These nutrients are involved in one-carbon metabolism, influencing the amount of available S-adenosylmethionine and co-enzymes which are required for methylation [14]. In human studies, participants who were affected by the Dutch Famine provide evidence for the lasting impact of severe caloric restriction during particular periods of gestation [12,15]. The role of nutrition on epigenetics beyond this fetal and early neonatal period is less studied [12]. Growth and body size in early life are related to nutrition, and indeed there is also evidence for predominantly cross-sectional associations between birth weight, childhood and adolescence BMI/obesity, body composition and DNA methylation from human studies [15]. The small number of human studies also suggest a role for early life SEP on DNA methylation [15].
Since this is a relatively new and rapidly developing area of research, most evidence examining the epigenetic effect of these key early life factors have come from animal and exploratory studies incorporating a variety of early life exposures and applying different analytical methods. In 2015 Demetriou et al. conducted a non-systematic review of the evidence for early-life nutrition, SEP and overweight/obesity on DNA methylation [15]. In 2017, Hartwig et al. systematically reviewed the literature of the effects of breastfeeding on DNA methylation [16]. To the best of our knowledge, there has been no comprehensive systematic review of the potential effects of the key early life exposures of nutrition, body size and SEP on epigenetic processes. Therefore, the aim of this study was to systematically review the literature on the association between 1) body size and growth in early life 2) nutrition during pregnancy and early life 3) markers of SEP in early life on epigenetic processes in human studies. This will provide information on the potential for epigenetics to mediate the association between these early life exposures and later life health.

Methods
This systematic review is registered with the PROSPERO database (registration number: CRD42016050193) and the protocol has been published in a peer-review journal [17].

Eligibility criteria
We included studies that tested the association between any measure of (i) body size or growth in early life, (ii) nutrition during pregnancy or early life, or (iii) SEP in early life on epigenetics in human samples. We defined early life as 12 years and under to capture exposures during the pre-adolescent period including prenatal, infancy, early and middle childhood. We considered any indicator of DNAm or histone modification measured in any tissue as an outcome. Early life factors could be prospectively measured or recorded, or retrospectively recalled at later data collections. Eligible measures of body size were weight, height, BMI, and head circumference at birth or any stage in early life or change in any of these measurements. Nutrition included any measure of maternal nutrition, supplement use and/or diet during pregnancy, breastfeeding/ formula, weaning practices and nutrition/diet of the child in early life measured using dietary questionnaires and/or objectively by nutritional biomarkers. Eligible measures of SEP included any recognised indicator of SEP within society, including occupation, education, income, occupational or social class, poverty, and household overcrowding, as defined by Krieger et al. [18].
Reviews, clinical trials, animal studies, studies assessing the effect of adulthood exposures on epigenetic markers and those assessing the epigenetic marker before the early life measure were excluded. Studies in samples with a specific clinical condition were excluded. Studies were only included if they were published in the English language in peer-reviewed journals.

Search strategy
We performed a systematic review of the literature in March 2017. Using OvidSP as the database interface, a joint electronic search on MEDLINE and Embase was conducted. We searched BIOSIS database using ISI Web of Science. The search used free-text search terms (S1 Table) with truncations to allow for different spellings, proximity operators ('adj' in OvidSP, 'NEAR' in ISI Web of Science) and joined using Boolean logic ("AND", "OR"). The reference lists' of relevant reviews, all included papers and their ISI citation index (via Web of Science) was searched for studies meeting inclusion criteria. Given the extensive number of studies identified using these databases; we did not search grey literature. Eligible studies identified were combined with the electronic search results.
The following information was extracted from selected papers: citation details, study details (including type, country/region and sample size), participant details (including age and sex), and exposure and outcome details (including details on methods used). A free-text box for recording main findings was used because of the expected heterogeneous methods that will have been used.
The following aspects of the paper which may relate to the quality of each study were extracted: study type, methods used to measure epigenetics, statistical analysis (including adjustment of relevant confounders), recall bias such as prospective or retrospective measures of early life factors, and generalisability [19].
Due to the diversity in eligible studies in terms of methods used, a meta-analysis was not conducted [19]. Therefore, a narrative synthesis was undertaken [20].

Results
Overall we identified 90 eligible papers (Fig 1 and Tables 1-3). Seventeen of these papers examined more than one early life exposure of interest. All of the included papers examined DNAm as the epigenetic marker with none examining histone modifications. Results of each of these papers will be outlined below according to the main exposure of interest.

Body size and growth in early life
Of the included papers, n = 56 examined the role of body size and growth in early life on DNAm (Table 1). There were 14 prospective (3 of which compared extreme groups), 33 crosssectional (6 of which compared extreme groups), and 9 twin studies.
Body size at birth: Three papers examined body size at birth in relation to childhood and adolescent genome-wide methylation using the Illumina Human-Methylation450 or Human-Meth-ylation27 BeadChip array [55,58,77]. Agha et al. demonstrated that birth weight-for-gestational age (GA) was associated with methylation at 34 CpGs of which 4 of these CpGs remained at age 7-10 years in 235 children. Three of these CpGs were located on PBX1 (embryonic development regulator) and one was on NOS1AP (neuronal nitric oxidase synthase) [55]. In the Accessible Resource for Integrated Epigenomic Studies cohort (ARIES, a sub sample of The Avon Longitudinal Study of Parents and Children (ALSPAC) cohort), birth weight was not associated with genome-wide DNA methylation in blood when the children were aged 7 and 17 years old [77]. However, analyses in the ARIES cohort did find that birth weight was associated with age acceleration based on Horvath's clock (i.e. residuals from regression of epigenetic age on actual age) at birth, 7 and 17 years; a finding that was replicated in an independent cohort [58].
Two studies examined associations between body size at birth and global DNA methylation in adulthood [59,60]. Rerkasem et al. found no associations between birth weight or birth length and blood methylation at LINE-1 or Alu in 249 20 year old adults [59]. In the other paper, global methylation measured in blood at age 38-48 years using a [ 3 H]-methyl acceptance assay, was associated with birth length, but not birth weight [60].
Five papers examined body size at birth and subsequent DNAm in candidate genes [53,61,62,64,65]. Three of these papers examined methylation in imprinted genes. In the Motherwell Cohort, there was an association between birth length, but not birth weight, and methylation at IGF2/H19 differentially methylated region (DMR) measured in blood at 40 years [61]. Birth weight was associated with H19 DMR measured in childhood (~8 years) in girls, but not boys [53] and with methylation at the IGF2 DMR measured in blood samples of infants aged 17                       LEP methylation was significantly associated with duration of breastfeeding: -0.6 (95%CI -      Conceived during extreme famine, but exposed for short period

±1.6y
Unexposed same-sex siblings: 57.3± 6.3y Changes in DNA methylation (%units) in exposed vs. all non-    months [62]. In relation to non-imprinted genes, birth weight was found to be associated with methylation at HSD2, but not GR (both related to glucocorticoid) in blood samples of 34 participants aged 40 years [61] while another study found it not to be associated with methylation at the LEP gene in blood among infants aged~17 months once confounders were taken into account [64]. Among the papers comparing extreme groups, one found no genome-wide differences in DNA methylation in adipose derived stem cells between 13 low birth weight (LBW) babies and controls [56]. Another found some evidence for a difference in methylation in specific CpG sties of IGF2 in blood between 158 very LBW ( 1500g) with controls [63]. The third paper found that methylation at two out of three CpG sites in ACE (angiotensin-converting enzyme, a gene related to cardiovascular disease) was lower among LBW children (6-12y) compared with normal birth weight children [79].
Childhood body size and growth: Using data from the ARIES cohort weak, associations between taller height at 7 years and epigenetic age acceleration at 7 and 17 years (p = 0.06, p = 0.07) were observed. However, no associations were seen with BMI [58].
Two papers examined growth in early life in relation to DNA methylation [59,67]. In one, catch up growth during the first year of life was associated with Alu but not LINE-1 methylation measured in blood at 20 years [59]. In the other, those defined as rapid growers between term and 12 weeks had higher methylation at TACSTD2 (associated with adiposity) at 12 years compared with slow growers. This was not replicated in ALSPAC where methylation was measured at 7 years [67].
Birth weight: Five papers examined birth weight and cord blood genome-wide methylation measured using the Illumina Human-Methylation450 or Human-Methylation27 BeadChip array [21,22,24,25,55]. In a Norwegian study, birth weight was associated with methylation at 19 CpG sites including CpGs on the ARID5B and XRCC3 genes which are related to adipogenesis and DNA repair respectively [21]. Birth weight percentile also related to methylation in three genes of which one, FGFR2 (involved in metabolic regulation) replicated in a cohort of 110 participants [22]. Fryer et al. observed 304 CpG sites to be associated with birth weight percentile in 12 newborns [25]. However no genome-wide significance between birth weight and cord blood methylation was found among 201 participants of another study [24]. Using a different microarray technique, Lee et al. found birth weight to be associated with differentially methylated regions (DMRs) near three genes involved in early development (NFIX, RAPGEF2, MSRB3) [26].
Six papers examined markers of global methylation in cord blood [27-30, 32, 84]. There was no evidence for an association between birth weight and cord blood global methylation measured using Methylamp, LUMA, LINE-1 or Alu in most papers [27,28,32,84]. One paper observed an association (p = 0.05) between lower birth weight and higher cord blood LINE-1 methylation,[29] while others found that LINE-1 methylation was slightly lower among newborns with high birth weight compared with normal weight [30].
The remaining papers examined cord blood methylation in candidate genes with the majority focused on imprinted genes. Five reported associations with cord blood methylation at imprinted genes in the Newborn Epigenetics Study (NEST) [35][36][37][38]40]. Most did not demonstrate an association between birth weight and IGF2 methylation [35,36,38]. However, one observed a lower methylation at IGF2 DMRs among low birth weight compared with normal weight newborns (p = 0.06) [37]. There was a significant relationship between birth weight and methylation at PEG10 and/or PLAGL1 in three NEST papers [35,37,40]. Findings for H19 methylation were inconsistent [35,36,38]. In another study, methylation at IGF2 was lower in high birth weight newborns compared with normal birth weight groups [39]. There was no correlation between birth weight and methylation at the ZAC1 DMR [43] or with methylation of IGF2, H19, PEG3, SNRPN [29,32].
In the papers investigating non-imprinted genes, birth weight was not associated with methylation in genes related to the glucocorticoid receptor [32,46]. A follow on study from the paper by Fryer et al. [25], found that increased cord blood methylation at GSTM5 and MAP2K3 was associated with a reduced risk of a lower birth weight percentile while higher methylation levels in APOB were associated with an increased risk [45]. Birth weight was also associated with AHRR (involved in cell growth and differentiation), HFI3A (obesity-associated gene) and LEP (appetite-related) methylation [44,47,48].
Among the papers comparing extreme groups, Qian et al. did see differences in the methylation of H19, but not MEST, in cord blood between 39 small-for-GA (SGA) versus averagefor-GA (AGA) babies [34]. Similarly, Zhang et al. found methylation at H19 DMR in blood to be different between AGA, SGA and large-for-GA infants [41].
Among 991 participants of Chinese, Malay or Indian ethnicity, subscapular skinfold thickness and subscapular:triceps skinfold thickness increased with increasing methylation at 2 CpG sites in HIF3A [47].
Childhood height/weight: In school age children (5-12y) in Columbia (n = 568), there was no association between global blood DNA methylation and height-for-age z-score [50]. Methylation in 4 out of 8 CpG sites at the P2 promoter region of IGF1 was inversely correlated with height in both a discovery and replication cohort [52]. There was no difference in the methylation of H19 DMR comparing overweight versus lean boys or girls aged~8 years [53]. Among 64 African-American children (5-6y), there was a weak association between lower BMI percentiles and higher saliva methylation in DNMT3B, but no relationships with other obesityrelated genes (FTO, MAOA, SH2B1, LEPR, BDNF or CCKAR) [54]. Ouni et al. identified differently methylated CpG sties in IGF promoters between 94 children (~10y) with idiopathic short structure compared to children of normal height [51].
TWIN-studies of body size and growth in early life and DNA methylation. All twin studies examined birth-weight discordance [68][69][70][71][72][73][74][75][76]. There were no genome-wide DNAm differences between birth weight-discordant monozygotic (MZ) twins in blood from adults in two papers [68,69], or using saliva samples from 15 year olds in another [71]. In twin participants aged 22-45 years, although 45 differentially methylated CpGs were identified using saliva samples, there was no difference in the methylation of repetitive elements [75]. In Twin-sUK, one CpG of IGF1 was associated with birth weight discordance [70] while there was a 13% average difference in methylation of COMT (implicated in psychiatric disorders) between MZ twins at 5 years [76].

Nutrition in early life
Thirty seven papers included in this systematic review examined the role of nutrition in early life ( Table 2). The majority of these studies (37%, n = 14) investigated maternal nutrition during pregnancy as a proxy for fetal nutrition. Nine studies examined nutrition in early life and six studies looked at both maternal pregnancy and early life nutrition. We also included eight studies that examined the impact of gestational exposure to famine or periods of restricted dietary intake Maternal nutrition during pregnancy and offspring DNA methylation. Most papers focused on the nutrients involved in one-carbon metabolism i.e. folate, vitamin B6, vitamin B12, methionine, choline, and betaine given their role as methyl donors [14].
Nutrition-related methyl donor intake and/or supplementation: Joubert et al. identified 443 CpG sites, measured on the Illumina Human-Methylation450 BeadChip, that were differentially methylated in cord blood in relation to maternal plasma folate [85]. No association was observed in three of the four papers which examined maternal nutrition-related methyl donor intake/folic acid supplementation in relation with infant cord blood global DNA methylation [81,[86][87][88]. The forth paper found an inverse association between folic acid supplementation after 12 weeks gestation and LINE-1 methylation [81].
Six papers examined imprinted genes. Hoyo et al. found no differences in cord blood IGF2 methylation among infants born to women taking moderate to high (!400 μg/d) folic acid supplements before or during pregnancy compared to non-users, however H19 methylation was reduced [90]. While Loke et al. also observed a reduction in infant's H19 methylation, they found an increase in one IGF2 DMR (DMR2) across different tissues for mothers taking folic acid [91]. Similarly mean blood IGF2 methylation of 17 month old infants was higher in those whose mothers took folic acid [62]. Another paper found that methylation at ZAC1 was positively correlated with maternal intakes of vitamin B2 prior to pregnancy, however no association was observed for any other B-vitamin intake or folic acid supplement [64].
Two papers considered the effect at other candidate genes. In one, a difference in cord blood methylation at LEP, RXRA and/or DNMT1 was observed for the intake of certain methyl donors [87]. However there was no association between maternal folic acid supplementation and blood LEP methylation among 17 month old infants in the other [64].
Nutrition-related methyl donor biomarker:In the paper by Haggarty et al., maternal red blood cell (RBC) folate was inversely associated with LINE-1 methylation [81]. Similarly, another paper observed that maternal serum markers of vitamin B12 were correlated with cord blood global DNA methylation [89]. Results from four papers examining maternal methyl donor biomarkers in relation to offspring's cord blood methylation at imprinted genes were inconsistent [35,93,94]. In the Gambian Keneba cohort, serum vitamin B2, vitamin B6, homocysteine, and cysteine were associated with methylation at the combined metastable epialleles (MEs i.e. alleles that are variably expressed in genetically identical individuals due to epigenetic modifications [109])) [95].
Other nutrient intake/biomarker:Four papers investigated the effect of maternal intake of other nutrients. One found no association of maternal intake of protein, fat or carbohydrate with LINE-1 or Alu methylation [59]. Findings from the Motherwell cohort suggest that higher maternal intake of meat/fish and vegetable and lower intake of bread/potato in late pregnancy is associated with methylation at HSD2 and GR in adult offspring blood [61], while another observed that lower maternal carbohydrate intake, but not fat or protein, was associated with higher cord blood methylation of RXRA but not of eNOS [96]. Finally, Simpkin et al. observed an association with maternal serum selenium, but not vitamin D, in children ages 7 and 17 years [58].
Early life nutrition and offspring DNA methylation. Breastfeeding:Five papers examined the impact of breastfeeding on DNA methylation. In Simpkin et al's epigenetic age paper there was no correlation with breastfeeding duration [58]. In secondary analyses in another paper there was an implied association between breastfeeding and DNA methylation at approximately 11 years as measured on the Illumina Human-Methylation27 BeadChip, however no statistical test was performed [97]. In two papers using the same sample of 17 month old infants, there was a reduction in blood methylation of LEP with increasing duration of breastfeeding [64,98]. A correlation between breastfeeding and methylation of a cancerrelated gene, CDKN2A, in tumour tissues among premenopausal but not postmenopausal women was observed in the final paper [65].
Nutrition-related methyl donor biomarker:Seven papers examined the role of early life nutrition-related methyl donor biomarkers [25,31,50,81,88,89,93]. Across three cross-sectional papers, plasma homocysteine concentrations were negatively correlated with cord blood LINE-1 methylation or were different between two clusters defined by unsupervised hierarchical clustering using data from the Illumina Human-Methylation27 BeadChip [25,31,88]. In the Haggarty et al. paper described above, authors also observed that RBC folate in cord blood was associated with cord blood LINE-1, and methylation in IGF2, PEG-3 but not SNRPN [81]. However, serum folate/plasma B12 was not cross-sectionally associated with cord blood LINE-1 methylation or blood samples of [5][6][7][8][9][10][11][12] year olds in two studies [50,88]. While a negative cross-sectional correlation between serum B12 and IGF2 cord blood methylation was observed in one study [89], this was not replicated by Ba et al, who also found no correlation with folate [93].
Other nutrient intake/biomarker:One paper found that fatty acid intake was associated with methylation levels in children's blood as measured by from Illumina Human-Methyla-tion27 BeadChip [99]. Another observed an association between HDL-cholesterol, but not LDL-cholesterol, and blood methylation at LEP and TNFα among young children. However this was attenuated after Bonferroni correction [98] Two cross-sectional studies examined the effect of other early life nutrient biomarkers. One observed an association with arachidonic acid and eicosapentaenoic acid, but not other fatty acids in lactating infants global blood methylation [100]. The other paper reported an association between serum copper and NFIX but not FAPGE or MSRB3 cord blood methylation [26].
Famine/rainy season exposure and offspring DNA methylation. The Dutch Hunger Winter, which lasted from September 1944 to May 1945, was the setting for 75% of the famine papers [104,106,107,[110][111][112]. In these papers DNA methylation was measured in blood samples of adults with mean age of 59 (0.5 SD) years who were exposed to famine at some point during gestation and compared with time and/or family matched controls. Using the Illumina Human-Methylation450 BeadChip, famine exposure during gestational weeks 1-10, but not later, was associated with differences in DNA methylation [105]. This time-sensitive association was also seen for IGF2 methylation [104], and in an investigation of 15 candidate genes that are involved in metabolism, CVD and growth [106]. However, one study did not find an association between famine exposure at any point in gestation and DNA methylation at genes involved in stress response, developmental process and lipid metabolism [107].
Two papers were from other settings. In a sample of children in rural Gambia, methylation at MEs was higher among children conceived during the rainy season (i.e. "hungry" period) compared with those conceived in the dry season [108]. In Bangladeshi young adults no genome-wide differences in methylation was observed between those postnatally exposed to famine, exposed during gestation or unexposed [102]. However, a difference in methylation at MEs between those exposed to famine during gestation compared to the other groups was found [102]. 17 papers investigated the association between markers of SEP and DNA methylation (Table 3).

Socioeconomic position in early life
Maternal education: There was no association between maternal education and epigenetic age acceleration in the Simpkin et al paper [58] and no association with global methylation in two other papers [27,50]. Tehranifar et al. found no association with LINE-1 or Alu methylation, but did observe higher blood Sat2 methylation among adults who's mother's had lower education compared with those whose mothers had at least a high school education [113]. Although one study found that maternal education was associated with cord blood IGF2 methylation, but not with other imprinted genes [114], two other papers did not observe an association with IGF2 methylation [38,115]. However, in one of these papers an increase in H19 methylation in cord blood of those with mothers who did not have a college education was reported [38].
In three papers using the same sample of 120 children aged 17 months, maternal education was correlated with INSIGF but not with LEP or TNFα blood methylation [64,115,122].
Other markers of SEP: No association was observed between family SEP measured by parental education and income at birth and 7 years, and blood measures of global DNA methylation in adults [60]. In a Columbian cohort of children aged 5-12 years, household socioeconomic stratum was not associated with blood LINE-1 methylation [50]. King et al. found that household income was associated with methylation at MEG3 in cord blood, but not with other imprinted genes [114]. Results from a peer-reviewed abstract suggested that parental SEP was associated with DNA methylation in adipose tissue, but not blood of adult women as measured by Illumina Human-Methylation450 BeadChip [116].
Two papers using the same sample found preadolescent cumulative SEP risk (measured by family poverty, primary caregiver education, primary caregiver unemployment, single-parent family, receipt of assistance, and income) to be related to 2,032 loci at false discovery rate (FDR) <0.05 using data from the Illumina Human-Methylation450 BeadChip [117] and to specific CpG sties in SLC6A4 [121].
Lam et al. used the Illumina Human-Methylation27 BeadChip to find three differentially methylated CpGs between adults with low early life SEP as defined by their parents occupation compared with high SEP [118]. Similarly, using a genome-wide approach, Borghol et al. found that childhood SEP as measured by father's occupation and access to household amenities, was associated with methylation at 1,252 gene promoters in blood measures of 45 year old adults [123]. In the multi-ethnic study of atherosclerosis study, there was no evidence for an association between childhood SEP and LINE-1 and Alu blood methylation in adulthood [120].

Discussion
This systematic review identified 90 papers that examined the relationship between body size, nutrition and/or SEP in early life with epigenetic markers measured at the same time or after the exposure. DNAm was the epigenetic marker used in all of the included studies. There was no strong evidence for a consistent association between these early life variables and DNAm. This may be due to the heterogeneous study designs, data collection methods and statistical analyses. Despite these inconclusive results, the hypothesis that the early life environment can impact DNAm, potentially persisting into adult life, was supported by some studies and warrants further investigation.
There has been one previous non-systematic review examining the impact of body size, and/or nutrition and SEP on DNAm [15] and one systematic review examining the effect of breastfeeding [16]. Our search strategy was designed to be sensitive; therefore we captured a large number of initial papers and included substantially more papers than the previous reviews. We limited results to articles published in English which may have excluded relevant non-English language papers There were slight differences in the papers included in our systematic review compared with previous reviews. For instance, Demetriou et al. included RCTs and studies where DNAm was the exposure. Hartwig et al. included animal studies and studies of methQTLs. However, our overall conclusions are in line with these reviews.
Of the three exposures (body size, nutrition and SEP) examined in this review, the majority of papers investigated body size in early life particularly birth weight. Birth weight can be considered as a proxy for the in utero environment, which may subsume maternal diet and parental SEP. This time in the life course marks a period of rapid development during which epigenetic processes, including DNAm are becoming established [10]. Therefore, it is no surprise that this sensitive time period has been the subject of the majority of epigenetic studies to date. However, the results from these studies have been inconsistent and the direction of the association, particularly in cross-sectional studies, remains unclear. One of the interesting findings from the Dutch Hunger Famine study is that nutritional insults in early gestation are more sensitive to lasting changes in DNAm compared with later gestation. Using birth weight as a proxy for the entire gestational period may mask these time-specific effects. There are fewer studies on the impact of post-natal body size, nutrition and SEP. There is some weak and inconsistent evidence to support the impact of body composition, childhood body size, breastfeeding, intake and biomarkers of nutrition related methyl-donors in early life as well as SEP on DNAm that can last into later life. There is also evidence from intervention studies suggesting folic acid and fish oil supplementation during pregnancy or early life results in changes in DNAm [124][125][126], which were outside the scope of our review.
The inability to come to a conclusive interpretation based on studies in this systematic review is due to extensive heterogeneity in the study designs, statistical analyses and small sample sizes. This is no surprise given that the field of epigenetics in relation to life course epidemiology is in its infancy. Since DNAm can be influenced by stochastic, genetic and environmental exposures, effect sizes, even if they represent causal effects, are likely to be small and therefore difficult to find in small studies [11]. The sources of heterogeneity common to other systematic reviews of observational studies are a concern here. For example, there is inconsistency in how exposures were recorded or measured between the studies which may have introduced heterogeneity. Similarly, not all studies adjusted for the same confounding factors, nor are we clear about what those confounders should be. Of particular concern is the oversight of some relevant studies to control for maternal smoking which is to date the strongest known environmental exposure to impact DNA methylation [127], and cellular heterogeneity [128]. Another source of heterogeneity is the method through which studies account (or do not account) for multiple testing with some studies using a Bonferroni correction and others using false discovery rate. It has been argued that using a Bonferroni correction in epigenome wide association studies may be too conservative due to potential patterns of comethylation [129]. However, the potential for false positives makes for cautious interpretation of any positive findings in studies which don't account appropriately for multiple testing. In addition, reproducibility of these findings will be an important goal for future research [128]. One of the unique characteristics of studying DNAm compared to genetics is that DNAm is tissue-specific [128]. The majority of studies included in this review have examined blood due to the ease of accessibility. It may be the case that the impact of e.g. nutrition in early life on DNAm may be more evident in adipose or other target tissues compared with blood.
A major limitation of all the studies is that knowledge of the epigenome, and DNAm, is still limited [128]. Most of the studies included in this review have focused on candidate genes, similar to how early genetic studies were carried out. A variety of assays were used to measure DNAm, which have been discussed in previous papers [129,130]. As technology has advanced, the study of genome-wide methylation has increased. However, even the relatively advanced methods such as Illumina 450k (or the new 850k) covers an estimated <2% of the epigenome [128]. This implies that sites of interest may be missed. These technological issues have been discussed extensively by Mill and Heijmans [128].
In addition to these statistical and technological issues, interpreting the functional consequences of some of the identified DNAm sites remains relatively unexplored, as is the potential impact of these DNAm changes on phenotypic health outcomes. A recent paper from the Dutch Hunger Famine study providing evidence that DNAm may mediate the link between adversity in early life and health outcomes in adulthood is one of the first to support this hypothesis [131].
In light of findings from this review and suggestions from previous commentaries [128,132,133], we propose the following recommendations for future studies: 1) use of longitudinal studies to assess the impact of early life environmental exposures on the dynamics of the epigenome through the life course 2) full consideration of statistical issues, such as adjustment for confounding, ensuring sufficient power, control for multiple testing, and reproducibility 3) control for cell heterogeneity and examine associations across different tissue types 4) assess the functional consequence of identified epigenetic marks through second-generation EWAS as part of an integrated functional genomics strategy 5) examine if DNAm mediates the relationship between early life exposures and health outcomes in later life and use of novel methods to assess causality e.g. Mendelian Randomisation.
Overall, evidence for the impact of body size, nutrition and/or SEP in early life on concurrent or subsequent DNAm is inconclusive. However, findings to date are supportive of the continued investigation using well designed studies which capitalise on emerging technologies to test these hypotheses. Whether these early life-mediated DNAm profiles translate into health outcomes in later life is something that should be incorporated into future studies.
Supporting information S1