Examining a Developmental Approach to Childhood Obesity The Fetal and Early Childhood Years: Workshop Summary (2015) / Chapter Skim
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3 Etiology and Causal Inference
3 Etiology and Causal Inference
Pages 23-50
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From page 23... ...
of the mothers, but not infant fatness, is predictive of higher liver fat at 2 weeks of age, which continues to increase during lactation. Friedman explained that excess maternal fuels in obese mothers crossing the placenta have nowhere to go but into the fetal liver, and suggested that this fatty liver transgenerational effect of maternal obesity may be accompanied by epigenetic changes in offspring liver and other tissues at 1 year of age.
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Among other suggestions, she called for more refined measures of maternal obesity, an increased awareness of the pitfalls of association studies, and the use of triangulation among multiple studies to infer causality. EPIGENETIC MECHANISMS FOR OBESITY RISK1 Maternal obesity in the United States has reached a point that compels Jacob Friedman to ask, "How could this not impact infant outcomes?
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data, he and his team are able to examine where the fat is accumulating in the infant. Additionally, by harvesting umbilical cord-derived mesenchymal stem cells from newborn infants exposed to maternal obesity, they are also able to detect epigenetic signatures associated with maternal obesity.
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Boyle and colleagues (data presented at the American Diabetes Association meeting, 2015) showed that epigenetic signatures associated with myocyte versus adipocyte differentiation are affected by maternal BMI, with suppressed expression of both epigenetic regulators, DNMT1 and KDM6A, in the m esenchymal stem cells of infants born to obese women.
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The question for Friedman is, are the effects of maternal obesity on fat mass in offspring liver reversible? In a study with macaques, again using animals that were fed either a control diet or a high-fat diet, Friedman and his research team weaned offspring of mothers on a high-fat diet on to a healthy diet at 7 months.
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While breastfeeding is generally associated with protection against rapid infant weight gain and later obesity, the mechanisms responsible are not known but likely involve the delivery of bioactive components that regulate infant appetite, metabolism, and weight gain and adiposity. In what Friedman referred to as a "remarkable" paper, Koren et al.
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Friedman interpreted these findings to mean that exposure to maternal diet through the breast milk appears to be patterning the infant microbiome and, therefore, might be either protecting the infant gut or making infants more prone to inflammation and weight gain, but that is not yet known. Final Thoughts To conclude, Friedman shared some final thoughts: • Humans share a core microbiome, yet they differ by genes, species, ecology, and gene count or richness.
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2 This section summarizes information presented by Linda Adair, Ph.D., University of North Carolina at Chapel Hill.
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R02869 Figure 3-1 In terms of which of these aspects of disparity the fetus or young vector editable infant actually perceives, nutritional exposures are arguably one of the most important factors to consider. Disparities in nutritional exposure are reflected in maternal stores, that is, how fat he mother is, or, in the case of limited resources, how thin she is; maternal dietary intake of specific macroand micronutrients associated with child growth (e.g., B vitamins, methyl donors)
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, excess gestational weight gain, and dietary excesses have all been associated with increased risk of large-for-gestational-age deliveries and infant m acrosomia (Siega-Riz et al.
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disparities in inadequate and excess weight gain during pregnancy among different races and ethnicities. Percentages of inadequate pregnancy weight gain (x-axis)
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Variation in Infant Outcomes Data from PPNSS 2010 indicate that adverse birth outcomes in the United States, including preterm births, macrosomia, and low birth weight, are highly disparate across different races and ethnicities, with preterm births and low birth weight being highest in non-Hispanic black populations. Additionally, data from the U.S.
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. Disparities in maternal diet, including carbohydrate intake, famine exposure, and vitamin and mineral uptake, have been associated with altered methylation patterns (Godfrey et al., 2011; McKay et al., 2012; Tobi et al., 2009)
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. Compared to a Caucasian baby that weighs an average of 3,500 grams, with 10 percent fat stores and 20 percent muscle mass, an Indian baby of average birth weight, which is 2,700 grams, has 20 percent fat stores and 10 percent muscle mass (Yajnik, 2004)
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Adair mentioned other studies of low birth weight or small-for- gestational-age infants who were deliberately being fed to catch up, with data indicating an increased risk of obesity associated with the catch-up growth. That situation may also represent mismatch.
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. On a per cell basis, sperm deliver about 3 This section summarizes information and opinions presented by Stephen Krawetz, Ph.D., Wayne State University, Detroit, Michigan.
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Evaluating Sperm RNAs To study the biological relevance of sperm RNA, Krawetz and colleagues pooled RNA from the testes of 19 individuals, pooled RNA extracts from the ejaculates of 9 individuals, and collected RNA from the ejaculate of a single individual, and synthesized from all of these different samples a series of cDNAs (Ostermeier et al., 2002)
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, translation of intact paternal mRNAs, transcriptional regulation by paternal microRNAs, activation of paternal pre-microRNAs by maternal DICER (as shown from microRNA-181c) , and transcriptional regulation by paternal microRNAs and RNA fragments (Jodar et al., 2013)
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s The Overkalix study was conducted on a series of Swedish cohorts born in 1890, 1905, and 1920 and followed until 1995. The researchers extrapo lated food access from historical data and asked whether an abundance of food during a child's slow growth period, that is, before the prepubertal peak, influenced descendants' risk of death from cardiovascular disease and diabetes.
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? When thinking about epigenetic processes as a potential mediating mechanism linking maternal over- or under-nutrition with offspring adiposity, Relton reminded the workshop audience that although her talk would be very much framed around epigenetic modifications -- DNA methylation in particular as the mediator -- one could very easily substitute "epigenetic modification" with microRNA expression, metabolomics profiles, or the microbiome.
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• tep 3: Establish an association between the child's DNA methylation and S the child's adiposity. • tep 4: Apply methods to strengthen causal inference.
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Relton and her team wanted to know whether the effects of gestational weight gain and/or maternal pre-pregnancy body mass index on birth weight, childhood adiposity, and adolescent adiposity were being mediated through altered methylation. Data generated from an epigenome-wide association study based on cord blood methylation in children at birth indicate a number of hits in relation to maternal underweight, very few hits in relation to maternal overweight, and some hits in relation to maternal obesity (Sharp et al., 2015)
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. Longitudinal modeling is yet another tool for strengthening causal inference with respect to DNA methylation.
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, one could use as the proxy for maternal BMI an allele score generated from allelic variants known to influence maternal BMI and examine the relationship between this genetic proxy and a child's DNA methylation. Additionally, if one wanted to know whether the child's DNA methylation was causally related to the child's BMI, one could identify genetic variants strongly correlated with site-specific DNA methylation and use those genetic variants as a proxy measure for DNA methylation.
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In sum, in terms of addressing the questions about whether maternal BMI changes offspring methylation at birth and whether offspring methylation at birth subsequently has an effect on childhood adiposity, it was postulated at the outset that, yes, maternal BMI alters cord blood or child methylation at the HIF3A gene and that methylation at that locus sub sequently alters the child's BMI. However, having conducted the Mendelian randomization analysis, Relton and her team concluded that maternal BMI likely has a direct causal effect on the child's BMI and that the effect is not mediated by early life changes in methylation.
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Improving the third step will require both better observational evidence and improved technology for the assessment of genome-wide DNA methylation. Finally, to improve the fourth step, Relton called for an increased awareness of the pitfalls of the association studies and approaches being used and for a more widespread implementation of what she referred to as "triangulation of evidence." She suggested not relying on one study design, but rather implementing a number of different tools to weigh the evidence.
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The Effect of Genetic Variation on Epigenetic Variation The effect of genetic variation on epigenetic variation came up several times during the course of the 2-day workshop. Here, in reference to C aroline Relton's demonstration of strong evidence indicating that maternal BMI is causally linked to child DNA methylation, Robert Waterland asked how Mendelian randomization rules out the alternative explanation that maternal genetics, which the child partially inherits, are causing the differences in the child's DNA methylation.
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The use of metabolic disease phenotypes as outcome measures instead of, or in addition to, BMI was an issue that was revisited several times throughout the workshop.
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