Genetic and epigenetic catalysts in early-life programming of adult cardiometabolic disorders

Evidence has emerged across the past few decades that the lifetime risk of developing morbidities like type 2 diabetes, obesity, and cardiovascular disease may be influenced by exposures that occur in utero and in childhood. Developmental abnormalities are known to occur at various stages in fetal growth. Epidemiological and mechanistic studies have sought to delineate developmental processes and plausible risk factors influencing pregnancy outcomes and later health. Whether these observations reflect causal processes or are confounded by genetic and social factors remains unclear, although animal (and some human) studies suggest that epigenetic programming events may be involved. Regardless of the causal basis to observations of early-life risk factors and later disease risk, the fact that such associations exist and that they are of a fairly large magnitude justifies further research around this topic. Furthermore, additional information is needed to substantiate public health guidelines on lifestyle behaviors during pregnancy to improve infant health outcomes. Indeed, lifestyle intervention clinical trials in pregnancy are now coming online, where materials and data are being collected that should facilitate understanding of the causal nature of intrauterine exposures related with gestational weight gain, such as elevated maternal blood glucose concentrations. In this review, we provide an overview of these concepts

Precision medicine in obesity and type 2 diabetes : The relevance of early-life exposures

BACKGROUND: Type 2 diabetes is highly prevalent and devastating. Obesity is a diabetogenic factor, driving insulin resistance and a compensatory demand for increased insulin secretion from the pancreatic cells; a failure to address this demand results in diabetes. Accordingly, primary and secondary prevention of obesity are at the core of diabetes prevention programs. The development of obesity and declining β-cell function often span many years or decades before diabetes is clinically manifest. Thus, characterizing the early-life process and risk factors that set disease trajectories may yield novel targets for early intervention and help improve the accuracy of prediction algorithms, factors germane to the emerging field of precision medicine. CONTENT: Here, we overview the concepts of precision medicine and fetal programming. We discuss the barriers to preventing obesity and type 2 diabetes in adulthood and present the rationale for considering early-life events in this context. In so doing, we discuss proof-of-concept studies and cutting-edge technological developments that are likely to transform current thinking on the etiology and pathogenesis of obesity and type 2 diabetes. We also review the factors hampering progress, including the success and failures of pregnancy intervention trials. SUMMARY: Obesity and type 2 diabetes are among the major health and economic burdens of our time. Defeating these diseases is likely to require life-course approaches, which may include aggressive interventions informed by biomarker profiling undertaken during early life

Association is not prediction : A landscape of confused reporting in diabetes – A systematic review

Aims: Appropriate analysis of big data is fundamental to precision medicine. While statistical analyses often uncover numerous associations, associations themselves do not convey predictive value. Confusion between association and prediction harms clinicians, scientists, and ultimately, the patients. We analyzed published papers in the field of diabetes that refer to “prediction” in their titles. We assessed whether these articles report metrics relevant to prediction. Methods: A systematic search was undertaken using NCBI PubMed. Articles with the terms “diabetes” and “prediction” were selected. All abstracts of original research articles, within the field of diabetes epidemiology, were searched for metrics pertaining to predictive statistics. Simulated data was generated to visually convey the differences between association and prediction. Results: The search-term yielded 2,182 results. After discarding non-relevant articles, 1,910 abstracts were evaluated. Of these, 39% (n = 745) reported metrics of predictive statistics, while 61% (n = 1,165) did not. The top reported metrics of prediction were ROC AUC, sensitivity and specificity. Using the simulated data, we demonstrated that biomarkers with large effect sizes and low P values can still offer poor discriminative utility. Conclusions: We demonstrate a landscape of confused reporting within the field of diabetes epidemiology where the term “prediction” is often incorrectly used to refer to association statistics. We propose guidelines for future reporting, and two major routes forward in terms of main analytic procedures and research goals: the explanatory route, which contributes to precision medicine, and the prediction route which contributes to personalized medicine

A prospective study of the relationships between movement and glycemic control during day and night in pregnancy

Both disturbed sleep and lack of exercise can disrupt metabolism in pregnancy. Accelerometery was used to objectively assess movement during waking (physical activity) and movement during sleeping (sleep disturbance) periods and evaluated relationships with continuous blood glucose variation during pregnancy. Data was analysed prospectively. 15-women without pre-existing diabetes mellitus wore continuous glucose monitors and triaxial accelerometers from February through June 2018 in Sweden. The relationships between physical activity and sleep disturbance with blood glucose rate of change were assessed. An interaction term was fitted to determine difference in the relationship between movement and glucose variation, conditional on waking/sleeping. Total movement was inversely related to glucose rate of change (p < 0.001, 95% CI (− 0.037, − 0.026)). Stratified analyses showed total physical activity was inversely related to glucose rate of change (p < 0.001, 95% CI (− 0.040, − 0.028)), whereas sleep disturbance was not related to glucose rate of change (p = 0.07, 95% CI (< − 0.001, 0.013)). The interaction term was positively related to glucose rate of change (p < 0.001, 95% CI (0.029, 0.047)). This study provides temporal evidence of a relationship between total movement and glycemic control in pregnancy, which is conditional on time of day. Movement is beneficially related with glycemic control while awake, but not during sleep

Lifestyle Intervention in Pregnant Women With Obesity Impacts Cord Blood DNA Methylation, Which Associates With Body Composition in the Offspring

Maternal obesity may lead to epigenetic alterations in the offspring and might thereby contribute to disease later in life. We investigated whether a lifestyle intervention in pregnant women with obesity is associated with epigenetic variation in cord blood and body composition in the offspring. Genome-wide DNA methylation was analyzed in cord blood from 208 offspring from the Treatment of Obese Pregnant women (TOP)-study, which includes pregnant women with obesity randomized to lifestyle interventions comprised of physical activity with or without dietary advice versus control subjects (standard of care). DNA methylation was altered at 379 sites, annotated to 370 genes, in cord blood from offspring of mothers following a lifestyle intervention versus control subjects (false discovery rate [FDR] <5%) when using the Houseman reference-free method to correct for cell composition, and three of these sites were significant based on Bonferroni correction. These 370 genes are overrepresented in gene ontology terms, including response to fatty acids and adipose tissue development. Offspring of mothers included in a lifestyle intervention were born with more lean mass compared with control subjects. Methylation at 17 sites, annotated to, for example, DISC1, GBX2, HERC2, and HUWE1, partially mediates the effect of the lifestyle intervention on lean mass in the offspring (FDR <5%). Moreover, 22 methylation sites were associated with offspring BMI z scores during the first 3 years of life (P < 0.05). Overall, lifestyle interventions in pregnant women with obesity are associated with epigenetic changes in offspring, potentially influencing the offspring's lean mass and early growth

The combined effects of FADS gene variation and dietary fats in obesity-related traits in a population from the far north of Sweden : the GLACIER Study

BACKGROUND: Recent analyses in Greenlandic Inuit identified six genetic polymorphisms (rs74771917, rs3168072, rs12577276, rs7115739, rs174602 and rs174570) in the fatty acid desaturase gene cluster (FADS1-FADS2-FADS3) that are associated with multiple metabolic and anthropometric traits. Our objectives were to systematically assess whether dietary polyunsaturated fatty acid (PUFA) intake modifies the associations between genetic variants in the FADS gene cluster and cardiometabolic traits, and to functionally annotate top-ranking candidates to estimate their regulatory potential. METHODS: Data analyses consisted of the following: interaction analyses between the 6 candidate genetic variants and dietary PUFA intake; gene-centric joint analyses to detect interaction signals in the FADS region; haplotype-centric joint tests across 30 haplotype blocks in the FADS region to refine interaction signals; and functional annotation of top-ranking loci from the previous steps. These analyses were undertaken in Swedish adults from the GLACIER Study (N = 5,160); data on genetic variation and eight cardiometabolic traits were used. RESULTS: Interactions were observed between rs174570 and n-6 PUFA intake on fasting glucose (Pint = 0.005) and between rs174602 and n-3 PUFA intake on total cholesterol (Pint = 0.001). Gene-centric analyses demonstrated a statistically significant interaction effect for FADS and n-3 PUFA on triglycerides (Pint = 0.005) considering genetic main effects as random. Haplotype analyses revealed three blocks (Pint &lt; 0.011) that could drive the interaction between FADS and n-3 PUFA on triglycerides; functional annotation of these regions showed that each block harbours a number of highly functional regulatory variants; FADS2 rs5792235 demonstrated the highest functionality score. CONCLUSIONS: The association between FADS variants and triglycerides may be modified by PUFA intake. The intronic FADS2 rs5792235 variant is a potential causal variant in the region, having the highest regulatory potential. However, our results suggest that multiple haplotypes may harbour functional variants in a region, rather than a single causal variant

Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood

International audienceEpidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = − 0.76, 95% CI − 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = − 0.06, 95% CI − 0.93 to 0.87 mmHg), or pulse pressure (β = − 0.65, 95% CI − 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses