Developmental responses to early-life adversity: Evolutionary and mechanistic perspectives

Adverse ecological and social conditions during early life are known to influence development, with rippling effects that may explain variation in adult health and fitness. The adaptive function of such developmental plasticity, however, remains relatively untested in long-lived animals, resulting in much debate over which evolutionary models are most applicable. Furthermore, despite the promise of clinical interventions that might alleviate the health consequences of early-life adversity, research on the proximate mechanisms governing phenotypic responses to adversity have been largely limited to studies on glucocorticoids. Here, we synthesize the current state of research on developmental plasticity, discussing both ultimate and proximate mechanisms. First, we evaluate the utility of adaptive models proposed to explain developmental responses to early-life adversity, particularly for long-lived mammals such as humans. In doing so, we highlight how parent-offspring conflict complicates our understanding of whether mothers or offspring benefit from these responses. Second, we discuss the role of glucocorticoids and a second physiological system-the gut microbiome-that has emerged as an additional, clinically relevant mechanism by which early-life adversity can influence development. Finally, we suggest ways in which nonhuman primates can serve as models to study the effects of early-life adversity, both from evolutionary and clinical perspectives.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152003/1/evan21791_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152003/2/evan21791.pd

Twenty-four hour metabolic rate measurements utilized as a reference to evaluate several prediction equations for calculating energy requirements in healthy infants

<p>Abstract</p> <p>Background</p> <p>To date, only short-duration metabolic rate measurements of less than four hours have been used to evaluate prediction equations for calculating energy requirements in healthy infants. Therefore, the objective of this analysis was to utilize direct 24-hour metabolic rate measurements from a prior study to evaluate the accuracy of several currently used prediction equations for calculating energy expenditure (EE) in healthy infants.</p> <p>Methods</p> <p>Data from 24-hour EE, resting (RMR) and sleeping (SMR) metabolic rates obtained from 10 healthy infants, served as a reference to evaluate 11 length-weight (LWT) and weight (WT) based prediction equations. Six prediction equations have been previously derived from 50 short-term EE measurements in the Enhanced Metabolic Testing Activity Chamber (EMTAC) for assessing 24-hour EE, (EMTACEE-LWT and EMTACEE-WT), RMR (EMTACRMR-LWT and EMTACRMR-WT) and SMR (EMTACSMR-LWT and EMTACSMR-WT). The last five additional prediction equations for calculating RMR consisted of the World Health Organization (WHO), the Schofield (SCH-LWT and SCH-WT) and the Oxford (OXFORD-LWT and OXFORD-WT). Paired t-tests and the Bland & Altman limit analysis were both applied to evaluate the performance of each equation in comparison to the reference data.</p> <p>Results</p> <p>24-hour EE, RMR and SMR calculated with the EMTACEE-WT, EMTACRMR-WT and both the EMTACSMR-LWT and EMTACSMR-WT prediction equations were similar, p = NS, to that obtained from the reference measurements. However, RMR calculated using the WHO, SCH-LWT, SCH-WT, OXFORD-LWT and OXFORD-WT prediction equations were not comparable to the direct 24-hour metabolic measurements (p < 0.05) obtained in the 10 reference infants. Moreover, the EMTACEE-LWT and EMTACRMR-LWT were also not similar (p < 0.05) to direct 24-hour metabolic measurements.</p> <p>Conclusions</p> <p>Weight based prediction equations, derived from short-duration EE measurements in the EMTAC, were accurate for calculating EE, RMR and SMR in healthy infants.</p

Plausible self-reported dietary intakes in a residential facility are not necessarily reliable

Background/Objectives: Comparing reported energy intakes with estimated energy requirements as multiples of basal metabolic rate (Ein:BMR) is an established method of identifying implausible food intake records. The present study aimed to examine the validity of self-reported food intakes believed to be plausible. Subjects/Methods: One hundred and eighty men and women were provided with all food and beverages for two consecutive days in a residential laboratory setting. Subjects self-reported their food and beverage intakes using the weighed food diary method (WDR). Investigators covertly measured subjects’ actual consumption over the same period. Subjects also reported intakes over four consecutive days at home. BMR was measured by indirect calorimetry. Results: Average reported energy intakes were significantly lower than actual intakes (11.2 and 11.8 MJ/d, respectively, P<0.001). Two-thirds (121) of the WDR were under-reported to varying degrees. Only five of these were considered as implausible using an Ein:BMR cut-off value of 1.03*BMR. Under-reporting of food and beverage intakes, as measured by the difference between reported and actual intake, was evident at all levels of Ein;BMR. Reported energy intakes were lower still (10.2 MJ/d) while subjects were at home. Conclusions: Under-recording of self-reported food intake records was extensive but very few under-reported food intake records were identified as implausible using energy intake to BMR ratios. Under-recording was evident at all levels of energy intake

Vitamin D status is inversely associated with markers of risk for type 2 diabetes: A population based study in Victoria, Australia

A growing body of evidence suggests a protective role of Vitamin D on the risk of type 2 diabetes mellitus (T2DM). We investigated this relationship in a population sample from one Australian state. The data of 3,393 Australian adults aged 18±75 years who participated in the 2009±2010 Victorian Health Monitor survey was analyzed. Socio-demographic information, biomedical variables, and dietary intakes were collected and fasting blood samples were analyzed for 25, hydroxycholecalciferol (25OHD), HbA1c, fasting plasma glucose (FPG), and lipid profiles. Logistic regression analyses were used to evaluate the association between tertiles of serum 25OHD and categories of FPG (&lt;5.6 mmol/L vs. 5.6±6.9 mmol/L), and HbA1c (&lt;5.7% vs. 5.7±6.4%). After adjusting for social, dietary, biomedical and metabolic syndrome (MetS) components (waist circumference, HDL cholesterol, triglycerides, and blood pressure), every 10 nmol/L increment in serum 25OHD significantly reduced the adjusted odds ratio (AOR) of a higher FPG [AOR 0.91, (0.86, 0.97); p = 0.002] and a higher HbA1c [AOR 0.94, (0.90, 0.98); p = 0.009]. Analysis by tertiles of 25OHD indicated that after adjustment for socio-demographic and dietary variables, those with high 25OHD (65±204 nmol/L) had reduced odds of a higher FPG [AOR 0.60, (0.43, 0.83); p = 0.008] as well as higher HbA1c [AOR 0.67, (0.53, 0.85); p = 0.005] compared to the lowest 25OHD (10±44 nmol/L) tertile. On final adjustment for other components of MetS, those in the highest tertile of 25OHD had significantly reduced odds of higher FPG [AOR 0.61, (0.44, 0.84); p = 0.011] and of higher HbA1c [AOR 0.74, (0.58, 0.93); p = 0.041] vs. low 25OHD tertile. Overall, the data support a direct, protective effect of higher 25OHD on FPG and HbA1c; two criteria for assessment of risk of T2DM