scholarly journals Predicting Later-Life Outcomes of Early-Life Exposures

2012 ◽  
Vol 120 (10) ◽  
pp. 1353-1361 ◽  
Author(s):  
Kim Boekelheide ◽  
Bruce Blumberg ◽  
Robert E. Chapin ◽  
Ila Cote ◽  
Joseph H. Graziano ◽  
...  
2017 ◽  
Vol 8 (5) ◽  
pp. 513-519 ◽  
Author(s):  
T. Bianco-Miotto ◽  
J. M. Craig ◽  
Y. P. Gasser ◽  
S. J. van Dijk ◽  
S. E. Ozanne

Developmental origins of health and disease (DOHaD) is the study of how the early life environment can impact the risk of chronic diseases from childhood to adulthood and the mechanisms involved. Epigenetic modifications such as DNA methylation, histone modifications and non-coding RNAs are involved in mediating how early life environment impacts later health. This review is a summary of the Epigenetics and DOHaD workshop held at the 2016 DOHaD Society of Australia and New Zealand Conference. Our extensive knowledge of how the early life environment impacts later risk for chronic disease would not have been possible without animal models. In this review we highlight some animal model examples that demonstrate how an adverse early life exposure results in epigenetic and gene expression changes that may contribute to increased risk of chronic disease later in life. Type 2 diabetes and cardiovascular disease are chronic diseases with an increasing incidence due to the increased number of children and adults that are obese. Epigenetic changes such as DNA methylation have been shown to be associated with metabolic health measures and potentially predict future metabolic health status. Although more difficult to elucidate in humans, recent studies suggest that DNA methylation may be one of the epigenetic mechanisms that mediates the effects of early life exposures on later life risk of obesity and obesity related diseases. Finally, we discuss the role of the microbiome and how it is a new player in developmental programming and mediating early life exposures on later risk of chronic disease.


2014 ◽  
Vol 45 (1) ◽  
pp. 244-259 ◽  
Author(s):  
Archana Chacko ◽  
David O. Carpenter ◽  
Leonie Callaway ◽  
Peter D. Sly

We have witnessed a change in disease patterns contributing to the global burden of disease, with a shift from early childhood deaths due to the classic infectious communicable diseases to years lived with disability from chronic noncommunicable diseases. In both developing and developed countries, the years lived with disability attributable to chronic disease have increased: cardiovascular diseases by 17.7%; chronic respiratory disease by 8.5%; neurological conditions by 12.2%; diabetes by 30.0%; and mental and behavioural disorders by 5.0% over the past 20 years. Recognition of the contribution made by adverse environmental exposures in early life to noncommunicable diseases in later life is increasing. These early-life exposures appear to contribute to both chronic respiratory and chronic nonrespiratory diseases. In this State of the Art article, we aim to examine early-life environmental exposures that have an epidemiological association with chronic nonrespiratory diseases, such as obesity and type II diabetes, cardiovascular disease, and neurocognitive and behavioural problems. We will highlight the potential overlap in environmental risks with respiratory diseases, and point out knowledge gaps and research opportunities.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254174
Author(s):  
Michael Topping ◽  
Jinho Kim ◽  
Jason Fletcher

Objective Accumulating evidence suggests the possibility that early life exposures may contribute to risk of Alzheimer’s Disease (AD). This paper explores geographic disparities in AD mortality based on both state of residence in older age as well as state of birth measures in order to assess the relative importance of these factors. Methods We use a subset of a large survey, the NIH-AARP Diet and Health Study, of over 150,000 individuals aged 65–70 with 15 years of mortality follow-up, allowing us to study over 1050 cases of AD mortality. We use multi-level logistic regression, where individuals are nested within states of residence and/or states of birth, to assess the contributions of place to AD mortality variation. Results We show that state of birth explains a modest amount of variation in AD mortality, approximately 4%, which is consistent with life course theories that suggest that early life conditions can produce old age health disparities. However, we also show that nearly all of the variation from state of birth is explained by state of residence in old age. Conclusions These results suggest that later life factors are potentially more consequential targets for intervention in reducing AD mortality and provide some evidence against the importance of macro-level environmental exposures at birth as a core determinant of later AD.


2015 ◽  
Vol 100 (11) ◽  
pp. 1058-1063 ◽  
Author(s):  
Thomas C Williams ◽  
Amanda J Drake

The process whereby early exposure to an adverse environment has an influence on later life outcomes has been called ‘early life programming’. While epidemiological evidence for this has been available for decades, only in recent years have the mechanisms, in particular epigenetic modifications, for this process begun to be elucidated. We discuss the evidence for early life programming, the possible mechanisms, how effects may be transmitted across generations, and conclude by looking at some examples relevant to general paediatrics.


2019 ◽  
Author(s):  
Tyler W. Watts ◽  
Greg J. Duncan

Longitudinal studies of development often rely on correlational methods to examine linkages between early-life constructs and later-life outcomes. As highlighted by responses to our article, “Revisiting the Marshmallow Test: A Conceptual Replication Investigating Links Between Delay of Gratification and Later Outcomes,” interpretations of these linkages can be difficult. In this commentary, we address criticisms that our approach “over-controlled” for key factors related to a child’s ability to delay gratification, allay concerns over multicollinearity, and discuss how multivariate regression techniques can help clarify the interpretation of observed predictive relations.


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