HW Week 3

HW Week 3

by Helen Weng -
Number of replies: 1
  1. Weaver et al propose that among rats, maternal behavior towards newborn pups influences their cortisol response to stress via epigenetic mechanisms that change the expression of glucocorticoid receptor gene for the rest of the pup’s life.  They argue that because epigenetic patterns are established at specific developmental periods, there is extreme time sensitivity to when the pup is exposed to particular maternal behaviors (licking and grooming, in this case), and maternal behavior before or after that sensitive period window is not as important.   Do you think this mechanism is relevant in humans?  If so, what behaviors are most analogous to “maternal licking and grooming”? 

1. I do think this mechanism is related in humans. Research with children raised in orphanages and then are adopted show that the critical window seems to be around 3 years old.  If children are adopted before the age of 3, they show less negative effects compared to those after the age of 3. I think behaviors that are most analogous to “maternal licking and grooming” are frequency and quality of maternal parental-baby touch through breast feeding, burping, holding, comforting, kissing, etc. Additional channels of information may be important for parental-baby interactions such as facial expression interaction and vocalizations (cooing, talking).

 2. Gruenewald, in contrast, emphasize the cumulative effects of SES adversity on a multi-system allostatic load measure.   Do you think that the Gruenewald findings are consistent, inconsistent, or unrelated to the Weaver findings?  Explain. 

2. I think the Guenewald findings can be integrated with the Weaver findings, and that there may be sensitive windows (such as very early childhood), as well as subsequent cumulative effects, e.g., “wear and tear” on physiological systems.  Hardship during sensitive periods may put people in a certain range of allostatic load, and then depending on subsequent experiences, a cumulative effect may occur.  This may be better identified using an interaction model and more sensitive measures of allostatic load across multiple time points.  The Gruenewald paper identified childhood SES through retrospective self-reports, and only indicated overall childhood rather than potentially sensitive periods during childhood. Furthermore, some of the reports were measured by subjective relative status compared to others (financial level growing up – worse off than others, about the same as others, better than others), which may reflect the subjective experience of their financial status but less about objective status (e.g., did they have enough money to pay basic bills).

 

3. Hertzmann and Boyce argue that “it is not genes or environment, nor is it genes and environment, but rather it is gene-by-environment interactions that influence developmental trajectories.”  To what extent do you think that GxE interactions can contribute to major disparities along racial/ethnic, socioeconomic, or geographic dimensions?

3. Gene by Environment interactions may contribute to disparities in race and ethnicity due to many of the resources being controlled by the dominant race (White race within the U.S.), which may favor environments that benefit genetic variations within that particular race. For example, if there is a type of grain that is more easily digestible by the dominant race, and they control most of the resources, they may set up the agricultural system to favor that kind of grain. In other races, their genetics may not favor digestion of that grain, which may result in health disparities such as greater susceptibility to food allergies (this is not my area, so not sure if this is biologically feasible, just thinking out a potential example).

In reply to Helen Weng

Re: HW Week 3

by Maria Glymour -

Helen,

Thanks for these comments.  Measurement of childhood SES is a major challenge because you can either link back to administrative records (e.g., birthweight, school records, but generally limited options), use a physical measure such as anthropometrics that likely reflects childhood conditions (which is indicative but is quite crude), or ask people.   You can ask people objective facts, like parent's education, which they may or may not be able to accurately report, or subjective perceptions, like standing in the community.  There's reason to believe that both the objective and subjective measures of adult SES are relevant, so also plausible that both measures in childhood are relevant.  But the concerns about retrospective reporting of subjective childhood SES seem more troubling to me than retrospective reporting of objective indicators.

Regarding GxE - I want to be very clear that GxE interactions can contribute to racial disparities in health even if there are no racial differences in minor allele frequencies whatsoever.  If the frequency of a genetic variant that makes eating Big Macs and fries (call it FTO) is equally prevalent in whites and blacks, but residential segregation makes it much more likely that blacks have convenient access to McDonald's offerings, then the GxE will differentially affect obesity in blacks. The FTO variant is most relevant if you live in an obesogenic environment, and disadvantaged groups are more likely to live in obesogenic environments. You can link this back to fundamental cause theory: one way people use social advantages such as money, networks, or education is to overcome genetic vulnerabilities.  

Here's an article you might find relevant. 

Liu SY, Walter S, Marden J, Rehkopf DH, Kubzansky LD, Nguyen T, Glymour MM. Genetic vulnerability to diabetes and obesity: does education offset the risk?. Social science & medicine. 2015 Feb 28;127:150-8.  https://ucsf.idm.oclc.org/login?url=http://dx.doi.org/10.1016/j.socscimed.2014.09.009

Maria