The metabolic syndrome (MetS) is a cluster of phenotypes that includes type 2 diabetes (T2D), obesity, hypertension, and dyslipidemia. These phenotypes show dramatic increases in prevalence in populations that recently switched from a traditional subsistence to a Western lifestyle and diet. A compelling hypothesis envisions that the disease risk genotypes result from metabolic adaptations to the diverse environments of ancestral human populations. Based on this hypothesis, the susceptibility variants for the MetS are expected to have distinct patterns of population genetics variation. The parent grant integrated the empirical characterization of patterns of variation with the development of new statistical methodology and population genetics modeling to elucidate the evolutionary origin of the the MetS. In this supplement, we plan to combine those population genetics approaches with functional genomics analyses to elucidate the genetic basis of inter-individual variation in glucocorticoid (GC) response. GCs, such as cortisol, are stress hormones that modulate a large number of physiological actions. Growing clinical evidence and animal studies have linked GC action with obesity and insulin resistance. Thus, genetic variation in the physiologic GC response is likely to influence the genetic susceptibility to the MetS. Building on recent developments in the area of expression quantitative trait locus (eQTL) mapping, we will take advantage of a panel of lymphoblastoid cell lines (LCLs) of unrelated individuals from different ethnic groups to map the genetic bases of inter-individual variation in GC response as follows: 1. We will identify the GR binding sites (by ChIPseq) at the genome-wide levels in LCLs;2. We will map the genetic variants associated with inter-individual variation in GC-mediated transcriptional response by assaying genome-wide mRNA levels in European and African LCLs following treatment with either a GC (i.e. dexamethasone) or with the vehicle (i.e. EtOH) as a control;3. We will perform population genetics analyses to determine if the genetic variants identified in aim 2 differ significantly in frequency across ethnic groups and if they were targets of selection during human evolution. This supplement builds on results obtained under the parent grant to take a new direction that exploits recently developed resources for genetic analysis. While the ultimate goal of the project remains unchanged, i.e. to understand the evolutionary genetics of the MetS, we now plan to add a functional genomics dimension and integrate it with the ongoing population genetics analyses.
This project aims to develop and use an experimental system to study the genetic bases of inter-individual and inter-ethnic variation in the physiological response to environmental stress, and in particular in the response to glucocorticoids. This response is key to the susceptibility to a number of common metabolic disorders in humans, including type 2 diabetes, obesity and hypertension. Therefore, this study is likely to help understand the susceptibility to these disorders and develop new treatments.
| Maranville, J C; Baxter, S S; Torres, J M et al. (2013) Inter-ethnic differences in lymphocyte sensitivity to glucocorticoids reflect variation in transcriptional response. Pharmacogenomics J 13:121-9 |
| Maranville, Joseph C; Baxter, Shaneen S; Witonsky, David B et al. (2013) Genetic mapping with multiple levels of phenotypic information reveals determinants of lymphocyte glucocorticoid sensitivity. Am J Hum Genet 93:735-43 |
| Luca, Francesca; Maranville, Joseph C; Richards, Allison L et al. (2013) Genetic, functional and molecular features of glucocorticoid receptor binding. PLoS One 8:e61654 |
| Hancock, Angela M; Witonsky, David B; Alkorta-Aranburu, Gorka et al. (2011) Adaptations to climate-mediated selective pressures in humans. PLoS Genet 7:e1001375 |
| Maranville, Joseph C; Luca, Francesca; Richards, Allison L et al. (2011) Interactions between glucocorticoid treatment and cis-regulatory polymorphisms contribute to cellular response phenotypes. PLoS Genet 7:e1002162 |
| Luca, Francesca; Hudson, Richard R; Witonsky, David B et al. (2011) A reduced representation approach to population genetic analyses and applications to human evolution. Genome Res 21:1087-98 |
| Sucheston, Lara; Witonsky, David B; Hastings, Darcie et al. (2011) Natural selection and functional genetic variation in the p53 pathway. Hum Mol Genet 20:1502-8 |
| Hancock, Angela M; Clark, Vanessa J; Qian, Yudong et al. (2011) Population genetic analysis of the uncoupling proteins supports a role for UCP3 in human cold resistance. Mol Biol Evol 28:601-14 |
| Coop, Graham; Witonsky, David; Di Rienzo, Anna et al. (2010) Using environmental correlations to identify loci underlying local adaptation. Genetics 185:1411-23 |
| Pritchard, Jonathan K; Di Rienzo, Anna (2010) Adaptation - not by sweeps alone. Nat Rev Genet 11:665-7 |
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