Neuroendocrine factors have been convincingly implicated in the etiology of obesity. Although genome-wide association studies (GWAS), have identified scores of genes and loci associated with obesity, insight into the functional roles for these genes, particularly within the human brain, is lacking. Many brain banks do not have a single body mass index (BMI) measure. However, brain donation programs within longitudinal, cohort studies represent a unique resource of brain samples with up to six decades of ante-mortem data including BMI. This proposal is a collaboration among three such longitudinal cohort studies: 1) The Framingham Heart Study (FHS) 2) The Religious Order Study (ROS) and 3) the Memory and Aging Project (MAP). Selection from over 1,300 post mortem brain samples already donated via these studies enabled identification of 75 samples from consistently obese individuals and 75 samples from individuals with consistently normal BMI (18.5
In Aim 2 we will integrate the genome-wide SNP and transcriptome data to perform eSNP, eQTL, and pathway analyses to identify underlying biological mechanisms. These studies will provide insight into the role of genes in the initiation and pathophysiology of obesity and create a valuable public database containing comprehensively characterized regional gene expression in brain in a cohort of comprehensively phenotypically characterized participants.
RNA sequencing is a method to measure how much each gene within humans are being expressed. Gene expression may differ among tissues, such as different parts of the brain. We are proposing to measure gene expression in brains donated upon death by participants of the Framingham Heart Study, the Religious Orders Study, and the Memory and Aging Project who have been examined regularly for up to 60 years. We propose to compare if gene expression differs across two specific brain regions and to determine if gene expression is associated with whether or not the participants were consistently obese over many years or consistently normal weight. This study will help understand the genetic basis of obesity.
|Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H et al. (2017) Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis. BMC Bioinformatics 18:91|
|Wake, Christian; Labadorf, Adam; Dumitriu, Alexandra et al. (2016) Novel microRNA discovery using small RNA sequencing in post-mortem human brain. BMC Genomics 17:776|