Identification and Evolutionary Analysis of Potential Candidate Genes in a Human Eating Disorder.
Ubadah SabbaghSaman MullegamaGerald J WyckoffPublished in: BioMed research international (2016)
The purpose of this study was to find genes linked with eating disorders and associated with both metabolic and neural systems. Our operating hypothesis was that there are genetic factors underlying some eating disorders resting in both those pathways. Specifically, we are interested in disorders that may rest in both sleep and metabolic function, generally called Night Eating Syndrome (NES). A meta-analysis of the Gene Expression Omnibus targeting the mammalian nervous system, sleep, and obesity studies was performed, yielding numerous genes of interest. Through a text-based analysis of the results, a number of potential candidate genes were identified. VGF, in particular, appeared to be relevant both to obesity and, broadly, to brain or neural development. VGF is a highly connected protein that interacts with numerous targets via proteolytically digested peptides. We examined VGF from an evolutionary perspective to determine whether other available evidence supported a role for the gene in human disease. We conclude that some of the already identified variants in VGF from human polymorphism studies may contribute to eating disorders and obesity. Our data suggest that there is enough evidence to warrant eGWAS and GWAS analysis of these genes in NES patients in a case-control study.
Keyphrases
- genome wide
- endothelial cells
- gene expression
- weight loss
- bioinformatics analysis
- metabolic syndrome
- insulin resistance
- dna methylation
- type diabetes
- copy number
- physical activity
- weight gain
- genome wide identification
- induced pluripotent stem cells
- high fat diet induced
- pluripotent stem cells
- sleep quality
- ejection fraction
- newly diagnosed
- end stage renal disease
- white matter
- electronic health record
- amino acid
- genome wide analysis
- heart rate variability
- smoking cessation
- depressive symptoms
- transcription factor
- body mass index
- skeletal muscle
- blood pressure
- machine learning
- cancer therapy
- prognostic factors
- case control
- small molecule
- peritoneal dialysis
- functional connectivity
- sewage sludge
- patient reported
- subarachnoid hemorrhage