Identifying Regulatory Variants Associated with Maternal Hyperglycemia

识别与母亲高血糖相关的调节变异

基本信息

批准号：
8983217
负责人：
Cong Guo
金额：
$ 3.39万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-07-17 至 2016-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8983217
关键词：
Adult Affect Alleles Binding Binomial Model Biological Assay Caribbean region Cell Line Cell model Child Childhood Chromosome Mapping Clustered Regularly Interspaced Short Palindromic Repeats Complex Computer Simulation DNA DNA-Protein Interaction Data Diabetes Mellitus Diagnostic Disease Electrophoretic Mobility Shift Assay Elements Environmental Risk Factor European Fetus Future Gene Expression Genes Genetic Genetic Variation Genetic study Genotype Gestational Diabetes Glucose Haplotypes Health HepG2 Hispanics Hour Human Hyperglycemia In Vitro Individual Introns Lead Libraries Life Lipids Measures Metabolic Metabolic Diseases Metabolism Methodology Methods Modeling Mothers Nucleic Acid Regulatory Sequences Obesity Outcome Pathway interactions Patients Phenotype Plasma Population Positioning Attribute Pregnancy Publishing Regulatory Element Reporter Research Risk Sampling Statistical Models System Testing Tissues Transcription factor genes Uncertainty Untranslated RNA Variant Woman Work Youth base cohort cost design genetic variant genome editing genome wide association study hexokinase impaired glucose tolerance in vivo novel novel diagnostics obesity risk offspring public health relevance trait transcription factor

项目摘要

DESCRIPTION (provided by applicant): Gestational diabetes mellitus (GDM), diabetes which occurs during pregnancy, affects about 3-10% of mothers. Offspring of mothers with pre-existing diabetes or GDM are at risk for developing metabolic disorders such as obesity and diabetes in childhood and later in life. Maternal glucose levels less than those of diagnostic GDM may impose similar risks to the child. Maternal metabolism is determined by both genetic and environmental factors. To define genetic factors that impact maternal metabolism, we used genetic mapping to identify non-coding genetic variants within a locus containing the gene hexokinase domain containing 1 (HKDC1) to be associated with 2 hour maternal glucose levels during pregnancy. We hypothesize that genetic variation in these non-coding regions act through altered gene expression and predict maternal glucose levels during pregnancy. We will test that hypothesis in three specific aims. First, we aim to identify functional non-coding geneti variants from directly from donor DNA using a high throughput reporter system. The advantage of assaying donor DNA directly is the ability to identify not only common, but also rare and personal regulatory variants and relate them directly with phenotype. Second, we will use our results to generate a model that can predict individual maternal glucose levels based on regulatory haplotypes. The outcome will be a population-scale association between allele-specific activity and phenotype. Third, we will identify transcription factors and genes that are affected by regulatory variation, which may lead to the discovery of new diagnostic markers and/or druggable targets. The expected outcomes are that we will identify regulatory mechanisms regulating maternal glucose levels, and demonstrate a working methodology in a patient cohort. Doing so will have immediate positive impacts on identifying mothers at risk for metabolic disease and new pathways for downstream studies. Meanwhile, the methods developed will be transferrable to study regulatory mechanisms of other human phenotypes without the need for primary tissues.

描述（由申请人提供）：妊娠糖尿病（GDM）发生在预性期间，会影响约3-10％的FFSPRING。诊断GDM的葡萄糖降低可能与儿童施加类似的风险。 1 EL在怀孕期间，我们假设这些非编码区域的遗传变异改变了基因表达，并预测孕妇在怀孕期间的母体葡萄糖水平。。在特异性活性和表型之间，我们将确定区域变化的转录因子和基因，发现新的诊断标记和/或可药物的靶标。关于代谢性疾病的促进和下游研究的途径。