Congenital heart defects (CHDs) are the leading causes of infant morbidity and mortality attributable to birth defects, affecting about 1% of all live births. The majority of CHDs are thought to be caused by a complex interplay among maternal genes, fetal genes and maternal environmental exposures. However, the disease etiology is largely unknown, and few strategies are available to reduce the burden of disease. To understand the genetic susceptibility of CHDs, most studies have evaluated individual genetic variants or maternal environmental factors one at a time. Less attention has been given to the identification of complex interactions among them. In this proposed project, we will focus on the identification of gene-by-gene (GXG) or gene-by- environment (GXE) interactions that may jointly influence CHD risk. The findings will shed light on various types of interactions during embryogenesis: 1) GXG interactions between maternal and fetal genes; 2) GXG interactions within maternal or fetal genes; and 3) complex interactions among maternal genes, fetal genes and maternal environmental exposures. The discovery process of GXG and GXE interactions is enhanced by the development of innovative biostatistical approaches and their application to samples from the National Birth Defect Prevention Study (NBDPS). In the proposed projects, we will use datasets from an ongoing genome-wide association study (GWAS) of CHDs, including ~1,000 case mother-father-infant triads and ~1,000 control mother-infant dyads (5,000 subjects in total) who are participants of NBDPS. Each sample is genotyped for approximately 5 million single nucleotide polymorphisms (SNPs) throughout the genome. The proposed project will be initiated by an early stage new investigator, who have developed novel biostatistical approaches for the GXG or GXE discovery process, and has applied these approaches to identify and replicate statistically significant GXG interactions predisposing to various complex human diseases, such as nicotine dependence, cannabis dependence, type II diabetes, small for gestational age and congenital heart defects. The proposed project is further enhanced by assembling a research team of senior scientists with complementary and extensive expertise in the field. The findings ultimately will provide insights into the underlying pathophysiological and etiological processes that result in CHDs, and more importantly, can provide a foundation for more precise preconceptional counseling and interventions.
The genetic and environmental determinants that influence the risk of congenital heart defects remain unclear. In the proposed project, we will develop innovative biostatistical approaches and apply them to identify gene-by-gene and gene-by-environment combinations that may jointly influence the disease risk. The finding of this proposed study may lead to more precise preconceptional counseling and interventions.
| Li, Ming; He, Zihuai; Tong, Xiaoran et al. (2018) Detecting Rare Mutations with Heterogeneous Effects Using a Family-Based Genetic Random Field Method. Genetics 210:463-476 |
