Secondary analysis and risk prediction of dental caries and oral clefts

University Of Alabama At Birmingham, Birmingham AL

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Abstract

? DESCRIPTION (provided by applicant): Dental caries (i.e., dental cavities or tooth decay) and orofacial clefts cause tremendous public health burdens for patients, their families, and society. In addition to direct costs from treatment, the quality of life of the affected individuals and ther families is greatly affected. The etiology of dental caries and orofacial clefts has been studied extensively, and both environmental and genetic factors have been implicated in their risks. Despite some success in the study of genetic factors of caries and oral clefts, there is still a large portion of the heritability missing (i.e., not explained by the identified genetic variants. In addition, translating the knowledge gained from scientific studies into clinical practice has been recognized as an essential step toward future personalized healthcare, but even more is lacking in this area. Such a lack of research on the risk prediction of dental caries and orofacial clefts needs to be addressed urgently given the critical role of the mouth and teeth in our daily lives. The long-term goals are to improve understanding of the mechanisms leading to the development of dental and craniofacial disorders and to use the scientific findings to aid clinical practice. The objectives of this application are to identify novel genetic variants contributing to dental caries and orofacial clefting and to use the results (from our study and others in the literature) to predict the risk of their occurring. The planned specific aims are as follows. (1) Identify new genetic variants associated with dental caries and orofacial clefts by analyzing existing data from genome-wide association studies using novel statistical methods. Based on a literature review and our own previous experience, we postulate that there are as yet unidentified genetic variants affecting the risks of dental caries and orofacial clefts and that these variants can be identified by using powerful statistical models. (2) Develop and validate high- dimensional, family-based Bayesian models to predict the risks of dental caries and orofacial clefts. Currently there is a great need for-but lack of-approaches that can accurately predict disease risk in clinical practice. This aim is to address this critical need for dental cares and orofacial clefts. With respect to expected outcomes, the successful completion of Aim 1 will lead to new discoveries about the etiology of dental caries and orofacial clefts, and in particular about novel genes and gene x environment interactions that affect risk of their occurrence. The work proposed in Aim 2 is expected to provide powerful statistical models to predict the risks of dental caries and orofacial clefts that can aid decision making in clinical practice. Such results are expected to have an important positive impact because the expected results will expand our understanding and ultimately enhance our ability to decipher the genetic basis of dental caries and orofacial clefts and help us to better understand, accurately predict, efficiently prevent, diagnose, and treat them.