Identifying Genetic Variants

The identification of inherited genetic risk variants is critical in understanding disease mechanisms. However, such discoveries are challenging for complex diseases. Novel methods and study designs play essential roles in addressing these challenges. Certainly there is no guarantee that a new method will produce a leap of knowledge; however, it can be high-impact and cutting edge when it does. The hope is that a better understanding of inherited genetic risk will lead to improvements in prevention, detection, diagnosis, and treatment strategies.

Our Lab Focus

The main focus of research in the Camp Lab is the identification of germ-line genetic variants that increase susceptibility to disease, with specific interests in breast cancer, chronic lymphocytic leukemia (CLL) and multiple myeloma (MM). Importantly, Camp's work includes both the development of novel statistical genetic approaches in addition to the application of such methods in applied gene-finding projects.

There is a natural and powerful synergy in the integration of the theoretical and the applied. Both can be ineffective in isolation: brilliant new methodological ideas can fail if they are too abstract, lack interpretability and ignore "real life" data issues; and while standard methods may identify "low-hanging fruit", these methods may not apply to all data structures and likely ignore other important dimensions of the problem.

Major Obstacles to Identifying Novel Risk Variants

Arguably two of the major obstacles to identification of novel risk variants are genetic and disease heterogeneity. Hence, these sources of heterogeneity often drive the types of statistical genetic techniques and study designs pursued. For example, current interests include the incorporation of gene-expression (or other molecular-level phenotypic data) with germ-line genetic data (high-density SNP and/or sequencing data) in novel methods for risk variant identification. Due to the unique and powerful genealogical resources available in Utah (the Utah Population Database, or UPDB), these methods also often include an emphasis on high-risk pedigrees.

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