Shared Genomic Segment Analysis for Localizing Multiple Myeloma Genes

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DESCRIPTION (provided by applicant): Multiple myeloma (MM) is a hematologic malignancy. It is a cancer of the plasma cells characterized by the accumulation of malignant plasma cells in the bone marrow and increased production of a monoclonal immunoglobulin. It represents 1% of all cancers and is usually incurable with a median survival of about four years. It accounts for approximately 20% of deaths from hematologic malignancies and 2% of deaths from all cancers. Recent studies indicate that MM may be increasing in incidence and occurring at earlier ages. The etiology of MM is unclear; however evidence for a genetic component is compelling. In particular, there is strong evidence to suggest the existence of rare risk variants. Rare risk variants of large effect size may be relatively insignificant with regard to population attributable risk, but have immediate relevance for individuals identified to carry such variants. The discovery of a single rare risk variant for MM would provide immediate clinical impact. This proposal will focus on mapping these rare variants. We describe a high-risk pedigree design and a novel analysis technique that is specifically developed and has good power to detect rare risk variants. In contrast, the popular case-control association design has little or no power. Our study will therefore be advantageous to the field, and is highly complementary to other on-going efforts to localize common variants for MM, because it broadens the scope of the types of variants that may be identified. We will use the unique and powerful Utah Population Database (UPDB) that brings together population-based genealogical and cancer registry data to identify extended high-risk MM pedigrees to study. We will use our novel shared genomic segment method for analysis. This analysis considers only sampled, distantly related MM cases and poses the question as to whether the length of any shared genomic segment is longer than expected by chance. Theoretically, chance sharing in distant relatives is extremely improbable. High-risk pedigrees with at least 15 meioses between MM cases have the capacity for identifying genome wide statistically significant sharing. These regions are therefore good candidates for harboring rare risk variants. Our innovative approach to mapping risk variants for MM is high-risk because it has not been attempted previously, although we believe our preliminary studies clearly indicate that this approach has excellent potential. If successful, the high pay-off of the proposal is evident both in terms of gene localization for MM and in the proof-of-principal that our novel approach has a valuable role to play in gene finding in general. The immediate goal of this proposal is to localize rare risk variants for MM. The ultimate goal will be to identify the specific risk variants. The impact of such discoveries will be high and will lead to significant advances in treatment and control of this fatal disease. In particular, the identification of even a single rare, genetic biomarker with large effect size for MM, will be an important and critical discovery in the etiology of MM and could have immediate clinical relevance for detection and diagnosis. PUBLIC HEALTH RELEVANCE: This project will use novel methods to localize rare genetic biomarkers for multiple myeloma. If successful, the clinical implication for at-risk individuals in high-risk pedigrees would be the early detection and diagnosis of multiple myeloma. Knowledge of genetic risk factors is informative in general for increasing our understanding of disease etiology. Ultimately, the potential public health implications are significant improvements in detection, diagnosis, intervention, treatment and prevention of MM.