Pooling and expansion of Chronic Lymphocytic Leukemia GWA data

PROJECT SUMMARY (See instructions): Chronic lymphocytic leukemia (CLL) is a neoplasm of the blood and is the most common form of adult leukemia in Caucasians in the Western countries. The evidence is great that a genetic component exists in the etiology of CLL, with the disease having amongst the highest familial risk of any cancer. Paradoxically despite this strong familial basis, the genetics of CLL disease is largely unknown. Further, there is profound heterogeneity in the clinical outcome among early-stage CLL patients. Biological characteristics of CLL have been found to predict survival in these early-stage patients, but to date, the role of inherited genetic variation as a determinant of CLL prognosis has received scant attention. Previous genetic studies have had limited success in elucidating the genetic components of CLL risk and progression, in large part due to low statistical power. Because CLL is relatively rare with approximately 4.1 new cases per 100,000 persons per year, a pooling effort is needed to achieve requisite statistical power. We have the opportunity to address this need efficiently and rapidly by exploiting four CLL studies with genome-wide association (GWA) data. In this application, we propose to maximize the sample size by combining data from four CLL GWA studies that are available, thereby providing data on approximately 3000 CLL cases and 13,000 controls. In addition, we will investigate the genetic determinants of CLL survival and progression in studies for which follow-up data is available. This research effort will yield an unprecedented genetic study of CLL risk and prognosis. Our Specific Aims are: (Aim 1) To combine data from four GWA studies in order to identify genetic variants associated with CLL risk. (Aim 2) To perform fine mapping of confirmed loci from Aim 1 to further refine and potentially identify causal variants. (Aim 3) To use the combined GWA data from Aim 1 in order to identify genetic variants that are associated with CLL prognosis. Our proposal combines genotype and phenotype data from four GWA studies. These studies constitute unique and synergistic resources that afford us the opportunity to efficiently test our hypotheses with the potential for rapid application. At the completion of this project, we expect to identify additional novel loci influencing CLL risk that could not have been identified by the individual GWA studies, improve the evidence of associations of findings identified from individual studies, and identify novel loci influencing CLL prognosis. Collectively, our findings will provide for a better understanding of CLL pathobiology and may lead to novel therapeutic approaches to treating CLL, as well as the development of etiological hypotheses.