This study is designed to maximize the likelihood of identifying genes responsible for the etiology of Chronic Lymphocytic Leukemia (CLL), a blood cancer. We propose to do this through a family-based study of 200 high-risk CLL pedigrees using a dense map of genetic markers. Since no single institution is able to collect this many pedigrees, mapping susceptibility genes for CLL will only be possible through a collaborative effort. As such, we have formed a multicenter, multidisciplinary team of experienced investigators. Through our concerted effort, our Genetic Epidemiology of CLL (GEC) consortium will develop into a family-based gene-discovery research resource that will be positioned to identify and characterize genetic risk of CLL. Moreover, given that other blood and lymph node disorders may arise from a common stem cell, the genetic information identified through this Consortium may provide important insight about the genetics of other blood and lymph node disorders and about cancer susceptibility in general. As a Consortium, our primary aims are (Aim 1) to ascertain high-risk CLL families for genetic linkage analysis. Investigators from each recruitment center will screen CLL patients in the clinic to identify and ascertain those patients who have a family history of CLL. In addition, CLL patients with a family history of CLL will be identified through the CLL Research Consortium (CRC), a consortium that identifies and tests promising therapies for CLL patients. Living relatives of identified CLL patients with a family history of CLL will then be recruited into our study. Biospecimens and risk-factor data will be obtained from all consented subjects.
(Aim 2) To ascertain precursor CLL individuals who are selected from the high-risk CLL families identified in Aim 1. We will conduct four-color flow cytometry on 200 unaffected first-degree relatives of CLL patients from a subset of the high-risk CLL families identified in Aim 1. Fresh blood will be used, and one lab will perform all flow cytometry tests, providing data quality assurance. The collected information will be used in Aim 3 to increase the statistical power to detect linkage and will also provide the basis for future translational studies.
(Aim 3) To carry out a genomic screen to map the chromosomal location of the gene or genes that increase susceptibility to CLL. Using a high-density panel of single nucleotide polymorphisms that are distributed across all chromosomes, we will genotype all individuals from the high-risk CLL pedigrees identified in Aim 1. We then will perform linkage analyses to identify chromosomal locations that are found to be linked with CLL. Our Secondary Aim is to fine map genetic regions identified through linkage analysis. We expect to identify at least one significant chromosomal region through the linkage analysis conducted in Aim 3. We will then fine map these regions by genotyping additional markers within the regions.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA118444-04
Application #
7661362
Study Section
Special Emphasis Panel (ZRG1-HOP-N (02))
Program Officer
Seminara, Daniela
Project Start
2006-08-23
Project End
2011-07-31
Budget Start
2009-08-01
Budget End
2010-07-31
Support Year
4
Fiscal Year
2009
Total Cost
$630,646
Indirect Cost
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
Wang, Sophia S; Carrington, Mary; Berndt, Sonja I et al. (2018) HLA Class I and II Diversity Contributes to the Etiologic Heterogeneity of Non-Hodgkin Lymphoma Subtypes. Cancer Res 78:4086-4096
Tian, Shulan; Yan, Huihuang; Klee, Eric W et al. (2018) Comparative analysis of de novo assemblers for variation discovery in personal genomes. Brief Bioinform 19:893-904
Zhou, Weiyin; Goldin, Lynn; Wang, Mingyi et al. (2018) Combined somatic mutation and copy number analysis in the survival of familial CLL. Br J Haematol 181:604-613
Law, Philip J; Berndt, Sonja I; Speedy, Helen E et al. (2017) Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia. Nat Commun 8:14175
Berndt, Sonja I; Camp, Nicola J; Skibola, Christine F et al. (2016) Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia. Nat Commun 7:10933
Tian, Shulan; Yan, Huihuang; Neuhauser, Claudia et al. (2016) An analytical workflow for accurate variant discovery in highly divergent regions. BMC Genomics 17:703
Tian, Shulan; Yan, Huihuang; Kalmbach, Michael et al. (2016) Impact of post-alignment processing in variant discovery from whole exome data. BMC Bioinformatics 17:403
Machiela, Mitchell J; Lan, Qing; Slager, Susan L et al. (2016) Genetically predicted longer telomere length is associated with increased risk of B-cell lymphoma subtypes. Hum Mol Genet 25:1663-76
Cerhan, James R; Slager, Susan L (2015) Familial predisposition and genetic risk factors for lymphoma. Blood 126:2265-73
Sun, Zhifu; Cunningham, Julie; Slager, Susan et al. (2015) Base resolution methylome profiling: considerations in platform selection, data preprocessing and analysis. Epigenomics 7:813-28

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