Principal Investigator: Professor John Witte
Department: Epidemiology and Biostatistics
University of California, San Francisco. Epidemiology and Biostatistics, Room 388, Helen Diller Family Cancer Center, 1450 3rd Street, San Francisco CA 94158, United StatesTags: 14105, cancer, genetics, heritability, pleiotropy
1a: The goal of our proposed research is to characterize pleiotropic loci in order to gain new insight into common carcinogenic mechanisms, shared etiology of multiple cancers, and treatment for cancer patients with seemingly distinct diseases. The UK cohort currently holds 80K subjects across multiple malignant cancer types. We propose to comprehensively assess the shared genetic basis underlying these different cancers within the UK cohort through the following aims: 1) Assess the co-inheritance of cancers due to common variation. 2) Evaluate locus-specific pleiotropy across different cancers.
1b: The detection and characterization of pleiotropy is key to understanding the biological and clinical underpinnings of cancer. While any single pleiotropic variant may have modest impact on disease, combinations of multiple variants can provide increasingly accurate prediction and be important for individualized risk counseling as well as for cancer screening and surveillance. Even where there already exist clinically relevant findings for individual cancers, our efforts to detect pleiotropy may provide an avenue for informing the successful development and application of treatments across cancers.
1c: Genotyping of all cancer subjects on the Affymetrix array is close to completion for the UK biobank subjects, and data on per subject cancer type is already available. We will use these data to determine genome-wide heritability for the most common cancers in the UK cohort, and calculate the co-inheritance and overall shared genomic basis among these cancers using complex statistical analysis methods.
1d: We request the full genotyped cohort.
We also propose to expand our research to characterizing the individual and shared genetic basis of other health-related diseases and their risk factors. The latter will include cardiovascular and cerebrovascular diseases (e.g., blood pressure/hypertension, lipids/lipidemia), serum (blood) chemistry, hearing impairment, obesity, glaucoma, macular degeneration, and other eye diseases, arthritis, osteoporosis, diabetes, dementia, alzhiemer’s disease, mortality.
Complex statistical analysis methods will be used. These include heritability and co-heritability analysis with Genome-wide Complex Trait Analysis, linear/logistic/time-to-onset analysis and with mixed models, pleiotropic models that we will develop, and other methods development.