The candidate's overall goal for this mentored career development award is to gain the expertise and training to enable her to become an independent researcher in statistical genetics and bioinformatics, and to act as a facilitator for cross-discipline collaborative research. To achieve this aim, the candidate has compiled a mentoring team consisting of experts in a variety of fields, all of which have a proven track record of successful collaboration. Genome wide association (GWA) studies may result in hundreds, if not thousands, of SNPs showing significant association with the trait(s) under investigation. For many complex traits, such as obesity, there are arguably thousands of genuinely influential polymorphisms with small effects. Hence, one of the challenges that will be faced by investigators will be the selection and prioritization of SNPs from within the lengthy lists of apparently associated SNPs. Building upon research from related high-dimensional biology fields such as microarray based gene expression studies, the candidate proposes to address the issue of candidate gene selection and interpretation of GWA studies. The proposed research introduces the use of cluster analysis in GWA studies, which will group genes together based on their similarity derived from functional annotations such as Gene Ontology and biochemical pathway information. Specifically, the aims of this project are: 1) implement an automated procedure to identify genes in the study and retrieve annotation information, 2) cluster genes based on shared annotations, and 3) evaluate a battery of methods for determining which clusters of genes are associated with the phenotype. By testing the clusters, instead of all the markers in the study, the multiple test correction burden is decreased and power is increased. The identification of genetic contribution to complex diseases such as obesity, heart disease and diabetes will be key in developing an understanding and and [sic] possible treatments for the many health problems associated with these and other diseases. The methods utilized will be packaged as a web-based software which will be made freely available. The components of the mentored career development award will build upon the candidate's background in molecular biology, biochemistry and statistical genetics in order to yield an independent investigator capable of leading future research into the inheritance of human genetic diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01DK080188-04
Application #
8122169
Study Section
Diabetes, Endocrinology and Metabolic Diseases B Subcommittee (DDK)
Program Officer
Podskalny, Judith M,
Project Start
2008-09-01
Project End
2013-08-31
Budget Start
2011-09-01
Budget End
2013-08-31
Support Year
4
Fiscal Year
2011
Total Cost
$150,590
Indirect Cost
Name
University of Alabama Birmingham
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Aslibekyan, Stella; Vaughan, Laura K; Wiener, Howard W et al. (2016) Linkage and association analysis of circulating vitamin D and parathyroid hormone identifies novel loci in Alaska Native Yup'ik people. Genes Nutr 11:23
Vaughan, Laura Kelly; Wiener, Howard W; Aslibekyan, Stella et al. (2015) Linkage and association analysis of obesity traits reveals novel loci and interactions with dietary n-3 fatty acids in an Alaska Native (Yup'ik) population. Metabolism 64:689-97
Aslibekyan, Stella; Vaughan, Laura Kelly; Wiener, Howard W et al. (2013) Evidence for novel genetic loci associated with metabolic traits in Yup'ik people. Am J Hum Biol 25:673-80
Vaughan, Laura K; Srinivasasainagendra, Vinodh (2013) Where in the genome are we? A cautionary tale of database use in genomics research. Front Genet 4:38
Reynolds, Richard J; Cui, Xiangqin; Vaughan, Laura K et al. (2013) Gene expression patterns in peripheral blood cells associated with radiographic severity in African Americans with early rheumatoid arthritis. Rheumatol Int 33:129-37
Duarte, Christine W; Willey, Christopher D; Zhi, Degui et al. (2012) Expression signature of IFN/STAT1 signaling genes predicts poor survival outcome in glioblastoma multiforme in a subtype-specific manner. PLoS One 7:e29653
Kurreeman, Fina A S; Stahl, Eli A; Okada, Yukinori et al. (2012) Use of a multiethnic approach to identify rheumatoid- arthritis-susceptibility loci, 1p36 and 17q12. Am J Hum Genet 90:524-32
Shriner, Daniel; Vaughan, Laura Kelly (2011) A unified framework for multi-locus association analysis of both common and rare variants. BMC Genomics 12:89
Arnett, Donna K; Meyers, Kristin J; Devereux, Richard B et al. (2011) Genetic variation in NCAM1 contributes to left ventricular wall thickness in hypertensive families. Circ Res 108:279-83
Irvin, Marguerite Ryan; Shrestha, Sadeep; Chen, Yii-Der I et al. (2011) Genes linked to energy metabolism and immunoregulatory mechanisms are associated with subcutaneous adipose tissue distribution in HIV-infected men. Pharmacogenet Genomics 21:798-807

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