We have an established program of research on genetic susceptibility in relation to disease risk. I collaborate with a number of PIs within the Epidemiology Branch to add measures of genetic susceptibility to their studies of reproductive, autoimmune, and neurologic diseases, while my own research continues to center primarily on bladder and prostate cancers. During the last few years my group has focused on DNA repair gene polymorphisms as we try to understand the risks and phenotypic consequences of the DNA repair gene polymorphisms that are being discovered by the NIEHS Environmental Genome Project. The large number of DNA repair genes (>200), coupled with the large number of polymorphisms (averaging >85 per gene) presents an increasingly daunting problem given that we have little or no information about the functional consequences of the polymorphisms, and do not yet have the technology to cheaply genotype thousands of polymorphisms in case-control studies. We are taking two approaches to simplify this problem: 1) we have been working to describe gene haplotypes (the specific combination of variant alleles) for DNA repair genes and 2) In order to find repair genotype-phenotype associations we are using single cell gel electrophoresis (the Comet assay) to measure rates of DNA repair phenotype in cells from a large sample of people where we have complete genotype (and now haplotype) information. We have started to apply our newly discovered haplotype information in our existing case-control studies, and are planning a new large study of prostate cancer. In addition, we are beginning to explore the use of SELDI proteomic profiling as a new molecular epidemiologic tool for understanding disease susceptibility. Last year's progress: Haplotype discovery: We characterized haplotypes in 107 genes using genotype data generated by the EGP from an ethnically diverse sample of 90 people. We find that although genes have many polymorphisms, most have only a few haplotypes and show surprisingly little evidence of recombination. The haplotypes of most genes have mutually exclusive sets of alleles and are shared across ethnic groups, suggesting that they are the consequence of ancient evolutionary bottlenecks prior to human migration out of Africa 100,000 years ago. These ancient haplotypes represent a simple organization to gene diversity that provides a 30-fold reduction in the genotyping requirements for studies of gene-disease association. Phenotypic measure of DNA repair in human populations: We have established the Comet assay in my laboratory to be able to measure levels of DNA damage in individual cells. We have adapted and extended this assay to measure rates of DNA repair in populations of cells. Using immortalized lymphocytes from the 90 people being resequenced as part of the EGP we are characterizing repair rates following damage with H2O2 and with MMS. Both exposures produce damage predominantly repaired via the base excision repair pathway. We have completed characterization of the first 65 individuals, and are working to finish the remaining 25. In addition, working in collaboration with David Dunson, we have developed new statistical methods for the analysis of Comet data and have one paper published, one submitted, and one in preparation on these methods. Prostate cancer study: I have obtained funding, as part of a $10M DOD Consortium with UNC and LSU to study DNA repair and hormone metabolism gene polymorphisms in relation ethnicity and prostate cancer aggressiveness. The Consortium project plans to enroll 2000 men with prostate cancer, half white, half black over the next 3 years. I am PI of the genetic susceptibility project and am a co-investigator, along with Alex Merrick and Ken Tomer from NIEHS, and others, on the SELDI proteomics project. Enrollment of patients should start in February 2004.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Intramural Research (Z01)
Project #
1Z01ES049033-07
Application #
6838352
Study Section
Epidemiology and Biometry Training Committee (EB)
Project Start
Project End
Budget Start
Budget End
Support Year
7
Fiscal Year
2003
Total Cost
Indirect Cost
Name
U.S. National Inst of Environ Hlth Scis
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Lu, Yingchang; Beeghly-Fadiel, Alicia; Wu, Lang et al. (2018) A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Cancer Res 78:5419-5430
Xu, Zongli; Langie, Sabine A S; De Boever, Patrick et al. (2017) RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip. BMC Genomics 18:4
Wilson, L E; Harlid, S; Xu, Z et al. (2017) An epigenome-wide study of body mass index and DNA methylation in blood using participants from the Sister Study cohort. Int J Obes (Lond) 41:194-199
Xu, Zongli; Taylor, Jack A; Leung, Yuet-Kin et al. (2016) oxBS-MLE: an efficient method to estimate 5-methylcytosine and 5-hydroxymethylcytosine in paired bisulfite and oxidative bisulfite treated DNA. Bioinformatics 32:3667-3669
Wilson, Lauren E; D'Aloisio, Aimee A; Sandler, Dale P et al. (2016) Long-term use of calcium channel blocking drugs and breast cancer risk in a prospective cohort of US and Puerto Rican women. Breast Cancer Res 18:61
Niu, Liang; Xu, Zongli; Taylor, Jack A (2016) RCP: a novel probe design bias correction method for Illumina Methylation BeadChip. Bioinformatics 32:2659-63
Xu, Zongli; Niu, Liang; Li, Leping et al. (2016) ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip. Nucleic Acids Res 44:e20
Wilson, Lauren E; Kim, Sangmi; Xu, Zongli et al. (2015) Non-Steroidal Anti-Inflammatory Drug Use and Genomic DNA Methylation in Blood. PLoS One 10:e0138920
Bensen, Jeannette T; Xu, Zongli; McKeigue, Paul M et al. (2014) Admixture mapping of prostate cancer in African Americans participating in the North Carolina-Louisiana Prostate Cancer Project (PCaP). Prostate 74:1-9
Harlid, Sophia; Xu, Zongli; Panduri, Vijayalakshmi et al. (2014) CpG sites associated with cigarette smoking: analysis of epigenome-wide data from the Sister Study. Environ Health Perspect 122:673-8

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