In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 73, No. 8_Supplement ( 2013-04-15), p. 4240-4240
Abstract:
Epigenome-wide association studies (EWAS) promise to advance our understanding of epigenetic variation in cancer and are made possible by the recent emergence of cost-effective high-throughput technologies. Blood is the most widely available source of genomic DNA that can be used for study of cancer-associated alterations in DNA methylation (DNAm). These analyses are complicated by the heterogeneity of blood, which represents multiple cell types with unique DNAm signatures. Shifts in immune profile could confound results since altered leukocyte numbers are common in response to exposures or disease. We applied a novel approach to blood-based EWAS, adjusting for leukocyte composition estimated by epigenetic deconvolution of blood. Normal human peripheral blood leukocytes (n = 47) were isolated by magnetic activated cell sorting and purity was confirmed by fluorescence activated cell sorting. DNAm was interrogated using the Infinium HumanMethylation27 BeadArray (Illumina) on the sorted leukocyte samples and peripheral blood samples from 3 independent case-control studies of bladder cancer (223 cases, 205 controls), head and neck squamous cell carcinoma (HNSCC; 92 cases, 92 controls), and ovarian cancer (131 cases, 274 controls). Differentially methylated loci associated with leukocyte lineage were identified using a series of linear mixed effects models fit to the DNAm data for each of the 26,486 autosomal CpGs for the sorted leukocytes, yielding an F-statistic for each locus. The subject-specific leukocyte distribution (vector ω) was estimated using constrained projections, as previously described by Houseman et al (2012). Several regression parameters were estimated: βj, representing the association of case-status and DNAm at CpG j, unadjusted for ω; αj, representing the corresponding association adjusted for ω, and Γ, the association of case-status and ω. Γ, β and α were each adjusted for age, sex and smoking for bladder cancer and HNSCC, and age for ovarian cancer. Statistical inference was achieved by permutation, where null distributions were obtained by permuting case-status with respect to DNAm values and other covariates, using an omnibus test adjusted for multiple-comparisons, constructed by comparing the observed average F-statistic across all CpGs to the corresponding quantity obtained from the permutation distribution. After adjusting for leukocyte composition (α), the association between DNAm and case-status was significant for all 3 studies (bladder cancer: p = 0.047; HNSCC: p = 0.013; ovarian cancer: p = 0.0002). Subsequent analyses revealed that cancer-associated pathways were overrepresented among significant loci. These results indicate cancer-specific variation in DNAm of peripheral blood, independent of immune cell shifts. Further research is indicated for elucidation of mechanisms driving these observations. Citation Format: Scott M. Langevin, E. A. Houseman, William P. Accomando, Devin C. Koestler, Brock C. Christensen, Heather H. Nelson, Margaret R. Karagas, Carmen J. Marsit, John K. Wiencke, Karl T. Kelsey. A novel approach to adjust for immune cell distribution in blood-based epigenome-wide association studies of cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4240. doi:10.1158/1538-7445.AM2013-4240
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2013-4240
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2013
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
Permalink
