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Integrating pathway analysis and genetics of gene expression for genome-wide association study of basal cell carcinoma

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Abstract

Genome-wide association studies (GWASs) have primarily focused on marginal effects for individual markers and have incorporated external functional information only after identifying robust statistical associations. We applied a new approach combining the genetics of gene expression and functional classification of genes to the GWAS of basal cell carcinoma (BCC) to identify potential biological pathways associated with BCC. We first identified 322,324 expression-associated single-nucleotide polymorphisms (eSNPs) from two existing GWASs of global gene expression in lymphoblastoid cell lines (n = 955), and evaluated the association of these functionally annotated SNPs with BCC among 2,045 BCC cases and 6,013 controls in Caucasians. We then grouped them into 99 KEGG pathways for pathway analysis and identified two pathways associated with BCC with p value <0.05 and false discovery rate (FDR) <0.5: the autoimmune thyroid disease pathway (mainly HLA class I and II antigens, p < 0.001, FDR = 0.24) and Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway (p = 0.02, FDR = 0.49). Seventy-nine (25.7%) out of 307 significant eSNPs in the JAK-STAT pathway were associated with BCC risk (p < 0.05) in an independent replication set of 278 BCC cases and 1,262 controls. In addition, the association of JAK-STAT signaling pathway was marginally validated using 16,691 eSNPs identified from 110 normal skin samples (p = 0.08). Based on the evidence of biological functions of the JAK-STAT pathway on oncogenesis, it is plausible that this pathway is involved in BCC pathogenesis.

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Acknowledgments

The authors thank Dr. David Hunter, Dr. Frank B. Hu, and Dr. Eric B. Rimm for their work on the five GWAS sets (BC_NHS, T2D_NHS, T2D_HPFS CHD_NHS and CHD_HPFS). They thank Dr. Hongmei Nan for her work in BCC GWAS dataset construction and Dr. Mousheng Xu for his technical support in programing. They thank the participants in the Nurses’ Health Study and the Health Professionals Follow-Up Study for their dedication and commitment. They also thank the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The NHS and HPFS cohorts are supported by NIH grants CA87969, CA055075, and CA49449.

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The authors state no conflict of interest.

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Authors and Affiliations

  1. Clinical Research Program, Department of Dermatology, Harvard Medical School, Brigham and Women’s Hospital, 181 Longwood Ave, 5th Floor, Boston, MA, 02115, USA

    Mingfeng Zhang, Abrar A. Qureshi & Jiali Han

  2. Department of Epidemiology and Biostatistics, Cancer Center, Nanjing Medical University, Nanjing, China

    Mingfeng Zhang

  3. Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA

    Liming Liang, Peter Kraft & Jiali Han

  4. National Heart and Lung Institute, Imperial College London, London, UK

    Nilesh Morar, Anna L. Dixon, Miriam F. Moffatt & William O. C. Cookson

  5. Center National de Genotypage, Evry Cedex, France

    G. Mark Lathrop

  6. Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA

    Jun Ding

  7. Channing Laboratory, Department of Medicine, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA

    Abrar A. Qureshi & Jiali Han

  8. Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA

    Liming Liang & Peter Kraft

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  1. Mingfeng Zhang
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Correspondence to Jiali Han.

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Zhang, M., Liang, L., Morar, N. et al. Integrating pathway analysis and genetics of gene expression for genome-wide association study of basal cell carcinoma. Hum Genet 131, 615–623 (2012). https://doi.org/10.1007/s00439-011-1107-5

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