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Hum Mol Genet. 2015 Oct 1;24(19):5603-18. doi: 10.1093/hmg/ddv269. Epub 2015 Jul 10.

Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions.

Author information

1
Department of Preventive Medicine, Keck School of Medicine.
2
Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
3
Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center.
4
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
5
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA, Cancer Genomics Research Laboratory, NCI-DCEG, SAIC-Frederick Inc., Frederick, MD, USA.
6
Cancer Genomics Research Laboratory, NCI-DCEG, SAIC-Frederick Inc., Frederick, MD, USA.
7
Program for Personalized Cancer Care and Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA.
8
Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
9
Department of Genomics of Common Disease, School of Public Health.
10
Genomic Epidemiology Group, German Cancer Research Center, Heidelberg, Germany.
11
Laboratory for Statistical Analysis.
12
Laboratory for Genotyping Development.
13
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA, Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.
14
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
15
Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA.
16
Department of Epidemiology.
17
Department of Urology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.
18
Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
19
The Institute of Cancer Research, London, UK.
20
The Institute of Cancer Research, London, UK, Royal Marsden National Health Services (NHS) Foundation Trust, London and Sutton, UK.
21
Korle Bu Teaching Hospital, Accra, Ghana, University of Ghana Medical School, Accra, Ghana.
22
Westat, Rockville, MD, USA.
23
School of Public Health, University of California, Berkeley, CA, USA.
24
James Buchanan Brady Urological Institute, Johns Hopkins Hospital and Medical Institution, Baltimore, MD, USA.
25
Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology.
26
Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
27
Department of Nutrition, Department of Epidemiology.
28
Department of Medical Oncology.
29
Department of Medical Oncology, Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.
30
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
31
Cancer Prevention Institute of California, Fremont, CA, USA, Division of Epidemiology, Department of Health Research and Policy, and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
32
University of Arizona College of Medicine and University of Arizona Cancer Center, Tucson, AZ, USA.
33
Department of Urology, Northwestern University, Chicago, IL, USA.
34
International Epidemiology Institute, Rockville, MD, USA, Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
35
Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
36
Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
37
Department of Preventive Medicine, Stony Brook University, Stony Brook, NY, USA.
38
The Translational Genomics Research Institute, Phoenix, AZ, USA.
39
Department of Preventive Medicine, Stony Brook University, Stony Brook, NY, USA, Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Bridgetown, Barbados.
40
Department of Public Health Sciences, Henry Ford Hospital, Detroit, MI, USA.
41
SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
42
Department of Urology, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA.
43
Center for Cancer Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA.
44
Department of Epidemiology and Biostatistics, Institute for Human Genetics, University of California, San Francisco, CA, USA and.
45
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK.
46
Medical College, Xiamen University, Xiamen 361102, China.
47
Laboratory for Genome Sequencing Analysis, RIKEN Center for Integrative Medical Sciences, Tokyo, Japan.
48
Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.
49
Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
50
Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, haiman@usc.edu.

Abstract

Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.

PMID:
26162851
PMCID:
PMC4572069
DOI:
10.1093/hmg/ddv269
[Indexed for MEDLINE]
Free PMC Article

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