Format

Send to

Choose Destination

See 1 citation:

Cell Cycle. 2016;15(1):22-4. doi: 10.1080/15384101.2015.1120928.

Reducing GWAS Complexity.

Author information

1
a Bioinformatics and Computational Biology Research Center, Biomedical Sciences, Cedars-Sinai Medical Center , Los Angeles , CA , USA.
2
b Departments of Preventive Medicine and Urology , USC/Norris Cancer Center , USA.
3
c Division of Genetics & Epidemiology, Centre of Cancer Genetic Epidemiology, University of Cambridge , Cambridge , UK.
4
d The Institute of Cancer Research & Royal Marsden NHS Foundation Trust , London , UK.

Abstract

Genome-wide association studies (GWAS) have revealed numerous genomic 'hits' associated with complex phenotypes. In most cases these hits, along with surrogate genetic variation as measure by numerous single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium, are not in coding genes making assignment of functionality or causality intractable. Here we propose that fine-mapping along with the matching of risk SNPs at chromatin biofeatures lessen this complexity by reducing the number of candidate functional/causal SNPs. For example, we show here that only on average 2 SNPs per prostate cancer risk locus are likely candidates for functionality/causality; we further propose that this manageable number should be taken forward in mechanistic studies. The candidate SNPs can be looked up for each prostate cancer risk region in 2 recent publications in 2015 (1,2) from our groups.

KEYWORDS:

Cancer; GWAS; SNP; chromatin; enhancer; fine-mapping; non-coding DNA

PMID:
26771711
PMCID:
PMC4825730
DOI:
10.1080/15384101.2015.1120928
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Taylor & Francis Icon for PubMed Central
Loading ...
Support Center