Incorporating prior knowledge to facilitate discoveries in a genome-wide association study on age-related macular degeneration

BackgroundSubstantial genotyping data produced by current high-throughput technologies have brought opportunities and difficulties. With the number of single-nucleotide polymorphisms (SNPs) going into millions comes the harsh challenge of multiple-testing adjustment. However, even with the false discovery rate (FDR) control approach, a genome-wide association study (GWAS) may still fall short of discovering any true positive gene, particularly when it has a relatively small sample size.FindingsTo counteract such a harsh multiple-testing penalty, in this report, we incorporate findings from previous linkage and association studies to re-analyze a GWAS on age-related macular degeneration. While previous Bonferroni correction and the traditional FDR approach detected only one significant SNP (rs380390), here we have been able to detect seven significant SNPs with an easy-to-implement prioritized subset analysis (PSA) with the overall FDR controlled at 0.05. These include SNPs within three genes: CFH, CFHR4, and SGCD.ConclusionsBased on the success of this example, we advocate using the simple method of PSA to facilitate discoveries in future GWASs.

[1]  Larry Wasserman,et al.  Using linkage genome scans to improve power of association in genome scans. , 2006, American journal of human genetics.

[2]  J. Haines,et al.  Age-related maculopathy: a genomewide scan with continued evidence of susceptibility loci within the 1q31, 10q26, and 17q25 regions. , 2004, American journal of human genetics.

[3]  Radu V. Craiu,et al.  Stratified false discovery control for large‐scale hypothesis testing with application to genome‐wide association studies , 2006, Genetic epidemiology.

[4]  Ethan M. Lange,et al.  Prioritized Subset Analysis: Improving Power in Genome-wide Association Studies , 2007, Human Heredity.

[5]  Jon Wakefield,et al.  Reporting and interpretation in genome-wide association studies. , 2008, International journal of epidemiology.

[6]  Lars G Fritsche,et al.  Hypothetical LOC387715 is a second major susceptibility gene for age-related macular degeneration, contributing independently of complement factor H to disease risk. , 2005, Human molecular genetics.

[7]  S. Santangelo,et al.  A genomewide scan for age-related macular degeneration provides evidence for linkage to several chromosomal regions. , 2003, American journal of human genetics.

[8]  T. Matise,et al.  Age-related macular degeneration--a genome scan in extended families. , 2003, American journal of human genetics.

[9]  L. Wasserman,et al.  False discovery control with p-value weighting , 2006 .

[10]  J. Ott,et al.  Complement Factor H Polymorphism in Age-Related Macular Degeneration , 2005, Science.

[11]  R. Klein,et al.  Genome-wide analyses demonstrate novel loci that predispose to drusen formation. , 2005, Investigative ophthalmology & visual science.

[12]  Shigeo Yoshida,et al.  Age-related macular degeneration: a high-resolution genome scan for susceptibility loci in a population enriched for late-stage disease. , 2004, American journal of human genetics.

[13]  J. Gilbert,et al.  Complement Factor H Variant Increases the Risk of Age-Related Macular Degeneration , 2005, Science.

[14]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[15]  R. T. Smith,et al.  A common haplotype in the complement regulatory gene factor H (HF1/CFH) predisposes individuals to age-related macular degeneration. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[16]  A. Edwards,et al.  Complement Factor H Polymorphism and Age-Related Macular Degeneration , 2005, Science.

[17]  J. Humphrey,et al.  Altered biomechanical properties of carotid arteries in two mouse models of muscular dystrophy. , 2007, Journal of applied physiology.

[18]  C. Keilhauer,et al.  An update on the genetics of age-related macular degeneration , 2007, Molecular vision.

[19]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[20]  D. Weeks,et al.  C2 and CFB Genes in Age-Related Maculopathy and Joint Action with CFH and LOC387715 Genes , 2008, PloS one.

[21]  Wei Pan,et al.  Gene expression A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data , 2005 .

[22]  Johanna M Seddon,et al.  The genetics of age-related macular degeneration: a review of progress to date. , 2006, Survey of ophthalmology.

[23]  T. Matise,et al.  Age-related macular degeneration. Clinical features in a large family and linkage to chromosome 1q. , 1998, Archives of ophthalmology.

[24]  S. Holm.  A Simple Sequentially Rejective Multiple Test Procedure , 1979 .

[25]  D. Weeks,et al.  C 2 and CFB Genes in Age-Related Maculopathy and Joint Action with CFH and LOC 387715 Genes , 2008 .

[26]  D. Weeks,et al.  Susceptibility genes for age-related maculopathy on chromosome 10q26. , 2005, American journal of human genetics.

[27]  Dissection of genomewide-scan data in extended families reveals a major locus and oligogenic susceptibility for age-related macular degeneration. , 2004, American journal of human genetics.

[28]  Adam Yao,et al.  GenoWatch: a disease gene mining browser for association study , 2008, Nucleic Acids Res..

[29]  Korbinian Strimmer,et al.  A unified approach to false discovery rate estimation , 2008, BMC Bioinformatics.

[30]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[31]  R. T. Smith,et al.  Variation in factor B (BF) and complement component 2 (C2) genes is associated with age-related macular degeneration , 2006, Nature Genetics.