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(Ingenuity® Systems, www.ingenuity.com). This approach bypasses the underlying enrichment effect of combining test statistics within the gene region and might miss genes that are comprised of SNPs not highly ranked individually because of small effects, but has an overall combined moderate effect on the disease.
Conclusion
This chapter presents a review of current approaches in utilizing genomic information in genetics study. Two approaches using genomic convergence and biological pathways are highlighted as complementary methods to potentially improve power in GWAS. Both methods depend on the type and relevance of the genomic information elicited for the analyses, requiring collaborative efforts from different expertise to keep afloat in the deluge of genomic information. As seen, there is still room to explore the similarity measures in pathway analysis and how these measures can be aggregated in a robust manner to allow comprehensive analysis of functionality within a statistical test. At present, each similarity measure is assessed individually. As we move towards integrative analysis in system biology, we need to think beyond our current GWAS approaches and develop methodology that will incorporate genomic information to enhance discovery. As more biological context is included in the analyses, the richer and more relevant the information, the better the outcome. In our study on the genetics of myopia, we have adopted genomic convergence in our GWAS and are currently applying pathway analysis on the genes in Table 2 to help us identify novel genes.
References
1.Curtin B. (1985) The Myopias: Basic Science and Clinical Management. Harper & Row, New York.
2.Javitt JC, Chiang YP. (1994) The socioeconomic aspects of laser refractive surgery. Arch Ophthalmol 112(12): 1526–1530.
3.Vitale S, et al. (2006) Costs of refractive correction of distance vision impairment in the United States, 1999–2002. Ophthalmology 113(12): 2163–2170.
4.Chow YC, et al. (1990) Refractive errors in Singapore medical students.
Singapore Med J. 31(5): 472–473.
178L.K. Goh, R. Metlapally and T. Young
5.Lin LL, et al. (1988) Nation-wide survey of myopia among schoolchildren in Taiwan, 1986. Acta Ophthalmol Suppl 185: 29–33.
6.Goss DA, Winkler RL. (1983) Progression of myopia in youth: age of cessation. Am J Optom Physiol Opt 60(8): 651–658.
7.Saw SM, et al. (1996) Epidemiology of myopia. Epidemiol Rev 18(2): 175–187.
8.Vitale S, et al. (2008) Prevalence of refractive error in the United States, 1999–2004. Arch Ophthalmol 126(8): 1111–1119.
9.Kleinstein RN, et al. (2003) Refractive error and ethnicity in children. Arch Ophthalmol 121(8): 1141–1147.
10.Zylbermann R, Landau D, Berson D. (1993) The influence of study habits on myopia in Jewish teenagers. J Pediatr Ophthalmol Strabismus 30(5): 319–322.
11.The Eye Disease Case-Control Study Group. (1993) Risk factors for idiopathic rhegmatogenous retinal detachment. Am J Epidemiol 137(7): 749–757.
12.Perkins ES. (1960) Glaucoma in the younger age groups. Arch Ophthalmol 64: 882–891.
13.Goss DA, Jackson TW. (1996) Clinical findings before the onset of myopia in youth: 4. Parental history of myopia. Optom Vis Sci 73(4): 279–282.
14.Zadnik K, et al. (1994) The effect of parental history of myopia on children’s eye size. JAMA 271(17): 1323–1327.
15.Ashton GC. (1985) Segregation analysis of ocular refraction and myopia. Hum Hered 35(4): 232–239.
16.Klein AP, et al. (2005) Support for polygenic influences on ocular refractive error. Invest Ophthalmol Vis Sci 46(2): 442–446.
17.Naiglin L, et al. (1999) Familial high myopia: evidence of an autosomal dominant mode of inheritance and genetic heterogeneity. Ann Genet 42(3): 140–146.
18.Teikari JM, et al. (1991) Impact of heredity in myopia. Hum Hered 41(3): 151–156.
19.Hammond CJ, et al. (2001) Genes and environment in refractive error: the twin eye study. Invest Ophthalmol Vis Sci 42(6): 1232–1236.
20.Lyhne N, et al. (2001) The importance of genes and environment for ocular refraction and its determiners: a population based study among 20–45 year old twins. Br J Ophthalmol 85(12): 1470–1476.
21.Schwartz M, Haim M, Skarsholm D. (1990) X-linked myopia: Bornholm eye disease. Linkage to DNA markers on the distal part of Xq. Clin Genet 38(4): 281–286.
22.Chen CY, et al. (2007) Linkage replication of the MYP12 locus in common myopia. Invest Ophthalmol Vis Sci 48(10): 4433–4439.
23.Farbrother JE, et al. (2004) Linkage analysis of the genetic loci for high myopia on 18p, 12q, and 17q in 51 U.K. families. Invest Ophthalmol Vis Sci
45(9): 2879–2885.
179New Approaches in the Genetics of Myopia
24.Klein AP, et al. (2007) Confirmation of linkage to ocular refraction on chromosome 22q and identification of a novel linkage region on 1q. Arch Ophthalmol 125(1): 80–85.
25.Lam DS, et al. (2003) Familial high myopia linkage to chromosome 18p. Ophthalmologica 217(2): 115–118.
26.Li YJ, et al. (2009) An international collaborative family-based wholegenome linkage scan for high-grade myopia. Invest Ophthalmol Vis Sci 50(7): 3116–3127.
27.Nurnberg G, et al. (2008) Refinement of the MYP3 locus on human chromosome 12 in a German family with Mendelian autosomal dominant high-grade myopia by SNP array mapping. Int J Mol Med 21(4): 429–438.
28.Young TL, et al. (2004) X-linked high myopia associated with cone dysfunction. Arch Ophthalmol 122(6): 897–908.
29.Barrett JC, et al. (2008) Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat Genet 40(8): 955–962.
30.Amos CI, et al. (2008) Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat Genet 40(5): 616–622.
31.Ferreira MA, et al. (2008) Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet.
32.Horikawa Y, et al. (2008) Replication of genome-wide association studies of type 2 diabetes susceptibility in Japan. J Clin Endocrinol Metab 93(8): 3136–3141.
33.Hasumi Y, et al. (2006) Analysis of single nucleotide polymorphisms at 13 loci within the transforming growth factor-induced factor gene shows no association with high myopia in Japanese subjects. Immunogenetics 58(12): 947–953.
34.Liang CL, et al. (2007) Systematic assessment of the tagging polymorphisms of the COL1A1 gene for high myopia. J Hum Genet 52(4): 374–377.
35.Metlapally R, et al. (2009) COL1A1 and COL2A1 genes and myopia susceptibility: evidence of association and suggestive linkage to the COL2A1 locus. Invest Ophthalmol Vis Sci 50(9): 4080–4086.
36.Paluru PC, et al. (2004) Exclusion of lumican and fibromodulin as candidate genes in MYP3 linked high grade myopia. Mol Vis 10: 917–922.
37.Mutti DO, et al. (2007) Candidate gene and locus analysis of myopia. Mol Vis 13: 1012–1019.
38.Scavello GS Jr, et al. (2005) Genomic structure and organization of the high grade Myopia-2 locus (MYP2) critical region: mutation screening of 9 positional candidate genes. Mol Vis 11: 97–110.
39.Simpson CL, et al. (2007) The roles of PAX6 and SOX2 in myopia: lessons from the 1958 British Birth Cohort. Invest Ophthalmol Vis Sci 48(10): 4421–4425.
180L.K. Goh, R. Metlapally and T. Young
40.Zayats T, et al. (2008) Comment on ‘A PAX6 gene polymorphism is associated with genetic predisposition to extreme myopia’. Eye 22(4): 598–599; author reply 599.
41.Hauser MA, et al. (2003) Genomic convergence: identifying candidate genes for Parkinson’s disease by combining serial analysis of gene expression and genetic linkage. Hum Mol Genet 12(6): 671–677.
42.Noureddine MA, et al. (2005) Genomic convergence to identify candidate genes for Parkinson disease: SAGE analysis of the substantia nigra. Mov Disord 20(10): 1299–1309.
43.Bowes Rickman C, et al. (2006) Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE. Invest Ophthalmol Vis Sci 47(6): 2305–2316.
44.Mootha VK, et al. (2003) PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 34(3): 267–273.
45.Edelman E, et al. (2006) Analysis of sample set enrichment scores: assaying the enrichment of sets of genes for individual samples in genome-wide expression profiles. Bioinformatics 22(14): p. e108–e116.
46.Tian L, et al. (2005) Discovering statistically significant pathways in expression profiling studies. Proc Natl Acad Sci USA 102(38): 13544–13549.
47.Kim SY, Volsky DJ. (2005) PAGE: parametric analysis of gene set enrichment. BMC Bioinformatics 6: 144.
48.Subramanian A, et al. (2005) Gene set enrichment analysis: a knowledgebased approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102(43): 15545–15550.
49.Barry WT, Nobel AB, Wright FA. (2005) Significance analysis of functional categories in gene expression studies: a structured permutation approach. Bioinformatics 21(9): 1943–1949.
50.Tomfohr J, Lu J, Kepler TB. (2005) Pathway level analysis of gene expression using singular value decomposition. BMC Bioinformatics 6: 225.
51.Slager SL, Huang J, Vieland VJ. (2000) Effect of allelic heterogeneity on the power of the transmission disequilibrium test. Genet Epidemiol 18(2): 143–156.
52.Sweet-Cordero A, et al. (2005) An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis. Nat Genet 37(1): 48–55.
53.Alvarez JV, et al. (2005) Identification of a genetic signature of activated signal transducer and activator of transcription 3 in human tumors. Cancer Res 65(12): 5054–5062.
54.Bild AH, et al. (2006) Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439(7074): 353–357.
181New Approaches in the Genetics of Myopia
55.Gauderman WJ, et al. (2007) Testing association between disease and multiple SNPs in a candidate gene. Genet Epidemiol 31(5): 383–395.
56.Wang K, Abbott D. (2008) A principal components regression approach to multilocus genetic association studies. Genet Epidemiol 32(2): 108–118.
57.Wang T, Elston RC. (2007) Improved power by use of a weighted score test for linkage disequilibrium mapping. Am J Hum Genet 80(2): 353–360.
58.Schaid DJ, et al. (2005) Nonparametric tests of association of multiple genes with human disease. Am J Hum Genet 76(5): 780–793.
59.Wessel J, Schork NJ. (2006) Generalized genomic distance-based regression methodology for multilocus association analysis. Am J Hum Genet 79(5): 792–806.
60.Wei Z, et al. (2008) U-Statistics-based tests for multiple genes in Genetic Association Studies. Ann Hum Genet.
61.Kwee LC, et al. (2008) A powerful and flexible multilocus association test for quantitative traits. Am J Hum Genet 82(2): 386–397.
62.Chapman J, Whittaker J. (2008) Analysis of multiple SNPs in a candidate gene or region. Genet Epidemiol 32(6): 560–566.
63.Wang K, Li M, Bucan M. (2007) Pathway-Based Approaches for Analysis of Genomewide Association Studies. Am J Hum Genet 81(6).
64.Zhou H, Wei LJ, Xu X. (2008) Combining association tests across multiple genetic markers in case-control studies. Hum Hered 65(3): 166–174.
65.Torkamani A, Topol EJ, Schork NJ. (2008) Pathway analysis of seven common diseases assessed by genome-wide association. Genomics 92(5): 265–272.
66.Yu K, et al. (2009) Pathway analysis by adaptive combination of P-values. Genet Epidemiol 33(8): 700–709.
67.Dinu V, Miller PL, Zhao H. (2007) Evidence for association between multiple complement pathway genes and AMD. Genet Epidemiol 31(3): 224–237.
68.Pan W. (2008) Network-based model weighting to detect multiple loci influencing complex diseases. Hum Genet 124(3): 225–234.
69.Clayton D, Chapman J, Cooper J. (2004) Use of unphased multilocus genotype data in indirect association studies. Genet Epidemiol 27(4): 415–428.
70.Salem RM, Wessel J, Schork NJ. (2005) A comprehensive literature review of haplotyping software and methods for use with unrelated individuals. Hum Genomics 2(1): 39–66.
71.Hoeffding W. (1948) A class of statistics with asymptotically normal distribution. Annals of Mathematical Statistics 22: 165–179.
72.Li M, et al. (2009) ATOM: a powerful gene-based association test by combining optimally weighted markers. Bioinformatics 25(4): 497–503.
73.Cheung VG, et al. (2005) Mapping determinants of human gene expression by regional and genome-wide association. Nature 437(7063): 1365–1369.
182L.K. Goh, R. Metlapally and T. Young
74.Marchini J, et al. (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39(7): 906–913.
75.Zaykin DV, et al. (2002) Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum Hered 53(2): 79–91.
76.Peng G, et al. (2009) Gene and pathway-based second-wave analysis of genome-wide association studies. Eur J Hum Genet.
77.Huang da W, et al. (2007) DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res. 35(Web Server issue): W169–W175.
78.Beissbarth T, Speed TP. (2004) GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics 20(9): 1464–1465.