Ann Lab Med.  2015 May;35(3):283-287. 10.3343/alm.2015.35.3.283.

Meta-Analysis of Genetic Association Studies

Affiliations
  • 1Division of Rheumatology, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea. lyhcgh@korea.ac.kr

Abstract

The object of this review is to help readers to understand meta-analysis of genetic association study. Genetic association studies are a powerful approach to identify susceptibility genes for common diseases. However, the results of these studies are not consistently reproducible. In order to overcome the limitations of individual studies, larger sample sizes or meta-analysis is required. Meta-analysis is a statistical tool for combining results of different studies on the same topic, thus increasing statistical strength and precision. Meta-analysis of genetic association studies combines the results from independent studies, explores the sources of heterogeneity, and identifies subgroups associated with the factor of interest. Meta-analysis of genetic association studies is an effective tool for garnering a greater understanding of complex diseases and potentially provides new insights into gene-disease associations.

Keyword

Gene; Polymorphism; Association study; Meta-analysis

MeSH Terms

Arthritis, Rheumatoid/genetics/pathology
Databases, Factual
*Genetic Association Studies
Genotype
Humans
Polymorphism, Single Nucleotide
Receptors, Immunologic/genetics
Receptors, Immunologic

Reference

1. Cardon LR, Bell JI. Association study designs for complex diseases. Nat Rev Genet. 2001; 2:91–99. PMID: 11253062.
Article
2. Ioannidis JP. Genetic associations: false or true? Trends Mol Med. 2003; 9:135–138. PMID: 12727138.
Article
3. Colhoun HM, McKeigue PM, Davey Smith G. Problems of reporting genetic associations with complex outcomes. Lancet. 2003; 361:865–872. PMID: 12642066.
Article
4. Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet. 2003; 33:177–182. PMID: 12524541.
Article
5. Trikalinos TA, Salanti G, Zintzaras E, Ioannidis JP. Meta-analysis methods. Adv Genet. 2008; 60:311–334. PMID: 18358326.
Article
6. Gotzsche PC. Why we need a broad perspective on meta-analysis. It may be crucially important for patients. BMJ. 2000; 321:585–586. PMID: 10977820.
7. Yuan Y, Hunt RH. Systematic reviews: the good, the bad, and the ugly. Am J Gastroenterol. 2009; 104:1086–1092. PMID: 19417748.
Article
8. Minelli C, Thompson JR, Abrams KR, Thakkinstian A, Attia J. The choice of a genetic model in the meta-analysis of molecular association studies. Int J Epidemiol. 2005; 34:1319–1328. PMID: 16115824.
Article
9. Thakkinstian A, McElduff P, D'Este C, Duffy D, Attia J. A method for meta-analysis of molecular association studies. Stat Med. 2005; 24:1291–1306. PMID: 15568190.
Article
10. Whitehead A, Whitehead J. A general parametric approach to the meta-analysis of randomized clinical trials. Stat Med. 1991; 10:1665–1677. PMID: 1792461.
Article
11. Munafò MR, Flint J. Meta-analysis of genetic association studies. Trends Genet. 2004; 20:439–444. PMID: 15313553.
Article
12. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002; 21:1539–1558. PMID: 12111919.
Article
13. Davey Smith G, Egger M. Meta-analyses of randomised controlled trials. Lancet. 1997; 350:1182. PMID: 9343537.
14. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986; 7:177–188. PMID: 3802833.
Article
15. Ried K. Interpreting and understanding meta-analysis graphs--a practical guide. Aust Fam Physician. 2006; 35:635–638. PMID: 16894442.
16. Zintzaras E, Lau J. Synthesis of genetic association studies for pertinent gene-disease associations requires appropriate methodological and statistical approaches. J Clin Epidemiol. 2008; 61:634–645. PMID: 18538260.
Article
17. Salanti G, Sanderson S, Higgins JP. Obstacles and opportunities in meta-analysis of genetic association studies. Genet Med. 2005; 7:13–20. PMID: 15654223.
Article
18. Wittke-Thompson JK, Pluzhnikov A, Cox NJ. Rational inferences about departures from Hardy-Weinberg equilibrium. Am J Hum Genet. 2005; 76:967–986. PMID: 15834813.
Article
19. Salanti G, Amountza G, Ntzani EE, Ioannidis JP. Hardy-Weinberg equilibrium in genetic association studies: an empirical evaluation of reporting, deviations, and power. Eur J Hum Genet. 2005; 13:840–848. PMID: 15827565.
Article
20. Dickersin K, Min YI. Publication bias: the problem that won't go away. Ann N Y Acad Sci. 1993; 703:135–146. discussion 146-8. PMID: 8192291.
Article
21. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997; 315:629–634. PMID: 9310563.
Article
22. Sterne JA, Egger M. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol. 2001; 54:1046–1055. PMID: 11576817.
23. Lau J, Ioannidis JP, Terrin N, Schmid CH, Olkin I. The case of the misleading funnel plot. BMJ. 2006; 333:597–600. PMID: 16974018.
Article
24. Song GG, Bae SC, Kim JH, Kim YH, Choi SJ, Ji JD, et al. Association between functional Fc receptor-like 3 (FCRL3) -169 C/T polymorphism and susceptibility to seropositive rheumatoid arthritis in Asians: a meta-analysis. Hum Immunol. 2013; 74:1206–1213. PMID: 23777926.
Article
25. Nath SK, Harley JB, Lee YH. Polymorphisms of complement receptor 1 and interleukin-10 genes and systemic lupus erythematosus: a meta-analysis. Hum Genet. 2005; 118:225–234. PMID: 16133175.
Article
26. Lee YH, Harley JB, Nath SK. Meta-analysis of TNF-alpha promoter -308 A/G polymorphism and SLE susceptibility. Eur J Hum Genet. 2006; 14:364–371. PMID: 16418737.
27. Lee YH, Rho YH, Choi SJ, Ji JD, Song GG. PADI4 polymorphisms and rheumatoid arthritis susceptibility: a meta-analysis. Rheumatol Int. 2007; 27:827–833. PMID: 17265154.
Article
28. Bailar JC 3rd. The promise and problems of meta-analysis. N Engl J Med. 1997; 337:559–561. PMID: 9262502.
Article
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