Skip to main content

Advertisement

SpringerLink
Log in

Meta-analysis in psychiatric genetics

  • Published:
Current Psychiatry Reports Aims and scope Submit manuscript

Abstract

The article reviews literature on methods for meta-analysis of genetic linkage and association studies, and summarizes and comments on specific meta-analysis findings for psychiatric disorders. The Genome Scan Meta-Analysis and Multiple Scan Probability methods assess the evidence for linkage across studies. Multiple Scan Probability analysis suggested linkage of two chromosomal regions (13q and 22q) to schizophrenia and bipolar disorder, whereas Genome Scan Meta-Analysis on a larger sample identified at least 10 schizophrenia linkage regions, but none for bipolar disorder. Metaanalyses of pooled ORs support association of schizophrenia to the Ser311Cys polymorphism in DRD2 and the T102C polymorphism in HTR2A, and of attention deficit hyperactivity disorder to the 48-bp repeat in DRD4. The 5-HTTLPR polymorphism in the serotonin transporter gene (SLC6A4) may contribute to the risk of bipolar disorder, suicidal behavior, and neuroticism, but association to the lifetime risk of major depression has not been shown. Meta-analyses support linkage of schizophrenia to regions where replicable associations to candidate genes have been identified through positional cloning methods. There are additional supported regions where susceptibility genes are likely to be identified. Linkage meta-analysis has had less clear success for bipolar disorder based on a smaller dataset. Meta-analysis can guide the prioritization of regions for study, but proof of association requires biological confirmation of hypotheses about gene actions. Elucidation of causal mechanisms will require more comprehensive study of sequence variation in candidate genes, better statistical and meta-analytic methods to take all variation into account, and biological strategies for testing etiologic hypotheses.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References and Recommended Reading

  1. Egger M, Smith GD, Sterne JA: Uses and abuses of meta-analysis. Clin Med 2001, 1:478–484. This is an excellent review on meta-analysis, with a focus on the importance of providing a critical review of the literature and not simply a statistical pooling of results.

    PubMed  CAS  Google Scholar 

  2. Pulver AE, Karayiorgou M, Lasseter VK, et al.: Follow-up of a report of a potential linkage for schizophrenia on chromosome 22q12-q13.1: Part 2. Am J Med Genet 1994, 54:44–50.

    Article  PubMed  CAS  Google Scholar 

  3. Nurnberger Jr JI, Blehar MC, Kaufmann CA, et al.: Diagnostic interview for genetic studies. Rationale, unique features, and training. NIMH Genetics Initiative. Arch Gen Psychiatry 1994, 51:849–859.

    PubMed  Google Scholar 

  4. Altmüller J, Palmer LJ, Fischer G, et al.: Genomewide scans of complex human diseases: true linkage is hard to find. Am J Hum Genet 2001, 69:936–950. This is an important report of a meta-analysis, not of linkage studies of one disease, but of genome scans for many complex disorders, to attempt to identify factors that predict which studies obtain significant results. The two most important predictors proved to be larger sample size, and restriction of a sample to a single reasonably homogeneous ethnic group (i.e., "European" or "Chinese" families).

    Article  PubMed  Google Scholar 

  5. Rice JP: The role of meta-analysis in linkage studies of complex traits. Am J Med Genet 1997, 74:112–114.

    Article  PubMed  CAS  Google Scholar 

  6. Dorr DA, Rice JP, Armstrong C, et al.: Meta-analysis of chromosome 18 linkage data for bipolar illness. Genet Epidemiol 1997, 14:617–622.

    Article  PubMed  CAS  Google Scholar 

  7. Badner JA, Gershon ES: Regional meta-analysis of published data supports linkage of autism with markers on chromosome. Mol Psychiatry 2002, 7:56–66. This paper includes the description of Multiple Scan Probability analysis, a method of meta-analysis based on Fisher’s formula for combining p-values, modified to take into account the genetic distance between the locations of peak p-values in different studies. The method was also applied to schizophrenia and bipolar disorder (reference 29).

    Article  PubMed  CAS  Google Scholar 

  8. Province MA: The significance of not finding a gene. Am J Hum Genet 2001, 69:660–663.

    Article  PubMed  CAS  Google Scholar 

  9. Wise LH, Lanchbury JS, Lewis CM: Meta-analysis of genome searches. Ann Hum Genet 1999, 63:263–72.

    Article  PubMed  CAS  Google Scholar 

  10. Levinson DF, Levinson MD, Segurado R, Lewis CM: Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis. Am J Hum Genet 2003, 73:17–33. This is a report on a comprehensive simulation study to explore the properties of the Genome Scan Meta-Analysis (GSMA) method (reference 10) in datasets modelled after the schizophrenia and bipolar disorder analyses reported in references 27 and 28. Not all GSMA studies (see references 12–18) have utilized the empirical significance thresholds derived in this study, but they appear to make GSMA more sensitive to weak linkage effects.

    Article  PubMed  CAS  Google Scholar 

  11. Chiodini BD, Lewis CM: Meta-analysis of 4 coronary heart disease genome-wide linkage studies confirms a susceptibility locus on chromosome 3q. Arterioscler Thromb Vasc Biol 2003, 23:1863–1868.

    Article  PubMed  CAS  Google Scholar 

  12. Demenais F, Kanninen T, Lindgren CM, et al.: A meta-analysis of four European genome screens (GIFT Consortium) shows evidence for a novel region on chromosome 17p11.2-q22 linked to type 2 diabetes. Hum Mol Genet 2003, 12:1865–1873.

    Article  PubMed  CAS  Google Scholar 

  13. Liu W, Zhao W, Chase GA: Genome scan meta-analysis for hypertension. Am J Hypertens 2004, 17:1100–1106.

    Article  PubMed  CAS  Google Scholar 

  14. Marazita ML, Murray JC, Lidral AC, et al.: Meta-analysis of 13 genome scans reveals multiple cleft lip/palate genes with novel loci on 9q21 and 2q32-35. Am J Hum Genet 2004, 75:161–173.

    Article  PubMed  CAS  Google Scholar 

  15. Sagoo GS, Tazi-Ahnini R, Barker JW, et al.: Meta-analysis of genome-wide studies of psoriasis susceptibility reveals linkage to chromosomes 6p21 and 4q28-q31 in Caucasian and Chinese Hans population. J Invest Dermatol 2004, 122:1401–1405.

    Article  PubMed  CAS  Google Scholar 

  16. van Heel DA, Fisher SA, Kirby A, et al.: Genome Scan Meta-Analysis Group of the IBD International Genetics Consortium. Inflammatory bowel disease susceptibility loci defined by genome scan meta-analysis of 1952 affected relative pairs. Hum Mol Genet 2004, 13:763–770.

    Article  PubMed  CAS  Google Scholar 

  17. Williams CN, Kocher K, Lander ES, et al.: Using a genome-wide scan and meta-analysis to identify a novel IBD locus and confirm previously identified IBD loci. Inflamm Bowel Dis 2002, 8:375–381.

    Article  PubMed  Google Scholar 

  18. Moises HW, Yang L, Kristbjarnarson H, et al.: An international two-stage genome-wide search for schizophrenia susceptibility genes. Nat Genet 1995, 11:321–324.

    Article  PubMed  CAS  Google Scholar 

  19. Schizophrenia Linkage Collaborative Group for Chromosomes 3, 6 and 8: Additional support for schizophrenia linkage on chromosomes 6, 8: a multicenter study. Am J Med Genet 1996, 67:580–594.

    Article  Google Scholar 

  20. Levinson DF, Holmans P, Straub RE, et al.: Multicenter linkage study of schizophrenia candidate regions on chromosomes 5q, 6q, 10p, and 13q: schizophrenia linkage collaborative group III. Am J Hum Genet 2000, 67:652–663.

    Article  PubMed  CAS  Google Scholar 

  21. Visscher PM, Haley CS, Ewald H, et al.: Joint multi-population analysis for genetic linkage of bipolar disorder or "wellness" to chromosome 4p. Am J Med Genet 2004

  22. Lewis CM, Levinson DF, Wise LH, et al.: Genome scan metaanalysis of schizophrenia and bipolar disorder, part II: Schizophrenia. Am J Hum Genet 2003, 73:34–48. This meta-analysis of schizophrenia genome scan projects provides evidence supporting at least 10 (and possibly more) chromosomal regions likely to contain schizophrenia linkage. Several of the bestsupported schizophrenia candidate genes are in some of these regions and were discovered as a result of systematic association mapping of linkage findings. These results demonstrate the utility of systematic positional cloning as a strategy to identify multiple genes that influence risk for common, genetically complex disorder.

    Article  PubMed  CAS  Google Scholar 

  23. Segurado R, Detera-Wadleigh SD, Levinson DF, et al.: Genome scan meta-analysis of schizophrenia and bipolar disorder, part III: Bipolar disorder. Am J Hum Genet 2003, 73:49–62. This GSMA of bipolar disorder was carried out using the same methods as the schizophrenia analysis reported in reference 22, but no significant findings were observed. The dataset was larger than that in reference 24, and differed in some other ways in the selection of studies and in the data provided by authors for analysis beyond the published data in some cases. It was striking to see how few families (under 400) had been collected worldwide for linkage analysis using a "narrow" diagnostic model (bipolar-I and schizoaffective disorder-bipolar type). Fortunately, additional large datasets (references 50–52) have since become available and can be analyzed in the future.

    Article  PubMed  CAS  Google Scholar 

  24. Badner JA, Gershon ES: Meta-analysis of whole-genome linkage scans of bipolar disorder and schizophrenia. Mol Psychiatry 2002, 7:405–411. This analysis, using the MSP method [7], produced different results than the two GSMA studies of these disorders [22,23], as discussed in the text. Although it is likely that the main contributing factor was the difference in the datasets that were studied, more work will need to be done to understand whether MSP has advantages over GSMA in some situations.

    Article  PubMed  CAS  Google Scholar 

  25. Berrettini W: Bipolar disorder and schizophrenia: convergent molecular data. Neuromolecular Med 2004, 5:109–17.

    Article  PubMed  CAS  Google Scholar 

  26. Straub RE, Jiang Y, MacLean CJ, et al.: Genetic variation in the 6p22.3 gene DTNBP1, the human ortholog of the mouse dysbindin gene, is associated with schizophrenia. Am J Hum Genet 2002, 71:337–348.

    Article  PubMed  CAS  Google Scholar 

  27. Schwab SG, Knapp M, Mondabon S, et al.: Support for association of schizophrenia with genetic variation in the 6p22.3 gene, dysbindin, in sib-pair families with linkage and in an additional sample of triad families. Am J Hum Genet 2003, 72:185–190.

    Article  PubMed  CAS  Google Scholar 

  28. Van Den Bogaert A, Schumacher J, Schulze TG, et al.: The DTNBP1 (dysbindin) gene contributes to schizophrenia, depending on family history of the disease. Am J Hum Genet 2003, 73:1438–43.

    Article  Google Scholar 

  29. Shifman S, Bronstein M, Sternfeld M, et al.: A highly significant association between a COMT haplotype and schizophrenia. Am J Hum Genet 2002, 71:1296–302.

    Article  PubMed  CAS  Google Scholar 

  30. Liu H, Heath SC, Sobin C, et al.: Genetic variation at the 22q11 PRODH2/DGCR6 locus presents an unusual pattern and increases susceptibility to schizophrenia. Proceedings of the Nat Acad Sci U S A 2002, 99:3717–3722.

    Article  CAS  Google Scholar 

  31. Stefansson H, Sigurdsson E, Steinthorsdottir V, et al.: Neuregulin 1 and susceptibility to schizophrenia. Am J Hum Genet 2002, 71:877–892.

    Article  PubMed  Google Scholar 

  32. Stefansson H, Sarginson J, Kong A, et al.: Association of neuregulin 1 with schizophrenia confirmed in a Scottish population. Am J Hum Genet 2003, 72:83–87.

    Article  PubMed  CAS  Google Scholar 

  33. Tang JX, Chen WY, He G, et al.: Polymorphisms within 5′ end of the Neuregulin 1 gene are genetically associated with schizophrenia in the Chinese population. Mol Psychiatry 2004, 9:11–12.

    Article  PubMed  CAS  Google Scholar 

  34. Yang JZ, Si TM, Ruan Y, et al.: Association study of neuregulin 1 gene with schizophrenia. Mol Psychiatry 2003, 8:706–709.

    Article  PubMed  CAS  Google Scholar 

  35. Williams NM, Preece A, Spurlock G, et al.: Support for genetic variation in neuregulin 1 and susceptibility to schizophrenia. Mol Psychiatry 2003, 8:485–487.

    Article  PubMed  CAS  Google Scholar 

  36. Straub RE, Matsumoto M, Egan MF, et al.: MRDS1 (6p24.3) is associated with schizophrenia in both adult onset and childhood onset schizophrenia families. Am J Med Genet Part B (Neuropsychiatric Genetics) 2003, 122B:18.

    Google Scholar 

  37. Datta SR, McQuillin A, Rizig MA, et al.: Further genetic analyses of the pcm1 gene association with schizophrenia on chromosome 8p21 and tests of the G72, dysbindin, RGS4, calcineurin, COMT, frizzled 3, MRDS1, AKT1 and CAPON associations. Am J Med Genet Part B (Neuropsychiatric Genetics) 2004, 130B:86.

    Google Scholar 

  38. Brzustowicz LM, Hodgkinson KA, Chow EW, et al.: Location of a major susceptibility locus for familial schizophrenia on chromosome 1q21-q22. Science 2000, 288:678–682.

    Article  PubMed  CAS  Google Scholar 

  39. Gurling HM, Kalsi G, Brynjolfson J, et al.: Genomewide genetic linkage analysis confirms the presence of susceptibility loci for schizophrenia, on chromosomes 1q32.2, 5q33.2,, 8p21–22, provides support for linkage to schizophrenia, on chromosomes 11q23.3-24, 20q12.1-11.23. Am J Hum Genet 2001, 68:661–673.

    Article  PubMed  CAS  Google Scholar 

  40. Levinson DF, Holmans PA, Laurent C, et al.: No major schizophrenia locus detected on chromosome 1q in a large multicenter sample. Science 2002, 296:739–741.

    Article  PubMed  CAS  Google Scholar 

  41. Blouin JL, Dombroski BA, Nath SK, et al.: Schizophrenia susceptibility loci on chromosomes 13q32, 8p21. Nat Genet 1998, 20:70–73.

    Article  PubMed  CAS  Google Scholar 

  42. Brzustowicz LM, Honer WG, Chow EW, et al.: Linkage of familial schizophrenia to chromosome 13q32. Am J Hum Genet 1999, 65:1096–103.

    Article  PubMed  CAS  Google Scholar 

  43. Chumakov I, Blumenfeld M, Guerassimenko O, et al.: The family based association test method: strategies for studying general genotype-phenotype associations. Eur J Hum Genet 2001, 9:301–306.

    Article  CAS  Google Scholar 

  44. Zou F, Li C, Duan S, et al.: A family-based study of the association between the G72/G30 genes and schizophrenia in the Chinese population. Schizophr Res 2005, 73:257–261.

    Article  PubMed  Google Scholar 

  45. Wang X, He G, Gu N, et al.: Association of G72/G30 with schizophrenia in the Chinese population. Biochem Biophys Res Commun 2004, 319:1281–1286.

    Article  PubMed  CAS  Google Scholar 

  46. Addington AM, Gornick M, Sporn AL, et al.: Polymorphisms in the 13q33.2 gene G72/G30 are associated with childhoodonset schizophrenia and psychosis not otherwise specified. Biol Psychiatry 2004, 55:976–980.

    Article  PubMed  CAS  Google Scholar 

  47. Schumacher J, Jamra RA, Freudenberg J, et al.: Examination of G72 and D-amino-acid oxidase as genetic risk factors for schizophrenia and bipolar affective disorder. Mol Psychiatry 2004, 9:203–207.

    Article  PubMed  CAS  Google Scholar 

  48. Chen YS, Akula N, Detera-Wadleigh SD, et al.: Findings in an independent sample support an association between bipolar affective disorder and the G72/G30 locus on chromosome 13q33. Mol Psychiatry 2004, 9:87–92.

    Article  PubMed  CAS  Google Scholar 

  49. Hattori E, Liu C, Badner JA, et al.: Polymorphisms at the G72/ G30 gene locus, on 13q33, are associated with bipolar disorder in two independent pedigree series. Am J Hum Genet 2003, 72:1131–1140.

    Article  PubMed  CAS  Google Scholar 

  50. Middleton FA, Pato MT, Gentile KL, et al.: Genomewide linkage analysis of bipolar disorder by use of a high-density singlenucleotide-polymorphism (SNP) genotyping assay: a comparison with microsatellite marker assays and finding of significant linkage to chromosome 6q22. Am J Hum Genet 2004, 74:886–897.

    Article  PubMed  CAS  Google Scholar 

  51. Fallin MD, Lasseter VK, Wolyniec PS, et al.: Genomewide linkage scan for bipolar-disorder susceptibility loci among Ashkenazi Jewish families. Am J Hum Genet 2004, 75:204–219.

    Article  PubMed  CAS  Google Scholar 

  52. McInnis MG, Dick DM, Willour VL, et al.: Genome-wide scan and conditional analysis in bipolar disorder: evidence for genomic interaction in the National Institute of Mental Health genetics initiative bipolar pedigrees. Biol Psychiatry 2003, 54:1265–1273.

    Article  PubMed  CAS  Google Scholar 

  53. Spielman RS, McGinnis RE, Ewens WJ: Transmission test for linkage disequilibrium: the insulin gene region and insulindependent diabetes mellitus (IDDM). Am J Hum Genet 1993, 52:506–516.

    PubMed  CAS  Google Scholar 

  54. Clayton D: A generalization of the transmission/disequilibrium test for uncertain-haplotype transmission. Am J Hum Genet 1999, 65:1170–1177.

    Article  PubMed  CAS  Google Scholar 

  55. Horvath S, Xu X, Laird NM: The family based association test method: strategies for studying general genotype-phenotype associations. Eur J Hum Genet 2001, 9:301–306.

    Article  PubMed  CAS  Google Scholar 

  56. Martin ER, Monks SA, Warren LL, Kaplan NL: A test for linkage and association in general pedigrees: the pedigree disequilibrium test. Am J Hum Genet 2000, 67:146–154.

    Article  PubMed  CAS  Google Scholar 

  57. Egger M, Smith GD, Phillips AN: Meta-analysis: principles and procedures. BMJ 1997, 315:1533–1537. This is not a very recent paper, but it provides a highly readable review of the meta-analysis methods currently being used for pooling of odds ratios of genetic association studies, and references for the various methods.

    PubMed  CAS  Google Scholar 

  58. Sutton AJ, Abrams KR, Jones DR, et al.: Methods for Meta-Analysis in Medical Research. New York: Wiley; 2000.

    Google Scholar 

  59. Lohmueller KE, Pearce CL, Pike M, et al.: Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 2003, 33:177–182. This paper includes meta-analyses of 25 reported associations of specific polymorphisms to common disorders, including psychiatric studies as listed in Tables 4 and 5. The authors make the valuable point that association results will tend to be quite variable in small samples due to lack of power, but that large samples or metaanalyses not infrequently detect significant association for polymorphisms that have produced positive results in some and negative results in other (mostly small) samples. The value of the individual meta-analyses reported in the paper is somewhat diminished by the failure of the journal to provide the details of each analysis (the studies included and the allele or genotype counts from each study) either in the text or online.

    Article  PubMed  CAS  Google Scholar 

  60. Egger M, Smith GD: Bias in location and selection of studies. BMJ 1998, 316:61–66.

    PubMed  CAS  Google Scholar 

  61. Egger M, Davey Smith G, Schneider M, Minder C: Bias in metaanalysis detected by a simple, graphical test. BMJ 1997, 315:629–634.

    PubMed  CAS  Google Scholar 

  62. Glatt SJ, Faraone SV, Tsuang MT: Meta-analysis identifies an association between the dopamine D2 receptor gene and schizophrenia. Mol Psychiatry 2003, 8:911–915.

    Article  PubMed  CAS  Google Scholar 

  63. Jonsson EG, Sillen A, Vares M, et al.: Dopamine D2 receptor gene Ser311Cys variant and schizophrenia: association study and meta-analysis. Am J Med Genet B Neuropsychiatr Genet 2003, 119:28–34.

    Article  PubMed  Google Scholar 

  64. Jonsson EG, Kaiser R, Brockmoller J, et al.: Meta-analysis of the dopamine D3 receptor gene (DRD3) Ser9Gly variant and schizophrenia. Psychiatr Genet 2004, 14:9–12.

    Article  PubMed  Google Scholar 

  65. Jonsson EG, Flyckt L, Burgert E, et al.: Dopamine D3 receptor gene Ser9Gly variant and schizophrenia: association study and meta-analysis. Psychiatr Genet 2003, 13:1–12.

    Article  PubMed  Google Scholar 

  66. Jonsson EG, Sedvall GC, Nothen MM, Cichon S: Dopamine D4 receptor gene (DRD4) variants and schizophrenia: metaanalyses. Schizophr Res 2003, 61:111–119.

    Article  PubMed  Google Scholar 

  67. Abdolmaleky HM, Faraone SV, Glatt SJ, Tsuang MT: Meta-analysis of association between the T102C polymorphism of the 5HT2a receptor gene and schizophrenia. Schizophr Res 2004, 67:53–62.

    Article  PubMed  Google Scholar 

  68. Lasky-Su JA, Faraone SV, Glatt SJ, Tsuang MT: Meta-analysis of the association between two polymorphisms in the serotonin transporter gene and affective disorders. Am J Med Genet 2004

  69. Lotrich FE, Pollock BG: Meta-analysis of serotonin transporter polymorphisms and affective disorders. Psychiatr Genet 2004, 14:121–129.

    Article  PubMed  Google Scholar 

  70. Lin PY, Tsai G: Association between serotonin transporter gene promoter polymorphism and suicide: results of a metaanalysis. Biol Psychiatry 2004, 55:1023–1030.

    Article  PubMed  CAS  Google Scholar 

  71. Anguelova M, Benkelfat C, Turecki G: A systematic review of association studies investigating genes coding for serotonin receptors and the serotonin transporter: II. Suicidal behavior. Mol Psychiatry 2003, 8:646–653.

    Article  PubMed  CAS  Google Scholar 

  72. Sen S, Burmeister M, Ghosh D: Meta-analysis of the association between a serotonin transporter promoter polymorphism (5-HTTLPR) and anxiety-related personality traits. Am J Med Genet B Neuropsychiatr Genet 2004, 127:85–89.

    Article  PubMed  Google Scholar 

  73. Faraone SV, Doyle AE, Mick E, Biederman J: Meta-analysis of the association between the 7-repeat allele of the dopamine D(4) receptor gene and attention deficit hyperactivity disorder. Am J Psychiatry 2001, 158:1052–1057.

    Article  PubMed  CAS  Google Scholar 

  74. Girault JA, Greengard P: The neurobiology of dopamine signaling. Arch Neurol 2004, 61:641–644.

    Article  PubMed  Google Scholar 

  75. Itokawa M, Arinami T, Futamura N, et al.: A structural polymorphism of human dopamine D2 receptor, D2(Ser311Cys). Biochem Biophys Res Commun 1993, 196:1369–1375.

    Article  PubMed  CAS  Google Scholar 

  76. Cravchik A, Sibley DR, Gejman PV: Functional analysis of the human D2 dopamine receptor missense variants. J Biol Chem 1996, 271:26013–26017.

    Article  PubMed  CAS  Google Scholar 

  77. Lannfelt L, Sokoloff P, Martres M, et al.: Amino-acid substitution in the dopamine D3 receptor as a useful polymorphism for investigating psychiatric disorders. Psychiatr Genet 1992, 2:249–256.

    Article  Google Scholar 

  78. Lichter JB, Barr CL, Kennedy JL, et al.: A hypervariable segment in the human dopamine receptor D4 (DRD4) gene. Hum Mol Genet 1993, 2:767–773.

    Article  PubMed  CAS  Google Scholar 

  79. Warren Jr JT, Peacock ML, Rodriguez LC, Fink JK: An MspI polymorphism in the hyman serotonin receptor gene (HTR2): detection by DGGE and RFLP analysis. Hum Mol Genet 1993, 2:338.

    Article  PubMed  CAS  Google Scholar 

  80. Glatt SJ, Faraone SV, Tsuang MT: Association between a functional catechol O-methyltransferase gene polymorphism and schizophrenia: meta-analysis of case-control and familybased studies. Am J Psychiatry 2003, 160:469–476.

    Article  PubMed  Google Scholar 

  81. Lotta T, Vidgren J, Tilgmann C, et al.: Kinetics of human soluble and membrane-bound catechol O-methyltransferase: a revised mechanism and description of the thermolabile variant of the enzyme. Biochemistry 1995, 34:4202–4210.

    Article  PubMed  CAS  Google Scholar 

  82. Sanders AR, Rusu I, Duan J, et al.: Haplotypic association spanning the 22q11.21 genes COMT and ARVCF with schizophrenia. Mol Psychiatry 2004

  83. Lesch KP, Balling U, Gross J, et al.: Organisation of the human serotonin transporter gene. J Neural Trans 1994, 95:157–162.

    Article  CAS  Google Scholar 

  84. Caspi A, Sugden K, Moffitt TE, et al.: Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 2003, 301:386–389.

    Article  PubMed  CAS  Google Scholar 

  85. Clayton D, Chapman J, Cooper J: Use of unphased multilocus genotype data in indirect association studies. Genet Epidemiol 2004, 27:415–428.

    Article  PubMed  Google Scholar 

  86. Seltman H, Roeder K, Devlin B: Evolutionary-based association analysis using haplotype data. Genet Epidemiol 2003, 25:48–58.

    Article  PubMed  Google Scholar 

  87. Neale BM, Sham PC: The future of association studies: genebased analysis and replication. Am J Hum Genet 2004, 75:353–362. This paper reviews prospects for more systematic genetic association studies based on methods for combining the effects of all polymorphisms in a gene into a single analysis (see also references 127 and 128), which would permit direct comparison and meta-analysis of studies when no single functional polymorphism is responsible for an association. Although there are problems with current methods, this is an important short-term goal in the field of genetic association studies.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Psychiatry, University of Pennsylvania School of Medicine, 3535 Market Street, Room 4006, 19104, Philadelphia, PA, USA

    Douglas F. Levinson MD

Authors
  1. Douglas F. Levinson MD
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Levinson, D.F. Meta-analysis in psychiatric genetics. Curr Psychiatry Rep 7, 143–152 (2005). https://doi.org/10.1007/s11920-005-0012-9

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11920-005-0012-9

Keywords

Search

Navigation