Updated 29 August 2007

1. Introduction

Schizophrenia is a complex disorder, the aetiology of which is extremely difficult to determine (Mueser and McGurk, 2004). Genetic research has been hindered by the non-Mendelian inheritance of schizophrenia and the lack of a neuropathological method of diagnosis or the availability of disease-specific biomarkers (Owen et al., 2005). Although the heritability of schizophrenia is high (~80 percent), environmental factors including obstetric complications and sociodemographic factors also play a significant role in the development of the disease, further complicating progress in the field of genetic schizophrenia research (Sullivan et al., 2003). Despite these difficulties, several chromosomal regions have been suggested from whole genome linkage analyses, but only a few of these loci overlap across studies or are consistently implied by meta-analyses (e.g., Badner and Gershon, 2002; Lewis et al., 2003).

In the past decade, literally hundreds of reports have been published claiming or refuting genetic association between putative schizophrenia genes and disease risk, onset age, or other certain endophenotypes. Overall, the results of these studies have been largely inconclusive. We estimate that 50 to 100 schizophrenia genetic association studies are currently being published annually from research groups worldwide. For the public but also for the schizophrenia genetics research community, this wealth of information is becoming increasingly more difficult to follow, evaluate, and much less to interpret.

2. Database Organization and Methods

Overview

The goal of the SchizophreniaGene database is to serve as a comprehensive, unbiased, publicly available and regularly updated collection of published genetic association studies performed on schizophrenia. Eligible publications are identified following systematic searches of scientific literature databases, as well as the table of contents of journals in genetics and psychiatry. If an association study also included subjects afflicted with disorders other than schizophrenia (e.g., bipolar disorder or schizoaffective disorder), generally only samples fulfilling diagnostic criteria for schizophrenia are included in the database and subsequent analyses, if they were listed separately in the original publication. Data selected for display summarize key characteristics of the investigated study cohorts (e.g., gene overview), as well as genotype distributions in cases and controls (e.g., polymorphism details). For polymorphisms with genotype data in at least four case-control samples, continuously updated random-effects meta-analyses are presented (see meta-analysis methods). Note that data obtained from family-based studies are not included in the meta-analyses, as crude odds ratios cannot be readily calculated from overall genotype distributions. However, these studies and their qualitative results are still listed on the gene-summary pages of the SchizophreniaGene website (see Table 2 for example).

To ensure the highest degree of scientific objectivity, only studies published in peer-reviewed journals available in English are considered for inclusion into the database. In particular, this precludes the inclusion of data presented only in abstracted form, e.g. at scientific meetings. We encourage authors of original reports fulfilling the above criteria to submit their data as soon as their work is accepted for publication.

Meta-Analysis Methods

For all polymorphisms with minor allele frequencies in healthy controls >1%, and for which case-control genotype data are available in four or more independent samples, crude odds ratios (ORs) and 95 percent confidence intervals (CIs) are calculated from the reported allele distributions for each study. Summary ORs and 95 percent CIs are calculated using the DerSimonian and Laird (1986) random-effects model, which utilizes weights that incorporate both within-study and between-study variance. This procedure is done including all studies irrespective of ethnicity (denoted by "All Studies" on the meta-analysis figures), and repeated after exclusion of the initial study ("All Excl Initial Study"), after exclusion of studies in which a deviation of Hardy-Weinberg Equilibrium (HWE) was detected in controls ("All Excl HWE Deviations"), and after exclusion of samples of non-Caucasian ancestry ("All Caucasian Studies"). Overlapping samples (of which usually only the largest is included), studies with missing data, or control samples deviating from HWE are indicated on the meta-analysis graphs. Please note, that when only a few studies are included in the meta-analyses (i.e. less than ~10), the random effects model may yield summary ORs and confidence bounds that are slightly anti-conservative.

To allow a visual assessment of the presence of publication bias (or other sorts of reporting bias), we use a Begg modified funnel plot which depicts the allele-specific OR (on a logarithmic scale) against its standard error for each study (Egger, 1997) including studies of all ethnicities. Note that the power to detect deviations from a symmetrical distribution is limited, especially for analyses based on less than ~20 individual studies.

Inclusion of Genome-wide Association (GWA) Analyses

The systematic inclusion of data from large-scale studies and GWA analyses represents a conceptual and computational challenge for any genetic database. We have devised the following step-wise protocol, which we believe allows us to capture the most relevant genetic information without the need to include every data-point from these studies. Note that this feature of SchizophreniaGene is new and still under development. Please visit this page to see a summary of all published large-scale studies currently included in SchizophreniaGene.

Stage I: Represents the inclusion of genes and polymorphisms “featured” or highlighted by the authors of the large-scale study, usually because they show some degree of genetic association after completion of all analyses, e.g. testing multiple independent samples. These genes and polymorphisms probably represent the most important findings of each large-scale analysis and are therefore included here with highest priority. This stage has already been implemented in the current version of SchizophreniaGene (e.g. for the CSF2RA gene featured in the GWA study by Lencz et al. [2007]).

For large-scale/GWA studies that have made their genotype data publicly available, we will also make use of “non-featured” genotype distributions, i.e. of polymorphisms not believed to be associated with schizophrenia in the original publications:

Stage II: Will add large-scale/GWA genotype data for polymorphisms already available in SchizophreniaGene, i.e. usually derived from candidate gene studies published prior to 2007. Large-scale/GWA data for such overlapping polymorphisms will be added to the gene-specific entries and, if genotype data is then available in a total of at least four independent case-control samples, included and displayed in the meta-analyses. This stage adds valuable information to the existing SchizophreniaGene meta-analyses as it is derived from assessments that are largely unbiased with respect to gene function, in contrast to most conventional candidate gene studies. This feature is not yet available in SchizophreniaGene.

Stage III: Applies to GWA studies only. If genotype distributions are publicly available for multiple GWA scans, we will perform systematic meta-analyses for all markers overlapping in at least four independent case-control samples. Only those showing significant summary ORs will be displayed on the SchizophreniaGene website. The threshold of declaring statistical significance (resulting in being displayed at the front-end of the database) in this context will be more stringent, due to the large number of tests performed (i.e. P-values of the summary ORs <<0.05). Procedures for implementing this stage, and the definition of appropriate threshold criteria is currently underway and will follow guidelines suggested previously (Evangelou, 2007). This feature is not yet available in SchizophreniaGene.

For more details on inclusion criteria, literature searches, data-management procedures, statistical analyses, and online database structure, please see Bertram et al. (2007).

3. Summary of Meta-analysis Highlights: The "Top Results" List

In an effort to facilitate the identification of the most promising meta-analysis results available in SchizophreniaGene, a continuously updated list displaying the most strongly associated genes ("Top Results") has been added to the homepage. The list is ranked by effect size, and only includes genes that contain at least one variant showing a nominally significant summary OR in the analysis of all ethnic groups (“All”), or those limited to samples of Caucasian ancestry (“Caucasian only”). While we believe that this list represents an up-to-date summary of particularly promising schizophrenia candidate genes that warrant follow-up with high priority, we note that many of these may represent false-positive findings, in particular those based on small (<10) sample sizes.

References

Badner JA, Gershon ES. Meta-analysis of whole-genome linkage scans of bipolar disorder and schizophrenia. Mol Psychiatry. 2002;7(4):405-11. Abstract

Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet. 2007 Jan 1;39(1):17-23. Abstract

Evangelou E, Maraganore DM, Ioannidis JP. "Meta-analysis in genome-wide association datasets: strategies and application in Parkinson disease." PLoS ONE. 2007 Feb 7;2:e196. Abstract

Harrison PJ, Owen MJ. Genes for schizophrenia? Recent findings and their pathophysiological implications. Lancet. 2003 Feb 1;361(9355):417-9. Review. Abstract

Lewis CM, Levinson DF, Wise LH, DeLisi LE, Straub RE, Hovatta I, Williams NM, Schwab SG, Pulver AE, Faraone SV, Brzustowicz LM, Kaufmann CA, Garver DL, Gurling HM, Lindholm E, Coon H, Moises HW, Byerley W, Shaw SH, Mesen A, Sherrington R, O'Neill FA, Walsh D, Kendler KS, Ekelund J, Paunio T, Lonnqvist J, Peltonen L, O'Donovan MC, Owen MJ, Wildenauer DB, Maier W, Nestadt G, Blouin JL, Antonarakis SE, Mowry BJ, Silverman JM, Crowe RR, Cloninger CR, Tsuang MT, Malaspina D, Harkavy-Friedman JM, Svrakic DM, Bassett AS, Holcomb J, Kalsi G, McQuillin A, Brynjolfson J, Sigmundsson T, Petursson H, Jazin E, Zoega T, Helgason T. Genome scan meta-analysis of schizophrenia and bipolar disorder, part II: Schizophrenia. Am J Hum Genet. 2003 Jul;73(1):34-48. Epub 2003 Jun 11. Abstract

Mueser KT, McGurk SR. Schizophrenia. Lancet. 2004 Jun 19;363(9426):2063-72. Review. Abstract

Owen MJ, Craddock N, O'Donovan MC. Schizophrenia: genes at last? Trends Genet. 2005 Sep;21(9):518-25. Review. Abstract

Sullivan PF, Kendler KS, Neale MC. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry. 2003 Dec;60(12):1187-92. Abstract