Controlling false discoveries in candidate gene studies

Variants in TERT influencing telomere length are associated with paranoid schizophrenia risk

Schizophrenia is one of the most severe psychiatric disorders, with a high heritability of up to 80%. Several studies have reported telomere dysfunction in schizophrenia, and common variants in the telomerase reverse transcriptase (TERT) gene. TERT is a key component of the telomerase complex that maintains telomere length by addition of telomere repeats to telomere ends, and has repeatedly shown association with mean lymphocyte telomere length (LTL). Thus, we hypothesized that TERT may be a novel susceptibility gene for schizophrenia. Using a Taqman protocol, we genotyped eight tag SNPs from the TERT locus in 1,072 patients with paranoid schizophrenia and 1,284 control subjects from a Chinese Han population. We also measured mean LTL in 98 cases and 109 controls using a quantitative PCR-based technique. Chi-square tests showed that two SNPs, rs2075786 (P = 0.0009, OR = 0.76, 95%CI = 0.65-0.90) and rs4975605 (P = 0.0026, OR = 0.73, 95%CI = 0.60-0.90), were associated with a protective effect, while rs10069690 was associated with risk of paranoid schizophrenia (P = 0.0044, OR = 1.23, 95%CI = 1.07-1.42). Additionally, the rs2736118-rs2075786 haplotype showed significant association with paranoid schizophrenia (P = 0.0013). Moreover, mean LTL correlated with rs2075786 genotypes was significantly shorter in the patient group than the control group. The present results suggest that the TERT gene may be a novel candidate involved in the development of paranoid schizophrenia.

Genetic variants in long non-coding RNA MIAT contribute to risk of paranoid schizophrenia in a Chinese Han population

The heritability of schizophrenia has been reported to be as high as ~80%, but the contribution of genetic variants identified to this heritability remains to be estimated. Long non-coding RNAs (LncRNAs) are involved in multiple processes critical to normal cellular function and dysfunction of lncRNA MIAT may contribute to the pathophysiology of schizophrenia. However, the genetic evidence of lncRNAs involved in schizophrenia has not been documented. Here, we conducted a two-stage association analysis on 8 tag SNPs that cover the whole MIAT locus in two independent Han Chinese schizophrenia case-control cohorts (discovery sample from Shanxi Province: 1093 patients with paranoid schizophrenia and 1180 control subjects; replication cohort from Jilin Province: 1255 cases and 1209 healthy controls). In discovery stage, significant genetic association with paranoid schizophrenia was observed for rs1894720 (χ(2)=74.20, P=7.1E-18), of which minor allele (T) had an OR of 1.70 (95% CI=1.50-1.91). This association was confirmed in the replication cohort (χ(2)=22.66, P=1.9E-06, OR=1.32, 95%CI 1.18-1.49). Besides, a weak genotypic association was detected for rs4274 (χ(2)=4.96, df=2, P=0.03); the AA carriers showed increased disease risk (OR=1.30, 95%CI=1.03-1.64). No significant association was found between any haplotype and paranoid schizophrenia. The present studies showed that lncRNA MIAT was a novel susceptibility gene for paranoid schizophrenia in the Chinese Han population. Considering that most lncRNAs locate in non-coding regions, our result may explain why most susceptibility loci for schizophrenia identified by genome wide association studies were out of coding regions.

The gender-specific association of EHD3 polymorphisms with major depressive disorder

Recent work suggests that women have a higher liability to major depressive disorder (MDD) than men, but the mechanism for the gender difference remains unknown. Given a genetic component involved in MDD, genome-wide association studies (GWAS) have been performed to search for susceptibility loci for the diseases and several genes of interest have been reported, including the EH-domain containing 3 (EHD3) gene that encodes a protein participating in endosome protein trafficking. However, the polymorphism association of the EHD3 gene with MDD failed to be replicated in a Chinese Han population. In the present study, we stratified 517 MDD patients and 455 control subjects by gender and symptoms and found 3 SNPs present in the EHD3 gene, of which rs619002 and rs644926 were exclusively associated with female MDD (p=0.0045 and p=0.0074, respectively) and rs649729 (p=0.0029) was closely related to anxious mood of female patients, suggesting a gender-specific role of EHD3 in MDD. These positive findings help explain, at least from one aspect, the poor replication of GWAS results. Further functional analysis is needed to clarify how variants in EHD3 may play a female-specific role in the pathogenesis of MDD.

Multi-species data integration and gene ranking enrich significant results in an alcoholism genome-wide association study

BACKGROUND

A variety of species and experimental designs have been used to study genetic influences on alcohol dependence, ethanol response, and related traits. Integration of these heterogeneous data can be used to produce a ranked target gene list for additional investigation.

RESULTS

In this study, we performed a unique multi-species evidence-based data integration using three microarray experiments in mice or humans that generated an initial alcohol dependence (AD) related genes list, human linkage and association results, and gene sets implicated in C. elegans and Drosophila. We then used permutation and false discovery rate (FDR) analyses on the genome-wide association studies (GWAS) dataset from the Collaborative Study on the Genetics of Alcoholism (COGA) to evaluate the ranking results and weighting matrices. We found one weighting score matrix could increase FDR based q-values for a list of 47 genes with a score greater than 2. Our follow up functional enrichment tests revealed these genes were primarily involved in brain responses to ethanol and neural adaptations occurring with alcoholism.

CONCLUSIONS

These results, along with our experimental validation of specific genes in mice, C. elegans and Drosophila, suggest that a cross-species evidence-based approach is useful to identify candidate genes contributing to alcoholism.

The genetics of alcohol dependence

Alcohol consumption dates back to the Neolithic period, and alcohol dependence contributes substantially to the current global burden of disease. Despite this, optimal therapies and preventive strategies are lacking. Formal genetic studies of alcohol dependence have shown that genetic factors play as large a role in disease etiology as environmental factors. Molecular genetic studies may identify causal factors and facilitate the development of novel preventive and therapeutic approaches. Whereas earlier studies involved the use of linkage- and candidate-gene approaches, recent years have witnessed the introduction of genome-wide association studies (GWAS). The present review provides a brief overview of the findings of formal genetic studies, summarizes the results of earlier molecular-genetic investigations, and presents a detailed overview of all published GWAS in the field of alcohol dependence research. To date, few genome-wide significant findings have been reported. However, through the polygenic approach, GWAS have both confirmed the existence of a multitude of novel risk genes and indicated interesting new candidates.

The influence of five monoamine genes on trajectories of depressive symptoms across adolescence and young adulthood

The influence of five monoamine candidate genes on depressive symptom trajectories in adolescence and young adulthood were examined in the Add Health genetic sample. Results indicated that, for all respondents, carriers of the dopamine receptor D4 5-repeat allele were characterized by distinct depressive symptom trajectories across adolescence and early adulthood. Similarly, for males, individuals with the monoamine oxidase A 3.5-repeat allele exhibited unique depressive symptom trajectories. Specifically, the trajectories of those with the dopamine receptor D4 5-repeat allele were characterized by rising levels in the transition to adulthood, while their peers were experiencing a normative drop in depressive symptom frequency. Conversely, males with the monoamine oxidase A 3.5-repeat allele were shown to experience increased distress in late adolescence. An empirical method for examining a wide array of allelic combinations was employed, and false discovery rate methods were used to control the risk of false positives due to multiple testing. Special attention was given to thoroughly interrogate the robustness of the putative genetic effects. These results demonstrate the value of combining dynamic developmental perspectives with statistical genetic methods to optimize the search for genetic influences on psychopathology across the life course.

Gender-specific role of the protein tyrosine phosphatase receptor type R gene in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a common, chronic, and recurrent mental disease affecting millions of individuals worldwide. The precise mechanism by which the illness is developed remains unknown, but it has been accepted that a genetic component is very likely to be involved. Studies of the pathogenesis of MDD have implicated a reduced activity of the extracellular regulated kinase (ERK) signaling system. Protein tyrosine phosphatase, receptor type R (PTPRR) is a key negative regulator of the ERK signaling pathway and its expression is regulated by androgen. Therefore, it is worth testing whether the PTPRR gene could confer a risk of MDD.

METHODS

We genotyped 16 SNPs in the PTPRR locus with the MALDI-TOF-MS-based genotyping protocol in 517 patients with MDD and 455 controls among a Chinese Han population. The UNPHASED program was applied to analyze the genotyping data.

RESULTS

Of the 16 SNPs selected, rs1513105 was the only one showing allelic association (χ2=9.019, p=0.0027) and genotypic association (χ2=8.813, df=2, p=0.012), of which the rs1513105(C) allele was associated with an increased risk of MDD (OR=1.331, 95% CI 1.104-1.604), but the rs1513105 association resulted mainly from female subjects (χ2=12.35, p=0.00044 for allelic association; χ2=11.26, df=2, p=0.0036 for genotypic association).

LIMITATIONS

Replication and functional study may be required to draw a firm conclusion.

CONCLUSIONS

Our results suggest that the PTPRR gene may play a role in conferring risk of MDD in the female subjects.

Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs

Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here, we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K single nucleotide polymorphisms (SNPs), from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness study. Outcomes included 12 indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. A total of 21 SNPs satisfied this criterion. The top finding indicated that a SNP in Meis homeobox 2 (MEIS2) mediated the effects of risperidone on hip circumference (q=0.004). The same SNP was also found to mediate risperidone's effect on waist circumference (q=0.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as in several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement, and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study shows the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication.

Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics

Schizophrenia is an often devastating neuropsychiatric illness. Understanding the genetic variation affecting response to antipsychotics is important to develop novel diagnostic tests to match individual schizophrenia patients to the most effective and safe medication. In this study, we use a genome-wide approach to detect genetic variation underlying individual differences in response to treatment with the antipsychotics olanzapine, quetiapine, risperidone, ziprasidone and perphenazine. Our sample consisted of 738 subjects with DSM-IV schizophrenia who took part in the Clinical Antipsychotic Trials of Intervention Effectiveness. Subjects were genotyped using the Affymetrix 500 K genotyping platform plus a custom 164 K chip to improve genome-wide coverage. Treatment outcome was measured using the Positive and Negative Syndrome Scale. Our criterion for genome-wide significance was a prespecified threshold that ensures that, on an average, only 10% of the significant findings are false discoveries. The top statistical result reached significance at our prespecified threshold and involved a single-nucleotide polymorphism (SNP) in an intergenic region on chromosome 4p15. In addition, SNPs in Ankyrin Repeat and Sterile Alpha Motif Domain-Containing Protein 1B (ANKS1B) and in the Contactin-Associated Protein-Like 5 gene (CNTNAP5), which mediated the effects of olanzapine and risperidone on Negative symptoms, were very close to our threshold for declaring significance. The most significant SNP in CNTNAP5 is nonsynonymous, giving rise to an amino-acid substitution. In addition to highlighting our top results, we provide all P-values for download as a resource for investigators with the requisite samples to carry out replication. This study demonstrates the potential of genome-wide association studies to discover novel genes that mediate the effects of antipsychotics, which could eventually help to tailor drug treatment to schizophrenic patients.

Association study of SNAP25 and schizophrenia in Irish family and case-control samples

SNAP25 occurs on chromosome 20p12.2, which has been linked to schizophrenia in some samples, and recently linked to latent classes of psychotic illness in our sample. SNAP25 is crucial to synaptic functioning, may be involved in axonal growth and dendritic sprouting, and its expression may be decreased in schizophrenia. We genotyped 18 haplotype-tagging SNPs in SNAP25 in a sample of 270 Irish high-density families. Single marker and haplotype analyses were performed in FBAT and PDT. We adjusted for multiple testing by computing q values. Association was followed up in an independent sample of 657 cases and 411 controls. We tested for allelic effects on the clinical phenotype by using the method of sequential addition and 5 factor-derived scores of the OPCRIT. Nine of 18 SNPs had P values <0.05 in either FBAT or PDT for one or more definitions of illness. Several two-marker haplotypes were also associated. Subjects inheriting the risk alleles of the most significantly associated two-marker haplotype were likely to have higher levels of hallucinations and delusions. The most significantly associated marker, rs6039820, was observed to perturb 12 transcription-factor binding sites in in silico analyses. An attempt to replicate association findings in the case-control sample resulted in no SNPs being significantly associated. We observed robust association in both single marker and haplotype-based analyses between SNAP25 and schizophrenia in an Irish family sample. Although we failed to replicate this in an independent sample, this gene should be further tested in other samples.

In silico whole genome association scan for murine prepulse inhibition

BACKGROUND

The complex trait of prepulse inhibition (PPI) is a sensory gating measure related to schizophrenia and can be measured in mice. Large-scale public repositories of inbred mouse strain genotypes and phenotypes such as PPI can be used to detect Quantitative Trait Loci (QTLs) in silico. However, the method has been criticized for issues including insufficient number of strains, not controlling for false discoveries, the complex haplotype structure of inbred mice, and failing to account for genotypic and phenotypic subgroups.

METHODOLOGY/PRINCIPAL FINDINGS

We have implemented a method that addresses these issues by incorporating phylogenetic analyses, multilevel regression with mixed effects, and false discovery rate (FDR) control. A genome-wide scan for PPI was conducted using over 17,000 single nucleotide polymorphisms (SNPs) in 37 strains phenotyped. Eighty-nine SNPs were significant at a false discovery rate (FDR) of 5%. After accounting for long-range linkage disequilibrium, we found 3 independent QTLs located on murine chromosomes 1 and 13. One of the PPI positives corresponds to a region of human chromosome 6p which includes DTNBP1, a gene implicated in schizophrenia. Another region includes the gene Tsn which alters PPI when knocked out. These genes also appear to have correlated expression with PPI.

CONCLUSIONS/SIGNIFICANCE

These results support the usefulness of using an improved in silico mapping method to identify QTLs for complex traits such as PPI which can be then be used for to help identify loci influencing schizophrenia in humans.

Genome-wide association for major depressive disorder: a possible role for the presynaptic protein piccolo

Major depressive disorder (MDD) is a common complex trait with enormous public health significance. As part of the Genetic Association Information Network initiative of the US Foundation for the National Institutes of Health, we conducted a genome-wide association study of 435 291 single nucleotide polymorphisms (SNPs) genotyped in 1738 MDD cases and 1802 controls selected to be at low liability for MDD. Of the top 200, 11 signals localized to a 167 kb region overlapping the gene piccolo (PCLO, whose protein product localizes to the cytomatrix of the presynaptic active zone and is important in monoaminergic neurotransmission in the brain) with P-values of 7.7 x 10(-7) for rs2715148 and 1.2 x 10(-6) for rs2522833. We undertook replication of SNPs in this region in five independent samples (6079 MDD independent cases and 5893 controls) but no SNP exceeded the replication significance threshold when all replication samples were analyzed together. However, there was heterogeneity in the replication samples, and secondary analysis of the original sample with the sample of greatest similarity yielded P=6.4 x 10(-8) for the nonsynonymous SNP rs2522833 that gives rise to a serine to alanine substitution near a C2 calcium-binding domain of the PCLO protein. With the integrated replication effort, we present a specific hypothesis for further studies.

A genome-wide scan for Eysenckian personality dimensions in adolescent twin sibships: psychoticism, extraversion, neuroticism, and lie

We report the first genome-wide scan of adolescent personality. We conducted a genome-wide scan to detect linkage for measures of adolescent Psychoticism, Extraversion, Neuroticism, and Lie from the Junior Eysenck Personality Questionnaire. Data are based on 1,280 genotyped Australian adolescent twins and their siblings. The highest linkage peaks were found on chromosomes 16 and 19 for Neuroticism, on chromosomes 1, 7, 10, 13 m, and 18 for Psychoticism, and on chromosomes 2 and 3 for Extraversion.

Catechol-O-methyltransferase contributes to genetic susceptibility shared among anxiety spectrum phenotypes

BACKGROUND

Catechol-O-methyltransferase (COMT) has been investigated for its possible role in a wide range of psychiatric phenotypes. In particular, several studies support association of this gene with panic disorder and other anxiety-related traits.

METHODS

We examined the COMT gene for association with genetic risk across a range of anxiety spectrum phenotypes. We used multivariate structural equation modeling to select twin pairs scoring at the extremes of a latent genetic risk factor shared by neuroticism, several anxiety disorders, and major depression from a large population-based twin sample. With one member from each of these pairs, the resulting sample of 589 cases and 539 control subjects were entered into a two-stage association study in which genetic markers were screened in stage 1, the positive results of which were tested for replication in stage 2.

RESULTS

The functional val158met polymorphism (rs4680) plus nine other single nucleotide polymorphism markers selected to capture the major allelic variation across the COMT locus were analyzed for differences between cases and control subjects. Although the val (G) allele of rs4680 showed marginally significant association in our combined stage 1 plus stage 2 sample, a high-risk haplotype of this allele with the A allele of rs165599 was significantly over-represented in cases (p = 1.97e-5, odds ratio = 1.95). This haplotype also predicted individual differences in neuroticism and risk for several anxiety disorders and major depression. Consistent with prior studies, our findings are female-specific.

CONCLUSIONS

Variations in the COMT gene contribute to genetic risk shared across a range of anxiety-related phenotypes.

Controlling false discoveries in genetic studies

A false discovery occurs when a researcher concludes that a marker is involved in the etiology of the disease whereas in reality it is not. In genetic studies the risk of false discoveries is very high because only few among the many markers that can be tested will have an effect on the disease. In this article, we argue that it may be best to use methods for controlling false discoveries that would introduce the same ratio of false discoveries divided by all rejected tests into the literature regardless of systematic differences between studies. After a brief discussion of traditional "multiple testing" methods, we show that methods that control the false discovery rate (FDR) may be more suitable to achieve this goal. These FDR methods are therefore discussed in more detail. Instead of merely testing for main effects, it may be important to search for gene-environment/covariate interactions, gene-gene interactions or genetic variants affecting disease subtypes. In the second section, we point out the challenges involved in controlling false discoveries in such searches. The final section discusses the role of replication studies for eliminating false discoveries and the complexities associated with the definition of what constitutes a replication and the design of these studies.

Genomewide association for schizophrenia in the CATIE study: results of stage 1

Little is known for certain about the genetics of schizophrenia. The advent of genomewide association has been widely anticipated as a promising means to identify reproducible DNA sequence variation associated with this important and debilitating disorder. A total of 738 cases with DSM-IV schizophrenia (all participants in the CATIE study) and 733 group-matched controls were genotyped for 492,900 single-nucleotide polymorphisms (SNPs) using the Affymetrix 500K two-chip genotyping platform plus a custom 164K fill-in chip. Following multiple quality control steps for both subjects and SNPs, logistic regression analyses were used to assess the evidence for association of all SNPs with schizophrenia. We identified a number of promising SNPs for follow-up studies, although no SNP or multimarker combination of SNPs achieved genomewide statistical significance. Although a few signals coincided with genomic regions previously implicated in schizophrenia, chance could not be excluded. These data do not provide evidence for the involvement of any genomic region with schizophrenia detectable with moderate sample size. However, a planned genomewide association study for response phenotypes and inclusion of individual phenotype and genotype data from this study in meta-analyses hold promise for eventual identification of susceptibility and protective variants.

Association of ADH and ALDH genes with alcohol dependence in the Irish Affected Sib Pair Study of alcohol dependence (IASPSAD) sample

BACKGROUND

The genes coding for ethanol metabolism enzymes [alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH)] have been widely studied for their influence on the risk to develop alcohol dependence (AD). However, the relation between polymorphisms of these metabolism genes and AD in Caucasian subjects has not been clearly established. The present study examined evidence for the association of alcohol metabolism genes with AD in the Irish Affected Sib Pair Study of alcohol dependence.

METHODS

We conducted a case-control association study with 575 independent subjects who met Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, AD diagnosis and 530 controls. A total of 77 single nucleotide polymorphisms (SNPs) in the seven ADH (ADH1-7) and two ALDH genes (ALDH1A1 and ALDH2) were genotyped using the Illumina GoldenGate protocols. Several statistical procedures were implemented to control for false discoveries.

RESULTS

All markers with minor allele frequency greater than 0.01 were in Hardy-Weinberg equilibrium. Numerous SNPs in ADH genes showed association with AD, including one marker in the coding region of ADH1C (rs1693482 in exon6, Ile271Gln). Haplotypic association was observed in the ADH5 and ADH1C genes, and in a long haplotype block formed by the ADH1A and ADH1B loci. We detected two significant interactions between pairs of markers in intron 6 of ADH6 and intron 12 of ALDH2 (p = 5 x 10(-5)), and 5' of both ADH4 and ADH1A (p = 2 x 10(-4)).

CONCLUSION

We found evidence for the association of several ADH genes with AD in a sample of Western European origin. The significant interaction effects between markers in ADH and ALDH genes suggest possible epistatic roles between alcohol metabolic enzymes in the risk for AD.

Catechol-O-methyltransferase and the clinical features of psychosis

A functional polymorphism (Val-158-Met) at the Catechol-O-methyltransferase (COMT) locus has been identified as a potential etiological factor in schizophrenia. Yet the association has not been convincingly replicated across independent samples. We hypothesized that phenotypic heterogeneity might be diluting the COMT effect. To clarify the putative association, we performed an exploratory analysis to test for association between COMT and five psychosis symptom scales. These were derived through factor analysis of the Operational Criteria Checklist for Psychiatric Illness. Our sample was the Irish Study of High Density Schizophrenia Families, a large collection consisting of 268 multiplex families. This sample has previously shown a small but significant effect of the COMT Val allele in conferring risk for schizophrenia. We tested for preferential transmission of COMT alleles from parent to affected offspring (n = 749) for each of the five factor-derived scales (negative symptoms, delusions, hallucinations, mania, and depression). Significant overtransmission of the Val allele was found for mania (P < 0.05) and depression (P = 0.01) scales. Examination of odds ratios (ORs) revealed a heterogeneous effect of COMT, whereby it had no effect on Negative Symptoms, but largest impact on Depression (OR = 1.4). These results suggest a modest affective vulnerability conferred by this allele in psychosis, but will require replication.

Association between glutamic acid decarboxylase genes and anxiety disorders, major depression, and neuroticism

Abnormalities in the gamma-aminobutyric acid (GABA) neurotransmitter system have been noted in subjects with mood and anxiety disorders. Glutamic acid decarboxylase (GAD) enzymes synthesize GABA from glutamate, and, thus, are reasonable candidate susceptibility genes for these conditions. In this study, we examined the GAD1 and GAD2 genes for their association with genetic risk across a range of internalizing disorders. We used multivariate structural equation modeling to identify common genetic risk factors for major depression, generalized anxiety disorder, panic disorder, agoraphobia, social phobia and neuroticism (N) in a sample of 9270 adult subjects from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. One member from each twin pair for whom DNA was available was selected as a case or control based on scoring at the extremes of the genetic factor extracted from the analysis. The resulting sample of 589 cases and 539 controls was entered into a two-stage association study in which candidate loci were screened in stage 1, the positive results of which were tested for replication in stage 2. Several of the six single-nucleotide polymorphisms tested in the GAD1 region demonstrated significant association in both stages, and a combined analysis in all 1128 subjects indicated that they formed a common high-risk haplotype that was significantly over-represented in cases (P=0.003) with effect size OR=1.23. Out of 14 GAD2 markers screened in stage 1, only one met the threshold criteria for follow-up in stage 2. This marker, plus three others that formed significant haplotype combinations in stage 1, did not replicate their association with the phenotype in stage 2. Subject to confirmation in an independent sample, our study suggests that variations in the GAD1 gene may contribute to individual differences in N and impact susceptibility across a range of anxiety disorders and major depression.

Optimization of Two-Stage Genetic Designs Where Data Are Combined Using an Accurate and Efficient Approximation for Pearson's Statistic

There is an increasing interest in the use of two-stage case-control studies to reduce genotyping costs in the search for genes underlying common disorders. Instead of analyzing the data from the second stage separately, a more powerful test can be performed by combining the data from both stages. However, standard tests cannot be used because only the markers that are significant in the first stage are selected for the second stage and the test statistics at both stages are dependent because they partly involve the same data. Theoretical approximations are not available for commonly used test statistics and in this specific context simulations can be problematic because of the computational burden. We therefore derived a cost-effective, that is, accurate but fast in terms of central processing unit (CPU) time, approximation for the distribution of Pearson's statistic on 2 xm contingency tables in two-stage design with combined data. We included this approximation in an iterative method for designing optimal two-stage studies. Simulations supported the accuracy of our approximation. Numerical results confirmed that the use of two-stage designs reduces the genotyping burden substantially. Compared to not combining data, combining the data decreases the required sample sizes on average by 15% and the genotyping burden by 5%.