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Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis.

ABSTRACT: This is the first of three articles on a meta-analysis of genome scans of schizophrenia (SCZ) and bipolar disorder (BPD) that uses the rank-based genome scan meta-analysis (GSMA) method. Here we used simulation to determine the power of GSMA to detect linkage and to identify thresholds of significance. We simulated replicates resembling the SCZ data set (20 scans; 1,208 pedigrees) and two BPD data sets using very narrow (9 scans; 347 pedigrees) and narrow (14 scans; 512 pedigrees) diagnoses. Samples were approximated by sets of affected sibling pairs with incomplete parental data. Genotypes were simulated and nonparametric linkage (NPL) scores computed for 20 180-cM chromosomes, each containing six 30-cM bins, with three markers/bin (or two, for some scans). Genomes contained 0, 1, 5, or 10 linked loci, and we assumed relative risk to siblings (lambda(sibs)) values of 1.15, 1.2, 1.3, or 1.4. For each replicate, bins were ranked within-study by maximum NPL scores, and the ranks were averaged (R(avg)) across scans. Analyses were repeated with weighted ranks ((sqrt)N[genotyped cases] for each scan). Two P values were determined for each R(avg): P(AvgRnk) (the pointwise probability) and P(ord) (the probability, given the bin's place in the order of average ranks). GSMA detected linkage with power comparable to or greater than the underlying NPL scores. Weighting for sample size increased power. When no genomewide significant P values were observed, the presence of linkage could be inferred from the number of bins with nominally significant P(AvgRnk), P(ord), or (most powerfully) both. The results suggest that GSMA can detect linkage across multiple genome scans.

SUBMITTER: Levinson DF

PROVIDER: S-EPMC1180578 | biostudies-literature | 2003 Jul

REPOSITORIES: biostudies-literature

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Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis.

Levinson Douglas F DF Levinson Matthew D MD Segurado Ricardo R Lewis Cathryn M CM

American journal of human genetics 20030611 1

This is the first of three articles on a meta-analysis of genome scans of schizophrenia (SCZ) and bipolar disorder (BPD) that uses the rank-based genome scan meta-analysis (GSMA) method. Here we used simulation to determine the power of GSMA to detect linkage and to identify thresholds of significance. We simulated replicates resembling the SCZ data set (20 scans; 1,208 pedigrees) and two BPD data sets using very narrow (9 scans; 347 pedigrees) and narrow (14 scans; 512 pedigrees) diagnoses. Sam ...[more]

PMID: 12802787

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Project description:OBJECTIVE:Family and twin studies indicate substantial overlap of genetic influences on psychotic and mood disorders. Linkage and candidate gene studies have also suggested overlap across schizophrenia, bipolar disorder, and major depressive disorder. The purpose of this study was to apply genomewide association study (GWAS) analysis to address the specificity of genetic effects on these disorders. METHOD:The authors combined GWAS data from three large effectiveness studies of schizophrenia (CATIE, genotyped: N=741), bipolar disorder (STEP-BD, geno-typed: N=1,575), and major depressive disorder (STAR*D, genotyped: N=1,938) as well as from psychiatrically screened control subjects (NIMH-Genetics Repository: N=1,204). A two-stage analytic procedure involving an omnibus test of allele frequency differences among case and control groups was applied, followed by a model selection step to identify the best-fitting model of allelic effects across disorders. RESULTS:The strongest result was seen for a single nucleotide polymorphism near the adrenomedullin (ADM) gene (rs6484218), with the best-fitting model indicating that the effect was specific to bipolar II disorder. Findings also revealed evidence suggesting that several genes may have effects that transcend clinical diagnostic boundaries, including variants in NPAS3 that showed pleiotropic effects across schizophrenia, bipolar disorder, and major depressive disorder. CONCLUSIONS:This study provides the first genomewide significant evidence implicating variants near the ADM gene on chromosome 11p15 in psychopathology, with effects that appear to be specific to bipolar II disorder. Although genomewide significant evidence of cross-disorder effects was not detected, the results provide evidence that there are both pleiotropic and disorder-specific effects on major mental illness and illustrate an approach to dissecting the genetic basis of mood and psychotic disorders that can inform future large-scale cross-disorder GWAS analyses.

Dataset Information

Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis.

Publications

Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis.

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