Replication in Genome-Wide Association Studies

Replication helps ensure that a genotype-phenotype association observed in a genome-wide association (GWA) study represents a credible association and is not a chance finding or an artifact due to uncontrolled biases. We discuss prerequisites for exact replication, issues of heterogeneity, advantages and disadvantages of different methods of data synthesis across multiple studies, frequentist vs. Bayesian inferences for replication, and challenges that arise from multi-team collaborations. While consistent replication can greatly improve the credibility of a genotype-phenotype association, it may not eliminate spurious associations due to biases shared by many studies. Conversely, lack of replication in well-powered follow-up studies usually invalidates the initially proposed association, although occasionally it may point to differences in linkage disequilibrium or effect modifiers across studies.Comment: Published in at http://dx.doi.org/10.1214/09-STS290 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Replicability analysis for genome-wide association studies

The paramount importance of replicating associations is well recognized in the genome-wide associaton (GWA) research community, yet methods for assessing replicability of associations are scarce. Published GWA studies often combine separately the results of primary studies and of the follow-up studies. Informally, reporting the two separate meta-analyses, that of the primary studies and follow-up studies, gives a sense of the replicability of the results. We suggest a formal empirical Bayes approach for discovering whether results have been replicated across studies, in which we estimate the optimal rejection region for discovering replicated results. We demonstrate, using realistic simulations, that the average false discovery proportion of our method remains small. We apply our method to six type two diabetes (T2D) GWA studies. Out of 803 SNPs discovered to be associated with T2D using a typical meta-analysis, we discovered 219 SNPs with replicated associations with T2D. We recommend complementing a meta-analysis with a replicability analysis for GWA studies.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS697 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Genome-wide association studies in ADHD

Attention-deficit/hyperactivity disorder, ADHD, is a common and highly heritable neuropsychiatric disorder that is seen in children and adults. Although heritability is estimated at around 76%, it has been hard to find genes underlying the disorder. ADHD is a multifactorial disorder, in which many genes, all with a small effect, are thought to cause the disorder in the presence of unfavorable environmental conditions. Whole genome linkage analyses have not yet lead to the identification of genes for ADHD, and results of candidate gene-based association studies have been able to explain only a tiny part of the genetic contribution to disease, either. A novel way of performing hypothesis-free analysis of the genome suitable for the identification of disease risk genes of considerably smaller effect is the genome-wide association study (GWAS). So far, five GWAS have been performed on the diagnosis of ADHD and related phenotypes. Four of these are based on a sample set of 958 parent–child trio’s collected as part of the International Multicentre ADHD Genetics (IMAGE) study and genotyped with funds from the Genetic Association Information Network (GAIN). The other is a pooled GWAS including adult patients with ADHD and controls. None of the papers reports any associations that are formally genome-wide significant after correction for multiple testing. There is also very limited overlap between studies, apart from an association with CDH13, which is reported in three of the studies. Little evidence supports an important role for the ‘classic’ ADHD genes, with possible exceptions for SLC9A9, NOS1 and CNR1. There is extensive overlap with findings from other psychiatric disorders. Though not genome-wide significant, findings from the individual studies converge to paint an interesting picture: whereas little evidence—as yet—points to a direct involvement of neurotransmitters (at least the classic dopaminergic, noradrenergic and serotonergic pathways) or regulators of neurotransmission, some suggestions are found for involvement of ‘new’ neurotransmission and cell–cell communication systems. A potential involvement of potassium channel subunits and regulators warrants further investigation. More basic processes also seem involved in ADHD, like cell division, adhesion (especially via cadherin and integrin systems), neuronal migration, and neuronal plasticity, as well as related transcription, cell polarity and extracellular matrix regulation, and cytoskeletal remodeling processes. In conclusion, the GWAS performed so far in ADHD, though far from conclusive, provide a first glimpse at genes for the disorder. Many more (much larger studies) will be needed. For this, collaboration between researchers as well as standardized protocols for phenotyping and DNA-collection will become increasingly important

Methodological Issues in Multistage Genome-Wide Association Studies

Because of the high cost of commercial genotyping chip technologies, many investigations have used a two-stage design for genome-wide association studies, using part of the sample for an initial discovery of ``promising'' SNPs at a less stringent significance level and the remainder in a joint analysis of just these SNPs using custom genotyping. Typical cost savings of about 50% are possible with this design to obtain comparable levels of overall type I error and power by using about half the sample for stage I and carrying about 0.1% of SNPs forward to the second stage, the optimal design depending primarily upon the ratio of costs per genotype for stages I and II. However, with the rapidly declining costs of the commercial panels, the generally low observed ORs of current studies, and many studies aiming to test multiple hypotheses and multiple endpoints, many investigators are abandoning the two-stage design in favor of simply genotyping all available subjects using a standard high-density panel. Concern is sometimes raised about the absence of a ``replication'' panel in this approach, as required by some high-profile journals, but it must be appreciated that the two-stage design is not a discovery/replication design but simply a more efficient design for discovery using a joint analysis of the data from both stages. Once a subset of highly-significant associations has been discovered, a truly independent ``exact replication'' study is needed in a similar population of the same promising SNPs using similar methods.Comment: Published in at http://dx.doi.org/10.1214/09-STS288 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Genome-wide association studies in Plasmodium species

Genome-wide association studies (GWAS) look for correlations between traits of interest and genetic markers spread throughout the genome. A recent study in BMC Genetics has found that populations of the malaria parasite Plasmodium vivax should be amenable to GWAS searching for a genetic basis of parasite pathogenicity. Geographical substructure in populations may, however, prove a problem in interpreting the results