Pak Sham

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

Genetic power calculator: Design of linkage and association genetic mapping studies of complex traits

SUMMARY A website for performing power calculations for the design of linkage and association genetic mapping studies of complex traits. AVAILABILITY The package is made available athttp://statgen.iop.kcl.ac.uk/gpc/.

Monte Carlo tests for associations between disease and alleles at highly polymorphic loci

In an association analysis comparing cases and controls with respect to allele frequencies at a highly polymorphic locus, a potential problem is that the conventional chi‐squared test may not be valid for a large, sparse contingency table. However, reliance on statistics with known asymptotic distribution is now unnecessary, as Monte Carlo simulations can be performed to estimate the significance level of any test statistic. We have implemented a Monte Carlo method for four ‘chi‐squared’ test statistics, three of which involved combination of alleles, and evaluated their performance on a real data set. Combining rare alleles to avoid small expected cell counts, and considering each allele in turn against the rest, reduced the power to detect a genuine association when the number of alleles was very large. We should either not combine alleles at all, or combine them in such a way that preserves the evidence for an association.

Genetic and physiological data implicating the new human gene G72 and the gene for d-amino acid oxidase in schizophrenia

A map of 191 single-nucleotide polymorphism (SNPs) was built across a 5-Mb segment from chromosome 13q34 that has been genetically linked to schizophrenia. DNA from 213 schizophrenic patients and 241 normal individuals from Canada were genotyped with this marker set. Two 1,400- and 65-kb regions contained markers associated with the disease. Two markers from the 65-kb region were also found to be associated to schizophrenia in a Russian sample. Two overlapping genes G72 and G30 transcribed in brain were experimentally annotated in this 65-kb region. Transfection experiments point to the existence of a 153-aa protein coded by the G72 gene. This protein is rapidly evolving in primates, is localized to endoplasmic reticulum/Golgi in transfected cells, is able to form multimers and specifically binds to carbohydrates. Yeast two-hybrid experiments with the G72 protein identified the enzyme d-amino acid oxidase (DAAO) as an interacting partner. DAAO is expressed in human brain where it oxidizes d-serine, a potent activator of N-methyl-D-aspartate type glutamate receptor. The interaction between G72 and DAAO was confirmed in vitro and resulted in activation of DAAO. Four SNP markers from DAAO were found to be associated with schizophrenia in the Canadian samples. Logistic regression revealed genetic interaction between associated SNPs in vicinity of two genes. The association of both DAAO and a new gene G72 from 13q34 with schizophrenia together with activation of DAAO activity by a G72 protein product points to the involvement of this N-methyl-d-aspartate receptor regulation pathway in schizophrenia.

Gene-environment interaction analysis of serotonin system markers with adolescent depression

We report analyses from a study of gene–environment interaction in adolescent depression. The sample was selected from 1990 adolescents aged 10–20 years: those with depression symptoms in the top or bottom 15% were identified and divided into high or low environmental risk groups. DNA was obtained from 377 adolescents, representing the four quadrants of high or low depression and high or low environmental risk. Markers within, or close to, each of the serotonergic genes 5HTT, HTR2A, HTR2C, MAOA (monoamine oxidase type A) and tryptophan hydroxylase (TPH) were genotyped. Environmental risk group was a nonsignificant predictor and sex was a significant predictor of the depression group. HTR2A and TPH significantly predicted the depression group, independent of the effects of sex, environmental risk group and their interaction. In addition, there was a trend for an effect of 5HTTLPR, which was significant in female subjects. Furthermore, there was a significant genotype–environmental risk interaction for 5HTTLPR in female subjects only, with the effect being in the same direction as another recent study, reaffirming that an important source of genetic heterogeneity is exposure to environmental risk.

An extended transmission/disequilibrium test (TDT) for multi-allele marker loci

The transmission/disequilibrium test (TDT) was recently introduced by Spielman et al. (1993) as a test for linkage and linkage disequilibrium. The test is based on the unequal probability of transmission of two different marker alleles from parents to affected offspring, when the marker locus and the hypothetical disease locus are linked and are in linkage disequilibrium. The probabilities of marker allele transmission to affected offspring conditional on parental genotype have been derived by Ott (1989) for a biallelic marker and a recessive disorder with no phenocopies. Here, we derive the transmission probabilities for a multi‐allele marker locus and a generalized single locus disease model in a random sample of affected individuals from a randomly mating population. The form of these transmission probabilities suggests an extension of the TDT to multi‐allele marker loci, in which the alternative hypothesis is restricted to take account of the likely pattern of unequal transmission when the recombination fraction is near 0. We show how our extended TDT can be implemented by standard software for logistic regression, although we have also written our own program which is available on request. We have evaluated the approximate power of the test under a range of realistic assumptions, and it appears that the test will often have good power when linkage disequilibrium is strong and if the disease is recessive.

The Future of Association Studies: Gene-Based Analysis and Replication

Historically, association tests were limited to single variants, so that the allele was considered the basic unit for association testing. As marker density increases and indirect approaches are used to assess association through linkage disequilibrium, association is now frequently considered at the haplotypic level. We suggest that there are difficulties in replicating association findings at the single-nucleotide-polymorphism (SNP) or the haplotype level, and we propose a shift toward a gene-based approach in which all common variation within a candidate gene is considered jointly. Inconsistencies arising from population differences are more readily resolved by use of a gene-based approach rather than either a SNP-based or a haplotype-based approach. A gene-based approach captures all of the potential risk-conferring variations; thus, negative findings are subject only to the issue of power. In addition, chance findings due to multiple testing can be readily accounted for by use of a genewide-significance level. Meta-analysis procedures can be formalized for gene-based methods through the combination of P values. It is only a matter of time before all variation within genes is mapped, at which point the gene-based approach will become the natural end point for association analysis and will inform our search for functional variants relevant to disease etiology.

DNA Pooling: a tool for large-scale association studies

DNA pooling is a practical way to reduce the cost of large-scale association studies to identify susceptibility loci for common diseases. Pooling allows allele frequencies in groups of individuals to be measured using far fewer PCR reactions and genotyping assays than are used when genotyping individuals. Here, we discuss recent developments in quantitative genotyping assays and in the design and analysis of pooling studies. Sophisticated pooling designs are being developed that can take account of hidden population stratification, confounders and inter-loci interactions, and that allow the analysis of haplotypes.

The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder : association signals in DRD4, DAT1 and 16 other genes

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, starting in early childhood and persisting into adulthood in the majority of cases. Family and twin studies have demonstrated the importance of genetic factors and candidate gene association studies have identified several loci that exert small but significant effects on ADHD. To provide further clarification of reported associations and identify novel associated genes, we examined 1038 single-nucleotide polymorphisms (SNPs) spanning 51 candidate genes involved in the regulation of neurotransmitter pathways, particularly dopamine, norepinephrine and serotonin pathways, in addition to circadian rhythm genes. Analysis used within family tests of association in a sample of 776 DSM-IV ADHD combined type cases ascertained for the International Multi-centre ADHD Gene project. We found nominal significance with one or more SNPs in 18 genes, including the two most replicated findings in the literature: DRD4 and DAT1. Gene-wide tests, adjusted for the number of SNPs analysed in each gene, identified associations with TPH2, ARRB2, SYP, DAT1, ADRB2, HES1, MAOA and PNMT. Further studies will be needed to confirm or refute the observed associations and their generalisability to other samples.

Model-Free Analysis and Permutation Tests for Allelic Associations

In this short report, we address some practical problems in performing likelihood-based allelic association analysis of case-control data. Model-free statistics are proposed and their properties assessed by simulation, and procedures based on permutation tests are described for marker-marker as well as marker-disease associations. A memory-efficient algorithm is developed which enables several highly polymorphic markers to be analysed.