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The correlation between alleles at a pair of genetic loci is a measure of linkage disequilibrium. The square of the sample correlation multiplied by sample size provides the usual test statistic for the hypothesis of no disequilibrium for loci with two alleles and this relation has proved useful for study design and marker selection. Nevertheless, this relation holds only in a diallelic case, and an extension to multiple alleles has not been made. Here we introduce a similar statistic, R2, which leads to a correlation-based test for loci with multiple alleles: for a pair of loci with k and m alleles, and a sample of n individuals, the approximate distribution of n(k - 1)(m - 1)/(km)R2 under independence between loci is chi2(k-1(m-1). One advantage of this statistic is that it can be interpreted as the total correlation between a pair of loci. When the phase of two-locus genotypes is known, the approach is equivalent to a test for the overall correlation between rows and columns in a contingency table. In the phase-known case, R2 is the sum of the squared sample correlations for all km 2 x 2 subtables formed by collapsing to one allele vs. the rest at each locus. We examine the approximate distribution under the null of independence for R2 and report its close agreement with the exact distribution obtained by permutation. The test for independence using R2 is a strong competitor to approaches such as Pearson's chi square, Fisher's exact test, and a test based on Cressie and Read's power divergence statistic. We combine this approach with our previous composite-disequilibrium measures to address the case when the genotypic phase is unknown. Calculation of the new multiallele test statistic and its P-value is very simple and utilizes the approximate distribution of R2. We provide a computer program that evaluates approximate as well as "exact" permutational P-values.

While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA) method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1) it tests for a joint effect of gene variants, including both common and rare; (2) it fully utilizes linkage disequilibrium and genetic position information; and (3) allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods – SKAT and a previously proposed method based on functional linear models (FLM), – especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM) to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity. [ABSTRACT FROM AUTHOR]

Chronic pain is highly variable between individuals, as is the response to analgesics. Although much of the variability in chronic pain and analgesic response is heritable, an understanding of the genetic determinants underlying this variability is rudimentary. Here we show that variation within the coding sequence of the gene encoding the P2X7 receptor (P2X7R) affects chronic pain sensitivity in both mice and humans. P2X7Rs, which are members of the family of ionotropic ATP-gated receptors, have two distinct modes of function: they can function through their intrinsic cationic channel or by forming nonselective pores that are permeable to molecules with a mass of up to 900 Da. Using genome-wide linkage analyses, we discovered an association between nerve-injury-induced pain behavior (mechanical allodynia) and the P451L mutation of the mouse P2rx7 gene, such that mice in which P2X7Rs have impaired pore formation as a result of this mutation showed less allodynia than mice with the pore-forming P2rx7 allele. Administration of a peptide corresponding to the P2X7R C-terminal domain, which blocked pore formation but not cation channel activity, selectively reduced nerve injury and inflammatory allodynia only in mice with the pore-forming P2rx7 allele. Moreover, in two independent human chronic pain cohorts, a cohort with pain after mastectomy and a cohort with osteoarthritis, we observed a genetic association between lower pain intensity and the hypofunctional His270 (rs7958311) allele of P2RX7. Our findings suggest that selectively targeting P2X7R pore formation may be a new strategy for individualizing the treatment of chronic pain. [ABSTRACT FROM AUTHOR]

Abstract: Human association studies of common genetic polymorphisms have identified many loci that are associated with risk of complex diseases, although individual loci typically have small effects. However, by envisaging genetic associations in terms of cellular pathways, rather than any specific polymorphism, combined effects of many biologically relevant alleles can be detected. The effects are likely to be most apparent in investigations of phenotypically homogenous subtypes of complex diseases. We report findings from a case-control, genetic association study of relationships between 2925 single nucleotide polymorphisms (SNPs) and 2 subtypes of a commonly occurring chronic facial pain condition, temporomandibular disorder (TMD): 1) localized TMD and 2) TMD with widespread pain. When compared to healthy controls, cases with localized TMD differed in allelic frequency of SNPs that mapped to a serotonergic receptor pathway (P =0.0012), while cases of TMD with widespread pain differed in allelic frequency of SNPs that mapped to a T-cell receptor pathway (P =0.0014). A risk index representing combined effects of 6 SNPs from the serotonergic pathway was associated with greater odds of localized TMD (odds ratio 2.7, P =1.3 E-09), and the result was reproduced in a replication case-control cohort study of 639 people (odds ratio 1.6, P =0.014). A risk index representing combined effects of 8 SNPs from the T-cell receptor pathway was associated with greater odds of TMD with widespread pain (P =1.9 E-08), although the result was not significant in the replication cohort. These findings illustrate potential for clinical classification of chronic pain based on distinct molecular profiles and genetic background. [Copyright &y& Elsevier]