We propose in this paper a statistical framework based on a shape-invariant model together with a false discovery rate (FDR) procedure for identifying periodically expressed genes based on microarray time-course gene expression data and a set of known periodically expressed guide genes. We applied the proposed methods to the alpha-factor, cdc15 and cdc28 synchronized yeast cell cycle data sets and identified a total of 1010 cell-cycle-regulated genes at a FDR of 0.5% in at least one of the three data sets analyzed, including 89 (86%) of 104 known periodic transcripts. We also identified 344 and 201 circadian rhythmic genes in vivo in mouse heart and liver tissues with FDR of 10 and 2.5%, respectively. Our results also indicate that the shape-invariant model fits the data well and provides estimate of the common shape function and the relative phases for these periodically regulated genes.

Several studies have identified the PTPN22 allelic variant 1858 C/T that encodes the R620W amino-acid change as a putative susceptibility factor in autoimmune diseases. The current study was undertaken to examine a large cohort of Finnish rheumatoid arthritis (RA) and juvenile idiopathic arthritis (JIA) subjects using both population control and, importantly, familybased association methods. The latter is particularly important when, as is the case for the 1858 C/T polymorphism, the frequency of the variant allele (T) differs in both major ancestral populations and in subpopulations. The analysis of rheumatoid factor-positive 1030 RA probands from Finland provides strong support for association of this variant in both population studies (allele specific odds ratio (OR) ¼ 1.47, 95% confidence interval (CI) ¼ 1.27-1.70, P ¼ 3 Â 10 À7 ) and in family studies (Po10 À6 ). In contrast, no allelic association was seen with JIA (230 probands) and only weak evidence for a genotypic effect of 1858T homozygotes was observed in this population. Genes and Immunity (2005) 6, 720-722.

Angiotensin II is a strong candidate for the perpetuation of autoimmunity, nephritis and visceral damage in systemic lupus erythematosus (SLE

Once a genetic region involved in a complex disease has been localized through linkage or association studies, we need methods to help us identify the actual disease predisposing genetic variant(s) in the region. A large number of single nucleotide polymorphic (SNP) sites may exist in this region. It is important to identify genetic variants directly involved in disease from those in linkage disequilibrium, and thus associated with, the disease predisposing variant(s). A question of great interest is to test whether a SNP, or a combination of SNPs, that influence the trait under investigation have been identified. For many complex HLA‐associated diseases, patterns of amino acid site variability raise the possibility that HLA‐variation association with a disease may not be due to a given allele but rather one or more variable amino acid sites occurring on several alleles. Here the question is whether an amino acid variant or a combination of amino acid variants involved in disease are identified. To address this question, this paper proposes a permutation procedure for the haplotype method, to test whether all the sites involved in the disease have been identified using the haplotypic data of patients and controls. The method is based on the theoretical result of Valdes and Thomson, that, for each haplotype combination containing all the amino acid sites involved in the disease process, the relative frequencies of amino acid variants at sites not involved in disease, but in linkage disequilibrium with the disease‐predisposing sites, are expected to be the same in patients and controls. This procedure takes into account the non‐independence of the sites sampled and is robust to mode of inheritance and penetrance of the disease, and can definitely specify when all the disease predisposing sites have not been identified. Application to both simulated data and real data sets on type 1 diabetes and alcoholism indicates that the proposed procedure works well in testing the important null hypothesis of whether all the predisposing sites are identified.

summaryInformation on the age of a patient at disease onset, an important feature of complex diseases, is often collected in studies designed to map the disease genes. Penetrance-model-free methods, requiring no specification of penetrance functions, have been used extensively for detecting linkage and association between marker and disease loci. In this paper, we conduct an analytical study to examine the effects of incorporation of age at onset information on the power of two commonly used penetrance-model-free methods, the affected sib-pair (ASP) and transmission/disequilibrium tests (TDT). Assuming a Cox model with a major gene effect for the age at onset, we quantify analytically how age at onset affects the identity by descent (IBD) probabilities, the mean IBD values, and the expected numbers of alleles transmitted from heterozygous parents to affected children under various genetic models. We show that the power of the mean IBD test and the TDT can be greatly affected by the ages at onset of affected siblings or children used in the study. Generally, the most powerful test for ASPs is that based on affected sib pairs both having early disease onset and for TDT analyses is that based on trios with early-onset children. Naively combining affected sib pairs with different ages at onset or parent-children trios with different ages at onset of affected children can result in reduced power for detecting linkage or association. These results may be used to guide collection and analysis of sib pairs or families for diseases with variable age at onset.