Hip joint replacement surgery for idiopathic osteoarthritis aggregates in families

In order to determine whether there is a genetic component to hip or knee joint failure due to idiopathic osteoarthritis (OA), we invited patients (probands) undergoing hip or knee arthroplasty for management of idiopathic OA to provide detailed family histories regarding the prevalence of idiopathic OA requiring joint replacement in their siblings. We also invited their spouses to provide detailed family histories about their siblings to serve as a control group. In the probands, we confirmed the diagnosis of idiopathic OA using American College of Rheumatology criteria. The cohorts included the siblings of 635 probands undergoing total hip replacement, the siblings of 486 probands undergoing total knee replacement, and the siblings of 787 spouses. We compared the prevalence of arthroplasty for idiopathic OA among the siblings of the probands with that among the siblings of the spouses, and we used logistic regression to identify independent risk factors for hip and knee arthroplasty in the siblings. Familial aggregation for hip arthroplasty, but not for knee arthroplasty, was observed after controlling for age and sex, suggesting a genetic contribution to end-stage hip OA but not to end-stage knee OA. We conclude that attempts to identify genes that predispose to idiopathic OA resulting in joint failure are more likely to be successful in patients with hip OA than in those with knee OA.     

Adding confidence to gene expression clustering

It has been well established that gene expression data contain large amounts of random variation that affects both the analysis and the results of microarray experiments. Typically, microarray data are either tested for differential expression between conditions or grouped on the basis of profiles that are assessed temporally or across genetic or environmental conditions. While testing differential expression relies on levels of certainty to evaluate the relative worth of various analyses, cluster analysis is exploratory in nature and has not had the benefit of any judgment of statistical inference. By using a novel dissimilarity function to ascertain gene expression clusters and conditional randomization of the data space to illuminate distinctions between statistically significant clusters of gene expression patterns, we aim to provide a level of confidence to inferred clusters of gene expression data. We apply both permutation and convex hull approaches for randomization of the data space and show that both methods can provide an effective assessment of gene expression profiles whose coregulation is statistically different from that expected by random chance alone.     

Model selection in binary trait locus mapping

Quantitative trait locus (QTL) mapping methodology for continuous normally distributed traits is the subject of much attention in the literature. Binary trait locus (BTL) mapping in experimental populations has received much less attention. A binary trait by definition has only two possible values, and the penetrance parameter is restricted to values between zero and one. Due to this restriction, the infinitesimal model appears to come into play even when only a few loci are involved, making selection of an appropriate genetic model in BTL mapping challenging. We present a probability model for an arbitrary number of BTL and demonstrate that, given adequate sample sizes, the power for detecting loci is high under a wide range of genetic models, including most epistatic models. A novel model selection strategy based upon the underlying genetic map is employed for choosing the genetic model. We propose selecting the "best" marker from each linkage group, regardless of significance. This reduces the model space so that an efficient search for epistatic loci can be conducted without invoking stepwise model selection. This procedure can identify unlinked epistatic BTL, demonstrated by our simulations and the reanalysis of Oncorhynchus mykiss experimental data.     

Effect of arylformamidase (kynurenine formamidase) gene inactivation in mice on enzymatic activity, kynurenine pathway metabolites and phenotype

The gene coding for arylformamidase (Afmid, also known as kynurenine formamidase) was inactivated in mice through the removal of a shared bidirectional promoter region regulating expression of the Afmid and thymidine kinase (Tk) genes. Afmid/Tk -deficient mice are known to develop sclerosis of glomeruli and to have an abnormal immune system. Afmid-catalyzed hydrolysis of N-formyl-kynurenine is a key step in tryptophan metabolism and biosynthesis of kynurenine-derived products including kynurenic acid, quinolinic acid, nicotinamide, NAD, and NADP. A disruption of these pathways is implicated in neurotoxicity and immunotoxicity. In wild-type (WT) mice, Afmid-specific activity (as measured by formyl-kynurenine hydrolysis) was 2-fold higher in the liver than in the kidney. Formyl-kynurenine hydrolysis was reduced by approximately 50% in mice heterozygous (HZ) for Afmid/Tk and almost completely eliminated in Afmid/Tk knockout (KO) mice. However, there was 13% residual formyl-kynurenine hydrolysis in the kidney of KO mice, suggesting the existence of a formamidase other than Afmid. Liver and kidney levels of nicotinamide plus NAD/NADP remained the same in WT, HZ and KO mice. Plasma concentrations of formyl-kynurenine, kynurenine, and kynurenic acid were elevated in KO mice (but not HZ mice) relative to WT mice, further suggesting that there must be enzymes other than Afmid (possibly in the kidney) capable of metabolizing formyl-kynurenine into kynurenine. Gradual kidney deterioration and subsequent failure in KO mice is consistent with high levels of tissue-specific Afmid expression in the kidney of WT but not KO mice. On this basis, the most significant function of the kynurenine pathway and Afmid in mice may be in eliminating toxic metabolites and to a lesser extent in providing intermediates for other processes.     

Modifying the Schwarz Bayesian information criterion to locate multiple interacting quantitative trait loci

The problem of locating multiple interacting quantitative trait loci (QTL) can be addressed as a multiple regression problem, with marker genotypes being the regressor variables. An important and difficult part in fitting such a regression model is the estimation of the QTL number and respective interactions. Among the many model selection criteria that can be used to estimate the number of regressor variables, none are used to estimate the number of interactions. Our simulations demonstrate that epistatic terms appearing in a model without the related main effects cause the standard model selection criteria to have a strong tendency to overestimate the number of interactions, and so the QTL number. With this as our motivation we investigate the behavior of the Schwarz Bayesian information criterion (BIC) by explaining the phenomenon of the overestimation and proposing a novel modification of BIC that allows the detection of main effects and pairwise interactions in a backcross population. Results of an extensive simulation study demonstrate that our modified version of BIC performs very well in practice. Our methodology can be extended to general populations and higher-order interactions.     

Structure and regulation of the anthranilate synthase genes in Pseudomonas aeruginosa: II. Cloning and expression in Escherichia coli

The genes for the large and small subunits of anthranilate synthase (trpE and trpG, respectively) have been cloned from Pseudomonas aeruginosa PAC174 into E. coli by R-prime formation with the broad-host- range plasmid R68.44. Sequential subcloning into plasmid vectors reduced the active Pseudomonas DNA fragment to a length of 3.1 kb. We obtained evidence that this region contains the promoter for its own expression and retains a vestigial regulatory response to tryptophan scarcity or excess.      

Schiff and pseudo-Schiff reagents: the reactions and reagents of Hugo Schiff,including a classification of various kinds of histochemical reagents used to detect aldehydes

During the 1860’s, Hugo Schiff studied many reactions between amines and aldehydes, some of which have been used in histochemistry, at times without credit to Schiff. Much controversy has surrounded the chemical structures and reaction mechanisms of the compounds involved, but modern analytical techniques have clarified the picture. I review these reactions here. I used molecular modeling software to investigate dyes that contain primary amines representing eight chemical families. All dyes were known to perform satisfactorily for detecting aldehydes in tissue sections. The models verified the correct chemical structures at various points in their reactions and also determined how decolorization occurred in those with “leuco” forms. Decolorization in the presence of sulfurous acid can occur by either adduction or reduction depending on the dye. The final condensation product with aldehyde was determined to be either a C-sulfonic acid adduct on the carbonyl carbon atom or an aminal at the same atom. Based on the various outcomes, I have placed the dyes and their reactions into five categories. Because Hugo Schiff studied the reactions between aldehydes and amines with and without various acids or alcohol, it is only proper to call each of them Schiff reactions that used various types of Schiff reagents.     

A genetic model and molecular markers for wild oat (Avena fatua L.) seed dormancy

Seed dormancy allows weed seeds to persist in agricultural soils. Wild oat (Avena fatua L.) is a major weed of cereal grains and expresses a range of seed dormancy phenotypes. Genetic analysis of wild oat dormancy has been complicated by the difficulty of phenotypic classification in segregating populations. Therefore, little is known about the nature of the genes that regulate dormancy in wild oat. The objectives of our studies were to develop methods to classify the germination responses of segregating wild oat populations and to find molecular markers linked to quantitative trait loci (QTL) that regulate seed dormancy in wild oat. RAPD markers OPX-06 and OPT-04 explained 12.6% and 6.8% respectively, of the F₂ phenotypic variance. OPF-17 was not significant in a simple regression model, but it was linked in repulsion to OPT-04. A three-locus model of seed dormancy in wild oat is presented based on the 41-day germination profiles of F₁, F₂, F₃, BC₁P₁F₁, BC₁P₁F₂, and BC₁P₂F₁ generations, and the 113 day germination profile of 126 F₇ recombinant inbred lines. Loci G ₁ and G ₂ promote early germination, and the D locus promotes late germination. If at least one copy of the dominant G ₁ or G ₂ alleles are present regardless of the genotype at D locus, then the individual will be nondormant. If the genotype is g ₁ g ₁ g ₂ g ₂ D_, then the phenotype will be dormant. Received: 1 December 1998 / Accepted: 1 February 1999     

Multiple testing with discrete data: Proportion of true null hypotheses and two adaptive FDR procedures

We consider multiple testing with false discovery rate (FDR) control when p values have discrete and heterogeneous null distributions. We propose a new estimator of the proportion of true null hypotheses and demonstrate that it is less upwardly biased than Storey's estimator and two other estimators. The new estimator induces two adaptive procedures, that is, an adaptive Benjamini–Hochberg (BH) procedure and an adaptive Benjamini–Hochberg–Heyse (BHH) procedure. We prove that the adaptive BH (aBH) procedure is conservative nonasymptotically. Through simulation studies, we show that these procedures are usually more powerful than their nonadaptive counterparts and that the adaptive BHH procedure is usually more powerful than the aBH procedure and a procedure based on randomized p‐value. The adaptive procedures are applied to a study of HIV vaccine efficacy, where they identify more differentially polymorphic positions than the BH procedure at the same FDR level.