Intake of B vitamins and the risk of developing islet autoimmunity and type 1 diabetes in the TEDDY study

PURPOSE

The aim was to study the association between dietary intake of B vitamins in childhood and the risk of islet autoimmunity (IA) and progression to type 1 diabetes (T1D) by the age of 10 years.

METHODS

We followed 8500 T1D-susceptible children born in the U.S., Finland, Sweden, and Germany in 2004 -2010 from the Environmental Determinants of Diabetes in the Young (TEDDY) study, which is a prospective observational birth cohort. Dietary intake of seven B vitamins was calculated from foods and dietary supplements based on 24-h recall at 3 months and 3-day food records collected regularly from 6 months to 10 years of age. Cox proportional hazard models were adjusted for energy, HLA-genotype, first-degree relative with T1D, sex, and country.

RESULTS

A total of 778 (9.2) children developed at least one autoantibody (any IA), and 335 (3.9%) developed multiple autoantibodies. 280 (3.3%) children had IAA and 319 (3.8%) GADA as the first autoantibody. 344 (44%) children with IA progressed to T1D. We observed that higher intake of niacin was associated with a decreased risk of developing multiple autoantibodies (HR 0.95; 95% CI 0.92, 0.98) per 1 mg/1000 kcal in niacin intake. Higher intake of pyridoxine (HR 0.66; 95% CI 0.46, 0.96) and vitamin B12 (HR 0.87; 95% CI 0.77, 0.97) was associated with a decreased risk of IAA-first autoimmunity. Higher intake of riboflavin (HR 1.38; 95% CI 1.05, 1.80) was associated with an increased risk of GADA-first autoimmunity. There were no associations between any of the B vitamins and the outcomes "any IA" and progression from IA to T1D.  CONCLUSION: In this multinational, prospective birth cohort of children with genetic susceptibility to T1D, we observed some direct and inverse associations between different B vitamins and risk of IA.

Physical Activity and the Development of Islet Autoimmunity and Type 1 Diabetes in 5- to 15-Year-Old Children Followed in the TEDDY Study

OBJECTIVE

This study investigated physical activity and its association with the development of islet autoimmunity and type 1 diabetes in genetically at-risk children aged 5-15 years.

RESEARCH DESIGN AND METHODS

As part of the longitudinal Environmental Determinants of Diabetes in the Young (TEDDY) study, annual assessment of activity using accelerometry was conducted from age 5 years. Time-to-event analyses using Cox proportional hazard models were used to assess the association between time spent in moderate to vigorous physical activity per day and the appearance of one or several autoantibodies and progression to type 1 diabetes in three risk groups: 1) 3,869 islet autoantibody (IA)-negative children, of whom 157 became single IA positive; 2) 302 single IA-positive children, of whom 73 became multiple IA positive; and 3) 294 multiple IA-positive children, of whom 148 developed type 1 diabetes.

RESULTS

No significant association was found in risk group 1 or risk group 2. A significant association was seen in risk group 3 (hazard ratio 0.920 [95% CI 0.856, 0.988] per 10-min increase; P = 0.021), particularly when glutamate decarboxylase autoantibody was the first autoantibody (hazard ratio 0.883 [95% CI 0.783, 0.996] per 10-min increase; P = 0.043).

CONCLUSIONS

More daily minutes spent in moderate to vigorous physical activity was associated with a reduced risk of progression to type 1 diabetes in children aged 5-15 years who had developed multiple IAs.

Dietary Intake and Body Mass Index Influence the Risk of Islet Autoimmunity in Genetically At-Risk Children: A Mediation Analysis Using the TEDDY Cohort

Background/Objective

Growth and obesity have been associated with increased risk of islet autoimmunity (IA) and progression to type 1 diabetes. We aimed to estimate the effect of energy-yielding macronutrient intake on the development of IA through BMI.

Research Design and Methods

Genetically at-risk children (n = 5,084) in Finland, Germany, Sweden, and the USA, who were autoantibody negative at 2 years of age, were followed to the age of 8 years, with anthropometric measurements and 3-day food records collected biannually. Of these, 495 (9.7%) children developed IA. Mediation analysis for time-varying covariates (BMI z-score) and exposure (energy intake) was conducted. Cox proportional hazard method was used in sensitivity analysis.

Results

We found an indirect effect of total energy intake (estimates: indirect effect 0.13 [0.05, 0.21]) and energy from protein (estimates: indirect effect 0.06 [0.02, 0.11]), fat (estimates: indirect effect 0.03 [0.01, 0.05]), and carbohydrates (estimates: indirect effect 0.02 [0.00, 0.04]) (kcal/day) on the development of IA. A direct effect was found for protein, expressed both as kcal/day (estimates: direct effect 1.09 [0.35, 1.56]) and energy percentage (estimates: direct effect 72.8 [3.0, 98.0]) and the development of GAD autoantibodies (GADA). In the sensitivity analysis, energy from protein (kcal/day) was associated with increased risk for GADA, hazard ratio 1.24 (95% CI: 1.09, 1.53), p = 0.042.

Conclusions

This study confirms that higher total energy intake is associated with higher BMI, which leads to higher risk of the development of IA. A diet with larger proportion of energy from protein has a direct effect on the development of GADA.

A novel network based linear model for prioritization of synergistic drug combinations

Drug combination therapies can improve drug efficacy, reduce drug dosage, and overcome drug resistance in cancer treatments. Current research strategies to determine which drug combinations have a synergistic effect rely mainly on clinical or empirical experience and screening predefined pools of drugs. Given the number of possible drug combinations, the speed, and scope to find new drug combinations are very limited using these methods. Due to the exponential growth in the number of drug combinations, it is difficult to test all possible combinations in the lab. There are several large-scale public genomic and phenotypic resources that provide data from single drug-treated cells as well as data from small molecule treated cells. These databases provide a wealth of information regarding cellular responses to drugs and offer an opportunity to overcome the limitations of the current methods. Developing a new advanced data processing and analysis strategy is imperative and a computational prediction algorithm is highly desirable. In this paper, we developed a computational algorithm for the enrichment of synergistic drug combinations using gene regulatory network knowledge and an operational module unit (OMU) system which we generate from single drug genomic and phenotypic data. As a proof of principle, we applied the pipeline to a group of anticancer drugs and demonstrate how the algorithm could help researchers efficiently find possible synergistic drug combinations using single drug data to evaluate all possible drug pairs.

Persistent STAT5 activation reprograms the epigenetic landscape in CD4+ T cells to drive polyfunctionality and antitumor immunity

The presence of polyfunctional CD4+ T cells is often associated with favorable antitumor immunity. We report here that persistent activation of signal transducer and activator of transcription 5 (STAT5) in tumor-specific CD4+ T cells drives the development of polyfunctional T cells. We showed that ectopic expression of a constitutively active form of murine STAT5A (CASTAT5) enabled tumor-specific CD4+ T cells to undergo robust expansion, infiltrate tumors vigorously, and elicit antitumor CD8+ T cell responses in a CD4+ T cell adoptive transfer model system. Integrated epigenomic and transcriptomic analysis revealed that CASTAT5 induced genome-wide chromatin remodeling in CD4+ T cells and established a distinct epigenetic and transcriptional landscape. Single-cell RNA sequencing analysis further identified a subset of CASTAT5-transduced CD4+ T cells with a molecular signature indicative of progenitor polyfunctional T cells. The therapeutic significance of CASTAT5 came from our finding that adoptive transfer of T cells engineered to coexpress CD19-targeting chimeric antigen receptor (CAR) and CASTAT5 gave rise to polyfunctional CD4+ CAR T cells in a mouse B cell lymphoma model. The optimal therapeutic outcome was obtained when both CD4+ and CD8+ CAR T cells were transduced with CASTAT5, indicating that CASTAT5 facilitates productive CD4 help to CD8+ T cells. Furthermore, we provide evidence that CASTAT5 is functional in primary human CD4+ T cells, underscoring its potential clinical relevance. Our results implicate STAT5 as a valid candidate for T cell engineering to generate polyfunctional, exhaustion-resistant, and tumor-tropic antitumor CD4+ T cells to potentiate adoptive T cell therapy for cancer.

The Geropathology Research Network: An Interdisciplinary Approach for Integrating Pathology Into Research on Aging

Geropathology is the study of aging and age-related lesions and diseases in the form of whole necropsies/autopsies, surgical biopsies, histology, and molecular biomarkers. It encompasses multiple subspecialties of geriatrics, anatomic pathology, molecular pathology, clinical pathology, and gerontology. In order to increase the consistency and scope of communication in the histologic and molecular pathology assessment of tissues from preclinical and clinical aging studies, a Geropathology Research Network has been established consisting of pathologists and scientists with expertise in the comparative pathology of aging, the design of aging research studies, biostatistical methods for analysis of aging data, and bioinformatics for compiling and annotating large sets of data generated from aging studies. The network provides an environment to promote learning and exchange of scientific information and ideas for the aging research community through a series of symposia, the development of uniform ways of integrating pathology into aging studies, and the statistical analysis of pathology data. The efforts of the network are ultimately expected to lead to a refined set of sentinel biomarkers of molecular and anatomic pathology that could be incorporated into preclinical and clinical aging intervention studies to increase the relevance and productivity of these types of investigations.

Research resource: dkCOIN, the National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) consortium interconnectivity network: a pilot program to aggregate research resources generated by multiple research consortia

The National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) supports multiple basic science consortia that generate high-content datasets, reagent resources, and methodologies, in the fields of kidney, urology, hematology, digestive, and endocrine diseases, as well as metabolic diseases such as diabetes and obesity. These currently include the Beta Cell Biology Consortium, the Nuclear Receptor Signaling Atlas, the Diabetic Complications Consortium, and the Mouse Metabolic Phenotyping Centers. Recognizing the synergy that would accrue from aggregating information generated and curated by these initiatives in a contiguous informatics network, we created the NIDDK Consortium Interconnectivity Network (dkCOIN; www.dkcoin.org). The goal of this pilot project, organized by the NIDDK, was to establish a single point of access to a toolkit of interconnected resources (datasets, reagents, and protocols) generated from individual consortia that could be readily accessed by biologists of diverse backgrounds and research interests. During the pilot phase of this activity dkCOIN collected nearly 2000 consortium-curated resources, including datasets (functional genomics) and reagents (mouse strains, antibodies, and adenoviral constructs) and built nearly 3000 resource-to-resource connections, thereby demonstrating the feasibility of further extending this database in the future. Thus, dkCOIN promises to be a useful informatics solution for rapidly identifying useful resources generated by participating research consortia.

Gene expression profiling of early-phase Sjögren's syndrome in C57BL/6.NOD-Aec1Aec2 mice identifies focal adhesion maturation associated with infiltrating leukocytes

PURPOSE

Despite considerable efforts, the molecular and cellular events in lacrimal gland tissues initiating inflammatory responses leading to keratoconjunctivitis sicca (KCS), autoimmunity, and Sjögren's syndrome (SjS) have yet to be defined. To determine whether altered glandular homeostasis occurs before the onset of autoimmunity, a temporal transcriptome study was carried out in an animal model of primary SjS.

METHODS

Using oligonucleotide microarrays, gene expression profiles were generated for lacrimal glands of C57BL/6.NOD-Aec1Aec2 mice 4 to 20 weeks of age. Pairwise analyses identified genes differentially expressed, relative to their 4-week expression, during the development of SjS-like disease. Statistical analyses defined differentially and coordinately expressed gene sets. The PANTHER (Protein ANalysis THrough Evolutionary Relationships) classification system was used to define annotated biological processes or functions.

RESULTS

Temporal transcript expression profiles of C57BL/6.NOD-Aec1Aec2 lacrimal glands before, or concomitant with, the first appearance of inflammatory cells revealed a highly restricted subset of differentially expressed genes encoding interactive extracellular matrix proteins, fibronectin, integrins, and syndecans. In contrast, genes encoding interepithelial junctional complex proteins defined alterations in tight junctions (TJ), adherens, desmosomes, and gap junctions, suggesting perturbations in the permeability of the paracellular spaces between epithelial barriers. Correlating with this were gene sets defining focal adhesion (FA) maturation and Ras/Raf-Mek/Erk signal transduction. Immunohistochemically, FAs were associated with infiltrating leukocytes and not with lacrimal epithelial cells.

CONCLUSIONS

For the first time, FA maturations are implicated as initial biomarkers of impending autoimmunity in lacrimal glands of SjS-prone mice. Changes in TJ complex genes support an increased movement of cells through paracellular spaces.

Hepatic gene expression profiling reveals key pathways involved in leptin-mediated weight loss in ob/ob mice

Background

Leptin, a cytokine-like protein, plays an important role in the regulation of body weight through inhibition of food intake and stimulation of energy expenditure. Leptin circulates in blood and acts on the brain, which sends downstream signals to regulate body weight. Leptin therapy has been successful in treating leptin deficient obese patients. However, high levels of leptin have been observed in more common forms of obesity indicating a state of leptin resistance which limits the application of leptin in the treatment of obesity. If the central effect of leptin could be by-passed and genes which respond to leptin treatment could be regulated directly, new therapeutic targets for the treatment of obesity may be possible. The purpose of this study was to identify genes and subsequent pathways correlated with leptin-mediated weight loss.

Methodology/Principal Findings

We utilized microarray technology to compare hepatic gene expression changes after two types of leptin administration: one involving a direct stimulatory effect when administered peripherally (subcutaneous: SQ) and another that is indirect, involving a hypothalamic relay that suppresses food intake when leptin is administered centrally (intracerebroventricular: ICV). We identified 214 genes that correlate with leptin mediated weight loss. Several biological processes such as mitochondrial metabolic pathways, lipid metabolic and catabolic processes, lipid biosynthetic processes, carboxylic acid metabolic processes, iron ion binding and glutathione S-transferases were downregulated after leptin administration. In contrast, genes involved in the immune system inflammatory response and lysosomal activity were found to be upregulated. Among the cellular compartments mitochondrion (32 genes), endoplasmic reticulum (22 genes) and vacuole (8 genes) were significantly over represented.

Conclusions/Significance

In this study we have identified key molecular pathways and downstream genes which respond to leptin treatment and are involved in leptin-mediated weight loss. Many of these genes have previously been shown to be associated with obesity; however, we have also identified a number of other novel target genes. Further investigation will be required to assess the possible use of these genes and their associated protein products as therapeutic targets for the treatment of obesity.

ParaSAM: a parallelized version of the significance analysis of microarrays algorithm

Motivation: Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements.

Summary: We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations.

Availability:A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx

Contact:rmcindoe@mail.mcg.edu

Supplementary information:Supplementary Data is available at Bioinformatics online.

Mouse models of diabetic nephropathy

Diabetic nephropathy is a major cause of ESRD worldwide. Despite its prevalence, a lack of reliable animal models that mimic human disease has delayed the identification of specific factors that cause or predict diabetic nephropathy. The Animal Models of Diabetic Complications Consortium (AMDCC) was created in 2001 by the National Institutes of Health to develop and characterize models of diabetic nephropathy and other complications. This interim report and our online supplement detail the progress made toward that goal, specifically in the development and testing of murine models. Updates are provided on validation criteria for early and advanced diabetic nephropathy, phenotyping methods, the effect of background strain on nephropathy, current best models of diabetic nephropathy, negative models, and views of future directions. AMDCC investigators and other investigators in the field have yet to validate a complete murine model of human diabetic kidney disease. Nonetheless, the critical analysis of existing murine models substantially enhances our understanding of this disease process.

Differential gene expression in the salivary gland during development and onset of xerostomia in Sjögren's syndrome-like disease of the C57BL/6.NOD-Aec1Aec2 mouse

INTRODUCTION

Recently, we reported the development of the C57BL/6.NOD-Aec1Aec2 mouse that carries two genetic intervals derived from the non-obese diabetic (NOD) mouse capable of conferring Sjögren's syndrome (SjS)-like disease in SjS-non-susceptible C57BL/6 mice. In an attempt to define the molecular bases underlying the onset of stomatitis sicca (xerostomia) in this C57BL/6.NOD-Aec1Aec2 mouse model, we have carried out a study using genomic microarray technology.

METHODS

By means of oligonucleotide microarrays, gene expression profiles of salivary glands at 4, 8, 12, 16, and 20 weeks of age were generated for C57BL/6.NOD-Aec1Aec2 male mice. Using Linear Models for Microarray Analysis and B-statistics software, 480 genes were identified as being differentially expressed (P < 0.01 and Q < 0.0001) during the development of SjS-like disease in the salivary glands.

RESULTS

The 480 genes could be arranged into four clusters, with each cluster defining a unique pattern of temporal expression, while the individual genes within each cluster could be grouped according to related biological functions. By means of pair-wise analysis, temporal changes in transcript expressions provided profiles indicating that many additional genes are differentially expressed at specific time points during the development of disease. Multiple genes reportedly showing an association with autoimmunity and/or SjS, in either humans or mouse models, were found to exhibit differential expressions, both quantitatively and temporally. Selecting various families of genes associated with specific functions (for example, antibody production, complement, and chemokines), we noted that only a limited number of family members showed differential expressions and these correlated with specific phases of disease.

CONCLUSIONS

Taking advantage of known functions of these genes, investigators can construct interactive gene pathways, leading to modeling of possible underlying events inducing salivary gland dysfunction. Thus, these different approaches to analyzing microarray data permit the identification of multiple sets of genes of interest whose expressions and expression profiles may correlate with molecular mechanisms, signaling pathways, and/or immunological processes involved in the development and onset of SjS.

A modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets

Motivation: As the number of publically available microarray experiments increases, the ability to analyze extremely large datasets across multiple experiments becomes critical. There is a requirement to develop algorithms which are fast and can cluster extremely large datasets without affecting the cluster quality. Clustering is an unsupervised exploratory technique applied to microarray data to find similar data structures or expression patterns. Because of the high input/output costs involved and large distance matrices calculated, most of the algomerative clustering algorithms fail on large datasets (30 000 + genes/200 + arrays). In this article, we propose a new two-stage algorithm which partitions the high-dimensional space associated with microarray data using hyperplanes. The first stage is based on the Balanced Iterative Reducing and Clustering using Hierarchies algorithm with the second stage being a conventional k-means clustering technique. This algorithm has been implemented in a software tool (HPCluster) designed to cluster gene expression data. We compared the clustering results using the two-stage hyperplane algorithm with the conventional k-means algorithm from other available programs. Because, the first stage traverses the data in a single scan, the performance and speed increases substantially. The data reduction accomplished in the first stage of the algorithm reduces the memory requirements allowing us to cluster 44 460 genes without failure and significantly decreases the time to complete when compared with popular k-means programs. The software was written in C# (.NET 1.1).

Availability: The program is freely available and can be downloaded from http://www.amdcc.org/bioinformatics/bioinformatics.aspx.

Contact:rmcindoe@mail.mcg.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Differential gene expressions in the lacrimal gland during development and onset of keratoconjunctivitis sicca in Sjögren's syndrome (SJS)-like disease of the C57BL/6.NOD-Aec1Aec2 mouse

Recently, we reported development of the C57BL/6.NOD-Aec1Aec2 mouse carrying two genetic intervals derived from the NOD mouse. These two genetic regions confer Sjögren's syndrome (SjS)-like disease in SjS-non-susceptible C57BL/6 mice. In an attempt to define the molecular bases underlying onset of dacryoadenitis and subsequently keratoconjunctivitis sicca (or xerophthalmia) in the C57BL/6.NOD-Aec1Aec2 mouse model, we have carried out a study utilizing microarray technology. Using oligonucleotide microarrays, gene expression profiles of lacrimal glands at 4, 8, 12, 16 and 20weeks of age were generated for C57BL/6.NOD-Aec1Aec2 male mice. Analyses using Linear Models for Microarray Analysis package and B-statistics, 552 genes were identified as being differentially expressed (adjusted p-value <0.01 and B <1.5) during the development of SjS-like disease. These 552 genes could be arranged into four clusters, with each cluster defining a unique pattern of temporal expression, while the individual genes within each cluster could be grouped according to related function. Using a pair-wise analysis, temporal changes in gene expressions provided profiles indicating that individual genes were differentially expressed at specific time points during development of SjS. In addition, multiple genes that have been reported to show, either in humans or mouse models, an association with autoimmunity and/or SjS, e.g., ApoE, Baff, Clu, Ctla4, Fas/Fasl, Irf5, Lyzs, Nfkb, Socs3, Stat4, Tap2, Tgfbeta1, Tnfa, and Vcam1 were also found to exhibit differential expressions, both quantitatively and temporally. Selecting a few families of genes, e.g., cystatins, cathepsins, metalloproteinases, lipocalins, complement, kallikreins, carbonic anhydrases and tumor necrosis factors, it was noted that only a limited number of family members showed differential expressions, suggesting a restricted glandular expression. Utilizing these genes, pathways of inter-reactive genes have been constructed for apoptosis and fatty acid homeostasis, leading to modeling of possible underlying events inducing disease. Thus, these different approaches to analyze microarray data permit identification of multiple sets of genes of interest whose expressions and expression profiles may correlate with molecular mechanisms, signaling pathways and/or immunological processes involved in the development and onset of SjS in this mouse model, thereby providing new insight into the underlying cause or regulation of this disease.

The IL-10 and IFN-gamma pathways are essential to the potent immunosuppressive activity of cultured CD8+ NKT-like cells

Global gene expression profiling of in vitro cultured CD8⁺ T cells that express natural killer cell markers revealed differential expression of about 3,000 genes between these cells and naïve CD8⁺ T cells.

Background

CD8⁺ NKT-like cells are naturally occurring but rare T cells that express both T cell and natural killer cell markers. These cells may play key roles in establishing tolerance to self-antigens; however, their mechanism of action and molecular profiles are poorly characterized due to their low frequencies. We developed an efficient in vitro protocol to produce CD8⁺ T cells that express natural killer cell markers (CD8⁺ NKT-like cells) and extensively characterized their functional and molecular phenotypes using a variety of techniques.

Results

Large numbers of CD8⁺ NKT-like cells were obtained through culture of naïve CD8⁺ T cells using anti-CD3/anti-CD28-coated beads and high dose IL-2. These cells possess potent activity in suppressing the proliferation of naïve responder T cells. Gene expression profiling suggests that the cultured CD8⁺ NKT-like cells and the naïve CD8⁺ T cells differ by more than 2-fold for about 3,000 genes, among which 314 are upregulated by more than 5-fold and 113 are upregulated by more than 10-fold in the CD8⁺ NKT-like cells. A large proportion of the highly upregulated genes are soluble factors or surface markers that have previously been implicated in immune suppression or are likely to possess immunosuppressive properties. Many of these genes are regulated by two key cytokines, IL-10 and IFN-γ. The immunosuppressive activities of cells cultured from IL-10^-/- and IFN-γ^-/- mice are reduced by about 70% and about 50%, respectively, compared to wild-type mice.

Conclusion

Immunosuppressive CD8⁺ NKT-like cells can be efficiently produced and their immunosuppressive activity is related to many surface and soluble molecules regulated by IL-10 and IFN-γ.

ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use

Background

During the last decade, the use of microarrays to assess the transcriptome of many biological systems has generated an enormous amount of data. A common technique used to organize and analyze microarray data is to perform cluster analysis. While many clustering algorithms have been developed, they all suffer a significant decrease in computational performance as the size of the dataset being analyzed becomes very large. For example, clustering 10000 genes from an experiment containing 200 microarrays can be quite time consuming and challenging on a desktop PC. One solution to the scalability problem of clustering algorithms is to distribute or parallelize the algorithm across multiple computers.

Results

The software described in this paper is a high performance multithreaded application that implements a parallelized version of the K-means Clustering algorithm. Most parallel processing applications are not accessible to the general public and require specialized software libraries (e.g. MPI) and specialized hardware configurations. The parallel nature of the application comes from the use of a web service to perform the distance calculations and cluster assignments. Here we show our parallel implementation provides significant performance gains over a wide range of datasets using as little as seven nodes. The software was written in C# and was designed in a modular fashion to provide both deployment flexibility as well as flexibility in the user interface.

Conclusion

ParaKMeans was designed to provide the general scientific community with an easy and manageable client-server application that can be installed on a wide variety of Windows operating systems.

Early pathogenic events associated with Sjögren's syndrome (SjS)-like disease of the NOD mouse using microarray analysis

Recently, we reported development of the C57BL/6.NOD-Aec1Aec2 mouse carrying two genetic intervals derived from the NOD mouse. These two genetic regions confer full Sjögren's syndrome (SjS)-like disease in SjS-non-susceptible C57BL/6 mice. The current study was undertaken to apply microarray technology to define the molecular basis underlying onset of SjS-disease in C57BL/6.NOD-Aec1Aec2 mice. Using oligonucleotide microarrays, gene expression profiles of submandibular glands derived from 8- to 12-week-old C57BL/6.NOD-Aec1Aec2 mice and 8-week-old C57BL/6 mice were performed for comparison. Significant differential expressions were determined using the Mann-Whitney U test. Hybridizations using submandibular cDNA probes revealed 75 differentially expressed genes at 8 weeks and 105 differentially expressed genes at 12 weeks of age in C57BL/6.NOD-Aec1Aec2 mice compared to 8-week-old C57BL/6 mice. These genes were related generally to basic cellular activities such as transcription, translation, DNA replication, and protein folding. During the predisease phase, genes upregulated encode proteins associated with the IFN-gamma signal-transduction-pathway (Jak/Stat1), TLR-3 (Irf3 and Traf6) and apoptosis (casp11 and casp3), indicative of chronic proinflammatory stimuli, especially IL-1. Between 8 and 12 weeks of age, sets of clustered genes were upregulated that are associated with adaptive immune responses, especially B cell activation, proliferation and differentiation (Baffr, Taci, Bcma, Blys, April, CD70, CD40L, Traf1, Traf3, Pax5, c-Jun, Elk1 and Nf-kB), and neural receptors (Taj/Troy). Altered gene expressions of TLR3 and TNF-superfamily-receptors and ligands during this early phase of SjS suggest a possible viral etiology in the altered glandular homeostasis with an upregulated, possibly overstimulated, B-lymphocyte activation in the early autoimmune response present in the submandibular glands. The importance of NF-kappaB as a critical signal transduction pathway is also suggested but its link is not yet clear.

The application of genomic and proteomic technologies in predictive, preventive and personalized medicine

The long asymptomatic period before the onset of chronic diseases offers good opportunities for disease prevention. Indeed, many chronic diseases may be preventable by avoiding those factors that trigger the disease process (primary prevention) or by use of therapy that modulates the disease process before the onset of clinical symptoms (secondary prevention). Accurate prediction is vital for disease prevention so that therapy can be given to those individuals who are most likely to develop the disease. The utility of predictive markers is dependent on three parameters, which must be carefully assessed: sensitivity, specificity and positive predictive value. Specificity is important if a biomarker is to be used to identify individuals either for counseling or for preventive therapy. However, a reciprocal relationship exists between sensitivity and specificity. Thus, successful biomarkers will be highly specific without sacrificing sensitivity. Unfortunately, biomarkers with ideal specificity and sensitivity are difficult to find for many diseases. One potential solution is to use the combinatorial power of a large number of biomarkers, each of which alone may not offer satisfactory specificity and sensitivity. Recent technological advances in genetics, genomics, proteomics, and bioinformatics offer a great opportunity for biomarker discovery. The newly identified biomarkers have the potential to bring increased accuracy in disease diagnosis and classification, as well as therapeutic monitoring. In this review, we will use type 1 diabetes (T1D) as an example, when appropriate, to discuss pertinent issues related to high throughput biomarker discovery.

Alterations of renal phenotype and gene expression profiles due to protein overload in NOD-related mouse strains

BACKGROUND

Despite multiple causes, Chronic Kidney Disease is commonly associated with proteinuria. A previous study on Non Obese Diabetic mice (NOD), which spontaneously develop type 1 diabetes, described histological and gene expression changes incurred by diabetes in the kidney. Because proteinuria is coincident to diabetes, the effects of proteinuria are difficult to distinguish from those of other factors such as hyperglycemia. Proteinuria can nevertheless be induced in mice by peritoneal injection of Bovine Serum Albumin (BSA). To gain more information on the specific effects of proteinuria, this study addresses renal changes in diabetes resistant NOD-related mouse strains (NON and NOD.B10) that were made to develop proteinuria by BSA overload.

METHODS

Proteinuria was induced by protein overload on NON and NOD.B10 mouse strains and histology and microarray technology were used to follow the kidney response. The effects of proteinuria were assessed and subsequently compared to changes that were observed in a prior study on NOD diabetic nephropathy.

RESULTS

Overload treatment significantly modified the renal phenotype and out of 5760 clones screened, 21 and 7 kidney transcripts were respectively altered in the NON and NOD.B10. Upregulated transcripts encoded signal transduction genes, as well as markers for inflammation (Calmodulin kinase beta). Down-regulated transcripts included FKBP52 which was also down-regulated in diabetic NOD kidney. Comparison of transcripts altered by proteinuria to those altered by diabetes identified mannosidase 2 alpha 1 as being more specifically induced by proteinuria.

CONCLUSION

By simulating a component of diabetes, and looking at the global response on mice resistant to the disease, by virtue of a small genetic difference, we were able to identify key factors in disease progression. This suggests the power of this approach in unraveling multifactorial disease processes.

caBIONet--A .NET wrapper to access and process genomic data stored at the National Cancer Institute's Center for Bioinformatics databases

MOTIVATION

The National Cancer Institute's Center for Bioinformatics (NCICB) has developed a Java based data management and information system called caCORE. One component of this software suite is the object oriented API (caBIO) used to access the rich biological datasets collected at the NCI. This API can access the data using native Java classes, SOAP requests or HTTP calls. Non-Java based clients wanting to use this API have to use the SOAP or HTTP interfaces with the data being returned from the NCI servers as an XML data stream. Although the XML can be read and manipulated using DOM or SAX parsers, one loses the convenience and usability of an object oriented programming paradigm. caBIONet is a set of .NET wrapper classes (managers, genes, chromosomes, sequences, etc.) capable of serializing the XML data stream into local .NET objects. The software is able to search NCICB databases and provide local objects representing the data that can be manipulated and used by other .NET programs. The software was written in C# and compiled as a .NET DLL.

Molecular pathways altered by insulin b9-23 immunization

Type 1 diabetes (T1D) in the nonobese diabetic (NOD) mouse can be delayed by administration of insulin or specific insulin peptides. To better understand how insulin treatment delays diabetes development, NOD mice treated with an insulin peptide (B9-23) were compared with age-matched NOD and NOD congenic mice for gene expression changes in spleen using cDNA microarray. Fifty genes were identified that were significantly altered by B9-23 treatment. Thirty-three of these genes are downregulated by the treatment while they are upregulated during the natural disease progression in NOD from immature (3-4 weeks) to mature (10 weeks) stages. Taken together, our data suggest that the B9-23 treatment, like the protective genes in NOD congenic strains, reduces pro-inflammatory activation of lymphocytes that normally occurs in NOD mice. Furthermore, our studies discovered two genes (Irf4 and Tra1) with increased expression in B9-23-treated mice that promote the Th2 response, providing a molecular basis for the B9-23-protective therapy.

Gene expression profiling during all-trans retinoic acid-induced cell differentiation of acute promyelocytic leukemia cells

Using cDNA microarrays we determined the gene expression patterns in the human acute promyelocytic leukemia (APL) cell line NB4 during all-trans retinoic acid (ATRA)-induced differentiation. We analyzed the expression of 12,288 genes in the NB4 cells after 12 hours, 24 hours, 48 hours, 72 hours, and 96 hours of ATRA exposure. During this time course, we found 168 up-regulated and more than 179 down-regulated genes, most of which have not been reported before. Many of the altered genes encode products that participate in signaling pathways, cell differentiation, programmed cell death, transcription regulation, and production of cytokines and chemokines. Of interest, the CD52 and protein kinase A regulatory subunit alpha (PKA-Rlalpha) genes, whose products are being used as therapeutic targets for certain human neoplasias in currently ongoing clinical trials, were among the genes observed to be markedly up-regulated after ATRA treatment. The present study provides valuable data to further understand the mechanism of ATRA-induced APL cell differentiation and suggests potential therapeutic alternatives for this leukemia.

Gene expression profiles define a key checkpoint for type 1 diabetes in NOD mice

cDNA microarrays with >11,000 cDNA clones from an NOD spleen cDNA library were used to identify temporal gene expression changes in NOD mice (1-10 weeks), which spontaneously develop type 1 diabetes, and changes between NOD and NOD congenic mice (NOD.Idd3/Idd10 and NOD.B10Sn-H2(b)), which have near zero incidence of insulitis and diabetes. The expression profiles identified two distinct groups of mice corresponding to an immature (1-4 weeks) and mature (6-10 weeks) state. The rapid switch of gene expression occurring around 5 weeks of age defines a key immunological checkpoint. Sixty-two known genes are upregulated, and 18 are downregulated at this checkpoint in the NOD. The expression profiles are consistent with increased antibody production, antigen presentation, and cell proliferation associated with an active autoimmune response. Seven of these genes map to confirmed diabetes susceptibility regions. Of these seven, three are excellent candidate genes not previously implicated in type 1 diabetes. Ten genes are differentially expressed between the NOD and congenic NOD at the immature stage (Hspa8, Hif1a, and several involved in cellular functions), while the other 70 genes exhibit expression differences during the mature (6-10 week) stage, suggesting that the expression differences of a small number of genes before onset of insulitis determine the disease progression.

Microarray experimental design: power and sample size considerations

Gene expression analysis using high-throughput microarray technology has become a powerful approach to study systems biology. The exponential growth in microarray experiments has spawned a number of investigations into the reliability and reproducibility of this type of data. However, the sample size requirements necessary to obtain statistically significant results has not had as much attention. We report here statistical methods for the determination of the sufficient number of subjects necessary to minimize the false discovery rate while maintaining high power to detect differentially expressed genes. Two experimental designs were considered: 1) a comparison between two groups at a single time point, and 2) a comparison of two experimental groups with sequential time points. Computer programs are available for the methods discussed in this paper and are adaptable to more complicated situations.

Microarray analysis of gene expression in the kidneys of new- and post-onset diabetic NOD mice

We profiled the expression of 5,760 clones from a kidney subtraction library in the kidneys of three groups of NOD mice: nondiabetic, new-onset, and long-term diabetic. A total of 27 genes had lower expression and 1 gene (Gpx3) had higher expression in the new-onset diabetic mice compared with nondiabetic control NOD mice (P < 0.001). Similarly, 19 of the above 27 genes and 7 additional genes had higher expression and the Gpx3 gene had lower expression in long-term diabetic mice compared with controls (P < 0.001). Interestingly, only three genes may be different between new-onset and long-term diabetic mice (P < 0.0004). These genes are from diverse functional groups, including oxidative phosphorylation, free radical neutralization, channels, pumps, lipid processing, transcription and translation machinery, protein trafficking, constitutive protein processing, and immune function. The majority of these genes fall into four signaling pathways: insulin, transforming growth factor-beta, tumor necrosis factor-alpha, and peroxisome proliferator-activated receptor. The most significant expression change was found for the stearoyl-coenzyme A desaturase 1 (SCD1) gene (P < 10(-7)). The lower expression levels of the SCD1 gene in both diabetic groups compared with controls were further confirmed by Northern blot analysis and immunohistochemistry.

Gene expression associated with interferon alfa antiviral activity in an HCV replicon cell line

Interferon alfa (IFN-alpha)-based treatment is the only therapeutic option for chronic hepatitis C viral infection. However, the molecular mechanisms of IFN-alpha antiviral activity are not completely understood. The recent development of an HCV replicon cell culture system provides a feasible experimental model to investigate the molecular details of IFN-induced direct antiviral activity in hepatocytes. In this report, we show that IFN-alpha can effectively inhibit HCV subgenomic RNA replication and suppress viral nonstructural protein synthesis. Using cDNA microarray analysis, we also show that the replicon cells have different gene expression profile compared with the parental hepatoma cells (Huh7). IFN-alpha can induce a number of responsive genes in the replicon cells. One of the genes, 6-16 (G1P3), can enhance IFN-alpha antiviral efficacy. In addition, we demonstrate that IFN-alpha can significantly activate STAT3 in hepatoma cells, suggesting that this pathway plays a role in IFN-alpha signaling. In conclusion, our results indicate that IFN-alpha antiviral activity is associated with activation of STAT3-signaling pathway and intracellular gene activation. Our results also suggest that IFN-alpha-induced target genes may play an important role in IFN-alpha anti-HCV activity.

MADGE: scalable distributed data management software for cDNA microarrays

MOTIVATION

The human genome project and the development of new high-throughput technologies have created unparalleled opportunities to study the mechanism of diseases, monitor the disease progression and evaluate effective therapies. Gene expression profiling is a critical tool to accomplish these goals. The use of nucleic acid microarrays to assess the gene expression of thousands of genes simultaneously has seen phenomenal growth over the past five years. Although commercial sources of microarrays exist, investigators wanting more flexibility in the genes represented on the array will turn to in-house production. The creation and use of cDNA microarrays is a complicated process that generates an enormous amount of information. Effective data management of this information is essential to efficiently access, analyze, troubleshoot and evaluate the microarray experiments.

RESULTS

We have developed a distributable software package designed to track and store the various pieces of data generated by a cDNA microarray facility. This includes the clone collection storage data, annotation data, workflow queues, microarray data, data repositories, sample submission information, and project/investigator information. This application was designed using a 3-tier client server model. The data access layer (1st tier) contains the relational database system tuned to support a large number of transactions. The data services layer (2nd tier) is a distributed COM server with full database transaction support. The application layer (3rd tier) is an internet based user interface that contains both client and server side code for dynamic interactions with the user.

AVAILABILITY

This software is freely available to academic institutions and non-profit organizations at http://www.genomics.mcg.edu/niddkbtc.

Rapid decrease of RNA level of a novel mouse mitochondria solute carrier protein (Mscp) gene at 4-5 weeks of age

We cloned a novel mouse gene that encodes a protein with homology to the mitochondria solute carrier proteins (Mscp). The major full-length Mscp transcript contains 4112 bp of cDNA and a deduced protein of 338 amino acids. The Mscp protein shares 50%, 40%, and 39% sequence identity with the C. elegans hypothetical protein T26089 and the yeast mitochondria carrier proteins MRS3 and MRS4, respectively. It also showed homology with the uncoupling proteins (UCP1, UCP2, and UCP3; 22%, 24%, and 29% identity, respectively). The protein has six transmembrane domains and three mitochondria energy-transfer protein signature motifs, which are conserved among all the members of mitochondria carrier protein family. Northern analysis indicated that the Mscp gene is highly expressed in the spleen. Using cDNA microarray and Northern analysis, we have shown a significant decrease of the splenic Mscp mRNA levels around 4-5 weeks of age in several mouse strains including C57BL/6J, nonobese diabetic (NOD), and several NOD-congenic mice. These results suggest that the Mscp gene is decreased during splenic lymphocyte maturation in these mice.

A statistical method for flagging weak spots improves normalization and ratio estimates in microarrays

Over the last few years, there has been a dramatic increase in the use of cDNA microarrays to monitor gene expression changes in biological systems. Data from these experiments are usually transformed into expression ratios between experimental samples and a common reference sample for subsequent data analysis. The accuracy of this critical transformation depends on two major parameters: the signal intensities and the normalization of the experiment vs. reference signal intensities. Here we describe and validate a new model for microarray signal intensity that has one multiplicative variation and one additive background variation. Using replicative experiments and simulated data, we found that the signal intensity is the most critical parameter that influences the performance of normalization, accuracy of ratio estimates, reproducibility, specificity, and sensitivity of microarray experiments. Therefore, we developed a statistical procedure to flag spots with weak signal intensity based on the standard deviation (delta(ij)) of background differences between a spot and the neighboring spots, i.e., a spot is considered as too weak if the signal is weaker than cdelta(ij). Our studies suggest that normalization and ratio estimates were unacceptable when this threshold (c) is small. We further showed that when a reasonable compromise of c (c = 6) is applied, normalization using trimmed mean of log ratios performed slightly better than global intensity and mean of ratios. These studies suggest that decreasing the background noise is critical to improve the quality of microarray experiments.

Linkage analysis of 150 high-risk prostate cancer families at 1q24-25

Confirmation of linkage and estimation of the proportion of families who are linked in large independent datasets is essential to understanding the significance of cancer susceptibility genes. We report here on an analysis of 150 high-risk prostate cancer families (2,176 individuals) for potential linkage to the HPC1 prostate cancer susceptibility locus at 1q24-25. This dataset includes 640 affected men with an average age at prostate cancer diagnosis of 66. 8 years (range, 39-94), representing the largest collection of high-risk families analyzed for linkage in this region to date. Linkage to multiple 1q24-25 markers was strongly rejected for the sample as a whole (lod scores at theta = 0 ranged from -30.83 to -18. 42). Assuming heterogeneity, the estimated proportion of families linked (alpha) at HPC1 in the entire dataset was 2.6%, using multipoint analysis. Because locus heterogeneity may lead to false rejection of linkage, data were stratified based on homogeneous subsets. When restricted to 21 Caucasian families with five or more affected family members and mean age at diagnosis < = 65 years, the lod scores at theta = 0 remained less than -4.0. These results indicate that the overall portion of hereditary prostate cancer families whose disease is due to inherited variation in HPC1 may be less than originally estimated.

WECHE: a novel hematopoietic regulatory factor

Previously, we described AGM-derived endothelial cell lines that either inhibited or permitted the development of erythroid or B cells. We utilized a differential gene expression method to isolate a chemokine, termed WECHE, from one of these cell lines. WECHE inhibited the formation of erythroid cells but had no effect on either myeloid or B cell formation. WECHE repressed BFU-E development from either mouse fetal liver or bone marrow progenitor cells but had no effect on colony formation induced by IL-3 or IL-7. WECHE reduced HPP-CFC production from fetal liver-derived stem cells. WECHE hindered the growth of yolk sac-derived endothelial cells. WECHE was also chemotactic for bone marrow cells. Thus, WECHE is a novel chemokine that regulates hematopoietic differentiation.

Localization of non-Mhc collagen-induced arthritis susceptibility loci in DBA/1j mice

One approach to understanding common human diseases is to determine the genetic defects responsible for similar diseases in animal models and place those defective genes in their corresponding biochemical pathways. Our laboratory is working with an animal model for human rheumatoid arthritis called collagen-induced arthritis (CIA). We are particularly interested in determining the location of disease-predisposing loci. To that end, we performed experiments to localize susceptibility loci for CIA in an F2 cross between the highly susceptible mouse strain DBA/1j and the highly resistant mouse strain SWR/j. Specifically, a quantitative trait locus analysis was performed to localize regions of the mouse genome responsible for susceptibility/severity to CIA. One susceptibility locus, Cia1 in the major histocompatibility locus, had been identified previously. Two additional loci were detected in our analysis that contribute to CIA severity (Cia2, Cia3) on chromosomes 2 and 6. A third locus was detected that contributes to the age of onset of the disease. This locus (Cia4) was located on chromosome 2 and was linked to the same region as Cia2. Determining the identity of these loci may provide insights into the etiology of human rheumatoid arthritis.

Evidence for a rare prostate cancer-susceptibility locus at chromosome 1p36

Combining data from a genomic screen in 70 families with a high risk for prostate cancer (PC) with data from candidate-region mapping in these families and an additional 71 families, we have localized a potential hereditary PC-susceptibility locus to chromosome 1p36. Because an excess of cases of primary brain cancer (BC) have been observed in some studies of families with a high risk for PC, and because loss of heterozygosity at 1p36 is frequently observed in BC, we further evaluated 12 families with both a history of PC and a blood relative with primary BC. The overall LOD score in these 12 families was 3.22 at a recombination fraction (theta) of .06, with marker D1S507. On the basis of an a priori hypothesis, this group was stratified by age at diagnosis of PC. In the younger age group (mean age at diagnosis <66 years), a maximum two-point LOD score of 3.65 at straight theta = .0 was observed, with D1S407. This linkage was rejected in both early- and late-onset families without a history of BC (LOD scores -7.12 and -6.03, respectively, at straight theta = .0). After exclusion of 3 of the 12 families that had better evidence of linkage to previously described PC-susceptibility loci, linkage to the 1p36 region was suggested by a two-point LOD score of 4.74 at straight theta = .0, with marker D1S407. We conclude that a significant proportion of these families with both a high risk for PC and a family member with BC show linkage to the 1p36 region.

Linkage analysis of 49 high-risk families does not support a common familial prostate cancer-susceptibility gene at 1q24-25

Linkage of a putative prostate cancer-susceptibility locus (HPC1) to chromosome 1q24-25 has recently been reported. Confirmation of this linkage in independent data sets is essential because of the complex nature of this disease. Here we report the results of a linkage analysis using 10 polymorphic markers spanning approximately 37 cM in the region of the putative HPC1 locus in 49 high-risk prostate cancer families. Data were analyzed by use of two parametric models and a nonparametric method. For the parametric LOD-score method, the first model was identical to the original report by Smith and coworkers ("Hopkins"), and the second was based on a segregation analysis previously reported by Carter and coworkers ("Seattle"). In both cases, our results do not confirm the linkage reported for this region. Calculated LOD scores from the two-point analysis for each marker were highly negative at small recombination fractions. Multipoint LOD scores for this linkage group were also highly negative. Additionally, we were unable to demonstrate heterogeneity within the data set, using HOMOG. Although these data do not formally exclude linkage of a prostate cancer-susceptibility locus at HPC1, it is likely that other prostate cancer-susceptibility loci play a more critical role in the families that we studied.

Data-adaptive algorithms for calling alleles in repeat polymorphisms

Data-adaptive algorithms are presented for separating overlapping signatures of heterozygotic allele pairs in electrophoresis data. Application is demonstrated for human microsatellite CA-repeat polymorphisms in LiCor 4000 and ABI 373 data. The algorithms allow overlapping alleles to be called correctly in almost every case where a trained observer could do so, and provide a fast automated objective alternative to human reading of the gels. The algorithm also supplies an indication of confidence level which can be used to flag marginal cases for verification by eye, or as input to later stages of statistical analysis.

An analysis of the dynamic range and linearity of an infrared DNA sequencer

We are currently developing genotyping software and protocols for use on the Li-Cor model 4000(L) infrared fluorescence DNA sequencers. During the development of the genotyping software it became apparent that the potential dynamic range of the instrument was not being realized when the data collection parameters were optimized to produce a high-contrast image on the computer screen. In particular, we were unable to obtain peaks with signal to noise (S/N) greater than about 30:1 and the stronger peaks often saturated the detector. Because the numerical dynamic range available in 16-bit data collection mode exceeds 65000, our limited dynamic range of about 30 in actual data was somewhat puzzling. Hence, we undertook a study to explore the dynamic range and linearity of the Li-Cor DNA sequencer in order to minimize background fluorescence and noise as well as maximize the available S/N. Data is presented on the background and noise using different polyacrylamide gel mixes with various signal gain and offset values, and the relative contribution of the glass, gel and instrumentation to the background fluorescence is discussed. Based on these results, optimum gain and offset values were determined that maintain the background fluorescence at approximately 1-2% of the maximum dynamic range with a minimum amount of noise. Using these optimized values, we determined the detection system is linear over three orders of magnitude by titrating known quantities of an infrared fluorophore-labeled primer. In addition, we were able to detect approximately 15.2 amoles of labeled primer. The results provided by this study establish a set of guidelines for evaluating how to set the signal gain and offset in order to minimize the background and maximize the S/N and dynamic range of the Li-Cor sequencer.

The relation of blood sodium concentration to blood pressure in the rat

Rises or falls in blood sodium concentration ([Na]) within a physiological range of +/- 15 mmol/l, sustained for 5 h, were produced in the rat by intraperitoneal dialysis with physiological salt solutions containing variable amounts of Na. In general, systolic and diastolic blood pressure rose and fell in direct relation to the alteration in [Na]. Solutions of equivalent osmolarity produced changes in blood pressure that were the inverse of those induced by Na. These effects could not be explained in terms of changes in blood or extracellular fluid volume, and indicated the need for an exploration of the partition of Na and water across the vascular smooth muscle cell.

The origin of MHC class II gene polymorphism within the genus Mus

The I region of the major histocompatibility complex (MHC) of the mouse (H-2) contains a tightly-linked cluster of highly polymorphic genes (class II MHC genes) which control immune responsiveness. Speculation on the origin of this polymorphism, which is believed to be essential for the function of the class II proteins in immune responses to disease, has given rise to two hypotheses. The first is that hypermutational mechanisms (gene conversion or segmental exchange) promote the rapid generation of diversity in MHC genes. The alternative is that polymorphism has arisen from the steady accumulation of mutations over long evolutionary periods, and multiple specific alleles have survived speciation (trans-species evolution). We have looked for evidence of 'segmental exchange' and/or 'trans-species evolution' in the class II genes of the genus Mus by molecular genetic analysis of I-A beta alleles. The results indicate that greater than 90% (28 out of 31) of the alleles examined can be organized into two evolutionary groups both on the basis of restriction site polymorphisms and by the presence or absence of a short interspersed nucleotide element (SINE). Using this SINE sequence as an evolutionary tag, we demonstrate that I-A beta alleles in these two evolutionary groups diverged at least three million years ago and have survived the speciation events leading to several modern Mus species. Nucleotide sequence comparisons of eight Mus m. domesticus I-A beta alleles representing all three evolutionary groups indicate that most of the divergence in exon sequences is due to the steady accumulation of mutations that are maintained independently in the different alleles. But segmental exchanges between alleles from different evolutionary groups have also played a role in the diversification of beta 1 exons.

The relation of cellular sodium to the onset of hypertension induced by DOCA-saline in the rat

Groups of 15 rats were injected subcutaneously with a microcrystalline suspension of DOCA and given 1% saline as drinking water for periods ranging from 2 to 16 days. The in vivo transmembrane distribution of Na and K in relation to blood pressure was assessed in terms of plasma [Na] and [K] measured with ion-specific electrodes; smooth muscle cell Na, K and water were measured in the rapidly excised tail artery. A small increase in blood pressure was observed in week 1 of treatment and was followed by an abrupt increase to higher levels at about day 10. Plasma [Na] was elevated and [K] lowered throughout in a new steady state with a reciprocal change of about 1 mmol/l. There were minor changes in intracellular [K] in rapidly excised fresh tail artery samples so that the transmembrane K gradient (EK) was at all times increased by greater than 10 mV, indicating enhanced Na-K transport. In general, intracellular [Na] was directly and Na gradient inversely related to blood pressure (P less than 0.01).

Prehypertensive changes in sodium transport induced by deoxycorticosterone acetate in incubated rat tail artery

The transport and distribution of sodium, potassium, and water were examined in tail arteries of rats treated with deoxycorticosterone acetate (DOCA)-saline for 10 days, a time that marks the earliest onset of a rise of blood pressure in the strain (Wistar) used. The arteries were incubated for more than 20 hours to ensure that any change observed was sufficiently built in so that it could not readily be washed out. Three distinct changes were observed. First, the steady state transmembrane sodium gradient (operationally [Na]o/[Na]i) was increased. Second, the amount of sodium excluded from participation in the sodium gradient, and hence probably bound, was increased. Third, after prolonged potassium depletion, the ouabain-insensitive loss of cell water and sodium that follows the readmittance of potassium was increased. These results suggest that fundamental embedded changes in sodium transport occur well before the blood pressure rises in response to DOCA-saline.

Na transport and blood pressure in the adrenalectomized rat

The transmembrane distribution of Na, K, and water in freshly excised rat tail artery was measured 7 days after adrenalectomy, 3 days after withdrawal of support with 1% NaCl as drinking water. Cell Na decreased from 35.8 +/- 0.9 to 31.6 +/- 0.7 mmol/kg dry wt, tissue water increased from 2.93 +/- 0.03 to 3.08 +/- 0.04 l/kg dry wt, and tissue K remained unchanged. As concentration, [Na]i decreased from 22.5 +/- 0.9 to 18.3 +/- 1.0 mM in parallel with [Na]o which fell from 140.6 +/- 0.3 to 133.6 +/- 1.0. Conversely, while [K]i fell from 140 +/- 2 to 128 +/- 3, [K]o rose from 2.15 +/- 0.12 to 5.40 +/- 0.33 so that EK dropped from -109 to -83 mV. Aldosterone (120 micrograms X 100 g-1 X 24 h-1 sc; 3 X 10(-7) M if immediately distributed in the extracellular fluid) partially restored blood pressure, plasma [Na] and [K], and tissue water within 24-26 h but did not increase cell Na. Similar effects were produced with corticosterone at 400 microgram X 100 g-1 X 24 h-1 (3 X 10(-6) M if immediately distributed in the extracellular fluid). We conclude that the restoration of blood pressure in the adrenalectomized rat is independent of [Na]i or [Na]o/[Na]i but is associated with enhanced Na transport activity.

Ion-selective electrode studies of cell Na components in vascular smooth muscle of WKY and SHR

Vascular smooth muscle cells of the rat tail artery were enriched with Na by overnight incubation at 10 degrees C in K-free physiological salt solution (K-free PSS). The cells were then returned to normal PSS in a series of steps so as to define the effect of varying temperature between 3 and 37 degrees C, the effect of ouabain, the effect of readmitting K+ in the continuing presence of ouabain, and, finally, the effect of removing ouabain in the continuing presence of K+. The effects were measured with flow-through Na+ and K+ glass-cannula electrodes as changes in a superfusate moving slowly past the artery. Where possible, confirmatory evidence was obtained by conventional incubations followed by chemical analysis of the tissues. About 10 mmol Na+/kg dry wt is transferred out of the cells when temperature is raised from 3 to 37 degrees C. Exposure of the tissue to ouabain while the tissue is still in the K-free state produces a further loss of about 8 mmol Na+/kg dry wt and 4 mmol k+/kg dry wt. Readmittance of K+ in the continuing presence of ouabain induces a further loss of about 25 mmol Na+/kg dry wt in exchange for an uptake of about 13 mmol K+ measured electrometrically or about 20 mmol K measured chemically. Finally, the removal of ouabain is followed by an extrusion of about 155 mmol Na+/kg dry wt in exchange for an uptake of 133 mmol K%. The ouabain-insensitive exchange of Na+ and K+ is enhanced in spontaneously hypertensive rats as compared with normotensive rats.

Increased erythrocyte permeability to Li and Na in the spontaneously hypertensive rat

Red blood cells incubated in a physiological medium in which Li replaces Na (LiPSS) gain Li in exchange for Na and K. The rate of Li uptake is modestly but significantly increased in the spontaneously hypertensive rat (SHR) at 37 degrees C and at 22 degrees C. The slow rate of Na gain and K loss during cooling at 2 degrees C was about doubled in unmodified whole blood samples from the SHR.