Antipsychotics activate the TGFβ pathway effector SMAD3

Although effective in treating an array of neurological disorders, antipsychotics are associated with deleterious metabolic side effects. Through high-throughput screening, we previously identified phenothiazine antipsychotics as modulators of the human insulin promoter. Here, we extended our initial finding to structurally diverse typical and atypical antipsychotics. We then identified the transforming growth factor beta (TGFβ) pathway as being involved in the effect of antipsychotics on the insulin promoter, finding that antipsychotics activated SMAD3, a downstream effector of the TGFβ pathway, through a receptor distinct from the TGFβ receptor family and known neurotransmitter receptor targets of antipsychotics. Of note, antipsychotics that do not cause metabolic side effects did not activate SMAD3. In vivo relevance was demonstrated by reanalysis of gene expression data from human brains treated with antipsychotics, which showed altered expression of SMAD3 responsive genes. This work raises the possibility that antipsychotics could be designed that retain beneficial CNS activity while lacking deleterious metabolic side effects.

Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis in irritable bowel syndrome

Enhanced stress responsiveness has been implicated as a potential mechanism contributing to the pathophysiology of irritable bowel syndrome (IBS), and should be reflected in altered function of the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic nervous system. Both of these systems can modulate mucosal immune function. The aims of this study were: (i) to characterize the basal circadian rhythm of adrenocorticotropin hormone (ACTH) and cortisol in IBS vs healthy controls; (ii) to compare stimulated ACTH, cortisol and noradrenaline responses to a pelvic visceral stressor (sigmoidoscopy) in IBS and controls; and (iii) to correlate neuroendocrine responses with colonic mucosal cytokine expression and symptoms in IBS. Two separate studies were conducted in women. In Study 1, basal cortisol levels were analysed in 41 IBS and 25 controls using 24-h collections of plasma ACTH and cortisol (q10 min sampling). In Study 2, 10 IBS patients with diarrhoea (IBS-D) and 10 controls underwent sigmoidoscopy with measurements of stimulated neuroendocrine responses and cytokine mRNA expression in colonic tissue. Basal ACTH levels were significantly blunted (P < 0.05), while basal and stimulated plasma cortisol levels were higher in patients. Basal cortisol levels prior to an experimental visceral stressor positively correlated with anxiety symptoms (P < 0.004), but not IBS symptoms. Irritable bowel syndrome patients with diarrhoea had significantly decreased mRNA expression of mucosal cytokines [interleukin (IL)-2, IL-6] in the sigmoid colon vs controls (P < 0.05). Although dysregulations in stress-responsive systems such as the HPA axis and mucosal immune function are demonstrated in IBS, they do not appear to have a primary role in modulating IBS severity and abdominal pain.

Profiling humoral immune responses to P. falciparum infection with protein microarrays

A complete description of the serological response following exposure of humans to complex pathogens is lacking and approaches suitable for accomplishing this are limited. Here we report, using malaria as a model, a method which elucidates the profile of antibodies that develop after natural or experimental infection or after vaccination with attenuated organisms, and which identifies immunoreactive antigens of interest for vaccine development or other applications. Expression vectors encoding 250 Plasmodium falciparum (Pf) proteins were generated by PCR/recombination cloning; the proteins were individually expressed with >90% efficiency in Escherichia coli cell-free in vitro transcription and translation reactions, and printed directly without purification onto microarray slides. The protein microarrays were probed with human sera from one of four groups which differed in immune status: sterile immunity or no immunity against experimental challenge following vaccination with radiation-attenuated Pf sporozoites, partial immunity acquired by natural exposure, and no previous exposure to Pf. Overall, 72 highly reactive Pf antigens were identified. Proteomic features associated with immunoreactivity were identified. Importantly, antibody profiles were distinct for each donor group. Information obtained from such analyses will facilitate identifying antigens for vaccine development, dissecting the molecular basis of immunity, monitoring the outcome of whole-organism vaccine trials, and identifying immune correlates of protection.

How noisy and replicable are DNA microarry data?

This paper analyses variability in highly replicated measurements of DNA microarray data conducted on nylon filters and Affymetrix GeneChips with different cDNA targets, filters, and imaging technology. Replicability is assessed quantitatively using correlation analysis as a global measure and differential expression analysis and ANOVA at the level of individual genes.

From protein microarrays to diagnostic antigen discovery: a study of the pathogen Francisella tularensis

MOTIVATION

An important application of protein microarray data analysis is identifying a serodiagnostic antigen set that can reliably detect patterns and classify antigen expression profiles. This work addresses this problem using antibody responses to protein markers measured by a novel high-throughput microarray technology. The findings from this study have direct relevance to rapid, broad-based diagnostic and vaccine development.

RESULTS

Protein microarray chips are probed with sera from individuals infected with the bacteria Francisella tularensis, a category A biodefense pathogen. A two-step approach to the diagnostic process is presented (1) feature (antigen) selection and (2) classification using antigen response measurements obtained from F.tularensis microarrays (244 antigens, 46 infected and 54 healthy human sera measurements). To select antigens, a ranking scheme based on the identification of significant immune responses and differential expression analysis is described. Classification methods including k-nearest neighbors, support vector machines (SVM) and k-Means clustering are applied to training data using selected antigen sets of various sizes. SVM based models yield prediction accuracy rates in the range of approximately 90% on validation data, when antigen set sizes are between 25 and 50. These results strongly indicate that the top-ranked antigens can be considered high-priority candidates for diagnostic development.

AVAILABILITY

All software programs are written in R and available at http://www.igb.uci.edu/index.php?page=tools and at http://www.r-project.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of humoral immune responses in protein microarrays using DNA microarray data analysis techniques

MOTIVATION

We present a study of antigen expression signals from a newly developed high-throughput protein microarray technique. These signals are a measure of antibody-antigen binding activity and provide a basis for understanding humoral immune responses to various infectious agents and supporting vaccine and diagnostic development.

RESULTS

We investigate the characteristics of these expression profiles and show that noise models, normalization, variance estimation and differential expression analysis techniques developed in the context of DNA microarray analysis can be adapted and applied to these protein arrays. Using a high-dimensional dataset containing measurements of expression profiles of antibody reactivity against each protein (295 antigens and 9 controls) in 42 malaria (Plasmodium falciparum) protein arrays derived from 22 donors with various clinical presentations of malaria, we present a methodology for the analysis and identification of significantly expressed antigens targeted by immune responses for individual sera, groups of sera and across stages of infection. We also conduct a short study highlighting the top immunoreactive antigens where we identify three novel high priority antigens for future evaluation.

AVAILABILITY

All software programs (in R) used for the analysis described in this paper are freely available for academic purposes at www.igb.uci.edu/servers/servers.html.

Supporting multi-level multi-perspective dynamic decision making in medicine

Most medical decision problems are exceedingly complex and contain a large number of variables. Abstraction facilitates the process of building a decision model by allowing a model builder to work at a level of detail that he is most comfortable with; it is also useful in time-critical situations or when there is insufficient data to support complete specification of probabilities of the uncertain events. In this paper, we identify and formalize abstraction and refinement operations commonly used in model construction. We illustrate the use of these mechanisms with an example on the follow-up management of colorectal cancer patients after surgery.

Decision analytic approach to severe head injury management

Severe head injury management in the intensive care unit is extremely challenging due to the complex domain, the uncertain intervention efficacies, and the time-critical setting. We adopt a decision analytic approach to automate the management process. We document our experience in building a simplified influence diagram that involves about 3000 numerical parameters. We identify the inherent problems in structuring a model with unclear domain relationships, numerous interacting variables, and real-time multiple inputs. We analyze the effectiveness and limitations of the decision analytic approach and present a set of desiderata for effective knowledge acquisition in this setting. We also propose a semi-qualitative approach to parameter elicitation.