Ricardo Henao

Host gene expression classifiers diagnose acute respiratory illness etiology.

Pathogen-specific host gene expression changes may combat inappropriate antibiotic use and emerging antibiotic resistance. Resisting antibiotics No matter the cause, acute respiratory infections can be miserable. Indeed, these infections are one of the most common reasons for seeking medical care. A clear diagnostic can help medical practitioners resist the patient-induced pressure to prescribe antibiotics as a catch-all therapy, which increases the risk of bacteria developing antibiotic resistance. Now, Tsalik et al. report clear differences in host gene expression induced by bacterial and viral infection as well as by noninfectious illness. These differences can be used to discriminate between these groups, and a host gene expression classifier may be a helpful diagnostic platform to curb unnecessary antibiotic use. Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational cohort study determined whether host gene expression patterns discriminate noninfectious from infectious illness and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or noninfectious illness, as well as 44 healthy controls, was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a noninfectious cause of illness (26 probes). Overall accuracy was 87% (238 of 273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, P < 0.03) and three published classifiers of bacterial versus viral infection (78 to 83%). The classifiers developed here externally validated in five publicly available data sets (AUC, 0.90 to 0.99). A sixth publicly available data set included 25 patients with co-identification of bacterial and viral pathogens. Applying the ARI classifiers defined four distinct groups: a host response to bacterial ARI, viral ARI, coinfection, and neither a bacterial nor a viral response. These findings create an opportunity to develop and use host gene expression classifiers as diagnostic platforms to combat inappropriate antibiotic use and emerging antibiotic resistance.

Down-regulation of microRNAs controlling tumourigenic factors in follicular thyroid carcinoma

The molecular determinants of thyroid follicular nodules are incompletely understood and assessment of malignancy is a diagnostic challenge. Since microRNA (miRNA) analyses could provide new leads to malignant progression, we characterised the global miRNA expression in follicular adenoma (FA) and follicular carcinoma (FC). Comparison of carcinoma and adenoma with normal thyroid revealed 150 and 107 differentially expressed miRNAs respectively. Most miRNAs were down-regulated and especially miR-199b-5p and miR-144 which were essentially lost in the carcinomas. Integration of the changed miRNAs with differentially expressed mRNAs demonstrated an enrichment of seed sites among up-regulated transcripts encoding proteins implicated in thyroid tumourigenesis. This was substantiated by the demonstration that pre-miR-199b reduced proliferation when added to cultured follicular thyroid carcinoma cells. The down-regulated miRNAs in FC exhibited a substantial similarity with down-regulated miRNAs in anaplastic carcinoma (AC) and by gene set enrichment analysis, we observed a significant identity between target mRNAs in FC and transcripts up-regulated in AC. To examine the diagnostic potential of miRNA expression pattern in distinguishing malignant from benign nodules we employed a supervised learning algorithm and leave-one-out-cross-validation. By this procedure, FA and FC were identified with a negative predicted value of 83% (data generated by microarray platform) and of 92% (data generated by qRT-PCR platform). We conclude that follicular neoplasia is associated with major changes in miRNA expression that may promote malignant transformation by increasing the expression of transcripts encoding tumourigenic factors. Moreover, miRNA profiling may facilitate the diagnosis of carcinoma vs adenoma.

A Network of Substrates of the E3 Ubiquitin Ligases MDM2 and HUWE1 Control Apoptosis Independently of p53

Inhibition of the ubiquitin E3 ligase MDM2 in breast cancer cells could overcome lapatinib resistance. Breaking Down to Build Resistance Chemotherapeutic resistance often arises because of the rewiring of signaling pathways in cancer cells. Kurokawa et al. found that the ubiquitin E3 ligase MDM2 triggered the breakdown of another ubiquitin E3 ligase, HUWE1. In breast cancer cells that died when exposed to the HER2 (human epidermal growth factor receptor 2) EGFR (epidermal growth factor receptor) tyrosine kinase inhibitor lapatinib, MDM2 was degraded, which enabled HUWE1 to trigger the degradation of a prosurvival protein and promote assembly and activation of a protein complex required for the execution of cell death. However, MDM2 degradation did not occur in lapatinib-resistant breast cancer cells, and thus, the abundance of HUWE1 was decreased, promoting cell survival. In a mouse xenograft model, an inhibitor of MDM2 reduced the growth of tumors generated from lapatinib-resistant breast cancer cells. Thus, MDM2 could be targeted to circumvent resistance to lapatinib in breast cancers. In the intrinsic pathway of apoptosis, cell-damaging signals promote the release of cytochrome c from mitochondria, triggering activation of the Apaf-1 and caspase-9 apoptosome. The ubiquitin E3 ligase MDM2 decreases the stability of the proapoptotic factor p53. We show that it also coordinated apoptotic events in a p53-independent manner by ubiquitylating the apoptosome activator CAS and the ubiquitin E3 ligase HUWE1. HUWE1 ubiquitylates the antiapoptotic factor Mcl-1, and we found that HUWE1 also ubiquitylated PP5 (protein phosphatase 5), which indirectly inhibited apoptosome activation. Breast cancers that are positive for the tyrosine receptor kinase HER2 (human epidermal growth factor receptor 2) tend to be highly aggressive. In HER2-positive breast cancer cells treated with the HER2 tyrosine kinase inhibitor lapatinib, MDM2 was degraded and HUWE1 was stabilized. In contrast, in breast cancer cells that acquired resistance to lapatinib, the abundance of MDM2 was not decreased and HUWE1 was degraded, which inhibited apoptosis, regardless of p53 status. MDM2 inhibition overcame lapatinib resistance in cells with either wild-type or mutant p53 and in xenograft models. These findings demonstrate broader, p53-independent roles for MDM2 and HUWE1 in apoptosis and specifically suggest the potential for therapy directed against MDM2 to overcome lapatinib resistance.

An integrated transcriptome and expressed variant analysis of sepsis survival and death.

BackgroundSepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality.MethodsThe Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (SIRS due to infection), including 78 sepsis survivors and 28 sepsis non-survivors who had previously undergone plasma proteomic and metabolomic profiling. Gene expression differences were identified between sepsis survivors, sepsis non-survivors, and SIRS followed by gene enrichment pathway analysis. Expressed sequence variants were identified followed by testing for association with sepsis outcomes.ResultsThe expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflecting immune activation in sepsis. Expression of 1,238 genes differed with sepsis outcome: non-survivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease-rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors. The presence of variants was associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology.ConclusionsThe activation of immune response-related genes seen in sepsis survivors was muted in sepsis non-survivors. The association of sepsis survival with a robust immune response and the presence of missense variants in VPS9D1 warrants replication and further functional studies.Trial registrationClinicalTrials.gov NCT00258869. Registered on 23 November 2005.

Molecular signatures of thyroid follicular neoplasia

The molecular pathways leading to thyroid follicular neoplasia are incompletely understood, and the diagnosis of follicular tumors is a clinical challenge. To provide leads to the pathogenesis and diagnosis of the tumors, we examined the global transcriptome signatures of follicular thyroid carcinoma (FC) and normofollicular adenoma (FA) as well as fetal/microFA (fetal adenoma). Carcinomas were strongly enriched in transcripts encoding proteins involved in DNA replication and mitosis corresponding to increased number of proliferating cells and depleted number of transcripts encoding factors involved in growth arrest and apoptosis. In the latter group, the combined loss of transcripts encoding the nuclear orphan receptors NR4A1 and NR4A3, which were recently shown to play a causal role in hematopoetic neoplasia, was noteworthy. The analysis of differentially expressed transcripts provided a mechanism for cancer progression, which is why we exploited the results in order to generate a molecular classifier that could identify 95% of all carcinomas. Validation employing public domain and cross-platform data demonstrated that the signature was robust and could diagnose follicular nodules originating from different geographical locations and platforms with similar accuracy. We came to the conclusion that down-regulation of factors involved in growth arrest and apoptosis may represent a decisive step in the pathogenesis of FC. Moreover, the described molecular pathways provide an accurate and robust genetic signature for the diagnosis of FA and FC.

Gene expression of the endolymphatic sac.

Abstract Conclusion: The endolymphatic sac is part of the membranous inner ear and is thought to play a role in the fluid homeostasis and immune defense of the inner ear; however, the exact function of the endolymphatic sac is not fully known. Many of the detected mRNAs in this study suggest that the endolymphatic sac has multiple and diverse functions in the inner ear. Objectives:The objective of this study was to provide a comprehensive review of the genes expressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Methods:Microarray technology was used to investigate the gene expression of the endolymphatic sac with the surrounding dura. Characteristic and novel endolymphatic sac genes were determined by comparing with expressions in pure dura. Results: In all, 463 genes were identified specific for the endolymphatic sac. Functional annotation clustering revealed 29 functional clusters.

Vitamin D is Not Associated With Severity in NAFLD: Results of a Paired Clinical and Gene Expression Profile Analysis

OBJECTIVES:The pathogenesis of nonalcoholic fatty liver disease (NAFLD) is complex. Vitamin D (VitD) has been implicated in NAFLD pathogenesis because it has roles in immune modulation, cell differentiation and proliferation, and regulation of inflammation. We evaluated the association of VitD levels, hepatic gene expression for VitD metabolizing genes, and NAFLD histological severity.METHODS:Two adult cohorts, controls (n=39) and NAFLD (n=244), who underwent liver biopsy were compared. Two-sided t-tests or Wilcoxon’s rank-sum tests for continuous predictors and chi-squared tests or Fisher’s exact tests for categorical variables were used to analyze the association of VitD and NAFLD. Generalized linear models were used to analyze the association of VitD levels and VitD metabolizing genes with histological severity of NAFLD while adjusting for potential confounders and correcting for multiple comparisons.RESULTS:NAFLD patients were more likely than controls to have higher HbA1c (6.5±1.2 vs 5.9±1.0; P=0.009), a risk factor for VitD deficiency. However, no difference in VitD levels was observed between groups. VitD levels did not correlate with the severity of hepatic steatosis, lobular or portal inflammation, or ballooned hepatocytes after adjusting for confounding factors. Furthermore, no association was noted between VitD deficiency or differential expression of genes involved in VitD metabolism and severity of hepatic fibrosis or any other histologic feature of NAFLD.CONCLUSIONS:Neither VitD deficiency, nor hepatic expression of VitD-related genes, associate with the presence or histologic severity of NAFLD in patients. Hence, despite preclinical evidence implicating VitD in NAFLD pathogenesis, VitD deficiency does not appear to be associated with NAFLD severity in humans.

High-Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections

In this article, we review recent progress in using high-dimensional longitudinal genomic data collected from virus challenge studies, per- formed with healthy human volun- teers. The focus of the article is on statistical signal processing, but we also show how the results may be used to yield biological insights.

Differential evolution of peripheral cytokine levels in symptomatic and asymptomatic responses to experimental influenza virus challenge.

Exposure to influenza virus triggers a complex cascade of events in the human host. In order to understand more clearly the evolution of this intricate response over time, human volunteers were inoculated with influenza A/Wisconsin/67/2005 (H3N2), and then had serial peripheral blood samples drawn and tested for the presence of 25 major human cytokines. Nine of 17 (53%) inoculated subjects developed symptomatic influenza infection. Individuals who will go on to become symptomatic demonstrate increased circulating levels of interleukin (IL)‐6, IL‐8, IL‐15, monocyte chemotactic protein (MCP)‐1 and interferon (IFN) gamma‐induced protein (IP)‐10 as early as 12–29 h post‐inoculation (during the presymptomatic phase), whereas challenged patients who remain asymptomatic do not. Overall, the immunological pathways of leucocyte recruitment, Toll‐like receptor (TLR)‐signalling, innate anti‐viral immunity and fever production are all over‐represented in symptomatic individuals very early in disease, but are also dynamic and evolve continuously over time. Comparison with simultaneous peripheral blood genomics demonstrates that some inflammatory mediators (MCP‐1, IP‐10, IL‐15) are being expressed actively in circulating cells, while others (IL‐6, IL‐8, IFN‐α and IFN‐γ) are probable effectors produced locally at the site of infection. Interestingly, asymptomatic exposed subjects are not quiescent either immunologically or genomically, but instead exhibit early and persistent down‐regulation of important inflammatory mediators in the periphery. The host inflammatory response to influenza infection is variable but robust, and evolves over time. These results offer critical insight into pathways driving influenza‐related symptomatology and offer the potential to contribute to early detection and differentiation of infected hosts.

PASS-GP: Predictive active set selection for Gaussian processes

We propose a new approximation method for Gaussian process (GP) learning for large data sets that combines inline active set selection with hyperparameter optimization. The predictive probability of the label is used for ranking the data points. We use the leave-one-out predictive probability available in GPs to make a common ranking for both active and inactive points, allowing points to be removed again from the active set. This is important for keeping the complexity down and at the same time focusing on points close to the decision boundary. We lend both theoretical and empirical support to the active set selection strategy and marginal likelihood optimization on the active set. We make extensive tests on the USPS and MNIST digit classification databases with and without incorporating invariances, demonstrating that we can get state-of-the-art results (e.g.0.86% error on MNIST) with reasonable time complexity.