Assessment of network module identification across complex diseases.

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the 'Disease Module Identification DREAM Challenge', an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.

Outcomes and Susceptibility to Neuraminidase Inhibitors in Individuals Infected With Different Influenza B Lineages: The Influenza Resistance Information Study.

BACKGROUND: Little is known about how influenza infections caused by B/Victoria and B/Yamagata virus lineages compare with respect to disease course and susceptibility to antiviral therapy. METHODS: Data from patients with influenza B infections from the first 5 years (2009-2013) of the prospective Influenza Resistance Information Study (IRIS, NCT00884117) were evaluated. Cultured viruses were phenotypically tested for neuraminidase inhibitor (NAI) sensitivity, and sequenced to determine virus lineage (B/Victoria or B/Yamagata). Differences in clinical outcomes (viral clearance and symptom resolution) between virus lineages were assessed using Kaplan-Meier analysis. RESULTS: In all, 914 patients were positive for influenza B by reverse transcriptase polymerase chain reaction ( RT-PCR: B/Victoria, 586; B/Yamagata, 289; not subtyped, 39); 474 were treated with antivirals. No phenotypic resistance to oseltamivir or zanamivir was found in B/Victoria or B/Yamagata viruses. Of 15 predefined resistance mutations, 2 were detected by neuraminidase sequencing: I221T had reduced sensitivity to oseltamivir, and I221V was sensitive to NAI inhibition. No consistent differences between virus lineages in times to viral clearance or to symptom or fever resolution were found in adults and adolescents or in children. CONCLUSIONS: Influenza B virus lineage had no notable effect on disease outcomes or antiviral susceptibility in this population.

Human pluripotent stem cell models of autism spectrum disorder: emerging frontiers, opportunities, and challenges towards neuronal networks in a dish.

Autism spectrum disorder (ASD) is characterized by deficits in language development and social cognition and the manifestation of repetitive and restrictive behaviors. Despite recent major advances, our understanding of the pathophysiological mechanisms leading to ASD is limited. Although most ASD cases have unknown genetic underpinnings, animal and human cellular models of several rare, genetically defined syndromic forms of ASD have provided evidence for shared pathophysiological mechanisms that may extend to idiopathic cases. Here, we review our current knowledge of the genetic basis and molecular etiology of ASD and highlight how human pluripotent stem cell-based disease models have the potential to advance our understanding of molecular dysfunction. We summarize landmark studies in which neuronal cell populations generated from human embryonic stem cells and patient-derived induced pluripotent stem cells have served to model disease mechanisms, and we discuss recent technological advances that may ultimately allow in vitro modeling of specific human neuronal circuitry dysfunction in ASD. We propose that these advances now offer an unprecedented opportunity to help better understand ASD pathophysiology. This should ultimately enable the development of cellular models for ASD, allowing drug screening and the identification of molecular biomarkers for patient stratification.

14-3-3ζ orchestrates mammary tumor onset and progression via miR-221-mediated cell proliferation.

14-3-3ζ is overexpressed in more than 40% of breast cancers, but its pathophysiologic relevance to tumorigenesis has not been established. Here, we show that 14-3-3ζ overexpression is sufficient to induce tumorigenesis in a transgenic mouse model of breast cancer. MMTV-LTR promoter-driven HA-14-3-3ζ transgenic mice (MMTV-HA-14-3-3ζ) developed mammary tumors, whereas control mice did not. Whey acidic protein promoter-driven HA-14-3-3ζ transgenic mice (WAP-HA-14-3-3ζ) developed hyperplastic lesions and showed increased susceptibility to carcinogen-induced tumorigenesis. When crossed with MMTV-neu transgenic mice, 14-3-3ζ.neu transgenic mice exhibited accelerated mammary tumorigenesis and metastasis compared with MMTV-neu mice. Mechanistically, 14-3-3ζ overexpression enhanced MAPK/c-Jun signaling, leading to increased miR-221 transcription, which inhibited p27 CDKI translation and, consequently, promoted cell proliferation. Importantly, this 14-3-3ζ-miR-221-p27 proliferation axis is also functioning in breast tumors in patients and is associated with high-grade cancers. Taken together, our findings show that overexpression of 14-3-3ζ has a causal role in mammary tumorigenesis and progression, acting through miR-221 in cooperation with known oncogenic events to drive neoplastic cell proliferation.

Plasma microRNA profiles for bladder cancer detection.

BACKGROUND: Bladder cancer (BC) is a burdensome disease with significant morbidity, mortality, and cost. The development of novel plasma-based biomarkers for BC diagnosis and surveillance could significantly improve clinical outcomes and decrease health expenditures. Plasma miRNAs are promising biomarkers that have yet to be rigorously investigated in BC. OBJECTIVE: To determine the feasibility and efficacy of detecting BC with plasma miRNA signatures. MATERIALS AND METHODS: Plasma miRNA was isolated from 20 patients with bladder cancer and 18 noncancerous controls. Samples were analyzed with a miRNA array containing duplicate probes for each miRNA in the Sanger database. Logistic regression modeling was used to optimize diagnostic miRNA signatures to distinguish between muscle invasive BC (MIBC), non-muscle-invasive BC (NMIBC) and noncancerous controls. RESULTS: Seventy-nine differentially expressed plasma miRNAs (local false discovery rate [FDR] <0.5) in patients with or without BC were identified. Some diagnostically relevant miRNAs, such as miR-200b, were up-regulated in MIBC patients, whereas others, such as miR-92 and miR-33, were inversely correlated with advanced clinical stage, supporting the notion that miRNAs released in the circulation have a variety of cellular origins. Logistic regression modeling was able to predict diagnosis with 89% accuracy for detecting the presence or absence of BC, 92% accuracy for distinguishing invasive BC from other cases, 100% accuracy for distinguishing MIBC from controls, and 79% accuracy for three-way classification between MIBC, NIMBC, and controls. CONCLUSIONS: This study provides preliminary data supporting the use of plasma miRNAs as a noninvasive means of BC detection. Future studies will be required to further specify the optimal plasma miRNA signature, and to apply these signatures to clinical scenarios, such as initial BC detection and BC surveillance.