Neurocognitive Function in Children with Primary Hypertension

To compare neurocognitive test performance of children with primary hypertension to that of normotensive controls

Sleep Disordered Breathing as Measured by SRBD-PSQ and Neurocognition in Children With Hypertension

Cognitive test performance is decreased in hypertensive adults and children, a finding postulated to represent early target-organ damage to the brain. Hypertensive children are often obese, a comorbidity associated with sleep disordered breathing (SDB), itself associated with cognitive problems; potentially confounding the relation between hypertension (HTN) and neurocognition. Our objective was to determine the association between SDB as measured by a scale and questionnaire score and neurocognition among participants enrolled in an ongoing multicenter study of cognition in children with HTN

MicroRNA-135b promotes cancer progression by acting as a downstream effector of oncogenic pathways in colon cancer

MicroRNA deregulation is frequent in human colorectal cancers (CRCs), but little is known as to whether it represents a bystander event or actually drives tumor progression in vivo. We show that miR-135b overexpression is triggered in mice and humans by APC loss, PTEN/PI3K pathway deregulation, and SRC overexpression and promotes tumor transformation and progression. We show that miR-135b upregulation is common in sporadic and inflammatory bowel disease-associated human CRCs and correlates with tumor stage and poor clinical outcome. Inhibition of miR-135b in CRC mouse models reduces tumor growth by controlling genes involved in proliferation, invasion, and apoptosis. We identify miR-135b as a key downsteam effector of oncogenic pathways and a potential target for CRC treatment

Exon expression arrays as a tool to identify new cancer genes

Background: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. Principal Findings: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). Conclusions: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes

Is My Network Module Preserved and Reproducible?

In many applications, one is interested in determining which of the properties of a network module change across conditions. For example, to validate the existence of a module, it is desirable to show that it is reproducible (or preserved) in an independent test network. Here we study several types of network preservation statistics that do not require a module assignment in the test network. We distinguish network preservation statistics by the type of the underlying network. Some preservation statistics are defined for a general network (defined by an adjacency matrix) while others are only defined for a correlation network (constructed on the basis of pairwise correlations between numeric variables). Our applications show that the correlation structure facilitates the definition of particularly powerful module preservation statistics. We illustrate that evaluating module preservation is in general different from evaluating cluster preservation. We find that it is advantageous to aggregate multiple preservation statistics into summary preservation statistics. We illustrate the use of these methods in six gene co-expression network applications including 1) preservation of cholesterol biosynthesis pathway in mouse tissues, 2) comparison of human and chimpanzee brain networks, 3) preservation of selected KEGG pathways between human and chimpanzee brain networks, 4) sex differences in human cortical networks, 5) sex differences in mouse liver networks. While we find no evidence for sex specific modules in human cortical networks, we find that several human cortical modules are less preserved in chimpanzees. In particular, apoptosis genes are differentially co-expressed between humans and chimpanzees. Our simulation studies and applications show that module preservation statistics are useful for studying differences between the modular structure of networks. Data, R software and accompanying tutorials can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/ModulePreservation