Sequence-Level Analysis of the Major European Huntington Disease Haplotype.

Huntington disease (HD) reflects the dominant consequences of a CAG-repeat expansion in HTT. Analysis of common SNP-based haplotypes has revealed that most European HD subjects have distinguishable HTT haplotypes on their normal and disease chromosomes and that ∼50% of the latter share the same major HD haplotype. We reasoned that sequence-level investigation of this founder haplotype could provide significant insights into the history of HD and valuable information for gene-targeting approaches. Consequently, we performed whole-genome sequencing of HD and control subjects from four independent families in whom the major European HD haplotype segregates with the disease. Analysis of the full-sequence-based HTT haplotype indicated that these four families share a common ancestor sufficiently distant to have permitted the accumulation of family-specific variants. Confirmation of new CAG-expansion mutations on this haplotype suggests that unlike most founders of human disease, the common ancestor of HD-affected families with the major haplotype most likely did not have HD. Further, availability of the full sequence data validated the use of SNP imputation to predict the optimal variants for capturing heterozygosity in personalized allele-specific gene-silencing approaches. As few as ten SNPs are capable of revealing heterozygosity in more than 97% of European HD subjects. Extension of allele-specific silencing strategies to the few remaining homozygous individuals is likely to be achievable through additional known SNPs and discovery of private variants by complete sequencing of HTT. These data suggest that the current development of gene-based targeting for HD could be extended to personalized allele-specific approaches in essentially all HD individuals of European ancestry.

Pitfalls and possibilities of radar compressive sensing.

In this paper, we consider the application of compressive sensing (CS) to radar remote sensing applications. We survey a suite of practical system-level issues related to the compression of radar measurements, and we advocate the consideration of these issues by researchers exploring potential gains of CS in radar applications. We also give abbreviated examples of decades-old radio-frequency (RF) practices that already embody elements of CS for relevant applications. In addition to the cautionary implications of system-level issues and historical precedents, we identify several promising results that RF practitioners may gain from the recent explosion of CS literature.

Temporal profiling of cytokine-induced genes in pancreatic ß-cells by meta-analysis and network inference.

Type 1 Diabetes (T1D) is an autoimmune disease where local release of cytokines such as IL-1ß and IFN-γ contributes to ß-cell apoptosis. To identify relevant genes regulating this process we performed a meta-analysis of 8 datasets of ß-cell gene expression after exposure to IL-1ß and IFN-γ. Two of these datasets are novel and contain time-series expressions in human islet cells and rat INS-1E cells. Genes were ranked according to their differential expression within and after 24 h from exposure, and characterized by function and prior knowledge in the literature. A regulatory network was then inferred from the human time expression datasets, using a time-series extension of a network inference method. The two most differentially expressed genes previously unknown in T1D literature (RIPK2 and ELF3) were found to modulate cytokine-induced apoptosis. The inferred regulatory network is thus supported by the experimental validation, providing a proof-of-concept for the proposed statistical inference approach.

Optically multiplexed imaging with superposition space tracking.

We describe a novel method to track targets in a large field of view. This method simultaneously images multiple, encoded sub-fields of view onto a common focal plane. Sub-field encoding enables target tracking by creating a unique connection between target characteristics in superposition space and the target's true position in real space. This is accomplished without reconstructing a conventional image of the large field of view. Potential encoding schemes include spatial shift, rotation, and magnification. We discuss each of these encoding schemes, but the main emphasis of the paper and all examples are based on one-dimensional spatial shift encoding. System performance is evaluated in terms of two criteria: average decoding time and probability of decoding error. We study these performance criteria as a function of resolution in the encoding scheme and signal-to-noise ratio. Finally, we include simulation and experimental results demonstrating our novel tracking method.

T1DBase: integration and presentation of complex data for type 1 diabetes research.

T1DBase (http://T1DBase.org) [Smink et al. (2005) Nucleic Acids Res., 33, D544-D549; Burren et al. (2004) Hum. Genomics, 1, 98-109] is a public website and database that supports the type 1 diabetes (T1D) research community. T1DBase provides a consolidated T1D-oriented view of the complex data world that now confronts medical researchers and enables scientists to navigate from information they know to information that is new to them. Overview pages for genes and markers summarize information for these elements. The Gene Dossier summarizes information for a list of genes. GBrowse [Stein et al. (2002) Genome Res., 10, 1599-1610] displays genes and other features in their genomic context, and Cytoscape [Shannon et al. (2003) Genome Res., 13, 2498-2504] shows genes in the context of interacting proteins and genes. The Beta Cell Gene Atlas shows gene expression in beta cells, islets, and related cell types and lines, and the Tissue Expression Viewer shows expression across other tissues. The Microarray Viewer shows expression from more than 20 array experiments. The Beta Cell Gene Expression Bank contains manually curated gene and pathway annotations for genes expressed in beta cells. T1DMart is a query tool for markers and genotypes. PosterPages are 'home pages' about specific topics or datasets. The key challenge, now and in the future, is to provide powerful informatics capabilities to T1D scientists in a form they can use to enhance their research.

Clinical Management of Neuropsychiatric Symptoms of Huntington Disease: Expert-Based Consensus Guidelines on Agitation, Anxiety, Apathy, Psychosis and Sleep Disorders.

BACKGROUND: In clinical practice, several strategies and pharmacological options are available to treat neuropsychiatric symptoms of Huntington disease (HD). However, there is currently insufficient data for evidence-based guidelines on the management of these common symptoms. OBJECTIVE: We aimed to develop expert-based recommendations regarding the management of agitation, anxiety, apathy, psychosis, and sleep disorders. METHODS: Guideline development was based on a modified Institute of Medicine guideline process that accounted for a lack of evidence base. An international committee of 11 multidisciplinary experts proposed a series of statements regarding the description and management of each symptom. Statement assessment and validation was performed using a web-based survey tool and 84 international HD experts (neurologists and psychiatrists) who assessed the statements and indicated their level of agreement. RESULTS: High-level agreement (≥85% experts strongly agreed or agreed) was reached for 107 of the 110 statements that have been incorporated into the expert-based clinical recommendations presented herein. CONCLUSIONS: Clinical statements to guide the routine management of agitation, anxiety, apathy, psychosis, and sleep disorders in HD have been developed. Although not specifically tested in the HD population, clinical experience has shown that most of the neuropsychiatric symptoms discussed, when considered in isolation are treatable using pharmacologic and non-pharmacologic strategies developed for use in other populations. However, the management of neuropsychiatric symptoms in HD can be complex because neuropsychiatric symptoms often co-exist and treatment decisions should be adapted to cover all symptoms while limiting polypharmacy.

T1DBase, a community web-based resource for type 1 diabetes research.

T1DBase (http://T1DBase.org) is a public website and database that supports the type 1 diabetes (T1D) research community. The site is currently focused on the molecular genetics and biology of T1D susceptibility and pathogenesis. It includes the following datasets: annotated genome sequence for human, rat and mouse; information on genetically identified T1D susceptibility regions in human, rat and mouse, and genetic linkage and association studies pertaining to T1D; descriptions of NOD mouse congenic strains; the Beta Cell Gene Expression Bank, which reports expression levels of genes in beta cells under various conditions, and annotations of gene function in beta cells; data on gene expression in a variety of tissues and organs; and biological pathways from KEGG and BioCarta. Tools on the site include the GBrowse genome browser, site-wide context dependent search, Connect-the-Dots for connecting gene and other identifiers from multiple data sources, Cytoscape for visualizing and analyzing biological networks, and the GESTALT workbench for genome annotation. All data are open access and all software is open source.

Analysis of tumor template from multiple compartments in a blood sample provides complementary access to peripheral tumor biomarkers.

Targeted cancer therapeutics are promised to have a major impact on cancer treatment and survival. Successful application of these novel treatments requires a molecular definition of a patient's disease typically achieved through the use of tissue biopsies. Alternatively, allowing longitudinal monitoring, biomarkers derived from blood, isolated either from circulating tumor cell derived DNA (ctcDNA) or circulating cell-free tumor DNA (ccfDNA) may be evaluated. In order to use blood derived templates for mutational profiling in clinical decisions, it is essential to understand the different template qualities and how they compare to biopsy derived template DNA as both blood-based templates are rare and distinct from the gold-standard. Using a next generation re-sequencing strategy, concordance of the mutational spectrum was evaluated in 32 patient-matched ctcDNA and ccfDNA templates with comparison to tissue biopsy derived DNA template. Different CTC antibody capture systems for DNA isolation from patient blood samples were also compared. Significant overlap was observed between ctcDNA, ccfDNA and tissue derived templates. Interestingly, if the results of ctcDNA and ccfDNA template sequencing were combined, productive samples showed similar detection frequency (56% vs 58%), were temporally flexible, and were complementary both to each other and the gold standard. These observations justify the use of a multiple template approach to the liquid biopsy, where germline, ctcDNA, and ccfDNA templates are employed for clinical diagnostic purposes and open a path to comprehensive blood derived biomarker access.

Feature-specific difference imaging.

Difference images quantify changes in the object scene over time. In this paper, we use the feature-specific imaging paradigm to present methods for estimating a sequence of difference images from a sequence of compressive measurements of the object scene. Our goal is twofold. First is to design, where possible, the optimal sensing matrix for taking compressive measurements. In scenarios where such sensing matrices are not tractable, we consider plausible candidate sensing matrices that either use the available a priori information or are nonadaptive. Second, we develop closed-form and iterative techniques for estimating the difference images. We specifically look at l(2)- and l(1)-based methods. We show that l(2)-based techniques can directly estimate the difference image from the measurements without first reconstructing the object scene. This direct estimation exploits the spatial and temporal correlations between the object scene at two consecutive time instants. We further develop a method to estimate a generalized difference image from multiple measurements and use it to estimate the sequence of difference images. For l(1)-based estimation, we consider modified forms of the total-variation method and basis pursuit denoising. We also look at a third method that directly exploits the sparsity of the difference image. We present results to show the efficacy of these techniques and discuss the advantages of each.

An International Survey-based Algorithm for the Pharmacologic Treatment of Irritability in Huntington's Disease.

It is generally believed that treatments are available to manage irritability in Huntington's disease (HD). However, lack of an evidence base prevents the establishment of treatment guidelines for this symptom. The research literature fails to address behavioral intervention strategies, drug selection, drug dosing, management of inadequate response to a single drug, or preferred drugs when additional behavioral symptoms comorbid to irritability are present. In an effort to inform clinical decision-making we surveyed an international group of experts to address these points. The experts consistently endorsed an antipsychotic drug (APD) as first choice for treatment of urgent and aggressive irritability behaviors. However, there was variation in practice patterns for treating less severe symptoms. Serotonin reuptake inhibitors (SSRIs) were first choice drug treatments by most respondents across all geographic regions. However, APDs were also endorsed as first choice for mild or moderate irritability, more frequently in Europe than in North America and Australia. Antiepileptic mood stabilizers (AEDs) were used by fewer respondents as first choice drug. Perceived efficacy for control of mild or moderate irritability was judged somewhat higher for APDs than SSRIs or AEDs. Benzodiazepines were not used as monotherapy, but frequently as an adjunctive drug in the setting of comorbid anxiety. Though many cited lack of experience with mirtazapine, others familiar with its use in HD chose it as an alternative monotherapy, or as adjunctive therapy if insomnia was a comorbid factor. This report presents survey results, reviews available irritability studies, and lastly proposes an algorithm for the treatment of irritability in HD derived from expert preferences obtained through this survey.

An International Survey-based Algorithm for the Pharmacologic Treatment of Obsessive-Compulsive Behaviors in Huntington's Disease.

It is generally believed that treatments are available to manage obsessive-compulsive behaviors (OCB's) in Huntington's disease (HD). However, lack of an evidence base prevents guideline development. The research literature fails to address the indications for behavioral interventions, drug selection, drug dosing, management of inadequate response to a single drug, and preferred drugs when additional behavioral symptoms comorbid to OCBs are present. In an effort to inform clinical decision-making, we surveyed an international group of experts to address these points. Survey results showed that experts utilized behavioral therapy only for patients with mild cognitive impairment. There was expert agreement that a selective serotonin reuptake inhibitor (SSRI) was the first choice drug, although clomipramine (CMI) was cited as a monotherapy choice by the smaller number of experts familiar with its use. Perceived efficacy for control of OCBs was similar for both SSRIs and CMI. Though less favored choices overall, antipsychotics (APDs) and antiepileptic mood stabilizers (AEDs) were most often used as augmentation strategies. In addition to survey results, this report reviews available studies, and lastly presents an algorithm for the treatment of OCBs in HD based on practice-based preferences obtained from this survey.

An International Survey-based Algorithm for the Pharmacologic Treatment of Chorea in Huntington's Disease.

It is generally believed that treatments are available to manage chorea in Huntington's disease (HD). However, lack of evidence prevents the establishment of treatment guidelines. The HD chorea research literature fails to address the indications for drug treatment, drug selection, drug dosing and side effect profiles, management of inadequate response to a single drug, and preferred drug when behavioral symptoms comorbid to chorea are present. Because there is lack of an evidence base to inform clinical decision-making, we surveyed an international group of experts to address these points. Survey results showed that patient stigma, physical injury, gait instability, work interference, and disturbed sleep were indications for a drug treatment trial. However, the experts did not agree on first choice of chorea drug, with the majority of experts in Europe favoring an antipsychotic drug (APD), and a near equal split in first choice between an APD and tetrabenazine (TBZ) among experts from North America and Australia. All experts chose an APD when comorbid psychotic or aggressive behaviors were present, or when active depression prevented the use of TBZ. However, there was agreement from all geographic regions that both APDs and TBZ were acceptable as monotherapy in other situations. Perceived efficacy and side effect profiles were similar for APDs and TBZ, except for depression as a significant side effect of TBZ. Experts used a combination of an APD and TBZ when treatment required both drugs for control of chorea and a concurrent comorbid symptom, or when severe chorea was inadequately controlled by either drug alone. The benzodiazepines (BZDs) were judged ineffective as monotherapy but useful as adjunctive therapy, particularly when chorea was exacerbated by anxiety. There was broad disagreement about the use of amantadine for chorea. Experts who had used amantadine described its benefit as small and transient. In addition to survey results, this report reviews available chorea studies, and lastly presents an algorithm for the treatment of chorea in HD which is based on expert preferences obtained through this international survey.

Analysis of genetic inheritance in a family quartet by whole-genome sequencing.

We analyzed the whole-genome sequences of a family of four, consisting of two siblings and their parents. Family-based sequencing allowed us to delineate recombination sites precisely, identify 70% of the sequencing errors (resulting in > 99.999% accuracy), and identify very rare single-nucleotide polymorphisms. We also directly estimated a human intergeneration mutation rate of approximately 1.1 x 10(-8) per position per haploid genome. Both offspring in this family have two recessive disorders: Miller syndrome, for which the gene was concurrently identified, and primary ciliary dyskinesia, for which causative genes have been previously identified. Family-based genome analysis enabled us to narrow the candidate genes for both of these Mendelian disorders to only four. Our results demonstrate the value of complete genome sequencing in families.

Detailed transcriptome atlas of the pancreatic beta cell.

BACKGROUND: Gene expression patterns provide a detailed view of cellular functions. Comparison of profiles in disease vs normal conditions provides insights into the processes underlying disease progression. However, availability and integration of public gene expression datasets remains a major challenge. The aim of the present study was to explore the transcriptome of pancreatic islets and, based on this information, to prepare a comprehensive and open access inventory of insulin-producing beta cell gene expression, the Beta Cell Gene Atlas (BCGA). METHODS: We performed Massively Parallel Signature Sequencing (MPSS) analysis of human pancreatic islet samples and microarray analyses of purified rat beta cells, alpha cells and INS-1 cells, and compared the information with available array data in the literature. RESULTS: MPSS analysis detected around 7600 mRNA transcripts, of which around a third were of low abundance. We identified 2000 and 1400 transcripts that are enriched/depleted in beta cells compared to alpha cells and INS-1 cells, respectively. Microarray analysis identified around 200 transcription factors that are differentially expressed in either beta or alpha cells. We reanalyzed publicly available gene expression data and integrated these results with the new data from this study to build the BCGA. The BCGA contains basal (untreated conditions) gene expression level estimates in beta cells as well as in different cell types in human, rat and mouse pancreas. Hierarchical clustering of expression profile estimates classify cell types based on species while beta cells were clustered together. CONCLUSION: Our gene atlas is a valuable source for detailed information on the gene expression distribution in beta cells and pancreatic islets along with insulin producing cell lines. The BCGA tool, as well as the data and code used to generate the Atlas are available at the T1Dbase website (T1DBase.org).