Use Base SAS FILENAME URL to Build Surveillance and Monitoring System for New Clinical Trial Registration

ABSTRACT Clinical trial is an irreplaceable approach to test the efficacy and safety of new drugs in human subjects. In recent years, the number of clinical trials sponsored by pharmaceutical industry, federal government or non-profit organizations has been rapidly increasing to develop new therapeutics for the unmet medical needs. Currently, Clinicaltrial.gov, the central repository for clinical trial registration developed by the national institute of health (NIH) and Food and Drug Administration (FDA), holds 80, 268 trials conducted in many nations and this database is expanding on the daily basis. To obtain the latest information on trials of interest require constantly checking the website, which may be time and labor consuming. It would be beneficial to patients, regulators and trial sponsors to have an automated data pipeline that extracts the latest data from registered trials by dynamically fetching the contents of on-line information in a pre-scheduled time frame. Here we demonstrate how to use base SAS® filename URL method to mine the data from Clinicaltrials.gov on real time. In addition, we also discuss how to launch a batch SAS task in a pre-define schedule and set up an email alert system to deliver the new findings to customer in a timely fashion. Throughout this paper, we demonstrate these utilities and functionalities with an example of reporting a new trial conducted in China sponsored by a big pharmaceutical company

Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo

Myostatin inhibition prevents skeletal muscle pathophysiology in Huntington's disease mice

Huntington's disease (HD) is an inherited neurodegenerative disorder of which skeletal muscle atrophy is a common feature, and multiple lines of evidence support a muscle-based pathophysiology in HD mouse models. Inhibition of myostatin signaling increases muscle mass, and therapeutic approaches based on this are in clinical development. We have used a soluble ActRIIB decoy receptor (ACVR2B/Fc) to test the effects of myostatin/activin A inhibition in the R6/2 mouse model of HD. Weekly administration from 5 to 11 weeks of age prevented body weight loss, skeletal muscle atrophy, muscle weakness, contractile abnormalities, the loss of functional motor units in EDL muscles and delayed end-stage disease. Inhibition of myostatin/activin A signaling activated transcriptional profiles to increase muscle mass in wild type and R6/2 mice but did little to modulate the extensive Huntington's disease-associated transcriptional dysregulation, consistent with treatment having little impact on HTT aggregation levels. Modalities that inhibit myostatin signaling are currently in clinical trials for a variety of indications, the outcomes of which will present the opportunity to assess the potential benefits of targeting this pathway in HD patients.</p

Transcriptional regulatory networks underlying gene expression changes in Huntington's disease

Abstract Transcriptional changes occur presymptomatically and throughout Huntington's disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD. We reconstructed a genome‐scale model for the target genes of 718 transcription factors (TFs) in the mouse striatum by integrating a model of genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF‐target gene modules associated with age‐ and CAG repeat length‐dependent gene expression changes in Htt CAG knock‐in mouse striatum and replicated many of these associations in independent transcriptomic and proteomic datasets. Thirteen of 48 of these predicted TF‐target gene modules were also differentially expressed in striatal tissue from human disease. We experimentally validated a specific model prediction that SMAD3 regulates HD‐related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP‐seq) of mouse striatum. We found CAG repeat length‐dependent changes in the genomic occupancy of SMAD3 and confirmed our model's prediction that many SMAD3 target genes are downregulated early in HD

JCSDA/crtm: v2.4.0_emc.3 fixes logic bug in internal version checking of SpcCoeff files

What's Changed Update SpcCoeff_Binary_IO.f90 by @ADCollard in https://github.com/JCSDA/crtm/pull/43 rollup fixes and features for release/REL-2.4.0_emc by @BenjaminTJohnson in https://github.com/JCSDA/crtm/pull/42 New Contributors @ADCollard made their first contribution in https://github.com/JCSDA/crtm/pull/43 Full Changelog: https://github.com/JCSDA/crtm/compare/v2.4.0_emc.2...v2.4.0_emc.

Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

International audienceBACKGROUND:MicroRNA (miRNA) regulation is associated with several diseases, including neurodegenerative diseases. Several approaches can be used for modeling miRNA regulation. However, their precision may be limited for analyzing multidimensional data. Here, we addressed this question by integrating shape analysis and feature selection into miRAMINT, a methodology that we used for analyzing multidimensional RNA-seq and proteomic data from a knock-in mouse model (Hdh mice) of Huntington's disease (HD), a disease caused by CAG repeat expansion in huntingtin (htt). This dataset covers 6 CAG repeat alleles and 3 age points in the striatum and cortex of Hdh mice.RESULTS:Remarkably, compared to previous analyzes of this multidimensional dataset, the miRAMINT approach retained only 31 explanatory striatal miRNA-mRNA pairs that are precisely associated with the shape of CAG repeat dependence over time, among which 5 pairs with a strong change of target expression levels. Several of these pairs were previously associated with neuronal homeostasis or HD pathogenesis, or both. Such miRNA-mRNA pairs were not detected in cortex.CONCLUSIONS:These data suggest that miRNA regulation has a limited global role in HD while providing accurately-selected miRNA-target pairs to study how the brain may compute molecular responses to HD over time. These data also provide a methodological framework for researchers to explore how shape analysis can enhance multidimensional data analytics in biology and disease

Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

Abstract Background MicroRNA (miRNA) regulation is associated with several diseases, including neurodegenerative diseases. Several approaches can be used for modeling miRNA regulation. However, their precision may be limited for analyzing multidimensional data. Here, we addressed this question by integrating shape analysis and feature selection into miRAMINT, a methodology that we used for analyzing multidimensional RNA-seq and proteomic data from a knock-in mouse model (Hdh mice) of Huntington’s disease (HD), a disease caused by CAG repeat expansion in huntingtin (htt). This dataset covers 6 CAG repeat alleles and 3 age points in the striatum and cortex of Hdh mice. Results Remarkably, compared to previous analyzes of this multidimensional dataset, the miRAMINT approach retained only 31 explanatory striatal miRNA-mRNA pairs that are precisely associated with the shape of CAG repeat dependence over time, among which 5 pairs with a strong change of target expression levels. Several of these pairs were previously associated with neuronal homeostasis or HD pathogenesis, or both. Such miRNA-mRNA pairs were not detected in cortex. Conclusions These data suggest that miRNA regulation has a limited global role in HD while providing accurately-selected miRNA-target pairs to study how the brain may compute molecular responses to HD over time. These data also provide a methodological framework for researchers to explore how shape analysis can enhance multidimensional data analytics in biology and disease. </jats:sec

Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

AbstractBackgroundMicroRNA (miRNA) regulation is associated with several diseases, including neurodegenerative diseases. Several approaches can be used for modeling miRNA regulation. However, their precision may be limited for analyzing multidimensional data. Here, we addressed this question by integrating shape analysis and feature selection into miRAMINT, a methodology that we used for analyzing multidimensional RNA-seq and proteomic data from a knock-in mouse model (Hdh mice) of Huntington’s disease (HD), a disease caused by CAG repeat expansion in huntingtin (htt). This dataset covers 6 CAG repeat alleles and 3 age points in the striatum and cortex of Hdh mice.ResultsRemarkably, compared to previous analyzes of this multidimensional dataset, the miRAMINT approach retained only 31 explanatory striatal miRNA-mRNA pairs that are precisely associated with the shape of CAG repeat dependence over time, among which 5 pairs with a strong change of target expression levels. Several of these pairs were previously associated with neuronal homeostasis or HD pathogenesis, or both. Such miRNA-mRNA pairs were not detected in cortex.ConclusionsThese data suggest that miRNA regulation has a limited global role in HD while providing accurately-selected miRNA-target pairs to study how the brain may compute molecular responses to HD over time. These data also provide a methodological framework for researchers to explore how shape analysis can enhance multidimensional data analytics in biology and disease.</jats:sec

Expression analysis of Huntington disease mouse models reveals robust striatum disease signatures

AbstractHuntington’s disease is caused by expanded trinucleotide repeats in the huntingtin gene (HTT), and a higher number of repeats is associated with an earlier age of disease onset. Although the causative gene has been identified, its connections to the observed disease phenotypes is still unclear. Mouse models engineered to contain increasing numbers of trinucleotide repeats were sacrificed at different ages to detect RNA-level and protein-level changes specific to each repeat length and age in order to examine the transcriptional and translational characteristics of the disease. RNA-seq and quantitative proteomics data were collected on 14 types of tissues at up to 8 repeat lengths and in up to 3 different ages, and differential gene and protein expression were examined. A modified method of imputing missing proteomics data was employed and is described here. The most dysregulated tissue at both the RNA and protein levels was the striatum, and a strong gender effect was observed in all of the liver experiments. The full differential expression results are available to the research community on the HDinHD.org website. The results of multiple expression tests in the striatum were combined to generate an RNA disease signature and a protein disease signature, and the signatures were validated in external data sets. These signatures represent molecular readouts of disease progression in HD mice, which further characterizes their HD-related phenotype and can be useful in the preclinical evaluation of candidate therapeutic interventions.Author SummaryMouse models of Huntington’s disease were engineered to allow a detailed examination of how the disease causes changes in gene activity in a variety of tissues. Among the 14 tissues studied, the one most affected by the disease in our experiments was the striatum, a brain region involved in voluntary movement. The liver results showed large differences in gene activity between the male and female mice. In our analysis, we propose a minor change in how proteomics data is typically analyzed in order to improve the ranking of significant results. Using the striatum data in this study and in others, we identified robust genetic signatures of disease at both the RNA and protein levels.</jats:sec

Additional file 1 of Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

Additional file 1: Table S1. Lists of nodes in miRNA and mRNA WGCNA modules. Module membership is indicated for mRNAs and miRNAs. NA, not applicable