Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes Mellitus.

Diabetes Care. 2017 Jan 11;:

Authors: Mayer G, Heerspink HJ, Aschauer C, Heinzel A, Heinze G, Kainz A, Sunzenauer J, Perco P, de Zeeuw D, Rossing P, Pena M, Oberbauer R, SYSKID Consortium

Abstract
OBJECTIVE: Chronic kidney disease (CKD) in diabetes has a complex molecular and likely multifaceted pathophysiology. We aimed to validate a panel of biomarkers identified using a systems biology approach to predict the individual decline of estimated glomerular filtration rate (eGFR) in a large group of patients with type 2 diabetes mellitus and CKD at various stages.
RESEARCH DESIGN AND METHODS: We used publicly available "omics" data to develop a molecular process model of CKD in diabetes and identified a representative parsimonious set of nine molecular biomarkers: chitinase 3-like protein 1, growth hormone 1, hepatocyte growth factor, matrix metalloproteinase (MMP) 2, MMP7, MMP8, MMP13, tyrosine kinase, and tumor necrosis factor receptor-1. These biomarkers were measured in baseline serum samples from 1,765 patients recruited into two large clinical trials. eGFR decline was predicted based on molecular markers, clinical risk factors (including baseline eGFR and albuminuria), and both combined, and these predictions were evaluated using mixed linear regression models for longitudinal data.
RESULTS: The variability of annual eGFR loss explained by the biomarkers, indicated by the adjusted R(2) value, was 15% and 34% for patients with eGFR ≥60 and <60 mL/min/1.73 m(2), respectively; variability explained by clinical predictors was 20% and 31%, respectively. A combination of molecular and clinical predictors increased the adjusted R(2) to 35% and 64%, respectively. Calibration analysis of marker models showed significant (all P < 0.0001) but largely irrelevant deviations from optimal calibration (calibration-in-the-large: -1.125 and 0.95; calibration slopes: 1.07 and 1.13 in the two groups, respectively).
CONCLUSIONS: A small set of serum protein biomarkers identified using a systems biology approach, combined with clinical variables, enhances the prediction of renal function loss over a wide range of baseline eGFR values in patients with type 2 diabetes mellitus and CKD.

PMID: 28077457 [PubMed - as supplied by publisher]

The BioC-BioGRID corpus: full text articles annotated for curation of protein-protein and genetic interactions.

Database (Oxford). 2017;2017:

Authors: Islamaj Doğan R, Kim S, Chatr-Aryamontri A, Chang CS, Oughtred R, Rust J, Wilbur WJ, Comeau DC, Dolinski K, Tyers M

Abstract
A great deal of information on the molecular genetics and biochemistry of model organisms has been reported in the scientific literature. However, this data is typically described in free text form and is not readily amenable to computational analyses. To this end, the BioGRID database systematically curates the biomedical literature for genetic and protein interaction data. This data is provided in a standardized computationally tractable format and includes structured annotation of experimental evidence. BioGRID curation necessarily involves substantial human effort by expert curators who must read each publication to extract the relevant information. Computational text-mining methods offer the potential to augment and accelerate manual curation. To facilitate the development of practical text-mining strategies, a new challenge was organized in BioCreative V for the BioC task, the collaborative Biocurator Assistant Task. This was a non-competitive, cooperative task in which the participants worked together to build BioC-compatible modules into an integrated pipeline to assist BioGRID curators. As an integral part of this task, a test collection of full text articles was developed that contained both biological entity annotations (gene/protein and organism/species) and molecular interaction annotations (protein-protein and genetic interactions (PPIs and GIs)). This collection, which we call the BioC-BioGRID corpus, was annotated by four BioGRID curators over three rounds of annotation and contains 120 full text articles curated in a dataset representing two major model organisms, namely budding yeast and human. The BioC-BioGRID corpus contains annotations for 6409 mentions of genes and their Entrez Gene IDs, 186 mentions of organism names and their NCBI Taxonomy IDs, 1867 mentions of PPIs and 701 annotations of PPI experimental evidence statements, 856 mentions of GIs and 399 annotations of GI evidence statements. The purpose, characteristics and possible future uses of the BioC-BioGRID corpus are detailed in this report.Database URL: http://bioc.sourceforge.net/BioC-BioGRID.html.

PMID: 28077563 [PubMed - in process]

Correction: A Network-Based Data Integration Approach to Support Drug Repurposing and Multi-Target Therapies in Triple Negative Breast Cancer.

PLoS One. 2017;12(1):e0170363

Authors: Vitali F, Cohen LD, Demartini A, Amato A, Eterno V, Zambelli A, Bellazzi R

Abstract
[This corrects the article DOI: 10.1371/journal.pone.0162407.].

PMID: 28076436 [PubMed - in process]

Construction of an miRNA-regulated drug-pathway network reveals drug repurposing candidates for myasthenia gravis.

Int J Mol Med. 2017 Jan 11;:

Authors: Cao Y, Lu X, Wang J, Zhang H, Liu Z, Xu S, Wang T, Ning S, Xiao B, Wang L

Abstract
Myasthenia gravis (MG) is a rare debilitating autoimmune neuromuscular disorder. Many studies have focused on the mechanism and treatment strategies of MG. However, the exact pathogenesis of MG and effective treatment strategies remain unclear. Recent studies have indicated that microRNAs (miRNAs or miRs) can regulate the pathological pathways of MG, suggesting their potential role in novel treatments. In the present study, we created a comprehensive catalog of experimentally confirmed MG risk genes and miRNAs by manually mining published literature and public databases. Based on these genes and miRNAs, we identified 41 MG risk pathways and 105 approved drugs that can affect these pathways. Some important MG-related pathways, such as hsa04060 (cytokine-cytokine receptor interaction) and hsa05200 (pathway in cancer), were found to be regulated by MG risk miRNAs and drugs. Furthermore, we constructed an miRNA-regulated drug-pathway network and identified miRNAs and drugs that synergistically regulate key MG pathways and biological processes. We developed a drug repurposing strategy to identify 25 drug repurposing candidates for MG; several of these drugs, such as rituximab, adalimumab, sunitinib, and muromonab, have the potential to be novel MG treatment drugs. This study provides novel insight into the pathogenesis of MG and potential drug candidates for MG were identified.

PMID: 28075449 [PubMed - as supplied by publisher]

Engaging Hmong adults in genomic and pharmacogenomic research: Toward reducing health disparities in genomic knowledge using a community-based participatory research approach.

J Community Genet. 2017 Jan 10;:

Authors: Culhane-Pera KA, Straka RJ, Moua M, Roman Y, Vue P, Xiaaj K, Lo MX, Lor M

Abstract
Advancing precision medicine relies in part on examining populations that may exhibit unique genetic variants that impact clinical outcomes. Failure to include diverse populations in genomic-based research represents a health disparity. We implemented a community-based participatory research (CBPR) process with the Hmong community in Minnesota, who were refugees from Laos, in order to assess the feasibility of conducting genomic and pharmacogenomic-based research for genetic variants that are relevant to the Hmong community. Our Hmong Genomics Board, consisting of Hmong and non-Hmong professionals, used CBPR principles and built on previous formative research to create and implement culturally and linguistically appropriate informed consent processes for Hmong people at six community venues. The Board chose genetic variants for diabetes risk and warfarin response as relevant to the community. The Institutional Review Board approved aggregate but not individual return of results. Two hundred thirty-seven Hmong participants with mean (range) age of 30.2 (18-81) years and diverse levels of education (22% without and 75% with high-school education) provided saliva for genetic (DNA) analyses. Eighty-five percent of participants agreed to store DNA for future analyses, 82% agreed to share DNA with other researchers, and 78% agreed to be contacted for future studies. Twenty-five elders refused to participate because they wanted individual results. Aggregate results were shared with all participants. This CBPR approach proved highly successful to obtain informed consent and recruit a sample from the Hmong community for a genomic and pharmacogenomic study. Investment in the CBPR process may prove successful to address the gap of genomic information in under-represented communities.

PMID: 28074382 [PubMed - as supplied by publisher]

Genomic information on multidrug-resistant livestock-associated methicillin-resistant Staphylococcus aureus ST398 isolated from a Brazilian patient with cystic fibrosis.

Mem Inst Oswaldo Cruz. 2017 Jan 01;112(1):79-80

Authors: Lima DF, Cohen RW, Rocha GA, Albano RM, Marques EA, Leão RS

Abstract
Alarmingly, the isolation of methicillin-resistant Staphylococcus aureus (MRSA) has been increasing among patients with cystic fibrosis (CF). During a previous molecular characterisation of MRSA isolates obtained from patients with CF from Rio de Janeiro, Brazil, one isolate was identified as the ST398 clone, a livestock-associated (LA) MRSA. In this study, we report the draft genome sequence of an LA-MRSA ST398 clone isolated from a patient with CF.

PMID: 28076471 [PubMed - in process]

Hospitalization rates for intussusception in children aged 0-59 months from 2009 to 2014 in Italy.

Hum Vaccin Immunother. 2017 Jan 11;:1-5

Authors: Restivo V, Costantino C, Tramuto F, Vitale F

Abstract
The real cause of intussusception is not fully understood and a variety of conditions have been associated with it (Meckel diverticulum, polyps, duplication cysts, parasites, Henoch-Schönlein purpura, cystic fibrosis, hemolytic-uremic syndrome and infectious gastroenteritis). Furthermore few European countries, following WHO recommendation to monitor baseline incidence of intussusception before implementation of immunization program for rotavirus, used intussusception rate as a baseline value to compare the same figures in the period before and after introduction of vaccination. In this study, data of intussusception hospitalizations occurred among Italian children aged 0 through 59 months from 2009 to 2014 were analyzed. A total amount of 3,088 children were included, accounting for a hospitalization rate of 20.2 per 100,000. Overall, the hospitalization rate for intussusception had a slight increase in trend from 2009 to 2014 (18%). In particular children 0-11 months had a hospitalization rate higher than 12-59 months with an aggregate value of 36 Vs. 16 per 100,000 respectively. Among all children hospitalized for intussusception a total of 239 (7.7%) had also a previous or concomitant hospitalization for gastroenteritis. This study demonstrates that Italian hospitalizations for intussusception are increasing by time and the role played by different risk factors, including acute gastroenteritis, have to be investigated in the future. These data could be useful to monitor intussusception hospitalization in the perspective of anti-rotavirus vaccination introduction in Italy.

PMID: 28075671 [PubMed - as supplied by publisher]

Role of IRE1α/XBP-1 in Cystic Fibrosis Airway Inflammation.

Int J Mol Sci. 2017 Jan 09;18(1):

Authors: Ribeiro CM, Lubamba BA

Abstract
Cystic fibrosis (CF) pulmonary disease is characterized by chronic airway infection and inflammation. The infectious and inflamed CF airway environment impacts on the innate defense of airway epithelia and airway macrophages. The CF airway milieu induces an adaptation in these cells characterized by increased basal inflammation and a robust inflammatory response to inflammatory mediators. Recent studies have indicated that these responses depend on activation of the unfolded protein response (UPR). This review discusses the contribution of airway epithelia and airway macrophages to CF airway inflammatory responses and specifically highlights the functional importance of the UPR pathway mediated by IRE1/XBP-1 in these processes. These findings suggest that targeting the IRE1/XBP-1 UPR pathway may be a therapeutic strategy for CF airway disease.

PMID: 28075361 [PubMed - in process]

Azoospermic patient's treatment: An experience of a PMA hospital unit and role of ultrasonography.

Arch Ital Urol Androl. 2016 Dec 30;88(4):314-316

Authors: Panella P, Pepe P, Borzì P, Vento ME, Pennisi M, Scollo P

Abstract
INTRODUCTION: Azoospermia causes about 10% of male infertility and the best therapeutic option is the retrieval of sperm from testis or epididymis.
MATERIAL AND METHODS: From Juanary 2008 to June 2016, 92 men (median 36 years; range: 25-54 years) were submitted in 47 cases to TESE (testicular sperm extraction) and in 45 cases to PESA (percutaneous epididymal sperm aspiration) for secretory and obstructive azoospermia, respectively; moreover, all the patients previously underwent color Doppler ultrasound of the testis and transrectal ultrasound of the prostate.
RESULTS: Serum FSH values were 9.4 ml/UI and 36.4 ml/UI (median 18.2 ml/UI) with an estimated volume of the testis equal to 5 ml; 40 men had the mutation for cystic fibrosis with bilateral agenesis of the deferentia vasa, 4 men had a cyst of the prostatic utricle, 1 man had retrograde ejaculation, 7 had an epididymis cyst and 2 had anejaculation secondary to traumatic neurologic spinal cord injury. The retrieval of sperm was performed in 39 (83%) and 36 (80%) of the patients submitted to TESE and PESA, respectively. The pregnancy rate was equal to 28% and 33% in men with secretory and obstructive azoospermia, respectively.
DISCUSSION: Assisted reproduction technology with a multidisciplinary team is provided of a pregnancy rate equal about 30% in men with azoospermia; ultrasound allows to evaluate abnormalities of the testis and prostate improving the percentage of pregnancy.

PMID: 28073201 [PubMed - in process]

Cell assemblies at multiple time scales with arbitrary lag constellations.

Elife. 2017 Jan 11;6:

Authors: Russo E, Durstewitz D

Abstract
Hebb's idea of a cell assembly as the fundamental unit of neural information processing has dominated neuroscience like no other theoretical concept within the past 60 years. A range of different physiological phenomena, from precisely synchronized spiking to broadly simultaneous rate increases, has been subsumed under this term. Yet progress in this area is hampered by the lack of statistical tools that would enable to extract assemblies with arbitrary constellations of time lags, and at multiple temporal scales, partly due to the severe computational burden. Here we present such a unifying methodological and conceptual framework which detects assembly structure at many different time scales, levels of precision, and with arbitrary internal organization. Applying this methodology to multiple single unit recordings from various cortical areas, we find that there is no universal cortical coding scheme, but that assembly structure and precision significantly depends on the brain area recorded and ongoing task demands.

PMID: 28074777 [PubMed - in process]

Advanced Boolean modeling of biological networks applied to systems pharmacology.

Bioinformatics. 2017 Jan 10;:

Authors: Irurzun-Arana I, Pastor JM, Trocóniz IF, Gómez-Mantilla JD

Abstract
MOTIVATION: Literature on complex diseases is abundant but not always quantitative. Many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. Tools for analysis of discrete networks are useful to capture the available information in the literature but have not been efficiently integrated by the pharmaceutical industry. We propose an expansion of the usual analysis of discrete networks that facilitates the identification/validation of therapeutic targets.
RESULTS: In this article, we propose a methodology to perform Boolean modeling of Systems Biology/Pharmacology networks by using SPIDDOR (Systems Pharmacology for effIcient Drug Development On R) R package. The resulting models can be used to analyze the dynamics of signaling networks associated to diseases to predict the pathogenesis mechanisms and identify potential therapeutic targets.
AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/SPIDDOR/SPIDDOR CONTACT: itzirurzun@alumni.unav.es, itroconiz@unav.esSupplementary information: Supplementary data are available at Bioinformatics online.

PMID: 28073755 [PubMed - as supplied by publisher]

Unsupervised Topic Modeling in a Large Free Text Radiology Report Repository.

J Digit Imaging. 2016 Feb;29(1):59-62

Authors: Hassanpour S, Langlotz CP

Abstract
Radiology report narrative contains a large amount of information about the patient's health and the radiologist's interpretation of medical findings. Most of this critical information is entered in free text format, even when structured radiology report templates are used. The radiology report narrative varies in use of terminology and language among different radiologists and organizations. The free text format and the subtlety and variations of natural language hinder the extraction of reusable information from radiology reports for decision support, quality improvement, and biomedical research. Therefore, as the first step to organize and extract the information content in a large multi-institutional free text radiology report repository, we have designed and developed an unsupervised machine learning approach to capture the main concepts in a radiology report repository and partition the reports based on their main foci. In this approach, radiology reports are modeled in a vector space and compared to each other through a cosine similarity measure. This similarity is used to cluster radiology reports and identify the repository's underlying topics. We applied our approach on a repository of 1,899,482 radiology reports from three major healthcare organizations. Our method identified 19 major radiology report topics in the repository and clustered the reports accordingly to these topics. Our results are verified by a domain expert radiologist and successfully explain the repository's primary topics and extract the corresponding reports. The results of our system provide a target-based corpus and framework for information extraction and retrieval systems for radiology reports.

PMID: 26353748 [PubMed - indexed for MEDLINE]

Bias in the reporting of sex and age in biomedical research on mouse models.

Elife. 2016 Mar 03;5:

Authors: Flórez-Vargas O, Brass A, Karystianis G, Bramhall M, Stevens R, Cruickshank S, Nenadic G

Abstract
In animal-based biomedical research, both the sex and the age of the animals studied affect disease phenotypes by modifying their susceptibility, presentation and response to treatment. The accurate reporting of experimental methods and materials, including the sex and age of animals, is essential so that other researchers can build on the results of such studies. Here we use text mining to study 15,311 research papers in which mice were the focus of the study. We find that the percentage of papers reporting the sex and age of mice has increased over the past two decades: however, only about 50% of the papers published in 2014 reported these two variables. We also compared the quality of reporting in six preclinical research areas and found evidence for different levels of sex-bias in these areas: the strongest male-bias was observed in cardiovascular disease models and the strongest female-bias was found in infectious disease models. These results demonstrate the ability of text mining to contribute to the ongoing debate about the reproducibility of research, and confirm the need to continue efforts to improve the reporting of experimental methods and materials.

PMID: 26939790 [PubMed - indexed for MEDLINE]

8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Rare Diseases"[Mesh] OR "orphan disease"

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7 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"cystic fibrosis"

These pubmed results were generated on 2017/01/11

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

A review of connectivity map and computational approaches in pharmacogenomics.

Brief Bioinform. 2017 Jan 09;:

Authors: Musa A, Ghoraie LS, Zhang SD, Galzko G, Yli-Harja O, Dehmer M, Haibe-Kains B, Emmert-Streib F

Abstract
Large-scale perturbation databases, such as Connectivity Map (CMap) or Library of Integrated Network-based Cellular Signatures (LINCS), provide enormous opportunities for computational pharmacogenomics and drug design. A reason for this is that in contrast to classical pharmacology focusing at one target at a time, the transcriptomics profiles provided by CMap and LINCS open the door for systems biology approaches on the pathway and network level. In this article, we provide a review of recent developments in computational pharmacogenomics with respect to CMap and LINCS and related applications.

PMID: 28069634 [PubMed - as supplied by publisher]

Gene editing and genetic engineering approaches for advanced probiotics: A Review.

Crit Rev Food Sci Nutr. 2017 Jan 10;:0

Authors: Yadav R, Kumar V, Baweja M, Shukla P

Abstract
The applications of probiotics are significant and thus resulted in need of genome analysis of probiotic strains. Various omics methods and systems biology approaches enables us to understand and optimize the metabolic processes. These techniques have increased the researcher's attention towards gut microbiome and provided a new source for the revelation of uncharacterized biosynthetic pathways which enables novel metabolic engineering approaches. In recent years, the broad and quantitative analysis of modified strains relies on systems biology tools such as in silico design which are commonly used methods for improving strain performance. The genetic manipulation of probiotic microorganisms is crucial for defining their role in intestinal microbiota and exploring their beneficial properties. This review describes an overview of gene editing and system biology approaches, highlighting the advent of omics methods which allows the study of new routes for studying probiotic bacteria. We have also summarized gene editing tools like TALEN, ZFNs and CRISPR-Cas that edits or cleave the specific target DNA. Furthermore, in this review an overview of proposed design of advanced customized probiotic is also hypothesized to improvise the probiotics.

PMID: 28071925 [PubMed - as supplied by publisher]

Elucidating the modes of action for bioactive compounds in a cell-specific manner by large-scale chemically-induced transcriptomics.

Sci Rep. 2017 Jan 10;7:40164

Authors: Iwata M, Sawada R, Iwata H, Kotera M, Yamanishi Y

Abstract
The identification of the modes of action of bioactive compounds is a major challenge in chemical systems biology of diseases. Genome-wide expression profiling of transcriptional responses to compound treatment for human cell lines is a promising unbiased approach for the mode-of-action analysis. Here we developed a novel approach to elucidate the modes of action of bioactive compounds in a cell-specific manner using large-scale chemically-induced transcriptome data acquired from the Library of Integrated Network-based Cellular Signatures (LINCS), and analyzed 16,268 compounds and 68 human cell lines. First, we performed pathway enrichment analyses of regulated genes to reveal active pathways among 163 biological pathways. Next, we explored potential target proteins (including primary targets and off-targets) with cell-specific transcriptional similarity using chemical-protein interactome. Finally, we predicted new therapeutic indications for 461 diseases based on the target proteins. We showed the usefulness of the proposed approach in terms of prediction coverage, interpretation, and large-scale applicability, and validated the new prediction results experimentally by an in vitro cellular assay. The approach has a high potential for advancing drug discovery and repositioning.

PMID: 28071740 [PubMed - in process]

A review of connectivity map and computational approaches in pharmacogenomics.

Brief Bioinform. 2017 Jan 09;:

Authors: Musa A, Ghoraie LS, Zhang SD, Galzko G, Yli-Harja O, Dehmer M, Haibe-Kains B, Emmert-Streib F

Abstract
Large-scale perturbation databases, such as Connectivity Map (CMap) or Library of Integrated Network-based Cellular Signatures (LINCS), provide enormous opportunities for computational pharmacogenomics and drug design. A reason for this is that in contrast to classical pharmacology focusing at one target at a time, the transcriptomics profiles provided by CMap and LINCS open the door for systems biology approaches on the pathway and network level. In this article, we provide a review of recent developments in computational pharmacogenomics with respect to CMap and LINCS and related applications.

PMID: 28069634 [PubMed - as supplied by publisher]

Multi-level evaluation of Escherichia coli polyphosphate related mutants using global transcriptomic, proteomic and phenomic analyses.

Biochim Biophys Acta. 2017 Jan 06;:

Authors: Varas M, Valdivieso C, Mauriaca C, Ortíz-Severín J, Paradela A, Poblete-Castro I, Cabrera R, Chávez FP

Abstract
BACKGROUND: Polyphosphate (polyP) is a linear biopolymer found in all living cells. In bacteria, mutants lacking polyphosphate kinase 1 (PPK1), the enzyme responsible for synthesis of most polyP, have many structural and functional defects. However, little is known about the causes of these pleiotropic alterations. The link between ppk1 deletion and those numerous phenotypes observed can be the result of complex molecular interactions that can be elucidated via a systems biology approach.
METHODS: By integrating different omics levels (transcriptome, proteome and phenome), we described the functioning of various metabolic pathways among Escherichia coli polyphosphate mutant strains (Δppk1, Δppx, and ΔpolyP). Bioinformatic analyses reveal the complex metabolic and regulatory bases of the phenotypes unique to polyP mutants.
RESULTS: Our results suggest that during polyP deficiency (Δppk1 mutant), metabolic pathways needed for energy supply are up-regulated, including fermentation, aerobic and anaerobic respiration. Transcriptomic and q-proteomic contrasting changes between Δppk1 and Δppx mutant strains were observed in those central metabolic pathways and confirmed by using Phenotypic microarrays. In addition, our results suggest a regulatory connection between polyP, second messenger metabolism, alternative Sigma/Anti-Sigma factors and type-II toxin-antitoxin (TA) systems.
CONCLUSIONS: We suggest a broader role for polyP via regulation of ATP-dependent proteolysis of type II toxin-antitoxin system and alternative Sigma/Anti-Sigma factors, that could explain the multiple structural and functional deficiencies described due to alteration of polyP metabolism.
GENERAL SIGNIFICANCE: Understanding the interplay of polyP in bacterial metabolism using a systems biology approach can help to improve design of novel antimicrobials toward pathogens.

PMID: 28069396 [PubMed - as supplied by publisher]