The metabolome 18 years on: a concept comes of age.

Metabolomics. 2016;12(9):148

Authors: Kell DB, Oliver SG

Abstract
BACKGROUND: The term 'metabolome' was introduced to the scientific literature in September 1998.
AIM AND KEY SCIENTIFIC CONCEPTS OF THE REVIEW: To mark its 18-year-old 'coming of age', two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.

PMID: 27695392 [PubMed - in process]

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

Database (Oxford). 2016;2016:

Authors: Madan S, Hodapp S, Senger P, Ansari S, Szostak J, Hoeng J, Peitsch M, Fluck J

Abstract
Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/.

PMID: 27694210 [PubMed - in process]

Uncoupling of mucosal gene regulation, mRNA splicing and adherent microbiota signatures in inflammatory bowel disease.

Gut. 2016 Sep 30;:

Authors: Häsler R, Sheibani-Tezerji R, Sinha A, Barann M, Rehman A, Esser D, Aden K, Knecht C, Brandt B, Nikolaus S, Schäuble S, Kaleta C, Franke A, Fretter C, Müller W, Hütt MT, Krawczak M, Schreiber S, Rosenstiel P

Abstract
OBJECTIVE: An inadequate host response to the intestinal microbiota likely contributes to the manifestation and progression of human inflammatory bowel disease (IBD). However, molecular approaches to unravelling the nature of the defective crosstalk and its consequences for intestinal metabolic and immunological networks are lacking. We assessed the mucosal transcript levels, splicing architecture and mucosa-attached microbial communities of patients with IBD to obtain a comprehensive view of the underlying, hitherto poorly characterised interactions, and how these are altered in IBD.
DESIGN: Mucosal biopsies from Crohn's disease and patients with UC, disease controls and healthy individuals (n=63) were subjected to microbiome, transcriptome and splicing analysis, employing next-generation sequencing. The three data levels were integrated by different bioinformatic approaches, including systems biology-inspired network and pathway analysis.
RESULTS: Microbiota, host transcript levels and host splicing patterns were influenced most strongly by tissue differences, followed by the effect of inflammation. Both factors point towards a substantial disease-related alteration of metabolic processes. We also observed a strong enrichment of splicing events in inflamed tissues, accompanied by an alteration of the mucosa-attached bacterial taxa. Finally, we noted a striking uncoupling of the three molecular entities when moving from healthy individuals via disease controls to patients with IBD.
CONCLUSIONS: Our results provide strong evidence that the interplay between microbiome and host transcriptome, which normally characterises a state of intestinal homeostasis, is drastically perturbed in Crohn's disease and UC. Consequently, integrating multiple OMICs levels appears to be a promising approach to further disentangle the complexity of IBD.

PMID: 27694142 [PubMed - as supplied by publisher]

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

Database (Oxford). 2016;2016:

Authors: Madan S, Hodapp S, Senger P, Ansari S, Szostak J, Hoeng J, Peitsch M, Fluck J

Abstract
Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/.

PMID: 27694210 [PubMed - in process]

Data Mining of Web-Based Documents on Social Networking Sites That Included Suicide-Related Words Among Korean Adolescents.

J Adolesc Health. 2016 Sep 29;:

Authors: Song J, Song TM, Seo DC, Jin JH

Abstract
PURPOSE: To investigate online search activity of suicide-related words in South Korean adolescents through data mining of social media Web sites as the suicide rate in South Korea is one of the highest in the world.
METHODS: Out of more than 2.35 billion posts for 2 years from January 1, 2011 to December 31, 2012 on 163 social media Web sites in South Korea, 99,693 suicide-related documents were retrieved by Crawler and analyzed using text mining and opinion mining. These data were further combined with monthly employment rate, monthly rental prices index, monthly youth suicide rate, and monthly number of reported bully victims to fit multilevel models as well as structural equation models.
RESULTS: The link from grade pressure to suicide risk showed the largest standardized path coefficient (beta = .357, p < .001) in structural models and a significant random effect (p < .01) in multilevel models. Depression was a partial mediator between suicide risk and grade pressure, low body image, victims of bullying, and concerns about disease. The largest total effect was observed in the grade pressure to depression to suicide risk. The multilevel models indicate about 27% of the variance in the daily suicide-related word search activity is explained by month-to-month variations. A lower employment rate, a higher rental prices index, and more bullying were associated with an increased suicide-related word search activity.
CONCLUSIONS: Academic pressure appears to be the biggest contributor to Korean adolescents' suicide risk. Real-time suicide-related word search activity monitoring and response system needs to be developed.

PMID: 27693129 [PubMed - as supplied by publisher]

Sentiment prediction by text mining medical documents using optimized swarm search-based feature selection.

Comput Med Imaging Graph. 2016 Aug 5;:

Authors: Zeng D, Peng J, Fong S, Qiu Y, Wong R, Mon YJ

Abstract
Sentiment prediction emerged as an important machine learning topic to gain insights from unstructured texts, recently gained popularity in health-care industries. Text mining has long been a fundamental data analytic for sentiment prediction. A popular pre-processing step in text mining is transforming text strings to word vectors which form a high-dimensional sparse matrix. This sparse matrix poses computational challenges to induction of accurate sentiment prediction model. Feature selection has been a popular dimensionality reduction technique that finds a subset of features from all the original features from the sparse matrix, in order to enhance the accuracy of the prediction model. In this paper, a new feature selection method called Optimized Swarm Search-based Feature Selection (OSS-FS) is applied. OSS-FS is a swarm-type of searching function that selects an ideal subset of features for enhanced classification accuracy. The swarm search in OSS-FS is optimized by a simple feature evaluation technique called Clustering-by-Coefficient-of-Variation (CCV). The proposed scheme is applied and verified via a case scenario where 279 medical articles related to 'meaningful use functionalities on health care quality, safety, and efficiency' from a systematic review of the health IT literature from January 2010 to August 2013. A multi-class of sentiments, positive, mixed-positive, neutral and negative would have to be recognized from the document contents, by computer using text mining. The results show superiority of OSS-FS over the traditional feature selection methods. The proposed sentiment prediction model will be useful for estimating the sentiments of the readers from some medical literatures. Authors may gauge the potential sentiments of their articles before they get published out.

PMID: 27693005 [PubMed - as supplied by publisher]

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In silico frameworks for systematic pre-clinical screening of potential anti-leukemia therapeutics.

Expert Opin Drug Discov. 2016 Sep 30;

Authors: Ung MH, Varn FS, Cheng C

Abstract
INTRODUCTION: Leukemia is a collection of highly heterogeneous cancers that arise from neoplastic transformation and clonal expansion of immature hematopoietic cells. Post-treatment recurrence is high, especially among elderly patients, thus necessitating more effective treatment modalities. Development of novel anti-leukemic compounds relies heavily on traditional in vitro screens which require extensive resources and time. Therefore, integration of in silico screens prior to experimental validation can improve the efficiency of pre-clinical drug development.
AREAS COVERED: This article reviews different methods and frameworks used to computationally screen for anti-leukemic agents. In particular, three approaches are discussed including molecular docking, transcriptomic integration, and network analysis.
EXPERT OPINION: Today's data deluge presents novel opportunities to develop computational tools and pipelines to screen for likely therapeutic candidates in the treatment of leukemia. Formal integration of these methodologies can accelerate and improve the efficiency of modern day anti-leukemic drug discovery and ease the economic and healthcare burden associated with it.

PMID: 27689915 [PubMed - as supplied by publisher]

Repurposing N,N'-bis-(arylamidino)-1,4-piperazinedicarboxamidines: An unexpected class of potent inhibitors of cholinesterases.

Eur J Med Chem. 2016 Sep 19;125:430-434

Authors: Loesche A, Wiese J, Sommerwerk S, Simon V, Brandt W, Csuk R

Abstract
Drug repurposing (=drug repositioning) is an effective way to cut costs for the development of new therapeutics and to reduce the time-to-market time-span. Following this concept a small library of compounds was screened for their ability to act as inhibitors of acetyl- and butyrylcholinesterase. Picloxydine, an established antiseptic, was shown to be an inhibitor for both enzymes. Systematic variation of the aryl substituents led to analogs possessing almost the same good properties as gold standard galantamine hydrobromide.

PMID: 27689726 [PubMed - as supplied by publisher]

Case-specific potentiation of glioblastoma drugs by pterostilbene.

Oncotarget. 2016 Sep 28;

Authors: Schmidt L, Baskaran S, Johansson P, Padhan N, Matuszewski D, Green LC, Elfineh L, Wee S, Häggblad M, Martens U, Westermark B, Forsberg-Nilsson K, Uhrbom L, Claesson-Welsh L, Andäng M, Sintorn IM, Lundgren B, Lönnstedt I, Krona C, Nelander S

Abstract
Glioblastoma multiforme (GBM, astrocytoma grade IV) is the most common malignant primary brain tumor in adults. Addressing the shortage of effective treatment options for this cancer, we explored repurposing of existing drugs into combinations with potent activity against GBM cells. We report that the phytoalexin pterostilbene is a potentiator of two drugs with previously reported anti-GBM activity, the EGFR inhibitor gefitinib and the antidepressant sertraline. Combinations of either of these two compounds with pterostilbene suppress cell growth, viability, sphere formation and inhibit migration in tumor GBM cell (GC) cultures. The potentiating effect of pterostilbene was observed to a varying degree across a panel of 41 patient-derived GCs, and correlated in a case specific manner with the presence of missense mutation of EGFR and PIK3CA and a focal deletion of the chromosomal region 1p32. We identify pterostilbene-induced cell cycle arrest, synergistic inhibition of MAPK activity and induction of Thioredoxin interacting protein (TXNIP) as possible mechanisms behind pterostilbene's effect. Our results highlight a nontoxic stilbenoid compound as a modulator of anticancer drug response, and indicate that pterostilbene might be used to modulate two anticancer compounds in well-defined sets of GBM patients.

PMID: 27689322 [PubMed - as supplied by publisher]

A Real-Time Web of Things Framework with Customizable Openness Considering Legacy Devices.

Sensors (Basel). 2016;16(10)

Authors: Zhao S, Yu L, Cheng B

Abstract
With the development of the Internet of Things (IoT), resources and applications based on it have emerged on a large scale. However, most efforts are "silo" solutions where devices and applications are tightly coupled. Infrastructures are needed to connect sensors to the Internet, open up and break the current application silos and move to a horizontal application mode. Based on the concept of Web of Things (WoT), many infrastructures have been proposed to integrate the physical world with the Web. However, issues such as no real-time guarantee, lack of fine-grained control of data, and the absence of explicit solutions for integrating heterogeneous legacy devices, hinder their widespread and practical use. To address these issues, this paper proposes a WoT resource framework that provides the infrastructures for the customizable openness and sharing of users' data and resources under the premise of ensuring the real-time behavior of their own applications. The proposed framework is validated by actual systems and experimental evaluations.

PMID: 27690038 [PubMed - as supplied by publisher]

Standardized data collection to build prediction models in oncology: a prototype for rectal cancer.

Future Oncol. 2016 Jan;12(1):119-36

Authors: Meldolesi E, van Soest J, Damiani A, Dekker A, Alitto AR, Campitelli M, Dinapoli N, Gatta R, Gambacorta MA, Lanzotti V, Lambin P, Valentini V

Abstract
The advances in diagnostic and treatment technology are responsible for a remarkable transformation in the internal medicine concept with the establishment of a new idea of personalized medicine. Inter- and intra-patient tumor heterogeneity and the clinical outcome and/or treatment's toxicity's complexity, justify the effort to develop predictive models from decision support systems. However, the number of evaluated variables coming from multiple disciplines: oncology, computer science, bioinformatics, statistics, genomics, imaging, among others could be very large thus making traditional statistical analysis difficult to exploit. Automated data-mining processes and machine learning approaches can be a solution to organize the massive amount of data, trying to unravel important interaction. The purpose of this paper is to describe the strategy to collect and analyze data properly for decision support and introduce the concept of an 'umbrella protocol' within the framework of 'rapid learning healthcare'.

PMID: 26674745 [PubMed - indexed for MEDLINE]

K-Ras and its inhibitors towards personalized cancer treatment: Pharmacological and structural perspectives.

Eur J Med Chem. 2016 Sep 16;125:299-314

Authors: Asati V, Mahapatra DK, Bharti SK

Abstract
The discovery of genetic, genomic and clinical biomarkers have revolutionized the treatment option in the form of personalized medicine which allows to accurately predict a person's susceptibility/progression of disease, the patient's response to therapy, and maximize the therapeutic outcome in terms of low/no toxicity for a particular patient. Recently, the U.S. Food and Drug Administration has realized the contribution of pharmacogenomics in better healthcare and advocated the consideration of pharmacogenomic principles in making safer and more effective drug. Many anticancer drugs show reduced or no response in cancer patients with tumor specific gene mutations such as B-Raf and K-Ras. The high incidence of K-Ras mutation has been reported in pancreatic, colon, and lung carcinomas. The identification of K-Ras as a clinical biomarker and potential therapeutic target has attracted the scientific community to develop effective and precise anticancer drug. Inhibitors which block farnesylation of Ras have been developed or under clinical trial studies. Tipifarnib, approved by USFDA for the treatment of elderly acute leukemia is a Ras pathway inhibitor. Some peptidomimetics and bi-substrate inhibitors like FTI 276, FTI 277, B956, B1086, L731, L735, L739, L750, BMS-214662, L778123, and L778123 are under clinical trials. Recently mutant K-Ras has been considered as potential biomarker and target for precise cancer therapy. This review focuses primarily on the Ras/Raf/MEK/ERK signaling pathway including K-Ras mutation as therapeutic target, inhibitors and their structure activity relationships (SARs) for the design and development of anticancer agents.

PMID: 27688185 [PubMed - as supplied by publisher]

Japonica array: improved genotype imputation by designing a population-specific SNP array with 1070 Japanese individuals.

J Hum Genet. 2015 Oct;60(10):581-7

Authors: Kawai Y, Mimori T, Kojima K, Nariai N, Danjoh I, Saito R, Yasuda J, Yamamoto M, Nagasaki M

Abstract
The Tohoku Medical Megabank Organization constructed the reference panel (referred to as the 1KJPN panel), which contains >20 million single nucleotide polymorphisms (SNPs), from whole-genome sequence data from 1070 Japanese individuals. The 1KJPN panel contains the largest number of haplotypes of Japanese ancestry to date. Here, from the 1KJPN panel, we designed a novel custom-made SNP array, named the Japonica array, which is suitable for whole-genome imputation of Japanese individuals. The array contains 659,253 SNPs, including tag SNPs for imputation, SNPs of Y chromosome and mitochondria, and SNPs related to previously reported genome-wide association studies and pharmacogenomics. The Japonica array provides better imputation performance for Japanese individuals than the existing commercially available SNP arrays with both the 1KJPN panel and the International 1000 genomes project panel. For common SNPs (minor allele frequency (MAF)>5%), the genomic coverage of the Japonica array (r(2)>0.8) was 96.9%, that is, almost all common SNPs were covered by this array. Nonetheless, the coverage of low-frequency SNPs (0.5%<MAF⩽5%) of the Japonica array reached 67.2%, which is higher than those of the existing arrays. In addition, we confirmed the high quality genotyping performance of the Japonica array using the 288 samples in 1KJPN; the average call rate 99.7% and the average concordance rate 99.7% to the genotypes obtained from high-throughput sequencer. As demonstrated in this study, the creation of custom-made SNP arrays based on a population-specific reference panel is a practical way to facilitate further association studies through genome-wide genotype imputations.

PMID: 26108142 [PubMed - indexed for MEDLINE]

Oral Supplementation with a Special Additive of Retinyl Palmitate and Alpha Tocopherol Reduces Growth Retardation in Young Pancreatic Duct Ligated Pigs Used as a Model for Children Suffering from Exocrine Pancreatic Insufficiency.

Int J Mol Sci. 2016;17(10)

Authors: Mößeler A, Schmicke M, Höltershinken M, Beyerbach M, Kamphues J

Abstract
Pancreatic exocrine insufficiency (PEI) is a disease of diverse aetiology-e.g., majority of patients suffering from cystic fibrosis (CF) show PEI congenitally. Malnutrition and malabsorption of nutrients impair growth and nutritional status. As reduced fat digestion leads to a deficiency of fat-soluble vitamins the supplementation is standard, but absorption is a critical point in PEI-patients. The pancreatic duct ligated (PL) pig is an established model for PEI in humans and has been proven to be a suitable model to compare different vitamin additives for supplementation. In a former study, PEI caused distinct growth retardation in young piglets, but did not affect growth in older ones. Our study hypothesised that this age-dependent effect is caused by exhausted body reserves of fat-soluble vitamins and, therefore, extra supply reduces growth retardation. PEI was induced by PL at the age of seven (PL-7) or 16 weeks (PL-16). Controls (C) underwent a sham surgery. Some PL-7 pigs (PL-7 + Vit) were fed a special vitamin additive. PEI reduced the mean final body weight (kg) at 26 weeks of age significantly with lower effect in PL-16-pigs (C:117; PL-7:49.5; PL-7 + Vit:77.1; PL-16:96.4). Extra vitamin supply resulted in an increased growth and normalised serum concentration of alpha-tocopherol, underlining the importance of special supplementation in PEI-patients.

PMID: 27690005 [PubMed - as supplied by publisher]

Of Pigs, Mice, and Men: Understanding Early Triggers of Cystic Fibrosis Lung Disease.

Am J Respir Crit Care Med. 2016 Oct 1;194(7):784-785

Authors: Stick SM, Kicic A, Ranganathan S

PMID: 27689703 [PubMed - as supplied by publisher]

miR-146a, miR-155, miR-370 and miR-708 are CFTR-dependent, Predicted FOXO1 Regulators and Change at Onset of CFRDs.

J Clin Endocrinol Metab. 2016 Sep 30;:jc20162431

Authors: Montanini L, Smerieri A, Gullì M, Cirillo F, Pisi G, Sartori C, Amarri S, Bernasconi S, Marmiroli N, Street ME

Abstract
CONTEXT: Cystic Fibrosis Related Diabetes (CFRD) is the most frequent and severe co-morbidity in CF. Presentation and severity are quite variable.
OBJECTIVE: To investigate changes in miRNAs due to CFTR malfunctioning in vitro and to study the circulating levels of selected miRNAs in serum samples from patients, and assess their relationships in different age-groups with genotype, glucose tolerance state and at onset of CFRD. Design/Setting/Patients/Interventions: Transcriptional profiling of all known miRNAs in CFBE41o- cells, in their normal counterparts (16HBE14o- cells), and in IB3 cells was performed. A set of miRNAs was differentially expressed in the CF cells. By in silico analysis four microRNAs (miR-146a; miR-155; miR-370; miR-708) were selected as potential regulators of the FOXO1 gene. Seventy-four CF patients and fifty healthy subjects whose glucose tolerance was characterized by an OGTT were enrolled in the study, and the identified miRNAs were quantified in serum by quantitative RT-PCR. Main Outcome Measurements /Results: 111 miRNAs were differentially expressed in the two CF cell lines. miR-155, miR-370, miR-708 were upregulated and miR-146a downregulated in vitro, whereas in vivo, miR-146a, miR-155 and miR-370 were upregulated, and miR-708 was downregulated. These changes showed relationships with genotype, glucose tolerance state and onset of CFRD.
CONCLUSIONS: The data showed significant changes in miRNAs dependent on genotype and glucose tolerance state in CF patients, and highlighted some miRNAs of importance in CFRD at onset. MiRNAs could explain some of the variability observed in cystic fibrosis.

PMID: 27689251 [PubMed - as supplied by publisher]

Population pharmacokinetics of mycophenolic acid and its glucuronide metabolite in lung transplant recipients with and without cystic fibrosis.

Xenobiotica. 2016 Aug 10;:1-8

Authors: Wang XX, Liu W, Zheng T, Park JM, Smith DE, Feng MR

Abstract
1. Cystic fibrosis (CF) is a disease affecting multiple organs that may reduce the systemic exposure of some drugs. The objective of this work was to characterize and compare the population pharmacokinetics (PK) of the immunosuppressant mycophenolic acid (MPA), and its glucuronide metabolite (MPAG) in adult lung transplant recipients with and without CF (NCF) following repeated oral administration of the prodrug mycophenolate mofetil (MMF). 2. A population PK model was developed, with simultaneous modeling of MPA and MPAG, using nonlinear mixed effects modeling. MPA and MPAG serum concentration-time data were adequately described by a compartmental model including enterohepatic recirculation (EHR). Both MPA and MPAG apparent clearance values were significantly elevated (>65%) in patients with CF (24.1 and 1.95 L/h, respectively) compared to the values in the NCF patients (14.5 and 1.12 L/h, respectively), suggesting a notable influence of CF on MPA absorption and disposition. 3. The population PK model developed from our study successfully characterized the absorption, distribution, elimination and EHR of MPA and the metabolite MPAG in lung transplant recipients with or without CF. This model may help to further understand the impact of CF to the overall clinical effects of MPA therapy including immunosuppression and gastrointestinal side effects.

PMID: 27686146 [PubMed - as supplied by publisher]

Pharmacovigilance implemented by patients: A necessity in the 21st century.

Therapie. 2016 Apr;71(2):245-7

Authors: Lafond J

Abstract
Pharmacovigilance should become a well-thought-out reflex for each of us, for any drugs taken on prescription or by self-medication. The issue of pharmacovigilance should naturally take its place in the dialogue between patients and health professionals, through advice given before medication is taken. Patients need to be told the importance of notifying any adverse drug reactions (ADRs). Pharmacovigilance would then become a post-hoc way of protecting patients. The importance of using pharmacovigilance should be promoted by emphasizing the fact that the life of a drug really starts after its marketing. This state of mind could be reinforced by a wider advertising campaign on the possibility of notifying the relevant authorities of any ADRs. Patient associations should encourage and help their members to do this. Notifying any ADRs should become a concern for all medical and paramedical staff: those who prescribe drugs, those who dispense them (pharmacists or pharmacy assistants), those who administer them (nurses), but also the consumers (patients) whose place is becoming more and more prominent.

PMID: 27080846 [PubMed - indexed for MEDLINE]

Hepatotoxicity prediction by systems biology modeling of disturbed metabolic pathways using gene expression data.

ALTEX. 2016 Sep 30;

Authors: Carbonell P, Lopez O, Amberg A, Pastor M, Sanz F

Abstract
The present study applies a systems biology approach for the in silico predictive modeling of drug toxicity on the basis of high-quality preclinical drug toxicity data with the aim of increasing the mechanistic understanding of toxic effects of compounds at different levels (pathway, cell, tissue, organ). The model development has been carried out using 77 compounds for which gene expression data are available in the LINCS database for primary human hepatocytes treated with the compounds, as well as rodent in vivo hepatotoxicity information is available in the eTOX database. The data from LINCS were used in a systems biology approach to determine the type and number of pathways disturbed by each compound, and to estimate the extent of disturbance (network perturbation elasticity), analyzing the correspondence with the in vivo information from eTOX. Predictive models were developed through this integrative analysis, and their specificity and sensitivity were assessed. The quality of the predictions was determined on the basis of the area under the curve (AUC) of plots of true positive vs. false positive rates (ROC curves). The ROC AUC reached values of up to 0.9 (out of 1.0) for some hepatotoxicity endpoints. Moreover, the most frequently disturbed metabolic pathways were determined across the studied toxicants. They included e.g. mitochondrial beta-oxidation of fatty acids and amino acid metabolism. The process was exemplified by successful predictions on various statins. In conclusion, an entirely new approach linking gene expression alterations to the prediction of complex organ toxicity has been developed and evaluated.

PMID: 27690270 [PubMed - as supplied by publisher]