Literature Watch
Discordant congenital Zika syndrome twins show differential in vitro viral susceptibility of neural progenitor cells.
Discordant congenital Zika syndrome twins show differential in vitro viral susceptibility of neural progenitor cells.
Nat Commun. 2018 02 02;9(1):475
Authors: Caires-Júnior LC, Goulart E, Melo US, Araujo BSH, Alvizi L, Soares-Schanoski A, de Oliveira DF, Kobayashi GS, Griesi-Oliveira K, Musso CM, Amaral MS, daSilva LF, Astray RM, Suárez-Patiño SF, Ventini DC, Gomes da Silva S, Yamamoto GL, Ezquina S, Naslavsky MS, Telles-Silva KA, Weinmann K, van der Linden V, van der Linden H, de Oliveira JMR, Arrais NRM, Melo A, Figueiredo T, Santos S, Meira JCG, Passos SD, de Almeida RP, Bispo AJB, Cavalheiro EA, Kalil J, Cunha-Neto E, Nakaya H, Andreata-Santos R, de Souza Ferreira LC, Verjovski-Almeida S, Ho PL, Passos-Bueno MR, Zatz M
Abstract
Congenital Zika syndrome (CZS) causes early brain development impairment by affecting neural progenitor cells (NPCs). Here, we analyze NPCs from three pairs of dizygotic twins discordant for CZS. We compare by RNA-Seq the NPCs derived from CZS-affected and CZS-unaffected twins. Prior to Zika virus (ZIKV) infection the NPCs from CZS babies show a significantly different gene expression signature of mTOR and Wnt pathway regulators, key to a neurodevelopmental program. Following ZIKV in vitro infection, cells from affected individuals have significantly higher ZIKV replication and reduced cell growth. Whole-exome analysis in 18 affected CZS babies as compared to 5 unaffected twins and 609 controls excludes a monogenic model to explain resistance or increased susceptibility to CZS development. Overall, our results indicate that CZS is not a stochastic event and depends on NPC intrinsic susceptibility, possibly related to oligogenic and/or epigenetic mechanisms.
PMID: 29396410 [PubMed - indexed for MEDLINE]
Whole exome sequencing in neurogenetic odysseys: An effective, cost- and time-saving diagnostic approach.
Whole exome sequencing in neurogenetic odysseys: An effective, cost- and time-saving diagnostic approach.
PLoS One. 2018;13(2):e0191228
Authors: Córdoba M, Rodriguez-Quiroga SA, Vega PA, Salinas V, Perez-Maturo J, Amartino H, Vásquez-Dusefante C, Medina N, González-Morón D, Kauffman MA
Abstract
BACKGROUND: Diagnostic trajectories for neurogenetic disorders frequently require the use of considerable time and resources, exposing patients and families to so-called "diagnostic odysseys". Previous studies have provided strong evidence for increased diagnostic and clinical utility of whole-exome sequencing in medical genetics. However, specific reports assessing its utility in a setting such as ours- a neurogeneticist led academic group serving in a low-income country-are rare.
OBJECTIVES: To assess the diagnostic yield of WES in patients suspected of having a neurogenetic condition and explore the cost-effectiveness of its implementation in a research group located in an Argentinean public hospital.
METHODS: This is a prospective study of the clinical utility of WES in a series of 40 consecutive patients selected from a Neurogenetic Clinic of a tertiary Hospital in Argentina. We evaluated patients retrospectively for previous diagnostic trajectories. Diagnostic yield, clinical impact on management and economic diagnostic burden were evaluated.
RESULTS: We demonstrated the clinical utility of Whole Exome Sequencing in our patient cohort, obtaining a diagnostic yield of 40% (95% CI, 24.8%-55.2%) among a diverse group of neurological disorders. The average age at the time of WES was 23 (range 3-70). The mean time elapsed from symptom onset to WES was 11 years (range 3-42). The mean cost of the diagnostic workup prior to WES was USD 1646 (USD 1439 to 1853), which is 60% higher than WES cost in our center.
CONCLUSIONS: WES for neurogenetics proved to be an effective, cost- and time-saving approach for the molecular diagnosis of this heterogeneous and complex group of patients.
PMID: 29389947 [PubMed - indexed for MEDLINE]
Genetics of Schizophrenia: Ready to Translate?
Genetics of Schizophrenia: Ready to Translate?
Curr Psychiatry Rep. 2017 Sep;19(9):61
Authors: Foley C, Corvin A, Nakagome S
Abstract
PURPOSE OF REVIEW: This is an era where we have significantly advanced the understanding of the genetic architecture of schizophrenia. In this review, we consider how this knowledge may translate into advances that will improve patient care.
RECENT FINDINGS: Large-scale genome-wide association studies (GWAS) have identified more than a hundred loci each making a small contribution to illness risk. Meta-analysis of copy number variants (CNVs) in the Psychiatric Genomics Consortium (PGC) dataset has confirmed that some variants have a moderate or large impact on risk, although these are rare in the population. Genome sequencing advances allow a much more comprehensive evaluation of genomic variation. We describe the key findings from whole exome studies to date. These studies are happening against a backdrop of growing understanding of the regulation and expression of genes and better functional tools to investigate molecular mechanisms in model systems. We provide an overview of how recent approaches in schizophrenia genetics are converging and consider how they could impact on diagnostics, the development of personalized medicine, and drug discovery.
PMID: 28741255 [PubMed - indexed for MEDLINE]
NIDCD Research Dissertation Fellowship for Au.D. Audiologists (F32) (Clinical Trials Not Allowed)
Notice of NIAMS Withdrawal from Participation in PAR-18-289 "Exploratory/Developmental Surgical Disparities Research (R21 Clinical Trial Optional)"
Notice of NIAMS Withdrawal from Participation in PAR-18-288 "Surgical Disparities Research (R01 Clinical Trial Optional)"
Notice of NIEHS' Participation in PA-18-676, "Research on the Health of Women of Understudied, Underrepresented and Underreported (U3) Populations - An ORWH FY18 Administrative Supplement (Admin Supp Clinical Trial Optional)"
Correction to Fellowship Administrative Supplement Package Associated with PA-18-591 "Administrative Supplements to Existing NIH Grants and Cooperative Agreements"
Notice of NIDCR's Participation in PA-17-460 "Biology of Lung, and Head and Neck Preneoplasias (R21- Clinical Trial Not Allowed)"
Notice of NIDCR's Participation in PA-17-459 "Biology of Lung, and Head and Neck Preneoplasias (R01- Clinical Trial Not Allowed)"
Notice of Pre-Application Webinar for: RFA-AR-19-001, NIAMS Skin Biology and Diseases Resource-based Centers (P30 - Clinical Trial Not Allowed), and RFA-AR-19-002, "NIAMS Musculoskeletal Biology and Medicine"
Notice to Clarify that Revision Applications are Prohibited under PAR-18-663 "Mind and Body Intervention Multi-Site Clinical Trial Data Coordinating Center (Collaborative U24 Clinical Trial Required)"
FY2018 - AHRQ to begin allowing Facilities and Administrative (F and A) costs of 8% MTDC for consortia located at foreign institutions
Update in Purpose Section of PAR-15-187 - Enhancing Regulatory Science for the Risk Based Assessment of Emerging Manufacturing Program
"systems biology"; +25 new citations
25 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:
These pubmed results were generated on 2018/03/13
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.
("drug-induced" OR "drug-related") AND ("adverse events" OR "side effects" OR "side-effects"); +15 new citations
15 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:
("drug-induced" OR "drug-related") AND ("adverse events" OR "side effects" OR "side-effects")
These pubmed results were generated on 2018/03/13
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.
Notice of NIDA's participation in PAR-18-694 "Interdisciplinary Research Teams to Investigate Reciprocal Basic Behavioral and Social Linkages Between Sleep and Stress (R24 - Clinical Trial Optional)"
Additional Awards Eligible for PA-18-586 Research Supplements to Promote Diversity in Health-Related Research (Admin Supp)
CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds.
CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds.
PLoS One. 2018;13(1):e0191838
Authors: Lagunin AA, Dubovskaja VI, Rudik AV, Pogodin PV, Druzhilovskiy DS, Gloriozova TA, Filimonov DA, Sastry NG, Poroikov VV
Abstract
In silico methods of phenotypic screening are necessary to reduce the time and cost of the experimental in vivo screening of anticancer agents through dozens of millions of natural and synthetic chemical compounds. We used the previously developed PASS (Prediction of Activity Spectra for Substances) algorithm to create and validate the classification SAR models for predicting the cytotoxicity of chemicals against different types of human cell lines using ChEMBL experimental data. A training set from 59,882 structures of compounds was created based on the experimental data (IG50, IC50, and % inhibition values) from ChEMBL. The average accuracy of prediction (AUC) calculated by leave-one-out and a 20-fold cross-validation procedure during the training was 0.930 and 0.927 for 278 cancer cell lines, respectively, and 0.948 and 0.947 for cytotoxicity prediction for 27 normal cell lines, respectively. Using the given SAR models, we developed a freely available web-service for cell-line cytotoxicity profile prediction (CLC-Pred: Cell-Line Cytotoxicity Predictor) based on the following structural formula: http://way2drug.com/Cell-line/.
PMID: 29370280 [PubMed - indexed for MEDLINE]
Prediction of Novel Drugs for Hepatocellular Carcinoma Based on Multi-Source Random Walk.
Prediction of Novel Drugs for Hepatocellular Carcinoma Based on Multi-Source Random Walk.
IEEE/ACM Trans Comput Biol Bioinform. 2017 Jul-Aug;14(4):966-977
Authors: Yu L, Su R, Wang B, Zhang L, Zou Y, Zhang J, Gao L
Abstract
Computational approaches for predicting drug-disease associations by integrating gene expression and biological network provide great insights to the complex relationships among drugs, targets, disease genes, and diseases at a system level. Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a high rate of morbidity and mortality. We provide an integrative framework to predict novel d rugs for HCC based on multi-source random walk (PD-MRW). Firstly, based on gene expression and protein interaction network, we construct a gene-gene weighted i nteraction network (GWIN). Then, based on multi-source random walk in GWIN, we build a drug-drug similarity network. Finally, based on the known drugs for HCC, we score all drugs in the drug-drug similarity network. The robustness of our predictions, their overlap with those reported in Comparative Toxicogenomics Database (CTD) and literatures, and their enriched KEGG pathway demonstrate our approach can effectively identify new drug indications. Specifically, regorafenib (Rank = 9 in top-20 list) is proven to be effective in Phase I and II clinical trials of HCC, and the Phase III trial is ongoing. And, it has 11 overlapping pathways with HCC with lower p-values. Focusing on a particular disease, we believe our approach is more accurate and possesses better scalability.
PMID: 27076463 [PubMed - indexed for MEDLINE]
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