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  1. AU=Hodos Rachel A
  2. AU="Sahin, Kazim"
  3. AU="Bieri, Jan"
  4. AU="Procter-Murphy, R"
  5. AU=Hauguel-Moreau Marie
  6. AU="Cheng, Delfine"
  7. AU="Stephanie C. Pennington"
  8. AU="O'Hanlon, Karen A"
  9. AU="Heide Glaesmer"
  10. AU="Paget-Bailly, Philippe"
  11. AU="Rory J McCrimmon"
  12. AU="Ahdoot, Aaron I."
  13. AU="Neote, Kuldeep S"
  14. AU="Shen, Congcong"
  15. AU="Rahi, Kosar"
  16. AU="Channabasavaiah, Jagadish Puralae"
  17. AU="Anselmi, Maurizio"
  18. AU="Chauhan, D."
  19. AU="Nicoll, Roger A"
  20. AU="Kwon, Young-Sam"
  21. AU="Mihwa Lee"
  22. AU="Yuanting Jin"
  23. AU="Ter Haar, Eva"
  24. AU="Wolin, Dan L"
  25. AU="Zhang, Tenan"
  26. AU="Piedrafita, Lídia"
  27. AU="Nandy, Ananya"
  28. AU="Bansemer, Sven"
  29. AU="Kochetov, O"
  30. AU="Liu, Fen"

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  1. Artikel ; Online: Integrative genomic meta-analysis reveals novel molecular insights into cystic fibrosis and ΔF508-CFTR rescue.

    Hodos, Rachel A / Strub, Matthew D / Ramachandran, Shyam / Li, Li / McCray, Paul B / Dudley, Joel T

    Scientific reports

    2020  Band 10, Heft 1, Seite(n) 20553

    Abstract: Cystic fibrosis (CF), caused by mutations to CFTR, leads to severe and progressive lung disease. The most common mutant, ΔF508-CFTR, undergoes proteasomal degradation, extinguishing its anion channel function. Numerous in vitro interventions have been ... ...

    Abstract Cystic fibrosis (CF), caused by mutations to CFTR, leads to severe and progressive lung disease. The most common mutant, ΔF508-CFTR, undergoes proteasomal degradation, extinguishing its anion channel function. Numerous in vitro interventions have been identified to partially rescue ΔF508-CFTR function yet remain poorly understood. Improved understanding of both the altered state of CF cells and the mechanisms of existing rescue strategies could reveal novel therapeutic strategies. Toward this aim, we measured transcriptional profiles of established temperature, genetic, and chemical interventions that rescue ΔF508-CFTR and also re-analyzed public datasets characterizing transcription in human CF vs. non-CF samples from airway and whole blood. Meta-analysis yielded a core disease signature and two core rescue signatures. To interpret these through the lens of prior knowledge, we compiled a "CFTR Gene Set Library" from literature. The core disease signature revealed remarkably strong connections to genes with established effects on CFTR trafficking and function and suggested novel roles of EGR1 and SGK1 in the disease state. Our data also revealed an unexpected mechanistic link between several genetic rescue interventions and the unfolded protein response. Finally, we found that C18, an analog of the CFTR corrector compound Lumacaftor, induces almost no transcriptional perturbation despite its rescue activity.
    Mesh-Begriff(e) Bronchi/metabolism ; Cell Line ; Computational Biology/methods ; Cystic Fibrosis/genetics ; Cystic Fibrosis Transmembrane Conductance Regulator/genetics ; Databases, Genetic ; Gene Expression/genetics ; Gene Expression Profiling/methods ; Genomics/methods ; Humans ; Mutation ; Protein Transport/genetics ; Transcriptome/genetics
    Chemische Substanzen cystic fibrosis transmembrane conductance regulator delta F508 ; Cystic Fibrosis Transmembrane Conductance Regulator (126880-72-6)
    Sprache Englisch
    Erscheinungsdatum 2020-11-25
    Erscheinungsland England
    Dokumenttyp Journal Article ; Meta-Analysis ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-020-76347-0
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: Causal inference on electronic health records to assess blood pressure treatment targets: an application of the parametric g formula.

    Johnson, Kipp W / Glicksberg, Benjamin S / Hodos, Rachel A / Shameer, Khader / Dudley, Joel T

    Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

    2018  Band 23, Seite(n) 180–191

    Abstract: Hypertension is a major risk factor for ischemic cardiovascular disease and cerebrovascular disease, which are respectively the primary and secondary most common causes of morbidity and mortality across the globe. To alleviate the risks of hypertension, ... ...

    Abstract Hypertension is a major risk factor for ischemic cardiovascular disease and cerebrovascular disease, which are respectively the primary and secondary most common causes of morbidity and mortality across the globe. To alleviate the risks of hypertension, there are a number of effective antihypertensive drugs available. However, the optimal treatment blood pressure goal for antihypertensive therapy remains an area of controversy. The results of the recent Systolic Blood Pressure Intervention Trial (SPRINT) trial, which found benefits for intensive lowering of systolic blood pressure, have been debated for several reasons. We aimed to assess the benefits of treating to four different blood pressure targets and to compare our results to those of SPRINT using a method for causal inference called the parametric g formula. We applied this method to blood pressure measurements obtained from the electronic health records of approximately 200,000 patients who visited the Mount Sinai Hospital in New York, NY. We simulated the effect of four clinically relevant dynamic treatment regimes, assessing the effectiveness of treating to four different blood pressure targets: 150 mmHg, 140 mmHg, 130 mmHg, and 120 mmHg. In contrast to current American Heart Association guidelines and in concordance with SPRINT, we find that targeting 120 mmHg systolic blood pressure is significantly associated with decreased incidence of major adverse cardiovascular events. Causal inference methods applied to electronic methods are a powerful and flexible technique and medicine may benefit from their increased usage.
    Mesh-Begriff(e) Algorithms ; Antihypertensive Agents/therapeutic use ; Blood Pressure/drug effects ; Cardiovascular Diseases/prevention & control ; Causality ; Cerebrovascular Disorders/prevention & control ; Computational Biology/methods ; Computer Simulation ; Electronic Health Records/statistics & numerical data ; Humans ; Hypertension/complications ; Hypertension/drug therapy ; Hypertension/physiopathology ; Models, Statistical ; Monte Carlo Method ; Risk Factors ; Survival Analysis
    Chemische Substanzen Antihypertensive Agents
    Sprache Englisch
    Erscheinungsdatum 2018-02-15
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 2335-6936
    ISSN (online) 2335-6936
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Integrative chemogenomic analysis identifies small molecules that partially rescue ΔF508-CFTR for cystic fibrosis.

    Hodos, Rachel A / Strub, Matthew D / Ramachandran, Shyam / Meleshkevitch, Ella A / Boudko, Dmitri Y / Bridges, Robert J / Dudley, Joel T / McCray, Paul B

    CPT: pharmacometrics & systems pharmacology

    2021  Band 10, Heft 5, Seite(n) 500–510

    Abstract: Rare diseases affect 10% of the first-world population, yet over 95% lack even a single pharmaceutical treatment. In the present age of information, we need ways to leverage our vast data and knowledge to streamline therapeutic development and lessen ... ...

    Abstract Rare diseases affect 10% of the first-world population, yet over 95% lack even a single pharmaceutical treatment. In the present age of information, we need ways to leverage our vast data and knowledge to streamline therapeutic development and lessen this gap. Here, we develop and implement an innovative informatic approach to identify therapeutic molecules, using the Connectivity Map and LINCS L1000 databases and disease-associated transcriptional signatures and pathways. We apply this to cystic fibrosis (CF), the most common genetic disease in people of northern European ancestry leading to chronic lung disease and reduced lifespan. We selected and tested 120 small molecules in a CF cell line, finding 8 with activity, and confirmed 3 in primary CF airway epithelia. Although chemically diverse, the transcriptional profiles of the hits suggest a common mechanism associated with the unfolded protein response and/or TNFα signaling. This study highlights the power of informatics to help identify new therapies and reveal mechanistic insights while moving beyond target-centric drug discovery.
    Mesh-Begriff(e) Cystic Fibrosis/genetics ; Cystic Fibrosis Transmembrane Conductance Regulator/genetics ; Genomics ; Humans
    Chemische Substanzen cystic fibrosis transmembrane conductance regulator delta F508 ; Cystic Fibrosis Transmembrane Conductance Regulator (126880-72-6)
    Sprache Englisch
    Erscheinungsdatum 2021-05-02
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2697010-7
    ISSN 2163-8306 ; 2163-8306
    ISSN (online) 2163-8306
    ISSN 2163-8306
    DOI 10.1002/psp4.12626
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Integrative genomic meta-analysis reveals novel molecular insights into cystic fibrosis and ΔF508-CFTR rescue

    Rachel A. Hodos / Matthew D. Strub / Shyam Ramachandran / Li Li / Paul B. McCray / Joel T. Dudley

    Scientific Reports, Vol 10, Iss 1, Pp 1-

    2020  Band 16

    Abstract: Abstract Cystic fibrosis (CF), caused by mutations to CFTR, leads to severe and progressive lung disease. The most common mutant, ΔF508-CFTR, undergoes proteasomal degradation, extinguishing its anion channel function. Numerous in vitro interventions ... ...

    Abstract Abstract Cystic fibrosis (CF), caused by mutations to CFTR, leads to severe and progressive lung disease. The most common mutant, ΔF508-CFTR, undergoes proteasomal degradation, extinguishing its anion channel function. Numerous in vitro interventions have been identified to partially rescue ΔF508-CFTR function yet remain poorly understood. Improved understanding of both the altered state of CF cells and the mechanisms of existing rescue strategies could reveal novel therapeutic strategies. Toward this aim, we measured transcriptional profiles of established temperature, genetic, and chemical interventions that rescue ΔF508-CFTR and also re-analyzed public datasets characterizing transcription in human CF vs. non-CF samples from airway and whole blood. Meta-analysis yielded a core disease signature and two core rescue signatures. To interpret these through the lens of prior knowledge, we compiled a “CFTR Gene Set Library” from literature. The core disease signature revealed remarkably strong connections to genes with established effects on CFTR trafficking and function and suggested novel roles of EGR1 and SGK1 in the disease state. Our data also revealed an unexpected mechanistic link between several genetic rescue interventions and the unfolded protein response. Finally, we found that C18, an analog of the CFTR corrector compound Lumacaftor, induces almost no transcriptional perturbation despite its rescue activity.
    Schlagwörter Medicine ; R ; Science ; Q
    Thema/Rubrik (Code) 570
    Sprache Englisch
    Erscheinungsdatum 2020-11-01T00:00:00Z
    Verlag Nature Portfolio
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: In silico methods for drug repurposing and pharmacology.

    Hodos, Rachel A / Kidd, Brian A / Shameer, Khader / Readhead, Ben P / Dudley, Joel T

    Wiley interdisciplinary reviews. Systems biology and medicine

    2016  Band 8, Heft 3, Seite(n) 186–210

    Abstract: Data in the biological, chemical, and clinical domains are accumulating at ever-increasing rates and have the potential to accelerate and inform drug development in new ways. Challenges and opportunities now lie in developing analytic tools to transform ... ...

    Abstract Data in the biological, chemical, and clinical domains are accumulating at ever-increasing rates and have the potential to accelerate and inform drug development in new ways. Challenges and opportunities now lie in developing analytic tools to transform these often complex and heterogeneous data into testable hypotheses and actionable insights. This is the aim of computational pharmacology, which uses in silico techniques to better understand and predict how drugs affect biological systems, which can in turn improve clinical use, avoid unwanted side effects, and guide selection and development of better treatments. One exciting application of computational pharmacology is drug repurposing-finding new uses for existing drugs. Already yielding many promising candidates, this strategy has the potential to improve the efficiency of the drug development process and reach patient populations with previously unmet needs such as those with rare diseases. While current techniques in computational pharmacology and drug repurposing often focus on just a single data modality such as gene expression or drug-target interactions, we argue that methods such as matrix factorization that can integrate data within and across diverse data types have the potential to improve predictive performance and provide a fuller picture of a drug's pharmacological action. WIREs Syst Biol Med 2016, 8:186-210. doi: 10.1002/wsbm.1337 For further resources related to this article, please visit the WIREs website.
    Mesh-Begriff(e) Animals ; Databases, Factual ; Drug Interactions ; Drug Repositioning/economics ; Drug Repositioning/methods ; Drug-Related Side Effects and Adverse Reactions ; Gene Expression ; Humans ; Molecular Docking Simulation ; Pharmaceutical Preparations/chemistry ; Pharmaceutical Preparations/classification ; Pharmaceutical Preparations/metabolism ; Proteins/chemistry ; Proteins/genetics ; Proteins/metabolism
    Chemische Substanzen Pharmaceutical Preparations ; Proteins
    Sprache Englisch
    Erscheinungsdatum 2016-04-15
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Review
    ZDB-ID 2503323-2
    ISSN 1939-005X ; 1939-5094
    ISSN (online) 1939-005X
    ISSN 1939-5094
    DOI 10.1002/wsbm.1337
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel ; Online: Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning.

    Shameer, Khader / Glicksberg, Benjamin S / Hodos, Rachel / Johnson, Kipp W / Badgeley, Marcus A / Readhead, Ben / Tomlinson, Max S / O'Connor, Timothy / Miotto, Riccardo / Kidd, Brian A / Chen, Rong / Ma'ayan, Avi / Dudley, Joel T

    Briefings in bioinformatics

    2017  Band 19, Heft 4, Seite(n) 656–678

    Abstract: Increase in global population and growing disease burden due to the emergence of infectious diseases (Zika virus), multidrug-resistant pathogens, drug-resistant cancers (cisplatin-resistant ovarian cancer) and chronic diseases (arterial hypertension) ... ...

    Abstract Increase in global population and growing disease burden due to the emergence of infectious diseases (Zika virus), multidrug-resistant pathogens, drug-resistant cancers (cisplatin-resistant ovarian cancer) and chronic diseases (arterial hypertension) necessitate effective therapies to improve health outcomes. However, the rapid increase in drug development cost demands innovative and sustainable drug discovery approaches. Drug repositioning, the discovery of new or improved therapies by reevaluation of approved or investigational compounds, solves a significant gap in the public health setting and improves the productivity of drug development. As the number of drug repurposing investigations increases, a new opportunity has emerged to understand factors driving drug repositioning through systematic analyses of drugs, drug targets and associated disease indications. However, such analyses have so far been hampered by the lack of a centralized knowledgebase, benchmarking data sets and reporting standards. To address these knowledge and clinical needs, here, we present RepurposeDB, a collection of repurposed drugs, drug targets and diseases, which was assembled, indexed and annotated from public data. RepurposeDB combines information on 253 drugs [small molecules (74.30%) and protein drugs (25.29%)] and 1125 diseases. Using RepurposeDB data, we identified pharmacological (chemical descriptors, physicochemical features and absorption, distribution, metabolism, excretion and toxicity properties), biological (protein domains, functional process, molecular mechanisms and pathway cross talks) and epidemiological (shared genetic architectures, disease comorbidities and clinical phenotype similarities) factors mediating drug repositioning. Collectively, RepurposeDB is developed as the reference database for drug repositioning investigations. The pharmacological, biological and epidemiological principles of drug repositioning identified from the meta-analyses could augment therapeutic development.
    Mesh-Begriff(e) Computational Biology/methods ; Databases, Factual ; Disease ; Drug Discovery ; Drug Repositioning ; Humans ; Molecular Epidemiology ; Proteins/genetics ; Proteins/metabolism
    Chemische Substanzen Proteins
    Sprache Englisch
    Erscheinungsdatum 2017-02-13
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2068142-2
    ISSN 1477-4054 ; 1467-5463
    ISSN (online) 1477-4054
    ISSN 1467-5463
    DOI 10.1093/bib/bbw136
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Artikel ; Online: Cell-specific prediction and application of drug-induced gene expression profiles.

    Hodos, Rachel / Zhang, Ping / Lee, Hao-Chih / Duan, Qiaonan / Wang, Zichen / Clark, Neil R / Ma'ayan, Avi / Wang, Fei / Kidd, Brian / Hu, Jianying / Sontag, David / Dudley, Joel

    Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

    2017  Band 23, Seite(n) 32–43

    Abstract: Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to ...

    Abstract Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.
    Mesh-Begriff(e) Algorithms ; Cells/drug effects ; Cells/metabolism ; Computational Biology/methods ; Databases, Genetic ; Databases, Pharmaceutical ; Drug Discovery ; Drug Repositioning ; Gene Expression Profiling/statistics & numerical data ; Humans ; Transcriptome/drug effects
    Sprache Englisch
    Erscheinungsdatum 2017-12-07
    Erscheinungsland United States
    Dokumenttyp Evaluation Study ; Journal Article ; Validation Study
    ISSN 2335-6936
    ISSN (online) 2335-6936
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Artikel: L1000CDS

    Duan, Qiaonan / Reid, St Patrick / Clark, Neil R / Wang, Zichen / Fernandez, Nicolas F / Rouillard, Andrew D / Readhead, Ben / Tritsch, Sarah R / Hodos, Rachel / Hafner, Marc / Niepel, Mario / Sorger, Peter K / Dudley, Joel T / Bavari, Sina / Panchal, Rekha G / Ma'ayan, Avi

    NPJ systems biology and applications

    2016  Band 2

    Abstract: The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking ... ...

    Abstract The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS
    Sprache Englisch
    Erscheinungsdatum 2016
    Erscheinungsland England
    Dokumenttyp Journal Article
    ISSN 2056-7189
    ISSN 2056-7189
    DOI 10.1038/npjsba.2016.15
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel: An optimization approach for aerosol retrievals using simulated MISR radiances

    Diner, David J / Hodos, Rachel A / Davis, Anthony B / Garay, Michael J / Martonchik, John V / Sanghavi, Suniti V / von Allmen, Paul / Kokhanovsky, Alexander A / Zhai, Pengwang

    Atmospheric research. 2012 Oct. 15, v. 116

    2012  

    Abstract: Currently, many satellite-based aerosol retrievals make use of lookup tables (LUTs) containing precomputed solutions to the radiative transfer (RT) equation. The benefit of this strategy is the avoidance of expensive runtime calculations, but its main ... ...

    Abstract Currently, many satellite-based aerosol retrievals make use of lookup tables (LUTs) containing precomputed solutions to the radiative transfer (RT) equation. The benefit of this strategy is the avoidance of expensive runtime calculations, but its main drawback is that the LUTs discretize what is inherently a continuous, multivariate solution space. The operational retrieval algorithm for the Multi-angle Imaging SpectroRadiometer (MISR), for example, compares the observations to a set of 74 aerosol mixtures, each composed of particle models having prescribed optical properties and size distributions. In a recent “blind” study comparing the performance of several satellite retrieval algorithms on simulated data over a black surface, the MISR algorithm performed reasonably well in recovering the “true” spectral aerosol optical depths (AODs), but because the correct aerosol model was not contained within the MISR LUT, the retrieved AODs were biased low by ~14%. This motivated an investigation of whether an optimization approach, in which the aerosols are modeled by a set of continuously variable parameters recovered using nonlinear least-squares, could improve the results. In this paper, we demonstrate that such an approach using Levenberg–Marquardt optimization yields superior accuracy. Advances in computer speed, development of more efficient RT codes, and algorithm innovations will be necessary for this approach to satisfy the demands of a global, production-level satellite aerosol retrieval process, especially when used in conjunction with future instruments having enhanced sensitivity to diverse aerosol properties.
    Schlagwörter aerosols ; algorithms ; equations ; image analysis ; least squares ; models ; optical properties ; radiative transfer ; satellites ; spectroradiometers
    Sprache Englisch
    Erscheinungsverlauf 2012-1015
    Umfang p. 1-14.
    Erscheinungsort Elsevier B.V.
    Dokumenttyp Artikel
    ISSN 0169-8095
    DOI 10.1016/j.atmosres.2011.05.020
    Datenquelle NAL Katalog (AGRICOLA)

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