1
|
Storey CM, Altai M, Bicak M, Veach DR, Lückerath K, Adrian G, McDevitt MR, Kalidindi T, Park JE, Herrmann K, Abou D, Zedan W, Peekhaus N, Klein RJ, Damoiseaux R, Larson SM, Lilja H, Thorek D, Ulmert D. Quantitative In Vivo Imaging of the Androgen Receptor Axis Reveals Degree of Prostate Cancer Radiotherapy Response. Mol Cancer Res 2023; 21:307-315. [PMID: 36608299 PMCID: PMC10355285 DOI: 10.1158/1541-7786.mcr-22-0736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/13/2022] [Accepted: 01/03/2023] [Indexed: 01/09/2023]
Abstract
Noninvasive biomarkers for androgen receptor (AR) pathway activation are urgently needed to better monitor patient response to prostate cancer therapies. AR is a critical driver and mediator of resistance of prostate cancer but currently available noninvasive prostate cancer biomarkers to monitor AR activity are discordant with downstream AR pathway activity. External beam radiotherapy (EBRT) remains a common treatment for all stages of prostate cancer, and DNA damage induced by EBRT upregulates AR pathway activity to promote therapeutic resistance. [89Zr]11B6-PET is a novel modality targeting prostate-specific protein human kallikrein 2 (hK2), which is a surrogate biomarker for AR activity. Here, we studied whether [89Zr]11B6-PET can accurately assess EBRT-induced AR activity.Genetic and human prostate cancer mouse models received EBRT (2-50 Gy) and treatment response was monitored by [89Zr]11B6-PET/CT. Radiotracer uptake and expression of AR and AR target genes was quantified in resected tissue.EBRT increased AR pathway activity and [89Zr]11B6 uptake in LNCaP-AR and 22RV1 tumors. EBRT increased prostate-specific [89Zr]11B6 uptake in prostate cancer-bearing mice (Hi-Myc x Pb_KLK2) with no significant changes in uptake in healthy (Pb_KLK2) mice, and this correlated with hK2 protein levels. IMPLICATIONS hK2 expression in prostate cancer tissue is a proxy of EBRT-induced AR activity that can noninvasively be detected using [89Zr]11B6-PET; further clinical evaluation of hK2-PET for monitoring response and development of resistance to EBRT in real time is warranted.
Collapse
Affiliation(s)
- Claire M Storey
- Department of Molecular & Medical Pharmacology, University of California Los Angeles (UCLA), Los Angeles, USA
| | - Mohamed Altai
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Mesude Bicak
- Hasso Plattner Institute for Digital Health, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Darren R Veach
- Department of Radiology, Memorial Sloan Kettering Cancer Center (MSKCC), New York, USA
| | - Katharina Lückerath
- Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, DKTK, Essen, Germany
| | - Gabriel Adrian
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Michael R McDevitt
- Department of Radiology, Memorial Sloan Kettering Cancer Center (MSKCC), New York, USA
| | - Teja Kalidindi
- Department of Radiology, Memorial Sloan Kettering Cancer Center (MSKCC), New York, USA
| | - Julie E Park
- Department of Molecular & Medical Pharmacology, University of California Los Angeles (UCLA), Los Angeles, USA
| | - Ken Herrmann
- Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, DKTK, Essen, Germany
| | - Diane Abou
- Department of Radiology, Washington University School of Medicine, St. Louis, USA
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, USA
| | - Wahed Zedan
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Norbert Peekhaus
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Robert J Klein
- Icahn Institute for Genomics and Multiscale Biology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Robert Damoiseaux
- Department of Molecular & Medical Pharmacology, University of California Los Angeles (UCLA), Los Angeles, USA
- California NanoSystems Institute, UCLA, Los Angeles, USA
| | - Steven M Larson
- Department of Radiology, Memorial Sloan Kettering Cancer Center (MSKCC), New York, USA
- Department of Radiology, Weill Cornell Medical College, New York, USA
| | - Hans Lilja
- Genitourinary Oncology Service, Department of Medicine, MSKCC, New York, USA
- Urology Service, Department of Surgery, MSKCC, New York, USA
- Department of Laboratory Medicine, MSKCC, New York, USA
- Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Daniel Thorek
- Department of Radiology, Washington University School of Medicine, St. Louis, USA
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, USA
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, USA
| | - David Ulmert
- Department of Molecular & Medical Pharmacology, University of California Los Angeles (UCLA), Los Angeles, USA
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
- California NanoSystems Institute, UCLA, Los Angeles, USA
- Department of Urology, Institute of Urologic Oncology, UCLA, Los Angeles, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, UCLA, Los Angeles, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, UCLA, Los Angeles, USA
| |
Collapse
|
2
|
Perez-Garcia G, Bicak M, Haure-Mirande JV, Perez GM, Otero-Pagan A, Gama Sosa MA, De Gasperi R, Sano M, Barlow C, Gage FH, Readhead B, Ehrlich ME, Gandy S, Elder GA. BCI-838, an orally active mGluR2/3 receptor antagonist pro-drug, rescues learning behavior deficits in the PS19 MAPT P301S mouse model of tauopathy. Neurosci Lett 2023; 797:137080. [PMID: 36657633 PMCID: PMC9974759 DOI: 10.1016/j.neulet.2023.137080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 01/04/2023] [Accepted: 01/12/2023] [Indexed: 01/18/2023]
Abstract
Tauopathies are a heterogeneous group of neurodegenerative disorders that are clinically and pathologically distinct from Alzheimer's disease (AD) having tau inclusions in neurons and/or glia as their most prominent neuropathological feature. BCI-838 (MGS00210) is a group II metabotropic glutamate receptor (mGluR2/3) antagonist pro-drug. Previously, we reported that orally administered BCI-838 improved learning behavior and reduced anxiety in Dutch (APPE693Q) transgenic mice, a model of the pathological accumulation of Aβ oligomers found in AD. Herein, we investigated effects of BCI-838 on PS19 male mice that express the tauopathy mutation MAPTP301S associated with human frontotemporal lobar degeneration (FTLD). These mice develop an aging-related tauopathy without amyloid accumulation. Mice were divided into three experimental groups: (1) non-transgenic wild type mice treated with vehicle, (2) PS19 mice treated with vehicle and (3) PS19 mice treated with 5 mg/kg BCI-838. Groups of 10-13 mice were utilized. Vehicle or BCI-838 was administered by oral gavage for 4 weeks. Behavioral testing consisting of a novel object recognition task was conducted after drug administration. Two studies were performed beginning treatment of mice at 3 or 7 months of age. One month of BCI-838 treatment rescued deficits in recognition memory in PS19 mice whether treatment was begun at 3 or 7 months of age. These studies extend the potential utility of BCI-838 to neurodegenerative conditions that have tauopathy as their underlying basis. They also suggest an mGluR2/3 dependent mechanism as a basis for the behavioral deficits in PS19 mice.
Collapse
Affiliation(s)
- Georgina Perez-Garcia
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Research and Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY 10468, USA
| | - Mesude Bicak
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Gissel M Perez
- Research and Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY 10468, USA
| | - Alena Otero-Pagan
- Research and Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY 10468, USA
| | - Miguel A Gama Sosa
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; General Medical Research Service, James J. Peters Department of Veterans Affairs Medical Center, Bronx, NY 10468, USA
| | - Rita De Gasperi
- Research and Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY 10468, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mary Sano
- Research and Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY 10468, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mount Sinai Alzheimer's Disease Research Center and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Carrolee Barlow
- BrainCells Inc., La Jolla, CA 92037, USA; EScape Bio, South San Francisco, CA 94080, USA
| | - Fred H Gage
- BrainCells Inc., La Jolla, CA 92037, USA; Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Benjamin Readhead
- Arizona State University-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ 85287, USA
| | - Michelle E Ehrlich
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sam Gandy
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Research and Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY 10468, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mount Sinai Alzheimer's Disease Research Center and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mount Sinai Center for Cognitive Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gregory A Elder
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mount Sinai Alzheimer's Disease Research Center and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Neurology Service, James J. Peters Veterans Affairs Medical Center, Bronx, NY 10468, USA.
| |
Collapse
|
3
|
Bicak M, Perez‐Garcia GE, Buros J, Haure‐Mirande J, Perez GE, Otero‐Pagan A, Gama‐Sosa ME, DeGasperi RE, Sano M, Gage FH, Barlow C, Dudley J, Glicksberg BS, Wang Y, Readhead B, Ehrlich ME, Elder GA, Gandy S. BCI‐838, an orally active mGluR2/3 antagonist pro‐drug, mimics the beneficial effects of physical exercise on neurogenesis, behavior and exercise‐related molecular pathways in an Alzheimer’s disease mouse model. Alzheimers Dement 2022. [DOI: 10.1002/alz.062751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Mesude Bicak
- Icahn School of Medicine at Mount Sinai New York NY USA
| | - Georgina E. Perez‐Garcia
- Icahn School of Medicine at Mount Sinai New York NY USA
- James J. Peters Veterans Affairs Medical Center Bronx NY USA
| | - Jacqueline Buros
- Icahn School of Medicine at Mount Sinai New York NY USA
- Generable Inc New York NY USA
| | | | - Gissel E. Perez
- James J. Peters Veterans Affairs Medical Center Bronx NY USA
| | | | | | - Rita E. DeGasperi
- Icahn School of Medicine at Mount Sinai New York NY USA
- James J. Peters Veterans Affairs Medical Center Bronx NY USA
| | - Mary Sano
- Icahn School of Medicine at Mount Sinai New York NY USA
- James J. Peters Veterans Affairs Medical Center Bronx NY USA
| | - Fred H. Gage
- BrainCells Inc. La Jolla CA USA
- Salk Institute for Biological Studies La Jolla CA USA
| | - Carrolee Barlow
- BrainCells Inc. La Jolla CA USA
- Escape Bio, South San Fransisco CA USA
| | - Joel Dudley
- Icahn School of Medicine at Mount Sinai New York NY USA
| | | | | | | | | | - Gregory A. Elder
- Icahn School of Medicine at Mount Sinai New York NY USA
- James J. Peters Veterans Affairs Medical Center Bronx NY USA
| | - Sam Gandy
- Icahn School of Medicine at Mount Sinai New York NY USA
- James J. Peters Veterans Affairs Medical Center Bronx NY USA
| |
Collapse
|
4
|
Tang AS, Oskotsky T, Havaldar S, Mantyh WG, Bicak M, Solsberg CW, Woldemariam S, Zeng B, Hu Z, Oskotsky B, Dubal D, Allen IE, Glicksberg BS, Sirota M. Deep phenotyping of Alzheimer's disease leveraging electronic medical records identifies sex-specific clinical associations. Nat Commun 2022; 13:675. [PMID: 35115528 PMCID: PMC8814236 DOI: 10.1038/s41467-022-28273-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 01/18/2022] [Indexed: 12/14/2022] Open
Abstract
Alzheimer's Disease (AD) is a neurodegenerative disorder that is still not fully understood. Sex modifies AD vulnerability, but the reasons for this are largely unknown. We utilize two independent electronic medical record (EMR) systems across 44,288 patients to perform deep clinical phenotyping and network analysis to gain insight into clinical characteristics and sex-specific clinical associations in AD. Embeddings and network representation of patient diagnoses demonstrate greater comorbidity interactions in AD in comparison to matched controls. Enrichment analysis identifies multiple known and new diagnostic, medication, and lab result associations across the whole cohort and in a sex-stratified analysis. With this data-driven method of phenotyping, we can represent AD complexity and generate hypotheses of clinical factors that can be followed-up for further diagnostic and predictive analyses, mechanistic understanding, or drug repurposing and therapeutic approaches.
Collapse
Affiliation(s)
- Alice S Tang
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
- Graduate Program in Bioengineering, UCSF, San Francisco, CA, USA.
- School of Medicine, UCSF, San Francisco, CA, USA.
| | - Tomiko Oskotsky
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
- Department of Pediatrics, UCSF, San Francisco, CA, USA
| | - Shreyas Havaldar
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - William G Mantyh
- Department of Neurology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Mesude Bicak
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Caroline Warly Solsberg
- Pharmaceutical Sciences and Pharmacogenomics, UCSF, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Memory and Aging Center, UCSF, San Francisco, CA, USA
| | - Sarah Woldemariam
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
| | - Billy Zeng
- School of Medicine, UCSF, San Francisco, CA, USA
| | - Zicheng Hu
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
| | - Boris Oskotsky
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA
| | - Dena Dubal
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Isabel E Allen
- Department of Epidemiology and Biostatistics, UCSF, San Francisco, CA, USA
| | - Benjamin S Glicksberg
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
- Department of Pediatrics, UCSF, San Francisco, CA, USA.
| |
Collapse
|
5
|
Taubes A, Nova P, Zalocusky KA, Kosti I, Bicak M, Zilberter MY, Hao Y, Yoon SY, Oskotsky T, Pineda S, Chen B, Aery Jones EA, Choudhary K, Grone B, Balestra ME, Chaudhry F, Paranjpe I, De Freitas J, Koutsodendris N, Chen N, Wang C, Chang W, An A, Glicksberg BS, Sirota M, Huang Y. Author Correction: Experimental and real-world evidence supporting the computational repurposing of bumetanide for APOE4-related Alzheimer's disease. Nat Aging 2021; 1:1202. [PMID: 37117528 DOI: 10.1038/s43587-021-00144-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Affiliation(s)
- Alice Taubes
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Phil Nova
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Kelly A Zalocusky
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
- Department of Pediatrics, University of California, San Francisco, CA, USA
| | - Mesude Bicak
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Misha Y Zilberter
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
| | - Yanxia Hao
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
| | - Seo Yeon Yoon
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Tomiko Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
- Department of Pediatrics, University of California, San Francisco, CA, USA
| | - Silvia Pineda
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
- Department of Surgery, University of California, San Francisco, CA, USA
| | - Bin Chen
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
| | - Emily A Aery Jones
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Krishna Choudhary
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
| | - Brian Grone
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Maureen E Balestra
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Fayzan Chaudhry
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ishan Paranjpe
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jessica De Freitas
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nicole Koutsodendris
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Development and Stem Cell Biology Graduate Program, University of California, San Francisco, CA, USA
| | - Nuo Chen
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Celine Wang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - William Chang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Alice An
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
| | - Benjamin S Glicksberg
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
- Department of Pediatrics, University of California, San Francisco, CA, USA.
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA.
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA.
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, CA, USA.
- Department of Pathology, University of California, San Francisco, CA, USA.
| |
Collapse
|
6
|
Vaid A, Johnson KW, Badgeley MA, Somani SS, Bicak M, Landi I, Russak A, Zhao S, Levin MA, Freeman RS, Charney AW, Kukar A, Kim B, Danilov T, Lerakis S, Argulian E, Narula J, Nadkarni GN, Glicksberg BS. Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram. JACC Cardiovasc Imaging 2021; 15:395-410. [PMID: 34656465 PMCID: PMC8917975 DOI: 10.1016/j.jcmg.2021.08.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/29/2021] [Accepted: 08/05/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVES This study sought to develop DL models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population. BACKGROUND Rapid evaluation of left and right ventricular function using deep learning (DL) on electrocardiograms (ECGs) can assist diagnostic workflow. However, DL tools to estimate right- ventricular (RV) function do not exist, whereas those to estimate left ventricular (LV) function are restricted to quantification of very low LV function only. METHODS A multicenter study was conducted with data from 5 New York City hospitals: 4 for internal testing and 1 serving as external validation. We created novel DL models to classify left ventricular ejection fraction (LVEF) into categories derived from the latest universal definition of heart failure, estimate LVEF through regression, and predict a composite outcome of either RV systolic dysfunction or RV dilation. RESULTS We obtained echocardiogram LVEF estimates for 147,636 patients paired to 715,890 ECGs. We used natural language processing (NLP) to extract RV size and systolic function information from 404,502 echocardiogram reports paired to 761,510 ECGs for 148,227 patients. For LVEF classification in internal testing, area under curve (AUC) at detection of LVEF ≤40%, 40% < LVEF ≤50%, and LVEF >50% was 0.94 (95% CI: 0.94-0.94), 0.82 (95% CI: 0.81-0.83), and 0.89 (95% CI: 0.89-0.89), respectively. For external validation, these results were 0.94 (95% CI: 0.94-0.95), 0.73 (95% CI: 0.72-0.74), and 0.87 (95% CI: 0.87-0.88). For regression, the mean absolute error was 5.84% (95% CI: 5.82%-5.85%) for internal testing and 6.14% (95% CI: 6.13%-6.16%) in external validation. For prediction of the composite RV outcome, AUC was 0.84 (95% CI: 0.84-0.84) in both internal testing and external validation. CONCLUSIONS DL on ECG data can be used to create inexpensive screening, diagnostic, and predictive tools for both LV and RV dysfunction. Such tools may bridge the applicability of ECGs and echocardiography and enable prioritization of patients for further interventions for either sided failure progressing to biventricular disease.
Collapse
Affiliation(s)
- Akhil Vaid
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Kipp W Johnson
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Sulaiman S Somani
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mesude Bicak
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Isotta Landi
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Adam Russak
- Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Shan Zhao
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Matthew A Levin
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Robert S Freeman
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Alexander W Charney
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Atul Kukar
- Department of Cardiology, Mount Sinai Queens Hospital, Astoria, New York, USA, and Icahn School of Medicine at Mount Sinai, New York, New York, USA; Division of Cardiology, Mount Sinai West Hospital and Icahn School of Medicine at Mount Sinai, New York, New York USA
| | - Bette Kim
- Mount Sinai Beth Israel Hospital, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Tatyana Danilov
- Department of Cardiology, Mount Sinai Morningside Hospital, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Stamatios Lerakis
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Edgar Argulian
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jagat Narula
- The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Girish N Nadkarni
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Benjamin S Glicksberg
- Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
| |
Collapse
|
7
|
Taubes A, Nova P, Zalocusky KA, Kosti I, Bicak M, Zilberter MY, Hao Y, Yoon SY, Oskotsky T, Pineda S, Chen B, Jones EAA, Choudhary K, Grone B, Balestra ME, Chaudhry F, Paranjpe I, De Freitas J, Koutsodendris N, Chen N, Wang C, Chang W, An A, Glicksberg BS, Sirota M, Huang Y. Experimental and real-world evidence supporting the computational repurposing of bumetanide for APOE4-related Alzheimer's disease. Nat Aging 2021; 1:932-947. [PMID: 36172600 PMCID: PMC9514594 DOI: 10.1038/s43587-021-00122-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
The evident genetic, pathological, and clinical heterogeneity of Alzheimer's disease (AD) poses challenges for traditional drug development. We conducted a computational drug repurposing screen for drugs to treat apolipoprotein (apo) E4-related AD. We first established apoE-genotype-dependent transcriptomic signatures of AD by analyzing publicly-available human brain database. We then queried these signatures against the Connectivity Map database containing transcriptomic perturbations of >1300 drugs to identify those that best reverse apoE-genotype-specific AD signatures. Bumetanide was identified as a top drug for apoE4 AD. Bumetanide treatment of apoE4 mice without or with Aβ accumulation rescued electrophysiological, pathological, or cognitive deficits. Single-nucleus RNA-sequencing revealed transcriptomic reversal of AD signatures in specific cell types in these mice, a finding confirmed in apoE4-iPSC-derived neurons. In humans, bumetanide exposure was associated with a significantly lower AD prevalence in individuals over the age of 65 in two electronic health record databases, suggesting effectiveness of bumetanide in preventing AD.
Collapse
Affiliation(s)
- Alice Taubes
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Phil Nova
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Kelly A. Zalocusky
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA, USA
| | - Mesude Bicak
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Misha Y. Zilberter
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Yanxia Hao
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Seo Yeon Yoon
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Tomiko Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA, USA
| | - Silvia Pineda
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Surgery, University of California, San Francisco, CA 94143, USA
| | - Bin Chen
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
| | - Emily A. Aery Jones
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Krishna Choudhary
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Brian Grone
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
| | - Maureen E. Balestra
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Fayzan Chaudhry
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Ishan Paranjpe
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Jessica De Freitas
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Nicole Koutsodendris
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Development and Stem Cell Biology Graduate Program, University of California, San Francisco, CA 94143, USA
| | - Nuo Chen
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Celine Wang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - William Chang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Alice An
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Benjamin S. Glicksberg
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10065, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA, USA
- Correspondence: Yadong Huang () or Marina Sirota ()
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA
- Gladstone Center for Translational Advancement, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
- Department of Pathology, University of California, San Francisco, CA 94143, USA
- Correspondence: Yadong Huang () or Marina Sirota ()
| |
Collapse
|
8
|
Vaid A, Jaladanki SK, Xu J, Teng S, Kumar A, Lee S, Somani S, Paranjpe I, De Freitas JK, Wanyan T, Johnson KW, Bicak M, Klang E, Kwon YJ, Costa A, Zhao S, Miotto R, Charney AW, Böttinger E, Fayad ZA, Nadkarni GN, Wang F, Glicksberg BS. Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach. JMIR Med Inform 2021; 9:e24207. [PMID: 33400679 PMCID: PMC7842859 DOI: 10.2196/24207] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 10/23/2020] [Accepted: 12/14/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Machine learning models require large datasets that may be siloed across different health care institutions. Machine learning studies that focus on COVID-19 have been limited to single-hospital data, which limits model generalizability. OBJECTIVE We aimed to use federated learning, a machine learning technique that avoids locally aggregating raw clinical data across multiple institutions, to predict mortality in hospitalized patients with COVID-19 within 7 days. METHODS Patient data were collected from the electronic health records of 5 hospitals within the Mount Sinai Health System. Logistic regression with L1 regularization/least absolute shrinkage and selection operator (LASSO) and multilayer perceptron (MLP) models were trained by using local data at each site. We developed a pooled model with combined data from all 5 sites, and a federated model that only shared parameters with a central aggregator. RESULTS The LASSOfederated model outperformed the LASSOlocal model at 3 hospitals, and the MLPfederated model performed better than the MLPlocal model at all 5 hospitals, as determined by the area under the receiver operating characteristic curve. The LASSOpooled model outperformed the LASSOfederated model at all hospitals, and the MLPfederated model outperformed the MLPpooled model at 2 hospitals. CONCLUSIONS The federated learning of COVID-19 electronic health record data shows promise in developing robust predictive models without compromising patient privacy.
Collapse
Affiliation(s)
- Akhil Vaid
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Suraj K Jaladanki
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Jie Xu
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
| | - Shelly Teng
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Arvind Kumar
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Samuel Lee
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Sulaiman Somani
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Ishan Paranjpe
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Jessica K De Freitas
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Tingyi Wanyan
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Intelligent System Engineering, Indiana University, Bloomington, IN, United States
- School of Information, University of Texas Austin, Austin, TX, United States
| | - Kipp W Johnson
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
| | - Mesude Bicak
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Eyal Klang
- Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Young Joon Kwon
- Department of Neurological Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Anthony Costa
- Department of Neurological Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Shan Zhao
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Riccardo Miotto
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Alexander W Charney
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Erwin Böttinger
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
- Digital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
| | - Zahi A Fayad
- The BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Girish N Nadkarni
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
| | - Benjamin S Glicksberg
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- The Mount Sinai Clinical Intelligence Center, New York, NY, United States
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| |
Collapse
|
9
|
Bicak M, Akelma H, Salik F, Kaya S. Combined Spinal and TAP Blocks for Laparoscopic Cholecystectomy for a Patient with Crigler-Najjar Type 2: A Case Report. Niger J Clin Pract 2020; 23:1772-1775. [PMID: 33355834 DOI: 10.4103/njcp.njcp_19_20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Crigler-Najjar syndrome is a rare disease which is associated with congenital deficiency of uridine-diphosphate-gulukronyltransferase (UDP-glucuronosyltransferase, UGT) enzyme. In the surgery of these patients, it is necessary to use an anesthetic method that causes less damage to the liver. Spinal anesthesia is a good alternative to general anesthesia in these patients. Transversus abdominis plane block is a new method for ultrasound guided abdominal wall block. It is less invasive and relatively safer than conventional regional anesthetic techniques. Our case is a 30-year-old male patient with the diagnosis of Crigler-Najjar type 2 (Arias syndrome). There was a history of gallbladder edema, multiple stones and thickened gallbladder wall. We applied Transversus abdominis plane block in addition to spinal anesthesia as primary anesthesia for our patient who underwent laparoscopic surgery. We didn't experience any postoperative complications in our patient. In conclusion, laparoscopic surgery performed under combined spinal anesthesia and transvesus abdominis plane block in a Criggler Najjar type 2 (Arias syndrome) patient may be a simple and effective technique.
Collapse
Affiliation(s)
- M Bicak
- Department of Anesthesiology, University of Health Sciences, Gazi Yasargil Diyarbakir Training and Research Hospital, Diyarbakir, Turkey
| | - H Akelma
- Department of Anesthesiology, University of Health Sciences, Gazi Yasargil Diyarbakir Training and Research Hospital, Diyarbakir, Turkey
| | - F Salik
- Department of Anesthesiology, University of Health Sciences, Gazi Yasargil Diyarbakir Training and Research Hospital, Diyarbakir, Turkey
| | - S Kaya
- Department of Anesthesiology, University of Health Sciences, Gazi Yasargil Diyarbakir Training and Research Hospital, Diyarbakir, Turkey
| |
Collapse
|
10
|
Li W, Bicak M, Sjoberg DD, Vertosick E, Dahlin A, Melander O, Ulmert D, Lilja H, Klein RJ. Genome-wide association study identifies novel single nucleotide polymorphisms having age-specific effect on prostate-specific antigen levels. Prostate 2020; 80:1405-1412. [PMID: 32914890 PMCID: PMC7606728 DOI: 10.1002/pros.24070] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 08/17/2020] [Accepted: 08/24/2020] [Indexed: 01/17/2023]
Abstract
BACKGROUND Testing for prostate-specific antigen (PSA) levels in blood are widely used and associated with prostate cancer risk and outcome. After puberty, PSA levels increase by age and multiple single nucleotide polymorphisms (SNPs) have been found to be associated with PSA levels. However, the relationship between the effects of SNPs and age on PSA remains unknown. METHODS To test for SNP × age interaction, we conducted a genome-wide association study using 2394 men without prostate cancer diagnosis from Malmö, Sweden as a discovery set and 2137 men from the eMERGE study (USA) for validation. Linear regression was used to identify significant interactions between SNP and age (p < 1 × 10-4 for discovery, p < .05 for validation). RESULTS The 15 SNPs from three different loci (8p11.22, 8p12, 3q25.31) are found to have age-specific effect on PSA levels. Expression quantitative trait loci (eQTLs) analysis shows that 12 SNPs from 3q25.31 locus affect the expression level of three genes: KCNAB1, SLC33A1, PLCH1. CONCLUSIONS Our results suggest that SNPs may have age-specific effect on PSA levels, which provides new direction to study genetic markers for PSA.
Collapse
Affiliation(s)
- Weiqiang Li
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Mesude Bicak
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Daniel D. Sjoberg
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Emily Vertosick
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Anders Dahlin
- Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden
| | - Olle Melander
- Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden
| | - David Ulmert
- Molecular pharmacology program, Sloan Kettering Institute, New York, NY USA
| | - Hans Lilja
- Departments of Laboratory Medicine, Surgery, and Medicine, Memorial Sloan Kettering Cancer Center, New York, NY USA; Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Robert J. Klein
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| |
Collapse
|
11
|
Vaid A, Jaladanki SK, Xu J, Teng S, Kumar A, Lee S, Somani S, Paranjpe I, De Freitas JK, Wanyan T, Johnson KW, Bicak M, Klang E, Kwon YJ, Costa A, Zhao S, Miotto R, Charney AW, Böttinger E, Fayad ZA, Nadkarni GN, Wang F, Glicksberg BS. Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19. medRxiv 2020:2020.08.11.20172809. [PMID: 32817979 PMCID: PMC7430624 DOI: 10.1101/2020.08.11.20172809] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Machine learning (ML) models require large datasets which may be siloed across different healthcare institutions. Using federated learning, a ML technique that avoids locally aggregating raw clinical data across multiple institutions, we predict mortality within seven days in hospitalized COVID-19 patients. Patient data was collected from Electronic Health Records (EHRs) from five hospitals within the Mount Sinai Health System (MSHS). Logistic Regression with L1 regularization (LASSO) and Multilayer Perceptron (MLP) models were trained using local data at each site, a pooled model with combined data from all five sites, and a federated model that only shared parameters with a central aggregator. Both the federated LASSO and federated MLP models performed better than their local model counterparts at four hospitals. The federated MLP model also outperformed the federated LASSO model at all hospitals. Federated learning shows promise in COVID-19 EHR data to develop robust predictive models without compromising patient privacy.
Collapse
Affiliation(s)
- Akhil Vaid
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Suraj K Jaladanki
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Jie Xu
- Department of Population Health Sciences. Weill Cornell Medicine. New York, USA
| | - Shelly Teng
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Arvind Kumar
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Samuel Lee
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Sulaiman Somani
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Ishan Paranjpe
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Jessica K De Freitas
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Tingyi Wanyan
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- Intelligent System Engineering, Indiana University, Bloomington, USA
- School of Information, University of Texas Austin, Austin, USA
| | - Kipp W Johnson
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
| | - Mesude Bicak
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Eyal Klang
- Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Young Joon Kwon
- Department of Neurological Surgery, Icahn School of Medicine, New York, USA
| | - Anthony Costa
- Department of Neurological Surgery, Icahn School of Medicine, New York, USA
| | - Shan Zhao
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Riccardo Miotto
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Alexander W Charney
- The Mount Sinai COVID Informatics Center, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- The Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Erwin Böttinger
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
- Digital Health Center, Hasso Plattner Institute, University of Potsdam, Germany
| | - Zahi A Fayad
- The BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Girish N Nadkarni
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Fei Wang
- Department of Population Health Sciences. Weill Cornell Medicine. New York, USA
| | - Benjamin S Glicksberg
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA
- The Mount Sinai COVID Informatics Center, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, USA
| |
Collapse
|
12
|
Bicak M, Lückerath K, Kalidindi T, Phelps ME, Strand SE, Morris MJ, Radu CG, Damoiseaux R, Peltola MT, Peekhaus N, Ho A, Veach D, Malmborg Hager AC, Larson SM, Lilja H, McDevitt MR, Klein RJ, Ulmert D. Genetic signature of prostate cancer mouse models resistant to optimized hK2 targeted α-particle therapy. Proc Natl Acad Sci U S A 2020; 117:15172-15181. [PMID: 32532924 PMCID: PMC7334567 DOI: 10.1073/pnas.1918744117] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Hu11B6 is a monoclonal antibody that internalizes in cells expressing androgen receptor (AR)-regulated prostate-specific enzyme human kallikrein-related peptidase 2 (hK2; KLK2). In multiple rodent models, Actinium-225-labeled hu11B6-IgG1 ([225Ac]hu11B6-IgG1) has shown promising treatment efficacy. In the present study, we investigated options to enhance and optimize [225Ac]hu11B6 treatment. First, we evaluated the possibility of exploiting IgG3, the IgG subclass with superior activation of complement and ability to mediate FC-γ-receptor binding, for immunotherapeutically enhanced hK2 targeted α-radioimmunotherapy. Second, we compared the therapeutic efficacy of a single high activity vs. fractionated activity. Finally, we used RNA sequencing to analyze the genomic signatures of prostate cancer that progressed after targeted α-therapy. [225Ac]hu11B6-IgG3 was a functionally enhanced alternative to [225Ac]hu11B6-IgG1 but offered no improvement of therapeutic efficacy. Progression-free survival was slightly increased with a single high activity compared to fractionated activity. Tumor-free animals succumbing after treatment revealed no evidence of treatment-associated toxicity. In addition to up-regulation of canonical aggressive prostate cancer genes, such as MMP7, ETV1, NTS, and SCHLAP1, we also noted a significant decrease in both KLK3 (prostate-specific antigen ) and FOLH1 (prostate-specific membrane antigen) but not in AR and KLK2, demonstrating efficacy of sequential [225Ac]hu11B6 in a mouse model.
Collapse
Affiliation(s)
- Mesude Bicak
- Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genome Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Katharina Lückerath
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095
- Ahmanson Translational Imaging Division, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | - Teja Kalidindi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
| | - Michael E Phelps
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095;
| | - Sven-Erik Strand
- Division of Oncology and Pathology, Department of Clinical Sciences, Lund University, 223 81 Lund, Sweden
| | - Michael J Morris
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065
| | - Caius G Radu
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095
- Ahmanson Translational Imaging Division, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | - Robert Damoiseaux
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095
| | - Mari T Peltola
- Department of Biochemistry-Biotechnology, University of Turku, FI-20014 Turun yliopisto, Finland
| | - Norbert Peekhaus
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095
| | - Austin Ho
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095
| | - Darren Veach
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
- Radiochemistry and Imaging Sciences Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
- Diaprost AB, 223 63 Lund, Sweden
| | | | - Steven M Larson
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
- Department of Radiology, Weill Cornell Medical College, New York, NY 10065
| | - Hans Lilja
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065
- Department of Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065
- Department of Translational Medicine, Lund University, 221 00 Lund, Sweden
- Nuffield Department of Surgical Sciences, University of Oxford, Headington, OX3 7DQ Oxford, United Kingdom
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065
| | - Michael R McDevitt
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
- Department of Radiology, Weill Cornell Medical College, New York, NY 10065
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genome Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029;
| | - David Ulmert
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095;
- Ahmanson Translational Imaging Division, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA 90095
| |
Collapse
|
13
|
Bicak M, Wang X, Gao X, Xu X, Väänänen RM, Taimen P, Lilja H, Pettersson K, Klein RJ. Prostate cancer risk SNP rs10993994 is a trans-eQTL for SNHG11 mediated through MSMB. Hum Mol Genet 2020; 29:1581-1591. [PMID: 32065238 PMCID: PMC7526792 DOI: 10.1093/hmg/ddaa026] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 12/25/2019] [Accepted: 02/12/2020] [Indexed: 02/06/2023] Open
Abstract
How genome-wide association studies-identified single-nucleotide polymorphisms (SNPs) affect remote genes remains unknown. Expression quantitative trait locus (eQTL) association meta-analysis on 496 prostate tumor and 602 normal prostate samples with 117 SNPs revealed novel cis-eQTLs and trans-eQTLs. Mediation testing and colocalization analysis demonstrate that MSMB is a cis-acting mediator for SNHG11 (P < 0.01). Removing rs10993994 in LNCaP cell lines by CRISPR/Cas9 editing shows that the C-allele corresponds with an over 100-fold increase in MSMB expression and 5-fold increase in SNHG11 compared with the T-allele. Colocalization analysis confirmed that the same set of SNPs associated with MSMB expression is associated with SNHG11 expression (posterior probability of shared variants is 66.6% in tumor and 91.4% in benign). These analyses further demonstrate variants driving MSMB expression differ in tumor and normal, suggesting regulatory network rewiring during tumorigenesis.
Collapse
Affiliation(s)
- Mesude Bicak
- Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genome Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Xing Wang
- Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genome Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Xiaoni Gao
- Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genome Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Program in Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Xing Xu
- Program in Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | | | - Pekka Taimen
- Department of Pathology, University of Turku, 20014 Turku, and Turku University Hospital, 20521 Turku, Finland
| | - Hans Lilja
- Department of Laboratory Medicine, Surgery and Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 7DQ, UK
- Department of Translational Medicine, Lund University, Malmö 205 02, Sweden
| | - Kim Pettersson
- Division of Biotechnology, University of Turku, Turku, Finland
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn Institute for Data Science and Genome Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Program in Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| |
Collapse
|
14
|
Beksac AT, Bicak M, Paranjpe I, Paulucci DJ, Sfakianos JP, Badani KK. Clinicopathologic and Genomic Factors Associated With Oncologic Outcome in Patients With Stage III to IV Chromophobe Renal Cell Carcinoma. Clin Genitourin Cancer 2019; 17:e314-e322. [PMID: 30639042 DOI: 10.1016/j.clgc.2018.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 11/15/2018] [Accepted: 12/03/2018] [Indexed: 11/29/2022]
Abstract
BACKGROUND Chromophobe renal cell carcinoma (chRCC) is known as an indolent tumor; however, mortality still occurs. We sought to determine the clinicopathologic and genomic factors associated with aggressive chRCC. PATIENTS AND METHODS Two different datasets were used to identify patients with clinical stage III and IV chRCC. Eighteen patients from The Cancer Genome Atlas (TCGA) database and 1693 patients from the American College of Surgeons National Cancer Database (NCDB) were used for analysis. From the TCGA, RNA-Seq expression analysis of 18,745 genes was conducted between the recurrent (n = 5; 27.8%) and nonrecurrent patients (n = 13; 72.2%). Biological significance was identified via pathway enrichment and gene function analyses. From the NCDB, Cox proportion hazards regression models were used to identify variables associated with overall survival (OS) at a median follow-up of 41.4 months. RESULTS Between the 2 groups, 2182 genes were differentially expressed. The most commonly overexpressed pathways were neuroactive ligand-receptor interactions and cytokine-cytokine receptor interactions. The most activated gene functions were cellular, metabolic, and multicellular organismal processes. In the NCDB, multivariable analysis, age (hazard ratio [HR], 1.04; 95% confidence interval [CI], 1.03-1.05; P < .001), TNM stage IV versus III (HR, 3.86; 95% CI, 2.98-5.00; P < .001), and positive surgical margin (HR, 1.68; 95% CI, 1.45-1.96; P < .001) were associated with worse OS at a median follow-up of 41.4 months. Five-year OS was significantly lower for stage IV patients compared with stage III patients (80.0% vs. 29.9%; P < .001). CONCLUSIONS Patients with recurrent chRCC demonstrated a differential gene expression of specific biochemical pathways. Clinical parameters associated with worse OS included age, stage, and positive surgical margin.
Collapse
Affiliation(s)
- Alp Tuna Beksac
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Mesude Bicak
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ishan Paranjpe
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - David J Paulucci
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - John P Sfakianos
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ketan K Badani
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, NY.
| |
Collapse
|
15
|
Li W, Middha M, Bicak M, Sjoberg DD, Vertosick E, Dahlin A, Häggström C, Hallmans G, Rönn AC, Stattin P, Melander O, Ulmert D, Lilja H, Klein RJ. Genome-wide Scan Identifies Role for AOX1 in Prostate Cancer Survival. Eur Urol 2018; 74:710-719. [PMID: 30289108 DOI: 10.1016/j.eururo.2018.06.021] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 06/13/2018] [Indexed: 12/24/2022]
Abstract
BACKGROUND Most men diagnosed with prostate cancer have low-risk cancers. How to predict prostate cancer progression at the time of diagnosis remains challenging. OBJECTIVE To identify single nucleotide polymorphisms (SNPs) associated with death from prostate cancer. DESIGN, SETTING, AND PARTICIPANTS Blood samples from 11 506 men in Sweden were collected during 1991-1996. Of these, 1053 men were diagnosed with prostate cancer and 245 died from the disease. Stage and grade at diagnosis and outcome information were obtained, and DNA from all cases was genotyped. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS A total of 6 126 633 SNPs were tested for association with prostate-cancer-specific survival time using a Cox proportional hazard model, adjusted for age, stage, and grade at diagnosis. A value of 1×10-6 was used as suggestive significance threshold. Positive candidate SNPs were tested for association with gene expression using expression quantitative trait locus analysis. RESULTS AND LIMITATIONS We found 12 SNPs at seven independent loci associated with prostate-cancer-specific survival time. One of 6 126 633 SNPs tested reached genome-wide significance (p<5×10-8) and replicated in an independent cohort: rs73055188 (p=5.27×10-9, per-allele hazard ratio [HR]=2.27, 95% confidence interval [CI] 1.72-2.98) in the AOX1 gene. A second SNP reached a suggestive level of significance (p<1×10-6) and replicated in an independent cohort: rs2702185 (p=7.1×10-7, per-allele HR=2.55, 95% CI=1.76-3.69) in the SMG7 gene. The SNP rs73055188 is correlated with AOX1 expression levels, which is associated with biochemical recurrence of prostate cancer in independent cohorts. This association is yet to be validated in other ethnic groups. CONCLUSIONS The SNP rs73055188 at the AOX1 locus is associated with prostate-cancer-specific survival time, and AOX1 gene expression level is correlated with biochemical recurrence of prostate cancer. PATIENT SUMMARY We identify two genetic markers that are associated with prostate-cancer-specific survival time.
Collapse
Affiliation(s)
- Weiqiang Li
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mridu Middha
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mesude Bicak
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel D Sjoberg
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Emily Vertosick
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anders Dahlin
- Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden
| | - Christel Häggström
- Department of Biobank Research, Umeå University, Umeå, Sweden; Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Göran Hallmans
- Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Sweden
| | - Ann-Charlotte Rönn
- Clinical Research Center, Karolinska University Hospital, Huddinge, Sweden
| | - Pär Stattin
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Olle Melander
- Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden
| | - David Ulmert
- Molecular Pharmacology Program, Sloan Kettering Institute, New York, NY, USA
| | - Hans Lilja
- Department of Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Robert J Klein
- Icahn Institute for Genomics and Multiscale Biology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| |
Collapse
|
16
|
Kopf A, Bicak M, Kottmann R, Schnetzer J, Kostadinov I, Lehmann K, Fernandez-Guerra A, Jeanthon C, Rahav E, Ullrich M, Wichels A, Gerdts G, Polymenakou P, Kotoulas G, Siam R, Abdallah RZ, Sonnenschein EC, Cariou T, O'Gara F, Jackson S, Orlic S, Steinke M, Busch J, Duarte B, Caçador I, Canning-Clode J, Bobrova O, Marteinsson V, Reynisson E, Loureiro CM, Luna GM, Quero GM, Löscher CR, Kremp A, DeLorenzo ME, Øvreås L, Tolman J, LaRoche J, Penna A, Frischer M, Davis T, Katherine B, Meyer CP, Ramos S, Magalhães C, Jude-Lemeilleur F, Aguirre-Macedo ML, Wang S, Poulton N, Jones S, Collin R, Fuhrman JA, Conan P, Alonso C, Stambler N, Goodwin K, Yakimov MM, Baltar F, Bodrossy L, Van De Kamp J, Frampton DM, Ostrowski M, Van Ruth P, Malthouse P, Claus S, Deneudt K, Mortelmans J, Pitois S, Wallom D, Salter I, Costa R, Schroeder DC, Kandil MM, Amaral V, Biancalana F, Santana R, Pedrotti ML, Yoshida T, Ogata H, Ingleton T, Munnik K, Rodriguez-Ezpeleta N, Berteaux-Lecellier V, Wecker P, Cancio I, Vaulot D, Bienhold C, Ghazal H, Chaouni B, Essayeh S, Ettamimi S, Zaid EH, Boukhatem N, Bouali A, Chahboune R, Barrijal S, Timinouni M, El Otmani F, Bennani M, Mea M, Todorova N, Karamfilov V, Ten Hoopen P, Cochrane G, L'Haridon S, Bizsel KC, Vezzi A, Lauro FM, Martin P, Jensen RM, Hinks J, Gebbels S, Rosselli R, De Pascale F, Schiavon R, Dos Santos A, Villar E, Pesant S, Cataletto B, Malfatti F, Edirisinghe R, Silveira JAH, Barbier M, Turk V, Tinta T, Fuller WJ, Salihoglu I, Serakinci N, Ergoren MC, Bresnan E, Iriberri J, Nyhus PAF, Bente E, Karlsen HE, Golyshin PN, Gasol JM, Moncheva S, Dzhembekova N, Johnson Z, Sinigalliano CD, Gidley ML, Zingone A, Danovaro R, Tsiamis G, Clark MS, Costa AC, El Bour M, Martins AM, Collins RE, Ducluzeau AL, Martinez J, Costello MJ, Amaral-Zettler LA, Gilbert JA, Davies N, Field D, Glöckner FO. The ocean sampling day consortium. Gigascience 2015; 4:27. [PMID: 26097697 PMCID: PMC4473829 DOI: 10.1186/s13742-015-0066-5] [Citation(s) in RCA: 135] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 05/06/2015] [Indexed: 11/26/2022] Open
Abstract
Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.
Collapse
Affiliation(s)
- Anna Kopf
- Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, D-28359 Bremen, Germany ; Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany
| | - Mesude Bicak
- University of Oxford, 7 Keble Road, OX1 3QG Oxford, Oxfordshire UK
| | - Renzo Kottmann
- Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, D-28359 Bremen, Germany
| | - Julia Schnetzer
- Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, D-28359 Bremen, Germany ; Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany
| | - Ivaylo Kostadinov
- Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany
| | - Katja Lehmann
- Centre for Ecology & Hydrology, MacLean Building, Benson Lane, Crowmarsh Gifford, OX10 8BB Wallingford, Oxfordshire UK
| | - Antonio Fernandez-Guerra
- Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, D-28359 Bremen, Germany ; University of Oxford, 7 Keble Road, OX1 3QG Oxford, Oxfordshire UK
| | - Christian Jeanthon
- CNRS & Sorbonne Universités, UPMC Univ Paris 06, Station Biologique, Place Georges Teissier, F-29680 Roscoff, France
| | - Eyal Rahav
- Israel Oceanographic and Limnological Research, National Institute of Oceanography, Tel- Shikmona, POB 8030, 31080 Haifa, Israel
| | - Matthias Ullrich
- Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany
| | - Antje Wichels
- Alfred Wegener Institute, Biologische Anstalt Helgoland, Kurpromenade 201, 27498 Helgoland, Germany
| | - Gunnar Gerdts
- Alfred Wegener Institute, Biologische Anstalt Helgoland, Kurpromenade 201, 27498 Helgoland, Germany
| | - Paraskevi Polymenakou
- Hellenic Centre for Marine Research, Institute of Marine Biology, Biotechnology and Aquaculture, Gournes Pediados, 71500 Heraklion, Crete Greece
| | - Giorgos Kotoulas
- Hellenic Centre for Marine Research, Institute of Marine Biology, Biotechnology and Aquaculture, Gournes Pediados, 71500 Heraklion, Crete Greece
| | - Rania Siam
- Biology Department and YJ-Science and Technology Research Center, American University in Cairo, New Cairo, 11835 Cairo Governorate Egypt
| | - Rehab Z Abdallah
- Biology Department and YJ-Science and Technology Research Center, American University in Cairo, New Cairo, 11835 Cairo Governorate Egypt
| | - Eva C Sonnenschein
- Department of Systems Biology, Technical University of Denmark, Matematiktorvet 301, 2800 Kgs., Lyngby, Denmark
| | - Thierry Cariou
- CNRS & Sorbonne Universités, UPMC Univ Paris 06, Station Biologique, Place Georges Teissier, F-29680 Roscoff, France
| | - Fergal O'Gara
- National University of Ireland-University College Cork, Cork, Ireland ; Curtin University, Biomedical Sciences, Perth, Western Australia Australia
| | - Stephen Jackson
- Department of Systems Biology, Technical University of Denmark, Matematiktorvet 301, 2800 Kgs., Lyngby, Denmark
| | - Sandi Orlic
- Ruđer Bošković Institute, Bijenička cesta 54, 10 000, Zagreb, Croatia
| | - Michael Steinke
- School of Biological Sciences, University of Essex, CO4 3SQ Colchester, Essex UK
| | - Julia Busch
- Institute for Chemistry and Biology of the Marine Environment (ICBM), Carl von Ossietzky University Oldenburg, Schleusenstrasse 1, 26383 Wilhemshaven, Germany
| | - Bernardo Duarte
- Marine and Environmental Sciences Centre, Faculty of Sciences of the University of Lisbon, Campo Grande 1749-016, Lisbon, Portugal
| | - Isabel Caçador
- Marine and Environmental Sciences Centre, Faculty of Sciences of the University of Lisbon, Campo Grande 1749-016, Lisbon, Portugal
| | - João Canning-Clode
- Marine and Environmental Sciences Centre, Faculty of Sciences of the University of Lisbon, Campo Grande 1749-016, Lisbon, Portugal ; Smithsonian Environmental Research Center, 21037 Edgewater, Maryland USA
| | - Oleksandra Bobrova
- Department of Microbiology, Virology and Biotechnology, Odessa National II Mechnikov University, Dvoryanskaya str.2, 65082 Odessa, Ukraine
| | | | | | - Clara Magalhães Loureiro
- InBio/CIBIO, Departamento de Biologia da Universidade dos Açores, 9501-801 Ponta Delgada, Portugal
| | - Gian Marco Luna
- National Research Council, Institute of Marine Sciences (CNR-ISMAR), Castello 2737/f, Arsenale Tesa 104, 30122 Venezia, Italy
| | - Grazia Marina Quero
- National Research Council, Institute of Marine Sciences (CNR-ISMAR), Castello 2737/f, Arsenale Tesa 104, 30122 Venezia, Italy
| | - Carolin R Löscher
- Institute of Microbiology/ GEOMAR, Am Botanischen Garten 1-9, 24118 Kiel, Germany
| | - Anke Kremp
- Marine Research Centre, Finnish Environment Institute, Erik Palmenin aukio 1, 00560 Helsinki, Finland
| | - Marie E DeLorenzo
- NOAA/National Ocean Service/NCCOS/Center for Coastal Environmental Health & Biomolecular Research Charleston, 29412 South Carolina, USA
| | - Lise Øvreås
- Department of Biology, University of Bergen, Thormøhlensgate 53B, 5020 Bergen, Norway
| | - Jennifer Tolman
- LaRoche Research Group, Department of Biology, Dalhousie University, B3H 4R2 Halifax, Nova Scotia Canada
| | - Julie LaRoche
- LaRoche Research Group, Department of Biology, Dalhousie University, B3H 4R2 Halifax, Nova Scotia Canada
| | - Antonella Penna
- Department of Biomolecular Sciences, University of Urbino, Viale Trieste 296, 61121 Pesaro, Italy
| | - Marc Frischer
- University of Georgia's Skidaway Institute of Oceanography, 10 Ocean Science Circle, 31411 Savannah, Georgia USA
| | - Timothy Davis
- NOAA-Great Lakes Environmental Research Laboratory, 4840 S State Road, 48108 Ann Arbor, Michigan USA
| | - Barker Katherine
- National Museum of Natural History, Smithsonian Institution, 10th and Constitution Avenue NW, 20013 Washington, DC USA
| | - Christopher P Meyer
- National Museum of Natural History, Smithsonian Institution, 10th and Constitution Avenue NW, 20013 Washington, DC USA
| | - Sandra Ramos
- CIIMAR, Interdisciplinary Center of Environmental and Marine Research, University of Porto, Rua dos Bragas 289, 4050-123 Porto, Portugal
| | - Catarina Magalhães
- CIIMAR, Interdisciplinary Center of Environmental and Marine Research, University of Porto, Rua dos Bragas 289, 4050-123 Porto, Portugal
| | - Florence Jude-Lemeilleur
- Station Marine d'Arcachon, CNRS & Univ Bordeaux, 2 rue Professeur Jolyet, F-33120 Arcachon, France
| | - Ma Leopoldina Aguirre-Macedo
- Centro de Investigación y de Estudios Avanzados (CINVESTAV), Unidad Mérida, Carretera Antigua a Progreso Km 6 Cordemex, C.P., 97310 Yucatan, Mexico
| | - Shiao Wang
- Department of Biological Sciences, University of Southern Mississippi, 39406 Hattiesburg, Mississippi USA
| | - Nicole Poulton
- Bigelow Laboratory for Ocean Sciences, 60 Bigelow Drive, 04544 East Boothbay, Maine USA
| | - Scott Jones
- Smithsonian Marine Station, 701 Seaway Drive, 34949 Fort Pierce, Florida USA
| | - Rachel Collin
- Smithsonian Tropical Research Institute, Apartado Postal 0843-03092, Balboa Ancon, Panama
| | - Jed A Fuhrman
- Wrigley Institute for Environmental Studies and Department of Biological Sciences, University of Southern California, 90089-0371 Los Angeles, California USA
| | - Pascal Conan
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR7621, Laboratoire d'Océanographie Microbienne, Observatoire Océanologique, F-66651 Banyuls sur Mer, France
| | - Cecilia Alonso
- Microbial Ecology of Aquatic Transitional Systems Research Group, Centro Universitario de la Región Este, Universidad de la República, Ruta 15, km 28.500, Rocha, Uruguay
| | - Noga Stambler
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, 5290002 Ramat-Gan, Israel ; Interuniversity Institute for Marine Sciences in Eilat, 88103 Eilat, Israel
| | - Kelly Goodwin
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Ocean Chemistry and Ecosystems Division, 4301 Rickenbacker Causeway, 33149 Miami, Florida USA
| | - Michael M Yakimov
- Institute for Coastal Marine Environment, IAMC-CNR, Spianata S Raineri, 86 - 98122, Messina, Sicily Italy
| | - Federico Baltar
- Department of Marine Science, University of Otago, PO Box 56, 9054 Dunedin, New Zealand
| | - Levente Bodrossy
- CSIRO Oceans and Atmosphere Flagship, 7000 Hobart, Tasmania Australia
| | - Jodie Van De Kamp
- CSIRO Oceans and Atmosphere Flagship, 7000 Hobart, Tasmania Australia
| | - Dion Mf Frampton
- CSIRO Oceans and Atmosphere Flagship, 7000 Hobart, Tasmania Australia
| | - Martin Ostrowski
- Department of Chemistry and Biomolecular Science, Macquarie University, 2109 Sydney, Australia
| | - Paul Van Ruth
- South Australian Research and Development Institute (SARDI) - Aquatic Sciences, PO Box 120, 5022 Henley Beach, South Australia Australia
| | - Paul Malthouse
- South Australian Research and Development Institute (SARDI) - Aquatic Sciences, PO Box 120, 5022 Henley Beach, South Australia Australia
| | - Simon Claus
- Flanders Marine Institute, InnovOcean site, Wandelaarkaai 7, 8400 Oostende, Belgium
| | - Klaas Deneudt
- Flanders Marine Institute, InnovOcean site, Wandelaarkaai 7, 8400 Oostende, Belgium
| | - Jonas Mortelmans
- Flanders Marine Institute, InnovOcean site, Wandelaarkaai 7, 8400 Oostende, Belgium
| | - Sophie Pitois
- Centre for Environment, Fisheries and Aquaculture Science (CEFAS), Pakefield Road, NR33 0HT Lowestoft, Suffolk UK
| | - David Wallom
- University of Oxford, 7 Keble Road, OX1 3QG Oxford, Oxfordshire UK
| | - Ian Salter
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR7621, Laboratoire d'Océanographie Microbienne, Observatoire Océanologique, F-66651 Banyuls sur Mer, France ; Alfred-Wegener-Institut-Helmholtz-Zentrum für Polar-und Meeresforschung, Am Handelshafen 12, 27570 Bremerhaven, Germany
| | - Rodrigo Costa
- Microbial Ecology and Evolution Research Group, Centre of Marine Sciences, Algarve University, Gambelas Campus, Building 7, Room 2.77, 8005-139 Faro, Portugal
| | - Declan C Schroeder
- Marine Biological Association of the UK, Citadel Hill, PL1 2PB Plymouth, Devon UK
| | - Mahrous M Kandil
- Soil and Water Science Department, Faculty of Agriculture, Alexandria University, El-Shatbi, 21545 Alexandria, Egypt
| | - Valentina Amaral
- Microbial Ecology of Aquatic Transitional Systems Research Group, Centro Universitario de la Región Este, Universidad de la República, Ruta 15, km 28.500, Rocha, Uruguay
| | - Florencia Biancalana
- Marine Biogeochemistry - Argentine Institute of Oceanography, Camino La Carrindanga Km 7,5, 8000 Florida, Bahia Blanca Argentina
| | - Rafael Santana
- Microbial Ecology of Aquatic Transitional Systems Research Group, Centro Universitario de la Región Este, Universidad de la República, Ruta 15, km 28.500, Rocha, Uruguay
| | - Maria Luiza Pedrotti
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR 7093, LOV, Observatoire océanologique, F-Villefranche-sur-Mer, Paris, France
| | - Takashi Yoshida
- Graduate School of Agriculture, Kyoto University, 606-8502 Sakyo-ku, Kyoto Japan
| | - Hiroyuki Ogata
- Graduate School of Agriculture, Kyoto University, 606-8502 Sakyo-ku, Kyoto Japan
| | - Tim Ingleton
- Waters, Wetlands and Coasts, New South Wales Office of Environment and Heritage, Sydney South 1232, 59-61 Goulburn Street, 2001 PO Box A290, Sydney, New South Wales Australia ; Antarctic and Southern Ocean Studies, University of Tasmania, 7004 Hobart, Tasmania Australia
| | - Kate Munnik
- Lwandle Technologies, Black River Park, Fir Road, 7925 Observatory, Cape Town South Africa
| | | | | | - Patricia Wecker
- CRIOBE, USR3278 CNRS-EPHE-UPVD, LabEx Corail, BP 1013-98729 Papetoai Moorea, French Polynesia
| | - Ibon Cancio
- University of the Basque Country, PO Box 644, E-48080 Bilbao, Basque Country Spain
| | - Daniel Vaulot
- CNRS & Sorbonne Universités, UPMC Univ Paris 06, Station Biologique, Place Georges Teissier, F-29680 Roscoff, France
| | - Christina Bienhold
- Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, D-28359 Bremen, Germany ; Alfred-Wegener-Institut-Helmholtz-Zentrum für Polar-und Meeresforschung, Am Handelshafen 12, 27570 Bremerhaven, Germany
| | - Hassan Ghazal
- Polydisciplinary Faculty of Nador, University Mohammed Premier, Selouane, Nador Morocco ; Laboratory of Genetics and Biotechnology, University Mohammed Premier, Oujda, Morocco
| | - Bouchra Chaouni
- Laboratory of Genetics and Biotechnology, University Mohammed Premier, Oujda, Morocco ; Faculty of Sciences of Rabat, University Mohammed Fifth Rabat, Rabat, Morocco
| | - Soumya Essayeh
- Polydisciplinary Faculty of Nador, University Mohammed Premier, Selouane, Nador Morocco
| | - Sara Ettamimi
- Laboratory of Genetics and Biotechnology, University Mohammed Premier, Oujda, Morocco ; Polydisciplinary Faculty of Taza, University Sidi Mohammed Ben Abdallah, Fes, Morocco
| | - El Houcine Zaid
- Faculty of Sciences of Rabat, University Mohammed Fifth Rabat, Rabat, Morocco
| | - Noureddine Boukhatem
- Laboratory of Genetics and Biotechnology, University Mohammed Premier, Oujda, Morocco
| | - Abderrahim Bouali
- Laboratory of Genetics and Biotechnology, University Mohammed Premier, Oujda, Morocco
| | - Rajaa Chahboune
- Polydisciplinary Faculty of Nador, University Mohammed Premier, Selouane, Nador Morocco ; Faculté des Sciences et Techniques de Tanger, Université Abdelmalek Essaâdi, Tanger, Morocco
| | - Said Barrijal
- Faculté des Sciences et Techniques de Tanger, Université Abdelmalek Essaâdi, Tanger, Morocco
| | - Mohammed Timinouni
- Pasteur Institute of Morocco, 1 Place Louis Pasteur, 20100 Casablanca, Morocco
| | - Fatima El Otmani
- Microbiology, Health and Environment Team, Department of Biology, Faculty of Sciences, Chouaib Doukkali University, Rte Ben Maachou, BP 20 Avenue des Facultés, El Jadida, Morocco
| | - Mohamed Bennani
- Pasteur Institute of Morocco, 1 Place Louis Pasteur, 20100 Casablanca, Morocco
| | - Marianna Mea
- Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany
| | - Nadezhda Todorova
- Institute of Biodiversity and Ecosystem Research (IBER), Bulgarian Academy of Sciences, 2 Gagarin Street, 1113 Sofia, Bulgaria
| | - Ventzislav Karamfilov
- Institute of Biodiversity and Ecosystem Research (IBER), Bulgarian Academy of Sciences, 2 Gagarin Street, 1113 Sofia, Bulgaria
| | - Petra Ten Hoopen
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge, Cambridgeshire UK
| | - Guy Cochrane
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge, Cambridgeshire UK
| | - Stephane L'Haridon
- Université de Bretagne Occidentale (UBO, UEB), Institut Universitaire Européen de la Mer (IUEM), Place Nicolas Copernic, F-29280 Plouzané, France
| | - Kemal Can Bizsel
- Dokuz Eylul University (DEU), Institute of Marine Sciences and Technology (IMST), Baku Bulvard, No: 100, Inciralti, 35340 Izmir, Balcova Turkey
| | - Alessandro Vezzi
- Department of Biology, University of Padova, Via Ugo Bassi 58/B, 35121 Padova, Italy
| | - Federico M Lauro
- Singapore Centre for Environmental Life Sciences Engineering, 60 Nanyang Drive, SBS 01N-27, 637551 Singapore, Singapore
| | - Patrick Martin
- Earth Observatory of Singapore, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore, Singapore
| | - Rachelle M Jensen
- Indigo V Expeditions, ONE°15 Marina, #01-01, 11 Cove Drive, Sentosa Cove, 098497 Singapore, Singapore
| | - Jamie Hinks
- Singapore Centre for Environmental Life Sciences Engineering, 60 Nanyang Drive, SBS 01N-27, 637551 Singapore, Singapore
| | - Susan Gebbels
- School of Marine Science and Technology, Newcastle University, Dove Marine Laboratory, Cullercoats, NE30 4PZ Tyne and Wear UK
| | - Riccardo Rosselli
- Department of Biology, University of Padova, Via Ugo Bassi 58/B, 35121 Padova, Italy
| | - Fabio De Pascale
- Department of Biology, University of Padova, Via Ugo Bassi 58/B, 35121 Padova, Italy
| | - Riccardo Schiavon
- Department of Biology, University of Padova, Via Ugo Bassi 58/B, 35121 Padova, Italy
| | - Antonina Dos Santos
- IPMA, Department of Sea and Marine Resources, Avenida de Brasília, s/n, 1449-006 Lisboa, Portugal
| | - Emilie Villar
- Aix Marseille Université, CNRS, IGS UMR 7256, 163 Avenue de Luminy, 13288 Marseille, France
| | - Stéphane Pesant
- PANGAEA - Data Publisher for Earth & Environmental Science, MARUM Center for Marine Environmental Sciences, University Bremen, Hochschulring 18, 28359 Bremen, Germany
| | - Bruno Cataletto
- OGS, National Institute of Oceanography and Experimental Geophysics, Via Auguste Piccard, 54, 34151, Santa Croce, Trieste, Italy
| | - Francesca Malfatti
- OGS, National Institute of Oceanography and Experimental Geophysics, Via Auguste Piccard, 54, 34151, Santa Croce, Trieste, Italy
| | - Ranjith Edirisinghe
- Department of Physical Sciences, Faculty of Applied Sciences, Rajarata University of Sri Lanka, Mihintale, Sri Lanka
| | - Jorge A Herrera Silveira
- Department of Biological Sciences, University of Southern Mississippi, 39406 Hattiesburg, Mississippi USA
| | - Michele Barbier
- Mediterranean Science Commission, 16 Bd de Suisse, 98 000 Monaco, Monaco
| | - Valentina Turk
- Marine Biology Station, National Institute of Biology, Fornače 41, 6330 Piran, Slovenia
| | - Tinkara Tinta
- Marine Biology Station, National Institute of Biology, Fornače 41, 6330 Piran, Slovenia
| | - Wayne J Fuller
- Near East University, TRNC Mersin 10, 99138 Nicosia, Northern Cyprus
| | - Ilkay Salihoglu
- Near East University, TRNC Mersin 10, 99138 Nicosia, Northern Cyprus
| | - Nedime Serakinci
- Near East University, TRNC Mersin 10, 99138 Nicosia, Northern Cyprus
| | | | - Eileen Bresnan
- Phytoplankton Ecology, Marine Scotland Marine Laboratory, 375 Victoria Road, AB11 9DB Aberdeen, Aberdeenshire UK
| | - Juan Iriberri
- University of the Basque Country, PO Box 644, E-48080 Bilbao, Basque Country Spain
| | | | - Edvardsen Bente
- Section for Aquatic Biology and Toxicology, Department of Biosciences, University of Oslo, PO Box 1066, 0316 Blindern, Oslo Norway
| | - Hans Erik Karlsen
- Drøbak Field Station, Marine Biology Research station, Biologiveien 2, 1440 Drøbak, Norway
| | - Peter N Golyshin
- School of Biological Sciences, College of Natural Sciences, Bangor University, LL57 2UW Gwynedd, Bangor UK
| | - Josep M Gasol
- Departament de Biologia Marina i Oceanografia, Institut de Ciències del Mar-CSIC, Pg Marítim de la Barceloneta 37-49, E08003 Barcelona, Catalunya Spain
| | - Snejana Moncheva
- Fridtjof Nansen Institute of Oceanology, First May Street 40, 9000 Varna, Bulgaria
| | - Nina Dzhembekova
- Fridtjof Nansen Institute of Oceanology, First May Street 40, 9000 Varna, Bulgaria
| | - Zackary Johnson
- Nicholas School of the Environment and Biology Department, Duke University, 135 Marine Lab Road, 28516 Beaufort, North Carolina USA
| | - Christopher David Sinigalliano
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Ocean Chemistry and Ecosystems Division, 4301 Rickenbacker Causeway, 33149 Miami, Florida USA
| | - Maribeth Louise Gidley
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Ocean Chemistry and Ecosystems Division, 4301 Rickenbacker Causeway, 33149 Miami, Florida USA ; Cooperative Institute of Marine and Atmospheric Sciences, Rosenstiel School of Marine & Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, 33149 Miami, Florida USA
| | - Adriana Zingone
- Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Napoli, Italy
| | - Roberto Danovaro
- Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Napoli, Italy ; Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy
| | - George Tsiamis
- Department of Environmental and Natural Resources Management, University of Patras, 2 Seferi Street, 301 00 Agrinio, Greece
| | - Melody S Clark
- British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, CB3 0ET Cambridge, Cambridgeshire UK
| | - Ana Cristina Costa
- InBio/CIBIO, Departamento de Biologia da Universidade dos Açores, 9501-801 Ponta Delgada, Portugal
| | - Monia El Bour
- Institut National des Sciences et Technologies de la Mer (INSTM), 28 rue du 2 mars 1934, 2025 Salammbô, Tunisia
| | - Ana M Martins
- InBio/CIBIO, Departamento de Biologia da Universidade dos Açores, 9501-801 Ponta Delgada, Portugal ; Department of Oceanography and Fisheries, University of the Azores, PT-9901-862 Horta, Portugal
| | - R Eric Collins
- University of Alaska Fairbanks, Box 757220, 99775 Fairbanks, Alaska USA
| | | | - Jonathan Martinez
- University of Hawaii at Manoa, Kewalo Marine Laboratory, 41 Ahui St., Honolulu, 96813 Hawaii, USA
| | - Mark J Costello
- Institute of Marine Science, University of Auckland, Private Bag 92019, Auckland, 1142 New Zealand
| | - Linda A Amaral-Zettler
- Marine Biological Laboratory, 7 MBL Street, Woods Hole, 02543 Massachusetts, USA ; Department of Earth, Environmental, and Planetary Sciences, Brown University, 02912 Providence, Rhode Island USA
| | - Jack A Gilbert
- College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China ; Institute for Genomic and Systems Biology, Bioscience Division, Argonne National Laboratory, 9700 South Cass Avenue, 60439 Argonne, Illinois USA ; University of Chicago, 1101 E 57th Street, 60637 Chicago, Illinois USA ; Marine Biological Laboratory, 7 MBL Street, Woods Hole, 02543 Massachusetts, USA
| | - Neil Davies
- Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany ; Gump South Pacific Research Station, University of California Berkeley, BP 244 98728 Moorea, French Polynesia
| | - Dawn Field
- Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany ; University of Oxford, 7 Keble Road, OX1 3QG Oxford, Oxfordshire UK
| | - Frank Oliver Glöckner
- Max Planck Institute for Marine Microbiology, Celsiusstrasse 1, D-28359 Bremen, Germany ; Jacobs University Bremen gGmbH, Campus Ring 1, D-28759 Bremen, Germany
| |
Collapse
|
17
|
Ten Hoopen P, Pesant S, Kottmann R, Kopf A, Bicak M, Claus S, Deneudt K, Borremans C, Thijsse P, Dekeyzer S, Schaap DM, Bowler C, Glöckner FO, Cochrane G. Marine microbial biodiversity, bioinformatics and biotechnology (M2B3) data reporting and service standards. Stand Genomic Sci 2015. [PMID: 26203332 PMCID: PMC4511511 DOI: 10.1186/s40793-015-0001-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Contextual data collected concurrently with molecular samples are critical to the use of metagenomics in the fields of marine biodiversity, bioinformatics and biotechnology. We present here Marine Microbial Biodiversity, Bioinformatics and Biotechnology (M2B3) standards for “Reporting” and “Serving” data. The M2B3 Reporting Standard (1) describes minimal mandatory and recommended contextual information for a marine microbial sample obtained in the epipelagic zone, (2) includes meaningful information for researchers in the oceanographic, biodiversity and molecular disciplines, and (3) can easily be adopted by any marine laboratory with minimum sampling resources. The M2B3 Service Standard defines a software interface through which these data can be discovered and explored in data repositories. The M2B3 Standards were developed by the European project Micro B3, funded under 7th Framework Programme “Ocean of Tomorrow”, and were first used with the Ocean Sampling Day initiative. We believe that these standards have value in broader marine science.
Collapse
Affiliation(s)
- Petra Ten Hoopen
- European Nucleotide Archive, EMBL-EBI, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK
| | - Stéphane Pesant
- PANGAEA - Data Publisher for Earth & Environmental Science, MARUM Center for Marine Environmental Sciences, Universität Bremen, Hochschulring 18 (Cognium), Bremen, POP 330 440, 28359, Germany
| | - Renzo Kottmann
- Max Planck Institute for Marine Microbial Ecology, Microbial Genomics and Bioinformatics Group, Celsiusstr. 1, Bremen, 28359, Germany
| | - Anna Kopf
- Max Planck Institute for Marine Microbial Ecology, Microbial Genomics and Bioinformatics Group, Celsiusstr. 1, Bremen, 28359, Germany ; Jacobs University Bremen gGmbH, Campusring 1, Bremen, 28759, Germany
| | - Mesude Bicak
- Oxford e-Research Centre (OeRC), University of Oxford, 7Keble Road, Oxford, UK
| | - Simon Claus
- Vlaams Instituut voor de Zee, InnovOcean site, Wandelaarkaai 7, Oostende, B-8400, Belgium
| | - Klaas Deneudt
- Vlaams Instituut voor de Zee, InnovOcean site, Wandelaarkaai 7, Oostende, B-8400, Belgium
| | - Catherine Borremans
- IFREMER-Centre de BREST, IDM/SISMER, ZI de la Pointe du Diable, Plouzane, CS 10070, 29280, France
| | - Peter Thijsse
- MARIS BV, Koningin Julianalaan 345 A 2273 JJ, Voorburg, The Netherlands
| | - Stefanie Dekeyzer
- Vlaams Instituut voor de Zee, InnovOcean site, Wandelaarkaai 7, Oostende, B-8400, Belgium
| | - Dick Ma Schaap
- MARIS BV, Koningin Julianalaan 345 A 2273 JJ, Voorburg, The Netherlands
| | - Chris Bowler
- Environmental and Evolutionary Genomics Section, Institut de Biologie de l'Ecole Normale Supérieure (IBENS), CNRS UMR8197 Inserm U1024, Paris, 75005, France
| | - Frank Oliver Glöckner
- Max Planck Institute for Marine Microbial Ecology, Microbial Genomics and Bioinformatics Group, Celsiusstr. 1, Bremen, 28359, Germany ; Jacobs University Bremen gGmbH, Campusring 1, Bremen, 28759, Germany
| | - Guy Cochrane
- European Nucleotide Archive, EMBL-EBI, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK
| |
Collapse
|
18
|
Davies N, Field D, Amaral-Zettler L, Barker K, Bicak M, Bourlat S, Coddington J, Deck J, Drummond A, Gilbert JA, Glöckner FO, Kottmann R, Meyer C, Morrison N, Obst M, Robbins R, Schriml L, Sterk P, Stones-Havas S. Report of the 14th Genomic Standards Consortium Meeting, Oxford, UK, September 17-21, 2012. Stand Genomic Sci 2014. [PMCID: PMC4148987 DOI: 10.4056/sigs.4319681] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
This report summarizes the proceedings of the 14th workshop of the Genomic Standards Consortium (GSC) held at the University of Oxford in September 2012. The primary goal of the workshop was to work towards the launch of the Genomic Observatories (GOs) Network under the GSC. For the first time, it brought together potential GOs sites, GSC members, and a range of interested partner organizations. It thus represented the first meeting of the GOs Network (GOs1). Key outcomes include the formation of a core group of “champions” ready to take the GOs Network forward, as well as the formation of working groups. The workshop also served as the first meeting of a wide range of participants in the Ocean Sampling Day (OSD) initiative, a first GOs action. Three projects with complementary interests – COST Action ES1103, MG4U and Micro B3 – organized joint sessions at the workshop. A two-day GSC Hackathon followed the main three days of meetings.
Collapse
Affiliation(s)
- Neil Davies
- Gump South Pacific Research Station, University of California Berkeley, BP 244 98728 Moorea, French Polynesia
- Biodiversity Institute, Department of Zoology, University of Oxford, The Tinbergen Building, South Parks Road, Oxford, OX1 3PS, United Kingdom
| | - Dawn Field
- Biodiversity Institute, Department of Zoology, University of Oxford, The Tinbergen Building, South Parks Road, Oxford, OX1 3PS, United Kingdom
- Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB, United Kingdom
- Oxford e-Research Centre, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, United Kingdom
- Corresponding Author: Dawn Field ()
| | - Linda Amaral-Zettler
- The Josephine Bay Paul Center for Comparative Molecular Biology and Evolution, Marine Biological Laboratory, Woods Hole, Massachusetts, USA
| | - Katharine Barker
- The Office of the Associate Director for Science, National Museum of Natural History, Smithsonian Institution, MRC-106, 10th and Constitution Avenue N.W. Washington, DC 20560, USA
| | - Mesude Bicak
- Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB, United Kingdom
| | - Sarah Bourlat
- Department of Biological and Environmental Sciences, University of Gothenburg, Box 463, SE-405 30 Gothenburg, Sweden
| | - Jonathan Coddington
- The Office of the Associate Director for Science, National Museum of Natural History, Smithsonian Institution, MRC-106, 10th and Constitution Avenue N.W. Washington, DC 20560, USA
| | - John Deck
- Gump South Pacific Research Station, University of California Berkeley, BP 244 98728 Moorea, French Polynesia
- Berkeley Natural History Museums, 1007 Valley Life Sciences, University of California, Berkeley, CA 94720, USA
| | - Alexei Drummond
- Department of Computer Science, University of Auckland, Auckland, New Zealand
- Allan Wilson Center for Molecular Ecology and Evolution, University of Auckland, Auckland, New Zealand
| | - Jack A. Gilbert
- Institute for Genomic and Systems Biology, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439, USA
- Department of Ecology and Evolution, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA
| | - Frank Oliver Glöckner
- Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen & Jacobs University Bremen, Germany
| | - Renzo Kottmann
- Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen & Jacobs University Bremen, Germany
| | - Chris Meyer
- The Office of the Associate Director for Science, National Museum of Natural History, Smithsonian Institution, MRC-106, 10th and Constitution Avenue N.W. Washington, DC 20560, USA
| | - Norman Morrison
- University of Manchester, Oxford Rd., Manchester, United Kingdom
| | - Matthias Obst
- Department of Biological and Environmental Sciences, University of Gothenburg, Box 463, SE-405 30 Gothenburg, Sweden
| | - Robert Robbins
- University of California San Diego, La Jolla, California USA
| | - Lynn Schriml
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 20742, USA
| | - Peter Sterk
- Oxford e-Research Centre, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, United Kingdom
| | | |
Collapse
|
19
|
Davies N, Field D, Amaral-Zettler L, Clark MS, Deck J, Drummond A, Faith DP, Geller J, Gilbert J, Glöckner FO, Hirsch PR, Leong JA, Meyer C, Obst M, Planes S, Scholin C, Vogler AP, Gates RD, Toonen R, Berteaux-Lecellier V, Barbier M, Barker K, Bertilsson S, Bicak M, Bietz MJ, Bobe J, Bodrossy L, Borja A, Coddington J, Fuhrman J, Gerdts G, Gillespie R, Goodwin K, Hanson PC, Hero JM, Hoekman D, Jansson J, Jeanthon C, Kao R, Klindworth A, Knight R, Kottmann R, Koo MS, Kotoulas G, Lowe AJ, Marteinsson VT, Meyer F, Morrison N, Myrold DD, Pafilis E, Parker S, Parnell JJ, Polymenakou PN, Ratnasingham S, Roderick GK, Rodriguez-Ezpeleta N, Schonrogge K, Simon N, Valette-Silver NJ, Springer YP, Stone GN, Stones-Havas S, Sansone SA, Thibault KM, Wecker P, Wichels A, Wooley JC, Yahara T, Zingone A. The founding charter of the Genomic Observatories Network. Gigascience 2014; 3:2. [PMID: 24606731 PMCID: PMC3995929 DOI: 10.1186/2047-217x-3-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2014] [Accepted: 02/24/2014] [Indexed: 11/10/2022] Open
Abstract
The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms.An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated.
Collapse
Affiliation(s)
- Neil Davies
- Gump South Pacific Research Station, University of California Berkeley, BP 244 98728 Moorea, French Polynesia.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
20
|
Davies N, Meyer C, Gilbert JA, Amaral-Zettler L, Deck J, Bicak M, Rocca-Serra P, Assunta-Sansone S, Willis K, Field D. A call for an international network of genomic observatories (GOs). Gigascience 2012; 1:5. [PMID: 23587188 PMCID: PMC3617453 DOI: 10.1186/2047-217x-1-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2012] [Accepted: 07/12/2012] [Indexed: 11/18/2022] Open
Abstract
We are entering a new era in genomics–that of large-scale, place-based, highly contextualized genomic research. Here we review this emerging paradigm shift and suggest that sites of utmost scientific importance be expanded into ‘Genomic Observatories’ (GOs). Investment in GOs should focus on the digital characterization of whole ecosystems, from all-taxa biotic inventories to time-series ’omics studies. The foundational layer of biodiversity–genetic variation–would thus be mainstreamed into Earth Observation systems enabling predictive modelling of biodiversity dynamics and resultant impacts on ecosystem services.
Collapse
Affiliation(s)
- Neil Davies
- Biodiversity Institute, Department of Zoology, University of Oxford, The Tinbergen Building, South Parks Road, Oxford, OX1 3PS, UK.
| | | | | | | | | | | | | | | | | | | |
Collapse
|
21
|
Krampis K, Booth T, Chapman B, Tiwari B, Bicak M, Field D, Nelson KE. Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community. BMC Bioinformatics 2012; 13:42. [PMID: 22429538 PMCID: PMC3372431 DOI: 10.1186/1471-2105-13-42] [Citation(s) in RCA: 124] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2011] [Accepted: 03/19/2012] [Indexed: 12/04/2022] Open
Abstract
Background A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Results Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Conclusions Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly customized versions from a shared code base. This shared community toolkit enables application specific analysis platforms on the cloud by minimizing the effort required to prepare and maintain them.
Collapse
|
22
|
Holcombe M, Adra S, Bicak M, Chin S, Coakley S, Graham AI, Green J, Greenough C, Jackson D, Kiran M, MacNeil S, Maleki-Dizaji A, McMinn P, Pogson M, Poole R, Qwarnstrom E, Ratnieks F, Rolfe MD, Smallwood R, Sun T, Worth D. Modelling complex biological systems using an agent-based approach. Integr Biol (Camb) 2011; 4:53-64. [PMID: 22052476 DOI: 10.1039/c1ib00042j] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Many of the complex systems found in biology are comprised of numerous components, where interactions between individual agents result in the emergence of structures and function, typically in a highly dynamic manner. Often these entities have limited lifetimes but their interactions both with each other and their environment can have profound biological consequences. We will demonstrate how modelling these entities, and their interactions, can lead to a new approach to experimental biology bringing new insights and a deeper understanding of biological systems.
Collapse
Affiliation(s)
- Mike Holcombe
- Department of Computer Science, University of Sheffield, UK
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
23
|
Thiele G, Bicak M, Grierson H, Lai P, Purtilo D. Antibody reactivity to a synthetic peptide (P62) of the Epstein-Barr nuclear antigen in sera of patients with X-linked lymphoproliferative syndrome. J Immunol Methods 1987; 100:249-59. [PMID: 3036951 DOI: 10.1016/0022-1759(87)90196-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
An enzyme-linked immunosorbent assay (ELISA) was used to measure IgG antibody titers against a synthetic peptide whose sequence was derived from the glycine-alanine repeating region of Epstein-Barr virus nuclear associated antigen 1 (EBNA-1). Antibody titers were determined in sera from 15 normal subjects, sera from 21 normal male siblings of X-linked lymphoproliferative syndrome (XLP) patients, from 20 XLP patients comprising a total of 42 samples, and ten samples before and ten samples after gamma-globulin therapy in ten patients with XLP. Data analysis demonstrated that while there are differences between the ELISA and ACIF, they appear to measure a similar response as demonstrated by their correlation coefficient (0.77) and the GMT to EBNA observed by both methods. No cross-reactivity of cytomegalovirus antibodies to the EBNA-1 peptide was observed by immunoblotting, ELISA or ACIF using adsorption against AD-169 infected MRC-5 cells. However, non-specific binding was observed if samples were not pre-incubated in a 10% goat serum PBS-Tween 20 solution. This pre-treatment removed the non-specific binding that falsely elevated the GMT in approximately 15% of both normal and XLP samples in ELISA. The ELISA system appears to be a sensitive, reproducible and objective test that may be useful for assessing the antibody response of patients to the EBNA-1 protein.
Collapse
|