Evidence map›Paper›PMID 29116224›Full record

ArticleScientific reports2017

Comparison of Transcriptomic Platforms for Analysis of Whole Blood from Ebola-Infected Cynomolgus Macaques.

Emily Speranza, Louis A Altamura, Kirsten Kulcsar, Sandra L Bixler, Cynthia A Rossi, Randal J Schoepp, Elyse Nagle, William Aguilar, Christina E Douglas, Korey L Delp and 4 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Transcriptional Profiling of Filovirus-Infected Nonhuman Primate Samples.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  5. Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.The Journal of clinical endocrinology and metabolism · 2024
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. mBio · 2021
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 2 institutions in 1 country.

Emily SperanzaDepartment of Microbiology, Bioinformatics Program, National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, United States.
Louis A AltamuraDiagnostic Systems Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.ORCID 0000-0001-7389-295X
Kirsten KulcsarCenter for Genome Sciences, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Sandra L BixlerMolecular and Translational Sciences Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Cynthia A RossiDiagnostic Systems Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Randal J SchoeppDiagnostic Systems Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Elyse NagleCenter for Genome Sciences, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
William AguilarDiagnostic Systems Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Christina E DouglasDiagnostic Systems Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Korey L DelpDiagnostic Systems Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Timothy D MinogueDiagnostic Systems Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.
Gustavo PalaciosCenter for Genome Sciences, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States.ORCID 0000-0001-5062-1938
Arthur J GoffVirology Division, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD, United States. arthur.j.goff.civ@mail.mil.
John H ConnorDepartment of Microbiology, Bioinformatics Program, National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, United States. jhconnor@bu.edu.ORCID 0000-0002-8867-7256
United States Army Medical Research Institute of Infectious Diseases · USBoston University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ebola virus disease (EVD) is a serious illness with mortality rates of 20-90% in various outbreaks. EVD is characterized by robust virus replication and strong host inflammatory response. Analyzing host immune responses has increasingly involved multimodal approaches including transcriptomics to profile gene expression. We studied cynomolgus macaques exposed to Ebola virus Makona via different routes with the intent of comparing RNA-Seq to a NanoString nCounter codeset targeting 769 non-human primate (NHP) genes. RNA-Seq analysis of serial blood samples showed different routes led to the same overall transcriptional response seen in previously reported EBOV-exposed NHP studies. Both platforms displayed a strong correlation in gene expression patterns, including a strong induction of innate immune response genes at early times post-exposure, and neutrophil-associated genes at later time points. A 41-gene classifier was tested in both platforms for ability to cluster samples by infection status. Both NanoString and RNA-Seq could be used to predict relative abundances of circulating immune cell populations that matched traditional hematology. This demonstrates the complementarity of RNA-Seq and NanoString. Moreover, the development of an NHP-specific NanoString codeset should augment studies of filoviruses and other high containment infectious diseases without the infrastructure requirements of RNA-Seq technology.

Indexed as

TranscriptomeAnimalsDisease Models, AnimalEbolavirusHemorrhagic Fever, EbolaHumansImmunity, InnateImmunity, MucosalMacaca fascicularisSequence Analysis, RNASignal TransductionVirulence

Identifiers

PMID29116224
PMCPMC5676990
OpenAlexW2765655348

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.