Evidence map›Paper›PMID 30699342›Full record

ArticleCell reports2019

A 20-Gene Set Predictive of Progression to Severe Dengue.

Makeda Robinson, Timothy E Sweeney, Rina Barouch-Bentov, Malaya Kumar Sahoo, Larry Kalesinskas, Francesco Vallania, Ana Maria Sanz, Eliana Ortiz-Lasso, Ludwig Luis Albornoz, Fernando Rosso and 4 more

Abstract read
In one paragraph

Article in Cell reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

50 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Article
  9. Article
  10. Dengue and severe dengue.Clinical microbiology reviews · 2025
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Proceedings of the 7Vaccines · 2025
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  17. Article
  18. Review
  19. Unraveling flavivirus pathogenesis: from bulk to single-cell RNA-sequencing strategies.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2024
    Review
  20. Review
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.

Makeda RobinsonDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA.
Timothy E SweeneyInstitute for Immunity, Transplantation, and Infection, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
Rina Barouch-BentovDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
Malaya Kumar SahooDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Larry KalesinskasInstitute for Immunity, Transplantation, and Infection, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
Francesco VallaniaInstitute for Immunity, Transplantation, and Infection, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
Ana Maria SanzClinical Research Center, Fundación Valle del Lili, Cali, Colombia.
Eliana Ortiz-LassoPathology and Laboratory Department, Fundación Valle del Lili, Cali, Colombia.
Ludwig Luis AlbornozPathology and Laboratory Department, Fundación Valle del Lili, Cali, Colombia.
Fernando RossoClinical Research Center, Fundación Valle del Lili, Cali, Colombia; Department of Internal Medicine, Division of Infectious Diseases, Fundación Valle del Lili, Cali, Colombia.
Jose G MontoyaDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
Benjamin A PinskyDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Purvesh KhatriInstitute for Immunity, Transplantation, and Infection, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, CA, USA. Electronic address: pkhatri@stanford.edu.
Shirit EinavDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA. Electronic address: seinav@stanford.edu.

Funding

Using a tonsil organoid system to probe conditions for the induction of protective antibody and T cell responses to influenza.U19AI057229 · NIAID · STANFORD UNIVERSITY · PI Mark Morris Davis · 2003 to 2026
$88.5M
Translational Incubator CoreU19AI109662 · NIAID · STANFORD UNIVERSITY · PI GLENN, JEFFREY S · 2014 to 2019
$28.6M
POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Giant MagnetoResistive (GMR) Sensors for Measuring Influenza VaccineR01AI125197 · NIAID · STANFORD UNIVERSITY · PI UTZ, PAUL JOSEPH, WANG, SHAN X. · 2016 to 2021
$5.0M
Stanford Career Development Program in Omics of Lung DiseasesK12HL120001 · NHLBI · STANFORD UNIVERSITY · PI NICOLLS, MARK ROBERT, RABINOVITCH, MARLENE · 2013 to 2017
$1.3M
NHLBI NIH HHS K12 HL120001NIAID NIH HHS R01 AI125197NIAID NIH HHS U19 AI057229NIAID NIH HHS U19 AI109662NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

There is a need to identify biomarkers predictive of severe dengue. Single-cohort transcriptomics has not yielded generalizable results or parsimonious, predictive gene sets. We analyzed blood samples of dengue patients from seven gene expression datasets (446 samples, five countries) using an integrated multi-cohort analysis framework and identified a 20-gene set that predicts progression to severe dengue. We validated the predictive power of this 20-gene set in three retrospective dengue datasets (84 samples, three countries) and a prospective Colombia cohort (34 patients), with an area under the receiver operating characteristic curve of 0.89, 100% sensitivity, and 76% specificity. The 20-gene dengue severity scores declined during the disease course, suggesting an infection-triggered host response. This 20-gene set is strongly associated with the progression to severe dengue and represents a predictive signature, generalizable across ages, host genetic factors, and virus strains, with potential implications for the development of a host response-based dengue prognostic assay.

Indexed as

Disease ProgressionCohort StudiesComputer SimulationHumansKiller Cells, NaturalNatural Killer T-CellsReproducibility of ResultsSevere Denguebiomarkersmulti-coherent analysisprognosticssevere denguetranscriptomics

Identifiers

PMID30699342
PMCPMC6352713

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.