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Record W3041489599 · doi:10.1172/jci137536

Dengue virus induces PCSK9 expression to alter antiviral responses and disease outcomes

2020· article· en· W3041489599 on OpenAlexaff
Esther S. Gan, Hwee Cheng Tan, Duyen Huynh Thi Le, Trieu Trung Huynh, Bridget Wills, Nabil G. Seidah, Eng Eong Ooi, Sophie Yacoub

Bibliographic record

VenueJournal of Clinical Investigation · 2020
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsMontreal Clinical Research Institute
FundersNational Medical Research CouncilMedical Research CouncilDuke-NUS Medical SchoolWellcome TrustWellcome
KeywordsDengue virusDengue feverPCSK9ViremiaVirologyBiologyAntibody-dependent enhancementCholesterolImmunologyLDL receptorFlavivirusVirusLipoproteinEndocrinology

Abstract

fetched live from OpenAlex

Dengue virus (DENV) infection requires cholesterol as a proviral factor, although statin treatment did not show antiviral efficacy in patients with dengue. Here, we show that DENV infection manipulated cholesterol metabolism in cells residing in low-oxygen microenvironments (hypoxia) such as in the liver, spleen, and lymph nodes. DENV infection induced expression of proprotein convertase subtilisin/kexin type 9 (PCSK9), which reduces low-density lipoprotein receptor (LDLR) recycling and hence cholesterol uptake. We found that, whereas LDLR uptake would have distributed cholesterol throughout the various cell compartments, de novo cholesterol synthesis enriched this lipid in the endoplasmic reticulum (ER). With cholesterol enrichment in the ER, ER-resident STING and type I IFN (IFN) activation was repressed during DENV infection. Our in vitro findings were further supported by the detection of elevated plasma PCSK9 levels in patients with dengue with high viremia and increased severity of plasma leakage. Our findings therefore suggest that PCSK9 plays a hitherto unrecognized role in dengue pathogenesis and that PCSK9 inhibitors could be a suitable host-directed treatment for patients with dengue.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.114
GPT teacher head0.418
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations73
Published2020
Admission routes1
Has abstractyes

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