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Effect of interleukin 1b inhibition with canakinumab on inflammation and viral persistence in people with human immunodeficiency virus

2024· article· en· W4403814796 on OpenAlexaff
Matthew S. Durstenfeld, Steven G Deeks, Shady Abohashem, Joseph M. Rocco, Katherine M. Bricker, Amélie Pagliuzza, Dapeng Li, Yifei Ma, Irini Sereti, Nicolas Chomont, Ahmed Tawakol, Priscilla Y. Hsue

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsUniversité de Montréal
FundersNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood Institute
KeywordsMedicineCanakinumabPersistence (discontinuity)InflammationVirologyImmunologyHuman immunodeficiency virus (HIV)Internal medicineAnakinraDisease

Abstract

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Abstract Introduction Effectively treated people with HIV (PWH) have elevated risk of cardiovascular disease (CVD). Inflammatory markers are predictive of CVD and mortality among PWH. The role of the myeloid system in driving inflammation and atherosclerosis has been recently recognized. Canakinumab (a monoclonal antibody to IL-1β) reduces inflammation and CVD events among people with elevated hsCRP after myocardial infarction without HIV. We evaluated the impact of IL-1β inhibition using canakinumab on HIV parameters, inflammation, HIV persistence markers, arterial inflammation, and hematopoietic activity in PWH. Methods PWH on effective ART who had CVD or were at risk for CVD were randomized 2:1 to receive 150 mg of canakinumab subcutaneously or matched placebo at weeks 0 and 12. Arterial inflammation and bone marrow metabolic activity were assessed using F18 FDG PET/CT at baseline and week 18. T cell and monocyte activation were evaluated using multiparameter spectral cytometry. The viral reservoir was quantified using Tat/rev Induced Limiting Dilution Assay (TILDA), HIV DNA and cell-associated RNA. The primary endpoints were change in CD4 and CD8 count. We assessed group effects over time using linear mixed effects models. Results 33 individuals were randomized (median age of 60 years old (IQR 57.5, 64.5) and 94% male); 25 received canakinumab and 8 received placebo. There were no significant differences at baseline. As expected, IL-1β increased among those treated with canakinumab at weeks 4- 24 (p<0.01 for each) and returned to baseline at week 36. There was one death from sepsis in an individual aged 84 with CVD and poorly controlled diabetes who received canakinumab. There were no significant changes in CD4 count, CD8 count, platelet count, creatinine, AST, or ALT by group. Treatment was not associated with a greater reduction in arterial inflammation in the most diseased segment compared to placebo (-6.9%; 95% CI -30.4 to 24.5%; p=0.62). However, bone marrow metabolic activity decreased in the canakinumab group versus placebo (-14.4%, 95% CI -26.5% to -0.2%; p=0.047). Treatment was associated with increased CD163 expression on monocytes at weeks 24 (p=0.03) and 36 (p<0.001), and lower caspase activity at week 36 (p=0.02). There was expansion of anti-inflammatory CD16+ patrolling monocytes that co-express CD163+CX3CR1+ and a decrease in pro-inflammatory CD16+ patrolling monocytes that are Caspase1+CCR2+. Treatment was not associated with differences in hsCRP, IL-6, IL-16, IL-18, MCP-1, sCD14, sCD163, T cell subsets, NK cell subsets, or viral persistence markers. Conclusion Among treated PWH, targeted inhibition of IL-1β using canakinumab results in decreased bone marrow metabolic activity and a shift toward anti-inflammatory monocyte populations. These findings shed light on mechanisms underlying how targeted IL-1β inhibition using canakinumab prevents CVD events by altering monocyte populations and reducing systemic inflammation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.289
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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