MétaCan
Menu
Back to cohort
Record W3009361371 · doi:10.1161/circ.141.suppl_1.p201

Abstract P201: Prospective Associations of Innate and Adaptive Immune Cell Subsets in Peripheral Blood With Incident Myocardial Infarction

2020· article· en· W3009361371 on OpenAlexaff
Nels C. Olson, Colleen M. Sitlani, Margaret F. Doyle, Sally A. Huber, Alan Landay, Russell P. Tracy, Bruce M. Psaty, Joseph A. Delaney

Bibliographic record

VenueCirculation · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAtherosclerosis and Cardiovascular Diseases
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineMyocardial infarctionImmune systemImmunologyCohortProportional hazards modelInternal medicineUnstable anginaProspective cohort studyAcquired immune systemAnginaT cellOncology

Abstract

fetched live from OpenAlex

Introduction: Activation of cell-mediated immunity promotes atherogenesis in animal models and correlates with advanced atherosclerosis and coronary syndromes in humans. Whether innate and adaptive immune cell subsets are risk factors for clinical cardiovascular disease (CVD) events is unknown. Hypothesis: Circulating proportions of pro-inflammatory (Th1, Th17), anti-inflammatory (Th2, T regulatory), and differentiated (naive, memory, and senescent) CD4 + T cells are risk factors for myocardial infarction (MI) and angina. We explored other cell types in secondary analyses. Methods: We performed a case-cohort study within the Multi-Ethnic Study of Atherosclerosis (MESA) and the Cardiovascular Health Study (CHS) (n=2,162). Case outcomes were incident MI and incident angina (n=869 total cases) compared to a cohort random sample (n=1,293). Immune cell phenotypes (n=34, including monocytes, T cells, and B cells) were measured by flow cytometry using cell samples cryopreserved at the MESA baseline and CHS Year 11 exams. Associations of immune cell phenotypes with MI and a composite outcome of incident MI or incident angina (MI-angina) were evaluated using Cox proportional hazards models, with sampling weights and CVD risk factor adjustment, over a median follow-up time of 9.3 years. We analyzed results separately in each cohort and in a combined-cohort meta-analysis. Based on previous findings, we specified seven CD4 + T cell populations as primary hypotheses (stated above). In Bonferroni-adjusted secondary analyses, we investigated associations of 27 additional cell phenotypes measured in the study. Results: In our primary hypotheses, the associations of Th1, Th2, T regulatory, naive, memory, and senescent CD4 + cells with incident MI were moderate and not statistically significant in either cohort individually or in combined-cohort analyses (hazards ratios ranging from 0.88 for naive cells (95% confidence interval (CI): 0.73, 1.06) to 1.15 for Th2 cells (95 CI: 0.96,1.38); all P-values >0.05). Associations of these cells with the composite endpoint of incident MI-angina were also null (hazards ratios ranging from 0.90 (Th1 cells; 95% CI: 0.74, 1.11) to 1.11 (Th17 cells; 95% CI: 0.91, 1.37); all P-values >0.10). In exploratory secondary analyses that investigated subsets of CD14 + monocytes, CD8 + T cells, and CD19 + B cells, no significant relationships with incident MI or MI-angina were observed. Conclusions: In a study of modest sample size, these results suggest that variation in the proportions of several lymphocyte and monocyte subsets measured in peripheral blood are only weakly, if at all, associated with incident MI or incident angina. Given the literature on the roles of cellular immunity in atherosclerosis, large prospective studies evaluating the relationships of immune cell subsets with the progression of atherosclerosis are warranted.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.204
Teacher spread0.190 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCirculationSame topicAtherosclerosis and Cardiovascular DiseasesFrench-language works237,207