MétaCan
Menu
← Back to cohort
Record W4394598478 · doi:10.1101/2024.04.05.24305379

Multimorbidity increases susceptibility to myocardial injury via dysregulated cardiac macrophage activation and the development of a cardiomyopathy phenotype

2024· preprint· en· W4394598478 on OpenAlexaff
Florence Lai, Adewale Adebayo, Sophia Sheikh, Marius Roman, Lathishia Joel‐David, Hardeep Aujla, Tom Chad, Kristina Tomkova, Shameem Ladak, Gianluigi Condorelli, Mustafa Zakkar, Charles U. Solomon, Marcin Woźniak, Gavin J. Murphy

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsSmiths Detection (Canada)
FundersUniversity of LeicesterNational Institute for Health and Care ResearchBritish Heart FoundationGlaxoSmithKline
KeywordsImmune systemHomeostasisTerm (time)MedicineIntensive care medicineImmunologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background This study investigated mechanisms underlying the association between multimorbidity (MM) and increased susceptibility to myocardial injury and organ failure following cardiac surgery. Methods K-means clustering was performed using data from five cardiac surgery cohorts with high prevalence of MM. The resulting Clusters were explored using single nuclei RNA sequencing (snRNAseq) of atrial biopsies collected at surgery from one of the study cohorts. Mechanisms were validated using causal inference methods in UK Biobank and aged cardiomyocytes exposed to ischaemia reperfusion injury (IRI) in vitro . Results K-means clustering using pre-surgery biomarkers of haematopoietic, cardiac, metabolic, liver, and renal disease identified two MM clusters. Cluster 1, characterised by higher baseline troponin I and interleukin-6 values, iron deficiency, anaemia, and immunological ageing, demonstrated significantly higher rates of myocardial injury (66% versus 52%) and multiple organ dysfunction (81% versus 57%) relative to Cluster 2. snRNAseq data from Cluster 1 demonstrated inflammageing characterised by enrichment for cardiomyopathy networks in cardiomyocytes, NF-kB and IL2 in monocyte derived macrophages (MDM), and pro-fibrotic and redox inflammation signaling in tissue resident macrophages (TRM). Cluster 2 showed enrichment for translation, type 1 inflammation, and immune activation in cardiomyocytes, and acute-phase immune responses in MDM and TRM. In UK Biobank, genetic modification of genes differentially expressed between clusters altered 90-day mortality post-surgery. Gene silencing of key regulatory nodes enriched in Cluster 1 cardiomyocytes including PDE1c (Ca 2+ homeostasis) and SNAI1 (TGFβ-SMAD), attenuated cardiomyocyte de-differentiation and susceptibility to IRI in vitro . Conclusions Inflammageing associated cardiomyocyte dedifferentiation represents a target for myocardial protection in people with MM. Study Schematic MaRACAS, the Observational Case Control Study to Identify the Role of MV and MV Derived Micro-RNA in Post CArdiac Surgery AKI, REVAKI-2, Revatio® for the Prevention of AKI -2 trial, REDWASH, Red Cell washing for the Prevention of Organ Injury after Cardiac Surgery Trial, OBCARD, the Case Control Study to Identify the Role of Epigenetic Regulation of Genes Responsible for Energy Metabolism and Mitochondrial Function in the Obesity Paradox in Cardiac Surgery, COPTIC, the Coagulation and Platelet Laboratory Testing in Cardiac Surgery study.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.278
Teacher spread0.263 · 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 designBench or experimental
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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuemedRxiv→Same topicCardiac, Anesthesia and Surgical Outcomes→French-language works237,207→