MétaCan
Menu
Back to cohort
Record W4319008012 · doi:10.1161/str.54.suppl_1.wp223

Abstract WP223: Identification Of Cerebral Amyloid Angiopathy With A Leukocyte Gene Expression Profile

2023· article· en· W4319008012 on OpenAlexaff
Danielle Munsterman, Sarina Falcione, Rebecca Long, Twinkle Joy, Mike Clarke, Andrew E. Beaudin, Richard Camicioli, Eric E. Smith, Glen C. Jickling

Bibliographic record

VenueStroke · 2023
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsCerebral amyloid angiopathyMedicineGene expressionImmunologyImmune systemFold changeGenePathologyBiologyDiseaseDementiaGenetics

Abstract

fetched live from OpenAlex

Introduction: Cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease featuring beta-amyloid deposits within the cerebral vasculature. It is a major cause of cognitive decline and intracerebral hemorrhage in the elderly. This study evaluated whether gene expression profiles in peripheral blood can differentiate patients with CAA from vascular risk factor and healthy controls. Methods: In 27 patients with CAA blood cell gene expression was compared to 55 controls. Total RNA was isolated from PAXgene tubes and measured by RNA sequencing. Differentially expressed genes between CAA and controls were identified by ANOVA adjusting for age and sex. Functional pathway analysis identified pathways associated with CAA. A prediction model to distinguish CAA from controls was developed using linear discriminant analysis with feature selection by forward selection. Model performance was evaluated by 10-fold leave-one-out cross validation. Results: 686 differentially expressed genes were identified (p<0.05, fold change >|1.2|), of interest ADAM15, CAMK1D, CAP1 and TGFB1 . Canonical pathway analysis identified cell movement of phagocytes, activation of phagocytes, CREB, degranulation of leukocytes, immune response of cells, inflammatory response, and IL-23 signaling. A 24 gene panel differentiated patients with CAA from controls with >95% sensitivity and specificity. The identified genes reveal differences in immune system regulation in patients with CAA compared to vascular risk factor and healthy control patients. Differences identified include a potential shift in beta-amyloid uptake by phagocytes ( TGFB1, CREB, CAMK1D ), an increase in vascular extracellular matrix disruption ( ADAM15, CAP1 ), and a possible alteration in amyloid precursor processing ( BRI3BP, SORCS3 ). Conclusion: Differences in peripheral leukocyte gene expression are present in patients with CAA compared to control patients. These relate to differences in immune activation and signaling associated with CAA. The differences in blood cell gene expression shows promise to distinguish CAA from controls, though further evaluation in larger cohorts is required to further evaluate potential diagnostic utility of this gene expression profile.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.281
Teacher spread0.261 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueStrokeSame topicIntracerebral and Subarachnoid Hemorrhage ResearchFrench-language works237,207