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Abstract 4359925: Brain-Derived Exosomal Biomarkers of Neuroinflammation and Brain Iron Deficiency in Infants with Critical Congenital Heart Disease: A Pilot Study

2025· article· en· W4415791034 on OpenAlexaffabout
Kristin M. Elgersma, Zia L. Maxim, Manjula Munirathinam, Shabnam Peyvandi, Mike Seed, Seema Mital, Michael Georgieff, Phu V. Tran

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsNeuroinflammationFerritinHeart diseaseInflammationDiseaseBiomarkerBiobankHeart failure

Abstract

fetched live from OpenAlex

Background: Up to 50% of infants with critical congenital heart disease (CCHD) experience neurodevelopmental delay, potentially due in part to neuroinflammation and iron deficiency. These factors contribute to long-term neurodevelopmental disorders in preterm infants, but it is unclear whether similar mechanisms occur in CCHD and thus represent intervention targets. To address knowledge gaps about brain inflammation and iron status in CCHD, we developed a novel, non-invasive method to isolate brain-derived exosomes (BDEs) from peripheral blood using contactin-2 (CNTN2), a brain-specific glycoprotein. BDEs cross the blood-brain barrier and carry biomarkers reflecting their origin. Aim: Determine the feasibility of isolating plasma BDEs and assessing therein markers for neuroinflammation and iron status in infants with CCHD. Methods: This pilot study included infants ≤6 months old with transposition of the great arteries (TGA) or hypoplastic left heart syndrome (HLHS), using plasma from the Heart Centre Biobank (Toronto). CNTN2+ BDEs were isolated via size exclusion spin columns, enriched by immunoprecipitation, and analyzed for size, concentration, and integrity. BDE contents were assessed with a validated (for clinical use) panel of cytokines, chemokines, iron, and brain biomarkers. Analysis included data visualization and Pearson’s correlation matrix to explore relationships and compare results to published BDE values of healthy newborns from mothers with or without overweight/obesity (OWO). Results: Infants (n=11; 5 HLHS, 6 TGA) were 55% female and mean age 3.7 months. Compared to healthy newborns (Fig. 1), infants with CCHD had higher ferritin and lower transferrin and S100B. While peripheral CRP (850.16 ± 637.94 ng/mL) was elevated, BDE CRP was lower compared to healthy newborn groups. BDE Ferritin was positively correlated (Fig. 2) with PARK7, a cell metabolism marker, and TfR correlated with S100B (reflects astrocytosis). Conclusions: Assessing BDE biomarkers in infants with CCHD is feasible. In this small cohort, preliminary results showed that CCHD iron biomarker patterns aligned with those in newborns of mothers with OWO, an inflammatory condition that sequesters iron as ferritin. Further research is warranted to determine if patterns of low BDE CRP (amid systemic inflammation), reduced S100B, and higher BDNF (a nerve growth factor), are replicated in larger CCHD cohorts, and if BDE inflammation and iron biomarkers can indicate neurodevelopmental deficits.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.017
GPT teacher head0.282
Teacher spread0.266 · 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
Published2025
Admission routes2
Has abstractyes

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