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Record W7117108335 · doi:10.1002/alz70855_103091

Hypothalamic and metabolic alterations at a pre‐symptomatic stage of Alzheimer's Disease

2025· article· en· W7117108335 on OpenAlexaff
Pablo Valderrama‐Carmona, Federico Pratesi, Paule E. H. M’Bra, Marta Turri, Anne Aumont, Marian Mayhue, Andres Villegas‐Lanau, Rafael Posada‐Duque, Karl J. L. Fernandes

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsQ & T ResearchUniversité de MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsDiseaseTranscriptomeImmune systemPeripheralMetabolic syndromeHypothalamusFight-or-flight responseStage (stratigraphy)

Abstract

fetched live from OpenAlex

BACKGROUND: The hypothalamus is the brain's center for metabolic regulation. It controls energy homeostasis, adiposity and glucose metabolism, acting as a link between the brain and peripheral tissues. Alzheimer's Disease (AD) is a multifactorial neurodegenerative disease. Besides the well-known cognitive impairment, patients often exhibit metabolic disturbances, including insulin resistance, dyslipidemia and body-weight disorders. Interestingly, these comorbidities have been associated with hypothalamic dysfunction; however, the role of the hypothalamus in AD remains largely unexplored. In this study, we aimed to characterize early hypothalamic cellular changes and identify potentially associated metabolic alterations during the pre-symptomatic stage of AD using the 3xTg-AD mouse model. METHOD: To characterize hypothalamic cellular changes at a presymptomatic stage we performed single-cell RNA sequencing (scRNAseq) on microdissected hypothalami from 3-months old WT and 3xTg-AD mice. Bioinformatic analysis were conducted in R. To gain further insight into metabolic-related hypothalamic functions we performed body-weight and blood glucose measurements, analyzed body mass composition and weighted peripheral metabolic organs of 3-months old 3xTg-AD mice. Additionally, we conducted a pilot snRNAseq experiment using post-mortem human hypothalami from control, familial (FAD) and sporadic (SAD) AD patients (n = 1) in collaboration with the Brainbank of the University of Antioquia. RESULT: We identified presymptomatic transcriptomic changes in hypothalamic endothelial cells in 3xTg-AD mice. These changes were primarily observed at the capillary level and were related to immune and stress response. At 3-months, 3xTg-AD mice exhibited sex-specific metabolic alterations. While females showed significant increases in body weight, glucose levels, fat and pancreas mass, males exhibited significant decreases in the same parameters compared to WT mice. The pilot snRNAseq experiment with human samples was successful, obtaining ∼10000 nuclei/patient, comprising the different brain cell types, with large populations of neurons and oligodendrocytes identified. CONCLUSION: Our results reveal early transcriptomic changes in hypothalamic endothelial cells of 3xTg-AD mice, related to immune and stress responses. Furthermore, peripheral metabolic alterations were also observed at this stage, suggesting a sex-specific effect. We propose that hypothalamic dysfunction may drive these metabolic alterations and play a key role in AD. Further analyses are underway to confirm this association using mouse and human samples.

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
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.312
Teacher spread0.289 · 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 routes1
Has abstractyes

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