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Record W4390198600 · doi:10.1002/alz.079619

GABA transporters gene expression associates with [<sup>18</sup>F]FDG‐PET signal in regions typically hypometabolic in Alzheimer’s disease

2023· article· en· W4390198600 on OpenAlexaff
Giovanna Carello‐Collar, João Pedro Ferrari‐Souza, Luiza Santos Machado, Guilherme Povala, Christian Limberger, Tharick A. Pascoal, Eduardo R. Zimmer

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsTransporterPositron emission tomographyNeuroimagingNeuroscienceStandardized uptake valueInternal medicineGene expressionEndocrinologyBiologyMedicinePsychologyGeneBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background It is suggested that the [18F]fluorodeoxyglucose(FDG)‐PET signal reflects astrocyte and neuronal activity, with the excitatory glutamate uptake by astrocytes as the trigger for brain glucose metabolism. The inhibitory neurotransmitter γ‐aminobutyric acid (GABA) is taken up by neurons and astrocytes through the GABA transporters (GAT) 1 and 3. However, its role in the [18F]FDG‐PET signal in healthy aging and Alzheimer’s disease (AD) remains poorly investigated. Thus, we aimed to explore associations between neuronal and astrocytic GABA transporters gene expression with [18F]FDG‐PET in cognitively unimpaired (CU) and AD individuals. Method We obtained [18F]FDG‐PET imaging data of CU and AD from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (Table 1). GAT1 and GAT3 gene expression in the brain was obtained from the Allen Brain Atlas (Table 1, Figure 1). We extracted SUVr (pons as reference region) and mRNA values using the RMINC package and performed Pearson’s correlation to test the association between [18F]FDG‐PET and GABA transporters mRNA (p‐value < 0.05). Result In brain regions typically hypometabolic in AD, we observed a strong positive association of [18F]FDG‐PET SUVr with GAT1 and GAT3 gene expression in CU (GAT1: r = 0.93; p < 0.0001; Figure 2A, GAT3: r = 0.94; p < 0.0001; Figure 2B) and AD individuals (GAT1: r = 0.9; p < 0.0001; Figure 2A, GAT3: r = 0.92; p < 0.0001; Figure 2B). By contrast, in brain regions typically resilient, we found a weak correlation with CU individuals (GAT1: r = 0.32; p = 0.016; Figure 2C, GAT3: r = 0.26; p = 0.04; Figure 2D) and no significant correlation in AD patients (GAT1: r = 0.24; p = 0.07; Figure 2C, GAT3: r = 0.24; p = 0.059; Figure 2D). Conclusion Our results demonstrate a significant strong positive association between [18F]FDG‐PET SUVr and GABA transporters gene expression in CU and AD in hypometabolic regions. These findings suggest that GABA transporters are involved with brain glucose metabolism in regions classically vulnerable to AD pathology.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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

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 head0.075
GPT teacher head0.324
Teacher spread0.250 · 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

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