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Record W4213061596 · doi:10.1186/s13195-022-00961-5

Altered central and blood glutathione in Alzheimer’s disease and mild cognitive impairment: a meta-analysis

2022· review· en· W4213061596 on OpenAlexafffund
Jinghan Jenny Chen, Mathura T. Thiyagarajah, Jianmeng Song, Clara Chen, Nathan Herrmann, Damien Gallagher, Mark Rapoport, Sandra E. Black, Joel Ramirez, Ana C. Andreazza, Paul Oh, Susan Marzolini, Simon J. Graham, Krista L. Lanctôt

Bibliographic record

VenueAlzheimer s Research & Therapy · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSulfur Compounds in Biology
Canadian institutionsUniversity of TorontoUniversity Health NetworkSunnybrook HospitalHealth Sciences CentreToronto Rehabilitation InstituteSunnybrook Health Science Centre
FundersCanadian Institutes of Health ResearchAlzheimer Society Research ProgramAlzheimer SocietyAlzheimer's Association
KeywordsGlutathioneOxidative stressNeurodegenerationMedicineNeurologyDiseaseAlzheimer's diseaseAntioxidantCognitive impairmentInternal medicineNeurosciencePsychologyPsychiatryChemistryBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Abstract Background Increasing evidence implicates oxidative stress (OS) in Alzheimer disease (AD) and mild cognitive impairment (MCI). Depletion of the brain antioxidant glutathione (GSH) may be important in OS-mediated neurodegeneration, though studies of post-mortem brain GSH changes in AD have been inconclusive. Recent in vivo measurements of the brain and blood GSH may shed light on GSH changes earlier in the disease. Aim To quantitatively review in vivo GSH in AD and MCI compared to healthy controls (HC) using meta-analyses. Method Studies with in vivo brain or blood GSH levels in MCI or AD with a HC group were identified using MEDLINE, PsychInfo, and Embase (1947–June 2020). Standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for outcomes using random effects models. Outcome measures included brain GSH (Meshcher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) versus non-MEGA-PRESS) and blood GSH (intracellular versus extracellular) in AD and MCI. The Q statistic and Egger’s test were used to assess heterogeneity and risk of publication bias, respectively. Results For brain GSH, 4 AD (AD=135, HC=223) and 4 MCI (MCI=213, HC=211) studies were included. For blood GSH, 26 AD (AD=1203, HC=1135) and 7 MCI (MCI=434, HC=408) studies were included. Brain GSH overall did not differ in AD or MCI compared to HC; however, the subgroup of studies using MEGA-PRESS reported lower brain GSH in AD (SMD [95%CI] −1.45 [−1.83, −1.06], p <0.001) and MCI (−1.15 [−1.71, −0.59], z =4.0, p <0.001). AD had lower intracellular and extracellular blood GSH overall (−0.87 [−1. 30, −0.44], z =3.96, p <0.001). In a subgroup analysis, intracellular GSH was lower in MCI (−0.66 [−1.11, −0.21], p =0.025). Heterogeneity was observed throughout ( I 2 >85%) and not fully accounted by subgroup analysis. Egger’s test indicated risk of publication bias. Conclusion Blood intracellular GSH decrease is seen in MCI, while both intra- and extracellular decreases were seen in AD. Brain GSH is decreased in AD and MCI in subgroup analysis. Potential bias and heterogeneity suggest the need for measurement standardization and additional studies to explore sources of heterogeneity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.712
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.298
GPT teacher head0.441
Teacher spread0.143 · 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 teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations78
Published2022
Admission routes2
Has abstractyes

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