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Record W4308123922 · doi:10.3389/fimmu.2022.1013784

Dynamic changes in kynurenine pathway metabolites in multiple sclerosis: A systematic review

2022· review· en· W4308123922 on OpenAlexaff
Mobina Fathi, Kimia Vakili, Shirin Yaghoobpoor, Arian Tavasol, Kimia Jazi, Ashraf Mohamadkhani, Andis Klegeris, Alyssa McElhinney, Zahedeh Mafi, Mohammadreza Hajiesmaeili, Fatemeh Sayehmiri

Bibliographic record

VenueFrontiers in Immunology · 2022
Typereview
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsKynurenineQuinolinic acidKynurenine pathwayKynurenic acidIndoleamine 2,3-dioxygenaseMultiple sclerosisMedicineNeuroprotectionImmunologyInternal medicinePharmacologyChemistryBiochemistryTryptophanGlutamate receptor

Abstract

fetched live from OpenAlex

Background: Multiple sclerosis (MS) is a debilitating neurodegenerative disorder characterized by axonal damage, demyelination, and perivascular inflammatory lesions in the white matter of the central nervous system (CNS). Kynurenine pathway (KP), which is the major route of tryptophan (TRP) metabolism, generates a variety of neurotoxic as well as neuroprotective compounds, affecting MS pathology and the severity of impairments. Alterations in KP have been described not only in MS, but also in various psychiatric and neurodegenerative diseases. The purpose of this systematic review is to investigate the previously reported dysregulation of KP and differences in its metabolites and enzymes in patients with MS compared to healthy control subjects. Method: Electronic databases of PubMed, Scopus, Cochrane Database of Systematic Reviews, and Web of Science were searched to identify studies measuring concentrations of KP metabolites and enzymes in MS patients and control subjects. The following metabolites and enzymes implicated in the KP were investigated: TRP, kynurenine (KYN), kynurenic acid (KYNA), quinolinic acid (QUIN), picolinic acid (PIC), hydroxyindoleacetic acid (HIAA), indoleamine 2,3-dioxygenase (IDO), kynurenine aminotransferase (KAT), and their related ratios. Result: Ten studies were included in our systematic review. Our review demonstrates that IDO expression is reduced in the peripheral blood mononuclear cells (PBMCs) of MS patients compared to healthy controls. Also, increased levels of QUIN and QUIN/KYNA in the serum and cerebrospinal fluid (CSF) of MS patients is observed. Differences in levels of other metabolites and enzymes of KP are also reported in some of the reviewed studies, however there are discrepancies among the included reports. Conclusion: The results of this investigation suggest a possible connection between alterations in the levels of KP metabolite or enzymes and MS. QUIN levels in CSF were higher in MS patients than in healthy controls, suggesting that QUIN may be involved in the pathogenesis of MS. The data indicate that differences in the serum/blood or CSF levels of certain KP metabolites and enzymes could potentially be used to differentiate between MS patients and control subjects.

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0110.012
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.272
Teacher spread0.217 · 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 designSystematic review
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

Citations38
Published2022
Admission routes1
Has abstractyes

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