Diffusion magnetic resonance spectroscopy captures microglial reactivity related to gut-derived systemic lipopolysaccharide: A preliminary study.

Corona radiata Diffusion weighted magnetic resonance spectroscopy (dMRS) Gut-brain Innate immune system Microglia Microglial activation Microglial reactivity Neuroinflammation Thalamus lipopolysaccharide (LPS)

Journal

Brain, behavior, and immunity
ISSN: 1090-2139
Titre abrégé: Brain Behav Immun
Pays: Netherlands
ID NLM: 8800478

Informations de publication

Date de publication:
18 Aug 2024
Historique:
received: 18 01 2024
revised: 11 07 2024
accepted: 17 08 2024
medline: 21 8 2024
pubmed: 21 8 2024
entrez: 20 8 2024
Statut: aheadofprint

Résumé

Neuroinflammation is a key component underlying multiple neurological disorders, yet non-invasive and cost-effective assessment of in vivo neuroinflammatory processes in the central nervous system remains challenging. Diffusion weighted magnetic resonance spectroscopy (dMRS) has shown promise in addressing these challenges by measuring diffusivity properties of different neurometabolites, which can reflect cell-specific morphologies. Prior work has demonstrated dMRS utility in capturing microglial reactivity in the context of lipopolysaccharide (LPS) challenges and serious neurological disorders, detected as changes of microglial neurometabolite diffusivity properties. However, the extent to which such dMRS metrics are capable of detecting subtler and more nuanced levels of neuroinflammation in populations without overt neuropathology is unknown. Here we examined the relationship between intrinsic, gut-derived levels of systemic LPS and dMRS-based apparent diffusion coefficients (ADC) of choline, creatine, and N-acetylaspartate (NAA) in two brain regions: the thalamus and the corona radiata. Higher plasma LPS concentrations were significantly associated with increased ADC of choline and NAA in the thalamic region, with no such relationships observed in the corona radiata for any of the metabolites examined. As such, dMRS may have the sensitivity to measure microglial reactivity across populations with highly variable levels of neuroinflammation, and holds promising potential for widespread applications in both research and clinical settings.

Identifiants

pubmed: 39163909
pii: S0889-1591(24)00555-5
doi: 10.1016/j.bbi.2024.08.034
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Aleksandr Birg (A)

Department of Internal Medicine, Raymond G. Murphy VA Medical Center, Albuquerque, NM, USA; Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA.

Harm J van der Horn (HJ)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Sephira G Ryman (SG)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute; Nene and Jamie Cock Comprehensive Movement Disorder Center, Department of Neurology, University of New Mexico School of Medicine, Albuquerque, NM, USA.

Francesca Branzoli (F)

Sorbonne University, Inserm U 1127, CNRS UMR 7225, The Paris Brain Institute, Paris, France.

Dinesh K Deelchand (DK)

Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.

Davin K Quinn (DK)

Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA.

Andrew R Mayer (AR)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Henry C Lin (HC)

Department of Internal Medicine, Raymond G. Murphy VA Medical Center, Albuquerque, NM, USA; Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA.

Erik B Erhardt (EB)

Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, USA.

Arvind Caprihan (A)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Vadim Zotev (V)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Alisha N Parada (AN)

Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA.

Tracey V Wick (TV)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Yvette L Matos (YL)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Kimberly A Barnhart (KA)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Stephanie R Nitschke (SR)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Nicholas A Shaff (NA)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Kayla R Julio (KR)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Haley E Prather (HE)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute.

Andrei A Vakhtin (AA)

The Mind Research Network/Lovelace Biomedical and Environmental Research Institute. Electronic address: avakhtin@mrn.org.

Classifications MeSH