Dataset Information

A cross-sectional study of MRI features and the gut microbiome in pediatric-onset multiple sclerosis.

ABSTRACT:

Objective

To identify gut microbiome features associated with MRI lesion burden in persons with pediatric-onset multiple sclerosis (symptom onset <18 years).

Methods

A cross-sectional study involving the Canadian Paediatric Demyelinating Disease Network study participants. Gut microbiome features (alpha diversity, phylum- and genus-level taxa) were derived using 16S rRNA sequencing from stool samples. T1- and T2-weighted lesion volumes were measured on brain MRI obtained within 6 months of stool sample procurement. Associations between the gut microbiota and MRI metrics (cube-root-transformed) were assessed using standard and Lasso regression models.

Results

Thirty-four participants were included; mean ages at symptom onset and MRI were 15.1 and 19.0 years, respectively, and 79% were female. The T1- and T2-weighted lesion volumes were not significantly associated with alpha diversity (age and sex-adjusted p > 0.08). At the phylum level, high Tenericutes (relative abundance) was associated with higher T1 and T2 volumes (β coefficient = 0.25, 0.37) and high Firmicutes, Patescibacteria or Actinobacteria with lower lesion volumes (β coefficient = -0.30 to -0.07). At the genus level, high Ruminiclostridium, whereas low Coprococcus 3 and low Erysipelatoclostridium were associated with higher lesion volumes.

Interpretation

Our study characterized the gut microbiota features associated with MRI lesion burden in pediatric-onset MS, shedding light onto possible pathophysiological mechanisms.

SUBMITTER: Zhu F

PROVIDER: S-EPMC10863907 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

A cross-sectional study of MRI features and the gut microbiome in pediatric-onset multiple sclerosis.

Zhu Feng F Zhao Yinshan Y Arnold Douglas L DL Bar-Or Amit A Bernstein Charles N CN Bonner Christine C Graham Morag M Hart Janace J Knox Natalie N Marrie Ruth Ann RA Mirza Ali I AI O'Mahony Julia J Van Domselaar Gary G Yeh E Ann EA Banwell Brenda B Waubant Emmanuelle E Tremlett Helen H

Annals of clinical and translational neurology 20231221 2

<h4>Objective</h4>To identify gut microbiome features associated with MRI lesion burden in persons with pediatric-onset multiple sclerosis (symptom onset <18 years).<h4>Methods</h4>A cross-sectional study involving the Canadian Paediatric Demyelinating Disease Network study participants. Gut microbiome features (alpha diversity, phylum- and genus-level taxa) were derived using 16S rRNA sequencing from stool samples. T1- and T2-weighted lesion volumes were measured on brain MRI obtained within 6 ...[more]

PMID: 38130033

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Project description:Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By combining longitudinal MRI-based brain morphometry and brain age estimation using machine learning, we tested the hypothesis that MS patients have higher brain age relative to chronological age than healthy controls (HC) and that longitudinal rate of brain aging in MS patients is associated with clinical course and severity. Seventy-six MS patients [71% females, mean age 34.8 years (range 21-49) at inclusion] were examined with brain MRI at three time points with a mean total follow up period of 4.4 years (±0.4 years). We used additional cross-sectional MRI data from 235 HC for case-control comparison. We applied a machine learning model trained on an independent set of 3,208 HC to estimate individual brain age and to calculate the difference between estimated and chronological age, termed brain age gap (BAG). We also assessed the longitudinal change rate in BAG in individuals with MS. MS patients showed significantly higher BAG (4.4 ± 6.6 years) compared to HC (Cohen's D = 0.69, p = 4.0 × 10-6). Longitudinal estimates of BAG in MS patients showed high reliability and suggested an accelerated rate of brain aging corresponding to an annual increase of 0.41 (SE = 0.15) years compared to chronological aging (p = 0.008). Multiple regression analyses revealed higher rate of brain aging in patients with more brain atrophy (Cohen's D = 0.86, p = 4.3 × 10-15) and increased white matter lesion load (WMLL) (Cohen's D = 0.55, p = 0.015). On average, patients with MS had significantly higher BAG compared to HC. Progressive brain aging in patients with MS was related to brain atrophy and increased WMLL. No significant clinical associations were found in our sample, future studies are warranted on this matter. Brain age estimation is a promising method for evaluation of subtle brain changes in MS, which is important for predicting clinical outcome and guide choice of intervention.

Project description:BackgroundMultiple sclerosis (MS) has a complex genetic, immune and metabolic pathophysiology. Recent studies implicated the gut microbiome in MS pathogenesis. However, interactions between the microbiome and host immune system, metabolism and diet have not been studied over time in this disorder.MethodsWe performed a six-month longitudinal multi-omics study of 49 participants (24 untreated relapse remitting MS patients and 25 age, sex, race matched healthy control individuals. Gut microbiome composition and function were characterized using 16S and metagenomic shotgun sequencing. Flow cytometry was used to characterize blood immune cell populations and cytokine profiles. Circulating metabolites were profiled by untargeted UPLC-MS. A four-day food diary was recorded to capture the habitual dietary pattern of study participants.FindingsTogether with changes in blood immune cells, metagenomic analysis identified a number of gut microbiota decreased in MS patients compared to healthy controls, and microbiota positively or negatively correlated with degree of disability in MS patients. MS patients demonstrated perturbations of their blood metabolome, such as linoleate metabolic pathway, fatty acid biosynthesis, chalcone, dihydrochalcone, 4-nitrocatechol and methionine. Global correlations between multi-omics demonstrated a disrupted immune-microbiome relationship and a positive blood metabolome-microbiome correlation in MS. Specific feature association analysis identified a potential correlation network linking meat servings with decreased gut microbe B. thetaiotaomicron, increased Th17 cell and greater abundance of meat-associated blood metabolites. The microbiome and metabolome profiles remained stable over six months in MS and control individuals.InterpretationOur study identified multi-system alterations in gut microbiota, immune and blood metabolome of MS patients at global and individual feature level. Multi-OMICS data integration deciphered a potential important biological network that links meat intakes with increased meat-associated blood metabolite, decreased polysaccharides digesting bacteria, and increased circulating proinflammatory marker.FundingThis work was supported by the Washington University in St. Louis Institute of Clinical and Translational Sciences, funded, in part, by Grant Number # UL1 TR000448 from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award (Zhou Y, Piccio, L, Lovett-Racke A and Tarr PI); R01 NS10263304 (Zhou Y, Piccio L); the Leon and Harriet Felman Fund for Human MS Research (Piccio L and Cross AH). Cantoni C. was supported by the National MS Society Career Transition Fellowship (TA-180531003) and by donations from Whitelaw Terry, Jr. / Valerie Terry Fund. Ghezzi L. was supported by the Italian Multiple Sclerosis Society research fellowship (FISM 2018/B/1) and the National Multiple Sclerosis Society Post-Doctoral Fellowship (FG-190734474). Anne Cross was supported by The Manny & Rosalyn Rosenthal-Dr. John L. Trotter MS Center Chair in Neuroimmunology of the Barnes-Jewish Hospital Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Dataset Information

A cross-sectional study of MRI features and the gut microbiome in pediatric-onset multiple sclerosis.

Objective

Methods

Results

Interpretation

Publications

A cross-sectional study of MRI features and the gut microbiome in pediatric-onset multiple sclerosis.

Similar Datasets

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