The developmental trajectory of 1H-MRS brain metabolites from childhood to adulthood
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PROVIDER: S-EPMC10908220 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
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Project description:Magnetic Resonance Spectroscopy (MRS) allows for the non-invasive quantification of neurochemicals and has the potential to differentiate between the pathologically distinct diseases, multiple sclerosis (MS) and AQP4Ab-positive neuromyelitis optica spectrum disorder (AQP4Ab-NMOSD). In this study we characterised the metabolite profiles of brain lesions in 11 MS and 4 AQP4Ab-NMOSD patients using an optimised MRS methodology at ultra-high field strength (7T) incorporating correction for T2 water relaxation differences between lesioned and normal tissue. MS metabolite results were in keeping with the existing literature: total N-acetylaspartate (NAA) was lower in lesions compared to normal appearing brain white matter (NAWM) with reciprocal findings for myo-Inositol. An unexpected subtlety revealed by our technique was that total NAA differences were likely driven by NAA-glutamate (NAAG), a ubiquitous CNS molecule with functions quite distinct from NAA though commonly quantified together with NAA in MRS studies as total NAA. Surprisingly, AQP4Ab-NMOSD showed no significant differences for total NAA, NAA, NAAG or myo-Inositol between lesion and NAWM sites, nor were there any differences between MS and AQP4Ab-NMOSD for a priori hypotheses. Post-hoc testing revealed a significant correlation between NAWM Ins:NAA and disability (as measured by EDSS) for disease groups combined, driven by the AP4Ab-NMOSD group. Utilising an optimised MRS methodology, our study highlights some under-explored subtleties in MRS profiles, such as the absence of myo-Inositol concentration differences in AQP4Ab-NMOSD brain lesions versus NAWM and the potential influence of NAAG differences between lesions and normal appearing white matter in MS.
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Project description:Background and purposeMR imaging and (1)H-MR spectroscopy changes are well reported in cirrhotic patients, whereas they are inadequately reported in EHPVO. The aim of this study was to investigate age-related changes in brain MR imaging and metabolite profile in EHPVO with and without MHE and to explore any correlation of imaging and (1)H-MR spectroscopy parameters with blood ammonia.Materials and methodsSixty-three patients with EHPVO (children, 7-12 years [n = 22], adolescents, 13-18 years [n = 15] and adults, 19-41 years [n = 26]) and 47 healthy age/sex-matched volunteers were studied. Neuropsychological tests, MR imaging, (1)H-MR spectroscopy, and blood ammonia estimation were performed in all subjects.ResultsOf 63 EHPVO patients, 25 (40%) who had MHE showed significantly increased MD, Glx, and blood ammonia in all 3 age groups; however, myo-inositol was significantly lower only in adults when compared with controls. MD positively correlated with blood ammonia and Glx in all age groups. Brain choline levels were normal in all patients with different age groups.ConclusionsIncreases in brain MD, Glx, and blood ammonia were associated with MHE in all age groups. Normal brain choline in EHPVO signifies healthy liver and may serve as a diagnostic marker for its differentiation from cirrhosis-induced encephalopathy. Significant decrease of myo-inositol in adults is probably due to cellular osmoregulation secondary to long-standing hyperammonemia.
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Project description:PurposeBody mass index (BMI) is associated with asthma but associations of BMI temporal patterns with asthma incidence are unclear. Previous studies suggest that DNA methylation (DNAm) is associated with asthma status and variation in DNAm is a consequence of BMI changes. This study assessed the direct and indirect (via DNAm) effects of BMI trajectories in childhood on asthma incidence at young adulthood.MethodsData from the Isle of Wight (IoW) birth cohort were included in the analyses. Group-based trajectory modelling was applied to infer latent BMI trajectories from ages 1 to 10 years. An R package, ttscreening, was applied to identify differentially methylated CpGs at age 10 years associated with BMI trajectories, stratified for sex. Logistic regressions were used to further exclude CpGs with DNAm at age 10 years not associated with asthma incidence at 18 years. CpGs discovered via path analyses that mediated the association of BMI trajectories with asthma incidence in the IoW cohort were further tested in an independent cohort, the Avon Longitudinal Study of Children and Parents (ALSPAC).ResultsTwo BMI trajectories (high vs. normal) were identified. Of the 442,474 CpG sites, DNAm at 159 CpGs in males and 212 in females were potentially associated with BMI trajectories. Assessment of their association with asthma incidence identified 9 CpGs in males and 6 CpGs in females. DNAm at 4 of these 15 CpGs showed statistically significant mediation effects (p-value < 0.05). At two of the 4 CpGs (cg23632109 and cg10817500), DNAm completely mediated the association (i.e., only statistically significant indirect effects were identified). In the ALSPAC cohort, at all four CpGs, the same direction of mediating effects were observed as those found in the IoW cohort, although statistically insignificant.ConclusionThe association of BMI trajectory in childhood with asthma incidence at young adulthood is possibly mediated by DNAm.
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Project description:BackgroundMagnetic Resonance Spectroscopy (MRS) can measure in vivo brain tissue metabolism that exhibits unique biochemical characteristics in brain tumors. For clinical application, an efficient and versatile quantification method of MRS would be an important tool for medical research, particularly for exploring the scientific problem of tumor monitoring. The objective of our study is to propose an automated MRS quantitative approach and assess the feasibility of this approach for glioma grading, prognosis and boundary detection.MethodsAn automated quantitative approach based on a convex envelope (AQoCE) is proposed in this paper, including preprocessing, convex-envelope based baseline fitting, bias correction, sectional baseline removal, and peak detection, in a total of 5 steps. Some metabolic ratios acquired by this quantification are selected for statistical analysis. An independent sample t-test and the Kruskal-Wallis test are used for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and for detecting the tumor, peritumoral and contralateral areas, respectively. Seventy-eight cases of pre-operative brain gliomas with pathological reports are included in this study.ResultsCho/NAA, Cho/Cr and Lip-Lac/Cr (LL/Cr) calculated by AQoCE in the tumor area differ significantly between LGG and HGG, with p≤0.005. Using logistic regression combining Cho/NAA, Cho/Cr and LL/Cr to generate a ROC curve, AQoCE achieves a sensitivity of 92.9%, a specificity of 72.2%, and an area under ROC curve (AUC) of 0.860. Moreover, both Cho/NAA and Cho/Cr in the AQoCE approach show a significant difference (p≤0.019) between tumoral, peritumoral, and contralateral areas. The comparison between the results of AQoCE and Siemens MRS processing software are also discussed in this paper.ConclusionsThe AQoCE approach is an automated method of residual water removal and metabolite quantification. It can be applied to multi-voxel 1H-MRS for evaluating brain glioma grading and demonstrating characteristics of brain glioma metabolism. It can also detect infiltration in the peritumoral area. Under the limited clinical data used, AQoCE is significantly more versatile and efficient compared to the reference approach of Siemens.
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