Proton NMR chemical shifts and coupling constants for brain metabolites

Integrating HRMAS-NMR Data and Machine Learning-Assisted Profiling of Metabolite Fluxes to Classify Low- and High-Grade Gliomas

Diagnosing and classifying central nervous system tumors such as gliomas or glioblastomas pose a significant challenge due to their aggressive and infiltrative nature. However, recent advancements in metabolomics and magnetic resonance spectroscopy (MRS) offer promising avenues for differentiating tumor grades both in vivo and ex vivo. This study aimed to explore tissue-based metabolic signatures to classify/distinguish between low- and high-grade gliomas. Forty-six histologically confirmed, intact solid tumor samples from glioma patients were analyzed using high-resolution magic angle spinning nuclear magnetic resonance (HRMAS-NMR) spectroscopy. By integrating machine learning (ML) algorithms, spectral regions with the most discriminative potential were identified. Validation was performed through univariate and multivariate statistical analyses, along with HRMAS-NMR analyses of 46 paired plasma samples. Amongst the various ML models applied, the logistics regression identified 46 spectral regions capable of sub-classifying gliomas with accuracy 87% (F1-measure 0.87, Precision 0.82, Recall 0.93), whereas the extra-tree classifier identified three spectral regions with predictive accuracy of 91% (F1-measure 0.91, Precision 0.85, Recall 0.97). Wilcoxon test presented 51 spectral regions significantly differentiating low- and high-grade glioma groups (p < 0.05). Based on sensitivity and area under the curve values, 40 spectral regions corresponding to 18 metabolites were considered as potential biomarkers for tissue-based glioma classification and amongst these N-acetyl aspartate, glutamate, and glutamine emerged as the most important markers. These markers were validated in paired plasma samples, and their absolute concentrations were computed. Our results demonstrate that the metabolic markers identified through the HRMAS-NMR-ML analysis framework, and their associated metabolic networks, hold promise for targeted treatment planning and clinical interventions in the future.

Understanding Proton Magnetic Resonance Spectroscopy Neurochemical Changes Using Alzheimer's Disease Biofluid, PET, Postmortem Pathology Biomarkers, and APOE Genotype

In vivo proton (1H) magnetic resonance spectroscopy (MRS) is a powerful non-invasive method that can measure Alzheimer's disease (AD)-related neuropathological alterations at the molecular level. AD biomarkers include amyloid-beta (Aβ) plaques and hyperphosphorylated tau neurofibrillary tangles. These biomarkers can be detected via postmortem analysis but also in living individuals through positron emission tomography (PET) or biofluid biomarkers of Aβ and tau. This review offers an overview of biochemical abnormalities detected by 1H MRS within the biologically defined AD spectrum. It includes a summary of earlier studies that explored the association of 1H MRS metabolites with biofluid, PET, and postmortem AD biomarkers and examined how apolipoprotein e4 allele carrier status influences brain biochemistry. Studying these associations is crucial for understanding how AD pathology affects brain homeostasis throughout the AD continuum and may eventually facilitate the development of potential novel therapeutic approaches.

Recurrent neural network-aided processing of incomplete free induction decays in 1H-MRS of the brain

In the case of limited sampling windows or truncation of free induction decays (FIDs) for artifact removal in proton magnetic resonance spectroscopy (1H-MRS) and spectroscopic imaging (1H-MRSI), metabolite quantification needs to be performed on incomplete FIDs. Given that FIDs are naturally time-domain sequential data, we investigated the potential of recurrent neural network (RNN)-types of neural networks (NNs) in the processing of incomplete human brain FIDs with or without FID restoration prior to quantitative analysis at 3.0T. First, we employed an RNN encoder-decoder and developed it to restore incomplete FIDs (rRNN) with different amounts of sampled data. The quantification of metabolites from the rRNN-restored FIDs was achieved by using LCModel. Second, we modified the RNN encoder-decoder and developed it to convert incomplete brain FIDs into incomplete metabolite-only FIDs without restoration, followed by linear regression using a metabolite basis set for quantitative analysis (cRNN). In consideration of the practical benefit of the FID restoration with respect to pure zero-filling, development and analysis of the NNs were focused particularly on the incomplete FIDs with only the first 64 data points retained. All NNs were trained on simulated data and tested mainly on in vivo data acquired from healthy volunteers (n = 27). Strong correlations were obtained between the NN-derived and ground truth metabolite content (LCModel-derived content on fully sampled FIDs) for myo-inositol, total choline, and total creatine (normalized to total N-acetylaspartate) on the in vivo data using both rRNN (R = 0.83-0.94; p ≤ 0.05) and cRNN (R = 0.86-0.91; p ≤ 0.05). RNN-types of NNs have potential in the quantification of the major brain metabolites from the FIDs with substantially reduced sampled data points. For the metabolites with low to medium SNR, the performance of the NNs needs to be further improved, for which development of more elaborate and advanced simulation techniques would be of help, but remains challenging.

Optimization and validation of echo times of point-resolved spectroscopy for cystathionine detection in gliomas

BACKGROUND

Cystathionine accumulates selectively in 1p/19q-codeleted gliomas, and can serve as a possible noninvasive biomarker. This study aims to optimize the echo time (TE) of point-resolved spectroscopy (PRESS) for cystathionine detection in gliomas, and evaluate the diagnostic accuracy of PRESS for 1p/19q-codeletion identification.

METHODS

The TE of PRESS was optimized with numerical and phantom analysis to better resolve cystathionine from the overlapping aspartate multiplets. The optimized and 97 ms TE PRESS were then applied to 84 prospectively enrolled patients suspected of glioma or glioma recurrence to examine the influence of aspartate on cystathionine quantification by fitting the spectra with and without aspartate. The diagnostic performance of PRESS for 1p/19q-codeleted gliomas were assessed.

RESULTS

The TE of PRESS was optimized as (TE1, TE2) = (17 ms, 28 ms). The spectral pattern of cystathionine and aspartate were consistent between calculation and phantom. The mean concentrations of cystathionine in vivo fitting without aspartate were significantly higher than those fitting with full basis-set for 97 ms TE PRESS (1.97 ± 2.01 mM vs. 1.55 ± 1.95 mM, p < 0.01), but not significantly different for 45 ms method (0.801 ± 1.217 mM and 0.796 ± 1.217 mM, p = 0.494). The cystathionine concentrations of 45 ms approach was better correlated with those of edited MRS than 97 ms counterparts (r = 0.68 vs. 0.49, both p < 0.01). The sensitivity and specificity for discriminating 1p/19q-codeleted gliomas were 66.7% and 73.7% for 45 ms method, and 44.4% and 52.5% for 97 ms method, respectively.

CONCLUSION

The 45 ms TE PRESS yields more precise cystathionine estimates than the 97 ms method, and is anticipated to facilitate noninvasive diagnosis of 1p/19q-codeleted gliomas, and treatment response monitoring in those patients. Medium diagnostic performance of PRESS for 1p/19q-codeleted gliomas were observed, and warrants further investigations.

Glutamate dynamics and BOLD response during OCD symptom provocation in the lateral occipital cortex: A 7 Tesla fMRI-fMRS study

Obsessive-compulsive disorder (OCD) is linked with dysfunction in frontal-striatal, fronto-limbic, and visual brain regions. Research using proton magnetic resonance spectroscopy (1H-MRS) suggests that altered neurometabolite levels, like glutamate, may contribute to this dysfunction. However, static neurometabolite levels in OCD patients have shown inconsistent results, likely due to previous studies' limited focus on neurometabolite dynamics. We employ functional MRS (fMRS) and functional magnetic resonance imaging (fMRI) to explore these dynamics and brain activation during OCD symptom provocation. We utilized a combined 7-tesla fMRI-fMRS setup to examine task-related BOLD response and glutamate changes in the lateral occipital cortex (LOC) of 30 OCD participants and 34 matched controls during an OCD-specific symptom provocation task. The study examined main effects and between-group differences in brain activation and glutamate levels during the task. A whole sample task-effects analysis on data meeting predefined quality criteria showed significant glutamate increases (n = 41 (22 OCD, 19 controls), mean change: 3.2 %, z = 3.75, p < .001) and task activation (n = 54 (26 OCD, 28 controls), p < .001) in the LOC during OCD blocks compared to neutral blocks. However, no differences in task-induced glutamate dynamics or activation between groups were found, nor a correlation between glutamate levels and task activation. We were able to measure task-induced increases in glutamate and BOLD levels, emphasizing its feasibility for OCD research. The absence of group differences highlights the need for further exploration to discern to what extent neurometabolite dynamics differ between OCD patients and controls. Once established, future studies can use pre-post intervention fMRS-fMRI to probe the effects of therapies modulating glutamate pathways in OCD.

Metabolic coupling between glutamate and N-acetylaspartate in the human brain

A metabolic coupling between glutamate and N-acetylaspartate measured by in vivo magnetic resonance spectroscopy has been recently reported in the literature with inconsistent findings. In this study, confounders originating from Pearson's spurious correlation of ratios and spectral correlation due to overlapping magnetic resonance spectroscopy signals of glutamate and N-acetylaspartate were practically eliminated to facilitate the determination of any metabolic link between glutamate and N-acetylaspartate in the human brain using in vivo magnetic resonance spectroscopy. In both occipital and medial prefrontal cortices of healthy individuals, correlations between glutamate and N-acetylaspartate were found to be insignificant. Our results do not lend support to a recent hypothesis that N-acetylaspartate serves as a significant reservoir for the rapid replenishment of glutamate during signaling or stress.

Frontal and occipital brain glutathione levels are unchanged in autistic adults

BACKGROUND

The neurobiological underpinnings of Autism Spectrum Disorder (ASD) are diverse and likely multifactorial. One possible mechanism is increased oxidative stress leading to altered neurodevelopment and brain function. However, this hypothesis has mostly been tested in post-mortem studies. So far, available in vivo studies in autistic individuals have reported no differences in glutathione (GSH) levels in frontal, occipital, and subcortical regions. However, these studies were limited by the technically challenging quantification of GSH, the main brain antioxidant molecule. This study aimed to overcome previous studies' limitations by using a GSH-tailored spectroscopy sequence and optimised quantification methodology to provide clarity on GSH levels in autistic adults.

METHODS

We used spectral editing proton-magnetic resonance spectroscopy (1H-MRS) combined with linear combination model fitting to quantify GSH in the dorsomedial prefrontal cortex (DMPFC) and medial occipital cortex (mOCC) of autistic and non-autistic adults (male and female). We compared GSH levels between groups. We also examined correlations between GSH and current autism symptoms, measured using the Autism Quotient (AQ).

RESULTS

Data were available from 31 adult autistic participants (24 males, 7 females) and 40 non-autistic participants (21 males, 16 females); the largest sample to date. The GSH levels did not differ between groups in either region. No correlations with AQ were observed.

CONCLUSION

GSH levels as measured using 1H-MRS are unaltered in the DMPFC and mOCC regions of autistic adults, suggesting that oxidative stress in these cortical regions is not a marked neurobiological signature of ASD.

Spiny dogfish, Squalus suckleyi, shows a good tolerance for hypoxia but need long recovery times

Pacific spiny dogfish, Squalus suckleyi, move to shallow coastal waters during critical reproductive life stages and are thus at risk of encountering hypoxic events which occur more frequently in these areas. For effective conservation management, we need to fully understand the consequences of hypoxia on marine key species such as elasmobranchs. Because of their benthic life style, we hypothesized that S. suckleyi are hypoxia tolerant and able to efficiently regulate oxygen consumption, and that anaerobic metabolism is supported by a broad range of metabolites including ketones, fatty acids and amino acids. Therefore, we studied oxygen consumption rates, ventilation frequency and amplitude, blood gasses, acid-base regulation, and changes in plasma and tissue metabolites during progressive hypoxia. Our results show that critical oxygen levels (P crit) where oxyregulation is lost were indeed low (18.1% air saturation or 28.5 Torr at 13°C). However, many dogfish behaved as oxyconformers rather than oxyregulators. Arterial blood PO2 levels mostly decreased linearly with decreasing environmental PO2. Blood gases and acid-base status were dependent on open versus closed respirometry but in both set-ups ventilation frequency increased. Hypoxia below Pcrit resulted in an up-regulation of anaerobic glycolysis, as evidenced by increased lactate levels in all tissues except brain. Elasmobranchs typically rely on ketone bodies as oxidative substrates, and decreased concentrations of acetoacetate and β-hydroxybutyrate were observed in white muscle of hypoxic and/or recovering fish. Furthermore, reductions in isoleucine, glutamate, glutamine and other amino acids were observed. After 6 hours of normoxic recovery, changes persisted and only lactate returned to normal in most tissues. This emphasizes the importance of using suitable bioindicators adjusted to preferred metabolic pathways of the target species in conservation physiology. We conclude that Pacific spiny dogfish can tolerate severe transient hypoxic events, but recovery is slow and negative impacts can be expected when hypoxia persists.

Ex-Vivo 13C NMR Spectroscopy of Rodent Brain: TNF Restricts Neuronal Utilization of Astrocyte-Derived Metabolites

Tumor necrosis factor (TNF) has well-established roles in neuroinflammatory disorders, but the effect of TNF on the biochemistry of brain cells remains poorly understood. Here, we microinjected TNF into the brain to study its impact on glial and neuronal metabolism (glycolysis, pentose phosphate pathway, citric acid cycle, pyruvate dehydrogenase, and pyruvate carboxylase pathways) using 13C NMR spectroscopy on brain extracts following intravenous [1,2-13C]-glucose (to probe glia and neuron metabolism), [2-13C]-acetate (probing astrocyte-specific metabolites), or [3-13C]-lactate. An increase in [4,5-13C]-glutamine and [2,3-13C]-lactate coupled with a decrease in [4,5-13C]-glutamate was observed in the [1,2-13C]-glucose-infused animals treated with TNF. As glutamine is produced from glutamate by astrocyte-specific glutamine synthetase the increase in [4,5-13C]-glutamine reflects increased production of glutamine by astrocytes. This was confirmed by infusion with astrocyte substrate [2-13C]-acetate. As lactate is metabolized in the brain to produce glutamate, the simultaneous increase in [2,3-13C]-lactate and decrease in [4,5-13C]-glutamate suggests decreased lactate utilization, which was confirmed using [3-13C]-lactate as a metabolic precursor. These results suggest that TNF rearranges the metabolic network, disrupting the energy supply chain perturbing the glutamine-glutamate shuttle between astrocytes and the neurons. These insights pave the way for developing astrocyte-targeted therapeutic strategies aimed at modulating effects of TNF to restore metabolic homeostasis in neuroinflammatory disorders.

1H-NMR-based metabolomics reveals metabolic alterations in early development of a mouse model of Angelman syndrome

BACKGROUND

Angelman syndrome (AS) is a rare neurodevelopmental genetic disorder caused by the loss of function of the ubiquitin ligase E3A (UBE3A) gene, affecting approximately 1:15,000 live births. We have recently shown that mitochondrial function in AS is altered during mid to late embryonic brain development leading to increased oxidative stress and enhanced apoptosis of neural precursor cells. However, the overall alterations of metabolic processes are still unknown. Hence, as a follow-up, we aim to investigate the metabolic profiles of wild-type (WT) and AS littermates and to identify which metabolic processes are aberrant in the brain of AS model mice during embryonic development.

METHODS

We collected brain tissue samples from mice embryos at E16.5 and performed metabolomic analyses using proton nuclear magnetic resonance (1H-NMR) spectroscopy. Multivariate and Univariate analyses were performed to determine the significantly altered metabolites in AS mice. Pathways associated with the altered metabolites were identified using metabolite set enrichment analysis.

RESULTS

Our analysis showed that overall, the metabolomic fingerprint of AS embryonic brains differed from those of their WT littermates. Moreover, we revealed a significant elevation of distinct metabolites, such as acetate, lactate, and succinate in the AS samples compared to the WT samples. The elevated metabolites were significantly associated with the pyruvate metabolism and glycolytic pathways.

LIMITATIONS

Only 14 metabolites were successfully identified and investigated in the present study. The effect of unidentified metabolites and their unresolved peaks was not determined. Additionally, we conducted the metabolomic study on whole brain tissue samples. Employing high-resolution NMR studies on different brain regions could further expand our knowledge regarding metabolic alterations in the AS brain. Furthermore, increasing the sample size could reveal the involvement of more significantly altered metabolites in the pathophysiology of the AS brain.

CONCLUSIONS

Ube3a loss of function alters bioenergy-related metabolism in the AS brain during embryonic development. Furthermore, these neurochemical changes could be linked to the mitochondrial reactive oxygen species and oxidative stress that occurs during the AS embryonic development.

Predicting performance in attention by measuring key metabolites in the PCC with 7T MRS

The posterior cingulate cortex (PCC) is a key hub of the default mode network and is known to play an important role in attention. Using ultra-high field 7 Tesla magnetic resonance spectroscopy (MRS) to quantify neurometabolite concentrations, this exploratory study investigated the effect of the concentrations of myo-inositol (Myo-Ins), glutamate (Glu), glutamine (Gln), aspartate or aspartic acid (Asp) and gamma-amino-butyric acid (GABA) in the PCC on attention in forty-six healthy participants. Each participant underwent an MRS scan and cognitive testing, consisting of a trail-making test (TMT A/B) and a test of attentional performance. After a multiple regression analysis and bootstrapping for correction, the findings show that Myo-Ins and Asp significantly influence (p < 0.05) attentional tasks. On one hand, Myo-Ins shows it can improve the completion times of both TMT A and TMT B. On the other hand, an increase in aspartate leads to more mistakes in Go/No-go tasks and shows a trend towards enhancing reaction time in Go/No-go tasks and stability of alertness without signal. No significant (p > 0.05) influence of Glu, Gln and GABA was observed.

Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy

BACKGROUND

Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have found a variety of applications on the process of MRS data. A quantification strategy compatible to DL base MRS spectral processing method is, therefore, useful.

MATERIALS AND METHODS

This study aims to investigate whether metabolite concentrations quantified using a convolutional neural network (CNN) based method, coupled with a scaling procedure that normalizes spectral signals for CNN input and linear regression, can effectively reflect variations in metabolite concentrations in IU across different brain regions with varying signal-to-noise ratios (SNR) and linewidths (LW). An error index based on standard error (SE) is proposed to indicate the confidence levels associated with metabolite predictions. In vivo MRS spectra were acquired from three brain regions of 43 subjects using a 3T system.

RESULTS

The metabolite concentrations in IU of five major metabolites, quantified using CNN and LCModel, exhibit similar ranges with Pearson's correlation coefficients ranging from 0.24 to 0.78. The SE of the metabolites shows a positive correlation with Cramer-Rao lower bound (CRLB) (r=0.46) and  absolute CRLB (r=0.81), calculated by multiplying CRLBs with the quantified metabolite content.

CONCLUSION

In conclusion, the CNN based method with the proposed scaling procedures can be employed to quantify in vivo MRS spectra and derive metabolites concentrations in IU. The SE can be used as error index, indicating predicted uncertainties for metabolites and sharing information similar to the absolute CRLB.

Omega-3 alleviates behavioral and molecular changes in a mouse model of stress-induced juvenile depression

Introduction

Depression is increasingly diagnosed in adolescence, necessitating specific prevention and treatment methods. However, there is a lack of animal models mimicking juvenile depression. This study explores a novel model using ultrasound (US) stress in juvenile mice.

Methods

We employed the US stress model in one-month-old C57/BL6 mice, exposing them to alternating ultrasound frequencies (20-25 kHz and 25-45 kHz) for three weeks. These frequencies correspond to negative and neutral emotional states in rodents and can induce a depressive-like syndrome. Concurrently, mice received either an omega-3 food supplement (FS) containing eicosapentaenoic acid (EPA; 0.55 mg/kg/day) and docosahexaenoic acid (DHA; 0.55 mg/kg/day) or a vehicle. Post-stress, we evaluated anxiety- and depressive-like behaviors, blood corticosterone levels, brain expression of pro-inflammatory cytokines, and conducted metabolome analysis of brain, liver and blood plasma.

Results

US-exposed mice treated with vehicle exhibited decreased sucrose preference, a sign of anhedonia, a key feature of depression, increased anxiety-like behavior, elevated corticosterone levels, and enhanced TNF and IL-1β gene expression in the brain. In contrast, US-FS mice did not display these changes. Omega-3 supplementation also reduced anxiety-like behavior in non-stressed mice. Metabolomic analysis revealed US-induced changes in brain energy metabolism, with FS increasing brain sphingomyelin. Liver metabolism was affected by both US and FS, while plasma metabolome changes were exclusive to FS. Brain glucose levels correlated positively with activity in anxiety tests.

Conclusion

Chronic omega-3 intake counteracted depressive- and anxiety-like behaviors in a US model of juvenile depression in mice. These effects likely stem from the anti-inflammatory properties of the supplement, suggesting potential therapeutic applications in juvenile depression.

Interactions of catecholamines and GABA+ in cognitive control: Insights from EEG and 1H-MRS

Catecholamines and amino acid transmitter systems are known to interact, the exact links and their impact on cognitive control functions have however remained unclear. Using a multi-modal imaging approach combining EEG and proton-magnetic resonance spectroscopy (1H-MRS), we investigated the effect of different degrees of pharmacological catecholaminergic enhancement onto theta band activity (TBA) as a measure of interference control during response inhibition and execution. It was central to our study to evaluate the predictive impact of in-vivo baseline GABA+ concentrations in the striatum, the anterior cingulate cortex (ACC) and the supplemental motor area (SMA) of healthy adults under varying degrees of methylphenidate (MPH) stimulation. We provide evidence for a predictive interrelation of baseline GABA+ concentrations in cognitive control relevant brain areas onto task-induced TBA during response control stimulated with MPH. Baseline GABA+ concentrations in the ACC, the striatum, and the SMA had a differential impact on predicting interference control-related TBA in response execution trials. GABA+ concentrations in the ACC appeared to be specifically important for TBA modulations when the cognitive effort needed for interference control was high - that is when no prior task experience exists, or in the absence of catecholaminergic enhancement with MPH. The study highlights the predictive role of baseline GABA+ concentrations in key brain areas influencing cognitive control and responsiveness to catecholaminergic enhancement, particularly in high-effort scenarios.

Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal

OBJECTIVE

Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of non-ideal acquisition conditions, and interference with strong background signals mainly from macromolecules. The most popular method, LCModel, adopts complicated non-linear least square to quantify metabolites and addresses these problems by designing empirical priors such as basis-sets, imperfection factors. However, when the signal-to-noise ratio of MRS signal is low, the solution may have large deviation.

METHODS

Linear Least Squares (LLS) is integrated with deep learning to reduce the complexity of solving this overall quantification. First, a neural network is designed to explicitly predict the imperfection factors and the overall signal from macromolecules. Then, metabolite quantification is solved analytically with the introduced LLS. In our Quantification Network (QNet), LLS takes part in the backpropagation of network training, which allows the feedback of the quantification error into metabolite spectrum estimation. This scheme greatly improves the generalization to metabolite concentrations unseen in training compared to the end-to-end deep learning method.

RESULTS

Experiments show that compared with LCModel, the proposed QNet, has smaller quantification errors for simulated data, and presents more stable quantification for 20 healthy in vivo data at a wide range of signal-to-noise ratio. QNet also outperforms other end-to-end deep learning methods.

CONCLUSION

This study provides an intelligent, reliable and robust MRS quantification.

SIGNIFICANCE

QNet is the first LLS quantification aided by deep learning.

Brain extended and closed forms glutathione levels decrease with age and extended glutathione is associated with visuospatial memory

During aging, the brain is subject to greater oxidative stress (OS), which is thought to play a critical role in cognitive impairment. Glutathione (GSH), as a major antioxidant in the brain, can be used to combat OS. However, how brain GSH levels vary with age and their associations with cognitive function is unclear. In this study, we combined point-resolved spectroscopy and edited spectroscopy sequences to investigate extended and closed forms GSH levels in the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and occipital cortex (OC) of 276 healthy participants (extended form, 166 females, age range 20-70 years) and 15 healthy participants (closed form, 7 females, age range 26-56 years), and examined their relationships with age and cognitive function. The results revealed decreased extended form GSH levels with age in the PCC among 276 participants. Notably, the timecourse of extended form GSH level changes in the PCC and ACC differed between males and females. Additionally, positive correlations were observed between extended form GSH levels in the PCC and OC and visuospatial memory. Additionally, a decreased trend of closed form GSH levels with age was also observed in the PCC among 15 participants. Taken together, these findings enhance our understanding of the brain both closed and extended form GSH time course during normal aging and associations with sex and memory, which is an essential first step for understanding the neurochemical underpinnings of healthy aging.

A Magnetic Resonance Spectroscopy Study on Polarity Subphenotypes in Bipolar Disorder

Although magnetic resonance spectroscopy (MRS) has provided in vivo measurements of brain chemical profiles in bipolar disorder (BD), there are no data on clinically and therapeutically important onset polarity (OP) and predominant polarity (PP). We conducted a proton MRS study in BD polarity subphenotypes, focusing on emotion regulation brain regions. Forty-one euthymic BD patients stratified according to OP and PP and sixteen healthy controls (HC) were compared. 1H-MRS spectra of the anterior and posterior cingulate cortex (ACC, PCC), left and right hippocampus (LHIPPO, RHIPPO) were acquired at 3.0T to determine metabolite concentrations. We found significant main effects of OP in ACC mI, mI/tNAA, mI/tCr, mI/tCho, PCC tCho, and RHIPPO tNAA/tCho and tCho/tCr. Although PP had no significant main effects, several medium and large effect sizes emerged. Compared to HC, manic subphenotypes (i.e., manic-OP, manic-PP) showed greater differences in RHIPPO and PCC, whereas depressive suphenotypes (i.e., depressive-OP, depressive-PP) in ACC. Effect sizes were consistent between OP and PP as high intraclass correlation coefficients (ICC) were confirmed. Our findings support the utility of MRS in the study of the neurobiological underpinnings of OP and PP, highlighting that the regional specificity of metabolite changes within the emotion regulation network consistently marks both polarity subphenotypes.

Glutamate Signaling in Patients With Parkinson Disease With REM Sleep Behavior Disorder

BACKGROUND AND OBJECTIVES

Clinical heterogeneity of patients with Parkinson disease (PD) is well recognized. PD with REM sleep behavior disorder (RBD) is a more malignant phenotype with faster motor progression and higher nonmotor symptom burden. However, the neural mechanisms underlying this clinical divergence concerning imbalances in neurotransmitter systems remain elusive.

METHODS

Combining magnetic resonance (MR) spectroscopy and [11C]ABP688 PET on a PET/MR hybrid system, we simultaneously investigated two different mechanisms of glutamate signaling in patients with PD. Patients were grouped according to their RBD status in overnight video-polysomnography and compared with age-matched and sex-matched healthy control (HC) participants. Total volumes of distribution (VT) of [11C]ABP688 were estimated with metabolite-corrected plasma concentrations during steady-state conditions between 45 and 60 minutes of the scan following a bolus-infusion protocol. Glutamate, glutamine, and glutathione levels were investigated with single-voxel stimulated echo acquisition mode MR spectroscopy of the left basal ganglia.

RESULTS

We measured globally elevated VT of [11C]ABP688 in 16 patients with PD and RBD compared with 17 patients without RBD and 15 HC participants (F(2,45) = 5.579, p = 0.007). Conversely, glutamatergic metabolites did not differ between groups and did not correlate with the regional VT of [11C]ABP688. VT of [11C]ABP688 correlated with the amount of REM sleep without atonia (F(1,42) = 5.600, p = 0.023) and with dopaminergic treatment response in patients with PD (F(1,30) = 5.823, p = 0.022).

DISCUSSION

Our results suggest that patients with PD and RBD exhibit altered glutamatergic signaling indicated by higher VT of [11C]ABP688 despite unaffected glutamate levels. The imbalance of glutamate receptors and MR spectroscopy glutamate metabolite levels indicates a novel mechanism contributing to the heterogeneity of PD and warrants further investigation of drugs targeting mGluR5.

The impact of spectral basis set composition on estimated levels of cingulate glutamate and its associations with different personality traits

BACKGROUND

1H-MRS is increasingly used in basic and clinical research to explain brain function and alterations respectively. In psychosis research it is now one of the main tools to investigate imbalances in the glutamatergic system. Interestingly, however, the findings are extremely variable even within patients of similar disease states. One reason may be the variability in analysis strategies, despite suggestions for standardization. Therefore, our study aimed to investigate the extent to which the basis set configuration- which metabolites are included in the basis set used for analysis- would affect the spectral fit and estimated glutamate (Glu) concentrations in the anterior cingulate cortex (ACC), and whether any changes in levels of glutamate would be associated with psychotic-like experiences and autistic traits.

METHODS

To ensure comparability, we utilized five different exemplar basis sets, used in research, and two different analysis tools, r-based spant applying the ABfit method and Osprey using the LCModel.

RESULTS

Our findings revealed that the types of metabolites included in the basis set significantly affected the glutamate concentration. We observed that three basis sets led to more consistent results across different concentration types (i.e., absolute Glu in mol/kg, Glx (glutamate + glutamine), Glu/tCr), spectral fit and quality measurements. Interestingly, all three basis sets included phosphocreatine. Importantly, our findings also revealed that glutamate levels were differently associated with both schizotypal and autistic traits depending on basis set configuration and analysis tool, with the same three basis sets showing more consistent results.

CONCLUSIONS

Our study highlights that scientific results may be significantly altered depending on the choices of metabolites included in the basis set, and with that emphasizes the importance of carefully selecting the configuration of the basis set to ensure accurate and consistent results, when using MR spectroscopy. Overall, our study points out the need for standardized analysis pipelines and reporting.

2-Hydroxyglutarate as an MR spectroscopic predictor of an IDH mutation in gliomas

The mutated enzyme isocitrate dehydrogenase (IDH) 1 and 2 has been detected in various tumor entities such as gliomas and can convert α-ketoglutarate into the oncometabolite 2-hydroxyglutarate (2-HG). This neuro-oncologically significant metabolic product can be detected by MR spectroscopy and is therefore suitable for noninvasive glioma classification and therapy monitoring.This paper provides an up-to-date overview of the methodology and relevance of 1H-MR spectroscopy (MRS) in the oncological primary and follow-up diagnosis of gliomas. The possibilities and limitations of this MR spectroscopic examination are evaluated on the basis of the available literature.By detecting 2-HG, MRS can in principle offer a noninvasive alternative to immunohistological analysis thus avoiding surgical intervention in some cases. However, in addition to an adapted and optimized examination protocol, the individual measurement conditions in the examination region are of decisive importance. Due to the inherently small signal of 2-HG, unfavorable measurement conditions can influence the reliability of detection. · MR spectroscopy enables the non-invasive detection of 2-hydroxyglutarate.. · The measurement of this metabolite allows the detection of an IDH mutation in gliomas.. · The choice of MR examination method is particularly important.. · Detection reliability is influenced by glioma size, necrotic tissue and the existing measurement conditions.. · Bauer J, Raum HN, Kugel H et al. 2-Hydroxyglutarate as an MR spectroscopic predictor of an IDH mutation in gliomas. Fortschr Röntgenstr 2024; DOI 10.1055/a-2285-4923.

VHL loss reprograms the immune landscape to promote an inflammatory myeloid microenvironment in renal tumorigenesis

Clear cell renal cell carcinoma (ccRCC) is characterized by dysregulated hypoxia signaling and a tumor microenvironment (TME) highly enriched in myeloid and lymphoid cells. Loss of the von Hippel Lindau (VHL) gene is a critical early event in ccRCC pathogenesis and promotes stabilization of HIF. Whether VHL loss in cancer cells affects immune cells in the TME remains unclear. Using Vhl WT and Vhl-KO in vivo murine kidney cancer Renca models, we found that Vhl-KO tumors were more infiltrated by immune cells. Tumor-associated macrophages (TAMs) from Vhl-deficient tumors demonstrated enhanced in vivo glucose consumption, phagocytosis, and inflammatory transcriptional signatures, whereas lymphocytes from Vhl-KO tumors showed reduced activation and a lower response to anti-programmed cell death 1 (anti-PD-1) therapy in vivo. The chemokine CX3CL1 was highly expressed in human ccRCC tumors and was associated with Vhl deficiency. Deletion of Cx3cl1 in cancer cells decreased myeloid cell infiltration associated with Vhl loss to provide a mechanism by which Vhl loss may have contributed to the altered immune landscape. Here, we identify cancer cell-specific genetic features that drove environmental reprogramming and shaped the tumor immune landscape, with therapeutic implications for the treatment of ccRCC.

Glutamate measurements using edited MRS

PURPOSE

To demonstrate J-difference coediting of glutamate using Hadamard encoding and reconstruction of Mescher-Garwood-edited spectroscopy (HERMES).

METHODS

Density-matrix simulations of HERMES (TE 80 ms) and 1D J-resolved (TE 31-229 ms) of glutamate (Glu), glutamine (Gln), γ-aminobutyric acid (GABA), and glutathione (GSH) were performed. HERMES comprised four sub-experiments with editing pulses applied as follows: (A) 1.9/4.56 ppm simultaneously (ONGABA /ONGSH ); (B) 1.9 ppm only (ONGABA /OFFGSH ); (C) 4.56 ppm only (OFFGABA /ONGSH ); and (D) 7.5 ppm (OFFGABA /OFFGSH ). Phantom HERMES and 1D J-resolved experiments of Glu were performed. Finally, in vivo HERMES (20-ms editing pulses) and 1D J-resolved (TE 31-229 ms) experiments were performed on 137 participants using 3 T MRI scanners. LCModel was used for quantification.

RESULTS

HERMES simulation and phantom experiments show a Glu-edited signal at 2.34 ppm in the Hadamard sum combination A+B+C+D with no overlapping Gln signal. The J-resolved simulations and phantom experiments show substantial TE modulation of the Glu and Gln signals across the TEs, whose average yields a well-resolved Glu signal closely matching the Glu-edited signal from the HERMES sum spectrum. In vivo quantification of Glu show that the two methods are highly correlated (p < 0.001) with a bias of ∼10%, along with similar between-subject coefficients of variation (HERMES/TE-averaged: ∼7.3%/∼6.9%). Other Hadamard combinations produce the expected GABA-edited (A+B-C-D) or GSH-edited (A-B+C-D) signal.

CONCLUSION

HERMES simulation and phantom experiments show the separation of Glu from Gln. In vivo HERMES experiments yield Glu (without Gln), GABA, and GSH in a single MRS scan.

1H and 31P magnetic resonance spectroscopy reveals potential pathogenic and biomarker metabolite alterations in Lafora disease

Lafora disease is a fatal teenage-onset progressive myoclonus epilepsy and neurodegenerative disease associated with polyglucosan bodies. Polyglucosans are long-branched and as a result precipitation- and aggregation-prone glycogen. In mouse models, downregulation of glycogen synthase, the enzyme that elongates glycogen branches, prevents polyglucosan formation and rescues Lafora disease. Mouse work, however, has not yet revealed the mechanisms of polyglucosan generation, and few in vivo human studies have been performed. Here, non-invasive in vivo magnetic resonance spectroscopy (1H and 31P) was applied to test scan feasibility and assess neurotransmitter balance and energy metabolism in Lafora disease towards a better understanding of pathogenesis. Macromolecule-suppressed gamma-aminobutyric acid (GABA)-edited 1H magnetic resonance spectroscopy and 31P magnetic resonance spectroscopy at 3 and 7 tesla, respectively, were performed in 4 Lafora disease patients and a total of 21 healthy controls (12 for the 1H magnetic resonance spectroscopy and 9 for the 31PMRS). Spectra were processed using in-house software and fit to extract metabolite concentrations. From the 1H spectra, we found 33% lower GABA concentrations (P = 0.013), 34% higher glutamate + glutamine concentrations (P = 0.011) and 24% lower N-acetylaspartate concentrations (P = 0.0043) in Lafora disease patients compared with controls. From the 31P spectra, we found 34% higher phosphoethanolamine concentrations (P = 0.016), 23% lower nicotinamide adenine dinucleotide concentrations (P = 0.003), 50% higher uridine diphosphate glucose concentrations (P = 0.004) and 225% higher glucose 6-phosphate concentrations in Lafora disease patients versus controls (P = 0.004). Uridine diphosphate glucose is the substrate of glycogen synthase, and glucose 6-phosphate is its extremely potent allosteric activator. The observed elevated uridine diphosphate glucose and glucose 6-phosphate levels are expected to hyperactivate glycogen synthase and may underlie the generation of polyglucosans in Lafora disease. The increased glutamate + glutamine and reduced GABA indicate altered neurotransmission and energy metabolism, which may contribute to the disease's intractable epilepsy. These results suggest a possible basis of polyglucosan formation and potential contributions to the epilepsy of Lafora disease. If confirmed in larger human and animal model studies, measurements of the dysregulated metabolites by magnetic resonance spectroscopy could be developed into non-invasive biomarkers for clinical trials.

Diffusion of brain metabolites highlights altered brain microstructure in type C hepatic encephalopathy: a 9.4 T preliminary study

Introduction

Type C hepatic encephalopathy (HE) is a decompensating event of chronic liver disease leading to severe motor and cognitive impairment. The progression of type C HE is associated with changes in brain metabolite concentrations measured by 1H magnetic resonance spectroscopy (MRS), most noticeably a strong increase in glutamine to detoxify brain ammonia. In addition, alterations of brain cellular architecture have been measured ex vivo by histology in a rat model of type C HE. The aim of this study was to assess the potential of diffusion-weighted MRS (dMRS) for probing these cellular shape alterations in vivo by monitoring the diffusion properties of the major brain metabolites.

Methods

The bile duct-ligated (BDL) rat model of type C HE was used. Five animals were scanned before surgery and 6- to 7-week post-BDL surgery, with each animal being used as its own control. 1H-MRS was performed in the hippocampus (SPECIAL, TE = 2.8 ms) and dMRS in a voxel encompassing the entire brain (DW-STEAM, TE = 15 ms, diffusion time = 120 ms, maximum b-value = 25 ms/μm2) on a 9.4 T scanner. The in vivo MRS acquisitions were further validated with histological measures (immunohistochemistry, Golgi-Cox, electron microscopy).

Results

The characteristic 1H-MRS pattern of type C HE, i.e., a gradual increase of brain glutamine and a decrease of the main organic osmolytes, was observed in the hippocampus of BDL rats. Overall increased metabolite diffusivities (apparent diffusion coefficient and intra-stick diffusivity-Callaghan's model, significant for glutamine, myo-inositol, and taurine) and decreased kurtosis coefficients were observed in BDL rats compared to control, highlighting the presence of osmotic stress and possibly of astrocytic and neuronal alterations. These results were consistent with the microstructure depicted by histology and represented by a decline in dendritic spines density in neurons, a shortening and decreased number of astrocytic processes, and extracellular edema.

Discussion

dMRS enables non-invasive and longitudinal monitoring of the diffusion behavior of brain metabolites, reflecting in the present study the globally altered brain microstructure in BDL rats, as confirmed ex vivo by histology. These findings give new insights into metabolic and microstructural abnormalities associated with high brain glutamine and its consequences in type C HE.

Quantification of Cerebral Glucose Concentrations via Detection of the H1-α-Glucose Peak in 1 H MRS at 7 T

BACKGROUND

Sensitive detection and quantification of cerebral glucose is desired.

PURPOSE

To quantify cerebral glucose by detecting the H1-α-glucose peak at 5.23 ppm in 1 H magnetic resonance spectroscopy at 7 T.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-eight non-fasted healthy subjects (aged 20-28 years).

FIELD STRENGTH/SEQUENCE

Short echo time stimulated echo acquisition mode (short-TE STEAM) and semi-localized by adiabatic selective refocusing (semi-LASER) at 7 T.

ASSESSMENT

Single voxel spectra were obtained from the posterior cingulate cortex (27-mL) using a 32-channel head coil. The H1-α-glucose peak in the spectrum with retrospective removal of the residual water peak was fitted using LCModel with a glucose basis set of only the H1-α-glucose peak. Conventional spectral analysis was performed with a glucose basis set of a full spectral pattern of glucose, also. Fitting precision was evaluated with Cramér-Rao lower bounds (CRLBs). The repeatability of glucose quantification via the semi-LASER sequence was tested.

STATISTICAL TESTS

Paired or Welch's t-test were used for normally distributed values. A P value of <0.05 was considered significant. The repeatability of measures was analyzed using coefficient of variation (CV).

RESULTS

Removal of the residual water peak improved the flatness and stability of baselines around the H1-α-glucose peak and reduced CRLBs for fitting the H1-α-glucose peak. The semi-LASER sequence was superior to the short-TE STEAM in the higher signal-to-noise ratio of the H1-α-glucose peak (mean ± SD 7.9 ± 2.5, P < 0.001). The conventional analysis overfitted the H1-α-glucose peak. The individual CVs of glucose quantification by detecting the H1-α-glucose peak were smaller than the corresponding CRLBs.

DATA CONCLUSION

Cerebral glucose concentration is quantitated to be 1.07 mM by detecting the H1-α-glucose peak in the semi-LASER spectra. Despite requiring long scan times, detecting the H1-α-glucose peak allows true glucose quantification free from the influence of overlapping taurine and macromolecule signals.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY STAGE: 1.

Improved reproducibility of γ-aminobutyric acid measurement from short-echo-time proton MR spectroscopy by linewidth-matched basis sets in LCModel

γ-Aminobutyric acid (GABA), as the primary inhibitory neurotransmitter, is extremely important for maintaining healthy brain function, and deviations from GABA homeostasis are related to various brain diseases. Short-echo-time (short-TE) proton MR spectroscopy (1 H-MRS) has been employed to measure GABA concentration from various human brain regions at high magnetic fields. The aim of this study was to investigate the effect of spectral linewidth on GABA quantification and explore the application of an optimized basis-set preparation approach using a spectral-linewidth-matched (LM) basis set in LCModel to improve the reproducibility of GABA quantification from short-TE 1 H-MRS. In contrast to the fixed-linewidth basis-set approach, the LM basis-set preparation approach, where all metabolite basis spectra were simulated with a linewidth 4 Hz narrower than that of water, showed a smaller standard deviation of estimated GABA concentration from synthetic spectra with varying linewidths and lineshapes. The test-retest reproducibility was assessed by the mean within-subject coefficient of variation, which improved from 19.2% to 12.0% in the thalamus, from 27.9% to 14.9% in the motor cortex, and from 9.7% to 2.8% in the medial prefrontal cortex using LM basis sets at 7 T. We conclude that spectral linewidth has a large effect on GABA quantification from short-TE 1 H-MRS data and that using LM basis sets in LCModel can improve the reproducibility of GABA quantification.

Improving magnetic resonance spectroscopy in the brainstem periaqueductal gray using spectral registration

PURPOSE

Functional understanding of the periaqueductal gray (PAG), a clinically relevant brainstem region, can be advanced using 1 H-MRS. However, the PAG's small size and high levels of physiological noise are methodologically challenging. This study aimed to (1) improve 1 H-MRS quality in the PAG using spectral registration for frequency and phase error correction; (2) investigate whether spectral registration is particularly useful in cases of greater head motion; and (3) examine metabolite quantification using literature-based or individual-based water relaxation times.

METHODS

Spectra were acquired in 33 healthy volunteers (50.1 years, SD = 17.19, 18 females) on a 3 T Philipps MR system using a point-resolved spectroscopy (PRESS) sequence optimized with very selective saturation pulses (OVERPRESS) and voxel-based flip angle calibration (effective volume of interest size: 8.8 × 10.2 × 12.2 mm3 ). Spectra were fitted using LCModel and SNR, NAA peak linewidths and Cramér-Rao lower bounds (CRLBs) were measured after spectral registration and after minimal frequency alignment.

RESULTS

Spectral registration improved SNR by 5% (p = 0.026, median value post-correction: 18.0) and spectral linewidth by 23% (p < 0.001, 4.3 Hz), and reduced the metabolites' CRLBs by 1% to 15% (p < 0.026). Correlational analyses revealed smaller SNR improvements with greater head motion (p = 0.010) recorded using a markerless motion tracking system. Higher metabolite concentrations were detected using individual-based compared to literature-based water relaxation times (p < 0.001).

CONCLUSION

This study demonstrates high-quality 1 H-MRS acquisition in the PAG using spectral registration. This shows promise for future 1 H-MRS studies in the PAG and possibly other clinically relevant brain regions with similar methodological challenges.

CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing, quantification, and analysis

Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or further infer their concentrations. Although the magnetic resonance vendors commonly provide basic functions of spectrum plots and metabolite quantification, the spread of clinical research of MRS is still limited due to the lack of easy-to-use processing software or platform. To address this issue, we have developed CloudBrain-MRS, a cloud-based online platform that provides powerful hardware and advanced algorithms. The platform can be accessed simply through a web browser, without the need of any program installation on the user side. CloudBrain-MRS also integrates the classic LCModel and advanced artificial intelligence algorithms and supports batch preprocessing, quantification, and analysis of MRS data from different vendors. Additionally, the platform offers useful functions: (1) Automatically statistical analysis to find biomarkers for diseases; (2) Consistency verification between the classic and artificial intelligence quantification algorithms; (3) Colorful three-dimensional visualization for easy observation of individual metabolite spectrum. Last, data of both healthy subjects and patients with mild cognitive impairment are used to demonstrate the functions of the platform. To the best of our knowledge, this is the first cloud computing platform for in vivo MRS with artificial intelligence processing. We have shared our cloud platform at MRSHub, providing at least two years of free access and service. If you are interested, please visit https://mrshub.org/software_all/#CloudBrain-MRS or https://csrc.xmu.edu.cn/CloudBrain.html.

Plasma Cell Differentiation, Antibody Quality, and Initial Germinal Center B Cell Population Depend on Glucose Influx Rate

Serum Ab concentrations, selection for higher affinity BCRs, and generation of higher Ab affinities are important elements of immune response optimization and functions of germinal center (GC) reactions. B cell proliferation requires nutrients to support the anabolism inherent in clonal expansion. Glucose usage by mouse GC B cells has been reported to contribute little to their energy needs, with questions raised as to whether glucose uptake or glycolysis increases in GC B cells compared with their naive precursors. Indeed, metabolism can be highly flexible, such that supply shortage along one pathway may be compensated by increased flux on others. We now show that reduction of the glucose transporter GLUT1 in mice after establishment of a preimmune B cell repertoire, even after initiation of the GC B cell gene expression program, decreased initial GC B cell population numbers, affinity maturation, and plasma cell outputs. Glucose oxidation was heightened in GC B cells, but this hexose flowed more into the pentose phosphate pathway, whose activity was important in controlling reactive oxygen species (ROS) and Ab-secreting cell production. In modeling how glucose usage by B cells promotes the Ab response, the control of ROS appeared insufficient. Surprisingly, the combination of galactose, which mitigated ROS, with provision of mannose, an efficient precursor to glycosylation, supported robust production of and normal Ab secretion by Ab-secreting cells under glucose-free conditions. Collectively, the findings indicate that GCs depend on normal glucose influx, especially in plasma cell production, but reveal an unexpected metabolic flexibility in hexose requirements.

Diffusion-weighted SPECIAL improves the detection of J-coupled metabolites at ultrahigh magnetic field

PURPOSE

To improve the detection and subsequent estimation of the diffusion properties of strongly J-coupled metabolites in diffusion-weighted MRS (DWS).

METHODS

A new sequence for single-voxel diffusion-weighted 1 H MR spectroscopy, named DW-SPECIAL, is proposed. It combines the semi-adiabatic SPECIAL sequence with a stimulated echo diffusion block. Acquisitions with DW-SPECIAL and STE-LASER, the current gold standard for rodent DWS experiments at high fields, were performed at 14.1T on phantoms and in vivo on the rat brain. The apparent diffusion coefficient and intra-stick diffusivity (Callaghan's model, randomly-oriented sticks) were fitted and compared between the sequences for glutamate, glutamine, myo-inositol, taurine, total NAA, total Cho, total Cr, and the macromolecules.

RESULTS

The shorter TE achieved with DW-SPECIAL (18 ms against 33 ms with STE-LASER) substantially limited the metabolites' signal loss caused by J-evolution. In addition, DW-SPECIAL preserved the main advantages of STE-LASER: absence of cross-terms, diffusion time during a stimulated echo, and limited sensitivity to B1 inhomogeneities. In vivo, compared to STE-LASER, DW-SPECIAL yielded the same spectral quality and reduced the Cramer Rao Lower Bounds for J-coupled metabolites, irrespective of the b-value. DW-SPECIAL also reduced the SD of the metabolites' diffusion estimates based on individual animal fitting without loss of accuracy compared to the fit on the averaged decay.

CONCLUSION

We conclude that due to its reduced TE, DW-SPECIAL can serve as an alternative to STE-LASER when strongly J-coupled metabolites like glutamine are investigated, thereby extending the range of accessible metabolites in the context of DWS acquisitions.

Anterior cingulate metabolite levels, memory, and inhibitory control in abstinent men and women with alcohol use disorder

Alcohol use disorder (AUD) has been shown to have harmful cognitive and physiological effects, including altered brain chemistry. Further, although men and women may differ in vulnerability to the neurobiological effects of AUD, the results of existing studies have been conflicting. We examined brain metabolite levels and cognitive functions in a cross-section of men with AUD (AUDm) and women with AUD (AUDw) to determine the degree of abnormalities after extended periods of abstinence (mean, 6 years) and to evaluate gender differences in neuropsychological and metabolite measures. Participants were 40 abstinent individuals with AUD (22 AUDw, 18 AUDm) and 50 age-equivalent non-AUD comparison participants (26 NCw, 24 NCm). Proton magnetic resonance spectroscopy (MRS) was employed at 3 Tesla to acquire metabolite spectra from the dorsal anterior cingulate cortex (dACC). Brain metabolites N-acetyl aspartate (NAA), choline (Cho), myo-Inositol (mI), and glutamate & glutamine (Glx) were examined relative to measures of memory and inhibitory control. Metabolite levels did not differ significantly between AUD and NC groups. Memory and inhibitory-control impairments were observed in the AUD group. There also were significant group-specific associations between metabolite ratios and measures of inhibitory control. There were no group-by-gender interactions for the four metabolite ratios. These findings demonstrate that brain metabolite levels in men and women with AUD, following long-term abstinence, do not differ from individuals without AUD. The data also provide preliminary evidence of sustained associations between metabolite levels and measures of inhibitory control, a functional domain important for curtailing harmful drinking.

Identifying placental metabolic biomarkers of preterm birth using nuclear magnetic resonance of intact tissue samples

INTRODUCTION

Our understanding of the etiology of preterm birth (PTB) is incomplete; however, recent evidence has found a strong association between placental dysfunction and PTB. Altered placental metabolism may precede placental dysfunction and therefore the study of placental metabolic profiles could identify early biomarkers of PTB. In this study, we evaluated the placental metabolome in PTB in intact tissue samples using nuclear magnetic resonance (NMR) and spectral editing.

METHODS

Placental tissue samples were collected from nine term pregnancies and nine preterm pregnancies (<37 weeks' gestation). 1H NMR experiments on unprocessed tissue samples were performed using a high field magnet (500 MHz spectrometer) and a comprehensive multiphase NMR probe. The relative concentrations of 23 metabolites were corrected for gestational age and compared between groups.

RESULTS

The relative concentration of valine, glutamate and creatine were significantly decreased while alanine, choline and glucose were elevated in placentas from PTB pregnancies compared to controls (p < 0.05). Multivariate analysis using principal component analysis showed the PTB and control groups were significantly separated (p < 0.0001) and pathway analysis identified perturbations in the glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis and valine, leucine and isoleucine biosynthesis pathways.

CONCLUSION

PTB is associated with significant alterations in placental metabolism. This study helps improve our understanding of the etiology of PTB. It also highlights the potential for small molecule metabolites to serve as placental metabolic biomarkers to aid in the prediction and diagnosis of PTB. The results can be translated to clinical use via in utero magnetic resonance spectroscopy.

Optimized multi-voxel TE-averaged PRESS for glutamate detection in the human brain at 3T

PURPOSE

To optimize possible combinations of echo times (TE) for multi-voxel TE-averaged Point RESolved Spectroscopy (PRESS) while reducing the total number of TEs required to separate glutamate (Glu) and glutamine (Gln) within a clinically feasible scan time.

METHODS

General Approach to Magnetic resonance Mathematical Analysis (GAMMA) was used to implement 2D J-resolved PRESS technique, and the spectra of 14 individual brain metabolites were simulated at 64 different TEs. Monte Carlo simulations were used for selecting the best TE combinations to separate Glu and Gln using TE-averaged PRESS with a total number of two, three, four and five TEs. Single-voxel 1H-MRS data were acquired using 64 different TEs from a healthy volunteer on a clinical 3T MR scanner to validate the echo time combinations selected with simulations. Additionally, 2D 1H-MRSI data of eight healthy volunteers were acquired on a clinical 3T MR scanner using four different TEs that were determined by Monte Carlo simulations. Optimized TE-averaged PRESS spectra were created by averaging the spectra acquired at selected TEs. LCModel was used for spectral quantification. A Wilcoxon signed-rank test was used to detect statistically significant differences in Glu/Gln ratios between 35 ms PRESS and optimized TE-averaged PRESS data.

RESULTS

Glu could be clearly separated from Gln at 2.35 ppm, using optimized TE-averaged PRESS with only four TEs (35, 37, 40, and 42 ms) that were selected through Monte Carlo simulations. Glu/Gln ratios were significantly higher in the optimized TE-averaged PRESS data of healthy volunteers than in the 35 ms PRESS data (P = 0.008).

CONCLUSION

Optimized multi-voxel TE-averaged PRESS enabled faster and unobstructed quantification of Glu at multiple voxels in the human brain in vivo at 3T.

Non-invasive biomarkers for mild cognitive impairment and Alzheimer's disease

Alzheimer's disease is the most common type of dementia in the elderly. It is a progressive degenerative disorder that may begin to develop up to 15 years before clinical symptoms appear. The identification of early biomarkers is crucial to enable a prompt diagnosis and to start effective interventions. In this work, we conducted a metabolomic study using proton Nuclear Magnetic Resonance (1H NMR) spectroscopy in serum samples from patients with neuropathologically confirmed Alzheimer's disease (AD, n = 51), mild cognitive impairment (MCI, n = 27), and cognitively healthy controls (HC, n = 50) to search for metabolites that could be used as biomarkers. Patients and controls underwent yearly clinical follow-ups for up to six years. MCI group included samples from three subgroups of subjects with different disease progression rates. The first subgroup included subjects that remained clinically stable at the MCI stage during the period of study (stable MCI, S-MCI, n = 9). The second subgroup accounted for subjects which were diagnosed with MCI at the moment of blood extraction, but progressed to clinical dementia in subsequent years (MCI-to-dementia, MCI-D, n = 14). The last subgroup was composed of subjects that had been diagnosed as dementia for the first time at the moment of sample collection (incipient dementia, Incp-D, n = 4). Partial Least Square Discriminant Analysis (PLS-DA) models were developed. Three models were obtained, one to discriminate between AD and HC samples with high sensitivity (93.75%) and specificity (94.75%), another model to discriminate between AD and MCI samples (100% sensitivity and 82.35% specificity), and a last model to discriminate HC and MCI with lower sensitivity and specificity (67% and 50%). Differences within the MCI group were further studied in an attempt to determine those MCI subjects that could develop AD-type dementia in the future. The relative concentration of metabolites, and metabolic pathways were studied. Alterations in the pathways of alanine, aspartate and glutamate metabolism, pantothenate and CoA biosynthesis, and beta-alanine metabolism, were found when HC and MCI- D patients were compared. In contrast, no pathway was found disturbed in the comparison of S-MCI with HC groups. These results highlight the potential of 1H NMR metabolomics to support the diagnosis of dementia in a less invasive way, and set a starting point for the study of potential biomarkers to identify MCI or HC subjects at risk of developing AD in the future.

How can I measure brain acetylcholine levels in vivo? Advantages and caveats of commonly used approaches

The neurotransmitter acetylcholine (ACh) plays a central role in the regulation of multiple cognitive and behavioral processes, including attention, learning, memory, motivation, anxiety, mood, appetite, and reward. As a result, understanding ACh dynamics in the brain is essential for elucidating the neural mechanisms underlying these processes. In vivo measurements of ACh in the brain have been challenging because of the low concentrations and rapid turnover of this neurotransmitter. Here, we review a number of techniques that have been developed to measure ACh levels in the brain in vivo. We follow this with a deeper focus on use of genetically encoded fluorescent sensors coupled with fiber photometry, an accessible technique that can be used to monitor neurotransmitter release with high temporal resolution and specificity. We conclude with a discussion of methods for analyzing fiber photometry data and their respective advantages and disadvantages. The development of genetically encoded fluorescent ACh sensors is revolutionizing the field of cholinergic signaling, allowing temporally precise measurement of ACh release in awake, behaving animals. Use of these sensors has already begun to contribute to a mechanistic understanding of cholinergic modulation of complex behaviors.

Antisense Oligonucleotide Silencing Reverses Abnormal Neurochemistry in Spinocerebellar Ataxia 3 Mice

OBJECTIVE

Spinocerebellar ataxia type 3 (SCA3) is the most common dominantly inherited ataxia, and biomarkers are needed to noninvasively monitor disease progression and treatment response. Anti-ATXN3 antisense oligonucleotide (ASO) treatment has been shown to mitigate neuropathology and rescue motor phenotypes in SCA3 mice. Here, we investigated whether repeated ASO administration reverses brainstem and cerebellar neurochemical abnormalities by magnetic resonance spectroscopy (MRS).

METHODS

Symptomatic SCA3 mice received intracerebroventricular treatment of ASO or vehicle and were compared to wild-type vehicle-treated littermates. To quantify neurochemical changes in treated mice, longitudinal 9.4T MRS of cerebellum and brainstem was performed. Acquired magnetic resonance (MR) group means were analyzed by 2-way analysis of variance mixed-effects sex-adjusted analysis with post hoc Sidak correlation for multiple comparisons. Pearson correlations were used to relate SCA3 pathology and behavior.

RESULTS

MR spectra yielded 15 to 16 neurochemical concentrations in the cerebellum and brainstem. ASO treatment in SCA3 mice resulted in significant total choline rescue and partial reversals of taurine, glutamine, and total N-acetylaspartate across both regions. Some ASO-rescued neurochemicals correlated with reduction in diseased protein and nuclear ATXN3 accumulation. ASO-corrected motor activity correlated with total choline and total N-acetylaspartate levels early in disease.

INTERPRETATION

SCA3 mouse cerebellar and brainstem neurochemical trends parallel those in patients with SCA3. Decreased total choline may reflect oligodendrocyte abnormalities, decreased total N-acetylaspartate highlights neuronal health disturbances, and high glutamine may indicate gliosis. ASO treatment fully or partially reversed select neurochemical abnormalities in SCA3 mice, indicating the potential for these measures to serve as noninvasive treatment biomarkers in future SCA3 gene silencing trials. ANN NEUROL 2023;94:658-671.

Plasma cell differentiation, antibody quality, and initial germinal center B cell population depend on glucose influx rate

Antibody secretion into sera, selection for higher affinity BCR, and the generation of higher Ab affinities are important elements of immune response optimization, and a core function of germinal center reactions. B cell proliferation requires nutrients to support the anabolism inherent in clonal expansion. Glucose usage by GC B cells has been reported to contribute little to their energy needs, with questions raised as to whether or not glucose uptake or glycolysis increases in GC B cells compared to their naïve precursors. Indeed, metabolism can be highly flexible, such that supply shortage along one pathway may be compensated by increased flux on others. We now show that elimination of the glucose transporter GLUT1 after establishment of a pre-immune B cell repertoire, even after initiation of the GC B cell gene expression program, decreased initial GC B cell population numbers, affinity maturation, and PC outputs. Glucose oxidation was heightened in GC B cells, but this hexose flowed more into the pentose phosphate pathway (PPP), whose activity was important in controlling reactive oxygen (ROS) and ASC production. In modeling how glucose usage by B cells promotes the Ab response, the control of ROS appeared insufficient. Surprisingly, the combination of galactose, which mitigated ROS, with provision of mannose - an efficient precursor to glycosylation - supported robust production of and normal Ab secretion by ASC under glucose-free conditions. Collectively, the findings indicate that GC depend on normal glucose influx, especially in PC production, but reveal an unexpected metabolic flexibility in hexose requirements.

KEY POINTS

Glucose influx is critical for GC homeostasis, affinity maturation and the generation of Ab-secreting cells.Plasma cell development uses the Pentose Phosphate Pathway, and hexose sugars maintain redox homeostasis.PCs can develop and achieve robust Ab secretion in the absence of glucose using a combination of hexose alternatives.

Tissue-Specific Dependence of Th1 Cells on the Amino Acid Transporter SLC38A1 in Inflammation

Amino acid (AA) uptake is essential for T cell metabolism and function, but how tissue sites and inflammation affect CD4+ T cell subset requirements for specific AA remains uncertain. Here we tested CD4+ T cell AA demands with in vitro and multiple in vivo CRISPR screens and identify subset- and tissue-specific dependencies on the AA transporter SLC38A1 (SNAT1). While dispensable for T cell persistence and expansion over time in vitro and in vivo lung inflammation, SLC38A1 was critical for Th1 but not Th17 cell-driven Experimental Autoimmune Encephalomyelitis (EAE) and contributed to Th1 cell-driven inflammatory bowel disease. SLC38A1 deficiency reduced mTORC1 signaling and glycolytic activity in Th1 cells, in part by reducing intracellular glutamine and disrupting hexosamine biosynthesis and redox regulation. Similarly, pharmacological inhibition of SLC38 transporters delayed EAE but did not affect lung inflammation. Subset- and tissue-specific dependencies of CD4+ T cells on AA transporters may guide selective immunotherapies.

Neurochemical Differences between 1p/19q Codeleted and Noncodeleted IDH-mutant Gliomas by in Vivo MR Spectroscopy

Background Noninvasive identification of glioma subtypes is important for optimizing treatment strategies. Purpose To compare the in vivo neurochemical profiles between isocitrate dehydrogenase (IDH) 1-mutant 1p/19q codeleted gliomas and their noncodeleted counterparts measured by MR spectroscopy at 3.0 T with a point-resolved spectroscopy (PRESS) sequence optimized for D-2-hydroxyglutarate (2HG) detection. Materials and Methods Adults with IDH1-mutant gliomas were retrospectively included for this study from two university hospitals (inclusion period: January 2015 to July 2016 and September 2019 to June 2021, respectively) based on availability of 1p/19q codeletion status and a PRESS acquisition optimized for 2HG detection (echo time, 97 msec) at 3.0 T before any treatment. Spectral analysis was performed using LCModel and a simulated basis set. Metabolite quantification was performed using the water signal as a reference and correcting for water and metabolite longitudinal and transverse relaxation time constants. Concentration ratios were computed using total creatine (tCr) and total choline. A two-tailed unpaired t test was used to compare metabolite concentrations obtained in codeleted versus noncodeleted gliomas, accounting for multiple comparisons. Results Thirty-one adults (mean age, 39 years ± 8 [SD]; 19 male) were included, and 19 metabolites were quantified. Cystathionine concentration was higher in codeleted (n = 13) than noncodeleted (n = 18) gliomas when quantification was performed using the water signal or tCr as references (2.33 mM ± 0.98 vs 0.93 mM ± 0.94, and 0.34 mM ± 0.14 vs 0.14 mM ± 0.14, respectively; both P < .001). The sensitivity and specificity of PRESS to detect codeletion by means of cystathionine quantification were 92% and 61%, respectively. Other metabolites did not show evidence of a difference between groups (P > .05). Conclusion Higher cystathionine levels were detected in IDH1-mutant 1p/19q codeleted gliomas than in their noncodeleted counterparts with use of a PRESS sequence optimized for 2HG detection. Of 19 metabolites quantified, only cystathionine showed evidence of a difference in concentration between groups. Clinical trial registry no. NCT01703962 © RSNA, 2023 See also the editorial by Lin in this issue.

Application of a 1H Brain MRS Benchmark Dataset to Deep Learning for Out-of-Voxel Artifacts

Neural networks are potentially valuable for many of the challenges associated with MRS data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains 259,200 synthetic 1H MRS examples for training and testing neural networks. AGNOSTIC was created using 270 basis sets that were simulated across 18 field strengths and 15 echo times. The synthetic examples were produced to resemble in vivo brain data with combinations of metabolite, macromolecule, residual water signals, and noise. To demonstrate the utility, we apply AGNOSTIC to train two Convolutional Neural Networks (CNNs) to address out-of-voxel (OOV) echoes. A Detection Network was trained to identify the point-wise presence of OOV echoes, providing proof of concept for real-time detection. A Prediction Network was trained to reconstruct OOV echoes, allowing subtraction during post-processing. Complex OOV signals were mixed into 85% of synthetic examples to train two separate CNNs for the detection and prediction of OOV signals. AGNOSTIC is available through Dryad and all Python 3 code is available through GitHub. The Detection network was shown to perform well, identifying 95% of OOV echoes. Traditional modeling of these detected OOV signals was evaluated and may prove to be an effective method during linear-combination modeling. The Prediction Network greatly reduces OOV echoes within FIDs and achieved a median log10 normed-MSE of -1.79, an improvement of almost two orders of magnitude.

Vespa: Integrated applications for RF pulse design, spectral simulation and MRS data analysis

PURPOSE

The Vespa package (Versatile Simulation, Pulses, and Analysis) is described and demonstrated. It provides workflows for developing and optimizing linear combination modeling (LCM) fitting for 1 H MRS data using intuitive graphical user interface interfaces for RF pulse design, spectral simulation, and MRS data analysis. Command line interfaces for embedding workflows in MR manufacturer platforms and utilities for synthetic dataset creation are included. Complete provenance is maintained for all steps in workflows.

THEORY AND METHODS

Vespa is written in Python for compatibility across operating systems. It embeds the PyGAMMA spectral simulation library for spectral simulation. Multiprocessing methods accelerate processing and visualization. Applications use the Vespa database for results storage and cross-application access. Three projects demonstrate pulse, sequence, simulation, and data analysis workflows: (1) short TE semi-LASER single-voxel spectroscopy (SVS) LCM fitting, (2) optimizing MEGA-PRESS (MEscher-GArwood Point RESolved Spectroscopy) flip angle and LCM fitting, and (3) creating a synthetic short TE dataset.

RESULTS

The LCM workflows for in vivo basis set creation and spectral analysis showed reasonable results for both the short TE semi-LASER and MEGA-PRESS. Examples of pulses, simulations, and data fitting are shown in Vespa application interfaces for various steps to demonstrate the interactive workflow.

CONCLUSION

Vespa provides an efficient and extensible platform for characterizing RF pulses, pulse design, spectral simulation optimization, and automated LCM fitting via an interactive platform. Modular design and command line interface make it easy to embed in other platforms. As open source, it is free to the MRS community for use and extension. Vespa source code and documentation are available through GitHub.

Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease

Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Downfield Proton MRSI at 3 Tesla: A Pilot Study in Human Brain Tumors

PURPOSE

To investigate the use of 3D downfield proton magnetic resonance spectroscopic imaging (DF-MRSI) for evaluation of tumor recurrence in patients with glioblastoma (GBM).

METHODS

Seven patients (4F, age range 44-65 and mean ± standard deviation 59.3 ± 7.5 years) with previously treated GBM were scanned using a recently developed 3D DF-MRSI sequence at 3T. Short TE 3D DF-MRSI and water reference 3D-MRSI scans were collected with a nominal spatial resolution of 0.7 cm3. DF volume data in eight slices covered 12 cm of brain in the cranio-caudal axis. Data were analyzed using the 'LCModel' program and a basis set containing nine peaks ranging in frequency between 6.83 to 8.49 ppm. The DF8.18 (assigned to amides) and DF7.90 peaks were selected for the creation of metabolic images and statistical analysis. Longitudinal MR images and clinical history were used to classify brain lesions as either recurrent tumor or treatment effect, which may include necrosis. DF-MRSI data were compared between lesion groups (recurrent tumor, treatment effect) and normal-appearing brain.

RESULTS

Of the seven brain tumor patients, two were classified as having recurrent tumor and the rest were classified as treatment effect. Amide metabolite levels from recurrent tumor regions were significantly (p < 0.05) higher compared to both normal-appearing brain and treatment effect regions. Amide levels in lesion voxels classified as treatment effect were significantly lower than normal brain.

CONCLUSIONS

3D DF-MRSI in human brain tumors at 3T is feasible and was well tolerated by all patients enrolled in this preliminary study. Amide levels measured by 3D DF-MRSI were significantly different between treatment effect and tumor regrowth.

Atlas-Based Adaptive Hadamard-Encoded MR Spectroscopic Imaging at 3T

BACKGROUND

This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism.

METHODS

Adaptive Hadamard-encoded pulses were developed and integrated with atlas-based automatic prescription. The excitation profiles were evaluated via simulation, phantom and volunteer experiments. The feasibility of γ-aminobutyric acid (GABA)-edited dual-slice MRSI was also assessed.

RESULTS

The signal between slices in the dual-band MRSI was less than 1% of the slice profiles. Data from a homemade phantom containing separate, interfacing compartments of creatine and acetate solutions demonstrated ~0.4% acetate signal contamination relative to the amplitude in the excited creatine compartment. The normalized signal-to-noise ratios from atlas-based acquisitions in volunteers were found to be comparable between dual-slice, Hadamard-encoded MRSI and 3D acquisitions. The mean and standard deviation of the coefficients of variation for NAA/Cho from the repeated volunteer scans were 8.2% ± 0.8% and 10.1% ± 3.7% in the top and bottom slices, respectively. GABA-edited, dual-slice MRSI demonstrated simultaneous detection of signals from GABA and coedited macromolecules (GABA+) from both superior grey and deep grey regions of volunteers.

CONCLUSION

This study demonstrated a fully automated dual-slice MRSI acquisition using atlas-based automatic prescription and adaptive Hadamard-encoded pulses.

In vivo cortical glutathione response to oral fumarate therapy in relapsing-remitting multiple sclerosis: A single-arm open-label phase IV trial using 7-Tesla 1H MRS

BACKGROUND

This is an open-label, single-arm, single-center pilot study using 7-Tesla in vivo proton magnetic resonance spectroscopy (1H MRS) to measure brain cortical glutathione concentration at baseline before and during the use of oral fumarates as a disease-modifying therapy for multiple sclerosis. The primary endpoint of this research was the change in prefrontal cortex glutathione concentration relative to a therapy-naïve baseline after one year of oral fumarate therapy.

METHODS

Brain glutathione concentrations were examined by 1H MRS in single prefrontal and occipital cortex cubic voxels (2.5 × 2.5 × 2.5 cm3) before and during initiation of oral fumarate therapy (120 mg b.i.d. for 7 days and 240 mg b.i.d. thereafter). Additional measurements of related metabolites glutamate, glutamine, myoinositol, total N-acetyl aspartate, and total choline were also acquired in voxels centered on the same regions. Seven relapsing-remitting multiple sclerosis patients (4 f / 3 m, age range 28-50 years, mean age 40 years) naïve to fumarate therapy were scanned at pre-therapy baseline and after 1, 3, 6 and 12 months of therapy. A group of 8 healthy volunteers (4 f / 4 m, age range 33-48 years, mean age 41 years) was also scanned at baseline and Month 6 to characterize 1H-MRS measurement reproducibility over a comparable time frame.

RESULTS

In the multiple sclerosis cohort, general linear models demonstrated a significant positive linear relationship between prefrontal glutathione and time either linearly across all time points (+0.05 ± 0.02 mM/month, t(27) = 2.6, p = 0.02) or specifically for factor variable Month 12 (+0.6 ± 0.3 mM/12 months, t(24) = 2.2, p = 0.04) relative to baseline. No such effects of time on glutathione concentration were demonstrated in the occipital cortex or in the healthy volunteer group. Changes in occipital total choline were further observed in the multiple sclerosis cohort as well as prefrontal total choline and occipital glutamine and myoinositol in the control cohort throughout the study duration.

CONCLUSIONS

While the open-label single-arm pilot study design and abbreviated control series cannot support firm conclusions about the influence of oral fumarate therapy independent of test-retest factors or normal biological variation in a state of either health or disease, these results do justify further investigation at a larger scale into the potential relationship between prefrontal cortex glutathione increases and oral fumarate therapy in relapsing-remitting multiple sclerosis.

Differential Effects of Glutamine Inhibition Strategies on Antitumor CD8 T Cells

Activated T cells undergo metabolic reprogramming to meet anabolic, differentiation, and functional demands. Glutamine supports many processes in activated T cells, and inhibition of glutamine metabolism alters T cell function in autoimmune disease and cancer. Multiple glutamine-targeting molecules are under investigation, yet the precise mechanisms of glutamine-dependent CD8 T cell differentiation remain unclear. We show that distinct strategies of glutamine inhibition by glutaminase-specific inhibition with small molecule CB-839, pan-glutamine inhibition with 6-diazo-5-oxo-l-norleucine (DON), or by glutamine-depleted conditions (No Q) produce distinct metabolic differentiation trajectories in murine CD8 T cells. T cell activation with CB-839 treatment had a milder effect than did DON or No Q treatment. A key difference was that CB-839-treated cells compensated with increased glycolytic metabolism, whereas DON and No Q-treated cells increased oxidative metabolism. However, all glutamine treatment strategies elevated CD8 T cell dependence on glucose metabolism, and No Q treatment caused adaptation toward reduced glutamine dependence. DON treatment reduced histone modifications and numbers of persisting cells in adoptive transfer studies, but those T cells that remained could expand normally upon secondary Ag encounter. In contrast, No Q-treated cells persisted well yet demonstrated decreased secondary expansion. Consistent with reduced persistence, CD8 T cells activated in the presence of DON had reduced ability to control tumor growth and reduced tumor infiltration in adoptive cell therapy. Overall, each approach to inhibit glutamine metabolism confers distinct effects on CD8 T cells and highlights that targeting the same pathway in different ways can elicit opposing metabolic and functional outcomes.

Decreased GABA levels of the anterior and posterior cingulate cortex are associated with executive dysfunction in mild cognitive impairment

Background and purpose

Executive function impairment, a slight but noticeable cognitive deficit in mild cognitive impairment (MCI) patients, is influenced by gamma-aminobutyric acid (GABA) levels. Reduced cognitive function is accompanied by thinning of the cerebral cortex, which has higher GABA levels than white matter. However, the relationships among GABA levels, cortical thickness, and executive function in MCI patients have not yet been elucidated. We investigated the relationships among GABA levels, cortical thickness, and executive function in MCI patients.

Methods

In this study, a total of 36 MCI patients and 36 sex-, age-, and education-matched healthy controls (HC) were recruited. But 33 MCI patients and 35 HC were included because of head motion or poor data quality for three MCI patients and one HC. The levels of gamma-aminobutyric acid plus relative to creatine (GABA+/Cr) and glutamate-glutamine relative to creatine (Glx/Cr) in the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) were measured using the Meshcher-Garwood point resolved spectroscopy (MEGA-PRESS) sequence. Metabolite ratios, cortical thickness, and executive function and their interrelationships were determined in the MCI and HC groups.

Results

Patients with MCI showed lower GABA+/Cr levels in the ACC and PCC. Combined levels of GABA+ and Glx in the ACC and GABA+ in the PCC showed good diagnostic efficacy for MCI (AUC: 0.82). But no differences in cortical thickness were found between the two groups. In the MCI group, lower GABA+/Cr level was correlated to worse performance on the digit span test backward, and the shape trail test-B. The cortical thickness was not associated with GABA+ levels and executive function in patients.

Conclusion

These results implied that decreased GABA levels in the ACC and PCC had a critical role in the early diagnosis of impaired executive function of MCI. Therefore, GABA in the ACC and PCC could be a potential diagnostic marker of the executive function decline of MCI.

Multinuclear MRI Reveals Early Efficacy of Stem Cell Therapy in Stroke

Compromised adult human mesenchymal stem cells (hMSC) can impair cell therapy efficacy and further reverse ischemic recovery. However, in vitro assays require extended passage to characterize cells, limiting rapid assessment for therapeutic potency. Multinuclear magnetic resonance imaging and spectroscopy (MRI/S) provides near real-time feedback on disease progression and tissue recovery. Applied to ischemic stroke, 23Na MRI evaluates treatment efficacy within 24 h after middle cerebral artery occlusion, showing recovery of sodium homeostasis and lesion reduction in specimens treated with hMSC while 1H MRS identifies reduction in lactate levels. This combined metric was confirmed by evaluating treatment groups receiving healthy or compromised hMSC versus vehicle (sham saline injection) over 21 days. Behavioral tests to assess functional recovery and cell analysis for immunomodulatory and macrophage activity to detect hMSC potency confirm MR findings. Clinically, these MR metrics may prove critical to early evaluations of therapeutic efficacy and overall stroke recovery.

Progressive myoclonic epilepsy type 1 (EPM1) patients present with abnormal 1H MRS brain metabolic profiles associated with cognitive function

PURPOSE

Progressive myoclonic epilepsy, type 1A (EPM1, Unverricht-Lundborg disease), is a rare neurodegenerative autosomal recessive disorder characterized by stimulus-sensitive and action myoclonus and tonic-clonic epileptic seizures. Patients develop neurological symptoms, including ataxia, intention tremor, and dysarthria, over time, with relatively limited and nonspecific MRI atrophy findings. The effects of the disease on brain metabolism are largely unknown.

METHOD

Eighteen EPM1 patients (9 M, 9F) underwent clinical evaluation and neuropsychological testing, which included the assessment of intellectual ability, verbal memory, and psychomotor and executive functions. Magnetic resonance spectroscopy (MRS) and imaging (MRI) were performed on a 1.5 T MRI system. 2D MRS chemical shift imaging (CSI) maps (TE = 270) were obtained from the following regions of the brain: basal ganglia, thalamus, insula, splenium, and occipital white and gray matter, and N-acetyl-aspartate (NAA)-, choline (Cho)-, and lactate (Lac)-to-creatine (Cr) ratios were analyzed. Ten healthy age-and sex-matched subjects (5M, 5F) were used as controls for MRS.

RESULTS

We found significant brain metabolic changes involving lactate, NAA, and choline, which are widespread in the basal ganglia, thalamic nuclei, insula, and occipital areas of EPM1 patients. Changes, especially in the right insula, basal ganglia, and thalamus, were associated with intellectual abilities and impairment of the psychomotor and executive functions of EPM1 patients.

CONCLUSION

Multiple brain metabolic alterations suggest the presence of neurodegeneration associated with EPM1 progression. The changes in metabolite ratios are associated with the neurocognitive dysfunction caused by the disease. However, the role of MRS findings in understanding pathophysiology of EPM1 warrants further studies.

Quantification of cross-relaxation in downfield 1 H MRS at 7 T in human calf muscle

PURPOSE

The purpose of this study was to characterize the 1 H downfield MR spectrum from 8.0 to 10.0 ppm of human skeletal muscle at 7 T and determine the T1 and cross-relaxation rates of observed resonances.

METHODS

We performed downfield MRS in the calf muscle of 7 healthy volunteers. Single-voxel downfield MRS was collected using alternately selective or broadband inversion-recovery sequences and spectrally selective 90° E-BURP RF pulse excitation centered at 9.0 ppm with bandwidth = 600 Hz (2.0 ppm). MRS was collected using TIs of 50-2500 ms. We modeled recovery of the longitudinal magnetization of three observable resonances using two models: (1) a three-parameter model accounting for the apparent T1 recovery and (2) a Solomon model explicitly including cross-relaxation effects.

RESULTS

Three resonances were observed in human calf muscle at 7 T at 8.0, 8.2, and 8.5 ppm. We found broadband (broad) and selective (sel) inversion recovery T1  = mean ± SD (ms): T1-broad,8.0ppm  = 2108.2 ± 664.5, T1-sel,8.0ppm  = 753.6 ± 141.0 (p = 0.003); T1-broad,8.2ppm  = 2033.5 ± 338.4, T1-sel,8.2ppm  = 135.3 ± 35.3 (p < 0.0001); and T1-broad,8.5ppm  = 1395.4 ± 75.4, T1-sel,8.5ppm  = 107.1 ± 40.0 (p < 0.0001). Using the Solomon model, we found T1  = mean ± SD (ms): T1-8.0ppm  = 1595.6 ± 491.1, T1-8.2ppm  = 1737.2 ± 963.7, and T1-8.5ppm  = 849.8 ± 282.0 (p = 0.04). Post hoc tests corrected for multiple comparisons showed no significant difference in T1 between peaks. The cross-relaxation rate σAB  = mean ± SD (Hz) of each peak was σAB,8.0ppm  = 0.76 ± 0.20, σAB,8.2ppm  = 5.31 ± 2.27, and σAB,8.5ppm  = 7.90 ± 2.74 (p < 0.0001); post hoc t-tests revealed the cross-relaxation rate of the 8.0 ppm peak was significantly slower than the peaks at 8.2 ppm (p = 0.0018) and 8.5 ppm (p = 0.0005).

CONCLUSION

We found significant differences in effective T1 and cross-relaxation rates of 1 H resonances between 8.0 and 8.5 ppm in the healthy human calf muscle at 7 T.