2D in-vivo L-COSY spectroscopy identifies neurometabolite alterations in treated multiple sclerosis

Two-dimensional correlated spectroscopy records reduced neurotransmission in blast-exposed artillery soldiers after live fire training

There is a requirement for an objective method to determine a safe level of low-level military occupational blast, having recognised it can lead to neurological damage. The purpose of the current study was to evaluate the effect of artillery firing training on the neurochemistry of frontline soldiers using two-dimensional (2D) COrrelated SpectroscopY (2D COSY) in a 3-T clinical MR scanner. Ten men considered to be of sound health were evaluated before and after a week-long live firing exercise in two ways. Prior to the live fire exercise, all participants were screened by a clinical psychologist using a combination of clinical interviews and psychometric tests, and were then scanned with 3-T MRI. The protocols included T1- and T2-weighted images for diagnostic reporting and anatomical localisation and 2D COSY to record any neurochemical effects from the firing. No changes to the structural MRI were recorded. Nine substantive and statistically significant changes in the neurochemistry were recorded as a consequence of firing training. Glutamine and glutamate, glutathione, and two of the seven fucose-α (1-2)-glycans were significantly increased. N-acetyl aspartate, myo-inositol + creatine, and glycerol were also increased. Significant decreases were recorded for the glutathione cysteine moiety and tentatively assigned glycan with a 1-6 linkage (F2: 4.00, F1: 1.31 ppm). These molecules are part of three neurochemical pathways at the terminus of the neurons providing evidence of early markers of disruption to neurotransmission. Using this technology, the extent of deregulation can now be monitored for each frontline defender on a personalised basis. The capacity to monitor early a disruption in neurotransmitters, using the 2D COSY protocol, can observe the effect of firing and may be used to prevent or limit these events.

Neurometabolic changes in multiple sclerosis: Fingolimod versus beta interferon or glatiramer acetate therapy

BACKGROUND AND PURPOSE

Fingolimod has been shown to be more effective in reducing relapse rate and disability than injectable therapies in clinical trials. An increase in N-acetylaspartate (NAA) as measured by MR spectroscopy is correlated with maintaining axonal metabolic functions. This study compared the neurometabolic and volumetric changes in relapsing-remitting multiple sclerosis (RRMS) patients on fingolimod or injectable therapies with healthy controls (HCs).

METHODS

Ninety-eight RRMS (52 on fingolimod, 46 on injectable therapies (27 on glatiramer acetate and 19 on interferon) were age and sex-matched to 51 HCs. RRMS patients underwent cognitive, fatigue, and mental health assessments, as well as an Expanded disability status scale (EDSS). MRI/S was acquired from the hippocampus, posterior cingulate gyrus (PCG), and prefrontal cortex (PFC). Volumetric and neurometabolic measures were compared across cohorts using a univariate general linear model and correlated with clinical severity and neuropsychological scores.

RESULTS

Clinical parameters, MR-volumetric, and neurometabolic profiles showed no differences between treatment groups (p > .05). Compared to HCs, both RRMS cohorts showed volume changes in white matter (-13%), gray matter (-16%), and cerebral spinal fluid (CSF) (+17-23%), as well as reduced NAA (-17%, p = .001, hippocampus), (-7%, p = .001, PCG), and (-9%, p = .001, PFC). MRI/S metrics in three regions were moderately correlated with cognition and fatigue functions.

CONCLUSION

While both treatment arms showed overall similar volumetric and neurometabolic profiles, longitudinal studies are warranted to clarify neurometabolic changes and associations with treatment efficacy.

Two-dimensional correlated spectroscopy distinguishes clear cell renal cell carcinoma from other kidney neoplasms and non-cancer kidney

Background

Routinely used clinical scanners, such as computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound (US), are unable to distinguish between aggressive and indolent tumor subtypes in masses localized to the kidney, often leading to surgical overtreatment. The results of the current investigation demonstrate that chemical differences, detected in human kidney biopsies using two-dimensional COrrelated SpectroscopY (2D L-COSY) and evaluated using multivariate statistical analysis, can distinguish these subtypes.

Methods

One hundred and twenty-six biopsy samples from patients with a confirmed enhancing kidney mass on abdominal imaging were analyzed as part of the training set. A further forty-three samples were used for model validation. In patients undergoing radical nephrectomy, biopsies of non-cancer kidney cortical tissue were also collected as a non-cancer control group. Spectroscopy data were analyzed using multivariate statistical analysis, including principal component analysis (PCA) and orthogonal projection to latent structures with discriminant analysis (OPLS-DA), to identify biomarkers in kidney cancer tissue that was also classified using the gold-standard of histopathology.

Results

The data analysis methodology showed good separation between clear cell renal cell carcinoma (ccRCC) versus non-clear cell RCC (non-ccRCC) and non-cancer cortical tissue from the kidneys of tumor-bearing patients. Variable Importance for the Projection (VIP) values, and OPLS-DA loadings plots were used to identify chemical species that correlated significantly with the histopathological classification. Model validation resulted in the correct classification of 37/43 biopsy samples, which included the correct classification of 15/17 ccRCC biopsies, achieving an overall predictive accuracy of 86%, Those chemical markers with a VIP value >1.2 were further analyzed using univariate statistical analysis. A subgroup analysis of 47 tumor tissues arising from T1 tumors revealed distinct separation between ccRCC and non-ccRCC tissues.

Conclusions

This study provides metabolic insights that could have future diagnostic and/or clinical value. The results of this work demonstrate a clear separation between clear cell and non-ccRCC and non-cancer kidney tissue from tumor-bearing patients. The clinical translation of these results will now require the development of a one-dimensional (1D) magnetic resonance spectroscopy (MRS) protocol, for the kidney, using an in vivo clinical MRI scanner.

Biochemical Correlations with Fatigue in Multiple Sclerosis Detected by MR 2D Localized Correlated Spectroscopy

BACKGROUND AND PURPOSE

Fatigue is the common symptom in patients with multiple sclerosis (MS), yet its pathophysiological mechanism is poorly understood. We investigated the metabolic changes in fatigue in a group of relapsing-remitting MS (RRMS) patients using MR two-dimensional localized correlated spectroscopy (2D L-COSY).

METHODS

Sixteen RRMS and 16 healthy controls were included in the study. Fatigue impact was assessed with the Modified Fatigue Impact Scale (MFIS). MR 2D L-COSY data were collected from the posterior cingulate cortex. Nonparametric statistical analysis was used to calculate the changes in creatine scaled metabolic ratios and their correlations with fatigue scores.

RESULTS

Compared to healthy controls, the RRMS group showed significantly higher fatigue and lower metabolic ratios for tyrosine, glutathione, homocarnosine (GSH+Hca), fucose-3, glutamine+glutamate (Glx), glycerophosphocholine (GPC), total choline, and N-acetylaspartate (NAA-2), while increased levels for isoleucine and glucose (P ≤ .05). Only GPC showed positive correlation with all fatigue domains (r = .537, P ≤ .05). On the other hand, Glx-upper, NAA-2, GSH+Hca, and fucose-3 showed negative correlations with all fatigue domains (r = -.345 to -.580, P ≤ .05). While tyrosine showed positive correlation with MFIS (r = .499, P ≤ .05), cognitive fatigue was negatively correlated with total GSH (r = -.530, P ≤ .05). No correlations were found between lesion load or brain volumes with fatigue score.

CONCLUSIONS

Our results suggest that fatigue in MS is strongly correlated with an imbalance in neurometabolites but not structural brain measurements.

Dysbiosis of the intestinal microbiome as a component of pathophysiology in the inborn errors of metabolism

Inborn errors of metabolism (IEMs) represent monogenic disorders in which specific enzyme deficiencies, or a group of enzyme deficiencies (e.g., peroxisomal biogenesis disorders) result in either toxic accumulation of metabolic intermediates or deficiency in the production of key end-products (e.g., low cholesterol in Smith-Lemli-Opitz syndrome (Gedam et al., 2012 [1]); low creatine in guanidinoacetic acid methyltransferase deficiency (Stromberger, 2003 [2])). Some IEMs can be effectively treated by dietary restrictions (e.g., phenylketonuria (PKU), maple syrup urine disease (MSUD)), and/or dietary intervention to remove offending compounds (e.g., acylcarnitine excretion with the oral intake of l-carnitine in the disorders of fatty acid oxidation). While the IEMs are predominantly monogenic disorders, their phenotypic presentation is complex and pleiotropic, impacting multiple physiological systems (hepatic and neurological function, renal and musculoskeletal impairment, cardiovascular and pulmonary activity, etc.). The metabolic dysfunction induced by the IEMs, as well as the dietary interventions used to treat them, are predicted to impact the gut microbiome in patients, and it is highly likely that microbiome dysbiosis leads to further exacerbation of the clinical phenotype. That said, only recently has the gut microbiome been considered as a potential pathomechanistic consideration in the IEMs. In this review, we overview the function of the gut-brain axis, the crosstalk between these compartments, and the expanding reports of dysbiosis in the IEMs recently reported. The potential use of pre- and probiotics to improve clinical outcomes in IEMs is also highlighted.

Current Methods of Magnetic Resonance for Noninvasive Assessment of Molecular Aspects of Pathoetiology in Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune disease with expanding axonal and neuronal degeneration in the central nervous system leading to motoric dysfunctions, psychical disability, and cognitive impairment during MS progression. The exact cascade of pathological processes (inflammation, demyelination, excitotoxicity, diffuse neuro-axonal degeneration, oxidative and metabolic stress, etc.) causing MS onset is still not fully understood, although several accompanying biomarkers are particularly suitable for the detection of early subclinical changes. Magnetic resonance (MR) methods are generally considered to be the most sensitive diagnostic tools. Their advantages include their noninvasive nature and their ability to image tissue in vivo. In particular, MR spectroscopy (proton 1H and phosphorus 31P MRS) is a powerful analytical tool for the detection and analysis of biomedically relevant metabolites, amino acids, and bioelements, and thus for providing information about neuro-axonal degradation, demyelination, reactive gliosis, mitochondrial and neurotransmitter failure, cellular energetic and membrane alternation, and the imbalance of magnesium homeostasis in specific tissues. Furthermore, the MR relaxometry-based detection of accumulated biogenic iron in the brain tissue is useful in disease evaluation. The early description and understanding of the developing pathological process might be critical for establishing clinically effective MS-modifying therapies.