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Nuclear Magnetic Resonance Derived Biomarkers for Evaluating Cardiometabolic Risk in Youth and Young Adults Across the Spectrum of Glucose Tolerance.
Chung, ST, Matta, ST, Meyers, AG, Cravalho, CK, Villalobos-Perez, A, Dawson, JM, Sharma, VR, Sampson, ML, Otvos, JD, Magge, SN
Frontiers in endocrinology. 2021;:665292
Abstract
UNLABELLED Youth with obesity have an increased risk for cardiometabolic disease, but identifying those at highest risk remains a challenge. Four biomarkers that might serve this purpose are "by products" of clinical NMR LipoProfile® lipid testing: LPIR (Lipoprotein Insulin Resistance Index), GlycA (inflammation marker), BCAA (total branched-chain amino acids), and glycine. All are strongly related to insulin resistance and type 2 diabetes (T2DM) in adults (glycine inversely) and are independent of biological and methodological variations in insulin assays. However, their clinical utility in youth is unclear. We compared fasting levels of these biomarkers in 186 youth (42 lean normal glucose tolerant (NGT), 88 obese NGT, 23 with prediabetes (PreDM), and 33 with T2DM. All four biomarkers were associated with obesity and glycemia in youth. LPIR and GlycA were highest in youth with PreDM and T2DM, whereas glycine was lowest in youth with T2DM. While all four were correlated with HOMA-IR (Homeostatic Model Assessment for Insulin Resistance), LPIR had the strongest correlation (LPIR: r = 0.6; GlycA: r = 0.4, glycine: r = -0.4, BCAA r = 0.2, all P < 0.01). All four markers correlated with HbA1c (LPIR, GlycA, BCAA r ≥ 0.3 and glycine: r = -0.3, all P < 0.001). In multi-variable regression models, LPIR, GlycA, and glycine were independently associated with HOMA-IR (Adjusted R2 = 0.473, P < 0.001) and LPIR, glycine, and BCAA were independently associated with HbA1c (Adjusted R2 = 0.33, P < 0.001). An LPIR index of >44 was associated with elevated blood pressure, BMI, and dyslipidemia. Plasma NMR-derived markers were related to adverse markers of cardiometabolic risk in youth. LPIR, either alone or in combination with GlycA, should be explored as a non-insulin dependent predictive tool for development of insulin resistance and diabetes in youth. CLINICAL TRIAL REGISTRATION Clinicaltrials.gov, identifier NCT:02960659.
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Compartmental diffusion and microstructural properties of human brain gray and white matter studied with double diffusion encoding magnetic resonance spectroscopy of metabolites and water.
Lundell, H, Najac, C, Bulk, M, Kan, HE, Webb, AG, Ronen, I
NeuroImage. 2021;:117981
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Abstract
Double diffusion encoding (DDE) of the water signal offers a unique ability to separate the effect of microscopic anisotropic diffusion in structural units of tissue from the overall macroscopic orientational distribution of cells. However, the specificity in detected microscopic anisotropy is limited as the signal is averaged over different cell types and across tissue compartments. Performing side-by-side water and metabolite DDE spectroscopic (DDES) experiments provides complementary measures from which intracellular and extracellular microscopic fractional anisotropies (μFA) and diffusivities can be estimated. Metabolites are largely confined to the intracellular space and therefore provide a benchmark for intracellular μFA and diffusivities of specific cell types. By contrast, water DDES measurements allow examination of the separate contributions to water μFA and diffusivity from the intra- and extracellular spaces, by using a wide range of b values to gradually eliminate the extracellular contribution. Here, we aimed to estimate tissue and compartment specific human brain microstructure by combining water and metabolites DDES experiments. We performed our DDES measurements in two brain regions that contain widely different amounts of white matter (WM) and gray matter (GM): parietal white matter (PWM) and occipital gray matter (OGM) in a total of 20 healthy volunteers at 7 Tesla. Metabolite DDES measurements were performed at b = 7199 s/mm2, while water DDES measurements were performed with a range of b values from 918 to 7199 s/mm2. The experimental framework we employed here resulted in a set of insights pertaining to the morphology of the intracellular and extracellular spaces in both gray and white matter. Results of the metabolite DDES experiments in both PWM and OGM suggest a highly anisotropic intracellular space within neurons and glia, with the possible exception of gray matter glia. The water μFA obtained from the DDES results at high b values in both regions converged with that of the metabolite DDES, suggesting that the signal from the extracellular space is indeed effectively suppressed at the highest b value. The μFA measured in the OGM significantly decreased at lower b values, suggesting a considerably lower anisotropy of the extracellular space in GM compared to WM. In PWM, the water μFA remained high even at the lowest b value, indicating a high degree of organization in the interstitial space in WM. Tortuosity values in the cytoplasm for water and tNAA, obtained with correlation analysis of microscopic parallel diffusivity with respect to GM/WM tissue fraction in the volume of interest, are remarkably similar for both molecules, while exhibiting a clear difference between gray and white matter, suggesting a more crowded cytoplasm and more complex cytomorphology of neuronal cell bodies and dendrites in GM than those found in long-range axons in WM.
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Deuterium metabolic imaging - Back to the future.
De Feyter, HM, de Graaf, RA
Journal of magnetic resonance (San Diego, Calif. : 1997). 2021;:106932
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Abstract
Deuterium metabolic spectroscopy (DMS) and imaging (DMI) have recently been described as simple and robust MR-based methods to map metabolism with high temporal and/or spatial resolution. The metabolic fate of a wide range of suitable deuterated substrates, including glucose and acetate, can be monitored with deuterium MR methods in which the favorable MR characteristics of deuterium prevent many of the complications that hamper other techniques. The short T1 relaxation times lead to good MR sensitivity, while the low natural abundance prevents the need for water or lipid suppression. The sparsity of the deuterium spectra in combination with the low resonance frequency provides relative immunity to magnetic field inhomogeneity. Taken together, these features combine into a highly robust metabolic imaging method that has strong potential to become a dominant MR research tool and a viable clinical imaging modality. This perspective reviews the history of deuterium as a metabolic tracer, the use of NMR as a detection method for deuterium in vitro and in vivo and the recent development of DMS and DMI. Following a review of the NMR characteristics and the biological effects of deuterium, the promising future of DMI is outlined.
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Myocardial inflammation and energetics by cardiac MRI: a review of emerging techniques.
Tsampasian, V, Swift, AJ, Assadi, H, Chowdhary, A, Swoboda, P, Sammut, E, Dastidar, A, Cabrero, JB, Del Val, JR, Nair, S, et al
BMC medical imaging. 2021;(1):164
Abstract
The role of inflammation in cardiovascular pathophysiology has gained a lot of research interest in recent years. Cardiovascular Magnetic Resonance has been a powerful tool in the non-invasive assessment of inflammation in several conditions. More recently, Ultrasmall superparamagnetic particles of iron oxide have been successfully used to evaluate macrophage activity and subsequently inflammation on a cellular level. Current evidence from research studies provides encouraging data and confirms that this evolving method can potentially have a huge impact on clinical practice as it can be used in the diagnosis and management of very common conditions such as coronary artery disease, ischaemic and non-ischaemic cardiomyopathy, myocarditis and atherosclerosis. Another important emerging concept is that of myocardial energetics. With the use of phosphorus magnetic resonance spectroscopy, myocardial energetic compromise has been proved to be an important feature in the pathophysiological process of several conditions including diabetic cardiomyopathy, inherited cardiomyopathies, valvular heart disease and cardiac transplant rejection. This unique tool is therefore being utilized to assess metabolic alterations in a wide range of cardiovascular diseases. This review systematically examines these state-of-the-art methods in detail and provides an insight into the mechanisms of action and the clinical implications of their use.
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Biological functions, genetic and biochemical characterization, and NMR structure determination of the small zinc finger protein HVO_2753 from Haloferax volcanii.
Zahn, S, Kubatova, N, Pyper, DJ, Cassidy, L, Saxena, K, Tholey, A, Schwalbe, H, Soppa, J
The FEBS journal. 2021;(6):2042-2062
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Abstract
The genome of the halophilic archaeon Haloferax volcanii encodes more than 40 one-domain zinc finger µ-proteins. Only one of these, HVO_2753, contains four C(P)XCG motifs, suggesting the presence of two zinc binding pockets (ZBPs). Homologs of HVO_2753 are widespread in many euryarchaeota. An in frame deletion mutant of HVO_2753 grew indistinguishably from the wild-type in several media, but had a severe defect in swarming and in biofilm formation. For further analyses, the protein was produced homologously as well as heterologously in Escherichia coli. HVO_2753 was stable and folded in low salt, in contrast to many other haloarchaeal proteins. Only haloarchaeal HVO_2753 homologs carry a very hydrophilic N terminus, and NMR analysis showed that this region is very flexible and not part of the core structure. Surprisingly, both NMR analysis and a fluorimetric assay revealed that HVO_2753 binds only one zinc ion, despite the presence of two ZBPs. Notably, the analysis of cysteine to alanine mutant proteins by NMR as well by in vivo complementation revealed that all four C(P)XCG motifs are essential for folding and function. The NMR solution structure of the major conformation of HVO_2753 was solved. Unexpectedly, it was revealed that ZBP1 was comprised of C(P)XCG motifs 1 and 3, and ZBP2 was comprised of C(P)XCG motifs 2 and 4. There are several indications that ZBP2 is occupied by zinc, in contrast to ZBP1. To our knowledge, this study represents the first in-depth analysis of a zinc finger µ-protein in all three domains of life.
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The nuclear magnetic resonance metabolic profile: Impact of fasting status.
Smy, L, De Biase, I, Genzen, JR, Yuzyuk, T
Clinical biochemistry. 2021;:85-92
Abstract
INTRODUCTION Measurement of lipoprotein subclass concentration (-c), particle number (-p), and size (-s) by nuclear magnetic resonance (NMR) has gained traction in the clinical laboratory due to associations between smaller lipid particle sizes and atherogenic risk, especially for LDL-p. The standard protocols for lipoprotein measurements by NMR require fasting blood samples; however, patients may not fast properly before sample collection. The study objective was to evaluate the impact of fasting status on the NMR-based lipid profile and to identify key parameters differentiating between fasting and post-meal specimens. METHODS Forty-eight self-reported healthy male and female participants were recruited. Blood was collected after a 12 h fast and 4 h after a high fat meal. Samples were analyzed using the AXINON LipoFIT by NMR assay. The measurements included triglyceride, total cholesterol, IDL-c, and LDL, HDL, VLDL concentration, particle number, and size, as well as glucose, and four amino acids (alanine, valine, leucine and isoleucine). RESULTS As expected, triglycerides increased after the meal (58%, p < 0.0001). Significant changes were also observed for VLDL, LDL, and HDL parameters, and the branched chain amino acids. The ratio of Valine*VLDL-c/LDL-c or Isoleucine*VLDL-c/LDL-c provided equally effective differentiation of fasting and post-meal samples. The ratio cutoffs (79.1 and 23.6 when calculated using valine and isoleucine, respectively) had sensitivities of 86% and specificities of 93-95%. CONCLUSIONS The clinical impact on NMR results from post-meal samples warrants further evaluation. Algorithms to differentiate fasting and post-meal specimens may be useful in identifying suboptimal specimens.
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MR imaging and spectroscopy in degenerative ataxias: toward multimodal, multisite, multistage monitoring of neurodegeneration.
Öz, G, Harding, IH, Krahe, J, Reetz, K
Current opinion in neurology. 2020;(4):451-461
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Abstract
PURPOSE OF REVIEW Degenerative ataxias are rare and currently untreatable movement disorders, primarily characterized by neurodegeneration in the cerebellum and brainstem. We highlight MRI studies with the most potential for utility in pending ataxia trials and underscore advances in disease characterization and diagnostics in the field. RECENT FINDINGS With availability of advanced MRI acquisition methods and specialized software dedicated to the analysis of MRI of the cerebellum, patterns of cerebellar atrophy in different degenerative ataxias are increasingly well defined. The field further embraced rigorous multimodal investigations to study network-level microstructural and functional brain changes and their neurochemical correlates. MRI and magnetic resonance spectroscopy were shown to be more sensitive to disease progression than clinical scales and to detect abnormalities in premanifest mutation carriers. SUMMARY Magnetic resonance techniques are increasingly well placed for characterizing the expression and progression of degenerative ataxias. The most impactful work has arguably come through multi-institutional studies that monitor relatively large cohorts, multimodal investigations that assess the sensitivity of different measures and their interrelationships, and novel imaging approaches that are targeted to known pathophysiology (e.g., iron and spinal imaging in Friedreich ataxia). These multimodal, multi-institutional studies are paving the way to clinical trial readiness and enhanced understanding of disease in degenerative ataxias.
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Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders? Findings from a UK birth cohort with independent validation.
McBride, N, Yousefi, P, White, SL, Poston, L, Farrar, D, Sattar, N, Nelson, SM, Wright, J, Mason, D, Suderman, M, et al
BMC medicine. 2020;(1):366
Abstract
BACKGROUND Prediction of pregnancy-related disorders is usually done based on established and easily measured risk factors. Recent advances in metabolomics may provide earlier and more accurate prediction of women at risk of pregnancy-related disorders. METHODS We used data collected from women in the Born in Bradford (BiB; n = 8212) and UK Pregnancies Better Eating and Activity Trial (UPBEAT; n = 859) studies to create and validate prediction models for pregnancy-related disorders. These were gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), small for gestational age (SGA), large for gestational age (LGA) and preterm birth (PTB). We used ten-fold cross-validation and penalised regression to create prediction models. We compared the predictive performance of (1) risk factors (maternal age, pregnancy smoking, body mass index (BMI), ethnicity and parity) to (2) nuclear magnetic resonance-derived metabolites (N = 156 quantified metabolites, collected at 24-28 weeks gestation) and (3) combined risk factors and metabolites. The multi-ethnic BiB cohort was used for training and testing the models, with independent validation conducted in UPBEAT, a multi-ethnic study of obese pregnant women. RESULTS Maternal age, pregnancy smoking, BMI, ethnicity and parity were retained in the combined risk factor and metabolite models for all outcomes apart from PTB, which did not include maternal age. In addition, 147, 33, 96, 51 and 14 of the 156 metabolite traits were retained in the combined risk factor and metabolite model for GDM, HDP, SGA, LGA and PTB, respectively. These include cholesterol and triglycerides in very low-density lipoproteins (VLDL) in the models predicting GDM, HDP, SGA and LGA, and monounsaturated fatty acids (MUFA), ratios of MUFA to omega 3 fatty acids and total fatty acids, and a ratio of apolipoprotein B to apolipoprotein A-1 (APOA:APOB1) were retained predictors for GDM and LGA. In BiB, discrimination for GDM, HDP, LGA and SGA was improved in the combined risk factors and metabolites models. Risk factor area under the curve (AUC 95% confidence interval (CI)): GDM (0.69 (0.64, 0.73)), HDP (0.74 (0.70, 0.78)) and LGA (0.71 (0.66, 0.75)), and SGA (0.59 (0.56, 0.63)). Combined risk factor and metabolite models AUC 95% (CI): GDM (0.78 (0.74, 0.81)), HDP (0.76 (0.73, 0.79)) and LGA (0.75 (0.70, 0.79)), and SGA (0.66 (0.63, 0.70)). For GDM, HDP and LGA, but not SGA, calibration was good for a combined risk factor and metabolite model. Prediction of PTB was poor for all models. Independent validation in UPBEAT at 24-28 weeks and 15-18 weeks gestation confirmed similar patterns of results, but AUCs were attenuated. CONCLUSIONS Our results suggest a combined risk factor and metabolite model improves prediction of GDM, HDP and LGA, and SGA, when compared to risk factors alone. They also highlight the difficulty of predicting PTB, with all models performing poorly.
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NMR spectroscopy: a powerful tool for the analysis of polyphenols in extra virgin olive oil.
Olmo-Cunillera, A, López-Yerena, A, Lozano-Castellón, J, Tresserra-Rimbau, A, Vallverdú-Queralt, A, Pérez, M
Journal of the science of food and agriculture. 2020;(5):1842-1851
Abstract
Extra virgin olive oil (EVOO), a key component of the Mediterranean diet, has aroused interest in recent years due to its health properties. Nuclear magnetic resonance (NMR) spectroscopy is an appropriate tool for the accurate quantification of minor compounds in complex food matrices, such as polyphenols in olive oil. Flavonoids, lignans, secoiridoids and phenolic acids and alcohols in EVOO have been identified and quantified by NMR. This review provides an overview of the major developments in the structural elucidation of polyphenol compounds in EVOO. © 2019 Society of Chemical Industry.
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Microbial growth rates and local external mass transfer coefficients in a porous bed biofilm system measured by 19 F magnetic resonance imaging of structure, oxygen concentration, and flow velocity.
Simkins, JW, Stewart, PS, Codd, SL, Seymour, JD
Biotechnology and bioengineering. 2020;(5):1458-1469
Abstract
19 F nuclear magnetic resonance (NMR) oximetry and 1 H NMR velocimetry were used to noninvasively map oxygen concentrations and hydrodynamics in space and time in a model packed bed biofilm system in the presence and absence of flow. The development of a local oxygen sink associated with a single gel bead inoculated with respiring Escherichia coli was analyzed with a phenomenological model to determine the specific growth rate of the bacteria in situ, returning a value (0.66 hr-1 ) that was close to that measured independently in planktonic culture (0.62 hr-1 ). The decay of oxygen concentration in and around the microbiologically active bead was delayed and slower in experiments conducted under continuous flow in comparison to no-flow experiments. Concentration boundary layer thicknesses were determined and Sherwood numbers calculated to quantify external mass transfer resistance. Boundary layers were thicker in no-flow experiments compared to experiments with flow. Whereas the oxygen concentration profile across a reactive biofilm particle was symmetric in no-flow experiments, it was asymmetric with respect to flow direction in flow experiments with Sherwood numbers on the leading edge (Sh = 7) being larger than the trailing edge (Sh = 3.5). The magnitude of the experimental Sh was comparable to values predicted by a variety of correlations. These spatially resolved measurements of oxygen distribution in a geometrically complex model reveal in innovative detail the local coupling between microbial growth, oxygen consumption, and external mass transfer.