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Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer's disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10-5 to 1.3 × 10-44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049-1.4 × 10-5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.
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Transportadoras de Casetes de Unión a ATP , Enfermedad de Alzheimer , Ceramidas , Animales , Ratones , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/metabolismo , Transportadoras de Casetes de Unión a ATP/genética , Transportadoras de Casetes de Unión a ATP/metabolismo , Ceramidas/metabolismo , Cromatografía Liquida , Estudio de Asociación del Genoma Completo , Lactosilceramidos , Metaboloma , Ratones Noqueados , Esfingomielinas , Espectrometría de Masas en TándemRESUMEN
Alzheimer's disease (AD) is a highly prevalent neurodegenerative disorder. Despite increasing evidence of the importance of metabolic dysregulation in AD, the underlying metabolic changes that may impact amyloid plaque formation are not understood, particularly for late-onset AD. This study analyzed genome-wide association studies (GWAS), transcriptomics, and proteomics data obtained from several data repositories to obtain differentially expressed (DE) multi-omics elements in mouse models of AD. We characterized the metabolic modulation in these data sets using gene ontology, transcription factor, pathway, and cell-type enrichment analyses. A predicted lipid signature was extracted from genome-scale metabolic networks (GSMN) and subsequently validated in a lipidomic data set derived from cortical tissue of ABCA-7 null mice, a mouse model of one of the genes associated with late-onset AD. Moreover, a metabolome-wide association study (MWAS) was performed to further characterize the association between dysregulated lipid metabolism in human blood serum and genes associated with AD risk. We found 203 DE transcripts, 164 DE proteins, and 58 DE GWAS-derived mouse orthologs associated with significantly enriched metabolic biological processes. Lipid and bioenergetic metabolic pathways were significantly over-represented across the AD multi-omics data sets. Microglia and astrocytes were significantly enriched in the lipid-predominant AD-metabolic transcriptome. We also extracted a predicted lipid signature that was validated and robustly modeled class separation in the ABCA7 mice cortical lipidome, with 11 of these lipid species exhibiting statistically significant modulations. MWAS revealed 298 AD single nucleotide polymorphisms-metabolite associations, of which 70% corresponded to lipid classes. These results support the importance of lipid metabolism dysregulation in AD and highlight the suitability of mapping AD multi-omics data into GSMNs to identify metabolic alterations.
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Enfermedad de Alzheimer , Humanos , Ratones , Animales , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/metabolismo , Lipidómica , Estudio de Asociación del Genoma Completo , Multiómica , Ratones Noqueados , Lípidos , Transportadoras de Casetes de Unión a ATP/genética , Transportadoras de Casetes de Unión a ATP/metabolismoRESUMEN
BACKGROUND: Poor diet quality is a risk factor for type 2 diabetes and cardiovascular disease. However, knowledge of metabolites marking adherence to Dietary Guidelines for Americans (2015 version) are limited. OBJECTIVES: The goal was to determine a pattern of metabolites associated with the Healthy Eating Index (HEI)-2015, which measures adherence to the Dietary Guidelines for Americans. METHODS: The analysis examined 3557 adult men and women from the longitudinal cohort Multiethnic Study of Atherosclerosis (MESA), without known cardiovascular disease and with complete dietary data. Fasting serum specimens and diet and demographic questionnaires were assessed at baseline. Untargeted 1H 1-dimensional nuclei magnetic resonance spectroscopy (600 MHz) was used to generate metabolomics and lipidomics. A metabolome-wide association study specified each spectral feature as outcomes, HEI-2015 score as predictor, adjusting for age, sex, race, and study site in linear regression analyses. Subsequently, hierarchical clustering defined the discrete groups of correlated nuclei magnetic resonance features associated with named metabolites, and the linear regression analysis assessed for associations with HEI-2015 total and component scores. RESULTS: The sample included 50% women with an mean age of 63 years, with 40% identifying as White, 23% as Black, 24% as Hispanic, and 13% as Chinese American. The mean HEI-2015 score was 66. The metabolome-wide association study identified 179 spectral features significantly associated with HEI-2015 score. The cluster analysis identified 7 clusters representing 4 metabolites; HEI-2015 score was significantly associated with all. HEI-2015 score was associated with proline betaine [ß = 0.12 (SE = 0.02); P = 4.70 × 10-13] and was inversely related to proline [ß = -0.13 (SE = 0.02); P = 4.45 × 10-14], 1,5 anhydrosorbitol [ß = -0.08 (SE = 0.02); P = 4.37 × 10-7] and unsaturated fatty acyl chains [ß = 0.08 (SE = 0.02); P = 8.98 × 10-7]. Intake of total fruit, whole grains, and seafood and plant proteins was associated with proline betaine. CONCLUSIONS: Diet quality is significantly associated with unsaturated fatty acyl chains, proline betaine, and proline. Further analysis may clarify the link between diet quality, metabolites, and pathogenesis of cardiometabolic disease.
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Enfermedades Cardiovasculares , Diabetes Mellitus Tipo 2 , Masculino , Adulto , Humanos , Femenino , Persona de Mediana Edad , Dieta Saludable , Dieta , MetabolómicaRESUMEN
BACKGROUND: Avocado consumption is linked to better glucose homeostasis, but small associations suggest potential population heterogeneity. Metabolomic data capture the effects of food intake after digestion and metabolism, thus accounting for individual differences in these processes. OBJECTIVES: To identify metabolomic biomarkers of avocado intake and to examine their associations with glycemia. METHODS: Baseline data from 6224 multi-ethnic older adults (62% female) included self-reported avocado intake, fasting glucose and insulin, and untargeted plasma proton nuclear magnetic resonance metabolomic features (metabolomic data were available for a randomly selected subset; N = 3438). Subsequently, incident type 2 diabetes (T2D) was assessed over an â¼18 y follow-up period. A metabolome-wide association study of avocado consumption status (consumer compared with nonconsumer) was conducted, and the relationship of these features with glycemia via cross-sectional associations with fasting insulin and glucose and longitudinal associations with incident T2D was examined. RESULTS: Three highly-correlated spectral features were associated with avocado intake at metabolome-wide significance levels (P < 5.3 ∗ 10-7) and combined into a single biomarker. We did not find evidence that these features were additionally associated with overall dietary quality, nor with any of 47 other food groups (all P > 0.001), supporting their suitability as a biomarker of avocado intake. Avocado intake showed a modest association only with lower fasting insulin (ß = -0.07 +/- 0.03, P = 0.03), an association that was attenuated to nonsignificance when additionally controlling for body mass index (kg/m2). However, our biomarker of avocado intake was strongly associated with lower fasting glucose (ß = -0.22 +/- 0.02, P < 2.0 ∗ 10-16), lower fasting insulin (ß = -0.17 +/- 0.02, P < 2.0 ∗ 10-16), and a lower incidence of T2D (hazard ratio: 0.68; 0.63-074, P < 2.0 ∗ 10-16), even when adjusting for BMI. CONCLUSIONS: Highly significant associations between glycemia and avocado-related metabolomic features, which serve as biomarkers of the physiological impact of dietary intake after digestion and absorption, compared to modest relationships between glycemia and avocado consumption, highlights the importance of considering individual differences in metabolism when considering diet-health relationships.
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Aterosclerosis , Diabetes Mellitus Tipo 2 , Persea , Humanos , Femenino , Anciano , Masculino , Diabetes Mellitus Tipo 2/epidemiología , Factores de Riesgo , Estudios Transversales , Biomarcadores , Insulina , GlucosaRESUMEN
More than 12 million people around the world suffer a stroke every year, one every 3 s. Stroke has a variety of causes and is often the result of a complex interaction of risk factors related to age, genetics, gender, lifestyle, and some cardiovascular and metabolic diseases. Despite this evidence, it is not possible to prevent the onset of stroke. The use of innovative methods for metabolite analysis has been explored in the last years to detect new stroke biomarkers. We use NMR spectroscopy to identify small molecule variations between different stages of stroke risk. The Framingham Stroke Risk Score was used in people over 63 years of age living in long-term care facilities (LTCF) to calculate the probability of suffering a stroke. Using this parameter, three study groups were formed: low stroke risk (LSR, control), moderate stroke risk (MSR) and high stroke risk (HSR). Univariate statistical analysis showed seven metabolites with increasing plasma levels across different stroke risk groups, from LSR to HSR: isoleucine, asparagine, formate, creatinine, dimethylsulfone and two unidentified molecules, which we termed "unknown-1" and "unknown-3". These metabolic markers can be used for early detection and to detect increasing stages of stroke risk more efficiently.
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Accidente Cerebrovascular , Humanos , Accidente Cerebrovascular/diagnóstico , Accidente Cerebrovascular/etiología , Espectroscopía de Resonancia Magnética/métodos , Imagen por Resonancia Magnética , Factores de Riesgo , Biomarcadores , Metabolómica/métodosRESUMEN
Untargeted metabolomics and lipidomics LC-MS experiments produce complex datasets, usually containing tens of thousands of features from thousands of metabolites whose annotation requires additional MS/MS experiments and expert knowledge. All-ion fragmentation (AIF) LC-MS/MS acquisition provides fragmentation data at no additional experimental time cost. However, analysis of such datasets requires reconstruction of parent-fragment relationships and annotation of the resulting pseudo-MS/MS spectra. Here, we propose a novel approach for automated annotation of isotopologues, adducts, and in-source fragments from AIF LC-MS datasets by combining correlation-based parent-fragment linking with molecular fragment matching. Our workflow focuses on a subset of features rather than trying to annotate the full dataset, saving time and simplifying the process. We demonstrate the workflow in three human serum datasets containing 599 features manually annotated by experts. Precision and recall values of 82-92% and 82-85%, respectively, were obtained for features found in the highest-rank scores (1-5). These results equal or outperform those obtained using MS-DIAL software, the current state of the art for AIF data annotation. Further validation for other biological matrices and different instrument types showed variable precision (60-89%) and recall (10-88%) particularly for datasets dominated by nonlipid metabolites. The workflow is freely available as an open-source R package, MetaboAnnotatoR, together with the fragment libraries from Github (https://github.com/gggraca/MetaboAnnotatoR).
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Metabolómica , Espectrometría de Masas en Tándem , Cromatografía Liquida/métodos , Humanos , Metabolómica/métodos , Programas Informáticos , Espectrometría de Masas en Tándem/métodos , Flujo de TrabajoRESUMEN
Integration of multiple datasets can greatly enhance bioanalytical studies, for example, by increasing power to discover and validate biomarkers. In liquid chromatography-mass spectrometry (LC-MS) metabolomics, it is especially hard to combine untargeted datasets since the majority of metabolomic features are not annotated and thus cannot be matched by chemical identity. Typically, the information available for each feature is retention time (RT), mass-to-charge ratio (m/z), and feature intensity (FI). Pairs of features from the same metabolite in separate datasets can exhibit small but significant differences, making matching very challenging. Current methods to address this issue are too simple or rely on assumptions that cannot be met in all cases. We present a method to find feature correspondence between two similar LC-MS metabolomics experiments or batches using only the features' RT, m/z, and FI. We demonstrate the method on both real and synthetic datasets, using six orthogonal validation strategies to gauge the matching quality. In our main example, 4953 features were uniquely matched, of which 585 (96.8%) of 604 manually annotated features were correct. In a second example, 2324 features could be uniquely matched, with 79 (90.8%) out of 87 annotated features correctly matched. Most of the missed annotated matches are between features that behave very differently from modeled inter-dataset shifts of RT, MZ, and FI. In a third example with simulated data with 4755 features per dataset, 99.6% of the matches were correct. Finally, the results of matching three other dataset pairs using our method are compared with a published alternative method, metabCombiner, showing the advantages of our approach. The method can be applied using M2S (Match 2 Sets), a free, open-source MATLAB toolbox, available at https://github.com/rjdossan/M2S.
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Metabolómica , Biomarcadores/análisis , Cromatografía Liquida/métodos , Espectrometría de Masas/métodos , Metabolómica/métodosRESUMEN
In this paper, we cover 4 years of live fish transports that ranged from 14 to 200 h (8 days), and bioloads from 3.8 to 76.9 kg/m3 . The key ingredients for success in all trips, where virtually no mortality occurred, was atributed to (1) pre-buffering the water with sodium bicarbonate and sodium carbonate at 50 g/m3 (each)-and/or ATM Alka-HaulTM at 25 g/m3 -and applying additional (partial or full) doses throughout each transport, whenever the tanks were accessible; (2) pre-quenching ammonia with ATM TriageTM at 32 g/m3 , and applying additional (partial or full) doses throughout each transport, whenever the tanks were accessible; (3) keeping the dissolved oxygen saturation rate above 100%, ideally above 150%; (4) Keeping temperature on the lower limit of each species' tolerance range; (5) Using foam fractionators to effectively eliminate organic matter from the water and (6) Using pure sine wave inverters, which allows for a steady supply of electrical current throughout the transport. The use of a 'preventive' versus 'corrective' pH buffering philosophy is also discussed.
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Salmo salar , Animales , Agua , Animales de ZoológicoRESUMEN
MOTIVATION: Liquid chromatography-mass spectrometry (LC-MS) is a standard method for proteomics and metabolomics analysis of biological samples. Unfortunately, it suffers from various changes in the retention times (RT) of the same compound in different samples, and these must be subsequently corrected (aligned) during data processing. Classic alignment methods such as in the popular XCMS package often assume a single time-warping function for each sample. Thus, the potentially varying RT drift for compounds with different masses in a sample is neglected in these methods. Moreover, the systematic change in RT drift across run order is often not considered by alignment algorithms. Therefore, these methods cannot effectively correct all misalignments. For a large-scale experiment involving many samples, the existence of misalignment becomes inevitable and concerning. RESULTS: Here, we describe an integrated reference-free profile alignment method, neighbor-wise compound-specific Graphical Time Warping (ncGTW), that can detect misaligned features and align profiles by leveraging expected RT drift structures and compound-specific warping functions. Specifically, ncGTW uses individualized warping functions for different compounds and assigns constraint edges on warping functions of neighboring samples. Validated with both realistic synthetic data and internal quality control samples, ncGTW applied to two large-scale metabolomics LC-MS datasets identifies many misaligned features and successfully realigns them. These features would otherwise be discarded or uncorrected using existing methods. The ncGTW software tool is developed currently as a plug-in to detect and realign misaligned features present in standard XCMS output. AVAILABILITY AND IMPLEMENTATION: An R package of ncGTW is freely available at Bioconductor and https://github.com/ChiungTingWu/ncGTW. A detailed user's manual and a vignette are provided within the package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Metabolómica , Espectrometría de Masas en Tándem , Algoritmos , Cromatografía Liquida , Proteómica , Programas InformáticosRESUMEN
Altered metabolism is one of the key hallmarks of cancer. The development of sensitive, reproducible and robust bioanalytical tools such as Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry techniques offers numerous opportunities for cancer metabolism research, and provides additional and exciting avenues in cancer diagnosis, prognosis and for the development of more effective and personalized treatments. In this chapter, we introduce the current state of the art of metabolomics and metabolic phenotyping approaches in cancer research and clinical diagnostics.
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Investigación Biomédica , Metabolómica , Neoplasias/diagnóstico , Neoplasias/metabolismo , Humanos , Espectroscopía de Resonancia Magnética , Espectrometría de MasasRESUMEN
Pyrococcus furiosus is a remarkable archaeon able to grow at temperatures around 100 °C. To gain insight into how this model hyperthermophile copes with heat stress, we compared transcriptomic and metabolomic data of cells subjected to a temperature shift from 90 °C to 97 °C. In this study, we used RNA-sequencing to characterize the global variation in gene expression levels, while nuclear magnetic resonance (NMR) and targeted ion exchange liquid chromatography-mass spectrometry (LC-MS) were used to determine changes in metabolite levels. Of the 552 differentially expressed genes in response to heat shock conditions, 257 were upregulated and 295 were downregulated. In particular, there was a significant downregulation of genes for synthesis and transport of amino acids. At the metabolite level, 37 compounds were quantified. The level of di-myo-inositol phosphate, a canonical heat stress solute among marine hyperthermophiles, increased considerably (5.4-fold) at elevated temperature. Also, the levels of mannosylglycerate, UDP-N-acetylglucosamine (UDPGlcNac) and UDP-N-acetylgalactosamine were enhanced. The increase in the pool of UDPGlcNac was concurrent with an increase in the transcript levels of the respective biosynthetic genes. This work provides the first metabolomic analysis of the heat shock response of a hyperthermophile.
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Respuesta al Choque Térmico , Metaboloma , Pyrococcus furiosus/genética , Transcriptoma , Pyrococcus furiosus/metabolismo , TermotoleranciaRESUMEN
After hatching, sea turtles leave the nest and disperse into the ocean. Many years later, they return to their natal coastlines. The period between their leaving and their returning to natal areas, known as the "Lost Years", is poorly understood. Satellite tracking studies aimed at studying the "Lost Years" are challenging due to the small size and prolonged dispersal phases of young individuals. Here, we summarize preliminary findings about the performance of prototype microsatellite tags deployed over a three-year period on 160 neonate to small juvenile sea turtles from four species released in the North Atlantic Ocean. We provide an overview of results analyzing tag performance with metrics to investigate transmission characteristics and causes of tag failure. Our results reveal that, despite certain unfavorable transmission features, overall tag performance was satisfactory. However, most track durations were shorter than those observed on individuals of similar size in other studies and did not allow for detailed analyses of trajectories and turtle behavior. Our study further suggests that tracking durations are correlated with the targeted species, highlighting a lack of robustness against some neritic behaviors. Unprecedented diving data obtained for neonate sea turtles in this study suggest that the vertical behaviors of early juveniles are already too strenuous for these miniaturized tags. Our findings will help to inform the biologging research community, showcasing recent technological advances for the species and life stages within our study.
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The evaluation of joint disease using synovial fluid is an emerging field of metabolic profiling. The analysis is challenged by multiple macromolecules which can obscure the small molecule chemistry. The use of protein precipitation and extraction has been evaluated previously, but not in synovial fluid. We systematically review the published NMR spectroscopy methods of synovial fluid analysis and investigated the efficacy of three different protein precipitation techniques: methanol, acetonitrile and trichloroacetic acid. The trichloroacetic wash removed the most protein. However, metabolite recoveries were universally very poor. Acetonitrile liquid/liquid extraction gave metabolite gains from four unknown compounds with spectral peaks at δ = 1.91 ppm, 3.64 ppm, 3.95 ppm & 4.05 ppm. The metabolite recoveries for acetonitrile were between 1.5 and 7 times higher than the methanol method, across all classes of metabolite. The methanol method was more effective in removing protein as reported by the free GAG undefined peak (44 % vs 125 %). However, qualitative evaluation showed that acetonitrile and methanol provided good restoration of the spectra to baseline. The methanol extraction has issues of a gelatinous substrate in the samples. All metabolite recoveries had a CV of > 15 %. A recommendation of acetonitrile liquid/liquid extraction was made for human synovial fluid (HSF) analysis. This is due to consistency, effective protein precipitation, recovery of metabolites and additional compounds not previously visible.
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Metanol , Líquido Sinovial , Humanos , Líquido Sinovial/química , Líquido Sinovial/metabolismo , Metanol/química , Espectroscopía de Resonancia Magnética/métodos , Extracción Líquido-Líquido , Acetonitrilos/metabolismoRESUMEN
BACKGROUND: Whether red meat consumption is associated with higher inflammation or confounded by increased adiposity remains unclear. Plasma metabolites capture the effects of diet after food is processed, digested, and absorbed, and correlate with markers of inflammation, so they can help clarify diet-health relationships. OBJECTIVE: To identify whether any metabolites associated with red meat intake are also associated with inflammation. METHODS: A cross-sectional analysis of observational data from older adults (52.84% women, mean age 63 ± 0.3 y) participating in the Multi-Ethnic Study of Atherosclerosis (MESA). Dietary intake was assessed by food-frequency questionnaire, alongside C-reactive protein (CRP), interleukin-2, interleukin-6, fibrinogen, homocysteine, and tumor necrosis factor alpha, and untargeted proton nuclear magnetic resonance (1H NMR) metabolomic features. Associations between these variables were examined using linear regression models, adjusted for demographic factors, lifestyle behaviors, and body mass index (BMI). RESULTS: In analyses that adjust for BMI, neither processed nor unprocessed forms of red meat were associated with any markers of inflammation (all P > 0.01). However, when adjusting for BMI, unprocessed red meat was inversely associated with spectral features representing the metabolite glutamine (sentinel hit: ß = -0.09 ± 0.02, P = 2.0 × 10-5), an amino acid which was also inversely associated with CRP level (ß = -0.11 ± 0.01, P = 3.3 × 10-10). CONCLUSIONS: Our analyses were unable to support a relationship between either processed or unprocessed red meat and inflammation, over and above any confounding by BMI. Glutamine, a plasma correlate of lower unprocessed red meat intake, was associated with lower CRP levels. The differences in diet-inflammation associations, compared with diet metabolite-inflammation associations, warrant further investigation to understand the extent that these arise from the following: 1) a reduction in measurement error with metabolite measures; 2) the extent that which factors other than unprocessed red meat intake contribute to glutamine levels; and 3) the ability of plasma metabolites to capture individual differences in how food intake is metabolized.
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Glutamina , Carne Roja , Humanos , Femenino , Anciano , Persona de Mediana Edad , Masculino , Estudios Transversales , Inflamación , Dieta , Carne , Factores de RiesgoRESUMEN
Predicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC.
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This work describes an exploratory NMR metabonomic study of second trimester maternal urine and plasma, in an attempt to characterize the metabolic changes underlying prenatal disorders and identify possible early biomarkers. Fetal malformations have the strongest metabolic impact in both biofluids, suggesting effects due to hypoxia (leading to hypoxanthine increased excretion) and a need for enhanced gluconeogenesis, with higher ketone bodies (acetone and 3-hydroxybutyric acid) production and TCA cycle demand (suggested by glucogenic amino acids and cis-aconitate overproduction). Choline and nucleotide metabolisms also seem affected and a distinct plasma lipids profile is observed for mothers with fetuses affected by central nervous system malformations. Urine from women who subsequently develop gestational diabetes mellitus exhibits higher 3-hydroxyisovalerate and 2-hydroxyisobutyrate levels, probably due to altered biotin status and amino acid and/or gut metabolisms (the latter possibly related to higher BMI values). Other urinary changes suggest choline and nucleotide metabolic alterations, whereas lower plasma betaine and TMAO levels are found. Chromosomal disorders and pre-preterm delivery groups show urinary changes in choline and, in the latter case, in 2-hydroxyisobutyrate. These results show that NMR metabonomics of maternal biofluids enables the noninvasive detection of metabolic changes associated to prenatal disorders, thus unveiling potential disorder biomarkers.
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Enfermedades Fetales/diagnóstico , Metabolómica , Resonancia Magnética Nuclear Biomolecular/métodos , Segundo Trimestre del Embarazo/metabolismo , Ciclo del Ácido Cítrico , Femenino , Enfermedades Fetales/sangre , Enfermedades Fetales/orina , Humanos , Embarazo , Segundo Trimestre del Embarazo/sangre , Segundo Trimestre del Embarazo/orinaRESUMEN
The impact of metabolism upon the altered pathology of joint disease is rapidly becoming recognized as an important area of study. Synovial joint fluid is an attractive and representative biofluid of joint disease. A systemic review revealed little evidence of the metabolic stability of synovial joint fluid collection, handling or storage, despite recent reports characterizing the metabolic phenotype in joint disease. We aim to report the changes in small molecule detection within human synovial fluid (HSF) using nuclear magnetic resonance (NMR) spectroscopy at varying storage temperatures, durations and conditions. HSF was harvested by arthrocentesis from patients with isolated monoarthropathy or undergoing joint replacement (nâ¯=â¯30). Short-term storage (0-12â¯h, 4°C & 18°C) and the effect of repeated freeze-thaw cycles (-80°C to 18°C) was assessed. Long-term storage was evaluated by early (-80°C, <21days) and late analysis (-80°C, 10-12 months). 1D NMR spectroscopy experiments, NOESYGPPR1D and CPMG identified metabolites and semi-quantification was performed. Samples demonstrated broad stability to freeze-thaw cycling and refrigeration of <4â¯h. Short-term room temperature or refrigerated storage showed significant variation in 2-ketoisovalerate, valine, dimethylamine, succinate, 2-hydroxybutyrate, and acetaminophen glucuronide. Lipid and macromolecule detection was variable. Long-term storage demonstrated significant changes in: acetate, acetoacetate, creatine, N,N-dimethylglycine, dimethylsulfone, 3-hydroxybutyrate and succinate. Changeable metabolites during short-term storage appeared to be energy-synthesis intermediates. Most metabolites were stable for the first four hours at room temperature or refrigeration, with notable exceptions. We therefore recommend that HSF samples should be kept refrigerated for no more than 4 hours prior to freezing at -80°C. Furthermore, storage of HSF samples for 10-12 months before analysis can affect the detection of selected metabolites.
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Manejo de Especímenes , Líquido Sinovial , Congelación , Humanos , Espectroscopía de Resonancia Magnética , Metabolómica , TemperaturaRESUMEN
AIMS: The diagnosis of joint infections is an inexact science using combinations of blood inflammatory markers and microscopy, culture, and sensitivity of synovial fluid (SF). There is potential for small molecule metabolites in infected SF to act as infection markers that could improve accuracy and speed of detection. The objective of this study was to use nuclear magnetic resonance (NMR) spectroscopy to identify small molecule differences between infected and noninfected human SF. METHODS: In all, 16 SF samples (eight infected native and prosthetic joints plus eight noninfected joints requiring arthroplasty for end-stage osteoarthritis) were collected from patients. NMR spectroscopy was used to analyze the metabolites present in each sample. Principal component analysis and univariate statistical analysis were undertaken to investigate metabolic differences between the two groups. RESULTS: A total of 16 metabolites were found in significantly different concentrations between the groups. Three were in higher relative concentrations (lipids, cholesterol, and N-acetylated molecules) and 13 in lower relative concentrations in the infected group (citrate, glycine, glycosaminoglycans, creatinine, histidine, lysine, formate, glucose, proline, valine, dimethylsulfone, mannose, and glutamine). CONCLUSION: Metabolites found in significantly greater concentrations in the infected cohort are markers of inflammation and infection. They play a role in lipid metabolism and the inflammatory response. Those found in significantly reduced concentrations were involved in carbohydrate metabolism, nucleoside metabolism, the glutamate metabolic pathway, increased oxidative stress in the diseased state, and reduced articular cartilage breakdown. This is the first study to demonstrate differences in the metabolic profile of infected and noninfected human SF, using a noninfected matched cohort, and may represent putative biomarkers that form the basis of new diagnostic tests for infected SF. Cite this article: Bone Joint Res 2021;10(1):85-95.
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This paper describes a metabonomic study of prenatal disorders using nuclear magnetic resonance (NMR) spectroscopy of amniotic fluid (AF) collected in the second trimester of pregnancy, to search for metabolite markers of fetal malformations, prediagnostic gestational diabetes (GD), preterm delivery (PTD), early rupture of membranes (PROM), and chromossomopathies. Fetal malformations were found to have the highest impact on AF metabolite composition, enabling statistical validation to be achieved by several multivariate analytical tools. Results confirmed previous indications that malformed fetuses seem to suffer altered energy metabolism and kidney underdevelopment. Newly found changes (namely in α-oxoisovalerate, ascorbate, creatinine, isoleucine, serine, threonine) suggest possible additional effects on protein and nucleotide sugar biosynthesis. Prediagnostic GD subjects showed an average increase in glucose and small decreases in several amino acids along with acetate, formate, creatinine, and glycerophosphocholine. Small metabolite changes were also observed in the AF of subjects eventually undergoing PTD and PROM, whereas no relevant changes were found for chromossomopathies (for which a low number of samples was considered). The potential value of these results for biochemical insight and prediction of prenatal disorders is discussed, as well as their limitations regarding number of samples and overlap of different disorders.
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Líquido Amniótico/metabolismo , Metaboloma/fisiología , Complicaciones del Embarazo/metabolismo , Segundo Trimestre del Embarazo/metabolismo , Biomarcadores , Metabolismo Energético , Femenino , Feto/anomalías , Humanos , Enfermedades Renales/embriología , Espectroscopía de Resonancia Magnética , Metabolómica/métodos , Embarazo , Complicaciones del Embarazo/diagnósticoRESUMEN
Esca is a destructive disease that affects vineyards leading to important losses in wine production. Information about the response of Vitis vinifera plants to this disease is scarce, particularly concerning changes in plant metabolism. In order to study the metabolic changes in Vitis plants affected by esca, leaves from both infected and non-affected cordons of V. vinifera cv. Alvarinho (collected in the Vinho Verde region, Portugal) were analysed. The metabolite composition of leaves from infected cordons with visible symptoms [diseased leaves (dl)] and from asymptomatic cordons [healthy leaves (hl)] was evaluated by 1D and 2D (1)H-nuclear magnetic resonance (NMR) spectroscopy. Principal component analysis (PCA) of the NMR spectra showed a clear separation between dl and hl leaves, indicating differential compound production due to the esca disease. NMR/PCA analysis allowed the identification of specific compounds characterizing each group, and the corresponding metabolic pathways are discussed. Altogether, the study revealed a significant increase of phenolic compounds in dl, compared with hl, accompanied by a decrease in carbohydrates, suggesting that dl are rerouting carbon and energy from primary to secondary metabolism. Other metabolic alterations detected comprised increased levels of methanol, alanine, and gamma-aminobutyric acid in dl, which might be the result of the activation of other defence mechanisms.