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Biomedical subjects

Elaine Holmes

Publications and source records attributed to Elaine Holmes.

At least 19 recordsLinked to original sources

Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice.

Here, we study the intricate relationship between gut microbiota and host cometabolic phenotypes associated with dietary-induced impaired glucose homeostasis and nonalcoholic fatty liver disease (NAFLD) in a mouse strain (129S6) known to be susceptible to these disease traits, using plasma and urine metabotyping, achieved by (1)H NMR spectroscopy. Multivariate statistical modeling of the spectra shows that the genetic predisposition of the 129S6 mouse to impaired glucose homeostasis and NAFLD is associated with disruptions of choline metabolism, i.e., low circulating levels of plasma phosphatidylcholine and high urinary excretion of methylamines (dimethylamine, trimethylamine, and trimethylamine-N-oxide), coprocessed by symbiotic gut microbiota and mammalian enzyme systems. Conversion of choline into methylamines by microbiota in strain 129S6 on a high-fat diet reduces the bioavailability of choline and mimics the effect of choline-deficient diets, causing NAFLD. These data also indicate that gut microbiota may play an active role in the development of insulin resistance.

Animals↗

Impact of analytical bias in metabonomic studies of human blood serum and plasma.

Concurrent with the explosion in the number of publications reporting biomarker discovery by profiling technologies, such as proteomics and pattern recognition, has been the increase in evidence highlighting the susceptibility of these approaches to analytical and experimental bias. The work presented here addresses these timely issues by delivering a detailed characterization of the effect of common sources of bias in clinical studies on serum and plasma profiles generated by a key technology in metabonomics, NMR spectroscopy. Specifically, differences in composition when blood samples were collected onto and in the absence of ice, over a series of serum-clot contact times, the stability of NMR-prepared samples over time and the effect on the metabolic profile of freeze-thawing were examined. While differences between individuals were far greater than variation from any other experimental factor, each of the conditions examined did cause slight alterations to the NMR profile that could produce a systematic bias. Variation due to clotting time caused changes in energy metabolites, which were delayed by ice with no other spectral effects. Room-temperature stability and hence NMR spectral repeatability were high (<1% intrasample variation). Higher molecular weight species such as lipoproteins were more susceptible to the variations present in the examined factors. These observations have implications for profiling study design, and hence, our results form a new and valuable resource for those attempting clinical metabolic profiling, for regulatory agencies involved in the licensing of clinical tests and in the generation of international reporting standards for metabonomics.

Humans↗

Statistical search space reduction and two-dimensional data display approaches for UPLC-MS in biomarker discovery and pathway analysis.

A new analytical strategy for biomarker recovery from directly coupled ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC Tof MS) data on biofluids is presented and exemplified using a study on hydrazine-induced liver toxicity. A key step in the strategy involves a novel procedure for reducing the spectroscopic search space by differential analysis of cohorts of normal and pathological samples using an orthogonal projection to latent structures discriminant analysis (O-PLS-DA). This efficiently sorts principal discriminators of toxicity from the background of thousands of metabolic features commonly observed in data sets generated by UPLC-MS analysis of biological fluids and is thus a powerful tool for biomarker discovery.

Animals↗

Metabonomics techniques and applications to pharmaceutical research & development.

In this review, the background to the approach known as metabonomics is provided, giving a brief historical perspective and summarizing the analytical and statistical techniques used. Some of the major applications of metabonomics relevant to pharmaceutical Research & Development are then reviewed including the study of various influences on metabolism, such as diet, lifestyle, and other environmental factors. The applications of metabonomics in drug safety studies are explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology. Next, the role that metabonomics might have in disease diagnosis and therapy monitoring is provided with some examples, and the concept of pharmacometabonomics as a way of predicting an individual's response to treatment is highlighted. Some discussion is given on the strengths and weaknesses, opportunities of, and threats to metabonomics.

Algorithms↗

Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study.

Large-scale population phenotyping for molecular epidemiological studies is subject to all the usual criteria of analytical chemistry. As part of a major phenotyping investigation we have used high-resolution 1H NMR spectroscopy to characterize 24-h urine specimens obtained from population samples in Aito Town, Japan (n = 259), Chicago, IL (n = 315), and Guangxi, China (n = 278). We have investigated analytical reproducibility, urine specimen storage procedures, interinstrument variability, and split specimen detection. Our data show that the multivariate analytical reproducibility of the NMR screening platform was >98% and that most classification errors were due to urine specimen handling inhomogeneity. Differences in metabolite profiles were then assessed for Aito Town, Chicago, and Guangxi population samples; novel combinations of biomarkers were detected that separated the population samples. These cross-population differences in urinary metabolites could be related to genetic, dietary, and gut microbial factors.

Biomarkers↗

Scaling and normalization effects in NMR spectroscopic metabonomic data sets.

Considerable confusion appears to exist in the metabonomics literature as to the real need for, and the role of, preprocessing the acquired spectroscopic data. A number of studies have presented various data manipulation approaches, some suggesting an optimum method. In metabonomics, data are usually presented as a table where each row relates to a given sample or analytical experiment and each column corresponds to a single measurement in that experiment, typically individual spectral peak intensities or metabolite concentrations. Here we suggest definitions for and discuss the operations usually termed normalization (a table row operation) and scaling (a table column operation) and demonstrate their need in 1H NMR spectroscopic data sets derived from urine. The problems associated with "binned" data (i.e., values integrated over discrete spectral regions) are also discussed, and the particular biological context problems of analytical data on urine are highlighted. It is shown that care must be exercised in calculation of correlation coefficients for data sets where normalization to a constant sum is used. Analogous considerations will be needed for other biofluids, other analytical approaches (e.g., HPLC-MS), and indeed for other "omics" techniques (i.e., transcriptomics or proteomics) and for integrated studies with "fused" data sets. It is concluded that data preprocessing is context dependent and there can be no single method for general use.

Algorithms↗

Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies.

Statistical heterospectroscopy (SHY) is a new statistical paradigm for the coanalysis of multispectroscopic data sets acquired on multiple samples. This method operates through the analysis of the intrinsic covariance between signal intensities in the same and related molecules measured by different techniques across cohorts of samples. The potential of SHY is illustrated using both 600-MHz 1H NMR and UPLC-TOFMS data obtained from control rat urine samples (n = 54) and from a corresponding hydrazine-treated group (n = 58). We show that direct cross-correlation of spectral parameters, viz. chemical shifts from NMR and m/z data from MS, is readily achievable for a variety of metabolites, which leads to improved efficiency of molecular biomarker identification. In addition to structure, higher level biological information can be obtained on metabolic pathway activity and connectivities by examination of different levels of the NMR to MS correlation and anticorrelation matrixes. The SHY approach is of general applicability to complex mixture analysis, if two or more independent spectroscopic data sets are available for any sample cohort. Biological applications of SHY as demonstrated here show promise as a new systems biology tool for biomarker recovery.

Animals↗

The application of NMR-based metabonomics in neurological disorders.

Advances in postgenomic technologies have radically changed the information output from complex biological systems, generating vast amounts of high complexity data that can be interpreted by means of chemometric and bioinformatic methods to achieve disease diagnosis and prognosis. High-resolution nuclear magnetic resonance (NMR) spectroscopy of biofluids such as plasma, cerebrospinal fluid (CSF), and urine can generate robust, interpretable metabolic fingerprints that contain latent information relating to physiological or pathological status. This technology has been successfully applied to both preclinical and clinical studies of neurodegenerative diseases such as Huntington's disease, muscular dystrophy, and cerebellar ataxia. An extension of this technology, (1)H magic-angle-spinning (HRMAS) NMR spectroscopy, can be used to generate metabolic information on small intact tissue samples, providing a metabolic link between metabolic profiling of biofluids and histology. In this review we provide a summary of high-resolution NMR studies in neurodegenerative disease and explore the potential of metabonomics in evaluating disease progression with respect to therapeutic intervention.

Animals↗

Metabolic characterization of the R6/2 transgenic mouse model of Huntington's disease by high-resolution MAS 1H NMR spectroscopy.

The metabolic consequences of Huntington's disease in the R6/2 mouse model were investigated using NMR spectroscopy and pattern recognition to characterize selected brain regions, muscle, blood, and urine. Global increases in relative brain concentrations of osmolytes, creatine, glutamine, and lactate, and decreases in acetate and N-acetylaspartate were found together with striatal-specific lower concentrations of GABA and choline. Clear differentiation of R6/2 and wild-type mice was also obtained for urine and blood metabolite profiles that may have applicability for monitoring HD in human populations.

Animals↗

Systems toxicology: integrated genomic, proteomic and metabonomic analysis of methapyrilene induced hepatotoxicity in the rat.

Administration of high doses of the histamine antagonist methapyrilene to rats causes periportal liver necrosis. The mechanism of toxicity is ill-defined and here we have utilized an integrated systems approach to understanding the toxic mechanisms by combining proteomics, metabonomics by 1H NMR spectroscopy and genomics by microarray gene expression profiling. Male rats were dosed with methapyrilene for 3 days at 150 mg/kg/day, which was sufficient to induce liver necrosis, or a subtoxic dose of 50 mg/kg/day. Urine was collected over 24 h each day, while blood and liver tissues were obtained at 2 h after the final dose. The resulting data further define the changes that occur in signal transduction and metabolic pathways during methapyrilene hepatotoxicity, revealing modification of expression levels of genes and proteins associated with oxidative stress and a change in energy usage that is reflected in both gene/protein expression patterns and metabolites. The difficulties of combining and interpreting multiomic data are considered.

Animals↗

Metabolic profiling of plasma from discordant schizophrenia twins: correlation between lipid signals and global functioning in female schizophrenia patients.

(1)H NMR spectroscopy-based metabonomic analysis was employed to investigate plasma samples from 21 pairs of monozygotic twins discordant for schizophrenia and 8 pairs of age-matched healthy twins in an effort to disentangle genetic and epigenetic components of schizophrenia. We identified alterations in the lipid profile of both affected and unaffected schizophrenia twins. Additionally, there is a close association of VLDL/LDL signals and Global Functioning Scores in female twins suffering from schizophrenia. Our results further support a link between metabolic disturbances and the etiopathology of schizophrenia.

Adult↗

Experimental metabonomic model of dietary variation and stress interactions.

Stress in the form of moderate periods of maternal separation of newborn rats has been postulated to cause permanent changes in the central nervous system and diseases in later life. It is also considered that dietary supplementation with long chain polyunsaturated fatty acids (LC-PUFAs) can potentially ameliorate the effects of stress. The metabolic consequences of early life maternal separation stress were investigated in rats (2-14 days after birth), either alone or in combination with secondary acute water avoidance stress at 3-4 months of age. The effect of a LC-PUFA-enriched dietary intervention in stressed animals was also assessed. Systematic changes in metabolic biochemistry were evaluated using 1H nuclear magnetic resonance spectroscopy of blood plasma and multivariate pattern recognition techniques. The biochemical response to stress was characterized by decreased levels of total lipoproteins and increased levels of amino acids, glucose, lactate, creatine, and citrate. Secondary acute water avoidance stress also caused elevated levels of O-acetyl glycoproteins in blood plasma. LC-PUFAs dietary enrichment did not alter the metabolic response to stress, but did result in a modified lipoprotein profile. This work indicates that the different stressor types resulted in some common systemic metabolic responses that involve changes in energy and muscle metabolism, but that they are not reversible by dietary intervention.

Amino Acids↗

Integrated metabonomic analysis of bromobenzene-induced hepatotoxicity: novel induction of 5-oxoprolinosis.

We present here a definitive metabonomic analysis in order to detect novel biomarker and metabolite information, implicating specific putative protein targets in the toxicological mechanism of bromobenzene-induced centrilobular hepatic necrosis. Male Han-Wistar rats were dosed with bromobenzene (1.5 g/kg, n = 25) and blood plasma, urine and liver samples were collected for NMR and magic angle spinning (MAS) NMR spectroscopy at various time-points postdose, with histopathology and clinical pathology performed in parallel. Liver samples were analyzed by 600 MHz 1H MAS NMR techniques and the resultant spectra were correlated to sequential 1H NMR measurements in urine and blood plasma using pattern recognition methods. 1D 1H NMR spectra were data-reduced and analyzed using principal components analysis (PCA) to show the time-dependent biochemical variations induced by bromobenzene toxicity. In addition to a holistic view of the effect of hepatic toxicity on the metabolome, a number of putative protein targets of bromobenzene and its metabolites were identified including those enzymes of the glutathione cycle, exemplified by the presence of a novel biomarker, 5-oxoproline, in liver tissue, blood plasma, and urine. As such, this work establishes the importance of metabonomics technology in resolving the mechanistic complexity of drug toxicity as well as the benefits of frontloading this approach in drug safety evaluation and biomarker discovery.

Animals↗

Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice.

A novel statistically integrated proteometabonomic method has been developed and applied to a human tumor xenograft mouse model of prostate cancer. Parallel 2D-DIGE proteomic and 1H NMR metabolic profile data were collected on blood plasma from mice implanted with a prostate cancer (PC-3) xenograft and from matched control animals. To interpret the xenograft-induced differences in plasma profiles, multivariate statistical algorithms including orthogonal projection to latent structure (OPLS) were applied to generate models characterizing the disease profile. Two approaches to integrating metabonomic data matrices are presented based on OPLS algorithms to provide a framework for generating models relating to the specific and common sources of variation in the metabolite concentrations and protein abundances that can be directly related to the disease model. Multiple correlations between metabolites and proteins were found, including associations between serotransferrin precursor and both tyrosine and 3-D-hydroxybutyrate. Additionally, a correlation between decreased concentration of tyrosine and increased presence of gelsolin was also observed. This approach can provide enhanced recovery of combination candidate biomarkers across multi-omic platforms, thus, enhancing understanding of in vivo model systems studied by multiple omic technologies.

Animals↗

Transgenomic metabolic interactions in a mouse disease model: interactions of Trichinella spiralis infection with dietary Lactobacillus paracasei supplementation.

Irritable Bowel Syndrome (IBS) is a common multifactorial intestinal disorder for which the aetiology remains largely undefined. Here, we have used a Trichinella spiralis (T. spiralis)-induced model of post-infective IBS, and the effects of probiotic bacteria on gut dysfunction have been investigated using a metabonomic strategy. A total of 44 mice were divided into four groups: an uninfected control group and three T. spiralis-infected groups, one as infected control and the two other groups subsequently treated with either Lactobacillus paracasei (L. paracasei) NCC2461 in spent culture medium (SCM) or with L. paracasei-free SCM. Plasma, jejunal wall and longitudinal myenteric muscle samples were collected at day 21 post-infection. An NMR-based metabonomic approach characterized that the plasma metabolic profile of T. spiralis-infected mice showed an increased energy metabolism (lactate, citrate, alanine), fat mobilization (acetoacetate, 3-D-hydroxybutyrate, lipoproteins) and a disruption of amino acid metabolism due to increased protein breakdown, which were related to the intestinal hypercontractility. Increased levels of taurine, creatine and glycerophosphorylcholine in the jejunal muscles were associated with the muscular hypertrophy and disrupted jejunal functions. L. paracasei treatment normalized the muscular activity and the disturbed energy metabolism as evidenced by decreased glycogenesis and elevated lipid breakdown in comparison with untreated T. spiralis-infected mice. Changes in the levels of plasma metabolites (glutamine, lysine, methionine) that might relate to a modulation of immunological responses were also observed in the presence of the probiotic treatment. The work presented here suggests that probiotics may be beneficial in patients with IBS.

Amino Acids↗

Susceptibility of human metabolic phenotypes to dietary modulation.

Dietary composition has been shown to influence metabolism and to impact on the prevalence and risk for certain diseases, but hitherto, there have been no systematic studies on the effects of dietary modulation of human metabolic phenotype (metabotype). Here, we have applied 1H NMR spectroscopy in combination with multivariate statistical analysis to characterize the effects of three diets: "vegetarian", "low meat", and "high meat" on the metabotype signature of human participants. Twelve healthy male participants (age range of 25-74 years) consumed each of these diets, in a randomized order, for continuous 15-day-periods with an intervening washout period between each diet of 7 days duration. Each participant provided three consecutive 24-hour urine collections on days 13, 14, and 15 of each dietary period, and 1H NMR spectra were acquired on all samples. Pattern recognition analysis allowed differentiation of the characteristic metabolic signatures of the diets with creatine, carnitine, acetylcarnitine, and trimethylamine-N-oxide (TMAO) being elevated in the high-meat consumption period. Application of orthogonal projection to latent structure discriminant analysis (O-PLS-DA) allowed the low-meat diet and vegetarian diet signatures to be characterized, and p-hydroxyphenylacetate (a microbial mammalian cometabolite) was higher in the vegetarian than meat diet samples, signaling an alteration of the bacterial composition or metabolism in response to diet. This work shows the potential for the routine use of metabonomics in nutritional and epidemiological studies, in characterizing and predicting the metabolic effects and the influence of diet on human metabotypes.

Acetylcarnitine↗

The assessment of plant metabolite profiles by NMR-based methodologies.

NMR-based metabolic profiling techniques can simultaneously track changes in many plant metabolites and have found a number of applications in both systems biology and biosafety. Together with multivariate statistical analyses, NMR spectroscopy has been successfully applied to the characterisation of various herbs and plant products for quality control, authentication, determining geographical origin and for detecting adulteration of products. Additionally, the metabolic consequences of plant extracts have been demonstrated in experimental animals and in man using NMR-based metabonomics approaches to characterise the response. Here the application of NMR spectroscopy and chemometric tools for analysing plant-based products and their metabolic consequences are considered with particular emphasis on deconvolving biological complexity and minimising confounding biological variability with analytical 'noise'.

Animals↗

Metabolic profiling of CSF: evidence that early intervention may impact on disease progression and outcome in schizophrenia.

BACKGROUND: The identification of schizophrenia biomarkers is a crucial step towards improving current diagnosis, developing new presymptomatic treatments, identifying high-risk individuals and disease subgroups, and assessing the efficacy of preventative interventions at a rate that is not currently possible. METHODS AND FINDINGS: (1)H nuclear magnetic resonance spectroscopy in conjunction with computerized pattern recognition analysis were employed to investigate metabolic profiles of a total of 152 cerebrospinal fluid (CSF) samples from drug-naïve or minimally treated patients with first-onset paranoid schizophrenia (referred to as "schizophrenia" in the following text) and healthy controls. Partial least square discriminant analysis showed a highly significant separation of patients with first-onset schizophrenia away from healthy controls. Short-term treatment with antipsychotic medication resulted in a normalization of the disease signature in over half the patients, well before overt clinical improvement. No normalization was observed in patients in which treatment had not been initiated at first presentation, providing the first molecular evidence for the importance of early intervention for psychotic disorders. Furthermore, the alterations identified in drug-naïve patients could be validated in a test sample set achieving a sensitivity and specificity of 82% and 85%, respectively. CONCLUSIONS: Our findings suggest brain-specific alterations in glucoregulatory processes in the CSF of drug-naïve patients with first-onset schizophrenia, implying that these abnormalities are intrinsic to the disease, rather than a side effect of antipsychotic medication. Short-term treatment with atypical antipsychotic medication resulted in a normalization of the CSF disease signature in half the patients well before a clinical improvement would be expected. Furthermore, our results suggest that the initiation of antipsychotic treatment during a first psychotic episode may influence treatment response and/or outcome.

Adult↗