Elaine Holmes

Imperial College London, Londinium, England, United Kingdom

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Publications (296)1845.08 Total impact

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    ABSTRACT: Current optimum medical treatments have had limited success in the primary prevention of cardiovascular events underscoring the need for new pharmaceutical targets and enhanced understanding of mechanistic metabolic dysregulation. Here, we use a combination of novel metabolic profiling methodologies, based on ultra performance liquid chromatography coupled to mass spectrometry (UPLC-MS), followed by chemometric modeling, data integration and pathway mapping, to create a systems level metabolic atlas of atherogenesis. We apply this workflow to compare arterial tissue incorporating plaque lesions to intimal thickening tissue (immediate pre-plaque stage). We find changes in several metabolite species consistent with well-established pathways in atherosclerosis, such as the cholesterol, purine, pyrimidine, and ceramide pathways. We then illustrate differential levels of previously unassociated lipids to atherogenesis, namely phosphatidylethanolamine-ceramides (t-test p-values: 3.8x10(-6)-9.8x10(-12)). Most importantly, these molecules appear to be interfacing two pathways recognized for their involvement in atherosclerosis: ceramide and cholesterol. Furthermore, we show that β-oxidation intermediates (i.e. acylcarnitines) manifest a pattern indicating truncation of the process and overall dysregulation of fatty acid metabolism and mitochondrial dysfunction. We develop a metabolic framework which offers the ability of mapping significant statistical associations between detected biomarkers. These dysregulated molecules and consequent pathway modulations may provide novel targets for pharmacotherapeutic intervention.
    Journal of Proteome Research 01/2015; · 5.06 Impact Factor
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    ABSTRACT: Objectives:The invasive nature of biopsy alongside issues with categorical staging and sampling error has driven research into noninvasive biomarkers for the assessment of liver fibrosis in order to stratify and personalize treatment of patients with liver disease. Here, we sought to determine whether a metabonomic approach could be used to identify signatures reflective of the dynamic, pathological metabolic perturbations associated with fibrosis in chronic hepatitis C (CHC) patients.Methods:Plasma nuclear magnetic resonance (NMR) spectral profiles were generated for two independent cohorts of CHC patients and healthy controls (n=50 original and n=63 validation). Spectral data were analyzed and significant discriminant biomarkers associated with fibrosis (as graded by enhanced liver fibrosis (ELF) and METAVIR scores) identified using orthogonal projection to latent structures (O-PLS).Results:Increased severity of fibrosis was associated with higher tyrosine, phenylalanine, methionine, citrate and, very-low-density lipoprotein (vLDL) and lower creatine, low-density lipoprotein (LDL), phosphatidylcholine, and N-Acetyl-α1-acid-glycoprotein. Although area under the receiver operator characteristic curve analysis revealed a high predictive performance for classification based on METAVIR-derived models, <40% of identified biomarkers were validated in the second cohort. In the ELF-derived models, however, over 80% of the biomarkers were validated.Conclusions:Our findings suggest that modeling against a continuous ELF-derived score of fibrosis provides a more robust assessment of the metabolic changes associated with fibrosis than modeling against the categorical METAVIR score. Plasma metabolic phenotypes reflective of CHC-induced fibrosis primarily define alterations in amino-acid and lipid metabolism, and hence identify mechanistically relevant pathways for further investigation as therapeutic targets.Am J Gastroenterol advance online publication, 23 December 2014; doi:10.1038/ajg.2014.370.
    The American Journal of Gastroenterology 12/2014; · 9.21 Impact Factor
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    ABSTRACT: Maternal Body Mass Index (BMI) is positively associated with infant obesity risk. Breast milk contains a number of hormones that may influence infant metabolism during the neonatal period; these may have additional downstream effects on infant appetite regulatory pathways, thereby influencing propensity towards obesity in later life. To conduct a systematic review of studies examining the association between maternal BMI and the concentration of appetite-regulating hormones in breast milk. Pubmed was searched for studies reporting the association between maternal BMI and leptin, adiponectin, insulin, ghrelin, resistin, obestatin, Peptide YY and Glucagon-Like Peptide 1 in breast milk. Twenty six studies were identified and included in the systematic review. There was a high degree of variability between studies with regard to collection, preparation and analysis of breast milk samples. Eleven of fifteen studies reporting breast milk leptin found a positive association between maternal BMI and milk leptin concentration. Two of nine studies investigating adiponectin found an association between maternal BMI and breast milk adiponectin concentration; however significance was lost in one study following adjustment for time post-partum. No association was seen between maternal BMI and milk adiponectin in the other seven studies identified. Evidence for an association between other appetite regulating hormones and maternal BMI was either inconclusive, or lacking. A positive association between maternal BMI and breast milk leptin concentration is consistently found in most studies, despite variable methodology. Evidence for such an association with breast milk adiponectin concentration, however, is lacking with additional research needed for other hormones including insulin, ghrelin, resistin, obestatin, peptide YY and glucagon-like peptide-1. As most current studies have been conducted with small sample sizes, future studies should ensure adequate sample sizes and standardized methodology.
    PLoS ONE 12/2014; 9(12):e115043. · 3.53 Impact Factor
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    ABSTRACT: Parasitic infections such as Leishmania induce a cascade of host physiological responses, including metabolic and immunological changes. Infection with Leishmania major protozoa causes cutaneous leishmaniasis in humans, a neglected tropical disease with suboptimal disease management. To understand the determinants of pathology, we studied L. major infection in two mouse models: the self-healing C57BL/6 strain and the non-healing BALB/c strain. Metabolic profiling of urine, plasma and faeces via proton NMR spectroscopy was performed, a method that has shown great promise in discovering parasite-specific imprints on global host metabolism. Plasma cytokine status and faecal microbiome were also characterised, as additional metrics of the host response to infection. Results demonstrated differences in glucose and lipid metabolism, distinctive immunological phenotypes, and shifts in microbial composition between the two models. We present a novel approach to integrate such metrics using correlation network analyses, whereby self-healing mice demonstrated an orchestrated interaction between the biological measures shortly after infection. In contrast, the response observed in non-healing mice was delayed and fragmented. Our study suggests that trans-system communication across host metabolism, the innate immune system and gut microbiome is key for a successful host response to L. major and provides a new concept, potentially translatable to other diseases. Please visit journal website to download full copy (free, subject to membership) at: http://dx.doi.org/10.1021/pr5008202
    Journal of Proteome Research 11/2014; · 5.06 Impact Factor
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    Dataset: JPRobese
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    ABSTRACT: Animal models are invaluable tools which allow us to investigate the microbiome-host dialogue. However, experimental design introduces biases in the data that we collect, also potentially leading to biased conclusions. With obesity at pandemic levels animal models of this disease have been developed; we investigated the role of experimental design on one such rodent model. We used 454 pyrosequencing to profile the faecal bacteria of obese (n = 6) and lean (homozygous n = 6; heterozygous n = 6) Zucker rats over a 10 week period, maintained in mixed-genotype cages, to further understand the relationships between the composition of the intestinal bacteria and age, obesity progression, genetic background and cage environment. Phylogenetic and taxon-based univariate and multivariate analyses (non-metric multidimensional scaling, principal component analysis) showed that age was the most significant source of variation in the composition of the faecal microbiota. Second to this, cage environment was found to clearly impact the composition of the faecal microbiota, with samples from animals from within the same cage showing high community structure concordance, but large differences seen between cages. Importantly, the genetically induced obese phenotype was not found to impact the faecal bacterial profiles. These findings demonstrate that the age and local environmental cage variables were driving the composition of the faecal bacteria and were more deterministically important than the host genotype. These findings have major implications for understanding the significance of functional metagenomic data in experimental studies and beg the question; what is being measured in animal experiments in which different strains are housed separately, nature or nurture?
    PLoS ONE 09/2014; 9(9):e100916. · 3.53 Impact Factor
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    ABSTRACT: We studied the extent and nature of renal involvement in a cohort of 117 adult patients with mitochondrial disease, by measuring urinary retinol-binding protein (RBP) and albumin; established markers of tubular and glomerular dysfunction, respectively. Seventy-five patients had the m.3243A>G mutation and the most frequent phenotypes within the entire cohort were 14 with MELAS, 33 with MIDD, and 17 with MERRF. Urinary RBP was increased in 29 of 75 of m.3243A>G patients, whereas albumin was increased in 23 of the 75. The corresponding numbers were 16 and 14, respectively, in the 42 non-m.3243A>G patients. RBP and albumin were higher in diabetic m.3243A>G patients than in nondiabetics, but there were no significant differences across the three major clinical phenotypes. The urine proteome (mass spectrometry) and metabonome (nuclear magnetic resonance) in a subset of the m.3243A>G patients were markedly different from controls, with the most significant alterations occurring in lysosomal proteins, calcium-binding proteins, and antioxidant defenses. Differences were also found between asymptomatic m.3243A>G carriers and controls. No patients had an elevated serum creatinine level, but 14% had hyponatremia, 10% had hypophosphatemia, and 14% had hypomagnesemia. Thus, abnormalities in kidney function are common in adults with mitochondrial disease, exist in the absence of elevated serum creatinine, and are not solely explained by diabetes.Kidney International advance online publication, 10 September 2014; doi:10.1038/ki.2014.297.
    Kidney International 09/2014; · 8.52 Impact Factor
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    ABSTRACT: In this study, we performed gas chromatography time-of-flight mass spectrometry (GC-TOFMS)-based extracellular metabolic profiling on AβPP-transfected CHO cells (CHO-AβPP695) and its wildtype. Orthogonal partial least squares discriminant analysis (OPLS-DA) was then used to identify discriminant metabolites, which gave clues on the effects of AβPP transgene on cellular processes. To confirm the hypotheses generated based on the metabolic data, we performed biochemical assays to gather further evidence to support our findings. The OPLS-DA showed a robust differentiation following 24 h of incubation (Q2(cum) = 0.884) and 15 discriminant metabolites were identified. In contrast, extracellular Aβ42 was identified to increase significantly in CHO-AβPP695 only after incubation for 48 h. The observed 24-h metabolic fluxes were associated with increased mitochondrial AβPP and reduced mitochondrial viabilities, which occurred before extracellular Aβ accumulation. We also investigated the therapeutic potential of peroxisome proliferator-activated receptor gamma (PPARγ) agonists, namely rosiglitazone (RSG) and pioglitazone (PIO), by employing the same approach to characterize the metabolic profiles of CHO-AβPP695 treated with RSG and PIO, with or without their respective receptor blockers. Treatment with PIO was found to reduce the perturbation of the discriminant metabolites in CHO-AβPP695 to a larger extent than treatment with RSG. We also attributed the PIO effects on the lowering of Aβ42, and restoration of mitochondrial activity to PPARγ and PPARα agonism, respectively. Taken together, PIO was demonstrated to be therapeutically superior to RSG. Our findings provide further insights into early disease stages in this AβPP model, and support the advancement of PIO in AD therapy.
    Journal of Alzheimer's disease: JAD 09/2014; · 3.61 Impact Factor
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    ABSTRACT: Proton NMR-based metabolic phenotyping of urine and blood plasma/serum samples provides important prognostic and diagnostic information and permits monitoring of disease progression in an objective manner. Much effort has been made in recent years to develop NMR instrumentation and technology to allow the acquisition of data in an effective, reproducible and high throughput approach that allows the study of general population samples from epidemiological collections for biomarkers of disease risk. The challenge remains to develop highly reproducible methods and standardized protocols that minimise technical or experimental bias, allowing realistic interlaboratory comparisons of subtle biomarker information. Here we present a detailed set of updated protocols that carefully consider major experimental conditions including sample preparation, spectrometer parameters, NMR pulse sequences, throughput, reproducibility, quality control and resolution. These results provide an experimental platform that facilitates NMR spectroscopy usage across different large cohorts of biofluid samples, enabling integration of global metabolic profiling that is a prerequisite for personalized healthcare.
    Analytical Chemistry 09/2014; · 5.83 Impact Factor
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    ABSTRACT: We have investigated the urinary and plasma metabolic phenotype of acute pancreatitis (AP) patients presenting to the emergency room at St. Mary's Hospital London with acute abdominal pain using 1H NMR spectroscopy and multivariate modelling. Patients were allocated to either the AP (n=15) or non-AP patients group (all other causes of abdominal pain, n=21) on the basis of the national guidelines. Patients were assessed for three clinical outcomes: 1) diagnosis of AP; 2) aetiology of AP caused by alcohol consumption and cholelithiasis; and 3) AP severity based on the Glasgow score. Samples from AP patients were characterized by high levels of urinary ketone bodies, glucose, plasma choline and lipid, and relatively low levels of urinary hippurate, creatine and plasma branched chain amino acids. AP could be reliably identified with a high degree of sensitivity and specificity (Q2= 0.76 and R2= 0.59) using panel of discriminatory biomarkers consisting of guanine, hippurate and creatine (urine), and valine, alanine and lipoproteins (plasma). Metabolic phenotyping was also able to distinguish between cholelithiasis and colonic inflammation amongst the heterogeneous non-AP group. This work has demonstrated that combinatorial biomarkers have a strong diagnostic and prognostic potential in AP with relevance to clinical decision making in the emergency unit.
    Journal of Proteome Research 08/2014; · 5.06 Impact Factor
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    ABSTRACT: Adverse drug reactions (ADRs) represent a significant clinical challenge with respect to patient morbidity and mortality. We investigated the hepatotoxicity and systems level metabolic phenotype of methotrexate (MTX) in the context of a prevalent liver disease; non-alcoholic steatohepatitis (NASH). An NMR spectroscopic based metabonomic approach was employed to analyze the metabolic consequences of MTX (0, 10, 40, 100 mg/kg) in urine and liver of healthy rats (control diet) and in a model of NASH (methionine-choline deficient diet). Histopathological analysis confirmed baseline (0 mg/kg) liver necrosis, liver inflammation and lipid accumulation in the NASH model. Administration of MTX (40 and 100 mg/kg) led to liver necrosis in the control cohort, whilst the NASH cohort also displayed biliary hyperplasia and liver fibrosis (100 mg/kg), providing evidence of the synergistic effect of MTX and NASH. The complementary hepatic and urinary metabolic phenotypes of the NASH model, at baseline, revealed perturbation of multiple metabolites associated with oxidative and energetic stress, and folate homeostasis. Administration of MTX in both diet cohorts showed dose-dependent metabolic consequences affecting gut microbial, energy, nucleobase, nucleoside and folate metabolism. Furthermore, a unique panel of metabolic changes reflective of the synergistic effect of MTX and NASH were identified, including the elevation of hepatic phenylalanine, urocanate, acetate and both urinary and hepatic formiminoglutamic acid. This systems level metabonomic analysis of the hepatotoxicity of MTX in the context of NASH provided novel mechanistic insight of potential wider clinical relevance for further understanding the role of liver pathology as a risk factor for ADRs.
    Toxicological Sciences 08/2014; · 4.48 Impact Factor
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    ABSTRACT: Reasons for performing studyMetabonomics is emerging as a powerful tool for disease screening and investigating mammalian metabolism. This study aims to create a metabolic framework by producing a preliminary reference guide for the normal equine metabolic milieu.Objectives To metabolically profile plasma, urine and faecal water from healthy racehorses using high resolution 1H-NMR spectroscopy and to provide a list of dominant metabolites present in each biofluid for the benefit of future research in this area.Study designThis study was performed using seven Thoroughbreds in race training at a single time-point. Urine and faecal samples were collected non-invasively and plasma was obtained from samples taken for routine clinical chemistry purposes.Methods Biofluids were analysed using 1H-NMR spectroscopy. Metabolite assignment was achieved via a range of 1D and 2D experiments.ResultsA total of 102 metabolites were assigned across the three biological matrices. A core metabonome of 14 metabolites was ubiquitous across all biofluids. All biological matrices provided a unique window on different aspects of systematic metabolism. Urine was the most populated metabolite matrix with 65 identified metabolites, 39 of which were unique to this biological compartment. A number of these were related to gut microbial host co-metabolism. Faecal samples were the most metabolically variable between animals; acetate was responsible for the majority (28%) of this variation. Short chain fatty acids were the predominant features identified within this biofluid by 1H-NMR spectroscopy.Conclusions Metabonomics provides a platform for investigating complex and dynamic interactions between the host and its consortium of gut microbes and has the potential to uncover markers for health and disease in a variety of biofluids. Inherent variation in faecal extracts along with the relative abundance of microbial-mammalian metabolites in urine and invasive nature of plasma sampling, infers that urine is the most appropriate biofluid for the purposes of metabonomic analysis.
    Equine Veterinary Journal 08/2014; · 2.37 Impact Factor
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    ABSTRACT: Breast milk (BM) is a biofluid, which has a fundamental role in early-life nutrition and directly impacts on growth, neurodevelopment and health. Global metabolic profiling is increasingly being utilized to characterize complex metabolic changes in biological samples. However, in order to achieve broad metabolite coverage, it is necessary to employ more than one analytical platform, typically requiring multiple sample preparation protocols. In an effort to improve analytical efficiency and retain comprehensive coverage of the metabolome, a new extraction methodology was developed that successfully retains metabolites from BM in a single-phase using an optimized methyl-tert-butyl ether solvent system. We conducted this single-phase extraction procedure on a representative pool of BM, and characterized the metabolic composition using LC-QTOF-MS and GC-Q-MS for polar and lipidic metabolites. To ensure that the extraction method was reproducible and fit-for-purpose, the analytical procedure was evaluated on both platforms using 18 metabolites selected to cover a range of chromatographic retention times and biochemical classes. Having validated the method, the metabolic signature of BM composition was mapped as a metabolic reaction network highlighting interconnected biological pathways and showing that the LC-MS and GC-MS platforms targeted largely different domains of the network. Subsequently, the same protocol was applied to ascertain compositional differences between BM at week 1 (n=10) and 4 weeks (n=9) post-partum. This single-phase approach is more efficient in terms of time, simplicity, cost and sample volume than the existing two phase methods, and will be suited to high-throughput metabolic profiling studies of BM.
    Analytical Chemistry 07/2014; · 5.83 Impact Factor
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    ABSTRACT: Concomitant infections with Plasmodium and gastrointestinal nematodes are frequently observed in humans. At the metabolic level, the cross-talk between the host and multiple coexisting pathogens is poorly characterized. The purpose of this study was to give a comprehensive insight into the systemic metabolic phenotype of mice with a single or dual infection with Plasmodium berghei and Heligmosomoides bakeri. Four groups of eight NMRI female mice were infected with P. berghei or H. bakeri, or with both species concurrently. An additional group remained uninfected, and served as control. Mice were sacrificed at day 19 of the experiment. We collected samples from the liver, spleen, kidney, three intestinal regions, and four brain regions. All biological samples were subjected to (1)H nuclear magnetic resonance spectroscopy, combined with multivariate data analysis, to establish metabolic fingerprints of each tissue from the various infection groups. Compared to uninfected mice, single and dual species infection models showed unique metabolic profiles. P. berghei exerted major effects on glycolysis, tricarboxylic acid cycle, and nucleotide and amino acid metabolism in all studied tissues with the exception of the gut. H. bakeri was characterized by a dysregulation of choline and lipid metabolism in most tissues examined with a particularly strong imprint in the jejunum. Simultaneous co-infection with P. berghei and H. bakeri induced the strongest and most diverse effects in the liver and spleen but led to only minor changes in the intestinal and cerebral parts assessed. Infection with P. berghei showed more pronounced and systemic alterations in the mice metabolic profile than H. bakeri infection. The metabolic fingerprints in the co-infection models were driven by P. berghei infection, whilst the presence of H. bakeri in co-infections had little effect. However, simultaneous co-infection showed indeed the least metabolic disruptions in the peripheral tissues, namely the gut and brain.
    Molecular BioSystems 06/2014; · 3.18 Impact Factor
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    ABSTRACT: There is no clinically applicable biomarker for surveillance of hepatocellular carcinoma (HCC), as the sensitivity of serum α-fetoprotein (AFP), is too low for this purpose. Here, we determined the diagnostic performance of a panel of urinary metabolites of HCC patients from West Africa. Urine samples were collected from Nigerian and Gambian patients recruited on the case-control platform of the "Prevention of Liver Fibrosis and Cancer in Africa" (PROLIFICA) program. Urinary proton nuclear magnetic resonance ((1) H NMR) spectroscopy was used to metabolically phenotype 290 subjects: 63 with HCC, 32 with cirrhosis (Cir), 107 with non-cirrhotic liver disease (DC) and 88 healthy volunteers (NC). Urine samples from a further cohort, 463 subjects: (141 HCC, 56 Cir, 178 DC and 88 NC) were analysed and the results of which validated the initial cohort. The urinary metabotype of patients with HCC was distinct from those with Cir, DC and NC with areas under the receiver operating characteristic (ROC) curves of 0.86(0.78-0.94), 0.93(0.89-0.97) and 0.89(0.80-0.98) in the training set; and 0.81(0.73-0.89), 0.96(0.94-0.99) and 0.90(0.85-0.96) respectively in the validation cohort. A urinary metabolite panel, comprising: inosine, indole-3-acetate, galactose and an N-acetylated amino acid (NAA) showed a high sensitivity [86.9% (75.8 - 94.2)] and specificity [90.3% (74.2 - 98.0)] in the discrimination of HCC from cirrhosis, a finding that was corroborated in a validation cohort (ROC: urinary panel=0.72; AFP=0.58). Metabolites that were significantly increased in urine of HCC patients, and which correlated with clinical stage of HCC were NAA, dimethylglycine, 1-methylnicotinamide, methionine, acetylcarnitine, 2-oxoglutarate, choline, and creatine. Conclusion: The urinary metabotyping of this West African cohort identified and validated a metabolite panel which diagnostically outperforms serum AFP. (Hepatology 2014;).
    Hepatology 06/2014; · 11.19 Impact Factor
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    ABSTRACT: Exploratory or untargeted Ultra-High Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) profiling offers an overview of the complex lipid species diversity present in blood plasma. Here, we evaluate and compare eight sample preparation protocols for optimized blood plasma lipid extraction and measurement by UPLC-MS lipid profiling, including four protein precipitation methods (i.e., methanol, acetonitrile, isopropanol and isopropanol-acetonitrile) and four liquid-liquid extractions (i.e., methanol combined with chloroform; dichloromethane and methyl-tert butyl ether and isopropanol with hexane). The eight methods were then benchmarked using a set of qualitative and quantitative criteria selected to warrant compliance with high-throughput analytical workflows: removal efficiency, selectivity, repeatability and recovery efficiency of the sample preparation. We found that protein removal was more efficient by precipitation (99%) than extraction (95%). Additionally, isopropanol appeared to be the most straightforward and robust solvent (61.1% of features with CV < 20 %) whilst enabling a broad coverage and recovery of plasma lipid species. These results demonstrate that isopropanol precipitation is an excellent sample preparation procedure for high-throughput untargeted lipid profiling using UPLC-MS. Isopropanol precipitation is not limited to untargeted profiling and could also be of interest for targeted UPLC-MS/MS lipid analysis. Collectively, these data show that lipid profiling greatly benefits from an isopropanol precipitation in terms of simplicity, protein removal efficiency, repeatability, lipid recovery and coverage.
    Analytical Chemistry 05/2014; · 5.83 Impact Factor
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    ABSTRACT: We propose a novel statistical approach to improve the reliability of 1H NMR spectral analysis in complex metabolic studies. The Statistical HOmogeneous Cluster SpectroscopY (SHOCSY) algorithm aims to reduce the variation within biological classes by selecting subsets of homogenous 1H NMR spectra that contain specific spectroscopic metabolic signatures related to each biological class in a study. In SHOCSY, we used a clustering method to categorize the whole dataset into a number of clusters of samples with each cluster showing a similar spectral feature and hence biochemical composition, and then used an enrichment test to identify the associations between the clusters and the biological classes in the dataset. We evaluated the performance of the SHOCSY algorithm using a simulated 1H NMR dataset to emulate renal tubules toxicity and further exemplified this method with a 1H NMR spectroscopic study of hydrazine-induced liver toxicity study in rats. The SHOCSY algorithm improved the predictive ability of the orthogonal partial least square discriminatory analysis (OPLS-DA) model through the use of 'truly' representative samples in each biological class (i.e. homogenous subsets). This method ensures that the analyses are no longer confounded by idiosyncratic responders and thus improves the reliability of biomarker extraction. SHOCSY is a useful tool for removing irrelevant variation that interfere with the interpretation and predictive ability of models and has widespread applicability to other spectroscopic data as well as other 'omics' type of data.
    Analytical Chemistry 04/2014; · 5.83 Impact Factor
  • Journal of Hepatology 04/2014; 60(1):S256. · 10.40 Impact Factor

Publication Stats

15k Citations
1,845.08 Total Impact Points

Institutions

  • 1999–2014
    • Imperial College London
      • • Department of Surgery and Cancer
      • • Section of Computational and Systems Medicine (CSM)
      • • Faculty of Medicine
      Londinium, England, United Kingdom
  • 2007–2013
    • University of Cambridge
      • Department of Chemical Engineering and Biotechnology
      Cambridge, ENG, United Kingdom
  • 2004–2013
    • Swiss Tropical and Public Health Institute
      • Department of Epidemiology and Public Health
      Basel, BS, Switzerland
    • SCYNEXIS, Inc.
      Durham, North Carolina, United States
  • 2012
    • Shanghai Jiao Tong University
      • School of Life Science and Biotechnology
      Shanghai, Shanghai Shi, China
    • Medway School Of Pharmacy
      Чатем, England, United Kingdom
  • 2008–2010
    • Northeast Institute of Geography and Agroecology
      • • Laboratory of Magnetic Resonance and Atomic and Molecular Physics
      • • Partner Institute for Computational Biology
      Beijing, Beijing Shi, China
    • Umeå University
      • Department of Chemistry
      Umeå, Vaesterbotten, Sweden
  • 2009
    • Wuhan Institute of Physics and Mathematics
      Wu-han-shih, Hubei, China
    • Nestlé S.A.
      Vevey, Vaud, Switzerland
    • University of Aveiro
      • Department of Chemistry
      Aveiro, Aveiro, Portugal
  • 2008–2009
    • Semmelweis University
      • Department of Pharmaceutical Chemistry
      Budapest, Budapest fovaros, Hungary
  • 2000–2003
    • University of London
      Londinium, England, United Kingdom