Effect of vitamin C supplementation on stroke recovery: A case-control study

Meheroz H Rabadi1, Bruce S Kristal2,31Burke Rehabilitation Hospital, an affiliate of Weill Medical College of Cornell Medical College, White Plains, NY, USA; 2Burke Medical Research Institute, an affiliate of Weill Medical College of Cornell Medical College, White Plains, NY, USA; 3Department of Neuroscience, Cornell University Medical College, White Plains, NY, USABackground and purpose: Epidemiological studies have associated increased dietary intake of antioxidants (vitamin C, E, and β-carotene) in preventing and decreasing the extent of ischemic brain injury. The effect of vitamin C supplementation on functional recovery after stroke has not been studied. Method: In this retrospective, case-control study of 23 patients with ischemic stroke taking vitamin C were identified and matched for age, sex, onset to admission, and admission total functional independence measure (TFIM) with 23 patients with ischemic stroke not taking Vitamin C supplementation. Vitamin C 1000 mg daily was prescribed on admission to our unit mainly to patients who were undernourished (defined as significant weight loss and/or 90% or less ideal body weight for age and sex) and those with pressure sores. The outcome measures were: change in the TFIM, FIM-Cognition (FIM-Cog), and FIM-Motor sub-scores, discharge disposition, and length of stay (LOS).Results: The change in TFIM (20 ± 13 standard deviation [SD] vs. 26 ± 6, p = 0.20), FIM-Cog (3 ± 3 SD vs. 4 ± 5, p = 0.41), FIM-Motor (15 ± 11 SD vs. 20 ± 13, p = 0.21) sub-scores were less in the vitamin C treated group, but these differences did not reach statistical significance. Similarly, no significant differences were found in LOS (21 ± 9 SD vs. 23 ± 9, p = 0.59), and discharge disposition (home/institution) (9/10 vs. 13/9, p = 0.60) between the vitamin C and the control groups.Conclusion: This study suggests vitamin C supplementation did not enhance functional recovery in undernourished ischemic stroke patients.Keywords: vitamin C; ischemic stroke; functional recover

Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Concerns and Approaches for Cohort and Gender Issues in Serum Metabolome Studies

This is the publisher's version, also available electronically from: http://online.liebertpub.com/doi/pdfplus/10.1089/omi.2004.8.209Mathematical models that reflect the effects of dietary restriction (DR) on the sera metabolome may have utility in understanding the mechanisms of DR and in applying this knowledge to human epidemiological studies. Previous studies demonstrated both the feasibility of identifying biomarkers through metabolome analysis and the validity of our approach in independent cohorts of 6-month-oId male and female ad libitum fed or DR rats. Cross-cohort studies showed that cohort-specific effects distorted the dataset The present study extends these observations across the entire sample set, thereby validating our markers independently of specific cohorts. Metabolites originally identified in males were examined in females and vice-versa. DR's effect on the metabolom e is partially gender-specific and is modulated by environmental factors. DR reduces inter-gender differences in the metabolome. Univariate statistical methods showed that 56/93 metabolites in the female samples and 39/93 metabolites in the male samples were significantly altered (using our previous cut-off criteria of p ^ 0.2) by DR. The metabolites modulated by DR present a wide spectrum of concentration, redox reactivity and hydrophilicity, suggesting that our serotype is broadly representative of the metabolome and that DR has broad effects on the metabolome. These studies, coupled with those in the preceding and following reports, also highlight the utility for consideration of the metabolome as a network of metabolites using appropriate data analysis approaches. The inter-cohort and inter-gender differences addressed herein suggest potential cautions, and potential approaches, for identification of multivariate biomarker profiles that reflect changes in physiological status, such as a metabolism that predisposes to increased risk of neoplasia

Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Practical Issues in Development of Expert System-Based Classification Models in Metabolomic Studies

This is the publisher's official version, also available electronically from: http://online.liebertpub.com/doi/pdfplus/10.1089/omi.2004.8.197Dietary restriction (DR)-induced changes in the serum metabolome may be biomarkers for physiological status (e.g., relative risk of developing age-related diseases such as cancer). Megavariate analysis (unsupervised hierarchical cluster analysis IHCAJ; principal components analysis [PCAJ) of serum metabolites reproducibly distinguish DR from ad libitum fed rats. Component-based approaches (i.e., PCA) consistently perform as well as or better than distance-based metrics (i.e., HCA). We therefore tested the following: (A) Do identified subsets of serum metabolites contain sufficient information to construct mathematical models of class membership (i.e., expert systems)? (B) Do component-based metrics out-perform distance-based metrics? Testing was conducted using KNN (k-nearest neighbors, supervised HCA) and SIMCA (soft independent modeling of class analogy, supervised PCA). Models were built with single cohorts, combined cohorts or mixed samples from previously studied cohorts as training sets. Both algorithms over-fit models based on single cohort training sets. KNN models had >85% accuracy within training/test sets, but were unstable (i.e., values of k could not be accurately set in advance). SIMCA models had 100% accuracy within all training sets, 89% accuracy in test sets, did not appear to over-fit mixed cohort training sets, and did not require post-hoc modeling adjustments. These data indicate that (i) previously defined metabolites are robust enough to construct classification models (expert systems) with SIMCA that can predict unknowns by dietary category; (ii) component-based analyses outperformed distance-based metrics; (iii) use of over-fitting controls is essential; and (iv) subtle inter-cohort variability may be a critical issue for high data density biomarker studies that lack state markers

Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Characteristics of Component-Based Models of Metabolic Serotypes

This is the publisher's version, also available electronically from: http://online.liebertpub.com/doi/pdfplus/10.1089/omi.2004Our research seeks to identify a scrum profile, or serotype, that reflects the systemic physiologic modifications resultant from dietary restriction (DR), in part such that this knowledge can be applied for biomarker studies. Direct comparison suggests that component-based classification algorithms consistently out-perform distance-based metrics for studies of nutritional modulation of metabolic serotype, but are subject to over-fitting concerns. Intercohort differences in the sera metabolome could partially obscure the effects of DR. Further analysis now shows that implementation of component-based approaches (also called projection methods) optimized for class separation and controlled for over-fitting have >97% accuracy for distinguishing sera from control or DR rats. DR's effect on the metabolome is shown to be robust across cohorts, but differs in males and females (although some metabolites are affected in both). We demonstrate the utility of projection-based methods for both sample and variable diagnostics, including identification of critical metabolites and samples that are atypical with respect to both class and variable models. Inclusion of non-statistically different variables enhances classification models. Variables that contribute to these models are sharply dependent on mathematical processing techniques; some variables that do not contribute under one paradigm arc powerful under alternative mathematical paradigms. In practical terms, this information may find purpose in other endeavors, such as mechanistic studies of DR. Application of these approaches confirms the utility of megavariate data analysis techniques for optimal generation of biomarkers based on nutritional modulation of physiological processes

Dietary Omega-3 Fatty Acids Do Not Change Resistance of Rat Brain or Liver Mitochondria to Ca2+ and/or Prooxidants

Omega-3 polyunsaturated fatty acids (n-3 PUFAs) block apoptotic neuronal cell death and are strongly neuroprotective in acute and chronic neurodegeneration. Theoretical considerations, indirect data, and consideration of parsimony lead to the hypothesis that modulation of mitochondrial pathway(s) underlies at least some of the neuroprotective effects of n-3 PUFAs. We therefore systematically tested this hypothesis on healthy male FBFN1 rats fed for four weeks with isocaloric, 10% fat-containing diets supplemented with 1, 3, or 10% fish oil (FO). High resolution mass spectrometric analysis confirmed expected diet-driven increases in docosahexaenoic acid (DHA, 22:6, n-3) and eicosapentaenoic acid (EPA, 20:5, n-3) in sera, liver and nonsynaptosomal brain mitochondria. We further evaluated the resistance of brain and liver mitochondria to Ca2+ overload and prooxidants. Under these conditions, neither mitochondrial resistance to Ca2+ overload and prooxidants nor mitochondrial physiology is altered by diet, despite the expected incorporation of DHA and EPA in mitochondrial membranes and plasma. Collectively, the data eliminate one of the previously proposed mechanism(s) that n-3 PUFA induced augmentation of mitochondrial resistance to the oxidant/calcium-driven dysfunction. These data furthermore allow us to define a specific series of follow-up experiments to test related hypotheses about the effect of n-3 PUFAs on brain mitochondria

UCP1 deficiency causes brown fat respiratory chain depletion and sensitizes mitochondria to calcium overload-induced dysfunction.

Brown adipose tissue (BAT) mitochondria exhibit high oxidative capacity and abundant expression of both electron transport chain components and uncoupling protein 1 (UCP1). UCP1 dissipates the mitochondrial proton motive force (Δp) generated by the respiratory chain and increases thermogenesis. Here we find that in mice genetically lacking UCP1, cold-induced activation of metabolism triggers innate immune signaling and markers of cell death in BAT. Moreover, global proteomic analysis reveals that this cascade induced by UCP1 deletion is associated with a dramatic reduction in electron transport chain abundance. UCP1-deficient BAT mitochondria exhibit reduced mitochondrial calcium buffering capacity and are highly sensitive to mitochondrial permeability transition induced by reactive oxygen species (ROS) and calcium overload. This dysfunction depends on ROS production by reverse electron transport through mitochondrial complex I, and can be rescued by inhibition of electron transfer through complex I or pharmacologic depletion of ROS levels. Our findings indicate that the interscapular BAT of Ucp1 knockout mice exhibits mitochondrial disruptions that extend well beyond the deletion of UCP1 itself. This finding should be carefully considered when using this mouse model to examine the role of UCP1 in physiology

Clinically Approved Heterocyclics Act on a Mitochondrial Target and Reduce Stroke-induced Pathology

Substantial evidence indicates that mitochondria are a major checkpoint in several pathways leading to neuronal cell death, but discerning critical propagation stages from downstream consequences has been difficult. The mitochondrial permeability transition (mPT) may be critical in stroke-related injury. To address this hypothesis, identify potential therapeutics, and screen for new uses for established drugs with known toxicity, 1,040 FDA-approved drugs and other bioactive compounds were tested as potential mPT inhibitors. We report the identification of 28 structurally related drugs, including tricyclic antidepressants and antipsychotics, capable of delaying the mPT. Clinically achievable doses of one drug in this general structural class that inhibits mPT, promethazine, were protective in both in vitro and mouse models of stroke. Specifically, promethazine protected primary neuronal cultures subjected to oxygen-glucose deprivation and reduced infarct size and neurological impairment in mice subjected to middle cerebral artery occlusion/reperfusion. These results, in conjunction with new insights provided to older studies, (a) suggest a class of safe, tolerable drugs for stroke and neurodegeneration; (b) provide new tools for understanding mitochondrial roles in neuronal cell death; (c) demonstrate the clinical/experimental value of screening collections of bioactive compounds enriched in clinically available agents; and (d) provide discovery-based evidence that mPT is an essential, causative event in stroke-related injury

Biological variability dominates and influences analytical variance in HPLC-ECD studies of the human plasma metabolome

<p>Abstract</p> <p>Background</p> <p>Biomarker-based assessments of biological samples are widespread in clinical, pre-clinical, and epidemiological investigations. We previously developed serum metabolomic profiles assessed by HPLC-separations coupled with coulometric array detection that can accurately identify <it>ad libitum </it>fed and caloric-restricted rats. These profiles are being adapted for human epidemiology studies, given the importance of energy balance in human disease.</p> <p>Methods</p> <p>Human plasma samples were biochemically analyzed using HPLC separations coupled with coulometric electrode array detection.</p> <p>Results</p> <p>We identified these markers/metabolites in human plasma, and then used them to determine which human samples represent blinded duplicates with 100% accuracy (N = 30 of 30). At least 47 of 61 metabolites tested were sufficiently stable for use even after 48 hours of exposure to shipping conditions. Stability of some metabolites differed between individuals (N = 10 at 0, 24, and 48 hours), suggesting the influence of some biological factors on parameters normally considered as analytical.</p> <p>Conclusion</p> <p>Overall analytical precision (mean median CV, ~9%) and total between-person variation (median CV, ~50–70%) appear well suited to enable use of metabolomics markers in human clinical trials and epidemiological studies, including studies of the effect of caloric intake and balance on long-term cancer risk.</p

Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research

Mass spectrometry (MS) techniques, because of their sensitivity and selectivity, have become methods of choice to characterize the human metabolome and MS-based metabolomics is increasingly used to characterize the complex metabolic effects of nutrients or foods. However progress is still hampered by many unsolved problems and most notably the lack of well established and standardized methods or procedures, and the difficulties still met in the identification of the metabolites influenced by a given nutritional intervention. The purpose of this paper is to review the main obstacles limiting progress and to make recommendations to overcome them. Propositions are made to improve the mode of collection and preparation of biological samples, the coverage and quality of mass spectrometry analyses, the extraction and exploitation of the raw data, the identification of the metabolites and the biological interpretation of the results