A laboratory approach for characterizing chronic fatigue: what does metabolomics tell us?

INTRODUCTION: Manifestations of fatigue range from chronic fatigue up to a severe syndrome and myalgic encephalomyelitis. Fatigue grossly affects the functional status and quality of life of affected individuals, prompting the World Health Organization to recognize it as a chronic non-communicable condition. OBJECTIVES: Here, we explore the potential of urinary metabolite information to complement clinical criteria of fatigue, providing an avenue towards an objective measure of fatigue in patients presenting with the full spectrum of fatigue levels. METHODS: The experimental group consisted of 578 chronic fatigue female patients. The measurement design was composed of (1) existing clinical fatigue scales, (2) a hepatic detoxification challenge test, and (3) untargeted proton nuclear magnetic resonance (1H-NMR) procedure to generate metabolomics data. Data analysed via an in-house Matlab script that combines functions from a Statistics and a PLS Toolbox. RESULTS: Multivariate analysis of the original 459 profiled 1H-NMR bins for the low (control) and high (patient) fatigue groups indicated complete separation following the detoxification experimental challenge. Important bins identified from the 1H-NMR spectra provided quantitative metabolite information on the detoxification challenge for the fatigue groups. CONCLUSIONS: Untargeted 1H-NMR metabolomics proved its applicability as a global profiling tool to reveal the impact of toxicological interventions in chronic fatigue patients. No clear potential biomarker emerged from this study, but the quantitative profile of the phase II biotransformation products provide a practical visible effect directing to up-regulation of crucial phase II enzyme systems in the high fatigue group in response to a high xenobiotic-load.

Risk assessment of herbal supplements containing ingredients that are genotoxic and carcinogenic.

Botanicals and botanical preparations including plant food supplements as well as medicinal herbal supplements can contain possible beneficial health compounds, but also ingredients of concern. Compounds that are both genotoxic and carcinogenic have been found in herbal supplements and may raise a safety concern. Genotoxic carcinogens that can be present in botanicals and botanical preprations include especially pyrrolizidine alkaloids (PAs), aristolochic acids (AAs) and alkenylbenzenes (ABs). The present manuscript provides an overview of the levels of these compounds reported to date to be present in herbal supplements with an associated risk assessment. Exposure was estimated based on levels of PAs, AAs and ABs in individual supplements and their proposed uses. In addition a probabilistic exposure assessment was performed based on the distribution of the level of the compounds of concern in the food supplements and of the recommended uses, resulting in 5th to 95th percentile consumer exposure values. To evaluate the risk of these exposures, the margin of exposure (MOE) approach for lifetime exposure was used. To correct exposure estimates for shorter than lifetime exposure, Haber's rule as a first tier approach was applied. It is concluded that the proposed uses and use levels as well as the presence of AAs, ABs and PAs in food supplements should be carefully monitored to manage potential consumer risks. More information on estimated daily intake resulting from supplement use, as well as consequences of concomitant exposure will further improve the risk evaluation of products containing these compounds of concern.

Predicting the influence of multiple components on microbial inhibition using a logistic response model--a novel approach.

BACKGROUND: There are several synergistic methods available. However, there is a vast discrepancy in the interpretation of the synergistic results. Also, these synergistic methods do not assess the influence the tested components (drugs, plant and natural extracts), have upon one another, when more than two components are combined. METHODS: A modified checkerboard method was used to evaluate the synergistic potential of Heteropyxis natalensis, Melaleuca alternifolia, Mentha piperita and the green tea extract known as TEAVIGO™. The synergistic combination was tested against the oral pathogens, Streptococcus mutans, Prevotella intermedia and Candida albicans. Inhibition data obtained from the checkerboard method, in the form of binary code, was used to compute a logistic response model with statistically significant results (p < 0.05). This information was used to construct a novel predictive inhibition model. RESULTS: Based on the predictive inhibition model for each microorganism, the oral pathogens tested were successfully inhibited (at 100% probability) with their respective synergistic combinations. The predictive inhibition model also provided information on the influence that different components have upon one another, and on the overall probability of inhibition. CONCLUSIONS: Using the logistic response model negates the need to 'calculate' synergism as the results are statistically significant. In successfully determining the influence multiple components have upon one another and their effect on microbial inhibition, a novel predictive model was established. This ability to screen multiple components may have far reaching effects in ethnopharmacology, agriculture and pharmaceuticals.

The Th1/Th2/Th17 cytokine profile of HIV-infected individuals: a multivariate cytokinomics approach.

HIV infection causes the dysregulation of cytokine production. A cytokinomics approach employing cytometric bead array (CBA) technology, flow cytometry and multivariate analysis was applied to the investigation of HIV-induced T helper cell type 1 (Th1), Th2 and Th17 cytokine changes in the sera of treatment naive individuals. Stepwise linear discriminant analysis (LDA) and logistic regression identified interleukin (IL)-6 to be discriminatory for HIV infection with 74.6% and 71.2% of the cases correctly classified. Analysis of variance (ANOVA) confirmed IL-6 and IL-10 concentrations to be significantly (p=0.001 and p=0.025) different between the groups. A scatter plot of the log IL-6 and IL-10 concentrations for the groups largely overlapped, with improved differentiation where patients were advancing to the acquired immunodeficiency syndrome (AIDS). IL-17A levels were higher than other cytokines but did not significantly distinguish the groups suggesting that the HIV- and HIV+ individuals had similar immune profiles. This possibility was supported by other clinical indicators. Taken together, the measured cytokines (IL-6, 10 and 17) have potential prognostic value.

Personality traits and dimensions of mental health.

Individuals are different in a relatively constant pattern of thoughts, feeling, and behaviors, which are called personality traits. Mental health is a condition of well-being in which people may reach their full potential and deal effectively with stress, work efficiently, and contribute to their communities. Indeed, the link between personality and mental health as indicated by the 12-item version of the general health questionnaires (GHQ-12) has been well-established according to evidence found by decades of research. However, the GHQ-12 comprises many questions asking about different dimensions of mental health. It is unclear how personality traits relate to these dimensions of mental health. In this paper, we try to address this question. We analyzed data from 12,007 participants from the British Household Panel Study (BHPS) using a confirmatory factor analysis (CFA) and generalized linear models. We replicated the factor structure of GHQ-12 labeled as GHQ-12A (social dysfunction & anhedonia; 6 items), GHQ-12B (depression & anxiety; 4 items), and GHQ-12C (loss of confidence; 2 items). Moreover, Neuroticism was positively related to all dimensions of mental health issues, Extraversion was negatively related to GHQ-12A (social dysfunction & anhedonia) and GHQ-12B (depression & anxiety), Agreeableness and Conscientiousness were negatively related to GHQ-12A (social dysfunction & anhedonia) and GHQ-12C (loss of confidence), and Openness was negatively related to GHQ-12B (depression & anxiety). These results contribute to theories including the predisposition/vulnerability model, complication/scar model, pathoplasty/exacerbation model, and the spectrum model, which propose that personality traits are linked to mental health and explained possible reasons. Psychologists may use results from this study to identify individuals who may be at high risk of developing various non-psychiatric mental health issues and intervene to avoid negative outcomes.

Back-Carrying in Children Is Related to Lower Limb Development.

Back-carrying of children is a culturally accepted method of transport and safekeeping of babies in many cultures. Developmental consequences related to back-carrying practices have not been directly investigated. This study determined the relationship between frontal and transverse plane lower limb (LL) development, and back-carrying practices, in black Setswana-speaking children. In 691 2- to 9-year-old Setswana-speaking children, the tibiofemoral angle, intermalleolar distance, femoral anteversion angle (AVA) and tibial torsion angle (TTA), were measured to determine LL development. Back-carrying practices were recorded with a questionnaire and Classification and Regression Tree (CART) was used for the analyses. Significant (p < 0.001) relationships, between back-carrying practices and LL development, were discovered. Statistically significant greater genu valgum (F(5, 690) = 7.2, p < 0.001), greater internal TTAs (F(9, 684) = 17.8, p < 0.001), and smaller AVAs (F(13, 685) = 5.1, p < 0.001) were observed in children back-carried more frequently than children back-carried less frequently. There are relationships between back-carrying practices and LL development in both the frontal and transverse plane. However, the genu valgum, internal TTA and smaller AVA noted in more frequently back-carried children is still within normal limits, thus no educational intervention in back-carrying methods or durations is required. Further research should determine the exact back-carrying practice factors (age until which the child is back-carried) impacting lower limb development the greatest.

Biotransformation profiles from a cohort of chronic fatigue women in response to a hepatic detoxification challenge.

Chronic fatigue, in its various manifestations, frequently co-occur with pain, sleep disturbances and depression and is a non-communicable condition which is rapidly becoming endemic worldwide. However, it is handicapped by a lack of objective definitions and diagnostic measures. This has prompted the World Health Organization to develop an international instrument whose intended purpose is to improve quality of life (QOL), with energy and fatigue as one domain of focus. To complement this objective, the interface between detoxification, the exposome, and xenobiotic-sensing by nuclear receptors that mediate induction of biotransformation-linked genes, is stimulating renewed attention to a rational development of strategies to identify the metabolic profiles in complex multifactorial conditions like fatigue. Here we present results from a seven-year study of a cohort of 576 female patients suffering from low to high levels of chronic fatigue, in which phase I and phase II biotransformation was assessed. The biotransformation profiles used were based on hepatic detoxification challenge tests through oral caffeine, acetaminophen and acetylsalicylic acid ingestion coupled with oxidative stress analyses. The interventions indicated normal phase I but increased phase II glucuronidation and glycination conjugation. Complementarity was indicated between a fatigue scale, medical symptoms and associated energy-related parameters by application of Chi-square Automatic Interaction Detector (CHAID) analysis. The presented study provides a cluster of data from which we propose that multidisciplinary inputs from the combination of a fatigue scale, medical symptoms and biotransformation profiles provide the rationale for the development of a comprehensive laboratory instrument for improved diagnostics and personalized interventions in patients with chronic fatigue with a view to improving their QOL.

In vitro effects of 2-methoxyestradiol on MCF-12A and MCF-7 cell growth, morphology and mitotic spindle formation.

The influence of 2-methoxyestradiol (2ME) was investigated on cell growth, morphology and spindle formation in a tumorigenic (MCF-7) and non-tumorigenic (MCF-12A) epithelial breast cell line. Inhibition of cell growth was more pronounced in the MCF-7 cells compared to the MCF-12A cells following 2ME treatment. Dose-dependent studies (10(-5)-10(-9) M) revealed that 10(-6) M 2ME inhibited cell growth by 44% in MCF-12A cells and by 84% in MCF-7 cells (p-value < 0.05). 2ME-treated MCF-7 cells showed abnormal metaphase cells, membrane blebbing, apoptotic cells and disrupted spindle formation. These observations were either absent or less prominent in MCF-12A cells. 2ME had no effect on the length of the cell cycle between S-phase and the time a mitotic peak was reached in either cell line but MCF-7 cells were blocked in mitosis with no statistically significant alterations in the phosphorylation status of Cdc25C. Nevertheless, Cdc2 activity was significantly increased in MCF-7 cells compared to MCF-12A cells (p-value < 0.05). The results indicate that 2ME disrupts mitotic spindle formation and enhances Cdc2 kinase activity, leading to persistence of the spindle checkpoint and thus prolonged metaphase arrest that may result in the induction of apoptosis. The tumorigenic MCF-7 cells were especially sensitive to 2ME treatment compared to the normal MCF-12A cells. Therefore, differential mechanism(s) of growth inhibition are evident between the normal and tumorigenic cells.

Views of clinical trial participants on the readability and their understanding of informed consent documents.

BACKGROUND: One of the ethical imperatives for a valid consent process in clinical medication trials is that the process be guided by and recorded in an informed consent document (ICD). Concerns have been expressed, however, about readability and participant understanding of ICDs, which are often 10-20 pages long. Objective measures of readability and understanding have been used to support these concerns in several articles, but surprisingly the voice of trial participants on ICDs has not been heard in previous studies. Hence, this study compares participants' subjective views on readability and their understanding of ICDs with those ICDs' objective readability scores. It also evaluates whether family, friends, and additional aids would foster better understanding of the ICD. METHODS: Sixty current trial participants rated the readability and their understanding of deidentified standard ICDs. These had been sourced from two multicenter international Phase III trials on medication for diabetes mellitus and cancer. RESULTS: Less than 10% of participants considered the ICDs difficult to read or difficult to understand in spite of objective readability scores at levels of about 12th grade education, but about a quarter considered the ICDs to be too technical. Participants gave mixed responses about friends or family members helping or the need for videos, pictures, additional reading material, and frequently answered questions (FAQ) sheets as an aid to their understanding. CONCLUSIONS: These findings suggest individual clinical trial participants should be engaged on their views of an ICD, for doing so is part of informed consent as a process rather than consent being merely focused on written information. Such participant-specific engagement should guide whether family and friends, videos, pictures, additional reading material, and FAQ sheets would be of assistance in improving understanding.

Impact of CYP2D6 genotype on amitriptyline efficacy for the treatment of diabetic peripheral neuropathy: a pilot study.

AIM: Therapy with low-dose amitriptyline is commonly used to treat painful diabetic peripheral neuropathy. There is a knowledge gap, however, regarding the role of variable CYP2D6-mediated drug metabolism and side effects (SEs). We aimed to generate pilot data to demonstrate that SEs are more frequent in patients with variant CYP2D6 alleles. METHOD: To that end, 31 randomly recruited participants were treated with low-dose amitriptyline for painful diabetic peripheral neuropathy and their CYP2D6 gene sequenced. RESULTS: Patients with predicted normal or ultra-rapid metabolizer phenotypes presented with less SEs compared with individuals with decreased CYP2D6 activity. CONCLUSION: Hence, CYP2D6 genotype contributes to treatment outcome and may be useful for guiding drug therapy. Future investigations in a larger patient population are planned to support these preliminary findings.

Multi-element analysis of South African wines by ICP-MS and their classification according to geographical origin.

Wines from three important wine-producing regions, Stellenbosch, Robertson, and Swartland, in the Western Cape Province of South Africa, were analyzed by ICP-MS and the elemental composition used in multivariate statistical analysis to classify the wines according to geographical origin. The method is based on the assumption that the provenance soil is an important contributor to the trace element composition of a wine. A total of 40 elements were determined in 40 wines. Of these, 20 elements: Li, B, Mg, Al, Si, Cl, Sc, Mn, Ni, Ga, Se, Rb, Sr, Nb, Cs, Ba, La, W, Tl, and U showed differences in their means across the three areas. In a stepwise discriminant analysis procedure, functions based on linear combinations of the log-transformed element concentrations of Al, Mn, Rb, Ba, W, and Tl were generated to correctly classify wines from each region. In an alternative approach, a pairwise discriminant analysis procedure, not previously used in wine provenance studies, was tested. In this procedure, the classification was done in three steps, with each step classifying a wine as coming from a certain region or not. The combination of elements characterizing wines from a particular region was different in each region. The discriminant functions were based on the following elements: Al, Mn, Rb, Ba, and W for Stellenbosch; Se, Rb, Cs, and Tl for Robertson; and Al, Mn, Rb, Sr, Ba, and Tl for Swartland. After this procedure, the classification of the wines into one of the groups was 100% successful.

The application of imaging technologies in the detection of trace evidence in forensic medical investigation.

In a country notorious for violent crime, it seems that South African medico-legal laboratories make minimal application of technology in the death investigation process and little attention is given to trace evidence. Non-destructive, non-invasive, portable and cost-effective tools are required. This study was conducted at the Pretoria Medico-Legal Laboratory. The surface area of the bodies and clothing of victims of fatal interpersonal violence were examined using a torch, magnifying lamp, portable digital microscope and alternate light source to gauge their potential for trace evidence detection. Most studies apply these and similar tools to inert surfaces, with few focusing on their application to human skin. There was a statistically significant difference in the detection of many of the evidence types between the naked-eye observation of the pathologists and the technologies. The different imaging technologies were compared as to their cost, evidence detection ability and ease of use. The most common evidence types discovered on the bodies and clothing of victims of fatal interpersonal violence, as well as the propensity of each tool to detect these, was evaluated in order to devise the best option for incorporation into the Pretoria Medico-Legal Laboratory routine. The digital microscope performed best overall followed by the magnifying lamp, torch and the Polilight(®). This study aimed to justify the investment of more time, effort and funding into trace evidence recovery in the South African mortuary environment.

Evaluation of predictive CYP2C19 genotyping assays relative to measured phenotype in a South African cohort.

AIM: To align predicted and measured CYP2C19 phenotype in a South African cohort. MATERIALS & METHODS: Genotyping of CYP2C19*2, *3, *9, *15, *17, *27 and *28 was performed using PCR-RFLP, and an activity score (AS) system was used to predict phenotype. True phenotype was measured using plasma concentrations of omeprazole and its metabolite 5'-hydroxyomperazole. RESULTS: Partial genotype-phenotype discrepancies were reported, and an adapted AS system was developed, which showed a marked improvement in phenotype prediction. Results highlight the need for a more comprehensive CYP2C19 genotyping approach to improve prediction of omeprazole metabolism. CONCLUSION: Evidence for the utility of a CYP2C19 AS system is provided, for which the accuracy can be further improved by means of comprehensive genotyping and substrate-specific modification.

Mid-ATR-FTIR spectroscopic profiling of HIV/AIDS sera for novel systems diagnostics in global health.

Global health, whether in developed or developing countries, is in need of robust systems diagnostics for major diseases, such as HIV/AIDS, impacting the world populations. Fourier transform Infrared (FTIR) spectroscopy of serum is a quick and reagent-free methodology with which to analyze metabolic alterations such as those caused by disease or treatment. In this study, Attenuated Total Reflectance Fourier-Transform (ATR-FTIR) Spectroscopy was investigated as a means of distinguishing HIV-infected treatment-experienced (HIV(pos) ART(pos), n=39) and HIV-infected-treatment-naïve (HIV(pos) ART(neg), n=16) subjects from uninfected control subjects (n=30). Multivariate pattern recognition techniques, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), successfully distinguished sample classes, while univariate approaches identified significant differences (p<0.05) after Benjamini-Hochberg corrections. OPLS-DA discriminated between all groups with sensitivity, specificity, and accuracy of >90%. Compared to uninfected controls, HIV(pos) ART(pos) and HIV(pos) ART(neg) subjects displayed significant differences in spectral regions linked to lipids/fatty acids (3010 cm(-1)), carbohydrates (1299 cm(-1); 1498 cm(-1)), glucose (1035 cm(-1)), and proteins (1600 cm(-1); 1652 cm(-1)). These are all molecules shown by conventional biochemical analysis to be affected by HIV/ART interference. The biofluid metabolomics approach applied here successfully differentiated global metabolic profiles of HIV-infected patients and uninfected controls and detected potential biomarkers for development into indicators of host response to treatment and/or disease progression. Our findings therefore contribute to ongoing efforts for capacity-building in global health for robust omics science and systems diagnostics towards major diseases impacting population health.

A combined chemometric and quantitative NMR analysis of HIV/AIDS serum discloses metabolic alterations associated with disease status.

Individuals infected with the human immunodeficiency virus (HIV) often suffer from concomitant metabolic complications. Treatment with antiretroviral therapy has also been shown to alter the metabolism of patients. Although chemometric analysis of nuclear magnetic resonance (NMR) spectra of human sera can distinguish normal sera (HIVneg) from HIV-infected sera (HIVpos) and sera from HIV-infected patients on antiretroviral therapy (ART), quantitative analysis of the discriminating metabolites and their relationship to disease status has yet to be determined. The objectives of the study were to analyze NMR spectra of HIVneg, HIVpos, and ART serum samples with a combination of chemometric and quantitative methods and to compare the NMR data with disease status as measured by viral load and CD4 count. High-resolution magic angle spinning (HRMAS) NMR spectroscopy was performed on HIVneg (N = 10), HIVpos (N = 10), and ART (N = 10) serum samples. Chemometric linear discriminant analysis classified the three groups of spectra with 100% accuracy. Concentrations of 12 metabolites were determined with a semi-parametric metabolite quantification method named high-resolution quantum estimation (HR-QUEST). CD4 count was directly associated with alanine (p = 0.008), and inversely correlated with both glutamine (p = 0.017) and glucose (p = 0.022) concentrations. A multivariate linear model using alanine, glutamine and glucose as covariates demonstrated an association with CD4 count (p = 0.038). The combined chemometric and quantitative analysis of the data disclosed previously unknown associations between specific metabolites and disease status. The observed associations with CD4 count are consistent with metabolic disorders that are commonly seen in HIV-infected patients.