138 research outputs found

    Interleukin-2 therapy in patients with HIV infection

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    BACKGROUND Used in combination with antiretroviral therapy, subcutaneous recombinant interleukin-2 raises CD4+ cell counts more than does antiretroviral therapy alone. The clinical implication of these increases is not known. METHODS We conducted two trials: the Subcutaneous Recombinant, Human Interleukin-2 in HIV-Infected Patients with Low CD4+ Counts under Active Antiretroviral Therapy (SILCAAT) study and the Evaluation of Subcutaneous Proleukin in a Randomized International Trial (ESPRIT). In each, patients infected with the human immunodeficiency virus (HIV) who had CD4+ cell counts of either 50 to 299 per cubic millimeter (SILCAAT) or 300 or more per cubic millimeter (ESPRIT) were randomly assigned to receive interleukin-2 plus antiretroviral therapy or antiretroviral therapy alone. The interleukin-2 regimen consisted of cycles of 5 consecutive days each, administered at 8-week intervals. The SILCAAT study involved six cycles and a dose of 4.5 million IU of interleukin-2 twice daily; ESPRIT involved three cycles and a dose of 7.5 million IU twice daily. Additional cycles were recommended to maintain the CD4+ cell count above predefined target levels. The primary end point of both studies was opportunistic disease or death from any cause. RESULTS In the SILCAAT study, 1695 patients (849 receiving interleukin-2 plus antiretroviral therapy and 846 receiving antiretroviral therapy alone) who had a median CD4+ cell count of 202 cells per cubic millimeter were enrolled; in ESPRIT, 4111 patients (2071 receiving interleukin-2 plus antiretroviral therapy and 2040 receiving antiretroviral therapy alone) who had a median CD4+ cell count of 457 cells per cubic millimeter were enrolled. Over a median follow-up period of 7 to 8 years, the CD4+ cell count was higher in the interleukin-2 group than in the group receiving antiretroviral therapy alone--by 53 and 159 cells per cubic millimeter, on average, in the SILCAAT study and ESPRIT, respectively. Hazard ratios for opportunistic disease or death from any cause with interleukin-2 plus antiretroviral therapy (vs. antiretroviral therapy alone) were 0.91 (95% confidence interval [CI], 0.70 to 1.18; P=0.47) in the SILCAAT study and 0.94 (95% CI, 0.75 to 1.16; P=0.55) in ESPRIT. The hazard ratios for death from any cause and for grade 4 clinical events were 1.06 (P=0.73) and 1.10 (P=0.35), respectively, in the SILCAAT study and 0.90 (P=0.42) and 1.23 (P=0.003), respectively, in ESPRIT. CONCLUSIONS Despite a substantial and sustained increase in the CD4+ cell count, as compared with antiretroviral therapy alone, interleukin-2 plus antiretroviral therapy yielded no clinical benefit in either study. (ClinicalTrials.gov numbers, NCT00004978 [ESPRIT] and NCT00013611 [SILCAAT study].

    A Protein Diet Score, Including Plant and Animal Protein, Investigating the Association with HbA1c and eGFR-The PREVIEW Project

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    Higher-protein diets have been advocated for body-weight regulation for the past few decades. However, the potential health risks of these diets are still uncertain. We aimed to develop a protein score based on the quantity and source of protein, and to examine the association of the score with glycated haemoglobin (HbA1c) and estimated glomerular filtration rate (eGFR). Analyses were based on three population studies included in the PREVIEW project (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World): NQplus, Lifelines, and the Young Finns Study. Cross-sectional data from food-frequency questionnaires (n = 76,777 subjects) were used to develop a protein score consisting of two components: 1) percentage of energy from total protein, and 2) plant to animal protein ratio. An inverse association between protein score and HbA1c (slope -0.02 +/- 0.01 mmol/mol, p <0.001) was seen in Lifelines. We found a positive association between the protein score and eGFR in Lifelines (slope 0.17 +/- 0.02 mL/min/1.73 m(2), p <0.0001). Protein scoring might be a useful tool to assess both the effect of quantity and source of protein on health parameters. Further studies are needed to validate this newly developed protein score.Peer reviewe

    Latent Tuberculosis in HIV positive, diagnosed by the M. Tuberculosis Specific Interferon-γ test

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    BACKGROUND: Although tuberculosis (TB) is a minor problem in Denmark, severe and complicated cases occur in HIV positive. Since the new M. tuberculosis specific test for latent TB, the QuantiFERON-TB In-Tube test (QFT-IT) became available the patients in our clinic have been screened for the presence of latent TB using the QFT-IT test. We here report the results from the first patients screened. METHODS: On a routine basis the QFT-IT test was performed and the results from 590 HIV positive individuals consecutively tested are presented here. CD4 cell count and TB risk-factors were recorded from patient files. MAIN FINDINGS: 27/590(4.6%) of the individuals were QFT-IT test positive, indicating the presence of latent TB infection. Among QFT-IT positive patients, 78% had risk factors such as long-term residency in a TB high endemic area (OR:5.7), known TB exposure (OR:4.9) or previous TB disease (OR:4.9). The prevalence of latent TB in these groups were 13%, 16% and 19% respectively. There was a strong correlation between low CD4 T-cell count and a low mitogen response (P < 0.001;Spearman) and more patients with low CD4 cell count had indeterminate results. CONCLUSION: We found an overall prevalence of latent TB infection of 4.6% among the HIV positive individuals and a much higher prevalence of latent infection among those with a history of exposure (16%) and long term residency in a high endemic country (13%). The QFT-IT test may indeed be a useful test for HIV positive individuals, but in severely immunocompromised, the test may be impaired by T-cell anergy

    Higher Protein Intake Is Not Associated with Decreased Kidney Function in Pre-Diabetic Older Adults Following a One-Year Intervention—A Preview Sub-Study

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    Concerns about detrimental renal effects of a high-protein intake have been raised due to an induced glomerular hyperfiltration, since this may accelerate the progression of kidney disease. The aim of this sub-study was to assess the effect of a higher intake of protein on kidney function in pre-diabetic men and women, aged 55 years and older. Analyses were based on baseline and one-year data in a sub-group of 310 participants included in the PREVIEW project (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World). Protein intake was estimated from four-day dietary records and 24-hour urinary urea excretion. We used linear regression to assess the association between protein intake after one year of intervention and kidney function markers: creatinine clearance, estimated glomerular filtration rate (eGFR), urinary albumin/creatinine ratio (ACR), urinary urea/creatinine ratio (UCR), serum creatinine, and serum urea before and after adjustments for potential confounders. A higher protein intake was associated with a significant increase in UCR (p = 0.03) and serum urea (p = 0.05) after one year. There were no associations between increased protein intake and creatinine clearance, eGFR, ACR, or serum creatinine. We found no indication of impaired kidney function after one year with a higher protein intake in pre-diabetic older adults.Peer reviewe

    Donor Fecal Microbiota Transplantation Alters Gut Microbiota and Metabolites in Obese Individuals With Steatohepatitis

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    The intestinal microbiota has been linked to the development and prevalence of steatohepatitis in humans. Interestingly, steatohepatitis is significantly lower in individuals taking a plant-based, low-animal-protein diet, which is thought to be mediated by gut microbiota. However, data on causality between these observations in humans is scarce. In this regard, fecal microbiota transplantation (FMT) using healthy donors is safe and is capable of changing microbial composition in human disease. We therefore performed a double-blind randomized controlled proof-of-principle study in which individuals with hepatic steatosis on ultrasound were randomized to two study arms: lean vegan donor (allogenic n = 10) or own (autologous n = 11) FMT. Both were performed three times at 8-week intervals. A liver biopsy was performed at baseline and after 24 weeks in every subject to determine histopathology (Nonalcoholic Steatohepatitis Clinical Research Network) classification and changes in hepatic gene expression based on RNA sequencing. Secondary outcome parameters were changes in intestinal microbiota composition and fasting plasma metabolomics. We observed a trend toward improved necro-inflammatory histology, and found significant changes in expression of hepatic genes involved in inflammation and lipid metabolism following allogenic FMT. Intestinal microbial community structure changed following allogenic FMT, which was associated with changes in plasma metabolites as well as markers of .Conclusion:Allogenic FMT using lean vegan donors in individuals with hepatic steatosis shows an effect on intestinal microbiota composition, which is associated with beneficial changes in plasma metabolites and markers of steatohepatitis.Peer reviewe

    Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance

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    FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between nutrition and health. Keywords: Dietary assessment; Food intake biomarkers; Food metabolome; Metabolomics

    Forecasting individual breast cancer risk using plasma metabolomics and biocontours

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    Breast cancer is a major cause of death for women. To improve treatment, current oncology research focuses on discovering and validating new biomarkers for early detection of cancer; so far with limited success. Metabolic profiling of plasma samples and auxiliary lifestyle information was combined by chemometric data fusion. It was possible to create a biocontour, which we define as a complex pattern of relevant biological and phenotypic information. While single markers or known risk factors have close to no predictive value, the developed biocontour provides a forecast which, several years before diagnosis, is on par with how well most current biomarkers can diagnose current cancer. Hence, while e.g. mammography can diagnose current cancer with a sensitivity and specificity of around 75 %, the currently developed biocontour can predict that there is an increased risk that breast cancer will develop in a subject 2–5 years after the sample is taken with sensitivity and specificity well above 80 %. The model was built on data obtained in 1993–1996 and tested on persons sampled a year later in 1997. Metabolic forecasting of cancer by biocontours opens new possibilities for early prediction of individual cancer risk and thus for efficient screening. This may provide new avenues for research into disease mechanisms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-015-0793-8) contains supplementary material, which is available to authorized users
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