44 research outputs found

    No reduction in C-reactive protein following a 12-month randomized controlled trial of exercise in men and women.

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    Low-grade systemic inflammation is suggested to play a role in the development of several chronic diseases including cancer. Higher levels of physical activity and lower adiposity have been associated with reduced levels of markers of systemic inflammation, such as C-reactive protein (CRP); however, reductions in CRP have not been observed consistently in randomized controlled trials of exercise. Purpose: To examine the effect of a 12-month aerobic exercise intervention on CRP levels in men and women. Methods: 102 men and 100 women, sedentary and aged 40-75 years, mean BMI of 29.9 and 28.7 kg/m2, respectively, were randomly assigned to a 12-month moderate-to-vigorous aerobic exercise intervention (6 d/wk, 60 min/d, 60-85% maximum heart rate) or control group. Fasting blood samples were collected at baseline and at 12-months. CRP levels were measured by high-sensitivity latex-enhanced nephelometry. Results: At baseline, CRP was 1.16 mg/L and 2.11 for men and women, respectively, and CRP was correlated with percent body fat (r=0.48, p ≤0.001), BMI (r=0.37, p ≤0.001) and aerobic fitness (r=-0.49, p ≤0.001). No intervention effects were observed for CRP in men or women, or when stratified by baseline BMI (< 30 kg/m2 vs. ≥ 30 kg/m2) , baseline CRP (< 3 mg/L vs. ≥ 3 mg/L) or change in body weight, body composition or aerobic fitness. Conclusion: A 12 month moderate-to-vigorous aerobic exercise intervention did not affect CRP levels in previously sedentary men or women with average-risk CRP values at baseline

    Structure, function and diversity of the healthy human microbiome

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    Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

    A framework for human microbiome research

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    A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

    The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

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    INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

    Characterizing and quantifying leukocyte populations in human adipose tissue: Impact of enzymatic tissue processing

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    Adipose tissue inflammation is a major mechanistic link between obesity and chronic disease. To isolate and characterize specific leukocyte populations, e.g. by flow cytometry, tissue needs to be processed to digest the extracellular matrix. We have systematically compared the impact of different commonly used collagenase preparations, digestion times, and normalization strategies on the reproducibility of flow cytometric phenotyping of adipose tissue leukocyte populations. Subcutaneous adipose tissue was obtained from 11 anonymous donors undergoing elective procedures at a plastic surgery clinic in Seattle, WA. We found that collagenase alone consistently produced better cell yields (p=0.007) than when combined with additional proteases such as the commercially available liberases. Moreover, liberase significantly degraded the cell surface expression of CD4 (p<0.001) on T cells and to a lesser extent CD16 (p=0.058) on neutrophils. Extension of the digestion interval from 30 to 120min did not significantly impact cell viability (p=0.319) or yield (p=0.247). Normalization by either 'live-gate' or percentage of CD45(pos) leukocytes exhibited the lowest coefficient of variation for tissue digests between 60 and 75min, compared to normalization per gram of tissue, which consistently exhibited the greatest variability. Our data suggest that digestion of adipose tissue using pure collagenase for 60-75min provides the best cell yield and viability, with minimal degradation of cell surface markers used to identify immune cell subpopulations, and best reproducibility independent of the normalization strategy

    Dietary weight loss and exercise interventions effects on quality of life in overweight/obese postmenopausal women: a randomized controlled trial

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    Background: Although lifestyle interventions targeting multiple lifestyle behaviors are more effective in preventing unhealthy weight gain and chronic diseases than intervening on a single behavior, few studies have compared individual and combined effects of diet and/or exercise interventions on health-related quality of life (HRQOL). In addition, the mechanisms of how these lifestyle interventions affect HRQOL are unknown. The primary aim of this study was to examine the individual and combined effects of dietary weight loss and/or exercise interventions on HRQOL and psychosocial factors (depression, anxiety, stress, social support). The secondary aim was to investigate predictors of changes in HRQOL. Methods: This study was a randomized controlled trial. Overweight/obese postmenopausal women were randomly assigned to 12 months of dietary weight loss (n = 118), moderate-to-vigorous aerobic exercise (225 minutes/week, n = 117), combined diet and exercise (n = 117), or control (n = 87). Demographic, health and anthropometric information, aerobic fitness, HRQOL (SF-36), stress (Perceived Stress Scale), depression [Brief Symptom Inventory (BSI)-18], anxiety (BSI-18) and social support (Medical Outcome Study Social Support Survey) were assessed at baseline and 12 months. The 12-month changes in HRQOL and psychosocial factors were compared using analysis of covariance, adjusting for baseline scores. Multiple regression was used to assess predictors of changes in HRQOL. Results: Twelve-month changes in HRQOL and psychosocial factors differed by intervention group. The combined diet + exercise group improved 4 aspects of HRQOL (physical functioning, role-physical, vitality, and mental health), and stress (p ≤ 0.01 vs. controls). The diet group increased vitality score (p < 0.01 vs. control), while HRQOL did not change differently in the exercise group compared with controls. However, regardless of intervention group, weight loss predicted increased physical functioning, role-physical, vitality, and mental health, while increased aerobic fitness predicted improved physical functioning. Positive changes in depression, stress, and social support were independently associated with increased HRQOL, after adjusting for changes in weight and aerobic fitness. Conclusions: A combined diet and exercise intervention has positive effects on HRQOL and psychological health, which may be greater than that from exercise or diet alone. Improvements in weight, aerobic fitness and psychosocial factors may mediate intervention effects on HRQOL.Medicine, Faculty ofPhysical Therapy, Department ofReviewedFacult
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