229 research outputs found

    Precision exercise medicine: understanding exercise response variability

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    There is evidence from human twin and family studies as well as mouse and rat selection experiments that there are considerable interindividual differences in the response of cardiorespiratory fitness (CRF) and other cardiometabolic traits to a given exercise programme dose. We developed this consensus statement on exercise response variability following a symposium dedicated to this topic. There is strong evidence from both animal and human studies that exercise training doses lead to variable responses. A genetic component contributes to exercise training response variability. In this consensus statement, we (1) briefly review the literature on exercise response variability and the various sources of variations in CRF response to an exercise programme, (2) introduce the key research designs and corresponding statistical models with an emphasis on randomised controlled designs with or without multiple pretests and post-tests, crossover designs and repeated measures designs, (3) discuss advantages and disadvantages of multiple methods of categorising exercise response levels-a topic that is of particular interest for personalised exercise medicine and (4) outline approaches that may identify determinants and modifiers of CRF exercise response. We also summarise gaps in knowledge and recommend future research to better understand exercise response variability531811411153The consensus meeting that led to the writing of this manuscript was held with the financial support of the Pennington Biomedical Research Foundation, the Pennington Biomedical Research Center Division of Education, the LSU Boyd Professorship and the John W. Barton, Sr. Chair in Genetics and Nutrition. No funding and/or honorarium was provided to any member of the writing group for the production of this manuscrip

    Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4)

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    The uptake of carbonyl sulfide (COS) by terrestrial plants is linked to photosynthetic uptake of CO2 as these gases partly share the same uptake pathway. Applying COS as a photosynthesis tracer in models requires an accurate representation of biosphere COS fluxes, but these models have not been extensively evaluated against field observations of COS fluxes. In this paper, the COS flux as simulated by the Simple Biosphere Model, version 4 (SiB4), is updated with the latest mechanistic insights and evaluated with site obser- vations from different biomes: one evergreen needleleaf forest, two deciduous broadleaf forests, three grasslands, and two crop fields spread over Europe and North America. We improved SiB4 in several ways to improve its representation of COS. To account for the effect of atmospheric COS mole fractions on COS biosphere uptake, we replaced the fixed atmospheric COS mole fraction boundary condition originally used in SiB4 with spatially and temporally varying COS mole fraction fields. Seasonal amplitudes of COS mole fractions are similar to 50-200 ppt at the investigated sites with a minimum mole fraction in the late growing season. Incorporating seasonal variability into the model reduces COS uptake rates in the late growing season, allowing better agreement with observations. We also replaced the empirical soil COS uptake model in SiB4 with a mechanistic model that represents both uptake and production of COS in soils, which improves the match with observations over agricultural fields and fertilized grassland soils. The improved version of SiB4 was capable of simulating the diurnal and seasonal variation in COS fluxes in the boreal, temperate, and Mediterranean region. Nonetheless, the daytime vegetation COS flux is underestimated on average by 8 +/- 27 %, albeit with large variability across sites. On a global scale, our model modifications decreased the modeled COS terrestrial biosphere sink from 922 Gg S yr(-1) in the original SiB4 to 753 Gg S yr(-1) in the updated version. The largest decrease in fluxes was driven by lower atmospheric COS mole fractions over regions with high productivity, which highlights the importance of accounting for variations in atmospheric COS mole fractions. The change to a different soil model, on the other hand, had a relatively small effect on the global biosphere COS sink. The secondary role of the modeled soil component in the global COS budget supports the use of COS as a global photosynthesis tracer. A more accurate representation of COS uptake in SiB4 should allow for improved application of atmospheric COS as a tracer of local- to global-scale terrestrial photosynthesis.Peer reviewe

    Quantile-Specific Penetrance of Genes Affecting Lipoproteins, Adiposity and Height

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    Quantile-dependent penetrance is proposed to occur when the phenotypic expression of a SNP depends upon the population percentile of the phenotype. To illustrate the phenomenon, quantiles of height, body mass index (BMI), and plasma lipids and lipoproteins were compared to genetic risk scores (GRS) derived from single nucleotide polymorphisms (SNP)s having established genome-wide significance: 180 SNPs for height, 32 for BMI, 37 for low-density lipoprotein (LDL)-cholesterol, 47 for high-density lipoprotein (HDL)-cholesterol, 52 for total cholesterol, and 31 for triglycerides in 1930 subjects. Both phenotypes and GRSs were adjusted for sex, age, study, and smoking status. Quantile regression showed that the slope of the genotype-phenotype relationships increased with the percentile of BMI (P = 0.002), LDL-cholesterol (P = 3×10−8), HDL-cholesterol (P = 5×10−6), total cholesterol (P = 2.5×10−6), and triglyceride distribution (P = 7.5×10−6), but not height (P = 0.09). Compared to a GRS's phenotypic effect at the 10th population percentile, its effect at the 90th percentile was 4.2-fold greater for BMI, 4.9-fold greater for LDL-cholesterol, 1.9-fold greater for HDL-cholesterol, 3.1-fold greater for total cholesterol, and 3.3-fold greater for triglycerides. Moreover, the effect of the rs1558902 (FTO) risk allele was 6.7-fold greater at the 90th than the 10th percentile of the BMI distribution, and that of the rs3764261 (CETP) risk allele was 2.4-fold greater at the 90th than the 10th percentile of the HDL-cholesterol distribution. Conceptually, it maybe useful to distinguish environmental effects on the phenotype that in turn alters a gene's phenotypic expression (quantile-dependent penetrance) from environmental effects affecting the gene's phenotypic expression directly (gene-environment interaction)

    Docetaxel plus cisplatin is effective for patients with metastatic breast cancer resistant to previous anthracycline treatment: a phase II clinical trial

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    BACKGROUND: Patients with metastatic breast cancer (MBC) are frequently exposed to high cumulative doses of anthracyclines and are at risk of resistance and cardiotoxicity. This phase II trial evaluated the efficacy and toxicity of docetaxel plus cisplatin, as salvage chemotherapy in patients with MBC resistant to prior anthracyclines. METHODS: Patients with MBC that had progressed after at least one prior chemotherapy regimen containing anthracyclines received docetaxel 75 mg/m(2 )followed by cisplatin 60 mg/m(2 )every 3 weeks for a maximum of 6 cycles or until disease progression. RESULTS: Between Jan 2000 and May 2002, 24 patients with tumors primary resistant and 15 with secondary resistant disease were accrued. All 39 patients were evaluable for safety and 36 for efficacy. The objective response rate was 31% (95% CI, 16–45%) with 3 complete responses. The median time to disease progression was 7 months, and the median overall survival was 23 months (median follow-up of 41 months). Neutropenia was the most frequently observed severe hematologic toxicity (39% of patients), whereas asthenia and nausea were the most common non-hematologic toxicities. No treatment-related death was observed. CONCLUSION: In conclusion, we found docetaxel plus cisplatin to be an active and safe chemotherapy regimen for patients with MBC resistant to anthracyclines

    Cerebral malaria: insights from host-parasite protein-protein interactions

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    <p>Abstract</p> <p>Background</p> <p>Cerebral malaria is a form of human malaria wherein <it>Plasmodium falciparum</it>-infected red blood cells adhere to the blood capillaries in the brain, potentially leading to coma and death. Interactions between parasite and host proteins are important in understanding the pathogenesis of this deadly form of malaria. It is, therefore, necessary to study available protein-protein interactions to identify lesser known interactions that could throw light on key events of cerebral malaria.</p> <p>Methods</p> <p>Sequestration, haemostasis dysfunction, systemic inflammation and neuronal damage are key processes of cerebral malaria. Key events were identified from literature as being crucial to these processes. An integrated interactome was created using available experimental and predicted datasets as well as from literature. Interactions from this interactome were filtered based on Gene Ontology and tissue-specific annotations, and further analysed for relevance to the key events.</p> <p>Results</p> <p>PfEMP1 presentation, platelet activation and astrocyte dysfunction were identified as the key events influencing the disease. 48896 host-parasite along with other host-parasite, host-host and parasite-parasite protein-protein interactions obtained from a disease-specific corpus were combined to form an integrated interactome. Filtering of the interactome resulted in five host-parasite PPI, six parasite-parasite and two host-host PPI. The analysis of these interactions revealed the potential significance of apolipoproteins and temperature/Hsp expression on efficient PfEMP1 presentation; role of MSP-1 in platelet activation; effect of parasite proteins in TGF-β regulation and the role of albumin in astrocyte dysfunction.</p> <p>Conclusions</p> <p>This work links key host-parasite, parasite-parasite and host-host protein-protein interactions to key processes of cerebral malaria and generates hypotheses for disease pathogenesis based on a filtered interaction dataset. These hypotheses provide novel and significant insights to cerebral malaria.</p

    Incidence of chemotherapy-induced amenorrhea associated with epirubicin, docetaxel and navelbine in younger breast cancer patients

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    <p>Abstract</p> <p>Background</p> <p>The rates of chemotherapy-induced amenorrhea (CIA) associated with docetaxel-based regimens reported by previous studies are discordant. For navelbine-based chemotherapies, rates of CIA have seldom been reported.</p> <p>Methods</p> <p>Of 170 premenopausal patients recruited between January 2003 and September 2008, 78 were treated with fluorouracil plus epirubicin and cyclophosphamide (FEC), 66 were treated with docetaxel plus epirubicin (TE), and 26 were treated with navelbine plus epirubicin (NE). Patient follow-up was carried up every 3-4 months during the first year, then every 9-12 months during subsequent years.</p> <p>Results</p> <p>In univariate analysis, the rates of CIA were 44.87% for the FEC regimen, 30.30% for the TE regimen and 23.08% for the NE regimen (<it>P </it>= 0.068). Significant differences in the rates of CIA were not found between the FEC and TE treatment groups (<it>P </it>> 0.05), but were found between the FEC and NE treatment groups (<it>P </it>< 0.05). Furthermore, no significant differences were found between the TE and NE regimens (<it>P </it>> 0.05). Tamoxifen use was a significant predictor for CIA (<it>P </it>= 0.001), and age was also a significant predictor (<it>P </it>< 0.001). In multivariate analysis, age (<it>P </it>< 0.001), the type of chemotherapy regimens (<it>P </it>= 0.009) and tamoxifen use (<it>P </it>= 0.003) were all significant predictors.</p> <p>Conclusions</p> <p>Age and administration of tamoxifen were found to be significant predictive factors of CIA, whereas docetaxel and navelbine based regimens were not associated with higher rates of CIA than epirubicin-based regimen.</p

    The Origins of Lactase Persistence in Europe

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    Lactase persistence (LP) is common among people of European ancestry, but with the exception of some African, Middle Eastern and southern Asian groups, is rare or absent elsewhere in the world. Lactase gene haplotype conservation around a polymorphism strongly associated with LP in Europeans (−13,910 C/T) indicates that the derived allele is recent in origin and has been subject to strong positive selection. Furthermore, ancient DNA work has shown that the −13,910*T (derived) allele was very rare or absent in early Neolithic central Europeans. It is unlikely that LP would provide a selective advantage without a supply of fresh milk, and this has lead to a gene-culture coevolutionary model where lactase persistence is only favoured in cultures practicing dairying, and dairying is more favoured in lactase persistent populations. We have developed a flexible demic computer simulation model to explore the spread of lactase persistence, dairying, other subsistence practices and unlinked genetic markers in Europe and western Asia's geographic space. Using data on −13,910*T allele frequency and farming arrival dates across Europe, and approximate Bayesian computation to estimate parameters of interest, we infer that the −13,910*T allele first underwent selection among dairying farmers around 7,500 years ago in a region between the central Balkans and central Europe, possibly in association with the dissemination of the Neolithic Linearbandkeramik culture over Central Europe. Furthermore, our results suggest that natural selection favouring a lactase persistence allele was not higher in northern latitudes through an increased requirement for dietary vitamin D. Our results provide a coherent and spatially explicit picture of the coevolution of lactase persistence and dairying in Europe

    PEDIA: prioritization of exome data by image analysis

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    Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

    Present state and future perspectives of using pluripotent stem cells in toxicology research

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    The use of novel drugs and chemicals requires reliable data on their potential toxic effects on humans. Current test systems are mainly based on animals or in vitro–cultured animal-derived cells and do not or not sufficiently mirror the situation in humans. Therefore, in vitro models based on human pluripotent stem cells (hPSCs) have become an attractive alternative. The article summarizes the characteristics of pluripotent stem cells, including embryonic carcinoma and embryonic germ cells, and discusses the potential of pluripotent stem cells for safety pharmacology and toxicology. Special attention is directed to the potential application of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) for the assessment of developmental toxicology as well as cardio- and hepatotoxicology. With respect to embryotoxicology, recent achievements of the embryonic stem cell test (EST) are described and current limitations as well as prospects of embryotoxicity studies using pluripotent stem cells are discussed. Furthermore, recent efforts to establish hPSC-based cell models for testing cardio- and hepatotoxicity are presented. In this context, methods for differentiation and selection of cardiac and hepatic cells from hPSCs are summarized, requirements and implications with respect to the use of these cells in safety pharmacology and toxicology are presented, and future challenges and perspectives of using hPSCs are discussed
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