27 research outputs found

    Running Speed in Mammals Increases with Muscle n-6 Polyunsaturated Fatty Acid Content

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    Polyunsaturated fatty acids (PUFAs) are important dietary components that mammals cannot synthesize de novo. Beneficial effects of PUFAs, in particular of the n-3 class, for certain aspects of animal and human health (e.g., cardiovascular function) are well known. Several observations suggest, however, that PUFAs may also affect the performance of skeletal muscles in vertebrates. For instance, it has been shown that experimentally n-6 PUFA-enriched diets increase the maximum swimming speed in salmon. Also, we recently found that the proportion of PUFAs in the muscle phospholipids of an extremely fast runner, the brown hare (Lepus europaeus), are very high compared to other mammals. Therefore, we predicted that locomotor performance, namely running speed, should be associated with differences in muscle fatty acid profiles. To test this hypothesis, we determined phospholipid fatty acid profiles in skeletal muscles of 36 mammalian species ranging from shrews to elephants. We found that there is indeed a general positive, surprisingly strong relation between the n-6 PUFAs content in muscle phospholipids and maximum running speed of mammals. This finding suggests that muscle fatty acid composition directly affects a highly fitness-relevant trait, which may be decisive for the ability of animals to escape from predators or catch prey

    Activation of Hif1α by the Prolylhydroxylase Inhibitor Dimethyoxalyglycine Decreases Radiosensitivity

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    Hypoxia inducible factor 1α (Hif1α) is a stress responsive transcription factor, which regulates the expression of genes required for adaption to hypoxia. Hif1α is normally hydroxylated by an oxygen-dependent prolylhydroxylase, leading to degradation and clearance of Hif1α from the cell. Under hypoxic conditions, the activity of the prolylhydroxylase is reduced and Hif1α accumulates. Hif1α is also constitutively expressed in tumor cells, where it is associated with resistance to ionizing radiation. Activation of the Hif1α transcriptional regulatory pathway may therefore function to protect normal cells from DNA damage caused by ionizing radiation. Here, we utilized the prolylhydroxylase inhibitor dimethyloxalylglycine (DMOG) to elevate Hif1α levels in mouse embryonic fibroblasts (MEFs) to determine if DMOG could function as a radioprotector. The results demonstrate that DMOG increased Hif1α protein levels and decreased the sensitivity of MEFs to ionizing radiation. Further, the ability of DMOG to function as a radioprotector required Hif1α, indicating a key role for Hif1α's transcriptional activity. DMOG also induced the Hif1α -dependent accumulation of several DNA damage response proteins, including CHD4 and MTA3 (sub-units of the NuRD deacetylase complex) and the Suv39h1 histone H3 methyltransferase. Depletion of Suv39h1, but not CHD4 or MTA3, reduced the ability of DMOG to protect cells from radiation damage, implicating increased histone H3 methylation in the radioprotection of cells. Finally, treatment of mice with DMOG prior to total body irradiation resulted in significant radioprotection of the mice, demonstrating the utility of DMOG and related prolylhydroxylase inhibitors to protect whole organisms from ionizing radiation. Activation of Hif1α through prolylhydroxylase inhibition therefore identifies a new pathway for the development of novel radiation protectors

    A saturated map of common genetic variants associated with human height

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    Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

    A saturated map of common genetic variants associated with human height.

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    Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries
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