1,222 research outputs found
The complete linkage disequilibrium test: a test that points to causative mutations underlying quantitative traits
<p>Abstract</p> <p>Background</p> <p>Genetically, SNP that are in complete linkage disequilibrium with the causative SNP cannot be distinguished from the causative SNP. The Complete Linkage Disequilibrium (CLD) test presented here tests whether a SNP is in complete LD with the causative mutation or not. The performance of the CLD test is evaluated in 1000 simulated datasets.</p> <p>Methods</p> <p>The CLD test consists of two steps i.e. analysis I and analysis II. Analysis I consists of an association analysis of the investigated region. The log-likelihood values from analysis I are next ranked in descending order and in analysis II the CLD test evaluates differences in log-likelihood ratios between the best and second best markers. Under the null-hypothesis distribution, the best SNP is in greater LD with the QTL than the second best, while under the alternative-CLD-hypothesis, the best SNP is alike-in-state with the QTL. To find a significance threshold, the test was also performed on data excluding the causative SNP. The 5<sup>th</sup>, 10<sup>th </sup>and 50<sup>th </sup>highest T<sub>CLD </sub>value from 1000 replicated analyses were used to control the type-I-error rate of the test at p = 0.005, p = 0.01 and p = 0.05, respectively.</p> <p>Results</p> <p>In a situation where the QTL explained 48% of the phenotypic variance analysis I detected a QTL in 994 replicates (p = 0.001), where 972 were positioned in the correct QTL position. When the causative SNP was excluded from the analysis, 714 replicates detected evidence of a QTL (p = 0.001). In analysis II, the CLD test confirmed 280 causative SNP from 1000 simulations (p = 0.05), i.e. power was 28%. When the effect of the QTL was reduced by doubling the error variance, the power of the test reduced relatively little to 23%. When sequence data were used, the power of the test reduced to 16%. All SNP that were confirmed by the CLD test were positioned in the correct QTL position.</p> <p>Conclusions</p> <p>The CLD test can provide evidence for a causative SNP, but its power may be low in situations with closely linked markers. In such situations, also functional evidence will be needed to definitely conclude whether the SNP is causative or not.</p
The effect of the systemic inflammatory response on plasma vitamin 25 (OH) D concentrations adjusted for albumin
<b>Aim</b><p></p>
To examine the relationship between plasma 25(OH)D, CRP and albumin concentrations in two patient cohorts.<p></p>
<b>Methods</b><p></p>
5327 patients referred for nutritional assessment and 117 patients with critical illness were examined. Plasma 25 (OH) D concentrations were measured using standard methods. Intra and between assay imprecision was <10%.<p></p>
<b>Result</b><p></p>
In the large cohort, plasma 25 (OH) D was significantly associated with CRP (rs = −0.113, p<0.001) and albumin (rs = 0.192, p<0.001). 3711 patients had CRP concentrations ≤10 mg/L; with decreasing albumin concentrations ≥35, 25–34 and <25 g/l, median concentrations of 25 (OH) D were significantly lower from 35 to 28 to 14 nmol/l (p<0.001). This decrease was significant when albumin concentrations were reduced between 25–34 g/L (p<0.001) and when albumin <25 g/L (p<0.001). 1271 patients had CRP concentrations between 11–80 mg/L; with decreasing albumin concentrations ≥35, 25–34 and <25 g/l, median concentrations of 25 (OH) D were significantly lower from 31 to 24 to 19 nmol/l (p<0.001). This decrease was significant when albumin concentration were 25–34 g/L (p<0.001) and when albumin <25 g/L (p<0.001). 345 patients had CRP concentrations >80 mg/L; with decreasing albumin concentrations ≥35, 25–34 and <25 g/l, median concentrations of 25 (OH) D were not significantly altered varying from 19 to 23 to 23 nmol/l. Similar relationships were also obtained in the cohort of patients with critical illness.<p></p>
<b>Conclusion</b><p></p>
Plasma concentrations of 25(OH) D were independently associated with both CRP and albumin and consistent with the systemic inflammatory response as a major confounding factor in determining vitamin D status.<p></p>
A Comparison of Phylogenetic Network Methods Using Computer Simulation
Background: We present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining and minimum spanning network) compared to standard tree approaches, (neighbor-joining and maximum parsimony) in the presence and absence of recombination. Principal Findings: In the absence of recombination, all methods recovered the correct topology and branch lengths nearly all of the time when the substitution rate was low, except for minimum spanning networks, which did considerably worse. At a higher substitution rate, maximum parsimony and union of maximum parsimony trees were the most accurate. With recombination, the ability to infer the correct topology was halved for all methods and no method could accurately estimate branch lengths. Conclusions: Our results highlight the need for more accurate phylogenetic network methods and the importance of detecting and accounting for recombination in phylogenetic studies. Furthermore, we provide useful information for choosing a network algorithm and a framework in which to evaluate improvements to existing methods and nove
Lymphocyte subsets and the role of Th1/Th2 balance in stressed chronic pain patients
Background: The complex regional pain syndrome (CRPS) and fibromyalgia (FM) are chronic pain syndromes occurring in highly stressed individuals. Despite the known connection between the nervous system and immune cells, information on distribution of lymphocyte subsets under stress and pain conditions is limited. Methods: We performed a comparative study in 15 patients with CRPS type I, 22 patients with FM and 37 age- and sex-matched healthy controls and investigated the influence of pain and stress on lymphocyte number, subpopulations and the Th1/Th2 cytokine ratio in T lymphocytes. Results: Lymphocyte numbers did not differ between groups. Quantitative analyses of lymphocyte subpopulations showed a significant reduction of cytotoxic CD8+ lymphocytes in both CRPS (p < 0.01) and FM (p < 0.05) patients as compared with healthy controls. Additionally, CRPS patients were characterized by a lower percentage of IL-2-producing T cell subpopulations reflecting a diminished Th1 response in contrast to no changes in the Th2 cytokine profile. Conclusions: Future studies are warranted to answer whether such immunological changes play a pathogenetic role in CRPS and FM or merely reflect the consequences of a pain-induced neurohumoral stress response, and whether they contribute to immunosuppression in stressed chronic pain patients. Copyright (c) 2008 S. Karger AG, Basel
On dynamic network entropy in cancer
The cellular phenotype is described by a complex network of molecular
interactions. Elucidating network properties that distinguish disease from the
healthy cellular state is therefore of critical importance for gaining
systems-level insights into disease mechanisms and ultimately for developing
improved therapies. By integrating gene expression data with a protein
interaction network to induce a stochastic dynamics on the network, we here
demonstrate that cancer cells are characterised by an increase in the dynamic
network entropy, compared to cells of normal physiology. Using a fundamental
relation between the macroscopic resilience of a dynamical system and the
uncertainty (entropy) in the underlying microscopic processes, we argue that
cancer cells will be more robust to random gene perturbations. In addition, we
formally demonstrate that gene expression differences between normal and cancer
tissue are anticorrelated with local dynamic entropy changes, thus providing a
systemic link between gene expression changes at the nodes and their local
network dynamics. In particular, we also find that genes which drive
cell-proliferation in cancer cells and which often encode oncogenes are
associated with reductions in the dynamic network entropy. In summary, our
results support the view that the observed increased robustness of cancer cells
to perturbation and therapy may be due to an increase in the dynamic network
entropy that allows cells to adapt to the new cellular stresses. Conversely,
genes that exhibit local flux entropy decreases in cancer may render cancer
cells more susceptible to targeted intervention and may therefore represent
promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte
Inference of population splits and mixtures from genome-wide allele frequency data
Many aspects of the historical relationships between populations in a species
are reflected in genetic data. Inferring these relationships from genetic data,
however, remains a challenging task. In this paper, we present a statistical
model for inferring the patterns of population splits and mixtures in multiple
populations. In this model, the sampled populations in a species are related to
their common ancestor through a graph of ancestral populations. Using
genome-wide allele frequency data and a Gaussian approximation to genetic
drift, we infer the structure of this graph. We applied this method to a set of
55 human populations and a set of 82 dog breeds and wild canids. In both
species, we show that a simple bifurcating tree does not fully describe the
data; in contrast, we infer many migration events. While some of the migration
events that we find have been detected previously, many have not. For example,
in the human data we infer that Cambodians trace approximately 16% of their
ancestry to a population ancestral to other extant East Asian populations. In
the dog data, we infer that both the boxer and basenji trace a considerable
fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to
domestication, and that East Asian toy breeds (the Shih Tzu and the Pekingese)
result from admixture between modern toy breeds and "ancient" Asian breeds.
Software implementing the model described here, called TreeMix, is available at
http://treemix.googlecode.comComment: 28 pages, 6 figures in main text. Attached supplement is 22 pages, 15
figures. This is an updated version of the preprint available at
http://precedings.nature.com/documents/6956/version/
Recombination rate and selection strength in HIV intra-patient evolution
The evolutionary dynamics of HIV during the chronic phase of infection is
driven by the host immune response and by selective pressures exerted through
drug treatment. To understand and model the evolution of HIV quantitatively,
the parameters governing genetic diversification and the strength of selection
need to be known. While mutation rates can be measured in single replication
cycles, the relevant effective recombination rate depends on the probability of
coinfection of a cell with more than one virus and can only be inferred from
population data. However, most population genetic estimators for recombination
rates assume absence of selection and are hence of limited applicability to
HIV, since positive and purifying selection are important in HIV evolution.
Here, we estimate the rate of recombination and the distribution of selection
coefficients from time-resolved sequence data tracking the evolution of HIV
within single patients. By examining temporal changes in the genetic
composition of the population, we estimate the effective recombination to be
r=1.4e-5 recombinations per site and generation. Furthermore, we provide
evidence that selection coefficients of at least 15% of the observed
non-synonymous polymorphisms exceed 0.8% per generation. These results provide
a basis for a more detailed understanding of the evolution of HIV. A
particularly interesting case is evolution in response to drug treatment, where
recombination can facilitate the rapid acquisition of multiple resistance
mutations. With the methods developed here, more precise and more detailed
studies will be possible, as soon as data with higher time resolution and
greater sample sizes is available.Comment: to appear in PLoS Computational Biolog
Resveratrol Suppresses Constitutive Activation of AKT via Generation of ROS and Induces Apoptosis in Diffuse Large B Cell Lymphoma Cell Lines
BACKGROUND: We have recently shown that deregulation PI3-kinase/AKT survival pathway plays an important role in pathogenesis of diffuse large B cell lymphoma (DLBCL). In an attempt to identify newer therapeutic agents, we investigated the role of Resveratrol (trans-3,4', 5-trihydroxystilbene), a naturally occurring polyphenolic compound on a panel of diffuse large B-cell lymphoma (DLBCL) cells in causing inhibition of cell viability and inducing apoptosis. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the action of Resveratrol on DLBCL cells and found that Resveratrol inhibited cell viability and induced apoptosis by inhibition of constitutively activated AKT and its downstream targets via generation of reactive oxygen species (ROS). Simultaneously, Resveratrol treatment of DLBCL cell lines also caused ROS dependent upregulation of DR5; and interestingly, co-treatment of DLBCL with sub-toxic doses of TRAIL and Resveratrol synergistically induced apoptosis via utilizing DR5, on the other hand, gene silencing of DR5 abolished this effect. CONCLUSION/SIGNIFICANCE: Altogether, these data suggest that Resveratrol acts as a suppressor of AKT/PKB pathway leading to apoptosis via generation of ROS and at the same time primes DLBCL cells via up-regulation of DR5 to TRAIL-mediated apoptosis. These data raise the possibility that Resveratrol may have a future therapeutic role in DLBCL and possibly other malignancies with constitutive activation of the AKT/PKB pathway
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