The effects of linkage disequilibrium in large scale SNP datasets for MDR

<p>Abstract</p> <p>Background</p> <p>In the analysis of large-scale genomic datasets, an important consideration is the power of analytical methods to identify accurate predictive models of disease. When trying to assess sensitivity from such analytical methods, a confounding factor up to this point has been the presence of linkage disequilibrium (LD). In this study, we examined the effect of LD on the sensitivity of the Multifactor Dimensionality Reduction (MDR) software package.</p> <p>Results</p> <p>Four relative amounts of LD were simulated in multiple one- and two-locus scenarios for which the position of the functional SNP(s) within LD blocks varied. Simulated data was analyzed with MDR to determine the sensitivity of the method in different contexts, where the sensitivity of the method was gauged as the number of times out of 100 that the method identifies the correct one- or two-locus model as the best overall model. As the amount of LD increases, the sensitivity of MDR to detect the correct functional SNP drops but the sensitivity to detect the disease signal and find an indirect association increases.</p> <p>Conclusions</p> <p>Higher levels of LD begin to confound the MDR algorithm and lead to a drop in sensitivity with respect to the identification of a direct association; it does not, however, affect the ability to detect indirect association. Careful examination of the solution models generated by MDR reveals that MDR can identify loci in the correct LD block; though it is not always the functional SNP. As such, the results of MDR analysis in datasets with LD should be carefully examined to consider the underlying LD structure of the dataset.</p

Dirac Equation with Spin Symmetry for the Modified P\"oschl-Teller Potential in DD-dimensions

We present solutions of the Dirac equation with spin symmetry for vector and scalar modified P\"oschl-Teller potential within framework of an approximation of the centrifugal term. The relativistic energy spectrum is obtained using the Nikiforov-Uvarov method and the two-component spinor wavefunctions are obtain are in terms of the Jacobi polynomials. It is found that there exist only positive-energy states for bound states under spin symmetry, and the energy levels increase with the dimension and the potential range parameter $\alpha$.Comment: 9 pages and 1tabl

State based model of long-term potentiation and synaptic tagging and capture

Recent data indicate that plasticity protocols have not only synapse-specific but also more widespread effects. In particular, in synaptic tagging and capture (STC), tagged synapses can capture plasticity-related proteins, synthesized in response to strong stimulation of other synapses. This leads to long-lasting modification of only weakly stimulated synapses. Here we present a biophysical model of synaptic plasticity in the hippocampus that incorporates several key results from experiments on STC. The model specifies a set of physical states in which a synapse can exist, together with transition rates that are affected by high- and low-frequency stimulation protocols. In contrast to most standard plasticity models, the model exhibits both early- and late-phase LTP/D, de-potentiation, and STC. As such, it provides a useful starting point for further theoretical work on the role of STC in learning and memory

Noradrenergic ‘Tone’ Determines Dichotomous Control of Cortical Spike-Timing-Dependent Plasticity

Norepinephrine (NE) is widely distributed throughout the brain. It modulates intrinsic currents, as well as amplitude and frequency of synaptic transmission affecting the ‘signal-to-noise ratio’ of sensory responses. In the visual cortex, α1- and β-adrenergic receptors (AR) gate opposing effects on long-term plasticity of excitatory transmission. Whether and how NE recruits these plastic mechanisms is not clear. Here, we show that NE modulates glutamatergic inputs with different efficacies for α1- and β-AR. As a consequence, the priming of synapses with different NE concentrations produces dose-dependent competing effects that determine the temporal window of spike-timing dependent plasticity (STDP). While a low NE concentration leads to long-term depression (LTD) over broad positive and negative delays, a high NE concentration results in bidirectional STDP restricted to very narrow intervals. These results indicate that the local availability of NE, released during emotional arousal, determines the compound modulatory effect and the output of STDP

Indirect exclusion of four candidate genes for generalized progressive retinal atrophy in several breeds of dogs

BACKGROUND: Generalized progressive retinal atrophy (gPRA) is a hereditary ocular disorder with progressive photoreceptor degeneration in dogs. Four retina-specific genes, ATP binding cassette transporter retina (ABCA4), connexin 36 (CX36), c-mer tyrosin kinase receptor (MERTK) and photoreceptor cell retinol dehydrogenase (RDH12) were investigated in order to identify mutations leading to autosomal recessive (ar) gPRA in 29 breeds of dogs. RESULTS: Mutation screening was performed initially by PCR and single strand conformation polymorphism (SSCP) analysis, representing a simple method with comparatively high reliability for identification of sequence variations in many samples. Conspicuous banding patterns were analyzed via sequence analyses in order to detect the underlying nucleotide variations. No pathogenetically relevant mutations were detected in the genes ABCA4, CX36, MERTK and RDH12 in 71 affected dogs of 29 breeds. Yet 30 new sequence variations were identified, both, in the coding regions and intronic sequences. Many of the sequence variations were in heterozygous state in affected dogs. CONCLUSION: Based on the ar transmittance of gPRA in the breeds investigated, informative sequence variations provide evidence allowing indirect exclusion of pathogenetic mutations in the genes ABCA4 (for 9 breeds), CX36 (for 12 breeds), MERTK (for all 29 breeds) and RDH12 (for 9 breeds)

A General Framework for Formal Tests of Interaction after Exhaustive Search Methods with Applications to MDR and MDR-PDT

The initial presentation of multifactor dimensionality reduction (MDR) featured cross-validation to mitigate over-fitting, computationally efficient searches of the epistatic model space, and variable construction with constructive induction to alleviate the curse of dimensionality. However, the method was unable to differentiate association signals arising from true interactions from those due to independent main effects at individual loci. This issue leads to problems in inference and interpretability for the results from MDR and the family-based compliment the MDR-pedigree disequilibrium test (PDT). A suggestion from previous work was to fit regression models post hoc to specifically evaluate the null hypothesis of no interaction for MDR or MDR-PDT models. We demonstrate with simulation that fitting a regression model on the same data as that analyzed by MDR or MDR-PDT is not a valid test of interaction. This is likely to be true for any other procedure that searches for models, and then performs an uncorrected test for interaction. We also show with simulation that when strong main effects are present and the null hypothesis of no interaction is true, that MDR and MDR-PDT reject at far greater than the nominal rate. We also provide a valid regression-based permutation test procedure that specifically tests the null hypothesis of no interaction, and does not reject the null when only main effects are present. The regression-based permutation test implemented here conducts a valid test of interaction after a search for multilocus models, and can be applied to any method that conducts a search to find a multilocus model representing an interaction

Molecular targeted therapies in head and neck cancer - An update of recent developements -

Targeted therapies have made their way into clinical practice during the past decade. They have caused a major impact on the survival of cancer patients in many areas of clinical oncology and hematology. Indeed, in some hematologic malignancies, such as chronic myelogenous leukemia or non-Hodgkin's lymphomas, biologicals and antibodies specifically designed to target tumour-specific proteins have revolutionized treatment standards. In solid tumours, new drugs targeting EGF- or VEGF- receptors are now approved and are entering clinical practise for treatment of colon, lung, kidney and other cancers, either alone or in combination with conventional treatment approaches

Coincident Activity of Converging Pathways Enables Simultaneous Long-Term Potentiation and Long-Term Depression in Hippocampal CA1 Network In Vivo

Memory is believed to depend on activity-dependent changes in the strength of synapses, e.g. long-term potentiation (LTP) and long-term depression (LTD), which can be determined by the sequence of coincident pre- and postsynaptic activity, respectively. It remains unclear, however, whether and how coincident activity of converging efferent pathways can enable LTP and LTD in the pathways simultaneously. Here, we report that, in pentobarbital-anesthetized rats, stimulation (600 pulses, 5 Hz) to Schaffer preceding to commissural pathway within a 40-ms timing window induced similar magnitudes of LTP in both pathways onto synapses of CA1 neurons, with varied LTP magnitudes after reversal of the stimulation sequence. In contrast, in urethane-anesthetized or freely-moving rats, the stimulation to Schaffer preceding to commissural pathway induced Schaffer LTP and commissural LTD simultaneously within a 40-ms timing window, without affecting synaptic efficacy in the reversed stimulation sequence. Coincident activity of Schaffer pathways confirmed the above findings under pentobarbital and urethane anesthesia. Thus, coincident activity of converging afferent pathways tends to switch the pathways to be LTP only or LTP/LTD depending on the activity states of the hippocampus. This network rule strengthens the view that activity-dependent synaptic plasticity may well contribute to memory process of the hippocampal network with flexibility or stability from one state to another