Integrated probability of coronary heart disease subject to the -308 tumor necrosis factor-alpha SNP: a Bayesian meta-analysis.

We present a meta-analysis of independent studies on the potential implication in the occurrence of coronary heart disease (CHD) of the single-nucleotide polymorphism (SNP) at the -308 position of the tumor necrosis factor alpha (TNF-alpha) gene. We use Bayesian analysis to integrate independent data sets and to infer statistically robust measurements of correlation. Bayesian hypothesis testing indicates that there is no preference for the hypothesis that the -308 TNF-alpha SNP is related to the occurrence of CHD, in the Caucasian or in the Asian population, over the null hypothesis. As a measure of correlation, we use the probability of occurrence of CHD conditional on the presence of the SNP, derived as the posterior probability of the Bayesian meta-analysis. The conditional probability indicates that CHD is not more likely to occur when the SNP is present, which suggests that the -308 TNF-alpha SNP is not implicated in the occurrence of CHD.

Protein signatures using electrostatic molecular surfaces in harmonic space.

We developed a novel method based on the Fourier analysis of protein molecular surfaces to speed up the analysis of the vast structural data generated in the post-genomic era. This method computes the power spectrum of surfaces of the molecular electrostatic potential, whose three-dimensional coordinates have been either experimentally or theoretically determined. Thus we achieve a reduction of the initial three-dimensional information on the molecular surface to the one-dimensional information on pairs of points at a fixed scale apart. Consequently, the similarity search in our method is computationally less demanding and significantly faster than shape comparison methods. As proof of principle, we applied our method to a training set of viral proteins that are involved in major diseases such as Hepatitis C, Dengue fever, Yellow fever, Bovine viral diarrhea and West Nile fever. The training set contains proteins of four different protein families, as well as a mammalian representative enzyme. We found that the power spectrum successfully assigns a unique signature to each protein included in our training set, thus providing a direct probe of functional similarity among proteins. The results agree with established biological data from conventional structural biochemistry analyses.

Detection of the power spectrum of cosmic microwave background lensing by the Atacama Cosmology Telescope.

We report the first detection of the gravitational lensing of the cosmic microwave background through a measurement of the four-point correlation function in the temperature maps made by the Atacama Cosmology Telescope. We verify our detection by calculating the levels of potential contaminants and performing a number of null tests. The resulting convergence power spectrum at 2° angular scales measures the amplitude of matter density fluctuations on comoving length scales of around 100 Mpc at redshifts around 0.5 to 3. The measured amplitude of the signal agrees with Lambda cold dark matter cosmology predictions. Since the amplitude of the convergence power spectrum scales as the square of the amplitude of the density fluctuations, the 4σ detection of the lensing signal measures the amplitude of density fluctuations to 12%.

Evidence for dark energy from the cosmic microwave background alone using the Atacama Cosmology Telescope lensing measurements.

For the first time, measurements of the cosmic microwave background radiation (CMB) alone favor cosmologies with w = -1 dark energy over models without dark energy at a 3.2-sigma level. We demonstrate this by combining the CMB lensing deflection power spectrum from the Atacama Cosmology Telescope with temperature and polarization power spectra from the Wilkinson Microwave Anisotropy Probe. The lensing data break the geometric degeneracy of different cosmological models with similar CMB temperature power spectra. Our CMB-only measurement of the dark energy density Ω(Λ) confirms other measurements from supernovae, galaxy clusters, and baryon acoustic oscillations, and demonstrates the power of CMB lensing as a new cosmological tool.

A Bayesian approach to the probability of coronary heart disease subject to the -308 tumor necrosis factor-α SNP.

We study the correlation of the occurrence of coronary heart disease (CHD) with the presence of the single-nucleotide polymorphism (SNP) at the -308 position of the tumor necrosis factor alpha (TNF-α) gene. We also consider the influence of the occurrence of type 2 diabetes (t2DM). Using Bayesian inference, we first pursue a bottom-up approach to compute the working hypothesis and the probabilities derivable from the data. We then pursue a top-down approach by modelling the signal pathway that causally connects the SNP with the emergence of CHD. We compute the functional form of the probability of CHD conditional on the presence of the SNP in terms of both the statistical and biochemical properties of the system. From the probability of occurrence of a disease conditional on a given risk factor, we explore the possibility of extracting information on the pathways involved in the occurrence of the disease. This is a first study that we want to systematise into a comprehensive formalism to be applied to the inference of the mechanism connecting the risk factors to the disease.