Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis

OBJECTIVE: Observational studies have demonstrated that type 2 diabetes is a stronger risk factor for coronary heart disease (CHD) in women compared with men. However, it is not clear whether this reflects a sex differential in the causal effect of diabetes on CHD risk or results from sex-specific residual confounding. RESEARCH DESIGN AND METHODS: Using 270 single nucleotide polymorphisms (SNPs) for type 2 diabetes identified in a type 2 diabetes genome-wide association study, we performed a sex-stratified Mendelian randomization (MR) study of type 2 diabetes and CHD using individual participant data in UK Biobank (251,420 women and 212,049 men). Weighted median, MR-Egger, MR-pleiotropy residual sum and outlier, and radial MR from summary-level analyses were used for pleiotropy assessment. RESULTS: MR analyses showed that genetic risk of type 2 diabetes increased the odds of CHD for women (odds ratio 1.13 [95% CI 1.08–1.18] per 1-log unit increase in odds of type 2 diabetes) and men (1.21 [1.17–1.26] per 1-log unit increase in odds of type 2 diabetes). Sensitivity analyses showed some evidence of directional pleiotropy; however, results were similar after correction for outlier SNPs. CONCLUSIONS: This MR analysis supports a causal effect of genetic liability to type 2 diabetes on risk of CHD that is not stronger for women than men. Assuming a lack of bias, these findings suggest that the prevention and management of type 2 diabetes for CHD risk reduction is of equal priority in both sexes

Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction

<p>Abstract</p> <p>Background</p> <p>Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods.</p> <p>Results</p> <p>We define a number of performance measures that can handle the different types of output data from the five methods. We use two evaluation datasets consisting of known HIV CTL epitopes and their source proteins. The source proteins are split into all possible 9 mers and except for annotated epitopes; all other 9 mers are considered non-epitopes. In the RANK measure, we compare two methods at a time and count how often each of the methods rank the epitope highest. In another measure, we find the specificity of the methods at three predefined sensitivity values. Lastly, for each method, we calculate the percentage of known epitopes that rank within the 5% peptides with the highest predicted score.</p> <p>Conclusion</p> <p>NetCTL-1.2 is demonstrated to have a higher predictive performance than EpiJen, MAPPP, MHC-pathway, and WAPP on all performance measures. The higher performance of NetCTL-1.2 as compared to EpiJen and MHC-pathway is, however, not statistically significant on all measures. In the large-scale benchmark calculation consisting of 216 known HIV epitopes covering all 12 recognized HLA supertypes, the NetCTL-1.2 method was shown to have a sensitivity among the 5% top-scoring peptides above 0.72. On this dataset, the best of the other methods achieved a sensitivity of 0.64. The NetCTL-1.2 method is available at <url>http://www.cbs.dtu.dk/services/NetCTL</url>.</p> <p>All used datasets are available at <url>http://www.cbs.dtu.dk/suppl/immunology/CTL-1.2.php</url>.</p

Considering the Case for Biodiversity Cycles: Reexamining the Evidence for Periodicity in the Fossil Record

Medvedev and Melott (2007) have suggested that periodicity in fossil biodiversity may be induced by cosmic rays which vary as the Solar System oscillates normal to the galactic disk. We re-examine the evidence for a 62 million year (Myr) periodicity in biodiversity throughout the Phanerozoic history of animal life reported by Rohde & Mueller (2005), as well as related questions of periodicity in origination and extinction. We find that the signal is robust against variations in methods of analysis, and is based on fluctuations in the Paleozoic and a substantial part of the Mesozoic. Examination of origination and extinction is somewhat ambiguous, with results depending upon procedure. Origination and extinction intensity as defined by RM may be affected by an artifact at 27 Myr in the duration of stratigraphic intervals. Nevertheless, when a procedure free of this artifact is implemented, the 27 Myr periodicity appears in origination, suggesting that the artifact may ultimately be based on a signal in the data. A 62 Myr feature appears in extinction, when this same procedure is used. We conclude that evidence for a periodicity at 62 Myr is robust, and evidence for periodicity at approximately 27 Myr is also present, albeit more ambiguous.Comment: Minor modifications to reflect final published versio

Long-term cycles in the history of life: Periodic biodiversity in the Paleobiology Database

Time series analysis of fossil biodiversity of marine invertebrates in the Paleobiology Database (PBDB) shows a significant periodicity at approximately 63 My, in agreement with previous analyses based on the Sepkoski database. I discuss how this result did not appear in a previous analysis of the PBDB. The existence of the 63 My periodicity, despite very different treatment of systematic error in both PBDB and Sepkoski databases strongly argues for consideration of its reality in the fossil record. Cross-spectral analysis of the two datasets finds that a 62 My periodicity coincides in phase by 1.6 My, equivalent to better than the errors in either measurement. Consequently, the two data sets not only contain the same strong periodicity, but its peaks and valleys closely correspond in time. Two other spectral peaks appear in the PBDB analysis, but appear to be artifacts associated with detrending and with the increased interval length. Sampling-standardization procedures implemented by the PBDB collaboration suggest that the signal is not an artifact of sampling bias. Further work should focus on finding the cause of the 62 My periodicity.Comment: Published in PLoS ONE. 5 pages, 3 figures. Version with live links, discussion available at http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004044#to

Pichinde virus induces microvascular endothelial cell permeability through the production of nitric oxide

This report is the first to demonstrate infection of human endothelial cells by Pichinde virus (PIC). PIC infection induces an upregulation of the inducible nitric oxide synthase gene; as well as an increase in detectable nitric oxide (NO). PIC induces an increase in permeability in endothelial cell monolayers which can be abrogated at all measured timepoints with the addition of a nitric oxide synthase inhibitor, indicating a role for NO in the alteration of endothelial barrier function. Because NO has shown antiviral activity against some viruses, viral titer was measured after addition of the NO synthase inhibitor and found to have no effect in altering virus load in infected EC. The NO synthase inhibition also has no effect on levels of activated caspases induced by PIC infection. Taken together, these data indicate NO production induced by Pichinde virus infection has a pathogenic effect on endothelial cell monolayer permeability

T-Cell Epitope Prediction: Rescaling Can Mask Biological Variation between MHC Molecules

Theoretical methods for predicting CD8+ T-cell epitopes are an important tool in vaccine design and for enhancing our understanding of the cellular immune system. The most popular methods currently available produce binding affinity predictions across a range of MHC molecules. In comparing results between these MHC molecules, it is common practice to apply a normalization procedure known as rescaling, to correct for possible discrepancies between the allelic predictors. Using two of the most popular prediction software packages, NetCTL and NetMHC, we tested the hypothesis that rescaling removes genuine biological variation from the predicted affinities when comparing predictions across a number of MHC molecules. We found that removing the condition of rescaling improved the prediction software's performance both qualitatively, in terms of ranking epitopes, and quantitatively, in the accuracy of their binding affinity predictions. We suggest that there is biologically significant variation among class 1 MHC molecules and find that retention of this variation leads to significantly more accurate epitope prediction

Prevalence of Childhood Atopic Dermatitis: An Urban and Rural Community-Based Study in Shanghai, China

Background: Atopic dermatitis (AD) is a common inflammatory and chronically relapsing disorder with increasing prevalence. However, little is known about its prevalence in Shanghai, the top metropolitan of China. This study will estimate and compare the prevalence of AD in urban and rural areas in representative samples of 3 to 6-year-old children in Shanghai. Methodology/Principal Findings: A descriptive cross-sectional study was performed. Pre-school children were obtained by cluster sampling from 8 communities in different districts in Shanghai. The main instrument was the core questionnaire module for AD used in the U.K. Working Party’s study. All the data were statistically analyzed by EpiData 3.1 and SPSS16.0. A total of 10436 children completed the study satisfactorily, with a response rate of 95.8%. The prevalence of AD in 3 to 6-year-old children was 8.3 % (Male: 8.5%, Female: 8.2%). The prevalence in urban areas of Shanghai was gradiently and significantly higher than that in rural areas. The highest prevalence was in the core urban area (10.2 % in Xuhui Tianping) vs. the lowest far from the urban areas (4.6 % in Chongming Baozhen). Conclusions/Significance: The prevalence of AD was 8.3 % (95%CI: 7.6%–9.1%) in children aged 3 to 6 in Shanghai. Th

NetCTLpan: pan-specific MHC class I pathway epitope predictions

Reliable predictions of immunogenic peptides are essential in rational vaccine design and can minimize the experimental effort needed to identify epitopes. In this work, we describe a pan-specific major histocompatibility complex (MHC) class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, transporter associated with antigen processing (TAP) transport efficiency, and MHC class I binding affinity into a MHC class I pathway likelihood score and is an improved and extended version of NetCTL. The NetCTLpan method performs predictions for all MHC class I molecules with known protein sequence and allows predictions for 8-, 9-, 10-, and 11-mer peptides. In order to meet the need for a low false positive rate, the method is optimized to achieve high specificity. The method was trained and validated on large datasets of experimentally identified MHC class I ligands and cytotoxic T lymphocyte (CTL) epitopes. It has been reported that MHC molecules are differentially dependent on TAP transport and proteasomal cleavage. Here, we did not find any consistent signs of such MHC dependencies, and the NetCTLpan method is implemented with fixed weights for proteasomal cleavage and TAP transport for all MHC molecules. The predictive performance of the NetCTLpan method was shown to outperform other state-of-the-art CTL epitope prediction methods. Our results further confirm the importance of using full-type human leukocyte antigen restriction information when identifying MHC class I epitopes. Using the NetCTLpan method, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40%, respectively, when compared to the NetMHCpan and NetCTL methods. The method and benchmark datasets are available at http://www.cbs.dtu.dk/services/NetCTLpan/

Amino Acid Similarity Accounts for T Cell Cross-Reactivity and for “Holes” in the T Cell Repertoire

Background: Cytotoxic T cell (CTL) cross-reactivity is believed to play a pivotal role in generating immune responses but the extent and mechanisms of CTL cross-reactivity remain largely unknown. Several studies suggest that CTL clones can recognize highly diverse peptides, some sharing no obvious sequence identity. The emerging realization in the field is that T cell receptors (TcR) recognize multiple distinct ligands. Principal Findings: First, we analyzed peptide scans of the HIV epitope SLFNTVATL (SFL9) and found that TCR specificity is position dependent and that biochemically similar amino acid substitutions do not drastically affect recognition. Inspired by this, we developed a general model of TCR peptide recognition using amino acid similarity matrices and found that such a model was able to predict the cross-reactivity of a diverse set of CTL epitopes. With this model, we were able to demonstrate that seemingly distinct T cell epitopes, i.e., ones with low sequence identity, are in fact more biochemically similar than expected. Additionally, an analysis of HIV immunogenicity data with our model showed that CTLs have the tendency to respond mostly to peptides that do not resemble self-antigens. Conclusions: T cell cross-reactivity can thus, to an extent greater than earlier appreciated, be explained by amino acid similarity. The results presented in this paper will help resolving some of the long-lasting discussions in the field of T cel