A Unifying Framework for Evaluating the Predictive Power of Genetic Variants Based on the Level of Heritability Explained

An increasing number of genetic variants have been identified for many complex diseases. However, it is controversial whether risk prediction based on genomic profiles will be useful clinically. Appropriate statistical measures to evaluate the performance of genetic risk prediction models are required. Previous studies have mainly focused on the use of the area under the receiver operating characteristic (ROC) curve, or AUC, to judge the predictive value of genetic tests. However, AUC has its limitations and should be complemented by other measures. In this study, we develop a novel unifying statistical framework that connects a large variety of predictive indices together. We showed that, given the overall disease probability and the level of variance in total liability (or heritability) explained by the genetic variants, we can estimate analytically a large variety of prediction metrics, for example the AUC, the mean risk difference between cases and non-cases, the net reclassification improvement (ability to reclassify people into high- and low-risk categories), the proportion of cases explained by a specific percentile of population at the highest risk, the variance of predicted risks, and the risk at any percentile. We also demonstrate how to construct graphs to visualize the performance of risk models, such as the ROC curve, the density of risks, and the predictiveness curve (disease risk plotted against risk percentile). The results from simulations match very well with our theoretical estimates. Finally we apply the methodology to nine complex diseases, evaluating the predictive power of genetic tests based on known susceptibility variants for each trait

Dosimetric precision of an ion beam tracking system

<p>Abstract</p> <p>Background</p> <p>Scanned ion beam therapy of intra-fractionally moving tumors requires motion mitigation. GSI proposed beam tracking and performed several experimental studies to analyse the dosimetric precision of the system for scanned carbon beams.</p> <p>Methods</p> <p>A beam tracking system has been developed and integrated in the scanned carbon ion beam therapy unit at GSI. The system adapts pencil beam positions and beam energy according to target motion.</p> <p>Motion compensation performance of the beam tracking system was assessed by measurements with radiographic films, a range telescope, a 3D array of 24 ionization chambers, and cell samples for biological dosimetry. Measurements were performed for stationary detectors and moving detectors using the beam tracking system.</p> <p>Results</p> <p>All detector systems showed comparable data for a moving setup when using beam tracking and the corresponding stationary setup. Within the target volume the mean relative differences of ionization chamber measurements were 0.3% (1.5% standard deviation, 3.7% maximum). Film responses demonstrated preserved lateral dose gradients. Measurements with the range telescope showed agreement of Bragg peak depth under motion induced range variations. Cell survival experiments showed a mean relative difference of -5% (-3%) between measurements and calculations within the target volume for beam tracking (stationary) measurements.</p> <p>Conclusions</p> <p>The beam tracking system has been successfully integrated. Full functionality has been validated dosimetrically in experiments with several detector types including biological cell systems.</p

The role of financial analysts in stock market efficiency with respect to annual earnings and its cash and accrual components

This study examines biases in stock prices and financial analysts\u27 earnings forecasts. These biases take the form of systematic overweighting or underweighting of the persistence characteristics of cash versus accrual earnings components. Our evidence suggests that stock prices tend to overweight and financial analysts tend to underweight these persistence characteristics. Furthermore, we find that analysts\u27 underweighting attenuates stock price overweighting. However, we find little evidence that the overweighting in stock prices attenuates analyst underweighting. This study brings a new perspective to the literature regarding the disciplining role of financial analysts in capital markets

4D treatment planning for scanned ion beams

At Gesellschaft für Schwerionenforschung (GSI) more than 330 patients have been treated with scanned carbon ion beams in a pilot project. To date, only stationary tumors have been treated. In the presence of motion, scanned ion beam therapy is not yet possible because of interplay effects between scanned beam and target motion which can cause severe mis-dosage. We have started a project to treat tumors that are subject to respiratory motion. A prototype beam application system for target tracking with the scanned pencil beam has been developed and commissioned

Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits

Important knowledge about the determinants of complex human phenotypes can be obtained from the estimation of heritability, the fraction of phenotypic variation in a population that is determined by genetic factors. Here, we make use of extensive phenotype data in Iceland, long-range phased genotypes, and a population-wide genealogical database to examine the heritability of 11 quantitative and 12 dichotomous phenotypes in a sample of 38,167 individuals. Most previous estimates of heritability are derived from family-based approaches such as twin studies, which may be biased upwards by epistatic interactions or shared environment. Our estimates of heritability, based on both closely and distantly related pairs of individuals, are significantly lower than those from previous studies. We examine phenotypic correlations across a range of relationships, from siblings to first cousins, and find that the excess phenotypic correlation in these related individuals is predominantly due to shared environment as opposed to dominance or epistasis. We also develop a new method to jointly estimate narrow-sense heritability and the heritability explained by genotyped SNPs. Unlike existing methods, this approach permits the use of information from both closely and distantly related pairs of individuals, thereby reducing the variance of estimates of heritability explained by genotyped SNPs while preventing upward bias. Our results show that common SNPs explain a larger proportion of the heritability than previously thought, with SNPs present on Illumina 300K genotyping arrays explaining more than half of the heritability for the 23 phenotypes examined in this study. Much of the remaining heritability is likely to be due to rare alleles that are not captured by standard genotyping arrays

Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies

Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low–BMI cases are larger than those estimated from high–BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1×10−9). The improvement varied across diseases with a 16% median increase in χ2 test statistics and a commensurate increase in power. This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci

TIMP-1 and VEGF-165 serum concentration during first-line therapy of ovarian cancer patients

<p>Abstract</p> <p>Background</p> <p>Angiogenesis appears to play an important role in ovarian cancer. Vascular endothelial growth factor (VEGF) has recently been implicated as a therapeutic target in ovarian cancer. The tissue inhibitor of metalloproteinase 1 (TIMP-1) is involved in tissue invasion and angiogenesis. The application of serum TIMP-1 and VEGF to monitor primary therapy and predict clinical outcome of patients with ovarian cancer is unclear.</p> <p>Methods</p> <p>Patients with epithelial ovarian cancer who presented for primary surgery were included in this study. A total of 148 serum samples from 37 patients were analyzed. Samples were prospectively collected at 4 predefined time points: 1. before radical debulking surgery, 2. after surgery and before platinum/taxane based chemotherapy, 3. during chemotherapy, 4. after chemotherapy. Serum VEGF-165 and TIMP-1 as well as CA-125 were quantified by ELISA or ECLIA and correlation with response and long-term clinical outcome was analyzed.</p> <p>Results</p> <p>Serum levels of all markers changed substantially during first-line therapy. High CA-125 (p = 0.002), TIMP-1 (p = 0.007) and VEGF-165 (p = 0.02) after chemotherapy were associated with reduced overall survival. In addition, elevated CA-125 (p < 0.001) and VEGF-165 (p = 0.006) at this time point predicted poor progression-free survival. TIMP-1 and VEGF-165 were closely correlated at all time-points during therapy.</p> <p>Conclusions</p> <p>TIMP-1 and VEGF serum levels changed significantly during first-line therapy of ovarian cancer patients and predicted prognosis. These findings support the role of angiogenesis in ovarian cancer progression and the use of antiangiogenic therapy.</p

Retinotopic Maps, Spatial Tuning, and Locations of Human Visual Areas in Surface Coordinates Characterized with Multifocal and Blocked fMRI Designs

The localization of visual areas in the human cortex is typically based on mapping the retinotopic organization with functional magnetic resonance imaging (fMRI). The most common approach is to encode the response phase for a slowly moving visual stimulus and to present the result on an individual's reconstructed cortical surface. The main aims of this study were to develop complementary general linear model (GLM)-based retinotopic mapping methods and to characterize the inter-individual variability of the visual area positions on the cortical surface. We studied 15 subjects with two methods: a 24-region multifocal checkerboard stimulus and a blocked presentation of object stimuli at different visual field locations. The retinotopic maps were based on weighted averaging of the GLM parameter estimates for the stimulus regions. In addition to localizing visual areas, both methods could be used to localize multiple retinotopic regions-of-interest. The two methods yielded consistent retinotopic maps in the visual areas V1, V2, V3, hV4, and V3AB. In the higher-level areas IPS0, VO1, LO1, LO2, TO1, and TO2, retinotopy could only be mapped with the blocked stimulus presentation. The gradual widening of spatial tuning and an increase in the responses to stimuli in the ipsilateral visual field along the hierarchy of visual areas likely reflected the increase in the average receptive field size. Finally, after registration to Freesurfer's surface-based atlas of the human cerebral cortex, we calculated the mean and variability of the visual area positions in the spherical surface-based coordinate system and generated probability maps of the visual areas on the average cortical surface. The inter-individual variability in the area locations decreased when the midpoints were calculated along the spherical cortical surface compared with volumetric coordinates. These results can facilitate both analysis of individual functional anatomy and comparisons of visual cortex topology across studies

Pitfalls of predicting complex traits from SNPs

The success of genome-wide association studies (GWASs) has led to increasing interest in making predictions of complex trait phenotypes, including disease, from genotype data. Rigorous assessment of the value of predictors is crucial before implementation. Here we discuss some of the limitations and pitfalls of prediction analysis and show how naive implementations can lead to severe bias and misinterpretation of results