Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors – consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.

BACKGROUND: To identify potential genetic markers for severe oxaliplatin-induced chronic peripheral neuropathy (OXCPN), the authors performed a genome-wide association analysis of patients with colon cancer who received oxaliplatin-based chemotherapy. METHODS: This was a prospective study in which DNA was purified in peripheral blood from patients with colon cancer who received oxaliplatin. The primary endpoint was the development of severe (grade 2 lasting for >7 days or grade 3) OXCPN. For the discovery set, genotyping was done for 96 patients who received adjuvant fluorouracil and oxaliplatin using the a genome-wide human single-nucleotide polymorphism (SNP) array. An association between polymorphisms and severe OXCPN was investigated. At the same time, 247 patients who received oxaliplatin-based, first-line chemotherapy for advanced disease were enrolled as a validation set. RESULTS: Among the 32 genotyped candidate SNPs selected from the discovery set, 9 SNPs in 8 genes ( The most significant association was observed at reference SNP number (rs)10486003 in TAC1 (P ¼ 4.84 Â 10 À7 ) in combined data from 2 sets. Five SNPs (rs10486003, rs2338, rs830884, rs843748, and rs797519) were significant in a multiple regression analysis (P < .05). Overall prediction accuracy calculated by the regression model was 72.8% (95% confidence interval, 65.8%-79.9%) in the model development and 75.9% (95% confidence interval, 66.9%-84.9%) in the model evaluation. CONCLUSIONS: The current results indicated that a genome-wide pharmacogenomic approach is useful for identifying novel polymorphism predictors of severe OXCPN that may be used in personalized chemotherapy.