Migraine is a chronic and agonizing neurological disorder prevalent worldwide. Although its pathogenesis remains unclear, limited evidence exists on the role of air pollution. We aimed to assess the association of short-term air pollution exposure with migraine in conjunction with the synergistic effect of temperature. We identified 18,921 patients who visited emergency departments (EDs) for migraine as a primary disease in Seoul from the national emergency database between 2008 and 2014. We conducted a time-stratified, case-crossover analysis to compare levels of particles <2.5 μm (PM2.5), particles <10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) on ED visit days and those on the control days matched to day of the week, month, and year. We evaluated the synergistic effects of air pollution and temperature using an interaction term. Higher air pollution levels were significantly associated with risk of migraine over various lag structures. In the best fitting lags, the odds ratio (OR) associated with an interquartile range increase of PM2.5, PM10, NO2, O3, and CO was 1.031 (95% CI: 1.010-1.053), 1.032 (95% CI: 1.007-1.057), 1.053 (95% CI: 1.022-1.085), 1.034 (95% CI: 1.001-1.067), and 1.029 (95% CI: 1.005-1.053), respectively. The SO2 effect was positive but not significant (OR 1.019 [95% CI: 0.991-1.047]). The PM effect was significantly stronger on high-temperature days (above the 75th percentile) than on low-temperature days (PM2.5, high: OR 1.068, low: OR 1.021, Pinteract = 0.03; PM10, high: OR 1.066, low: OR 1.014, Pinteract = 0.02). Our study provides new evidence that air pollution exposure may trigger migraine especially on high-temperature days, and this finding may contribute in establishing preventive measures against migraine.

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.

Metabolic syndrome (MetS) is a complex hereditary condition comprising various metabolic traits as risk factors. Although the genetics of individual MetS components have been investigated actively through large-scale genome-wide association studies, the conjoint genetic architecture has not been fully elucidated. Here, we performed the largest multivariate genome-wide association study of MetS in Europe (n_observed = 4,947,860) by leveraging genetic correlation between MetS components. We identified 1,307 genetic loci associated with MetS that were enriched primarily in brain tissues. Using transcriptomic data, we identified 11 genes associated strongly with MetS. Our phenome-wide association and Mendelian randomization analyses highlighted associations of MetS with diverse diseases beyond cardiometabolic diseases. Polygenic risk score analysis demonstrated better discrimination of MetS and predictive power in European and East Asian populations. Altogether, our findings will guide future studies aimed at elucidating the genetic architecture of MetS.

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci. The genetic architecture of serum urate control is similar between European and East Asian populations. A transcriptome-wide association study, enrichment analysis, and colocalization analysis in relevant tissues identify candidate serum urate-associated genes, including CTBP1, SKIV2L, and WWP2. A phenome-wide association study using polygenic risk scores identifies serum urate-correlated diseases including heart failure and hypertension. Mendelian randomization and mediation analyses show that serum urate-associated genes might have a causal relationship with serum urate-correlated diseases via mediation effects. This study elucidates our understanding of the genetic architecture of serum urate control.