Prediction models of atrial fibrillation (AF) have been developed; however, there was no AF prediction model validated in Chinese population. Therefore, we aimed to investigate the incidence of AF in urban Han Chinese health check-up population, as well as to develop AF prediction models using behavioral, anthropometric, biochemical, electrocardiogram (ECG) markers, as well as visit-to-visit variability (VVV) in blood pressures available in the routine health check-up. A total of 33 186 participants aged 45-85 years and free of AF at baseline were included in this cohort, to follow up for incident AF with an annually routine health check-up. Cox regression models were used to develop AF prediction model and 10-fold cross-validation was used to test the discriminatory accuracy of prediction model. We developed three prediction models, with age, sex, history of coronary heart disease (CHD), hypertension as predictors for simple model, with left high-amplitude waves, premature beats added for ECG model, and with age, sex, history of CHD and VVV in systolic and diabolic blood pressures as predictors for VVV model, to estimate risk of incident AF. The calibration of our models ranged from 1.001 to 1.004 (P for Hosmer Lemeshow test >0.05). The area under receiver operator characteristics curve were 78%, 80% and 82%, respectively, for predicting risk of AF. In conclusion, we have identified predictors of incident AF and developed prediction models for AF with variables readily available in routine health check-up.

To date, the pathogenesis of Ménière's disease (MD) remains unclear. This study aims to investigate the possible relationship between potential immune system-related genes and sporadic MD. The whole RNA-sequencing (RNA-seq) technology was used to analyse the transcriptome of peripheral blood mononuclear cells of three MD patients and three control individuals. Of 366 differentially expressed genes (DEGs), 154 genes were up-regulated and 212 genes were down-regulated (|log fold change| > 1 and P < 0·05). Gene ontology (GO) enrichment analysis illustrated that immune relevant factors played a key role in the pathogenesis of MD. Of 366 DEGs, we focused upon analysing the possible immune-related genes, among which the significantly up-regulated genes [glutathione S-transferase mu 1 (GSTM1), transmembrane protein 176 (TMEM176)B, TMEM176A] and down-regulated genes [solute carrier family 4 member (SLC4A)10 and SLC4A1] especially drew our attention. The mRNA expression levels of GSTM1, TMEM176B, TMEM176A, SLC4A1 and SLC4A10 were analysed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The serum concentration of GSTM1, TMEM176B and SLC4A10 proteins were measured by enzyme-linked immunosorbent assay (ELISA). Considering the results of qRT-PCR and ELISA, it was noteworthy that GSTM1 exhibited the highest fold change between two groups, which was consistent with the deep sequencing results by RNA-seq. In conclusion, our study first offers a new perspective in MD development on the basis of RNA expression patterns, suggesting that immune factors might be involved in the MD pathogenesis. Remarkably, GSTM1 might be a possible candidate gene for the diagnostic biomarker of MD and provides the basis for further biological and functional investigations.

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