Reclassification of aortic stenosis by fusion of echocardiography and computed tomography in low-gradient aortic stenosis

Background The integration of computed tomography (CT)-derived left ventricular outflow tract area into the echocardiography-derived continuity equation results in the reclassification of a significant proportion of patients with severe aortic stenosis (AS) into moderate AS based on aortic valve area indexed to body surface area determined by fusion imaging (fusion AVA(i)). The aim of this study was to evaluate AS severity by a fusion imaging technique in patients with low-gradient AS and to compare the clinical impact of reclassified moderate AS versus severe AS. Methods We included 359 consecutive patients who underwent transcatheter aortic valve implantation for low-gradient, severe AS at two academic institutions and created a joint database. The primary endpoint was a composite of all-cause mortality and rehospitalisations for heart failure at 1 year. Results Overall, 35% of the population (n= 126) were reclassified to moderate AS [median fusion AVAi 0.70 (interquartile range, IQR 0.65-0.80)cm(2)/m(2)] and severe AS was retained as the classification in 65% [median fusion AVAi 0.49 (IQR 0.43-0.54) cm(2)/m(2)]. Lower body mass index, higher logistic EuroSCORE and larger aortic dimensions characterised patients reclassified to moderate AS. Overall, 57% of patients had a left ventricular ejection fraction (LVEF) = 50% (log-rankp= 0.029). Conclusions The integration of CT and transthoracic echocardiography to obtain fusion AVAi led to the reclassification of one third of patients with low-gradient AS to moderate AS. Reclassification did not affect clinical outcome, although patients reclassified to moderate AS with a LVEF <50% had worse outcomes owing to excess non-cardiac mortality.Cardiolog

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc