Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Effect of Student Involvement on Patient Perceptions of Ambulatory Care Visits: A Randomized Controlled Trial

OBJECTIVE: To determine if patient satisfaction with ambulatory care visits differs when medical students participate in the visit. DESIGN: Randomized controlled trial. SETTING: Academic general internal medicine practice. PARTICIPANTS: Outpatients randomly assigned to see an attending physician only (N = 66) or an attending physician plus medical student (N = 68). MEASUREMENTS AND MAIN RESULTS: Patient perceptions of the office visit were determined by telephone survey. Overall office visit satisfaction was higher for the “attending physician only” group (61% vs 48% excellent), although this was not statistically significant (P = .16). There was no difference between the study groups for patient ratings of their physician overall (80% vs 85% excellent; P = .44). In subsidiary analyses, patients who rated their attending physician as “excellent” rated the overall office visit significantly higher in the “attending physician only” group (74% vs 55%; P = .04). Among patients in the “attending physician plus medical student” group, 40% indicated that medical student involvement “probably” or “definitely” did not improve their care, and 30% responded that they “probably” or “definitely” did not want to see a student at subsequent office visits. CONCLUSIONS: Although our sample size was small, we found no significant decrement in patient ratings of office visit satisfaction from medical student involvement in a global satisfaction survey. However, a significant number of patients expressed discontent with student involvement in the visit when asked directly. Global assessment of patient satisfaction may lack sensitivity for detection of dissatisfaction. Future research in this area should employ more sensitive measures of patient satisfaction