Genetics provides a potentially powerful approach to dissect host-gut microbiota interactions. Toward this end, we profiled gut microbiota using 16s rRNA gene sequencing in a panel of 110 diverse inbred strains of mice. This panel has previously been studied for a wide range of metabolic traits and can be used for high-resolution association mapping. Using a SNPbased approach with a linear mixed model, we estimated the heritability of microbiota composition. We conclude that, in a controlled environment, the genetic background accounts for a substantial fraction of abundance of most common microbiota. The mice were previously studied for response to a high-fat, high-sucrose diet, and we hypothesized that the dietary response was determined in part by gut microbiota composition. We tested this using a cross-fostering strategy in which a strain showing a modest response, SWR, was seeded with microbiota from a strain showing a strong response, A×B19. Consistent with a role of microbiota in dietary response, the cross-fostered SWR pups exhibited a significantly increased response in weight gain. To examine specific microbiota contributing to the response, we identified various genera whose abundance correlated with dietary response. Among these, we chose Akkermansia muciniphila, a common anaerobe previously associated with metabolic effects. When administered to strain A×B19 by gavage, the dietary response was significantly blunted for obesity, plasma lipids, and insulin resistance. In an effort to further understand host-microbiota interactions, we mapped loci controlling microbiota composition and prioritized candidate genes. Our publicly available data provide a resource for future studies.

Aims While most patients with myocardial infarction (MI) have underlying coronary atherosclerosis, not all patients with coronary artery disease (CAD) develop MI. We sought to address the hypothesis that some of the genetic factors which establish atherosclerosis may be distinct from those that predispose to vulnerable plaques and thrombus formation. Methods and results We carried out a genome-wide association study for MI in the UK Biobank (n∼472 000), followed by a meta-analysis with summary statistics from the CARDIoGRAMplusC4D Consortium (n∼167 000). Multiple independent replication analyses and functional approaches were used to prioritize loci and evaluate positional candidate genes. Eight novel regions were identified for MI at the genome wide significance level, of which effect sizes at six loci were more robust for MI than for CAD without the presence of MI. Confirmatory evidence for association of a locus on chromosome 1p21.3 harbouring choline-like transporter 3 (SLC44A3) with MI in the context of CAD, but not with coronary atherosclerosis itself, was obtained in Biobank Japan (n∼165 000) and 16 independent angiography-based cohorts (n∼27 000). Follow-up analyses did not reveal association of the SLC44A3 locus with CAD risk factors, biomarkers of coagulation, other thrombotic diseases, or plasma levels of a broad array of metabolites, including choline, trimethylamine N-oxide, and betaine. However, aortic expression of SLC44A3 was increased in carriers of the MI risk allele at chromosome 1p21.3, increased in ischaemic (vs. non-diseased) coronary arteries, up-regulated in human aortic endothelial cells treated with interleukin-1β (vs. vehicle), and associated with smooth muscle cell migration in vitro. Conclusions A large-scale analysis comprising ∼831 000 subjects revealed novel genetic determinants of MI and implicated SLC44A3 in the pathophysiology of vulnerable plaques.

Hospital readmissions are a major contributor to increased health care costs and are associated with worse patient outcomes after neurosurgery. We used the newly released Nationwide Readmissions Database (NRD) to describe the association between patient, hospital and payer factors with 30- and 90-day readmission following craniotomy for malignant brain tumor. All adult inpatients undergoing craniotomy for primary and secondary malignant brain tumors in the NRD from 2013 to 2014 were included. We identified all cause readmissions within 30- and 90-days following craniotomy for tumor, excluding scheduled chemotherapeutic procedures. We used univariate and multivariate models to identify patient, hospital and administrative factors associated with readmission. We identified 27,717 admissions for brain tumor craniotomy in 2013-2014, with 3343 (13.2%) 30-day and 5271 (25.7%) 90-day readmissions. In multivariate analysis, patients with Medicaid and Medicare were more likely to be readmitted at 30- and 90-days compared to privately insured patients. Patients with two or more comorbidities were more likely to be readmitted at 30- and 90-days, and patients discharged to skilled nursing facilities or home health care were associated with increased 90-day readmission rates. Finally, hospital procedural volume above the 75th percentile was associated with decreased 90-day readmission rates. Patients treated at high volume hospitals are less likely to be readmitted at 90-days. Insurance type, non-routine discharge and patient comorbidities are predictors of postoperative non-scheduled readmission. Further studies may elucidate potentially modifiable risk factors when attempting to improve outcomes and reduce cost associated with brain tumor surgery.

Purpose of review We provide an overview of our current understanding of the genetic architecture of coronary artery disease (CAD)and discuss areas of research that provide excellent opportunities for further exploration. Recent findings Large-scale studies in human populations, coupled with rapid advances in genetic technologies over the last decade, have clearly established the association of common genetic variation with risk of CAD. However, the effect sizes of the susceptibility alleles are for the most part modest and collectively explain only a small fraction of the overall heritability. By comparison, evidence that rare variants make a substantial contribution to risk of CAD has been somewhat disappointing thus far, suggesting that other biological mechanisms have yet to be discovered. Emerging data suggests that novel pathways involved in the development of CAD can be identified through complementary and integrative systems genetics strategies in mice or humans. There is also convincing evidence that gut bacteria play a previously unrecognized role in the development of CAD, particularly through metabolism of certain dietary nutrients that lead to proatherogenic metabolites in the circulation. Summary A major effort is now underway to functionally understand the newly discovered genetic and biological associations for CAD, which could lead to the development of potentially novel therapeutic strategies. Other important areas of investigation for understanding the pathophysiology of CAD, including epistatic interactions between genes or with either sex and environmental factors, have not been studied on a broad scope and represent additional opportunities for future studies.