Molecular Characterization and Antimicrobial Susceptibility of Nasal Staphylococcus aureus Isolates from a Chinese Medical College Campus

Staphylococcus aureus colonization and infection occur more commonly among persons living or working in crowded conditions, but characterization of S. aureus colonization within medical communities in China is lacking. A total of 144 (15.4%, 144/935) S. aureus isolates, including 28 (3.0%, 28/935) MRSA isolates, were recovered from the nares of 935 healthy human volunteers residing on a Chinese medical college campus. All S. aureus isolates were susceptible to vancomycin, quinupristin/dalfopristin and linezolid but the majority were resistant to penicillin (96.5%), ampicillin/sulbactam (83.3%) and trimethoprim/sulfamethoxazole (93.1%). 82%, (23/28) of the MRSA isolates and 66% (77/116) of the MSSA isolates were resistant to multiple antibiotics, and 3 MRSA isolates were resistant to mupirocin—an agent commonly used for nasal decolonization. 16 different sequence types (STs), as well as SCCmec genes II, III, IVd, and V, were represented among MRSA isolates. We also identified, for the first time, two novel STs (ST1778 and ST1779) and 5 novel spa types for MRSA. MRSA isolates were distributed in different sporadic clones, and ST59-MRSA-VId- t437 was found within 3 MRSA isolates. Moreover, one isolate with multidrug resistance belonging to ST398-MRSA-V- t571 associated with animal infections was identified, and 3 isolates distributed in three different clones harbored PVL genes. Collectively, these data indicate a high prevalence of nasal MRSA carriage and molecular heterogeneity of S. aureus isolates among persons residing on a Chinese medical college campus. Identification of epidemic MRSA clones associated with community infection supports the need for more effective infection control measures to reduce nasal carriage and prevent dissemination of MRSA to hospitalized patients and health care workers in this community

Introduction to “A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals: 2014 Updates”

Abstract Since the publication of "A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals" in 2008, prevention of healthcare-associated infections (HAIs) has become a national priority. Despite improvements, preventable HAIs continue to occur. The 2014 updates to the Compendium were created to provide acute care hospitals with up-to-date, practical, expert guidance to assist in prioritizing and implementing their HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Diseases Society of America (IDSA), the American Hospital Association (AHA), the Association for Professionals in Infection Control and Epidemiology (APIC), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Institute for Healthcare Improvement (IHI), the Pediatric Infectious Diseases Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), and the Surgical Infection Society (SIS)

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p