IMPORTANCE Mendelian randomization (MR) studies use genetic variation associated with modifiable exposures to assess their possible causal relationship with outcomes and aim to reduce potential bias from confounding and reverse causation. OBJECTIVE To develop the STROBE-MR Statement as a stand-alone extension to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guideline for the reporting of MR studies. DESIGN, SETTING, AND PARTICIPANTS The development of the STROBE-MR Statement followed the Enhancing the Quality and Transparency of Health Research (EQUATOR) framework guidance and used the STROBE Statement as a starting point to draft a checklist tailored to MR studies. The project was initiated in 2018 by reviewing the literature on the reporting of instrumental variable and MR studies. A group of 17 experts, including MR methodologists, MR study design users, developers of previous reporting guidelines, and journal editors, participated in a workshop in May 2019 to define the scope of the Statement and draft the checklist. The draft checklist was published as a preprint in July 2019 and discussed on the preprint platform, in social media, and at the 4th Mendelian Randomization Conference. The checklist was then revised based on comments, further refined through 2020, and finalized in July 2021.

In observational epidemiology, mendelian randomisation (MR) studies provide an opportunity to study the causal association between an exposure and an outcome while reducing the risk of certain biases Little consensus exists around the reporting of MR studies, and the quality of reporting of these studies has been inconsistent; many MR study reports do not state or examine the various assumptions of MR and report insufficient details on the data sources STROBE-MR (strengthening the reporting of observational studies in epidemiology using mendelian randomisation), a checklist of 20 reporting items, has been developed for the communication of MR studies This article explains the rationale of these checklist items and provides examples of transparent reporting MR study authors, reviewers, and journal editors are encouraged to use STROBE-MR to improve the reporting of these studies on 3 November 2021 by guest. Protected by copyright.

The ability to identify bacterial pathogens at the subspecies level in clinical diagnostics is currently limited. We investigated whether splitting Escherichia coli species into clonal groups (clonotypes) predicts antimicrobial susceptibility or clinical outcome. A total of 1,679 extraintestinal E. coli isolates (collected from 2010 to 2012) were collected from one German and 5 U.S. clinical microbiology laboratories. Clonotype identity was determined by fumC and fimH (CH) sequencing. The associations of clonotype with antimicrobial susceptibility and clinical variables were evaluated. CH typing divided the isolates into >200 CH clonotypes, with 93% of the isolates belonging to clonotypes with >2 isolates. Antimicrobial susceptibility varied substantially among clonotypes but was consistent across different locations. Clonotype-guided antimicrobial selection significantly reduced "drug-bug" mismatch compared to that which occurs with the use of conventional empirical therapy. With trimethoprim-sulfamethoxazole and fluoroquinolones, the drug-bug mismatch was predicted to decrease 62% and 78%, respectively. Recurrent or persistent urinary tract infection and clinical sepsis were significantly correlated with specific clonotypes, especially with CH40-30 (also known as H30), a recently described clonotype within sequence type 131 (ST131). We were able to clonotype directly from patient urine samples within 1 to 3 h of obtaining the specimen. In E. coli, subspecies-level identification by clonotyping can be used to significantly improve empirical predictions of antimicrobial susceptibility and clinical outcomes in a timely manner. Bacterial species identification is essential for the correct diagnosis of disease and to optimize the empirical choice of antimicrobial treatment before the results of culturing and susceptibility testing are available (up to 2 to 3 days) (1, 2). However, even within a single bacterial species, there is substantial strain-tostrain variation in antimicrobial susceptibilities and virulence (3), and the increasing prevalence of antimicrobial-resistant and multidrug-resistant bacterial pathogens is one of the greatest challenges in clinical medicine today (4, 5). Thus, subspecies-, strain-, or clonal group-level identification might provide significant advantages for the diagnosis of bacterial infections.Escherichia coli is a leading extraintestinal (found especially in the urine and blood) pathogen in the United States, causing millions of infections and tens of thousands of deaths each year (6). As a clonal species, E. coli contains a limited number of genetically related lineages (i.e., clonotypes) (10). Although several E. coli clonotypes with distinctive antimicrobial susceptibility patterns have been described (11)(12)(13)(14)(15), the use of clonotyping as a general predictive marker for antimicrobial susceptibility among unselected extraintestinal clinical E. coli isolates has not been reported. Additionally, the two most-commonly used clonal typing methods for E. coli, multilocus sequ...