Anti-racist strategies for clinical and translational research: Design, implementation, and lessons learned from a new course.

Translational research should examine racism and bias and improve health equity. We designed and implemented a course for the Master of Science in Clinical Investigation program of the Northwestern University Clinical and Translational Sciences Institute. We describe curriculum development, content, outcomes, and revisions involving 36 students in 2 years of "Anti-Racist Strategies for Clinical and Translational Science." Ninety-six percent of students reported they would recommend the course. Many reported changes in research approaches based on course content. A course designed to teach anti-racist research design is feasible and has a positive short-term impact on learners.

Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics.

OBJECTIVE: High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach. METHODS: This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank. RESULTS: Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux. CONCLUSIONS: This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

Multiplexing mutation rate assessment: determining pathogenicity of Msh2 variants in Saccharomyces cerevisiae.

Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time-consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway. Loss-of-function mutations in MSH2 are associated with hereditary nonpolyposis colorectal cancer, an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria-Delbrück fluctuation tests using a collection of published MSH2 missense variants. Our pooled screen successfully identified previously characterized nonfunctional alleles as high mutators. We then created an additional 185 human missense variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVar's classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the frequency of antibiotic resistance emergence.