About

Sophia Johnson is the Humphrey School’s Creative Multimedia Manager and leads the School’s digital accessibility initiatives. She manages the School’s social media accounts, creates print and digital marketing materials, and helps keep the website up to date. Sophia holds a bachelor’s degree in graphic design from the College of Design at the University of Minnesota.

Research topics

• Medicine
• Computer Science
• Political Science
• Medical education
• Gerontology
• Knowledge management
• Virology
• Genetics
• Pharmacology
• Business
• Biology
• Internal medicine

Selected publications

• NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health

  Nature Aging · 2022 · 122 citations

  • Gerontology
  • Biology
  • Medicine
  PublisherOA PDFDOI

• Pharmacogenomics Education, Research and Clinical Implementation in the State of Minnesota

  Pharmacogenomics · 2021 · 21 citations

  • Computer Science
  • Political Science
  • Medical education

  Several healthcare organizations across Minnesota have developed formal pharmacogenomic (PGx) clinical programs to increase drug safety and effectiveness. Healthcare professional and student education is strong and there are multiple opportunities in the state for learners to gain workforce skills and develop advanced competency in PGx. Implementation planning is occurring at several organizations and others have incorporated structured utilization of PGx into routine workflows. Laboratory-based and translational PGx research in Minnesota has driven important discoveries in several therapeutic areas. This article reviews the state of PGx activities in Minnesota including educational programs, research, national consortia involvement, technology, clinical implementation and utilization and reimbursement, and outlines the challenges and opportunities in equitable implementation of these advances.

  DOI

• Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative

  JAMA Network Open · 2021 · 246 citations

  • Medicine
  • Virology
  • Internal medicine

  Importance: The National COVID Cohort Collaborative (N3C) is a centralized, harmonized, high-granularity electronic health record repository that is the largest, most representative COVID-19 cohort to date. This multicenter data set can support robust evidence-based development of predictive and diagnostic tools and inform clinical care and policy. Objectives: To evaluate COVID-19 severity and risk factors over time and assess the use of machine learning to predict clinical severity. Design, Setting, and Participants: In a retrospective cohort study of 1 926 526 US adults with SARS-CoV-2 infection (polymerase chain reaction >99% or antigen <1%) and adult patients without SARS-CoV-2 infection who served as controls from 34 medical centers nationwide between January 1, 2020, and December 7, 2020, patients were stratified using a World Health Organization COVID-19 severity scale and demographic characteristics. Differences between groups over time were evaluated using multivariable logistic regression. Random forest and XGBoost models were used to predict severe clinical course (death, discharge to hospice, invasive ventilatory support, or extracorporeal membrane oxygenation). Main Outcomes and Measures: Patient demographic characteristics and COVID-19 severity using the World Health Organization COVID-19 severity scale and differences between groups over time using multivariable logistic regression. Results: The cohort included 174 568 adults who tested positive for SARS-CoV-2 (mean [SD] age, 44.4 [18.6] years; 53.2% female) and 1 133 848 adult controls who tested negative for SARS-CoV-2 (mean [SD] age, 49.5 [19.2] years; 57.1% female). Of the 174 568 adults with SARS-CoV-2, 32 472 (18.6%) were hospitalized, and 6565 (20.2%) of those had a severe clinical course (invasive ventilatory support, extracorporeal membrane oxygenation, death, or discharge to hospice). Of the hospitalized patients, mortality was 11.6% overall and decreased from 16.4% in March to April 2020 to 8.6% in September to October 2020 (P = .002 for monthly trend). Using 64 inputs available on the first hospital day, this study predicted a severe clinical course using random forest and XGBoost models (area under the receiver operating curve = 0.87 for both) that were stable over time. The factor most strongly associated with clinical severity was pH; this result was consistent across machine learning methods. In a separate multivariable logistic regression model built for inference, age (odds ratio [OR], 1.03 per year; 95% CI, 1.03-1.04), male sex (OR, 1.60; 95% CI, 1.51-1.69), liver disease (OR, 1.20; 95% CI, 1.08-1.34), dementia (OR, 1.26; 95% CI, 1.13-1.41), African American (OR, 1.12; 95% CI, 1.05-1.20) and Asian (OR, 1.33; 95% CI, 1.12-1.57) race, and obesity (OR, 1.36; 95% CI, 1.27-1.46) were independently associated with higher clinical severity. Conclusions and Relevance: This cohort study found that COVID-19 mortality decreased over time during 2020 and that patient demographic characteristics and comorbidities were associated with higher clinical severity. The machine learning models accurately predicted ultimate clinical severity using commonly collected clinical data from the first 24 hours of a hospital admission.

  PublisherOA PDFDOI

Recent grants

• RUI: Experimental Investigation of Ecological and Genetic Correlates of Parthenogenetic and Reproduction in a Fresh Water Snail

  NSF · $108k · 1996–2000

• Tests of Competing Hypotheses for the Maintenance of Sex and Parthenogenesis in Campeloma limum, a SE United States Snail

  NSF · $153k · 2000–2006

• University of Minnesota Clinical and TranslationalmScience Institute (UMN CTSI)

  NIH · $34.9M · 2018–2023

Frequent coauthors

• Bonnie L. Westra

  University of Minnesota

  66 shared

• Kay S. Lytle

  Mayo Clinic in Florida

  40 shared

• LuAnn Whittenburg

  University of Minnesota

  40 shared

• Michelle Leverette

  University of Minnesota

  36 shared

• Elizabeth E. Umberfield

  Mayo Clinic in Florida

  36 shared

• I. A. Tokareva

  Association of Perioperative Registered Nurses

  36 shared

• Luke Jobman

  Mayo Clinic in Florida

  36 shared

• Rachel Buchleiter

  Center For Policy Research

  36 shared

Education

• PhD, Institute for Health Informatics

  University of Minnesota

  2016

Awards & honors

• Humphrey-Johnson Book Prize

Similar researchers at University of Minnesota

• David Jacobsh-223
• Eamonn Maherh-172
• Robert Kruegerh-132
• Paul Robbinsh-126
• Matt McGueh-125