Jason Karnes

Early Career Tenure-track Researcher, University of Arizona

2 active projects

Race/Ethnicity PheWAS

Our primary objective is to establish disparities in disease diagnosis by race and ethnicity and to characterize how patient-reported sociocultural factors such as educational level and family income contribute to these disparities. Our study will investigate diagnosis of human disease…

Scientific Questions Being Studied

Our primary objective is to establish disparities in disease diagnosis by race and ethnicity and to characterize how patient-reported sociocultural factors such as educational level and family income contribute to these disparities. Our study will investigate diagnosis of human disease comprehensively across multiple disease systems to systematically identify such disparities. The amazing breadth and impressive diversity of the All of Us dataset combined with patient-provided information enables an investigation of racial/ethnic disparities in disease diagnosis in the context of how patient-reported sociocultural factors contribute to these disparities. This project is relevant to public health in that it will combat misinterpretation and oversimplification regarding the causes of associations with race/ethnicity.

Project Purpose(s)

  • Population Health

Scientific Approaches

We plan to employ the phenome-wide association study approach (PheWAS) to determine the association of race/ethnicity across a broad array of human disease. The PheWAS catalogue will be used to generate disease classification among All of Us participants and self-reported race and ethnicity, will be considered the primary independent variable. Participant-provided survey information, including responses related to educational attainment, socio-economic status, and healthcare access, will be examined for direct effects on disease diagnosis and used as covariates in PheWAS analyses to determine how patient-reported sociocultural factors contribute to observed disparities independent of race/ethnicity.

Anticipated Findings

We expect that considering sociocultural factors will provide evidence of racial disparities in disease diagnosis that are not related to biology but to factors such as educational attainment, socioeconomic status, and limited access to specialty care. We expect that the focus of our study will be how racial/ethnic disparities in disease prevalence change overall rather than providing a detailed analysis or explanation of individual disease associations. This broader approach will prevent stigmatizing observations as well as overemphasis and misinterpretation of specific associations. We expect to stress how these sociocultural factors are driving forces for racial/ethnic differences in disease diagnosis. We expect that ultimately this analysis will combat common misinterpretations and oversimplifications regarding the causes of disease associations with race/ethnicity.

Demographic Categories of Interest

  • Race / Ethnicity
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

RacialEthnicDifferences_AnthropoLipidALT

Obesity is one of the most important risks for many diseases in the United States and across the world. Differences in body weight and shape across gender and race/ethnicity have been extensively described. We sought to replicate these differences and…

Scientific Questions Being Studied

Obesity is one of the most important risks for many diseases in the United States and across the world. Differences in body weight and shape across gender and race/ethnicity have been extensively described. We sought to replicate these differences and evaluate newly emerging data from the All of Us Research Program (AoU). In this project, we ask the scientific question: How do individuals from different genders and different racial/ethnic groups in the All Of Us dataset differ with respect to weight, waist and hip circumferences, cholesterol levels and levels of alanine aminotransferase?

Project Purpose(s)

  • Disease Focused Research (Obesity)
  • Other Purpose (This work is the result of an All of Us Research Program Demonstration Project. Demonstration Projects are efforts by the All of Us Research Program designed to meet the goal of ensuring the quality and utility of the Research Hub as a resource for accelerating precision medicine. This work has been approved, reviewed, and overseen by the All of Us Research Program Science Committee and Data and Research Center to ensure compliance with program policy.)

Scientific Approaches

Within each ethnic/racial group and each gender group, we first visually examine histograms of each outcome variable to determine the presence of any major outliers that may represent measurement errors. Then we tabulated the mean values and other descriptive statistics for continuous variables such as waist and hip circumferences. We also determined the proportion of individuals with abdominal obesity. To formally test for differences among groups and to adjust for age and other covariates, we will use linear regression, transforming variables to conform to assumptions of linear regression. Data for race and ethnicity was obtained from participants in participant-provided information (PPI). Biological sex at birth, height, weight, waist circumference (WC), and hip circumference measurements were obtained according to AoU baseline visit protocols. Levels of alanine aminotransferase (ALT) were obtained from the EHR records of participants.

Anticipated Findings

For this study, we anticipate that we will be able to replicate known differences in body weight and shape across gender and race/ethnicity. We anticipate that we will find racial/ethnic and gender disparities related to ALT, a surrogate marker of hepatic steatosis. We anticipate the ability to evaluate the consistency of the All of Us cohort with national averages related to obesity and indicate that this resource is likely to be a major source of scientific inquiry and discovery. This project will serve to demonstrate the quality, utility, and diversity of the All of Us data and tools and the power of gathering multiple data sources for a single set of phenotypes, providing researchers options for study design and validation.

Demographic Categories of Interest

  • Race / Ethnicity
  • Sex at Birth

Research Team

Owner:

Collaborators:

  • Jianglin Feng - Other, University of Arizona
  • Lina Sulieman - Other, All of Us Program Operational Use
  • Heidi Steiner - Graduate Trainee, University of Arizona
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