Yann Klimentidis

Mid-career Tenured Researcher, University of Arizona

5 active projects

Phenome-wide associations of metabolic disorder measurements_v4

THe aims of this project are to identify known and novel disease associations with cardiometabolic traits, utilizing the All of Us (AoU) dataset. Evaluate if known racial/ethnic, education, and socioeconomic differences in cardiometabolic disorder can be replicated utilizing the AoU…

Scientific Questions Being Studied

THe aims of this project are to identify known and novel disease associations with cardiometabolic traits, utilizing the All of Us (AoU) dataset. Evaluate if known racial/ethnic, education, and socioeconomic differences in cardiometabolic disorder can be replicated utilizing the AoU dataset. We hope to expand the scope to include all relevant measures related to cardiometabolic disorders and assess the possibility for selection bias and issues of generalizability in cohort participant selection. There are well established disparities in rates of metabolic disorders related to race/ethnicity, gender, and socioeconomic status. There is also a general lack of diversity and the potential for healthy-patient bias in large epidemiological datasets. For these reasons we seek to use All of Us data to forerun projects that are more inclusive and facilitate a change in traditionally underrepresented research.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

Utilizing the CDC National Health and Nutrition Examination Survey(NHANES), a nationally representative sample, we will compare prevalence rates and racial/ethnic and gender group distributions of key metabolic disorder parameters. To quantitatively investigate the generalizability of the AoU data we will assess differences in the demographic and healthy-lifestyle characteristics between the AofU data and the NHANES data. We will use linear, logistic, and Poisson regression where appropriate to compare differences between groups.

Anticipated Findings

This project will serve as a springboard for future collaborations and grant applications utilizing AoU data and will generate information that will help future researchers better understand both the internal and external validity of the AofU dataset. We will build a foundation for understanding both the internal and external validity of this novel data source having this formative work influence the scientific communities’ understanding of the All of Us data source. We anticipate that this work will be highly cited and useful for future generations of researchers.

Demographic Categories of Interest

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

Research Team

Owner:

Collaborators:

  • Victoria Bland - Graduate Trainee, University of Arizona

Training_v4

I would like to use this workspace purely for educational purposes only. It will be used to demonstrate to students various data analysis approaches using large datasets and to familiarize them with All of Us cloud storage workflow.

Scientific Questions Being Studied

I would like to use this workspace purely for educational purposes only. It will be used to demonstrate to students various data analysis approaches using large datasets and to familiarize them with All of Us cloud storage workflow.

Project Purpose(s)

  • Educational

Scientific Approaches

To produce aggregate summary statistics and regression models for various measurement variables available in All of Us data.

Anticipated Findings

This exploratory analysis will enable us to explore heterogeneity in anthropometric measures among various racial-ethnic groups

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Heidi Steiner - Graduate Trainee, University of Arizona

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

Phenome-wide associations of metabolic disorder measurements_v3

THe aims of this project are to identify known and novel disease associations with cardiometabolic traits, utilizing the All of Us (AoU) dataset. Evaluate if known racial/ethnic, education, and socioeconomic differences in cardiometabolic disorder can be replicated utilizing the AoU…

Scientific Questions Being Studied

THe aims of this project are to identify known and novel disease associations with cardiometabolic traits, utilizing the All of Us (AoU) dataset. Evaluate if known racial/ethnic, education, and socioeconomic differences in cardiometabolic disorder can be replicated utilizing the AoU dataset. We hope to expand the scope to include all relevant measures related to cardiometabolic disorders and assess the possibility for selection bias and issues of generalizability in cohort participant selection. There are well established disparities in rates of metabolic disorders related to race/ethnicity, gender, and socioeconomic status. There is also a general lack of diversity and the potential for healthy-patient bias in large epidemiological datasets. For these reasons we seek to use All of Us data to forerun projects that are more inclusive and facilitate a change in traditionally underrepresented research.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

Utilizing the CDC National Health and Nutrition Examination Survey(NHANES), a nationally representative sample, we will compare prevalence rates and racial/ethnic and gender group distributions of key metabolic disorder parameters. To quantitatively investigate the generalizability of the AoU data we will assess differences in the demographic and healthy-lifestyle characteristics between the AofU data and the NHANES data. We will use linear, logistic, and Poisson regression where appropriate to compare differences between groups.

Anticipated Findings

This project will serve as a springboard for future collaborations and grant applications utilizing AoU data and will generate information that will help future researchers better understand both the internal and external validity of the AofU dataset. We will build a foundation for understanding both the internal and external validity of this novel data source having this formative work influence the scientific communities’ understanding of the All of Us data source. We anticipate that this work will be highly cited and useful for future generations of researchers.

Demographic Categories of Interest

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

Research Team

Owner:

Collaborators:

  • Victoria Bland - Graduate Trainee, University of Arizona

Training_v3

I would like to use this workspace purely for educational purposes only. It will be used to demonstrate to students various data analysis approaches using large datasets and to familiarize them with All of Us cloud storage workflow.

Scientific Questions Being Studied

I would like to use this workspace purely for educational purposes only. It will be used to demonstrate to students various data analysis approaches using large datasets and to familiarize them with All of Us cloud storage workflow.

Project Purpose(s)

  • Educational

Scientific Approaches

To produce aggregate summary statistics and regression models for various measurement variables available in All of Us data.

Anticipated Findings

This exploratory analysis will enable us to explore heterogeneity in anthropometric measures among various racial-ethnic groups

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Jo-el Banini - Undergraduate Student, University of Arizona
  • Heidi Steiner - Graduate Trainee, University of Arizona
  • Claire Jurecky - Undergraduate Student, University of Arizona
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