Peter Barr
Virginia Commonwealth University
4 active projects
Social Determinants of Sleep Disorders in Multiethnic Sample
Scientific Questions Being Studied
Studies show that social characteristics associated with good health, such as a high education level, marriage, and employment, are associated with healthier sleep health.
Specifically, the present research project aims to investigate the following research question:
"What is the relationship between social determinants of health such as race/ethnicity, sex/gender, age, education level, income, insurance, location, and place of birth on sleep health diagnosis in US Adults?"
Investigating the social determinants of sleep disorders in the NIH All of Us Research Program is essential for understanding the underlying causes, addressing health disparities, designing effective interventions, understanding health comprehensively, and influencing policy decisions to promote healthy sleep behaviors and overall well-being.
Project Purpose(s)
- Disease Focused Research (Sleep Disorders)
- Population Health
- Social / Behavioral
Scientific Approaches
Phecodes for diagnoses will derive from the ICD-9/10 billing codes in participants’ electronic health records (EHRs). We used 0 phecodes of the parent category of sleep disorders (insomnia and sleep apnea) (phecode 327) in a person’s EHR to classify individuals as not having a diagnosis and 2+ phecodes as having a diagnosis (those with only one instance in their EHR were dropped). A Longitudinal study using Logistic regression analysis will assess associations between sleep disorders and social determinants of health such as race/ethnicity, sex/gender, age, education level, income, insurance, location, and place of birth level using the R statistical framework.
Anticipated Findings
Among All Of Us populations, we hypothesize that participants from low-income communities, women, and those without insurance will be less likely to have recorded insomnia or sleep apnea diagnoses. Potential within-group differences could be due to self-reported versus clinically recorded diagnoses and access to healthcare.
Our findings will contribute to advanced data on which subcategory of the population is more affected by sleep health disparities, the impact of healthcare coverage on sleep health, designing effective sleep health interventions, and influencing policy decisions to promote sleep health equity.
Demographic Categories of Interest
- Race / Ethnicity
- Gender Identity
- Sexual Orientation
- Geography
- Access to Care
- Education Level
- Income Level
Data Set Used
Registered TierResearch Team
Owner:
- Peter Barr - Other, Virginia Commonwealth University
- Judite Blanc - Early Career Tenure-track Researcher, University of Miami
Collaborators:
- Peter Barr - Early Career Tenure-track Researcher, SUNY Downstate Health Sciences University
- tim bigdeli - Early Career Tenure-track Researcher, SUNY Downstate Health Sciences University
Polygenic Scores for Severe Mental Illness in Diverse Samples
Scientific Questions Being Studied
This research is part of a broader project within the Veterans Administration Million Veteran Program (MVP). First, we will validate polygenic scores (PGS) for schizophrenia (SCZ) and bipolar disorder (BIP) derived from genome wide association studies (GWAS) in veterans of Admixed African and American ancestries within ancestrally-matched participants in All of Us. We will benchmark PGS results against those from All of Us participants of primarily European ancestries. Second we will explore the associations between PGSs and phecodes derived from SNOMED codes in the electronic health records (EHR) and self-reported health outcomes/behaviors (e.g., alcohol use, smoking, lifestyle factors).
To date, genetic analyses have been limited to primarily individuals of European ancestries. This project will help to address disparities in psychiatric genetics by validating the GWASs of schizophrenia and bipolar disorder in participants of African and American ancestries to date.
Project Purpose(s)
- Disease Focused Research (schizophrenia, bipolar disorder, and comorbid conditions)
- Population Health
- Ancestry
Scientific Approaches
We will use a combination of EHR, survey, and genetic data. For genetic data, we will estimate polygenic scores, which are aggregate measures of genetic risk weighted by effect sizes from genome wide association studies (GWAS), using PRS-CSx (Ruan et al. 2022), a method that corrects for the non-independence of variants close to one another in the genome using a Bayesian continuous shrinkage approach. Second, we will create phecodes from EHR data, which are curated groupings of diagnostic codes (e.g., ICD10, SNOMED, etc.). We will then take PGS into to the EHR to test whether the PGS are associated with SCZ and BIP diagnosis in All of Us (validating results in MVP) and test what other phecodes are associated with the PGS in a phenome-wide association study (PheWAS). Lastly, we will examine whether the PGS are associated with various lifestyle factors.
Ruan, Y, et al. “Improving polygenic prediction in ancestrally diverse populations.” Nature Genetics, 54(5): 573-580, 2022.
Anticipated Findings
We expect the polygenic score from the combined MVP+PGC GWAS results to outperform existing PGS. Featuring results from veterans of African and American ancestries help to move forward the goal of improving representation and diversity in genetic studies. We also expect the large and well-powered EHR data to reveal additional associations between both the SCZ and BIP PGSs and various downstream health consequences that we have observed in other studies (Bigdeli et al 2022).
Bigdeli, TB., et al. Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia, Bipolar Disorder, and Depression Among Adults in the US Veterans Affairs Health Care System. JAMA Psychiatry 2022.
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Controlled TierResearch Team
Owner:
- Peter Barr - Early Career Tenure-track Researcher, SUNY Downstate Health Sciences University
- Peter Barr - Other, Virginia Commonwealth University
Collaborators:
- tim bigdeli - Early Career Tenure-track Researcher, SUNY Downstate Health Sciences University
Duplicate of Psychiatric comorbidities
Scientific Questions Being Studied
This analysis will explore the comorbidities between psychiatric and substance use disorders across demographic groups. The goal is to better understand the correlation between conditions in the US population broadly, and to see if there are varying patterns across different demographic characteristics.
Project Purpose(s)
- Population Health
Scientific Approaches
We will use all available data to calculate estimates of lifetime prevalence for psychiatric disorders and test for patterns of correlations between these disorders.
Anticipated Findings
This research will help to provide current population estimates of psychiatric disorders and their patterns of comorbidity.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Peter Barr - Early Career Tenure-track Researcher, SUNY Downstate Health Sciences University
- Peter Barr - Other, Virginia Commonwealth University
Psychiatric comorbidities
Scientific Questions Being Studied
This analysis will explore the comorbidities between psychiatric and substance use disorders across demographic groups. The goal is to better understand the correlation between conditions in the US population broadly, and to see if there are varying patterns across different demographic characteristics.
Project Purpose(s)
- Population Health
Scientific Approaches
We will use all available data to calculate estimates of lifetime prevalence for psychiatric disorders and test for patterns of correlations between these disorders.
Anticipated Findings
This research will help to provide current population estimates of psychiatric disorders and their patterns of comorbidity.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierRequest a Review of this Research Project
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