Micah Hysong
Graduate Trainee, University of North Carolina, Chapel Hill
5 active projects
Elena_lit_review
Scientific Questions Being Studied
Demographics of those with Multiple Sclerosis, COPD, Ischaemic Stroke, Atopic Dermatitis, Asthma, Rheumatoid Arthritis, Venuous Thromboembolism, ALS, Major Depressive Disorder, Schizophrenia, Platelet Count, Alzheimers in v7
Project Purpose(s)
- Ancestry
Scientific Approaches
Want to test blood cell traits for associations with these diseases, but first need to assess if AllofUs has enough individuals with these diseases.
Anticipated Findings
I will obtain the age, sex, and ancestry of indivduals with these diseases. This will determine if there is enough data to look for associations
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Controlled Tier
G6PD
Scientific Questions Being Studied
HbA1c is a clinical measure used to assess glycemic control over time. However some genetic variants may interfere with the accuracy of HbA1c as a measure of glycemic control. This could have negative implications for management of patients with diabetes/prediabetes and lead to an increased risk of complications. This is particularly an issue for individuals with ancestry from malaria endemic regions, whose genomes may contain high impact variants in genes such as G6PD and HBB (i.e. sickle cell trait) that have been under selective pressure from malaria in the past and may now be interfering with accurate clinical use of the HbA1c measure. Our goal for this study is to characterize whether variants in G6PD and HBB impact the rate of diabetes related complications, likely due to impacts on HbA1c measurement accuracy.
Project Purpose(s)
- Disease Focused Research (Diabetes)
- Ancestry
Scientific Approaches
- Datasets: those with type 1 or 2 diabetes and WGS
- Sickle Cell status rs334(A;T) - yes or no
- G6PD variants – where males are multiplied by two
Hypothesis 1: Individuals with diabetes and with known G6PD coding variants, particularly hemizygous males or homozygous females, will have a higher rate of diabetic retinopathy.
Cox proportional hazards models:
1. outcome~age+ sex + G6PD variant count+ sickle cell trait status + 10 principal components of genetic ancestry
2. + BMI
Hypothesis 2: In individuals with diabetes, HbA1c will be more predictive of retinopathy when adjusted for G6PD coding variant status. All models should be stratified by diabetes status (any diabetes, including either type 1 or type 2) at beginning of follow-up.
Cox proportional hazards models:
1. outcome~HbA1c+age+ sex + G6PD variant count+ sickle cell trait status + 10 principal components of genetic ancestry
2. +BMI
Anticipated Findings
We anticipate that coding variants in G6PD and HBB will lead to increased diabetic retinopathy. Understanding how variants from diverse populations impact our clinical measures and outcomes is imperative for reducing racial health disparities.
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Controlled TierResearch Team
Owner:
- Micah Hysong - Graduate Trainee, University of North Carolina, Chapel Hill
Collaborators:
- Jun Qian - Other, All of Us Program Operational Use
BCX PRS (V7)
Scientific Questions Being Studied
PRS have been demonstrated to have low portability between ancestry groups (Duncan et al., 2019). This is largely due to the fact that 78% of GWAS has been performed in individuals of European ancestry (Gurdasani et al., 2019). Generous participants in the All of Us research program are from diverse genetic ancestry backgrounds, allowing for the statistical power necessary to test methods to improve PRS performance in individuals of non-European ancestry. Specifically, I will be exploring the performance of the PRS for a variety of test quantitative traits, including blood cell indices. Moreover, I will use the All of Us data to test/train new PRS in non-European ancestry groups and assess if this leads to higher performance. Increasing PRS performance in different ancestry groups is imperative to equitable implementation of PRS to improve health outcomes.
Project Purpose(s)
- Ancestry
Scientific Approaches
Datasets: Cohort: Whole Genome Sequencing Derive PRS that includes all ancestry groups and then individual PRS for each ancestry group. Generate a generalized linear model that includes age, sex at birth, and PRS as covariates.
Anticipated Findings
We expect that PRS scores trained in European ancestry will have lower accuracy for predicting blood cell indices in cohorts with non-European ancestry. We also predict that training a new PRS in more diverse populations will make a PRS that is more accurate across all ancestries. Overall, these findings would contribute to the growing body of literature supporting the need for including more diverse ancestry groups in genomic studies. Importantly, this will improve health-outcomes in minoritized groups.
Demographic Categories of Interest
- Race / Ethnicity
- Age
Data Set Used
Controlled TierResearch Team
Owner:
- Micah Hysong - Graduate Trainee, University of North Carolina, Chapel Hill
Collaborators:
- Jun Qian - Other, All of Us Program Operational Use
PRS for Alzheimer's
Scientific Questions Being Studied
PRS have been demonstrated to have low portability between ancestry groups (Duncan et al., 2019). This is largely due to the fact that 78% of GWAS has been performed in individuals of European ancestry (Gurdasani et al., 2019). Generous participants in the All of Us research program are from diverse genetic ancestry backgrounds, allowing for the statistical power necessary to test methods to improve PRS performance in individuals of non-European ancestry.
Specifically, I will be exploring the performance of the PRS for Alzheimer's Disease derived in European ancestry cohorts in various genetic ancestry groups. Increasing PRS performance in different ancestry groups is imperative to equitable implementation of PRS to improve health outcomes.
Project Purpose(s)
- Disease Focused Research (Alzheimer's disease)
- Ancestry
Scientific Approaches
Datasets:
Cohort: Whole Genome Sequencing
Alzheimer's vs Control: Non-Alzheimer's
Derive PRS that includes all ancestry groups and then individual PRS for each ancestry group. Generate a generalized linear model that includes age, sex at birth, and PRS as covariates. Additionally, generate a model that also includes the number of APOE-ε4 and APOE-ε2 alleles.
Anticipated Findings
We expect that PRS scores trained in European ancestry will have lower accuracy for predicting Alzheimer's disease in cohorts with non-European ancestry. We also predict that training a new PRS in more diverse populations will make a PRS that is more accurate across all ancestries.
Overall, these findings would contribute to the growing body of literature supporting the need for including more diverse ancestry groups in genomic studies. Importantly, this will improve health-outcomes in minoritized groups.
Demographic Categories of Interest
- Race / Ethnicity
- Age
Data Set Used
Controlled TierPRS for Blood Cell Traits
Scientific Questions Being Studied
PRS have been demonstrated to have low portability between ancestry groups (Duncan et al., 2019). This is largely due to the fact that 78% of GWAS has been performed in individuals of European ancestry (Gurdasani et al., 2019). Generous participants in the All of Us research program are from diverse genetic ancestry backgrounds, allowing for the statistical power necessary to test methods to improve PRS performance in individuals of non-European ancestry. Specifically, I will be exploring the performance of the PRS for a variety of test quantitative traits, including blood cell indices. Moreover, I will use the All of Us data to test/train new PRS in non-European ancestry groups and assess if this leads to higher performance. Increasing PRS performance in different ancestry groups is imperative to equitable implementation of PRS to improve health outcomes.
Project Purpose(s)
- Ancestry
Scientific Approaches
Datasets: Cohort: Whole Genome Sequencing Derive PRS that includes all ancestry groups and then individual PRS for each ancestry group. Generate a generalized linear model that includes age, sex at birth, and PRS as covariates.
Anticipated Findings
We expect that PRS scores trained in European ancestry will have lower accuracy for predicting blood cell indices in cohorts with non-European ancestry. We also predict that training a new PRS in more diverse populations will make a PRS that is more accurate across all ancestries. Overall, these findings would contribute to the growing body of literature supporting the need for including more diverse ancestry groups in genomic studies. Importantly, this will improve health-outcomes in minoritized groups.
Demographic Categories of Interest
- Race / Ethnicity
- Age
Data Set Used
Controlled TierRequest a Review of this Research Project
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