akhil pampana

Project Personnel, University of Alabama at Birmingham

3 active projects

Blood Pressure Polygenic Risk Score

We aim to examine a multi-ethnic cohort of US adults to examine: 1) the association of BP PRS (blood pressure polygenic risk score) with BP traits (systolic BP, diastolic BP, mean arterial pressure [MAP], pulse pressure [PP], hypertension [HTN]) (overall…

Scientific Questions Being Studied

We aim to examine a multi-ethnic cohort of US adults to examine:
1) the association of BP PRS (blood pressure polygenic risk score) with BP traits (systolic BP, diastolic BP, mean arterial pressure [MAP], pulse pressure [PP], hypertension [HTN]) (overall and stratified by self-reported race/ethnicity),
2) the association of BP PRS with cardiovascular disease (CVD) events;
3) the association of traditional CV risk factor profile with CVD events stratified by BP PRS categories;
4) the incremental contribution of BP PRS to CVD risk prediction using the ACC/AHA Pooled Cohorts Equation (PCE).

This study will help us understand if a genome-wide polygenic risk score can be used to guide risk stratification of primary care patients with hypertension.

Project Purpose(s)

  • Disease Focused Research (hypertension)
  • Population Health
  • Methods Development
  • Ancestry

Scientific Approaches

Dataset: We will use the All of Us controlled tier genomic data and phenotypic data to construct and validate a genome-wide polygenic risk score

Methods: We utilized the multi-ethnic pan-ancestry UK Biobank GWAS data (available at:https://pan.ukbb.broadinstitute.org) for systolic and diastolic BP as the base data for the computation of the PRS (SNPs and their associated β-coefficients). The BP PRS will be constructed using the PRS-CS approach. The PRS-CS is a Bayesian approach to computing PRS that derives each genetic variant’s posterior mean effect size (weight) from the prior GWAS base data while accounting for the LD using the 1000 Genomes as the reference population. We will use the ϕ values set to 10^-2, 10^-4, 10^-6, and auto, with a p-value threshold of 0.05. Unlike other Bayesian methods such as LDPred, PRS-CS-auto does not require separate derivation and validation subcohorts.

Tools: Plink 2.0; R Statistical Software;

Anticipated Findings

In this comprehensive investigation involving a multi-ethnic cohort of American adults, we anticipate finding a robust cross-sectional association of multi-ethnic BP PRS (polygenic risk score) with BP traits overall and across subgroups of self-identified race/ethnicity was observed.

Second, we anticipate that individuals at an increased genetic risk for elevated BP (measured using BP PRS) are also predisposed individuals to an increased risk of adverse CV events such as heart failure (HF), coronary heart disease (CHD), or stroke, after accounting for traditional CV risk factors (ACC/AHA Pooled Cohorts Equation [PCE]).

Third, we anticipate that among those with a high genetic predisposition to elevated BP, a low traditional CV risk factor burden (low ACC/AHA PCE risk) will be associated with a lower risk of adverse CV events.

Lastly, in a multi-ethnic cohort of middle-aged adults, BP PRS will provide a modest improvement in adverse CV risk prediction beyond the ACC/AHA PCE.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

  • akhil pampana - Project Personnel, University of Alabama at Birmingham

LIPIDS_GWAS

We will investigate lipids and how lipids play a role in cardiovascular disease risk. All the studies we have conducted in lipids are mostly based on either European cohorts like UK-biobank and multi-ethnic cohorts like TOPmed. We would like to…

Scientific Questions Being Studied

We will investigate lipids and how lipids play a role in cardiovascular disease risk. All the studies we have conducted in lipids are mostly based on either European cohorts like UK-biobank and multi-ethnic cohorts like TOPmed. We would like to understand how the lipid patterns and role in mechanism of cardiovascular disease risk.
1.) Are there any genetic risk factors observed specific to the All OF US cohort than others?
2.) how are other diseases like Diabetes/obesity are linked to lipids?
3.) Are there any underlying mechanisms that help us in understanding disease prognosis and helps towards therapeutics?

This study will give an idea of how lipid patterns play a role in understanding disease risk in the United States.

Project Purpose(s)

  • Disease Focused Research (CVD, diabetes, lipids, liver disease)
  • Population Health
  • Drug Development
  • Ancestry

Scientific Approaches

1.) We will use Hail(developed by the Broad Institute) to do initial quality control checks for the dataset.
2.) Generation of PCs and relatedness matrix using GENESIS package in R
3.) We will extract lipids and statins use status from Health records. (if already extracted, we will use those)
4.) We will conduct a whole scale genome-wide association study using lipids profiles which are adjusted for statins (4 lipids traits - HDL, LDL, TC, TG) and model is adjusted with age, sex, pcs.(Tool - Not decided)
5.) The significant variants identified will be replicated in other cohorts like TOPmed, UK-biobank, etc
6.) We will also perform rare variant burden test using tools available like STAAR package in R
7.)Based on initial findings we will conduct downstream analysis which is to be determined.

Anticipated Findings

For this study, We expect there will be novel genes/variants which are specific to the USA population. Given a diverse population structure, we expect to find many more genes involved that were not previously discovered which helps us understand underlying mechanisms of disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • akhil pampana - Project Personnel, University of Alabama at Birmingham

LIPIDS_GWAS

We will investigate lipids and how lipids play a role in cardiovascular disease risk. All the studies we have conducted in lipids are mostly based on either European cohorts like UK-biobank and multi-ethnic cohorts like TOPmed. We would like to…

Scientific Questions Being Studied

We will investigate lipids and how lipids play a role in cardiovascular disease risk. All the studies we have conducted in lipids are mostly based on either European cohorts like UK-biobank and multi-ethnic cohorts like TOPmed. We would like to understand how the lipid patterns and role in mechanism of cardiovascular disease risk.
1.) Are there any genetic risk factors observed specific to the All OF US cohort than others?
2.) how are other diseases like Diabetes/obesity are linked to lipids?
3.) Are there any underlying mechanisms that help us in understanding disease prognosis and helps towards therapeutics?

This study will give an idea of how lipid patterns play a role in understanding disease risk in the United States.

Project Purpose(s)

  • Disease Focused Research (CVD, diabetes, lipids, liver disease)
  • Population Health
  • Drug Development
  • Ancestry

Scientific Approaches

1.) We will use Hail(developed by the Broad Institute) to do initial quality control checks for the dataset.
2.) Generation of PCs and relatedness matrix using GENESIS package in R
3.) We will extract lipids and statins use status from Health records. (if already extracted, we will use those)
4.) We will conduct a whole scale genome-wide association study using lipids profiles which are adjusted for statins (4 lipids traits - HDL, LDL, TC, TG) and model is adjusted with age, sex, pcs.(Tool - Not decided)
5.) The significant variants identified will be replicated in other cohorts like TOPmed, UK-biobank, etc
6.) We will also perform rare variant burden test using tools available like STAAR package in R
7.)Based on initial findings we will conduct downstream analysis which is to be determined.

Anticipated Findings

For this study, We expect there will be novel genes/variants which are specific to the USA population. Given a diverse population structure, we expect to find many more genes involved that were not previously discovered which helps us understand underlying mechanisms of disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • akhil pampana - Project Personnel, University of Alabama at Birmingham

Collaborators:

  • Thomas Gilliland - Research Fellow, The Broad Institute
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