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Principal Investigator: Sally Nneoma Adebamowo
Organization: UNIVERSITY OF MARYLAND BALTIMORE
Fiscal Year: 2024
Award: $901,157
Funding agency: National Human Genome Research Institute
Abstract/Summary
Globally, non-communicable diseases (NCDs) outrank infectious diseases in terms of public health burden.
Cardiometabolic diseases (CMD) such as heart disease and stroke are the leading causes of death worldwide.
In this application we will explore the genomic risk for common CMD, including hypertension, stroke, diabetes,
obesity, dyslipidemia and kidney disease, and related traits (including BMI, blood pressure, lipid, glucose, insulin
and creatine) across populations with African ancestry (AA). There is evidence to suggest that polygenic risk
scores (PRSs) translate poorly from a discovery study in one ancestral population (e.g. European Americans) to
a target population (e.g. sub-Saharan Africans), especially when they are separated by large genetic differences.
However, this has not been evaluated with large, well-powered AA datasets. Furthermore, the high genetic
diversity and population structure among non-European Ancestry (EA) populations need to be investigated to
understand the performance of PRSs in other regions populated by people with diverse genomic backgrounds.
We bring together the Human Heredity and Health in Africa Consortium (H3Africa), other African, Jamaican and
African American core cohorts, to develop a joint resource of over 50,000 participants with relevant phenotype
and genomics data, referred to as the CARdiometabolic Disorders IN African-ancestry PopuLations
(CARDINAL) Study Site. In addition, the CARDINAL Study Site will include 5 replication cohorts with >100,000
participants from diverse ancestry populations. Our main objective is to establish a Study Site for PRS
Methods and Analysis for AA Populations and to collaboratively generate and refine PRS for other
populations of diverse ancestry by integrating existing datasets with genomics and phenotype data for
a range of complex diseases and traits. Our first aim is to integrate phenotype and genomic datasets from
~50,000 African individuals from seven individual cohort studies. Subsequently, we will evaluate PRSs and
develop a novel method that takes into consideration, ancestry-specific genomic regions to improve prediction
of PRSs in populations characterised by genetic sub-structure. Finally, we will develop an interactive dashboard
for dissemination of PRS-related data from diverse ancestry populations. CARDINAL Study Site is ideal for
generating novel biologic insights into complex disease etiology, with applications in global populations.
Members of the CARDINAL team have successfully worked together for about a decade, generating and
disseminating scientific knowledge through high impact publications. By establishing a Study Site in the
Polygenic Risk Score Diversity Consortium, CARDINAL brings the largest cohort of African-ancestry
participants to the table, to explore the genomics contribution to common CMDs and other NCDs.
Terms: <Admixture><Affect><Africa><African><African American><African American group><African American individual><African American people><African American population><African Americans><African ancestry><African descent><Afro American><Afroamerican><Algorithms><Allele Frequency><Alleles><Allelomorphs><American><Apoplexy><BMI><BMI percentile><BMI z-score><Biological><Blood Pressure><Body mass index><Brain Vascular Accident><Cardiac Diseases><Cardiac Disorders><Cardiometabolic Disease><Cardiometabolic Disorder><Cardiovascular Diseases><Causality><Cause of Death><Cell Communication and Signaling><Cell Signaling><Cerebral Stroke><Cerebrovascular Apoplexy><Cerebrovascular Stroke><Clinical Management><Cohort Studies><Communicable Diseases><Complex><Concurrent Studies><Country><Creatine><D-Glucose><Data><Data Collection><Data Set><Development><Dextrose><Diabetes Mellitus><Diagnosis><Disease><Disorder><Dyslipidemias><Environment><Environmental Factor><Environmental Risk Factor><Ethnic Origin><Ethnicity><Etiology><European><European ancestry><Funding><GWA study><GWAS><Gene Frequency><Genetic><Genetic Diversity><Genetic Risk><Genetic Variation><Genome><Genomic Segment><Genomics><Genotype><Glucose><Guidelines><Health><Health Inequity><Health Policy><Heart Diseases><Heredity><Heterogeneity><Human><Humulin R><Hypertension><Individual><Inequalities in Health><Inequities in Health><Infectious Disease Pathway><Infectious Diseases><Infectious Disorder><Insulin><Intracellular Communication and Signaling><Jamaican><Joints><Kidney Diseases><Knowledge><Lead><Life Style><Lifestyle><Linkage Disequilibrium><Lipids><Methods><Modeling><Modern Man><Morbidity><Morbidity - disease rate><NIH><National Institutes of Health><Nephropathy><North Africa><North America><Northern Africa><Novolin R><Obesity><Participant><Patients><Pb element><Performance><Persons><Phenotype><Population><Population Analysis><Population Heterogeneity><Population Study><Preventative strategy><Prevention strategy><Preventive strategy><Process><Protocol><Protocols documentation><Public Health><Publications><Quality Control><Quetelet index><Regular Insulin><Renal Disease><Research><Research Resources><Resources><Risk><Risk Factors><Scientific Publication><Scientist><Scoring Method><Signal Transduction><Signal Transduction Systems><Signaling><Site><Stroke><Structure><Target Populations><Translating><Trust><United States National Institutes of Health><Variant><Variation><Vascular Hypertensive Disease><Vascular Hypertensive Disorder><Work><adiposity><allelic frequency><biologic><biological signal transduction><brain attack><burden of chronic disease><burden of chronic illness><cardiometabolic><cardiometabolism><cardiovascular disorder><causation><cerebral vascular accident><cerebrovascular accident><clinical risk><cohort><corpulence><dashboard><data diversity><data harmonization><data integration><data standardization><data standards><developmental><diabetes><diagnostic approach><diagnostic strategy><disease causation><disease risk><disorder risk><disparity in health><diverse data><diverse populations><environmental risk><genome segment><genome wide association><genome wide association scan><genome wide association studies><genome wide association study><genomewide association scan><genomewide association studies><genomewide association study><genomic data><genomic data-set><genomic dataset><genomic region><genomic variation><harmonized data><health care policy><health disparity><health inequalities><healthcare policy><heart disorder><heavy metal Pb><heavy metal lead><heterogeneous population><high blood pressure><hyperpiesia><hyperpiesis><hypertensive disease><hypertensive disorder><improved><insight><interactive tool><kidney disorder><life-style data><lifestyle data><machine learning based method><machine learning method><machine learning methodologies><member><mortality><multi-ethnic><multiethnic><novel><phenotypic data><polygenic risk score><population diversity><population stratification><population-based study><population-level study><prevent><preventing><renal disorder><stroked><strokes><studies of populations><study of the population><tool><trait><whole genome association analysis><whole genome association studies><whole genome association study><work group><working group>