Newton001 Genetic and Electronic Medical Records to predict outcomes in Heart Failure patients - Bridging Brazilian and UK genetic epidemiology

Lead Research Organisation: London School of Hygiene & Tropical Medicine
Department Name: Epidemiology and Population Health

Abstract

Heart failure (HF) is the main cause of hospitalization based on available data from approximately 50% of the South American population. Moreover, infectious diseases such as Chagas disease and rheumatic heart disease, known causes of HF, are still frequent in this population. Strategies are required to reduce risk and predict the future burden of this disease.
The working group focuses on the development and implementation of algorithms for validation and application of medical decision routines using genetic information and electronic medical record systems in order to help the clinical management of heart failure patients.
The Brazilian group is already performing data collection and development of an integrated biobank merging demographical, clinical and genetic information. The British group will establish collaborative arrangement in cardiovascular genetics and the development and application of computational tools and quantitative methods and models for the Brazilian heart failure population with expected results leading to biomarker discovery for aetiology, treatment response and integration analysis of genomics, metabolomics and proteomics.

Technical Summary

Studies adopting electronic medical records (EMR) and genomic information are becoming widespread. Through this ne
modality of research, it is possible to study how genetic variants influence susceptibility towards chronic conditions and can improve patient care. Both Brazil and UK are developing projects towards using this information to predict different outcomes in heart failure patients. Our aim is to develop a collaborative project using Brazilian heart failure patients with genome-wide data already available, conduct genome-wide association studies (GWAS) for derivation of target hits associated with heart failure-related phenotypes and use UK-based cohort studies to validate the hits disclosed. Patients between 18 and 80 years old with heart failure diagnosis and LVEF < 50%, with already generated GWAS data will be eligible for enrollment on the study. The discovery phase will use data on 1,000 Brazilian patients. We will investigate the effects of multiple data imputation algorithms (using 1000 genomes data with or without Brazilian genomes). Main hits will be tested against available UK-cohort studies in a second-stage analysis. The expect results is to create a UK-Brazil working group focused on the development and implementation of algorithms for validation and application of medical routines using genetic information for heart failure management. Moreover, to build capacity of young researchers, to do a pilot study of plasma or serum samples on metabolomics with metabolon US platform and with a proteomics platform and to show proof of concept with Brazilian GWAs data using Brazilian sequencing data for imputation and the impact of population stratification on known genetic hits for a well established trait available in the Brazilian cohort.

Planned Impact

N/A

Publications

10 25 50

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Dudbridge F (2016) Polygenic Epidemiology. in Genetic epidemiology

 
Description Wellcome 4-year PhD Programme in Science
Amount £5,153,712 (GBP)
Funding ID 218505/Z/19/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 09/2020 
End 09/2028
 
Description USP 
Organisation Universidade de São Paulo
Country Brazil 
Sector Academic/University 
PI Contribution Expertise in statistical genetics
Collaborator Contribution Genetic epidemiological studies in Brazil
Impact Guidance on student projects. Attendance at training courses.
Start Year 2015