Bridging gaps on the genetics of age-related disorder among under-represented populations

This project is suitable for PhD students only. Some experience in biostatistics and data analysis is essential, and a background in statistics, engineering, health sciences, epidemiology, health economics, computer science and/or public health is recommended. Crucially, candidates must demonstrate adequate interpersonal skills, critical thinking and cultural competence to effectively engage with stakeholders from diverse backgrounds. Special attention will be given to ensuring the respectful engagement of under-represented populations and safeguarding their rights throughout the research process.

Introduction

Genomics research stands as a pivotal domain providing insights into the genetic foundations of human diseases, paving the way for personalized treatments. However, it is increasingly evident that this research has not been conducted equitably across diverse populations. The historical Eurocentric bias in genomics has resulted in a notable lack of representation for non-European populations in significant genetic discoveries. Such disparity holds profound implications for health equity and precision medicine, underscoring the necessity to address hurdles in genomics research among diverse populations.

Aim

This project meticulously examines opportunities and challenges in human genetic research on age-related disorders across diverse ancestries. It involves identifying factors affecting statistical genetics techniques, evaluating feasibility of genetic screening programs, and addressing disparities in research capacity.

Objectives and Scope

The PhD candidate will analyse multi-ancestry genetic data on various age-related human diseases, contributing to diversity in genomic research. They’ll have the opportunity to work on genomic data from large established biobanks and co-design pilot genetic studies focused on under-represented populations. The project is flexible, allowing candidates to focus on specific/multiple disease endpoints or ethnicities; or focus on specific research question of interest.

Methodology and Approach

The candidate will employ a multifaceted approach, examining technical and non-technical aspects influencing genetic research adoption across regions. Utilizing various research methodologies and technologies, including AI, they’ll explore factors such as perception, culture, policy, and community engagement to enable genomic medicine in different healthcare landscape. The candidate will also work closely with relevant stakeholders will validate research assumptions and derive equitable solutions

Innovation and Impact

This project offers an innovative opportunity to address the need for equitable representation in genomic research. Through co-designing pilot studies and leveraging emerging technologies, the candidate will advance genomic knowledge, promote health equity, and guide capacity-building efforts in diverse communities.