At the Meeks lab, we study the causes of type 2 diabetes and related cardiometabolic conditions, including obesity, high blood pressure, abnormal cholesterol levels, and cardiovascular disease. These conditions result from complex interactions between genetic makeup and environmental exposures. Understanding that interplay is key to improving health outcomes.
Our work blends epidemiologic and genomic approaches, with a strong focus on African-ancestry populations and migrant health. Below are the core themes of our research:
Cardiometabolic Disease Epidemiology
We study the distribution and burden of cardiometabolic diseases in African-ancestry populations, including people living in Africa and African migrants around the world. Our research has shown that African migrants often face a higher burden of type 2 diabetes, obesity, and hypertension compared to both European-ancestry populations and their peers who remain in Africa. These insights help guide prevention strategies and policy decisions.
Environmental Drivers of Cardiometabolic Health
We know that the environment in which we live plays an important role in driving cardiometabolic disease risk, but what aspects of the environment? Our research investigates factors such as urbanization, diet, physical activity, stress, and social determinants of health to understand how they impact health outcomes, especially in the context of migration and rapid environmental change.
Genomic Insights into Cardiometabolic Diseases
We cannot fully understand the underlying causes of cardiometabolic health without studying genetics and genomics. African genomes harbor the highest degree of genetic diversity, yet African-ancestry populations are severely underrepresented in genomics research. We address this gap by analyzing whole-genome sequencing, DNA methylation, RNA sequencing, metabolomics, and microbiome data to identify biological pathways and molecular markers associated with disease risk in African populations.
Mendelian Randomization for Causal Inference
One of the biggest challenges in population health science is distinguishing correlation from causation. Our lab uses Mendelian randomization, an analytical method that leverages genetic variants as natural experiments and reduces bias from confounding and reverse causation. Using this approach, we have uncovered circulating cytokines and DNA methylation sites that may play a causal role in type 2 diabetes among Africans.