Project 454545
Prouricemic diets, microbial composition and functional potential, and plasma uric acid
Prouricemic diets, microbial composition and functional potential, and plasma uric acid
Project Information
| Study Type: | Unclear |
| Research Theme: | Social / Cultural / Environmental / Population Health |
Institution & Funding
| Principal Investigator(s): | Rai, Sharan |
| Supervisor(s): | Sun, Qi; Lee, Kyu Ha |
| Institution: | Harvard School of Public Health (Massachusetts) |
| CIHR Institute: | Nutrition, Metabolism and Diabetes |
| Program: | |
| Peer Review Committee: | Health Research Training A - Post-PhD (HTA) |
| Competition Year: | 2021 |
| Term: | 3 yrs 0 mth |
Abstract Summary
Gout is the most common inflammatory arthritis among Canadians and is associated with increased risks of other metabolic diseases and premature death. Gout is caused by hyperuricemia, which refers to having elevated levels of a substance called uric acid in the blood. When a person's uric acid reaches a certain level, it forms crystals within the joints and causes inflammation and pain. Prior research has shown that individual foods and beverages may lead to hyperuricemia and gout. However, no study has evaluated the overall uric acid-promoting potential of an individual's diet. By linking participants' dietary habits with blood uric acid levels, we could gain valuable insights into what diet patterns most predict gout In addition, prior researchers have found that the human gut microbiome (which refers to the microorganisms living in our digestive tract) may also play a role in how people metabolize uric acid, which in turn may impact their risk of developing hyperuricemia and eventually gout. Therefore, if we can better understand how diet interacts with microbiome to influence uric acid levels, then we will better understand how individuals may respond differently to the same diet. To do this research, I am going to use three large datasets spanning over two decades of follow-up with detailed diet, lifestyle and medical data. I am going to use dietary questionnaires to create a diet index that predicts hyperuricemia and reflects the overall uric acid-promoting potential of an individual's diet. I will then use statistical modeling to evaluate how this index is related to gout risk. Finally, I will examine the relationship between this diet index, gut microbiome data, and uric acid levels to better understand how these factors interact. This research has clear public health significance since it could assist us to develop effective dietary strategies to help prevent and manage gout.
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