Principal Investigator: Dr Kaixiong Ye
University of Georgia (USA)Tags: 48818, biomarkers, Causal Effects, Clinical Outcomes, Dietary Supplements, genetics, Mendelian randomization
Taking dietary supplements could be an effective means of managing health and
preventing diseases. The specific health benefits of a dietary supplement have to
be evaluated by a clinical trial, which is usually resource-intensive and
complicated. An innovative statistical method, called Mendelian randomization,
provides a cost-effective alternative to evaluate the causal effect of a specific
environmental exposure on a clinical outcome. Our research will develop
computational tools implementing this kind of methods and apply them to
available data in the UK Biobank. We will un-biasedly evaluate the relationship
between all diet-modifiable biomarkers and clinical outcomes. We expect the
proposed project will take three years in implementation and then another year
in the publication of findings and software. Our research will demonstrate the
presence or absence of causal benefits of a biomarker on a clinical condition.
These discoveries will guide our future practice of dietary recommendation.
Scope extension – June 2020
This research aims to develop and apply a computational pipeline based on Mendelian randomization to evaluate the causal effects of diet-modifiable blood biomarkers on clinical outcomes, especially metabolic diseases. Our research will provide the computational tools to or directly answer the following practical question: are the claimed health benefits of various dietary supplements real? We focus on blood biomarkers that are known to respond to dietary inputs, such as cholesterol, triglyceride, HbA1c, Urea, vitamin D, and calcium. Our research discoveries will provide practical insights into disease prevention with proper dietary supplements.
For dietary factors of special importance to clinical outcomes, we would like to identify genetic variants that have diet-modifying effects on the outcomes (Gene-Diet Interaction Analysis) and we will develop genetic predictions of one’s disease risk under specific dietary conditions. Diet-specific genetic prediction of disease risk will guide dietary recommendations to lower disease risks. For genetic variants of special interest, we are also interested in understanding their broader clinical impacts by testing their associations with a large range of traits and diseases.
Last updated Jun 2, 2020