Evaluation of a Computational Model That Predicts the Effects of Quercetin on Metabolic Health Using Biological Age and Other Lipid-related Blood Metrics
Abstract
Quercetin is a natural flavonoid compound widely found in vegetables, fruits, and nuts. It has a long history of use as a dietary supplement. This study aims to assess results from a computational model suggesting that quercetin may offer novel benefits to metabolic health. Participants will take quercetin (as Quercetin Phytosome, a proprietary formulation with enhanced absorption properties) for 90 days while keeping lifestyle habits consistent throughout to estimate net effects of quercetin as much as possible. Blood samples will be collected at the beginning and end of the study to assess the effects of quercetin supplementation on metabolic health metrics such as LDL cholesterol, blood sugar, liver, kidney and immune function and calculated metabolic age. In addition, questionnaires will be completed to ensure compliance with study requirements and assess potential quercetin benefits in the participants' quality of life. This work will provide a proof-of-concept from a computational model of nutraceutical compounds and proposes a new application of quercetin in support of healthy human metabolism.
Conditions: Quercetin, Lipid Metabolism, Aging.
Primary outcome: Change in Biological Age score from before (day 0) to after (day 90) supplementation; Change in Apolipoprotein B from before (day 0) to after (day 90) supplementation; Change in Lipoprotein Fractions from before (day 0) to after (day 90) supplementation; Quality of Life scale changes from before (day 0) to after…
How strong is the evidence?
Evidence Hub reads this as a clinical trial, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 5 participants or records.
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