Hypercholesterolemia
Conditions
Keywords
Red yeast rice, Monacolins, Dietary supplement, Randomized clinical study
Brief summary
The primary purpose of our research will be to evaluate if, in healthy subjects with a low- moderate cardiovascular risk (CV risk\>1% but \< 5%) evidenced by sub-optimal cholesterol levels as per ESC/EAS guidelines (LDL cholesterol \>115 mg/dL, \< 190 mg/dL) supplementation with a red yeast rice food supplement containing less than 3 mg total monacolins per daily dose is able to significantly influence plasma lipid levels. Furthermore, liver and muscle proteomic pattern and vascular response to dietary supplementation will be investigated.
Interventions
Red yeast rice 160 mg (total monacolins 2.8 mg)
Placebo
Sponsors
Study design
Eligibility
Inclusion criteria
* Male or female aged ≥ 30 years and ≤ 70 years old. * Body Mass Index included between 18 Kg/m2 and 35 Kg/m2 * Total cholesterolemia between 200 and 280 mg/dL and/or LDL-Cholesterol between 130 mg/dL and 190 mg/dL. * TG\<400 mg/dL. * Subjects who, according to the SCORE charts, have a low or moderate cardiovascular risk (defined as a total cardiovascular risk \< 5%) and for whom, according to ESC/EAS guidelines 2012, the intervention strategy does not require a pharmacological lipid-lowering intervention. * Subjects who have the capability to communicate, to make themselves understood, and to comply with the study's requirements. * Subjects agree to participate in the study and having dated and signed the informed consent form.
Exclusion criteria
* Assumption of lipid lowering drugs or dietary supplements, or drugs potentially affecting the lipid metabolism; * Assumption of any kind of drug treatment non-stabilized for at least 3 months; * Known current thyroid, gastrointestinal or hepatobiliary diseases (including liver transaminases ≥3ULN), as well as any muscular disorders (even subclinical, including serum CPK ≥3ULN); * Current or previous alcohol abuse; * Pregnancy and Breastfeeding * Known previous intolerance to red yeast rice * History or clinical evidence of any significant concomitant disease that could compromise the safety of the subject or the possibility of completing the study; * Any medical or surgical condition that would limit the patient adhesion to the study protocol.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Treatment-dependent change in LDL-C | 6 weeks | The primary objective is to evaluate the effect of the tested dietary supplement containing less than 3 mg of total monacolins per daily dose on LDL cholesterol level versus placebo after 6 weeks of treatment vs placebo in healthy subjects with suboptimal cholesterolemia |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Treatment-dependent change in Total Cholesterol | 6 weeks | To compare the effect of the tested dietary supplement on total cholesterol level after 6 weeks of treatment vs placebo vs placebo in healthy subjects with suboptimal cholesterolemia |
| Treatment-dependent change in Non-HDL-C | 6 weeks | To compare the effect of the tested dietary supplement on Non-HDL cholesterol level after 6 weeks of treatment vs placebo vs placebo in healthy subjects with suboptimal cholesterolemia |
| Treatment-dependent change in liver parameters | 6 weeks | To evaluate if the tested dietary supplement is associated with changes in liver parameters (i.e. AST, ALT, gamma-GT) vs placebo in healthy subjects with suboptimal cholesterolemia |
| Treatment-dependent change in CPK plasma levels | 6 weeks | To evaluate if the tested dietary supplement is associated with changes in CPK plasma levels compared to placebo in healthy subjects with suboptimal cholesterolemia |
| Treatment-dependent change in plasma proteomic pattern | 6 weeks | To evaluate if the tested dietary supplement is associated with significant changes on plasma proteomic pattern with focus on liver and muscle protein parameters in healthy subjects with suboptimal cholesterolemia. Protein abundances will be calculated with the generation of spectral features by the node FeatureFinderMultiplex followed by PIA-assisted FDR-multiple scores estimation and filtering (combined FDR score\<0.01), their ID mapping and combination with peptide IDs, their subsequent alignment, grouping and normalization (e.g., MapAlignerIdentification, FeatureUnlabeledQT and ConsensusmapNormalizer nodes). |
Countries
Italy