| Title |
Effect of a novel nutraceutical combination on serum lipoprotein functional profile and circulating PCSK9
|
|---|---|
| Published in |
Therapeutics and Clinical Risk Management, December 2017
|
| DOI | 10.2147/tcrm.s144121 |
| Pubmed ID | |
| Authors |
Maria Pia Adorni, Nicola Ferri, Silvia Marchianò, Valentina Trimarco, Francesco Rozza, Raffaele Izzo, Franco Bernini, Francesca Zimetti |
| Abstract |
A beneficial effect on cardiovascular risk may be obtained by improving lipid-related serum lipoprotein functions such as high-density lipoproteins (HDLs) cholesterol efflux capacity (CEC) and serum cholesterol loading capacity (CLC) and by reducing proprotein convertase subtilisin kexin type 9 (PCSK9), independently of lipoprotein concentrations. We aimed to evaluate the effect of an innovative nutraceutical (NUT) combination containing red yeast rice (monacolin K 3.3 mg), berberine 531.25 mg and leaf extract of Morus alba 200 mg (LopiGLIK®), on HDL-CEC, serum CLC and on circulating PCSK9 levels. Twenty three dyslipidemic subjects were treated for 4 weeks with the above NUT combination. HDL-CEC was measured using specific cell-based radioisotopic assays; serum CLC and PCSK9 concentrations were measured fluorimetrically and by enzyme-linked immunosorbent assay, respectively. The NUT combination significantly reduced plasma level of the total cholesterol and low-density lipoprotein cholesterol (-9.8% and -12.6%, respectively). Despite no changes in HDL-cholesterol, the NUT combination improved total HDL-CEC in 83% of the patients, by an average of 16%, as a consequence of the increase mainly of the ATP-binding cassette A1-mediated CEC (+28.5%). The NUT combination significantly reduced serum CLC (-11.4%) while it did not change PCSK9 plasma levels (312.9±69.4 ng/mL vs 334.8±103.5 mg/L, before and after treatment, respectively). The present NUT combination improves the serum lipoprotein functional profile providing complementary beneficial effects, without any detrimental increase of PCSK9 plasma levels. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 18% |
| Student > Bachelor | 8 | 18% |
| Researcher | 5 | 11% |
| Student > Master | 4 | 9% |
| Student > Doctoral Student | 3 | 7% |
| Other | 8 | 18% |
| Unknown | 9 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 12 | 27% |
| Medicine and Dentistry | 9 | 20% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Unspecified | 1 | 2% |
| Computer Science | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 17 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 December 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Therapeutics and Clinical Risk Management
#1,204
of 1,323 outputs
Outputs of similar age
#384,359
of 444,941 outputs
Outputs of similar age from Therapeutics and Clinical Risk Management
#23
of 24 outputs
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