Myo-inositol, D-chiro-inositol and Glucomannan in PCOS

NCT ID: NCT03608813

Last Updated: 2018-08-03

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 120 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2016-09-10
• Study Completion Date: 2017-07-31

Brief Summary

The aim of this study is to analyze the metabolic profiles in women with PCOS before and after 3 months of therapy with a combination of myo-inositol, D-chiro-inositol and glucomannan, and compare these data with a group of healthy control women.

Detailed Description

1. RATIONALE & BACKGROUND INFORMATION Polycystic ovary syndrome (PCOS) is a heterogeneous syndrome and one of the most common female endocrine disorders, affecting 5-20% of women in reproductive age . Clinical expression is highly variable, but typically includes oligo-ovulation or anovulation, hyperandrogenism and polycystic ovaries . PCOS is associated with an increased risk of type 2 diabetes, cardiovascular events and endometrial cancer. Insulin Resistance (IR) plays a central role in approximately 70-80% of obese women and in 15-30% of lean women with PCOS, and represents the pathogenic link between metabolic and reproductive disorders in PCOS. According to recent guidelines, insulin-sensitizer drugs, like inositols, are the first-line therapy in women with metabolic abnormalities and irregular menstrual cycle with the purpose to improve fertility, whereas a lifestyle change with weight loss and physical activity is the first step in overweight and obese PCOS patients . Moreover, the association inositols-glucomannan may represent a good therapeutic strategy in the treatment of PCOS women with insulin resistance. Metabolomic approach is used to better define the pathophysiology of PCOS and to describe how different therapies can modify metabolic profiles. Although the association inositols-glucomannan may represent a good therapeutic strategy in the treatment of PCOS women with insulin resistance, the effect of inositols on the metabolomic profile of these women has not been described yet.

2. STUDY GOALDS AND OBJECTIVES The aim of this study is to analyze the metabolic profiles in women with PCOS before and after 3 months of therapy with a combination of myo-inositol, D-chiro-inositol and glucomannan, and compare these data with a group of healthy control women.

3. STUDY DESIGN The study is a prospective and observation. The inclusion criteria are: age between 18 and 35 years, overweight/obesity (BMI > 25 kg/m2), absence of any other acute intercurrent or chronic illness, a positive diagnosis of PCOS according to Rotterdam criteria. Exclusion criterion is using hormonal medications or drugs that affect insulin sensitivity (e.g., inositols or metformin) before enrollment.

The use of myo-inositol (1.75 g), D-chiro-inositol (0.25 g) and glucomannan (4.0 g)/die must precede the recruitment of no more than 30 days. The decision to start treatment must have already been made before and independently of the start of the study. The use of inositol and glucomannan must take place according to the technical data sheet. In particular, myo-inositol (1.75 g), D-chiro-inositol (0.25 g) and glucomannan (4.0 g) are expected to be subdivided into two doses before main meals.

4. METHODOLOGY 4.1 Admission visit (V0) Once the eligibility criteria have been checked, the investigator will inform the patient about the objectives of the study during the initial visit (V0) and obtain written informed consent form.

The compilation of a clinical card includes general information, anamnesis, BMI, the characteristics of the menstrual cycle, the amount of menstrual loss, the degree of hirsutism according to the Ferriman-Gallwey index and the degree of acne in agreement to the Global evaluation scale proposed in 2002 by FDA.

The investigator will collect from the clinical documentation available the baseline glycaemia, insulin, triglycerides, cholesterol values before the start of the treatment. Furthermore, information on the ultrasound picture will be collected in terms of ovary volumes and antral follicles.

A sample of 2-3 ml of basal blood will be collected for metabolomic evaluations, using a BD vacutainer (Becton Dickinson, Oxfordshire, UK) blood collection red tube (with no additives). After centrifugation, the sample will immediately freeze to -80 °C until the time of analysis.

The patient will then be invited to continue treatment with myo-inositol (1.75 g), D-chiro-inositol (0.25 g) and glucomannan (4 g) die and to show up for control after 90 days (V1).

4.2 Follow-up visit 90th day (±15) after enrollment (V1) During the V1 the patient will be interviewed on the regular therapy and clinical symptoms, any adverse events and the course of the menstrual cycle.

Furthermore, all patients will be re-evaluated regarding the anthropometric, biochemical and ultrasound parameters.

At V1 a second blood sample of 2-3 ml will be collected with the same methods describe above.

4.3 Biochemical and metabolomics samples analysis Blood concentration of glucose, insulin, triglycerides and cholesterol is evaluated for control subjects and for cases at baseline and after 3 months of treatment. HOMA-IR si also calculated. Ovary volumes and the antral follicles count were evaluated by a vaginal ultrasound performed by a trained gynecologist.

Metabolome extraction, purification and derivatization is carried out with the MetaboPrep GC kit (Theoreo srl, Montecorvino Pugliano [SA], Italy) according to the manufacturer's instructions. Details regarding metabolite extraction and the overall analytical scheme, including QA/QC sample analyses, were reported in Troisi et al. (2017, 2018)

5. Follow-Up Three months.

6. Data Management and Statistical Analysis At the end of the treatments the data collection of all patients is scheduled and the introduction of the same, in coded or clear form, in a database (Excel for windows) appropriately structured to contain all the expected items. In order to comply with the privacy law, the sensitive nominal data will be appropriately replaced by the numerical codes assigned to each patient, so that from the simple consultation of the data it will not be possible to deduce any individual direct reference. Moreover, the only data that can be extracted from the database are related to aggregated sets to be published for scientific purposes.

Data is reported as mean±standard deviation for continuous variables and number (percentage) for categorical variables.

Statistical analysis are performed using Statistica software (StatSoft, Oklahoma, USA) and Minitab (Minitab Inc, Pennsylvania, USA). Normal distribution of data is verified using the Shapiro-Wilks test. Since the data are normally distributed, the investigators use one-way ANOVA with the Tukey post hoc test for inter-group comparisons. The alpha (ɑ) value is set to 0.05. Pearson's chi-squared test is used to determine differences among groups for the categorical variables.

For multivariate data analysis, the chromatographic data are tabulated with one sample per row and one variable (metabolite) per column. Data pre-treatment consists of normalizing each metabolite peak area to that of the internal standard followed by generalized log transformation and data scaling by autoscaling (mean-centered and divide it by standard deviation of each variable). PLS-DA is performed using the statistical software package R (Foundation for Statistical Computing, Vienna, Austria). Class separation is achieved by PLS-DA, which is a supervised method that uses multivariate regression techniques to extract, via linear combinations of original variables (X), the information that can predict class membership (Y). PLS regression is performed using the plsr function included in the R pls package. Classification and cross-validation is performed using the corresponding wrapper function included in the caret package. A permutation test is performed to assess the significance of class discrimination. In each permutation, a PLS-DA model is built between the data (X) and the permuted class labels (Y) using the optimal number of components determined by cross validation for the model based on the original class assignment. Variable Importance in Projection (VIP) scores are calculated for each metabolite. The VIP score is a weighted sum of squares of the PLS loadings, taking into account the amount of explained Y-variation in each dimension. The highest scoring VIP metabolites are compared in terms of fold changes (FC). FC is the ratio of the mean abundances between any two classes and is a measure describing how much a quantity changes going from an initial to a final value.

The metabolic pathways are constructed using MetScape application of the software Cytoscape.

7. Expected Outcomes of the Study The goal of this pilot study is to identify a complex network of serum molecules that appear to be correlated with PCOS, and with a combined treatment with inositols and glucomannan.

8. Duration of the Project 24 months

Conditions

PCOS

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

Controls

Healthy subjects

Serum Metabolomics profiling

Intervention Type: OTHER

Untargeted serum metabolomics profiling

Case

PCOS affected subjects

Serum Metabolomics profiling

Intervention Type: OTHER

Untargeted serum metabolomics profiling

Interventions

Serum Metabolomics profiling

Untargeted serum metabolomics profiling

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• overweight/obesity (BMI > 25 kg/m2);
• absence of any other acute intercurrent or chronic illness;
• a positive diagnosis of PCOS according to Rotterdam criteria.

Exclusion Criteria

• Use of hormonal medications or drugs that affect insulin sensitivity (e.g., inositols or metformin) before enrollment

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 35 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

Theoreo Srl

INDUSTRY

Sponsor Role: collaborator

University of Salerno

OTHER

Sponsor Role: lead

Responsible Party

Jacopo Troisi

Ob/Gyn Clinical Research Coordinator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Jacopo Troisi, CEO

Role: PRINCIPAL_INVESTIGATOR

Theoreo Srl

References

Azziz R, Carmina E, Dewailly D, Diamanti-Kandarakis E, Escobar-Morreale HF, Futterweit W, Janssen OE, Legro RS, Norman RJ, Taylor AE, Witchel SF; Task Force on the Phenotype of the Polycystic Ovary Syndrome of The Androgen Excess and PCOS Society. The Androgen Excess and PCOS Society criteria for the polycystic ovary syndrome: the complete task force report. Fertil Steril. 2009 Feb;91(2):456-88. doi: 10.1016/j.fertnstert.2008.06.035. Epub 2008 Oct 23.

Reference Type: BACKGROUND

PMID: 18950759 (View on PubMed)

Azziz R, Woods KS, Reyna R, Key TJ, Knochenhauer ES, Yildiz BO. The prevalence and features of the polycystic ovary syndrome in an unselected population. J Clin Endocrinol Metab. 2004 Jun;89(6):2745-9. doi: 10.1210/jc.2003-032046.

Reference Type: BACKGROUND

PMID: 15181052 (View on PubMed)

Fauser BC, Tarlatzis BC, Rebar RW, Legro RS, Balen AH, Lobo R, Carmina E, Chang J, Yildiz BO, Laven JS, Boivin J, Petraglia F, Wijeyeratne CN, Norman RJ, Dunaif A, Franks S, Wild RA, Dumesic D, Barnhart K. Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group. Fertil Steril. 2012 Jan;97(1):28-38.e25. doi: 10.1016/j.fertnstert.2011.09.024. Epub 2011 Dec 6.

Reference Type: BACKGROUND

PMID: 22153789 (View on PubMed)

Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group. Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome. Fertil Steril. 2004 Jan;81(1):19-25. doi: 10.1016/j.fertnstert.2003.10.004.

Reference Type: BACKGROUND

PMID: 14711538 (View on PubMed)

Sortino MA, Salomone S, Carruba MO, Drago F. Polycystic Ovary Syndrome: Insights into the Therapeutic Approach with Inositols. Front Pharmacol. 2017 Jun 8;8:341. doi: 10.3389/fphar.2017.00341. eCollection 2017.

Reference Type: BACKGROUND

PMID: 28642705 (View on PubMed)

Troisi J, Sarno L, Landolfi A, Scala G, Martinelli P, Venturella R, Di Cello A, Zullo F, Guida M. Metabolomic Signature of Endometrial Cancer. J Proteome Res. 2018 Feb 2;17(2):804-812. doi: 10.1021/acs.jproteome.7b00503. Epub 2018 Jan 2.

Reference Type: BACKGROUND

PMID: 29235868 (View on PubMed)

Troisi J, Cinque C, Giugliano L, Symes S, Richards S, Adair D, Cavallo P, Sarno L, Scala G, Caiazza M, Guida M. Metabolomic change due to combined treatment with myo-inositol, D-chiro-inositol and glucomannan in polycystic ovarian syndrome patients: a pilot study. J Ovarian Res. 2019 Mar 23;12(1):25. doi: 10.1186/s13048-019-0500-x.

Reference Type: DERIVED

PMID: 30904021 (View on PubMed)

Other Identifiers

PCOS-01

Identifier Type: -

Identifier Source: org_study_id