Network Medicine, Epigenetics and Obesity

NCT03903757 | Unknown

• 1 other identifier: PRIN2017F8ZB89
• Study Type: observational
• Target: 100
• Locations: 0 countries
• Sites: N/A

Brief Summary

The prevalence of obesity is increasing and affects more than 650 million people of all ages to become one of the foremost global health threats. Obesity is a complex syndrome that can seriously impair health through a broad range of complications such as cardiovascular disease, type 1 and 2 diabetes (T1D and T2D), cancer, musculoskeletal disorders, psychosocial imbalances, and reduced quality of life, and impacts the treatment of other conditions. Weight reduction has been shown to have a positive effect on these co-morbidities and may increase the effectiveness of treatments specific for other co-morbidities. Lifestyle modification is an integral part of the weight management journey, but is often insufficient on its own, and can be complimented by pharmacological and surgical add-on treatments to achieve greater and more sustainable weight loss, as appropriate. It is likely that there are subgroups of patients that are more suited to certain types of treatment and results risk dilution of perceived efficacy unless these groups are identified and treatment is personalised. The aim of this project is to identify pathophysiologically and clinically meaningful subgroups of obesity by performing Next Generation Sequencing (NGS) approaches and network based algorithm that will allow the optimisation of prevention and treatment of obesity and its complications.

Conditions

Obesity; Type2 Diabetes

Keywords

Epigenetics; Network medicine; Personalized therapy

Outcome Measures

Primary Outcomes (3)

• DNA methylation pattern in adipose tissues

  Using Methylation 27K BeadChip platform based on Bisulfite conversion technology, DNA methylation profile in adipose tissues of 25 preselected obese subject and 25 obese subjects respect with controls (n=50) will be performed.

  3 months

• Bioinformatics analysis to predict putative novel candidate genes underlying obesity phenotype

  The network-based algorithm "Weighted Human DNA methylation PPI network (WMPN)" will be applied to methylome data in order to obtain a disease module containing the crucial differentially methylated genes both in obese patients and obese patients with T2D compared to controls.

  6 months

• RNA sequencing analysisin adipose tissues

  RNA sequencing analysis by using Illumina HiSeq2000 Next Generatin Sequencing (NGS) platform will be performed for identifying differentially expressed micro-RNA and mRNA target both in obese patients and obese patients with T2D compared to controls.

  3 months

Secondary Outcomes (4)

• ROC curves analysis to evaluate putative DNA methylation/microRNA interactions

  12 months

• Linear regression analysis and BMI (Kg/m2).

  12 months

• Linear regression to correlate epigenetic biomarkers with proinflammatory cytokines

  12 months

• Linear regression to correlate epigenetic biomarkers with HOMA index

  12 months

Study Arms (2)

Obese subjects with and without T2D

Other: DNA methylome and total RNA sequencing

control subjects

Other: DNA methylome and total RNA sequencing

Interventions

DNA methylome and total RNA sequencing OTHER

Epigenomics tools combined with bioinformatic analysis to correlate putative useful clinical biomarkers with clinical features

Obese subjects with and without T2D; control subjects

Eligibility Criteria

• Age: 18 Years - 60 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Subcutaneous adipose tissues located in the surgical incision will be withdrawn without the use of surgical devices in order to avoid the degradation of the biological sample from 50 obese subjects (25 obese subjects with Type 2 Diabetes vs 25 obese subjects without Type 2 Diabetes) undergoing bariatric surgery. As controls (n=50) we will recruit subcutaneous adipose tissues from patients without a clinical history of cardiovascular or dysmetabolic diseases undergoing to surgery for stress inguinal hernia.

You may qualify if:

• Meets the current American Diabetes Association guideline for diagnosis of diabetes (Diabetic group) and obesity
• Must be willing and able to comply with study requirements
• Must indicate their understanding of the study and willingness to participate by signing an appropriate informed consent form

You may not qualify if:

• History of cancer
• Malignancy disorders
• Active infections
• Chronic or immune-mediated diseases
• Primary disease requiring surgical intervention
• Unable to comply with the complication screening
• Less than 18 y of age
• Pregnant or are planning to become pregnant during the duration of the investigation
• Life expectancy \<12 m
• Currently participating in any other clinical investigation

Sponsors & Collaborators

• University of Campania Luigi Vanvitelli: lead

Biospecimen

Retention: SAMPLES WITH DNA

Subcutaneous adipose tissue

MeSH Terms

Conditions

Obesity

Interventions

Epigenome; Base Sequence

Condition Hierarchy (Ancestors)

Overweight; Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Intervention Hierarchy (Ancestors)

Genome; Genetic Structures; Genetic Phenomena; Molecular Structure; Biochemical Phenomena; Chemical Phenomena

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: March 31, 2019
• First Posted: April 4, 2019
• Study Start: December 1, 2019
• Primary Completion: June 1, 2020
• Study Completion: June 1, 2021
• Last Updated: September 18, 2019

Record last verified: 2019-09

Data Sharing

• IPD Sharing: Will not share