Integrated Multi-omics Data for Personalized Treatment of Obesity-associated Fatty Liver Disease

NCT ID: NCT05554224

Last Updated: 2024-11-13

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

1104 participants

Study Classification

OBSERVATIONAL

Study Start Date

2008-06-25

Study Completion Date

2028-12-31

Brief Summary

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The investigators seek to analyze the samples provided by patients with obesity-associated fatty liver disease at the multi-omics level and to integrate the results with clinical information, genotypic variants, and factors influencing inter-organ crosstalk. The main aim is to improve the interpretation of fatty liver disease associated with obesity and diabetes by developing predictive models built with algorithms from artificial intelligence. The challenge is to decipher the flow of information by exploring contributing factors, proximate causes of regulatory defects, and maladaptive responses that may promote therapeutic approaches.

Detailed Description

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The investigators study the most prevalent liver disease in the history of humankind, which is the leading cause of liver transplantation in its severe forms. It results from two silent pandemics with enormous health impacts: obesity and diabetes. Together or separately, they affect more than 30% of the world's population. The current term for the disease is MAFLD (metabolic (dysfunction)-associated fatty liver disease). This designation indicates that metabolic disorders related to obesity, diabetes, dyslipidemia, and hypertension are its primary cause. These disorders are related and lead to fat accumulation in the liver, the first step in a broad spectrum of chronic liver diseases. These diseases respond clinically in a very variable way and remain undiagnosed and untreated for a long time. There is no accepted pharmacological treatment, and lifestyle changes, although possibly effective, usually fail because they require particularly favorable conditions. Therefore, the identified problems that should be solve are:

(1) The diagnosis of MAFLD requires a liver biopsy, a costly and aggressive procedure. (2) Without examining the liver, clinicians can know little about the progression of the disease and the underlying causes. (3) The results in experimental models can be informative but difficult to translate to the clinic. Recent reports suggest the essential role of phospholipid biosynthesis and transport between the endoplasmic reticulum and mitochondria. (4) All of the above makes it difficult to obtain the necessary information to propose changes in clinical guidelines.

Considering these aspects, patients with morbid obesity can be an informative human model. Among other advantages, patients have surgical options that allow us to obtain portions of affected organs that facilitate specific diagnosis and that, because they require constant care, can be studied on an ongoing basis. The presented approach can improve patient care and essentially consists of identifying the most significant number of variables that can help. In particular, here are proposed the inclusion of variables that can already be obtained from recent advances in the laboratory, encompassed within the omics sciences (genomics, transcriptomics, proteomics, metabolomics, lipidomics, microbiomics). Each of these has its advantages and limitations. Predictive models can integrate these variables into clinical data to explore organ crosstalk.

Conditions

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NAFLD Obesity, Morbid Comorbidities and Coexisting Conditions

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Severe obesity without liver disease

Patients with severe obesity who did not meet the criteria described in Kleiner et al. (2005) for nonalcoholic steatohepatitis diagnosis (score 0-2).

To propose diagnostic tests for liver diseases before surgical decisions.

Intervention Type DIAGNOSTIC_TEST

Observational although patients are candidates for metabolic surgery.

Severe obesity with liver disease without criteria for steatohepatitis

Patients with severe obesity who did not meet the criteria described in Kleiner et al. (2005) for nonalcoholic steatohepatitis diagnosis, but their biopsies presented some liver severity (scores 3 and 4).

To propose diagnostic tests for liver diseases before surgical decisions.

Intervention Type DIAGNOSTIC_TEST

Observational although patients are candidates for metabolic surgery.

Severe obesity with well-defined steatohepatitis and/or cirrhosis

Patients with severe obesity who met the criteria described in Kleiner et al. (2005) for nonalcoholic steatohepatitis diagnosis (score 5-8).

To propose diagnostic tests for liver diseases before surgical decisions.

Intervention Type DIAGNOSTIC_TEST

Observational although patients are candidates for metabolic surgery.

Interventions

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To propose diagnostic tests for liver diseases before surgical decisions.

Observational although patients are candidates for metabolic surgery.

Intervention Type DIAGNOSTIC_TEST

Other Intervention Names

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External follow up monitoring liver diseases and weight loss.

Eligibility Criteria

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Inclusion Criteria

* Body mass index greater or equal to 40 kg/m\^2.
* Body mass index between 35 and 40 kg/m\^2 with high-risk comorbidities (diagnosis or treatment for hypertension, dyslipidemia, or type 2 diabetes mellitus).
* Positive psychiatric evaluation.
* Age greater or equal to 18 years old.

Exclusion Criteria

* Legal or illegal drug consumption, including alcohol.
* Diagnosis of Hepatitis.
* Current cancer diagnosis or treatment.
* Clinical or analytical evidence of severe illness.
* Clinical or analytical evidence of chronic or acute inflammation.
* Clinical or analytical evidence of infectious diseases.
* Clinical or analytical evidence of terminal illness.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Hospital Universitari Sant Joan

UNKNOWN

Sponsor Role collaborator

La Caixa Foundation

OTHER

Sponsor Role collaborator

Instituto de Salud Carlos III

OTHER_GOV

Sponsor Role collaborator

University of Barcelona

OTHER

Sponsor Role collaborator

Institut Investigacio Sanitaria Pere Virgili

OTHER

Sponsor Role lead

Responsible Party

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Jorge Joven

Professor of Medicine at the Rovira i Virgili University

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Jorge Joven, Professor

Role: PRINCIPAL_INVESTIGATOR

Institut Investigacio Sanitaria Pere Virgili

Locations

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Hospital Universitari Sant Joan

Reus, Tarragona, Spain

Site Status RECRUITING

Countries

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Spain

Central Contacts

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Jorge Joven, Professor

Role: CONTACT

+34977310300 ext. 55409

Helena Castañé, MSc

Role: CONTACT

+34977310300 ext. 55409

Facility Contacts

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Jorge Joven, Professor

Role: primary

+34977310300 ext. 55409

Jorge Joven, Professor

Role: backup

Daniel del Castillo, Professor

Role: backup

Jordi Camps, PhD

Role: backup

Isabel Fort-Gallifa, PhD

Role: backup

Anna Hernández-Aguilera, PhD

Role: backup

Marta Paris, PhD

Role: backup

Gerard Baiges-Gaya, MSc

Role: backup

Elisabet Rodríguez-Tomàs, MSc

Role: backup

Jordi Riu, PhD

Role: backup

Adria Cereto-Massague, PhD

Role: backup

Helena Castañé, MSc

Role: backup

Andrea Jiménez-Franco, MSc

Role: backup

Alina-Iuliana Onoiu, MSc

Role: backup

References

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Jimenez-Franco A, Castane H, Martinez-Navidad C, Placed-Gallego C, Hernandez-Aguilera A, Fernandez-Arroyo S, Samarra I, Canela-Capdevila M, Arenas M, Zorzano A, Hernandez-Alvarez MI, Castillo DD, Paris M, Menendez JA, Camps J, Joven J. Metabolic adaptations in severe obesity: Insights from circulating oxylipins before and after weight loss. Clin Nutr. 2024 Jan;43(1):246-258. doi: 10.1016/j.clnu.2023.12.002. Epub 2023 Dec 6.

Reference Type DERIVED
PMID: 38101315 (View on PubMed)

Other Identifiers

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EPIMET

Identifier Type: OTHER

Identifier Source: secondary_id

EOM study

Identifier Type: -

Identifier Source: org_study_id

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