NCT06279780

Brief Summary

It has been suggested that individuals with the condition known as metabolically healthy obesity (MHO) may not have the same increased risk of developing metabolic abnormalities as their non-metabolically healthy counterparts. In addition, to date, the identification of metabolic biomarkers and microbiota underlying the MHO state is limited. In this study, our goal is to provide insight into the underlying metabolic pathways affected by obesity. To achieve this, we will compare the metabolic profile, inflammatory parameters and mitochondrial function, as well as metabolomic analysis and differential expression of microbiota in obese patients categorized as metabolically healthy vs. non healthy. In parallel, the effect of a hypocaloric diet on obese subjects' metabolism and microbiota will be assessed to approve their use in the treatment of said disorder. Specifically, we propose an observational, clinical-basic, comparative and interventional study in a population of 80 obese (BMI\>35 kg/m2) patients clustered in two groups according to the presence or absence of altered metabolism (altered fasting glycemia, hypertension, atherogenic dyslipidemia). Anthropometric and clinical variables and biological samples (serum, plasma, peripheral blood cells and feces) will be collected for the determination of biochemical parameters (glucose, lipid and hormonal profile by enzymatic techniques) and protein-based peripheral biomarkers of mitochondrial function \[total and mitochondrial reactive oxygen species (ROS) production, mitochondrial membrane potential, glutathione levels by static cytometry\], markers of mitochondrial dynamics \[Mitofusin 1 (MFN1), Mitofusin 2 (MFN2), Mitochondrial fision protein 1 (FIS1) and Dynamin-related protein 1 (DRP1) by RT-PCR and Western Blot\], markers of inflammation \[Interleukin 6 (IL6), Tumoral necrosis factor alpha (TNFα), IL1b, adiponectin, resistin, plasminogen activator inhibitor 1 (PAI-1), Monocyte chemoattractant protein-1 (MCP-1), caspase 1 and NLRP3 by Western Blot and technology XMAP), metabolomic assay (NMR spectroscopy and PLS-DA), as well as gut microbiota content and diversity (16S rRNA, MiSeq sequencing). Finally, we will evaluate the effect of a dietary weight loss intervention on these biomarkers.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
109

participants targeted

Target at P50-P75 for not_applicable

Timeline
Completed

Started Jan 2019

Longer than P75 for not_applicable

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

January 1, 2019

Completed
5 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2023

Completed
1 month until next milestone

First Submitted

Initial submission to the registry

February 2, 2024

Completed
26 days until next milestone

First Posted

Study publicly available on registry

February 28, 2024

Completed
6 months until next milestone

Study Completion

Last participant's last visit for all outcomes

August 31, 2024

Completed
Last Updated

February 27, 2025

Status Verified

February 1, 2024

Enrollment Period

5 years

First QC Date

February 2, 2024

Last Update Submit

February 25, 2025

Conditions

Keywords

metabolic syndromeVery low-calorie dietMicrobiotaoxidative stressInflammation

Outcome Measures

Primary Outcomes (2)

  • Analyze the changes in the diversity of the intestinal microbiota after dietetic intervention.

    To assess the alpha-diversity of the intestinal microbiota, defined as the average diversity of species in an ecosystem, the Shannon index will be used. The results are interpreted as follows: values less than 2 are considered low in diversity and values greater than 3 are high in species diversity.

    5 years

  • Evaluate the differences in the diversity of the intestinal microbiota depending on whether patients present metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUHO).

    To asses the differences in alpha-diversity of the intestinal microbiota in both groups, it will be evaluated whether there are significant differences between the Shannon indices of the two groups. The classification of patients between MHO and MUHO will be carried out using the following criteria: MUHO will be considered when patients with obesity present ≥2 metabolic abnormalities, and MHO with ≤1 metabolic abnormalities; the following cardiovascular risk factors are considered metabolic abnormalities: elevated blood pressure (defined as either SBP ≥130 mm Hg, DBP ≥85 mm Hg, or treatment with antihypertensive medications), elevated triglycerides (as fasting triglyceride concentration ≥1.7 mmol/l), low HDL-C levels (defined as HDL-C \<1.04 mmol/l, in men, \<1.29 mmol/l/l in women, or treatment with lipid-lowering medications), dysglycemia (fasting plasma glucose 5.6 to 6.9 mmol/l, and/or and insulin resistance as HOMA-IR \>3.8).

    5 years

Secondary Outcomes (15)

  • Evaluate significant changes in body fat mass percentage after the dietetic intervention.

    2 years

  • Assess significant changes in high-sensitivity C-reactive protein (hs-CRP) as an inflammatory parameter after the dietetic intervention.

    2 years

  • Evaluate significant changes in C3 protein as an inflammatory parameter after the dietetic intervention.

    2 years

  • Assess significant changes in plasmatic homocysteine as an inflammatory parameter after the dietetic intervention.

    2 years

  • Evaluate significant changes in interleukin 1-beta (IL-1B) levels as a pro-inflammatory molecule after the dietetic intervention.

    2 years

  • +10 more secondary outcomes

Study Arms (1)

Very low-calorie diet Intervention

EXPERIMENTAL
Dietary Supplement: very low-calorie diet

Interventions

very low-calorie dietDIETARY_SUPPLEMENT

Subjects undergo two cycles of a very-low-calorie diet (VLCD) for 6 weeks each, alternating with a hypocaloric diet (12 weeks). The dietetic intervention consists of a VLCD using a liquid formula (Optisource Plus, Nestlé S.A., Vevey, Switzerland), providing 52.8 g protein, 75.0 g carbohydrates, 13.5 g fat, 11.4 g fiber, and essential vitamins and minerals based on Recommended Dietary Allowances (RDA). This formula supplies 2738 kJ/day (654 kcal/day), replacing the participants' three daily meals. Following this and before the second VLCD cycle, a dietician performs an individualized nutritional assessment to calculate the resting energy expenditure, and personalized hypocaloric diets were prepared, reducing 500 kcal for each individual on their daily caloric expenditure, maintaining the recommended intake of each of the macronutrients (55% carbohydrates, 30% fats and 15% proteins) for 12-weeks.

Also known as: VLCD
Very low-calorie diet Intervention

Eligibility Criteria

Age18 Years - 60 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64)

You may qualify if:

  • Patients with BMI≥30kg/m2, with at least 5 years of diagnosed obesity evolution.
  • Patients have had stable body weight (±2 kg) during the 3 months prior to the study.

You may not qualify if:

  • All patients with acute or chronic inflammatory diseases, neoplasic disease, secondary causes of obesity (uncontrolled hypothyroidism, Cushing's syndrome), and established liver and kidney failure (according to transaminase levels ±2 SD of the mean and estimated glomerular filtration rate using the CKD-EPI formula \>60) will be excluded.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

FISABIO

Valencia, Valencia, 46020, Spain

Location

Related Publications (33)

  • Smith KB, Smith MS. Obesity Statistics. Prim Care. 2016 Mar;43(1):121-35, ix. doi: 10.1016/j.pop.2015.10.001. Epub 2016 Jan 12.

    PMID: 26896205BACKGROUND
  • Lagerros YT, Rossner S. Obesity management: what brings success? Therap Adv Gastroenterol. 2013 Jan;6(1):77-88. doi: 10.1177/1756283X12459413.

    PMID: 23320052BACKGROUND
  • Gomez-Ambrosi J, Silva C, Galofre JC, Escalada J, Santos S, Millan D, Vila N, Ibanez P, Gil MJ, Valenti V, Rotellar F, Ramirez B, Salvador J, Fruhbeck G. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J Obes (Lond). 2012 Feb;36(2):286-94. doi: 10.1038/ijo.2011.100. Epub 2011 May 17.

    PMID: 21587201BACKGROUND
  • Tchernof A, Despres JP. Pathophysiology of human visceral obesity: an update. Physiol Rev. 2013 Jan;93(1):359-404. doi: 10.1152/physrev.00033.2011.

    PMID: 23303913BACKGROUND
  • Stefan N, Haring HU, Hu FB, Schulze MB. Metabolically healthy obesity: epidemiology, mechanisms, and clinical implications. Lancet Diabetes Endocrinol. 2013 Oct;1(2):152-62. doi: 10.1016/S2213-8587(13)70062-7. Epub 2013 Aug 30.

    PMID: 24622321BACKGROUND
  • Phillips CM. Metabolically healthy obesity across the life course: epidemiology, determinants, and implications. Ann N Y Acad Sci. 2017 Mar;1391(1):85-100. doi: 10.1111/nyas.13230. Epub 2016 Oct 10.

    PMID: 27723940BACKGROUND
  • Primeau V, Coderre L, Karelis AD, Brochu M, Lavoie ME, Messier V, Sladek R, Rabasa-Lhoret R. Characterizing the profile of obese patients who are metabolically healthy. Int J Obes (Lond). 2011 Jul;35(7):971-81. doi: 10.1038/ijo.2010.216. Epub 2010 Oct 26.

    PMID: 20975726BACKGROUND
  • Naukkarinen J, Heinonen S, Hakkarainen A, Lundbom J, Vuolteenaho K, Saarinen L, Hautaniemi S, Rodriguez A, Fruhbeck G, Pajunen P, Hyotylainen T, Oresic M, Moilanen E, Suomalainen A, Lundbom N, Kaprio J, Rissanen A, Pietilainen KH. Characterising metabolically healthy obesity in weight-discordant monozygotic twins. Diabetologia. 2014 Jan;57(1):167-76. doi: 10.1007/s00125-013-3066-y. Epub 2013 Oct 8.

    PMID: 24100782BACKGROUND
  • Plourde G, Karelis AD. Current issues in the identification and treatment of metabolically healthy but obese individuals. Nutr Metab Cardiovasc Dis. 2014 May;24(5):455-9. doi: 10.1016/j.numecd.2013.12.002. Epub 2014 Jan 12.

    PMID: 24529490BACKGROUND
  • Velho S, Paccaud F, Waeber G, Vollenweider P, Marques-Vidal P. Metabolically healthy obesity: different prevalences using different criteria. Eur J Clin Nutr. 2010 Oct;64(10):1043-51. doi: 10.1038/ejcn.2010.114. Epub 2010 Jul 14.

    PMID: 20628408BACKGROUND
  • Fruhbeck G, Gomez-Ambrosi J. Rationale for the existence of additional adipostatic hormones. FASEB J. 2001 Sep;15(11):1996-2006. doi: 10.1096/fj.00-0829hyp.

    PMID: 11532980BACKGROUND
  • Mangge H, Zelzer S, Puerstner P, Schnedl WJ, Reeves G, Postolache TT, Weghuber D. Uric acid best predicts metabolically unhealthy obesity with increased cardiovascular risk in youth and adults. Obesity (Silver Spring). 2013 Jan;21(1):E71-7. doi: 10.1002/oby.20061. Epub 2013 Jan 29.

    PMID: 23401248BACKGROUND
  • Messier V, Karelis AD, Robillard ME, Bellefeuille P, Brochu M, Lavoie JM, Rabasa-Lhoret R. Metabolically healthy but obese individuals: relationship with hepatic enzymes. Metabolism. 2010 Jan;59(1):20-4. doi: 10.1016/j.metabol.2009.06.020. Epub 2009 Aug 25.

    PMID: 19709695BACKGROUND
  • Gaye A, Doumatey AP, Davis SK, Rotimi CN, Gibbons GH. Whole-genome transcriptomic insights into protective molecular mechanisms in metabolically healthy obese African Americans. NPJ Genom Med. 2018 Jan 29;3:4. doi: 10.1038/s41525-018-0043-x. eCollection 2018.

    PMID: 29387454BACKGROUND
  • Hotamisligil GS. Inflammation and metabolic disorders. Nature. 2006 Dec 14;444(7121):860-7. doi: 10.1038/nature05485.

    PMID: 17167474BACKGROUND
  • Gregor MF, Hotamisligil GS. Thematic review series: Adipocyte Biology. Adipocyte stress: the endoplasmic reticulum and metabolic disease. J Lipid Res. 2007 Sep;48(9):1905-14. doi: 10.1194/jlr.R700007-JLR200. Epub 2007 May 9.

    PMID: 17699733BACKGROUND
  • Hotamisligil GS. Endoplasmic reticulum stress and the inflammatory basis of metabolic disease. Cell. 2010 Mar 19;140(6):900-17. doi: 10.1016/j.cell.2010.02.034.

    PMID: 20303879BACKGROUND
  • Olefsky JM, Glass CK. Macrophages, inflammation, and insulin resistance. Annu Rev Physiol. 2010;72:219-46. doi: 10.1146/annurev-physiol-021909-135846.

    PMID: 20148674BACKGROUND
  • Howard JK, Flier JS. Attenuation of leptin and insulin signaling by SOCS proteins. Trends Endocrinol Metab. 2006 Nov;17(9):365-71. doi: 10.1016/j.tem.2006.09.007. Epub 2006 Sep 28.

    PMID: 17010638BACKGROUND
  • Lebrun P, Van Obberghen E. SOCS proteins causing trouble in insulin action. Acta Physiol (Oxf). 2008 Jan;192(1):29-36. doi: 10.1111/j.1748-1716.2007.01782.x.

    PMID: 18171427BACKGROUND
  • Cai D, Yuan M, Frantz DF, Melendez PA, Hansen L, Lee J, Shoelson SE. Local and systemic insulin resistance resulting from hepatic activation of IKK-beta and NF-kappaB. Nat Med. 2005 Feb;11(2):183-90. doi: 10.1038/nm1166. Epub 2005 Jan 30.

    PMID: 15685173BACKGROUND
  • Kogelman LJ, Fu J, Franke L, Greve JW, Hofker M, Rensen SS, Kadarmideen HN. Inter-Tissue Gene Co-Expression Networks between Metabolically Healthy and Unhealthy Obese Individuals. PLoS One. 2016 Dec 1;11(12):e0167519. doi: 10.1371/journal.pone.0167519. eCollection 2016.

    PMID: 27907186BACKGROUND
  • Esser N, L'homme L, De Roover A, Kohnen L, Scheen AJ, Moutschen M, Piette J, Legrand-Poels S, Paquot N. Obesity phenotype is related to NLRP3 inflammasome activity and immunological profile of visceral adipose tissue. Diabetologia. 2013 Nov;56(11):2487-97. doi: 10.1007/s00125-013-3023-9. Epub 2013 Sep 7.

    PMID: 24013717BACKGROUND
  • Zorzano A, Claret M. Implications of mitochondrial dynamics on neurodegeneration and on hypothalamic dysfunction. Front Aging Neurosci. 2015 Jun 10;7:101. doi: 10.3389/fnagi.2015.00101. eCollection 2015.

    PMID: 26113818BACKGROUND
  • Westermann B. Mitochondrial fusion and fission in cell life and death. Nat Rev Mol Cell Biol. 2010 Dec;11(12):872-84. doi: 10.1038/nrm3013.

    PMID: 21102612BACKGROUND
  • Armitage EG, Rupérez FJ, Barbas C. Metabolomics of diet-related diseases using mass spectrometry. Trends Analyt Chem. 2013; 52: 61-73.

    BACKGROUND
  • Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, Haqq AM, Shah SH, Arlotto M, Slentz CA, Rochon J, Gallup D, Ilkayeva O, Wenner BR, Yancy WS Jr, Eisenson H, Musante G, Surwit RS, Millington DS, Butler MD, Svetkey LP. A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab. 2009 Apr;9(4):311-26. doi: 10.1016/j.cmet.2009.02.002.

    PMID: 19356713BACKGROUND
  • Fiehn O, Garvey WT, Newman JW, Lok KH, Hoppel CL, Adams SH. Plasma metabolomic profiles reflective of glucose homeostasis in non-diabetic and type 2 diabetic obese African-American women. PLoS One. 2010 Dec 10;5(12):e15234. doi: 10.1371/journal.pone.0015234.

    PMID: 21170321BACKGROUND
  • Suhre K, Meisinger C, Doring A, Altmaier E, Belcredi P, Gieger C, Chang D, Milburn MV, Gall WE, Weinberger KM, Mewes HW, Hrabe de Angelis M, Wichmann HE, Kronenberg F, Adamski J, Illig T. Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting. PLoS One. 2010 Nov 11;5(11):e13953. doi: 10.1371/journal.pone.0013953.

    PMID: 21085649BACKGROUND
  • Wiklund PK, Pekkala S, Autio R, Munukka E, Xu L, Saltevo J, Cheng S, Kujala UM, Alen M, Cheng S. Serum metabolic profiles in overweight and obese women with and without metabolic syndrome. Diabetol Metab Syndr. 2014 Mar 20;6(1):40. doi: 10.1186/1758-5996-6-40.

    PMID: 24650495BACKGROUND
  • Chen HH, Tseng YJ, Wang SY, Tsai YS, Chang CS, Kuo TC, Yao WJ, Shieh CC, Wu CH, Kuo PH. The metabolome profiling and pathway analysis in metabolic healthy and abnormal obesity. Int J Obes (Lond). 2015 Aug;39(8):1241-8. doi: 10.1038/ijo.2015.65. Epub 2015 Apr 24.

    PMID: 25907313BACKGROUND
  • Gao X, Zhang W, Wang Y, Pedram P, Cahill F, Zhai G, Randell E, Gulliver W, Sun G. Serum metabolic biomarkers distinguish metabolically healthy peripherally obese from unhealthy centrally obese individuals. Nutr Metab (Lond). 2016 May 12;13:33. doi: 10.1186/s12986-016-0095-9. eCollection 2016.

    PMID: 27175209BACKGROUND
  • Grau-Del Valle C, Bosch-Sierra N, Hermo-Argibay A, Lopez-Domenech S, Rocha M, Victor VM, Morillas C, Rovira-Llopis S, Banuls C. Weight loss increases circadian gene expression and emotional well-being in individuals with obesity. Front Nutr. 2025 Nov 26;12:1722428. doi: 10.3389/fnut.2025.1722428. eCollection 2025.

MeSH Terms

Conditions

Metabolic SyndromeInflammation

Condition Hierarchy (Ancestors)

Insulin ResistanceHyperinsulinismGlucose Metabolism DisordersMetabolic DiseasesNutritional and Metabolic DiseasesPathologic ProcessesPathological Conditions, Signs and Symptoms

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
TREATMENT
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
SPONSOR INVESTIGATOR
PI Title
Principal Investigator

Study Record Dates

First Submitted

February 2, 2024

First Posted

February 28, 2024

Study Start

January 1, 2019

Primary Completion

December 31, 2023

Study Completion

August 31, 2024

Last Updated

February 27, 2025

Record last verified: 2024-02

Data Sharing

IPD Sharing
Will not share

Locations