Individual Factors Related to Chronic Low-grade Inflammation and Cardiometabolic Disease Risk (PINEAPPL)

Integrative and Personalized Lifestyle Approach to Reduce Low-Grade Inflammation in People at Risk of Cardiometabolic Diseases

The goal of this observational study is to learn about low-grade inflammation in healthy individuals and individuals with overweight or obesity.

The main questions it aims to answer are:

• Whether it is possible to predict low-grade inflammation
• What are the medical, biological, and lifestyle variables related to low-grade inflammation?

Participants will be asked to:

1. Attend a general medical visit to collect vital signs, anthropometric measurements, and collect blood samples.
2. Complete questionnaires and collect a stool sample at home.

Study Overview

• Status: Not yet recruiting
• Conditions: Hypertension; Healthy; Obesity; Overweight; Metabolic Syndrome; Hypercholesterolemia; Risk Factor, Cardiovascular; Abdominal Obesity; Normal Weight Adults; Low-grade Inflammation; Metabolically Healthy Controls

Detailed Description

Cardiometabolic diseases (CMDs) are a heterogeneous spectrum of nutrition-related chronic diseases, ranging from obesity to diabetes and, ultimately, to acute and chronic cardiovascular diseases. Once established, these diseases are usually irreversible and evolve over time. Since these diseases are born out of societal and lifestyle changes, the cornerstones of prevention and management are changes in nutrition and lifestyle. This inevitable increase in CMDs, including obesity, particularly affects socially vulnerable populations.

The etiology of cardiometabolic diseases is complex and involves environmental, biological and genetic elements. Weight gain is at the heart of these pathologies: it frequently precedes their development or contributes to the progression of these diseases. To this end, even modest weight loss is suggested as an important line of prevention or treatment of cardiometabolic diseases. For example, diabetes remission can be achieved with weight loss and is directly correlated with the amount of weight lost. Despite the beneficial effects of weight loss on preventing the progression of cardiometabolic diseases, maintaining weight loss is difficult, with only 30% of individuals achieving long-term weight loss (5 years). The same is true with the development of anti-obesity treatments (new analogues of glucagon-like peptide 1 (GLP1)); Discontinuation of treatment is accompanied by weight gain. In the case of diabetes, weight gain is associated with the recurrence of previously remitted diabetes.

Chronic low-grade inflammation is tightly linked with obesity and a central feature of cardiometabolic diseases and associated diseases. Furthermore, it paves the way for future comorbidities. This inflammation is characterized by a rise of systemic or circulating inflammatory molecules. However, no single cytokine can reflect the inflammatory state seen in cardiometabolic diseases and these systemic factors are highly variable from subject to subject. Recently, combinatorial indexes, using multiple inflammatory markers have been strongly associated with coronary risks and Metabolic alterations.

Over the past 10 years, the gut microbiome has become a recognized contributor to our metabolic health. Accumulating evidence has shown that the gut microbiome strongly reflects environmental and lifestyle changes (including nutrition) by altering its diversity and composition as well as its functions by producing molecules that interact with host organs, including the brain. The excess or deficit production of molecules produced by the microbiota, bacterial metabolites (such as trimethylamine oxide (TMAO), Imidazole propionate, branched-chain amino acids (BCAAs), or short-chain fatty acids (SCFAs), etc.) are molecules implicated in the link between the environment, microbiota and metabolic and inflammatory disturbances.

Current strong evidence indicates that the gut microbiota is altered early in people with inflammatory diseases that include CMDs. Relationships between the inflammatory component of the diet and the gut microbiome have also been identified.

In an effort to predict chronic-low grade inflammation in a real-world population and decipher the relationships between chronic low-grade inflammation and individual factors, comprising lifestyle, diet, behavior, environment, the gut microbiome, and health-related clinical data, the present study recruits a cohort of participants across age, sex, body mass index, and metabolic health spectra. Chronic low-grade inflammation markers of interest will be measured to establish a multi-component index of inflammation relative in the population.

• Study Type: Observational
• Enrollment (Estimated): 3000

Contacts and Locations

• Study Contact: Name: Karine Clément, MD, PhD; Phone Number: 33142177031; Email: karine.clement@aphp.fr

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Existing or new patients with overweight or obesity from primary care at La Pitié-Salpetriere Hospital in Paris, Marseille Public Hospital, Colmar Civil Hospital, Bordeaux University Hospital.

Healthy volunteers throughout France.

Description

Inclusion Criteria:

• Male or female between the ages of 18 and 70 included,
• One of the following two criteria:
• Clinically at-risk group Body Mass Index between 25 (included) and up to 35 kg/m2 (excluded)
• Non-clinically at-risk group Body Mass Index between 18.5 (included) and up to 25 kg/m2 (excluded) and absence of metabolic syndrome criteria
• Subject covered by social security or a similar system.
• Ability to use a mobile phone application on a daily basis (food intake).
• Subject, after being informed of the contents of this study, fully understanding and accepting its purpose; and able to personally sign a written informed consent

Exclusion Criteria:

• Subject with diagnosed inflammatory disease or infection-related inflammation (viral or bacterial) or medical history (viral) within the last 2 months:
• Rheumatoid arthritis, reactive or psoriatic arthritis (non-osteoarthritis)
• Inflammatory bowel disease (IBD) (Crohn's disease or ulcerative colitis) or irritable bowel syndrome
• Systemic lupus erythematosus
• Uncontrolled psoriasis
• Viral hepatitis or ongoing viral infection
• Seasonal virus (influenza-like illness)
• Subjects who have taken antibiotics in the last 2 months
• Subject under treatment within the last 2 months of an:
• Antiviral (for HIV, hepatitis, influenza, chickenpox/shingles)
• Oral, topical, or injectable treatment of a drug that modulates the inflammatory response (e.g. Corticosteroid, non-steroidal anti-inflammatory drugs (e.g. ibuprofen, diclofenac, celecoxib, naproxen, aspirin, etc.)
• Dietary supplement that can modulate the inflammatory response (e.g.
• Omega 3 fatty acid, curcuma/turmeric, probiotic, prebiotics)
• Subject with diabetes (type 1 or 2) known treated prior to the inclusion visit (specifically subjects recently diagnosed or diagnosed with diabetes at the time of the laboratory assessment may be retained in the study if they are not taking anti-diabetic treatment): i.e. exclusion of subject with diabetes diagnosed with fasting blood glucose ≥ 126 mg/dL (7.0 mmol measured twice/L OR glycated hemoglobin ≥ 6.5% (48 mmol/mol) AND anti-diabetic therapy (metformin, GLP-1 receptor agonist, insulin, sulphonylurea, alpha-glucosidase inhibitor)
• Subject with severe or unstable hepatic, renal, cardiovascular, respiratory, endocrine, or metabolic disorders or cancer diagnosed with or without treatment
• Subject suffering from gastrointestinal disorders resulting in the use of laxatives or drugs for intestinal transit (e.g., loperamide) in the last 2 months.
• Subject with a complication or procedure in the last 2 months that could result in inflammation
• Minor or acute tendonitis, sprain, or contusion
• Severe contusion (e.g. Bone contusion)
• Major or invasive surgery
• Subject in a situation that, in the opinion of the investigator, could interfere with optimal participation in the present study or pose a particular risk to the subject.
• Subject currently participating in an interventional clinical study
• Subject not affiliated to the Social Security scheme
• Subject who did not comply with the exclusion period of the study in which they would have previously participated
• Subject not being able to use the internet

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Not clinically at-risk; Individuals with BMI between 18.5 kg/m2 (included) and 25 kg/m2 (excluded) and without risk factors for metabolic syndrome
Clinically at-risk; Individuals with BMI between 25 (included) and 35 kg/m2 (excluded) with or without metabolic syndrome and without treated type-2 diabetes mellitus

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Low-grade inflammation	Assessed as a z-score composed of six markers (C reactive protein (CRP), interleukin (IL)-6, serum amyloid-A (SAA), soluble intracellular adhesion molecule (sICAM), tumor necrosis factor alpha (TNF)-alpha) and categorized into 3 tertiles: Low/ Moderate/High	Baseline

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gut microbiome metabolites	Consumption and production in mmol/day assessed through in silico metabolic modeling	Baseline
Fasting glucose	Serum glucose in mg/dl	Baseline
Stool microbiome composition	Relative abundance of microbiome taxonomies (Phyla, Order, Class, Family, Genus, Species), metagenomic species (MGS), and co-abundance genes (CAGs) in stool samples assessed through shot-gun sequencing	Baseline
Stool microbiome functional pathways	Relative abundances of microbiome functional pathways assessed through metagenomics and in silico metabolic modeling	Baseline
Systolic blood pressure	mmHg	Baseline
Resting heart rate	Beats per minute	Baseline
Serum glycated hemoglobin (HbA1c)	Percentage of HbA1c or mmol/L	Baseline
Diastolic blood pressure	millimeters mercury (mmHg)	Baseline
Height	Centimeters	Baseline
Waist circumference	Centimeters	Baseline
Neck circumference	Centimeters	Baseline
Hip circumference	Centimeters	Baseline
Body fat mass	Percentage of bodymass measured by impedance	Baseline
Water body mass	Percentage of body mass measured by impedance	Baseline
Lean body mass	Percentage of body mass measured by impedance	Baseline
Serum fasting low-density lipoprotein	mmol/L	Baseline
Fasting serum high-density lipoprotein	mmol/L	Baseline
Fasting total serum cholesterol	mmol/L	Baseline
Consumption of dietary macronutrients	Dietary macronutrient consumption assessed in g/day from dietary records and food frequency questionnaires	Baseline
Consumption of dietary micronutrients	Daily micronutrient consumption (mg/d) assessed by dietary records and food frequency questionnaire	Baseline
Consumption of dietary metabolites	Dietary metabolite consumption expressed in mmol/day assessed by dietary records and food frequency questionnaire	Baseline
Food item consumption	Consumption of food items in g/day assessed by dietary records and food frequency questionnaires	Baseline
Food group consumption	Consumption of food groups in g/day assessed by dietary records and food frequency questionnaires	Baseline
Body weight	Kilograms	Baseline
Serum Alanine Transaminase (ALT)	Serum Units per Liter (U/L)	Baseline
Serum Aspartate Aminotransferase (ALT)	Serum Units per Liter (U/L)	Baseline
Serum gamma-glutamyl transferase (GGT)	Serum Units per Liter (U/L)	Baseline
Fasting serum triglycerides	mmol/L	Baseline
Fasting serum uric acid	mmol/L	Baseline
Fasting serum creatinine	mmol/L	Baseline
Fasting serum insulin	mmol/L	Baseline
Blood hemoglobin	grams per 100 milliliters (g/100ml)	Baseline
Blood hematocrit	Percentage (%) of whole blood sample	Baseline
Red blood cells	Cell counts in 10^9 per liter (10^9/L)	Baseline
Red blood cell volume	Mean volume in cubic micrometers (um^3)	Baseline
Hemoglobin relative red blood cell size	Mean relative hemoglobin relative to red blood cell size in percentage	Baseline
Mean cell hemoglobin (MCH)	Mass of hemoglobin per red blood cell in picograms (pg)	Baseline
Blood platelets	Cell counts expressed in billions/L (10^9/L)	Baseline
White blood cells	Cell counts expressed in billions/L (10^9/L) and differential	Baseline
Perceived quality of life	Self-perceived measurements of mental, physical, emotional, social, and general quality of life, fatigue, energy assessed by questionnaire	Baseline
Eating behavior	Self-perceived emotional, uncontrolled, and eating restriction assessed by questionnaire	Baseline
Physical activity	Total, leisure, work, and sports physical activity assessed by questionnaire	Baseline
Stool consistency	Stool consistency assessed and self-reported by Bristol Stool Scale	Baseline
Stress	Self-perceived stress assessed by questionnaire	Baseline
Deprivation	Economic, material, and social deprivation assessed by questionnaire	Baseline
Sleep	Sleep latency, duration, efficiency, quality, disturbances, and daytime dysfunction assessed by questionnaire	Baseline
Sleep apnea	Binary value (yes/no) assessed from questionnaire	Baseline

Collaborators and Investigators

• Sponsor: Integrative Phenomics
• Collaborators: Assistance Publique - Hôpitaux de Paris; Assistance Publique Hopitaux De Marseille; Centre Hospitalier Universitaire Dijon; University Hospital, Bordeaux; Institut Pasteur de Lille; Hopitaux Civils de Colmar

Study record dates

Study Major Dates

• Study Start (Estimated): April 1, 2024
• Primary Completion (Estimated): May 30, 2026
• Study Completion (Estimated): June 30, 2026

Study Registration Dates

• First Submitted: March 28, 2024
• First Submitted That Met QC Criteria: April 4, 2024
• First Posted (Actual): April 9, 2024

Study Record Updates

• Last Update Posted (Actual): April 9, 2024
• Last Update Submitted That Met QC Criteria: April 4, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Keywords: nutrition; microbiome; low-grade inflammation; personalized nutrition; precision nutrition; lifestyle factors
• Additional Relevant MeSH Terms: Pathologic Processes; Glucose Metabolism Disorders; Metabolic Diseases; Overnutrition; Nutrition Disorders; Body Weight; Insulin Resistance; Hyperinsulinism; Lipid Metabolism Disorders; Hyperlipidemias; Dyslipidemias; Obesity; Inflammation; Metabolic Syndrome; Overweight; Hypercholesterolemia; Obesity, Abdominal
• Other Study ID Numbers: PINEAPPL2023; 2023-A02494-41 (Other Identifier: Agence nationale de sécurité du médicament et des produits de santé)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No