Glucose, Brain and Microbiota (IRONMET+CGM)

Integrated Analysis of the Interactions Between Glycemia and Microbiota Composition, and Their Impact on Brain Iron Deposition and Cognition in Subjects With Obesity

The accumulation of iron is known to affect the functions of the liver, adipose tissue and muscle. The brain is a well-known place of iron deposition, which is associated with cognitive parameters of subjects with obesity.

The hypothesis is that certain parameters related to glucose metabolism (glycemic variability, the circulating concentration of AGE receptor agonists, pentosidine and HbA1c) are associated with cognitive function, brain iron content and gut microbiota composition in subjects with obesity.

The study includes both a cross-sectional (comparison of subjects with and without obesity) and a longitudinal design (evaluation one year after weight loss induced by bariatric surgery or by diet in patient with obesity) to evaluate the associations between continuous glucose monitoring, brain iron content (by magnetic resonance), cognitive function (by means of cognitive tests), physical activity (measured by activity and sleep tracker device) and the composition of the microbiota, evaluated by metagenomics.

Study Overview

• Status: Completed
• Conditions: Obesity
• Intervention / Treatment: Procedure: Bariatric Surgery

Detailed Description

Subjects and methods:

A. Cross-sectional study:

Patients with obesity previously scheduled at the Service of Endocrinology, Diabetes and Nutrition (UDEN) of the Hospital "Dr. Josep Trueta" of Girona (Spain) will be recruited and studied. Subjects without obesity will also be recruited through a public announcement.

A blood glucose sensor will be implanted for ten days, as well as an activity and sleep tracker device to record physical activity during this period of time. Interstitial subcutaneous glucose concentrations will be monitored on an outpatient basis for a period of time of 10 consecutive days using a glucose sensor validated by the FDA (Dexcom G6 ®). The sensor will be implanted in on day 0 and will retire on day 10 midmorning. Glucose records will preferably be evaluated on days 2 to 9 to avoid the bias caused by the insertion and removal of the sensor, which prevents a sufficient stabilization of the monitoring system. The characteristic glycemic pattern of each patient will be calculated on average from the profiles obtained on days 2 to 9.

At the end of the week an magnetic resonance imaging will be done to evaluate the iron content in the brain and parameters of "Diffusion Tensor Imaging" in different brain territories.

Cognitive tests will be carried out and feces will be collected for the study of the microbiota.

The project will be carried out in subjects with obesity (20 men, 20 premenopausal women and 20 women postmenopausal, BMI > = 30kg/m2) and subjects without obesity, similar in age, sex and menopausal status (20 men, 20 premenopausal women and 20 postmenopausal women, BMI <30kg/m2).

B. Longitudinal study:

After one year of follow-up, in which, subjects with obesity will undergo conventional treatment (hypocaloric diet and physical activity advise) or bariatric surgery for weight loss, a second visit will be carried out.

For comparison, the same protocol of the cross-sectional study will be done again. See information above.

Data collection of subjects of cross-sectional and longitudinal studies:

• Subsidiary data: Age, sex and birth date.
• Clinical variables: Weight, height, body mass index, waist and hip perimeters, waist-to-hip ratio, blood pressure (systolic and diastolic), fat mass and fat free-mass (bioelectric impedance and DEXA), smoking status, alcohol intake, registry of usual medicines and registry of antecedent relatives with obesity, diabetes and comorbidities.
• Laboratory variables: 15cc of blood will be extracted from fasted subjects to determine the following variables using the usual routine techniques of the clinical laboratory (hemogram, glucose, bilirubin, aspartate aminotransferase (AST/GOT), alanine aminotransferase (ALT/GPT), gamma-glutamyl transpeptidase (GGT), urea, creatinine, uric acid, total proteins, albumin, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, glycated haemoglobin (HbA1c), ferritin, soluble transferrin receptor, ultrasensitive C reactive protein, erythrocyte sedimentation rate, lipopolysaccharide binding protein, free thyroxine (free T4), thyroid stimulating hormone (TSH) and baseline cortisol). An additional 15cc of blood (plasma-EDTA) will be extracted for further analyses.
• Stool samples collection: A stool sample will be provided from each patient. The sample should be collected at home or in the hospital, sent to the laboratory within 4 hours from the collection, fragmented and stored at -80ºC.
• Magnetic Resonance Imaging: All MRI examinations will be performed on a 1.5-T scanner (Ingenia ®; Philips Medical Systems). First, fluid-attenuated inversion recovery (FLAIR) sequence will be used to exclude subjects with preexisting brain lesions. Brain iron load will be assessed by means of R2* values. T2* relaxation data will be acquired with a multi-echo gradient-echo sequence with 10 equally spaced echoes (first echo=4.6ms; inter echo spacing=4.6ms; repetition time=1300ms). T2* will be calculated by fitting the single exponential terms to the signal decay curves of the respective multi-echo data.R2* values will be calculated as R2*=1/T2* and expressed as Hz. In addition, R2* values will be converted to μmol Fe/g units as previously validated on phantom tests. Brain iron images from control subjects will be normalized to a standard space using a template image for this purpose (EPI MNI template). Subsequently, all normalized images will be averaged for the determination of normal iron content. Normal values (mean and SD) will be also calculated for anatomical regions of interest using different atlas masks, addressing possible differences between gender and age. The brain iron comparison between control and obese subjects will be performed using voxel-based analysis. Obese-subjects images will be normalized to a standard space. The normalized image will be compared to normal population using t-test analysis with age and sex as co-variables. As result, a parametric map will show individual differences in iron deposition. Based on previous observational studies showing increased brain iron load at some specific regions and the evidence suggesting hippocampal and hypothalamic changes in association with obesity and insulin resistance, the statistical and image analyses will be focused on iron differences at the caudate, lenticular, thalamus, hypothalamus, hippocampus, and amygdala.
• Neuropsychological examination: General cognitive functioning will be measured using the Vocabulary and Similarities subtests of the Wechsler Adult Intelligence Scale-III (WAIS-III); attention and working memory by the Forward and Backward Digit Span subtest of the WAIS-II; memory using the California Verbal Learning Test II; executive functions by the Trail Making Test, the Color-Word Stroop Test and the Verbal Fluency; mood using the Patient Health Questionnaire-9 and impulsive behaviors using the Iowa Gambling Task.
• Microbiota composition: the microbiota composition will be analyzed according to a previous described protocol. 16s rRNA qPCR and LPS-binding protein in blood samples will be used for detection of bacterial translocation.

The information will remain registered in a notebook and will be computerized in the database of the study.

Statistical methods:

Sample size: There are no previous data showing expected differences for sample size estimation regarding glucose variability, physical activity, composition of gut microbiota and cognitive function. In a previous study, differences in brain iron content were observed in 20 obese vs. 20 nonobese subjects. Thus, the proposed sample size is at least 20 individuals per group, with balanced age and gender (pre- and postmenopausal women) representation.

Statistical analyses: Firstly, normal distribution and homogeneity of variances will be tested. To determine differences between study groups, it will be used χ2 for categorical variables, unpaired Student's t-test in normal quantitative and Mann-Whitney U test for non-normal quantitative variables. Nonparametric Spearman analysis will be used to determine the correlation between quantitative variables. The same tests will also be used to study differences before and after follow-up. The significant associations, whether positive or negative, will be explored more-in-depth (simple and multivariate linear regression analyses).

The microbiota composition will be analyzed and compared using HeatMaps, Principal Component Analysis (PCA) and PLSDA. For multivariate statistics (PLSDA and hierarchical clustering), variables comprising morphological tissue characteristics, gut microbiota and functional test will be log transformed, filtered using interquartile range estimate and scaled using auto-scaling calculation (mean-centered and divided by the standard deviation of each variable) by using the Metaboanalyst ® platform, the R ® package ropls and MATLAB ® scripts. Alpha and beta biodiversity will be compared according to obesity, insulin resistance and iron status. It will also be used SPSS ® statistical software and Minitab ®.

• Study Type: Observational
• Enrollment (Actual): 128

Contacts and Locations

Study Locations

• Spain
  • Girona
    • Girona, Girona, Spain, 17007
      • Institut d'Investigació Biomèdica de Girona (IDIBGI)

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 30 years to 65 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Patients with obesity, without known type 2 diabetes, previously scheduled at the Service of Endocrinology, Diabetes and Nutrition (UDEN) of the Hospital "Dr. Josep Trueta" of Girona (Spain) will be recruited and studied.

Subjects without obesity will also be recruited through a public announcement.

Description

Inclusion Criteria:

1. Men and women aged 30-65 years.
2. Informed consent for participation in the study.

Exclusion Criteria:

1. Serious systemic disease unrelated to obesity such as cancer, severe kidney, or liver disease, known type 1 or type 2 diabetes.
2. Systemic diseases with intrinsic inflammatory activity such as rheumatoid arthritis, Crohn's disease, asthma, chronic infection (e.g., HIV, active tuberculosis) or any type of infectious disease.
3. Pregnancy and lactation.
4. Patients with severe disorders of eating behaviour.
5. Persons whose liberty is under legal or administrative requirement.
6. Clinical symptoms and signs of infection in the previous month.
7. Antibiotic, antifungal or antiviral treatment in the previous 3 months.
8. Anti-inflammatory chronic treatment with steroidal and/or non-steroidal anti-inflammatory drugs.
9. Major psychiatric antecedents.
10. Excessive alcohol intake, either acute or chronic (alcohol intake greater than 40 g a day (women) or 80 g/day (men)) or drugs abuse.
11. Serum liver enzymes (AST, ALT) activity over twice the upper limit of normal.
12. History of disturbances in iron balance (e.g., genetic hemochromatosis, hemosiderosis from any cause, atransferrinemia, paroxysmal nocturnal hemoglobinuria).

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Control
• Time Perspectives: Prospective

Number of groups / cohorts

6

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Premenopausal women with obesity	Procedure: Bariatric Surgery; Subjects with obesity (N=60) will be undertaken a hypocaloric diet and a periodic follow up, also 30 of them will undergo bariatric surgery
Postmenopausal women with obesity	Procedure: Bariatric Surgery; Subjects with obesity (N=60) will be undertaken a hypocaloric diet and a periodic follow up, also 30 of them will undergo bariatric surgery
Men with obesity	Procedure: Bariatric Surgery; Subjects with obesity (N=60) will be undertaken a hypocaloric diet and a periodic follow up, also 30 of them will undergo bariatric surgery
Premenopausal women without obesity
Postmenopausal women without obesity
Men without obesity

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Concentration of advanced glycation end products (AGE) receptor agonists.	Enzyme-linked immunosorbent assay (ELISA).	30 months
Glycemic variability.	Mean and standard deviation of glucose measures in mg/dL using a continuous glucose monitoring during 10 days.	30 months
The percentage of time in glucose target range (glucose level 100mg/dl-125mg/dl)		30 months
The glycaemic variability measured with mean amplitude of glycaemic excursions (MAGE)	measured in mg/dl	30 months
Minutes light sleep	Mean and standard deviation of minutes light sleep measures by activity and sleep tracker device.	30 months
Minutes deep sleep	Mean and standard deviation of minutes deep sleep measures by activity and sleep tracker device.	30 months
Minutes rapid eye movement (REM)	Mean and standard deviation of minutes REM measures by activity and sleep tracker device.	30 months
The glycaemic risk measured with low blood glucose index (LBGI)	Low blood glucose index (LBGI) is a parameter that quantifies the risk of glycaemic excursions in non-negative numbers.	30 months
The glycaemic risk measured with high blood glucose index (HBGI)	High blood glucose index (HBGI) is a parameter that quantifies the risk of glycaemic excursions in non-negative numbers.	30 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Effect on brain structure.	Brain structure will be assessed using magnetic resonance imaging.	30 months
Effect on gut microbiota.	Gut microbiota will be analysed by metagenomics and metabolomics.	30 months
Changes from baseline in circulating concentration of AGE receptor agonists and glycemic variability one year of follow-up after weight loss in association with changes in brain structure and gut microbiota.	Subjects with obesity will be undertaken conventional treatment or bariatric surgery for weight loss; controls will not undergo any additional measure.	30 months
Audioverbal memory	It will be measured by California Verbal Learning Test (CVLT). Minimum/maximum scale values (0-16), where 16 is a better audioverbal memory.	30 months
Visual memory	It will be measured by Rey-Osterrieth Complex Figure. Minimum/maximum scale values (0-36), where 36 is a better visual memory	30 months
Depressive symptomatology	It will be measured by Patient Health Questionnaire-9 (PHQ-9). Minimum/maximum scale values (0-27), where ≥ 20 is severe depression.	30 months
Food Addiction	It will be measured by Yale Food Addiction Scale.It is a symptom score from 0-11, based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria, for substance dependence. Food addiction is diagnosed if ≥3 symptoms are reported.	30 months
Behavioral inhibition	It will be measured by Sensitivity to Punishment and Sensitivity to Reward (SPSRQ). The scale of sensitivity to punishment is related to the behavioral inhibition system. It is made up of two subscales of 24 items each, where the higher the score, the greater the sensitivity to punishment.	30 months
Behavioral activation	It will be measured by Sensitivity to Punishment and Sensitivity to Reward (SPSRQ). The reward sensitivity scale is related to the behavioral activation system. It is made up of two subscales of 24 items each, where the higher the score, the greater the sensitivity to reward.	30 months
Visoconstructive function	It will be measured by Rey-Osterrieth Complex Figure. Minimum/maximum scale values (0-36), where 36 is a better visoconstructive function.	30 months
Selective and alternating attention	It will be measured by Trail making test (Part A y B).	30 months
Attention and working memory	It will be measured by the Digits subtest of Wechsler Adult Intelligence Scales, Fourth Edition (WAIS-IV).	30 months
Inhibition	It will be measured by Stroop Color-Word Test.	30 months
Semantic verbal fluency	It will be measured by Animals test. The person must name as many animals as possible in 1 minute. The result is corrected by standard scores, according to age and level of education.	30 months
Diffusion Tensor Imaging brain sequences	Diffusion Tensor Imaging was acquired at 1.5 T (Philips ingenia) using a single-shot spin echo sequence with echo-planar imaging (EPI), 50 contiguous slices, voxel size 2x2x2.5 mm3, TE/TR of 72/3581 ms/ms, a diffusion-weighting factor b = 800 s/mm2 and diffusion encoding along 32 directions.	30 months
Brain iron accumulation	It will be assessed using magnetic resonance imaging using (R2*)	30 months
Resting-state functional brain sequences	It will be assessed using magnetic resonance imaging (T2*-weighted echo-planar imaging). T2 * relaxation data will be acquired with a multi-echo gradient sequence with 10 equidistant echoes (first echo = 4.6ms; echo spacing = 4.6ms; repetition time = 1300ms). The value value of T2 * will be calculated by adjusting the simple exponential terms for the signal decay of the respective echo time values.	30 months
Insulin resistance	It will be measured by HOMA	30 months
Markers of chronic inflammation: C-reactive protein, IL-6, adiponectin and soluble, tumor necrosis factor-α receptor fractions.	Enzyme-linked immunosorbent assay (ELISA) and quantitative polymerase chain reaction (qPCR)	30 months
Glycosylated hemoglobin (HbA1c) value	Glycosylated hemoglobin (HbA1c) in % or mmol/mol	30 months
The percentage of time in hyperglycaemia (glucose level above 250 mg/dl)		30 months
The percentage of time in hypoglycaemia (glucose level below 70mg/dl)		30 months
The percentage of time in glucose range (glucose level below 100 mg/dl)		30 months
The percentage of time in glucose range (glucose level between 126-139 mg/dl)		30 months
The percentage of time in glucose range (glucose level between 140-199 mg/dl)		30 months
The percentage of time in glucose range (glucose level above 200 mg/dl)		30 months
Burned calories	Mean and standard deviation of burned calories measures by activity and sleep tracker device.	30 months
Steps	Mean and standard deviation of steps measures by activity and sleep tracker device.	30 months
Distance	Mean and standard deviation of distance measures by activity and sleep tracker device.	30 months
Minutes mean activity	Mean and standard deviation of minutes mean activity measures by activity and sleep tracker device.	30 months
Minutes high activity	Mean and standard deviation of minutes high activity measures by activity and sleep tracker device.	30 months
Calories	Mean and standard deviation of calories measures by activity and sleep tracker device.	30 months
Bed time	Mean and standard deviation of bed time measures by activity and sleep tracker device.	30 months
Cognitive impairment	It will be measured by Mini-Examen Cognoscitivo (MEC). Minimum/maximum scale values (0-30), where ≥ 27 is a normal score.	30 months
Impulsivity	It will be measured by Impulsive Behavior Scale (UPPS-P). The test evaluates: Negative urgency (tendency to act rashly under extreme negative emotions), Lack of Premeditation (tendency to act without thinking), Lack of Perseverance (inability to remain focused on a task) and Sensation Seeking (tendency to seek out novel and thrilling experiences). All items are rated on a four point scale from 1 (strongly agree) to 4 (strongly disagree).	30 months
Visuospatial perception	It will be measured by Judgment Line Orientation	30 months
Naming	It will be measured by Boston Naming Test.	30 months
Phonemic verbal fluency	It will be measured by PMR	30 months
Minutes null activity	Mean and standard deviation of minutes null activity measures by activity and sleep tracker device.	30 months
Minutes slight activity	Mean and standard deviation of minutes slight activity measures by activity and sleep tracker device.	30 months
Minutes asleep	Mean and standard deviation of minutes asleep measures by activity and sleep tracker device.	30 months
Minutes awake	Mean and standard deviation of minutes awake measures by activity and sleep tracker device.	30 months
Number time awake	Mean and standard deviation of number time awake measures by activity and sleep tracker device.	30 months

Collaborators and Investigators

• Sponsor: Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
• Investigators: Principal Investigator: José Manuel Fernández-Real, M.D., Ph.D., Institut d'Investigacio Biomedica de Girona Dr. Josep Trueta

Publications and helpful links

General Publications

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• Fernandez-Real JM, Ricart-Engel W, Arroyo E, Balanca R, Casamitjana-Abella R, Cabrero D, Fernandez-Castaner M, Soler J. Serum ferritin as a component of the insulin resistance syndrome. Diabetes Care. 1998 Jan;21(1):62-8. doi: 10.2337/diacare.21.1.62.
• Fernandez-Real JM, Lopez-Bermejo A, Ricart W. Cross-talk between iron metabolism and diabetes. Diabetes. 2002 Aug;51(8):2348-54. doi: 10.2337/diabetes.51.8.2348.
• Fernandez-Real JM, Manco M. Effects of iron overload on chronic metabolic diseases. Lancet Diabetes Endocrinol. 2014 Jun;2(6):513-26. doi: 10.1016/S2213-8587(13)70174-8. Epub 2013 Dec 30.
• Fernandez-Real JM, Blasco G, Puig J, Moreno M, Xifra G, Sanchez-Gonzalez J, Maria Alustiza J, Pedraza S, Ricart W, Maria Moreno-Navarrete J. Adipose tissue R2* signal is increased in subjects with obesity: A preliminary MRI study. Obesity (Silver Spring). 2016 Feb;24(2):352-8. doi: 10.1002/oby.21347. Epub 2015 Dec 26.
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• Moreno-Navarrete JM, Moreno M, Puig J, Blasco G, Ortega F, Xifra G, Ricart W, Fernandez-Real JM. Hepatic iron content is independently associated with serum hepcidin levels in subjects with obesity. Clin Nutr. 2017 Oct;36(5):1434-1439. doi: 10.1016/j.clnu.2016.09.022. Epub 2016 Sep 29.
• Moreno-Navarrete JM, Rodriguez A, Becerril S, Valenti V, Salvador J, Fruhbeck G, Fernandez-Real JM. Increased Small Intestine Expression of Non-Heme Iron Transporters in Morbidly Obese Patients With Newly Diagnosed Type 2 Diabetes. Mol Nutr Food Res. 2018 Jan;62(2). doi: 10.1002/mnfr.201700301. Epub 2017 Dec 29.
• Fernandez Real JM, Moreno-Navarrete JM, Manco M. Iron influences on the Gut-Brain axis and development of type 2 diabetes. Crit Rev Food Sci Nutr. 2019;59(3):443-449. doi: 10.1080/10408398.2017.1376616. Epub 2017 Oct 17.
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• Blasco G, Puig J, Daunis-I-Estadella J, Molina X, Xifra G, Fernandez-Aranda F, Pedraza S, Ricart W, Portero-Otin M, Fernandez-Real JM. Brain iron overload, insulin resistance, and cognitive performance in obese subjects: a preliminary MRI case-control study. Diabetes Care. 2014 Nov;37(11):3076-83. doi: 10.2337/dc14-0664. Epub 2014 Aug 14.
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• Pedersen HK, Gudmundsdottir V, Nielsen HB, Hyotylainen T, Nielsen T, Jensen BA, Forslund K, Hildebrand F, Prifti E, Falony G, Le Chatelier E, Levenez F, Dore J, Mattila I, Plichta DR, Poho P, Hellgren LI, Arumugam M, Sunagawa S, Vieira-Silva S, Jorgensen T, Holm JB, Trost K; MetaHIT Consortium; Kristiansen K, Brix S, Raes J, Wang J, Hansen T, Bork P, Brunak S, Oresic M, Ehrlich SD, Pedersen O. Human gut microbes impact host serum metabolome and insulin sensitivity. Nature. 2016 Jul 21;535(7612):376-81. doi: 10.1038/nature18646. Epub 2016 Jul 13.
• Geijselaers SLC, Sep SJS, Stehouwer CDA, Biessels GJ. Glucose regulation, cognition, and brain MRI in type 2 diabetes: a systematic review. Lancet Diabetes Endocrinol. 2015 Jan;3(1):75-89. doi: 10.1016/S2213-8587(14)70148-2. Epub 2014 Aug 24.

Study record dates

Study Major Dates

• Study Start (Actual): March 5, 2019
• Primary Completion (Actual): July 31, 2022
• Study Completion (Actual): May 31, 2025

Study Registration Dates

• First Submitted: February 27, 2019
• First Submitted That Met QC Criteria: March 21, 2019
• First Posted (Actual): March 26, 2019

Study Record Updates

• Last Update Posted (Actual): March 31, 2026
• Last Update Submitted That Met QC Criteria: March 26, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: Obesity; Cognition; Continous Glucose Monitoring; Brain Iron content
• Additional Relevant MeSH Terms: Nutrition Disorders; Overnutrition; Body Weight; Overweight; Pathological Conditions, Signs and Symptoms; Nutritional and Metabolic Diseases; Signs and Symptoms; Obesity; Therapeutics; Surgical Procedures, Operative; Bariatrics; Obesity Management; Bariatric Surgery
• Other Study ID Numbers: IRONMET+CGM-2017.139

Drug and device information, study documents

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