ObesityIRONmiRNANCT05345106
Inter-relationships Among Glucose, Brain, Gut Microbiota and MicroRNAs (IRONmiRNA).
An observational study of Obesity, run by Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta at 1 site in Spain.
Trial summary
The brain is a recognized target of iron deposition. This process is enhanced by the presence of obesity and hyperglycemia and impacts cognitive functions. There is evidence suggesting that the gut microbiota composition modulates this process. Read more about this study
- Who is it for?
- Ages 30 to 65 yearsHealthy volunteers can take part
- Conditions the study is for
- Obesity
- What is being tested?
- Bariatric Surgery
- Type of treatment
- Surgery or procedure
- How many people
- 138 participants
- Where
- 1 siteSpain
- Study dates
- 28 Mar 2022to 31 Jan 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 30 to 65 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
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.
Who may be able to join
- Men and women aged 30-65 years.
- Informed consent for participation in the study.
Who cannot join
- Serious systemic disease unrelated to obesity such as cancer, severe kidney, or liver disease, known type 1 or type 2 diabetes.
- 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.
- Pregnancy and lactation.
- Patients with severe disorders of eating behaviour.
- Persons whose liberty is under legal or administrative requirement.
- Clinical symptoms and signs of infection in the previous month.
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- Antibiotic, antifungal or antiviral treatment in the previous 3 months.
- Anti-inflammatory chronic treatment with steroidal and/or non-steroidal anti-inflammatory drugs.
- Major psychiatric antecedents.
- Excessive alcohol intake, either acute or chronic (alcohol intake greater than 40 g a day (women) or 80 g/day (men)) or drugs abuse.
- Serum liver enzymes (AST, ALT) activity over twice the upper limit of normal.
- History of disturbances in iron balance (e.g., genetic hemochromatosis, hemosiderosis from any cause, atransferrinemia, paroxysmal nocturnal hemoglobinuria).
Trial locations and contacts
1 site in 1 country.
Spain1 site
Institut d'Investigació Biomèdica de Girona (IDIBGI)
Girona, Girona, 17007
About this study
Official title: Inter-relationships Among Iron Stores, the Gut Metagenome, Glucose Levels, and Different Cognitive Domains: the Role of Circulating MicroRNAs (IRONmiRNA Study).
The brain is a recognized target of iron deposition. This process is enhanced by the presence of obesity and hyperglycemia and impacts cognitive functions. There is evidence suggesting that the gut microbiota composition modulates this process. It has been proposed that microRNAs are mediators in the dialogue between the composition and functionality of the intestinal microbiota and increased iron deposition in the brain.
The hypothesis is that circulating microRNAs are associated with parameters of cognitive dysfunction, gut microbiota, brain iron content, glucose levels, and physical activity in subjects with and without 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 patients with obesity) to evaluate the associations between circulating microRNAs, 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.
Read the detailed description
Subjects and methods:
- 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 glycemia sensor will be inserted for ten days, as well as an activity and sleep tracker device (Fitbit) 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 Food and Drug Administration (Dexcom G6 ®). The sensor will be inserted on day 0 and it will retire on day 10 mid-morning.
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, 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 and urine will be collected for the study of the microbiota. Additionally, blood samples will be collected for the extraction and purification of circulating RNA and then retrotranscription of circulating miRNAs and preamplification.
The project will be carried out in subjects with obesity (20 men, 20 premenopausal women, and 20 women postmenopausal, Body mass index (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).
- Longitudinal study:
After one year of follow-up, in which, subjects with obesity will undergo conventional treatment (hypocaloric diet, and physical activity advice) 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 the 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
- personal history of blood transfusion and/or donation
- a record of family history of obesity, cardiovascular events, and diabetes
- psychiatric and eating disorder history.
- 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 hemoglobin (HbA1c)
- ferritin | soluble transferrin receptor
- ultrasensitive C reactive protein
- erythrocyte sedimentation rate
- lipopolysaccharide binding protein
- free thyroxine (free T4) | thyroid stimulating hormone (TSH) | baseline cortisol -plasma insulin
- inflammation markers | interleukin 6 (IL-6). 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. Analysis of gut microbiota in stool: *Determination of bacterial DNA and mRNA and study of the LBP binding protein in the blood for the detection of bacterial translocation. LBP binding protein in the blood for the detection of bacterial translocation. Hiseq and Nextseq technology (qPCR and protein analysis (WB, ELISA), OMICS (RNAseq, 16S, Metabolomics, Metagenomics).
- Urine sample collection: Necessary to determine alterations in the metabolic pathways involved in tryptophan metabolism, and to determine the role of the intestinal microbiota in these metabolic changes.
- Magnetic Resonance Imaging: All MRI examinations will be performed on a 1.5-T scanner (Ingenia ®; Philips Medical Systems). First, a 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-subject images will be normalized to a standard space. The normalized image will be compared to the normal population using t-test analysis with age and sex as co-variables. As a result, a parametric map will show individual differences in the 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: Different domains of cognition will be explored: memory (Test aprendizaje verbal-TAVEC, Rey-Osterrieth Complex Figure) attention, and executive function(WAIS-IV, Trail making test (Part A y B), Stroop test), social cognition(POFA and BFRT), language (animals). Furthermore, depression (PHQ9), anxiety (State-Trait Anxiety Inventory (STAI)), impulsivity (Impulsive Behavior Scale (UPPS-P)), sensitivity to punishment and reward (Sensitivity to Punishment and Sensitivity to Reward (SRSPQ)), food addiction (Yale Food Addiction Scale (YFAS II)), subjective well being, positive and negative affect (Positive and Negative Affect Schedule (PANAS)) will be explored through psychological tests.
- Profile of circulating miRNAs
- Circulating RNA extraction and purification: Plasma will be obtained by standard venipuncture and centrifugation using EDTA-coated Vacutainer tubes (Becton-Dickinson, Franklin Lakes, NJ). Plasma separation will be performed by double centrifugation using a laboratory centrifuge (Beckman J-6M Induction Drive Centrifuge, Beckman Instruments Inc). RNA extraction will be performed from an initial volume of 300 μL of plasma using the mirVana PARIS isolation kit (Applied Biosystems, Darmstadt, Germany).
- Retrotranscription of circulating miRNAs and preamplification: A fixed volume of 3 μL of RNA solution from the 40 mL, eluate of the RNA isolate will be used as input for retrotranscription using the TaqMan miRNA reverse transcription kit (Life Technology, Darmstadt, Germany). Preamplification will be carried out using the TaqMan PreAmp Master Mix (Life Technology, Darmstadt, Germany).
- Analysis of individual miRNAs by TaqMan hydrolysis probes: Gene expression will be assessed by real-time PCR using the LightCycler 480 real-time PCR system (Roche Diagnostics, Barcelona, Spain), using the appropriate TaqMan technology for the quantification of relative gene expression.
The information will remain registered in a notebook and will be computerized in the database of the study.
STATICAL METHODS:
Sample size: There are no previous data showing expected differences for sample size estimation regarding glucose variability, physical activity, the 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 R "ALDEx2". Bacterial species and functions associated with brain iron and circulating microRNAs will be identified using robust linear regression models as implemented in the R package (Limma R). Moreover, p-values will be adjusted for multiple comparisons using the R package "SGoF".Measures of glycemic variability will be calculated using Matlab software (R2018a).
- Conditions
- Obesity
- Being tested
- Bariatric Surgery
- Keywords
- Continous Glucose Monitoring, Cognition, Brain Iron content
- Medical subject headings
- Obesity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Bariatric SurgeryProcedure or 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
| Study group | Role | What they receive |
|---|---|---|
| Premenopausal women with obesity | Not described Receives: Procedure: Bariatric Surgery | |
| Postmenopausal women with obesity | Not described Receives: Procedure: Bariatric Surgery | |
| Men with obesity | Not described Receives: Procedure: Bariatric Surgery | |
| Premenopausal women without obesity | Not described | |
| Postmenopausal women without obesity | Not described | |
| Men without obesity | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Concentration of advanced glycation end products (AGE) receptor agonists.
Enzyme-linked immunosorbent assay (ELISA).
Measured: 30 months
Glycemic variability.
Mean and standard deviation of glucose measures in mg/dL using a continuous glucose monitoring during 10 days.
Measured: 30 months
The percentage of time in glucose target range (glucose level 100mg/dl-125mg/dl)
Measured: 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
Measured: 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
Measured: 30 months
The glycaemic variability measured with mean amplitude of glycaemic excursions (MAGE)
measured in mg/dl
Measured: 30 months
Minutes light sleep
Mean and standard deviation of minutes light sleep measures by activity and sleep tracker device.
Measured: 30 months
Minutes deep sleep
Mean and standard deviation of minutes deep sleep measures by activity and sleep tracker device.
Measured: 30 months
Minutes rapid eye movement (REM)
Mean and standard deviation of minutes REM measures by activity and sleep tracker device.
Measured: 30 months
Secondary outcomes (43)
Effect on brain structure.
Brain structure will be assessed using magnetic resonance imaging.
Measured: 30 months
Effect on gut microbiota.
Gut microbiota will be analysed by metagenomics and metabolomics.
Measured: 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.
Measured: 30 months
Anxiety state
It will be measured by State-Trate Anxiety Inventory (STAI).
Measured: 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.
Measured: 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
Measured: 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.
Measured: 30 months
Impulsivity
It will be measured by Impulsive Behavior Scale (UPPS-P). The test evaluates: Negative
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 30 months
Selective and alternating attention
It will be measured by Trail making test (Part A y B).
Measured: 30 months
Attention and working memory
It will be measured by the Digits subtest of Wechsler Adult Intelligence Scales, Fourth Edition (WAIS-IV).
Measured: 30 months
Inhibition
It will be measured by Stroop Color-Word Test.
Measured: 30 months
Phonemic verbal fluency
It will be measured by PMR.
Measured: 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.
Measured: 30 months
Facial recognition
It will be measured by Picture of Facial Recognition Test (POFA).
Measured: 30 months
Emotion recognition
It will be measured by Benton Facial Recognition Test (BFRT).This test evaluates the recognition of the five basic emotions: happiness, sadness, surprise, disgust, and anger.
Measured: 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.
Measured: 30 months
Brain iron accumulation
It will be assessed using magnetic resonance imaging using (R2*)
Measured: 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.
Measured: 30 months
Insulin resistance
It will be measured by HOMA
Measured: 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)
Measured: 30 months
Glycosylated hemoglobin (HbA1c) value
Glycosylated hemoglobin (HbA1c) in % or mmol/mol
Measured: 30 months
The percentage of time in hyperglycaemia (glucose level above 250 mg/dl)
Measured: 30 months
The percentage of time in hypoglycaemia (glucose level below 70mg/dl)
Measured: 30 months
The percentage of time in glucose range (glucose level below 100 mg/dl)
Measured: 30 months
The percentage of time in glucose range (glucose level between 126-139 mg/dl)
Measured: 30 months
The percentage of time in glucose range (glucose level between 140-199 mg/dl)
Measured: 30 months
The percentage of time in glucose range (glucose level above 200 mg/dl)
Measured: 30 months
Burned calories
Mean and standard deviation of burned calories measures by activity and sleep tracker device.
Measured: 30 months
Steps
Mean and standard deviation of steps measures by activity and sleep tracker device.
Measured: 30 months
Distance
Mean and standard deviation of distance measures by activity and sleep tracker device.
Measured: 30 months
Minutes null activity
Mean and standard deviation of minutes null activity measures by activity and sleep
Measured: 30 months
Minutes slight activity
Mean and standard deviation of minutes slight activity measures by activity and sleep
Measured: 30 months
Minutes mean activity
Mean and standard deviation of minutes mean activity measures by activity and sleep tracker device.
Measured: 30 months
Minutes high activity
Mean and standard deviation of minutes high activity measures by activity and sleep tracker device.
Measured: 30 months
Calories
Mean and standard deviation of calories measures by activity and sleep tracker device.
Measured: 30 months
Minutes asleep
Mean and standard deviation of minutes asleep measures by activity and sleep tracker
Measured: 30 months
Minutes awake
Mean and standard deviation of minutes awake measures by activity and sleep tracker
Measured: 30 months
Bed time
Mean and standard deviation of bed time measures by activity and sleep tracker device.
Measured: 30 months
Number time awake
Mean and standard deviation of number time awake measures by activity and sleep
Measured: 30 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Apr 2022
- Study start28 Mar 2022
- Primary completion22 Jan 2026
- Study completion31 Jan 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (39)Papers the sponsor has linked to this study.
- Other trials for ObesityStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 138 participants (actual)
Sponsor and investigators
- Lead sponsor
- Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, José Manuel Fernández-Real, Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
- Investigators
- José Manuel Fernández-Real, M.D., Ph.D., Principal investigator, Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05345106
- Sponsor's protocol ID
- IRONmiRNA-2022.043
- Acronym
- IRONmiRNA
- Status last verified
- Mar 2026
- First submitted
- 19 Apr 2022
- Last updated
- 31 Mar 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Finch C. Regulators of iron balance in humans. Blood. 1994 Sep 15;84(6):1697-702. No abstract available.
PubMed 8080980Fernandez-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.
PubMed 9580307Fernandez-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.
PubMed 12145144Fernandez-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.
PubMed 24731656Fernandez-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.
PubMed 26813526Moreno-Navarrete JM, Blasco G, Xifra G, Karczewska-Kupczewska M, Stefanowicz M, Matulewicz N, Puig J, Ortega F, Ricart W, Straczkowski M, Fernandez-Real JM. Obesity Is Associated With Gene Expression and Imaging Markers of Iron Accumulation in Skeletal Muscle. J Clin Endocrinol Metab. 2016 Mar;101(3):1282-9. doi: 10.1210/jc.2015-3303. Epub 2016 Jan 14.
PubMed 26765579Moreno-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.
PubMed 27745814Moreno-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.
PubMed 29082606Fernandez 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.
PubMed 28886251Geijselaers 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.
PubMed 25163604Kharabian Masouleh S, Beyer F, Lampe L, Loeffler M, Luck T, Riedel-Heller SG, Schroeter ML, Stumvoll M, Villringer A, Witte AV. Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults. J Cereb Blood Flow Metab. 2018 Feb;38(2):360-372. doi: 10.1177/0271678X17729111. Epub 2017 Aug 31.
PubMed 28857651Ryan CM, Freed MI, Rood JA, Cobitz AR, Waterhouse BR, Strachan MW. Improving metabolic control leads to better working memory in adults with type 2 diabetes. Diabetes Care. 2006 Feb;29(2):345-51. doi: 10.2337/diacare.29.02.06.dc05-1626.
PubMed 16443885Weinstein G, Maillard P, Himali JJ, Beiser AS, Au R, Wolf PA, Seshadri S, DeCarli C. Glucose indices are associated with cognitive and structural brain measures in young adults. Neurology. 2015 Jun 9;84(23):2329-37. doi: 10.1212/WNL.0000000000001655. Epub 2015 May 6.
PubMed 25948725Rolandsson O, Backestrom A, Eriksson S, Hallmans G, Nilsson LG. Increased glucose levels are associated with episodic memory in nondiabetic women. Diabetes. 2008 Feb;57(2):440-3. doi: 10.2337/db07-1215. Epub 2007 Oct 31.
PubMed 17977953Marden JR, Mayeda ER, Tchetgen Tchetgen EJ, Kawachi I, Glymour MM. High Hemoglobin A1c and Diabetes Predict Memory Decline in the Health and Retirement Study. Alzheimer Dis Assoc Disord. 2017 Jan-Mar;31(1):48-54. doi: 10.1097/WAD.0000000000000182.
PubMed 28225507
Study at a glance
From the registry record, last updated by the sponsor on 31 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Inter-relationships Among Iron Stores, the Gut Metagenome, Glucose Levels, and Different Cognitive Domains: the Role of Circulating MicroRNAs (IRONmiRNA Study).
- ClinicalTrials.gov ID
- NCT05345106
- Acronym / sponsor ID
- IRONmiRNA / IRONmiRNA-2022.043
- Conditions
- Obesity
- Keywords
- Continous Glucose Monitoring, Cognition, Brain Iron content
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 138 participants (actual)
- Lead sponsor
- Institut d'Investigació Biomèdica de Girona Dr. Josep TruetaUniversity, hospital or other
- Study start
- 28 Mar 2022 (actual)
- Primary completion
- 22 Jan 2026 (actual)
- Study completion
- 31 Jan 2027 (estimated)
- First posted
- 25 Apr 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The brain is a recognized target of iron deposition. This process is enhanced by the presence of obesity and hyperglycemia and impacts cognitive functions. There is evidence suggesting that the gut microbiota composition modulates this process. It has been proposed that microRNAs are mediators in the dialogue between the composition and functionality of the intestinal microbiota and increased iron deposition in the brain.
The hypothesis is that circulating microRNAs are associated with parameters of cognitive dysfunction, gut microbiota, brain iron content, glucose levels, and physical activity in subjects with and without 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 patients with obesity) to evaluate the associations between circulating microRNAs, 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.
Detailed description
Subjects and methods:
- 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 glycemia sensor will be inserted for ten days, as well as an activity and sleep tracker device (Fitbit) 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 Food and Drug Administration (Dexcom G6 ®). The sensor will be inserted on day 0 and it will retire on day 10 mid-morning.
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, 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 and urine will be collected for the study of the microbiota. Additionally, blood samples will be collected for the extraction and purification of circulating RNA and then retrotranscription of circulating miRNAs and preamplification.
The project will be carried out in subjects with obesity (20 men, 20 premenopausal women, and 20 women postmenopausal, Body mass index (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).
- Longitudinal study:
After one year of follow-up, in which, subjects with obesity will undergo conventional treatment (hypocaloric diet, and physical activity advice) 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 the 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
- personal history of blood transfusion and/or donation
- a record of family history of obesity, cardiovascular events, and diabetes
- psychiatric and eating disorder history.
- 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 hemoglobin (HbA1c)
- ferritin | soluble transferrin receptor
- ultrasensitive C reactive protein
- erythrocyte sedimentation rate
- lipopolysaccharide binding protein
- free thyroxine (free T4) | thyroid stimulating hormone (TSH) | baseline cortisol -plasma insulin
- inflammation markers | interleukin 6 (IL-6). 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. Analysis of gut microbiota in stool: *Determination of bacterial DNA and mRNA and study of the LBP binding protein in the blood for the detection of bacterial translocation. LBP binding protein in the blood for the detection of bacterial translocation. Hiseq and Nextseq technology (qPCR and protein analysis (WB, ELISA), OMICS (RNAseq, 16S, Metabolomics, Metagenomics).
- Urine sample collection: Necessary to determine alterations in the metabolic pathways involved in tryptophan metabolism, and to determine the role of the intestinal microbiota in these metabolic changes.
- Magnetic Resonance Imaging: All MRI examinations will be performed on a 1.5-T scanner (Ingenia ®; Philips Medical Systems). First, a 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-subject images will be normalized to a standard space. The normalized image will be compared to the normal population using t-test analysis with age and sex as co-variables. As a result, a parametric map will show individual differences in the 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: Different domains of cognition will be explored: memory (Test aprendizaje verbal-TAVEC, Rey-Osterrieth Complex Figure) attention, and executive function(WAIS-IV, Trail making test (Part A y B), Stroop test), social cognition(POFA and BFRT), language (animals). Furthermore, depression (PHQ9), anxiety (State-Trait Anxiety Inventory (STAI)), impulsivity (Impulsive Behavior Scale (UPPS-P)), sensitivity to punishment and reward (Sensitivity to Punishment and Sensitivity to Reward (SRSPQ)), food addiction (Yale Food Addiction Scale (YFAS II)), subjective well being, positive and negative affect (Positive and Negative Affect Schedule (PANAS)) will be explored through psychological tests.
- Profile of circulating miRNAs
- Circulating RNA extraction and purification: Plasma will be obtained by standard venipuncture and centrifugation using EDTA-coated Vacutainer tubes (Becton-Dickinson, Franklin Lakes, NJ). Plasma separation will be performed by double centrifugation using a laboratory centrifuge (Beckman J-6M Induction Drive Centrifuge, Beckman Instruments Inc). RNA extraction will be performed from an initial volume of 300 μL of plasma using the mirVana PARIS isolation kit (Applied Biosystems, Darmstadt, Germany).
- Retrotranscription of circulating miRNAs and preamplification: A fixed volume of 3 μL of RNA solution from the 40 mL, eluate of the RNA isolate will be used as input for retrotranscription using the TaqMan miRNA reverse transcription kit (Life Technology, Darmstadt, Germany). Preamplification will be carried out using the TaqMan PreAmp Master Mix (Life Technology, Darmstadt, Germany).
- Analysis of individual miRNAs by TaqMan hydrolysis probes: Gene expression will be assessed by real-time PCR using the LightCycler 480 real-time PCR system (Roche Diagnostics, Barcelona, Spain), using the appropriate TaqMan technology for the quantification of relative gene expression.
The information will remain registered in a notebook and will be computerized in the database of the study.
STATICAL METHODS:
Sample size: There are no previous data showing expected differences for sample size estimation regarding glucose variability, physical activity, the 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 R "ALDEx2". Bacterial species and functions associated with brain iron and circulating microRNAs will be identified using robust linear regression models as implemented in the R package (Limma R). Moreover, p-values will be adjusted for multiple comparisons using the R package "SGoF".Measures of glycemic variability will be calculated using Matlab software (R2018a).
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 6
| Arm | Type | Receives |
|---|---|---|
| Premenopausal women with obesity | – | Procedure: Bariatric Surgery |
| Postmenopausal women with obesity | – | Procedure: Bariatric Surgery |
| Men with obesity | – | Procedure: Bariatric Surgery |
| Premenopausal women without obesity | – | – |
| Postmenopausal women without obesity | – | – |
| Men without obesity | – | – |
Who may qualify
- Ages
- 30 to 65 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (2 listed)
- Men and women aged 30-65 years.
- Informed consent for participation in the study.
Key exclusion criteria (12 listed)
- Serious systemic disease unrelated to obesity such as cancer, severe kidney, or liver disease, known type 1 or type 2 diabetes.
- 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.
- Pregnancy and lactation.
- Patients with severe disorders of eating behaviour.
- Persons whose liberty is under legal or administrative requirement.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Bariatric SurgerySubjects with obesity (N=60) will be undertaken a hypocaloric diet and a periodic follow up, also 30 of them will undergo bariatric surgery | Procedure or surgery | Men with obesity, Postmenopausal women with obesity, Premenopausal women with obesity |
Primary outcome
Concentration of advanced glycation end products (AGE) receptor agonists.
Time frame: 30 months
Enzyme-linked immunosorbent assay (ELISA).
Glycemic variability.
Time frame: 30 months
Mean and standard deviation of glucose measures in mg/dL using a continuous glucose monitoring during 10 days.
The percentage of time in glucose target range (glucose level 100mg/dl-125mg/dl)
Time frame: 30 months
The glycaemic risk measured with low blood glucose index (LBGI)
Time frame: 30 months
Low blood glucose index (LBGI) is a parameter that quantifies the risk of glycaemic
The glycaemic risk measured with high blood glucose index (HBGI)
Time frame: 30 months
High blood glucose index (HBGI) is a parameter that quantifies the risk of glycaemic
The glycaemic variability measured with mean amplitude of glycaemic excursions (MAGE)
Time frame: 30 months
measured in mg/dl
Minutes light sleep
Time frame: 30 months
Mean and standard deviation of minutes light sleep measures by activity and sleep tracker device.
Minutes deep sleep
Time frame: 30 months
Mean and standard deviation of minutes deep sleep measures by activity and sleep tracker device.
Minutes rapid eye movement (REM)
Time frame: 30 months
Mean and standard deviation of minutes REM measures by activity and sleep tracker device.
43 secondary outcomes
Effect on brain structure.
Time frame: 30 months
Effect on gut microbiota.
Time frame: 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.
Time frame: 30 months
Anxiety state
Time frame: 30 months
Audioverbal memory
Time frame: 30 months
Visual memory
Time frame: 30 months
Depressive symptomatology
Time frame: 30 months
Impulsivity
Time frame: 30 months
Food Addiction
Time frame: 30 months
Behavioral inhibition
Time frame: 30 months
Behavioral activation
Time frame: 30 months
Visoconstructive function
Time frame: 30 months
Selective and alternating attention
Time frame: 30 months
Attention and working memory
Time frame: 30 months
Inhibition
Time frame: 30 months
Phonemic verbal fluency
Time frame: 30 months
Semantic verbal fluency
Time frame: 30 months
Facial recognition
Time frame: 30 months
Emotion recognition
Time frame: 30 months
Diffusion Tensor Imaging brain sequences
Time frame: 30 months
Brain iron accumulation
Time frame: 30 months
Resting-state functional brain sequences
Time frame: 30 months
Insulin resistance
Time frame: 30 months
Markers of chronic inflammation: C-reactive protein, IL-6, adiponectin and soluble, tumor necrosis factor-α receptor fractions.
Time frame: 30 months
Glycosylated hemoglobin (HbA1c) value
Time frame: 30 months
The percentage of time in hyperglycaemia (glucose level above 250 mg/dl)
Time frame: 30 months
The percentage of time in hypoglycaemia (glucose level below 70mg/dl)
Time frame: 30 months
The percentage of time in glucose range (glucose level below 100 mg/dl)
Time frame: 30 months
The percentage of time in glucose range (glucose level between 126-139 mg/dl)
Time frame: 30 months
The percentage of time in glucose range (glucose level between 140-199 mg/dl)
Time frame: 30 months
The percentage of time in glucose range (glucose level above 200 mg/dl)
Time frame: 30 months
Burned calories
Time frame: 30 months
Steps
Time frame: 30 months
Distance
Time frame: 30 months
Minutes null activity
Time frame: 30 months
Minutes slight activity
Time frame: 30 months
Minutes mean activity
Time frame: 30 months
Minutes high activity
Time frame: 30 months
Calories
Time frame: 30 months
Minutes asleep
Time frame: 30 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 Mar 2026.
- Background: PubMed 8080980Finch C. Regulators of iron balance in humans. Blood. 1994 Sep 15;84(6):1697-702. No abstract available.
- Background: PubMed 9580307Fernandez-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.
- Background: PubMed 12145144Fernandez-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.
- Background: PubMed 24731656Fernandez-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.
- Background: PubMed 26813526Fernandez-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.
- Background: PubMed 26765579Moreno-Navarrete JM, Blasco G, Xifra G, Karczewska-Kupczewska M, Stefanowicz M, Matulewicz N, Puig J, Ortega F, Ricart W, Straczkowski M, Fernandez-Real JM. Obesity Is Associated With Gene Expression and Imaging Markers of Iron Accumulation in Skeletal Muscle. J Clin Endocrinol Metab. 2016 Mar;101(3):1282-9. doi: 10.1210/jc.2015-3303. Epub 2016 Jan 14.
- Background: PubMed 27745814Moreno-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.
- Background: PubMed 29082606Moreno-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.
- Background: PubMed 28886251Fernandez 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.
- Background: PubMed 25163604Geijselaers 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.
- Background: PubMed 28857651Kharabian Masouleh S, Beyer F, Lampe L, Loeffler M, Luck T, Riedel-Heller SG, Schroeter ML, Stumvoll M, Villringer A, Witte AV. Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults. J Cereb Blood Flow Metab. 2018 Feb;38(2):360-372. doi: 10.1177/0271678X17729111. Epub 2017 Aug 31.
- Background: PubMed 16443885Ryan CM, Freed MI, Rood JA, Cobitz AR, Waterhouse BR, Strachan MW. Improving metabolic control leads to better working memory in adults with type 2 diabetes. Diabetes Care. 2006 Feb;29(2):345-51. doi: 10.2337/diacare.29.02.06.dc05-1626.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
José Manuel Fernández-Real, M.D., Ph.D. principal investigator
Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Obesity, run by Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta at 1 site in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 12 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 31 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Concentration of advanced glycation end products (AGE) receptor agonists. (time frame: 30 months). The study lists 9 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05345106, which also lists 39 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 31 Mar 2026.