Inter-relationships Among Glucose, Brain, Gut Microbiota and MicroRNAs (IRONmiRNA).

Overview

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.

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 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). B. 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: 1. Subsidiary data: Age, sex, and birth date. 2. 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. 3. 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. 4. 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). 5. 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. 6. 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. 7. 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. 8. 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).