precision medicine approach to unravel the risk factors for renal, cardiovascular, ophthalmologic, neurologic and hepatic complications of metabolic disorders

Conditions: Chronic Kidney Diseases; Diabetes; Obesity

Summary: there is currently no way to predict the progression of chronic kidney disease in patients with metabolic disease(s). furthermore, the mechanisms responsible for the development and/or progression of complications remain largely unknown. in order to identify the predictive factors and/or mechanisms involved in the different complications of these diseases, we propose an approach coupling : * a classical phenotypic characterization (clinical, biological, imaging) of the patients * high-throughput screening of the genome, transcriptome, metabolome, proteome, and immunophenotyping. according to our hypothesis, this approach should allow : * early detection of complications * classification of patients in homogeneous groups of patients with identical evolution * identification of the molecular mechanisms involved.

eligible patients will be detected during one of their consultations at the precision medicine center of the amiens-picardy university hospital. they will be informed of the proposed research pathway during a care consultation. after a period of reflection, patients who accept this pathway will be included and a written consent form will be collected. the inclusion visit will be scheduled at the precision medicine center of the amiens-picardy university hospital and will take place during a day hospital (hdj) which is part of a routine care pathway (neurological, cardiovascular, hepatic and renal primary prevention). at the time of inclusion, the informed consent will be signed by the investigator as well as by the patient the collection of data obtained during the patient's routine care will be performed by a physician from the precision medicine center and a clinical research nurse and will be recorded in the patient's medical record. biological samples for the research (additional blood volume, urine) will be taken in conjunction with those for the routine check-up. a hair strand of approximately 100 hairs (approx. 2 mm diameter) will be collected at the inclusion visit. this sample will be optional and will be subject to a specific authorization from the patient on the consent form. biological samples intended for research will be sent by the department's staff to the biobank of picardie (chu amiens-picardie) for processing and storage. the follow-up of the patient will be done strictly within the framework of his care adapted to his pathology. no visits will be made specifically for research purposes. the schedule of follow-up visits for the study corresponds to the visits usually scheduled as part of patient care: at 1 year after the inclusion visit (a1), at 4 years (a4) and at 7 years (a7). in summary: one year after the inclusion visit, the patient will have a clinical and biological evaluation including a measurement of renal function to determine the rate of decline of glomerular filtration rate in order to classify the patient as a non-progressor, a moderate-progressor, or a rapid-progressor (see primary endpoints). the rate of decline of gfr will be correlated with clinical, biological, genetic and environmental data collected at patient inclusion, by means of dedicated questionnaires, biological results collected and analyses performed on research samples taken during the patient inclusion visit. the prognostic power of the classic clinical and biological criteria and of the new biomarkers discovered during the study to predict the patient's all-cause evolutionary profile will be evaluated́ by hazard ratio and 95% confidence interval. this reassessment will then be repeated at each visit until the end of the study. follow-up visits will be conducted in the same manner as the inclusion visit. the collection of data obtained during the routine care follow-up will be performed by a precision medicine center physician and a clinical research nurse and will be recorded in the patient's medical record. additional biological samples (additional volume of blood, urine) will be taken during the care samples to meet the research objectives. the occurrence of a pregnancy during the follow-up period will not constitute an exclusion criterion. the patient will be able to continue her participation in the study. failure to complete one of the follow-up visits will not be considered an early exit from the research. the patient will be scheduled for the next protocol visit.

Eligibility criteria:
inclusion criteria: * adult persons, male or female, age ≥ 18 and ≤ 65 years * persons able to understand the information provided and to object to it (at the discretion of the investigator) * patient affiliated to a social security system. * patient willing to sign an informed consent form * patient with the following metabolic profile diabetic (of any type) treated or not (diabetes will be defined by a fasting blood glucose \> 7mm or a hba1c \> 6.5% or by the use of an antidiabetic treatment) and/or obese patient (bmi \> 30 kg/m2) treated or not * patient with evidence of renal parenchymal damage defined by an albuminuria/creatinuria ratio ≥ 3 mg/mmol (30mg/g), and/or a glomerular filtration rate estimated by the ckd-epi (edfg) formula classifying the patient as stage 2 to 3a of the kdigo classification (i.e., 90ml/min/1.73 m2 \> gfr \> 45ml/min), and/or a renal lithiasis exclusion criteria: * patient deprived of liberty * person subject to a legal protection measure (guardianship, curatorship or safeguard of justice) * patient refusing to participate in the study * pregnant, parturient or nursing woman * patient in emergency situation * patient with advanced chronic kidney disease defined as gfr \< 45ml/min/1.73 m². * contraindication to iohexol injection * patient with or who has had any of the following complications: symptomatic coronary artery disease, symptomatic peripheral arterial disease, previous stroke, previous myocardial infarction, heart failure ≥ stage b, dementia, liver fibrosis, hepatocarcinoma.

Keywords: chronic kidney diseases diabetes precision medicine biomarkers