Signature of the Risk Profile of Mortality in a Hospital Cohort of Patients With Metabolic Diseases
Signature of the Risk Profile of Mortality in a Hospital Cohort of Patients With Metabolic Diseases
Epidemiological studies are usually conducted in the general population in adults without
 complications or pathology at baseline. The results obtained are therefore often better
 designed for primary prevention use. The prediction of mortality risk in patients with
 complications and requiring hospital follow-up is less well known.

 The study purpose is to determine a mortality risk profile in a hospital cohort of patients
 with pathologies associated with metabolic diseases.

 Today the "multimaker" scores based on a panel of biomarkers - have significantly improved
 the discriminating power of prediction models existing in many pathologies. It is no longer a
 single biomarker that can improve risk prediction but a complete and cross-sectional profile
 that is sought after. We aim to establish a personalised mortality risk profile by combining
 clinical and biological parameters including metabolomics, genetics, transcriptomics and
 epigenomics by high throughput screening of biological samples.
The prediction of the onset of diabetes and metabolic complications, especially
 cardiovascular, renal, or hepatic, is a major challenge to optimize the management of this
 disease.

 Teams from the University Hospital of Lille have developed the Integra cohort study to
 identify the clinical and biological determinants of the occurrence of these complications
 and the mortality of patients with metabolic disorders.

 The aim of the study is to identify clinico-biological determinants that are able to predict
 the occurence of death, cardiovascular events as well as hepatic or nephrotic one.

 Follow-up data will be collected from National System of Health Data (SNDS) where data
 concerning hospitalisations, medical consultations and treatments are registered.

 Biological samples are collected at baseline for a large OMICs analysis (metabolomics,
 genetics, transcriptomics and epigenomics) that would feed our predictive scoring system.

 This project will allow us to describe new models of prediction of metabolic diseases and its
 complications, and to offer adapted and personalised methods of management, which can slow
 the progression of the disease and improve its prognosis.
Inclusion Criteria:

 -  Diabetic: antecedent - treatment - or glycemia> = 1.26 g / dl - or HbA1C> = 6.5% and
 or

 -  Obese: BMI> = 30 and or

 -  Metabolic syndrome defined AND

 -  Patient having given written consent to participate in the study or collection of the
 consent of the witness

 -  Social insured patient (excluding AME)

 -  Patient willing to comply with all procedures of the study and its duration AND

 Patient also presenting a pathology among:

 -  Cardiology:

 -  Coronary patient(history of myocardial infarction, coronary bypass, or coronary
 angioplasty or stenosis greater than 50% on an epicardial vessel documented on
 coronary angiography)

 -  Patient with systolic or diastolic heart failure

 -  Patient with atrial fibrillation

 -  Patient with aortic stenosis (Vmax> 2.5 m / s)

 -  Patient with high blood pressure

 -  neurology:

 -  ischemic stroke

 -  intracerebral hemorrhage

 -  transient ischemic attack

 -  diabetology:

 -  Obesity without diabetes

 -  Diabetes T2

 -  T1 diabetes

 -  Monogenic Diabetes / MODY

 -  African Diabetes

 -  Diabetes secondary to pancreatopathy / liver cirrhosis

 -  Diabetes post transplantation / post immunotherapy

 -  Diabetes associated with Steinert's disease

 -  hepatology: hepatological pathology

 -  nephrology: nephrology

 Exclusion Criteria:

 -  Unscheduled hospitalization less than 3 months old

 -  Ongoing treatment :

 -  Cytotoxic chemotherapy

 -  Radiotherapy

 -  HIV and / or HCV and / or active HBV infection

 -  OMS score> = 2

 -  Pregnant woman