Biomarkers, Diabetes Mellitus, Diabetic Kidney Disease, Early Diagnosis
Conditions
Brief summary
Diabetic kidney disease(DKD) is a leading cause of chronic kidney disease and end-stage renal disease across the world. Early identification of DKD is vitally important for the effective prevention and control of it. However, the available indicators are doubtful in the early diagnosis of DKD. This study aims to develop a novel system of multidimensional network biomarkers (MDNBs) to estimating early diabetic nephropathy, and further validating the performance of the novel systemin in prediction of the risk for early diabetic nephropathy by a nested case-control study.
Detailed description
Patients with a history of more than 5 years of diabetes without DKD were recruited. At the baseline visit, the patients' serum, plasma and urine were collected after obtaining informed patient consent. Simultaneously, the basic information, anthropometric indicators (including height, weight, waist circumference, hip circumference, blood pressure), past history, family history, menstrual history, birth history, medication history, lifestyle of the patients were registered, and the corresponding laboratory examination and auxiliary examination were carried out according to the diagnostic process. All data and data were entered into the database for later analysis. After 5years of follow up, subjects will be divided into two groups(the new onset DKD group and the non-DKD group), the base line level of MDNBs were tested in the two group to validate the performance of the novel MDNBs in in prediction of the risk for early diabetic nephropathy.
Interventions
None listed
Sponsors
Second Affiliated Hospital of Wenzhou Medical University
Lishui Country People's Hospital
Second Affiliated Hospital, School of Medicine, Zhejiang University
Study design
Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
20 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
* Subjects who have signed informed consent. * Subjects who were diagnosed with diabetes at least 5 years. * Subjects showed good compliance, and the follow-up data was available for \>5 years.
Exclusion criteria
* Renal diseases caused by other causes, including primary and secondary; * All kinds of acute infections; * The expected life expectancy (life expectancy or related diseases) was less than 5 years according to the researcher's judgment. * Drug users or drug abusers; * Sexually transmitted diseases such as viral hepatitis, AIDS and syphilis, and infectious diseases such as tuberculosis are in an active period; * Any situation judged by the researcher that affects enrollment.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| multidimensional network biomarkers | 5years | a novel system of multidimensional network biomarkers (MDNBs) based on a widely targeted metabolomics. Our previous study demonstrated that the combination of Linolelaidic Acid (C18:2N6T), L-Dihydroorotic Acid, and Azoxystrobin Acid might serve as a potential multidimensional network biomarkers of DKD. So we create a panel of MDNBs containing these biomakers as primary outcome measure. |
Contacts
Primary ContactZheng Chao, MD, PhD
Backup ContactYikai Zhang, PhD
Outcome results
None listed