Research on Potential Biomarkers of Prediabetes and Diabetes Based on MALDI-TOF MS Platform.

Zhujiang Hospital2,860 enrolled

Overview

Through the MALDI-TOF MS platform, explore the proteomics and peptidomics differences of fasting serum/plasma and urine between non pregnant people with normal glucose tolerance test and prediabetes /diabetes patients, pregnant people with normal glucose tolerance test and pregnant diabetes patients respectively; To explore the role of its proteomics and peptidomics differences in the diagnosis of prediabetes and diabetes, and to establish a new method of differential diagnosis by using the omics data and key characteristic peaks to find potential new diagnostic markers.

Prediabetes is a stage of abnormal glucose metabolism between normal blood glucose level and diabetes, which is a "gray zone" between normal and abnormal, including impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or both. It is a very important high-risk group of diabetes. Diabetes is a group of metabolic diseases characterized by hyperglycemia caused by a variety of causes. Gestational diabetes mellitus refers to varying degrees of abnormal glucose metabolism that occur during pregnancy. This project aims to detect differential feature peaks through MALDI-TOF MS technology between non pregnant people with normal glucose tolerance test and prediabetes/diabetes patients, pregnant people with normal glucose tolerance test and pregnant diabetes patients respectively and to establish a clinical predictive diagnostic model based on differences, and to evaluate the model.

Study Type

OBSERVATIONAL

Enrollment

2,860

Conditions

Prediabetes Diabetes Mellitus Gestational Diabetes Mellitus

Eligibility

Sex: ALLHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: 1. Inclusion criteria for cases: Non pregnant people: the remaining fasting serum/plasma and urine samples of prediabetes/diabetes patients (prediabetes: IFG: FPG 6.1-6.9mmol/L, Blood glucose 2h after meal\<7.8mmol/L（WHO）; IGT: FPG\<7.0mmol/L, Blood glucose 2h after meal 7.8-11.1mmol/L（WHO）; diabetes: Typical symptoms of diabetes, FPG \>= 7.0mmol/L or 75g OGTT 2h blood glucose \>= 11.1mmol/L). Pregnant people: the remaining fasting serum/plasma and urine samples of gestational diabetes patients (75g OGTT test FPG \>= 5.1mmol/L or 1h blood glucose \>= 10.0mmol/L or 2h blood glucose \>= 8.5mmol/L（IADPSG; ADA)). 2. Inclusion criteria of the controls were as follows: Non pregnant people: the remaining fasting serum/plasma and urine samples of normal population for glucose tolerance test (FPG 3.9-6.1mmol/L,75g OGTT test 1h blood glucose 6.7-11.1mmol/L,75g OGTT test 2h blood glucose 3.6-7.8mmol/L). Pregnant people: the remaining fasting serum/plasma and urine samples of people who do not meet the diagnostic criteria for gestational diabetes (3.9\<=75g OGTT test FPG\<5.1mmol/L,6.7 \<= 1h blood glucose\<10.0mmol/L,3.6\<=2h blood glucose\<8.5mmol/L). \- Exclusion Criteria: Common exclusion criteria for cases and control were as follows: The sample volume of serum/plasma/urine is less than 300ul; Improper storage of samples or repeated freezing and thawing; The serum /plasma has obvious hemolysis, lipemia or jaundice. \-

Outcomes

Primary Outcomes

Number and types of proteins/peptides differential characteristic peaks

Obtain the number and types of proteins/peptides differential characteristic peaks between the case group and the control group through data analysis.

Time frame: one year

Secondary Outcomes

ROC curve and area under curve AUC of clinical predictive diagnostic model

Construct a clinical predictive diagnostic model based on the obtained proteins/peptides differential feature peaks and calculate the area under the ROC curve AUC to evaluate the predictive effect of the model.