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NCT Number: NCT06097065

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

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.

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Key information

Sex eligibility

All sexes

Study type

Observational

Primary location

Zhujiang Hospital of Southern Medical University

Guangzhou, Guangdong, 510000, China

Location status: Recruiting

Location contact

Nianyi Zeng

CONTACT

[email protected]

13928801657 ext. +86

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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)).

  • 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).

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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.

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Treatment and study plan

Oral glucose tolerance test

Diagnostic Test

Grouping based on detected oral glucose tolerance test results without any other intervention.

Primary outcomes

  1. Number and types of proteins/peptides differential characteristic peaks

    Time frame: one year

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

Secondary outcomes

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

    Time frame: one year

    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.

Study contacts

Contact information is provided by the study sponsor or research team.

Hongwei Zhou, Professor

CONTACT

[email protected]

18688489622 ext. +86

Nianyi Zeng

CONTACT

[email protected]

13928801657 ext. +86

Sponsors and collaborators

Lead sponsor

Zhujiang Hospital

Other

Registry information

Important dates

Study start
2022
Primary completion
2025
Study completion
2026
First posted
Oct 24, 2023
Registry last updated
Oct 24, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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