We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
BIO-RAD LABORATORIES

Download Mobile App




Peptide Serum Markers Predict Type 1 Diabetes

By LabMedica International staff writers
Posted on 01 Dec 2016
Print article
Image: A diagram of Type1 diabetes as an autoimmune disease (Photo courtesy of the US National Institutes of Health).
Image: A diagram of Type1 diabetes as an autoimmune disease (Photo courtesy of the US National Institutes of Health).
Certain proteins in the blood of children can predict incipient type 1 diabetes, even before the first symptoms appear. Children who have a first-degree relative with type 1 diabetes and who consequently have an increased risk of developing the disease due to the familial predisposition.

This autoimmune process does not develop from one day to the next. Often the young patients go through longer asymptomatic preliminary stages that see the formation of the first antibodies against the child's own insulin-producing cells in the pancreas; these are the so-called autoantibodies. Biomarkers that indicate whether and when this is the case and how quickly the clinical symptoms will appear could significantly improve the treatment of patients at-risk.

Scientists at the Helmholtz Zentrum München (Munich, Germany) and their colleagues analyzed blood samples from 30 children with autoantibodies who had developed type 1 diabetes either very rapidly or with a very long delay. The team compared the data with data on children who displayed neither autoantibodies nor diabetes symptoms. In a second step with samples from another 140 children, they confirmed the protein composition differences that they found in this approach.

A double cross-validation approach was applied to first prioritize peptides from a shotgun proteomic approach in 45 islet autoantibody-positive and -negative children. Targeted proteomics for 82 discriminating peptides were then applied to samples from another 140 children from these cohorts. A total of 41 peptides (26 proteins) enriched for the functional category lipid metabolism were significantly different between islet autoantibody-positive and autoantibody-negative children. Two peptides from apolipoprotein M and apolipoprotein C-IV were sufficient to discriminate autoantibody-positive from autoantibody-negative children. Hepatocyte growth factor activator, complement factor H, ceruloplasmin and age predicted progression time to type 1 diabetes with a significant improvement compared with age alone.

Anette‐Gabriele Ziegler, MD, PhD, a professor and a senior author of the study, said, “The progression of type 1 diabetes into a clinical disease takes place over a period of time that varies from individual to individual and that at this time is insufficiently predictable. The biomarkers that we have identified allow a more precise classification of this presymptomatic stage and they are relatively simple to acquire from blood samples.” The study was published on November 4, 2016, in the journal Diabetologia.

Related Links:
Helmholtz Zentrum München

Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Magnetic Bead Separation Modules
MAG and HEATMAG
POCT Fluorescent Immunoassay Analyzer
FIA Go
Gold Member
Systemic Autoimmune Testing Assay
BioPlex 2200 ANA Screen with MDSS

Print article

Channels

Hematology

view channel
Image: The CAPILLARYS 3 DBS devices have received U.S. FDA 510(k) clearance (Photo courtesy of Sebia)

Next Generation Instrument Screens for Hemoglobin Disorders in Newborns

Hemoglobinopathies, the most widespread inherited conditions globally, affect about 7% of the population as carriers, with 2.7% of newborns being born with these conditions. The spectrum of clinical manifestations... Read more

Immunology

view channel
Image: A false color scanning election micrograph of lung cancer cells grown in culture (Photo courtesy of Anne Weston)

AI Tool Precisely Matches Cancer Drugs to Patients Using Information from Each Tumor Cell

Current strategies for matching cancer patients with specific treatments often depend on bulk sequencing of tumor DNA and RNA, which provides an average profile from all cells within a tumor sample.... Read more

Microbiology

view channel
Image: Microscope image showing human colorectal cancer tumor with Fusobacterium nucleatum stained in a red-purple color (Photo courtesy of Fred Hutch Cancer Center)

Mouth Bacteria Test Could Predict Colon Cancer Progression

Colon cancer, a relatively common but challenging disease to diagnose, requires confirmation through a colonoscopy or surgery. Recently, there has been a worrying increase in colon cancer rates among younger... Read more

Pathology

view channel
Image: Fingertip blood sample collection on the Babson Handwarmer (Photo courtesy of Babson Diagnostics)

Unique Hand-Warming Technology Supports High-Quality Fingertip Blood Sample Collection

Warming the hand is an effective way to facilitate blood collection from a fingertip, yet off-the-shelf solutions often do not fulfill laboratory requirements. Now, a unique hand-warming technology has... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.