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
PURITAN MEDICAL

Download Mobile App




AI Algorithm Predicts Diabetic Kidney Disease through Blood Tests

By LabMedica International staff writers
Posted on 01 Jun 2023
Print article
Image: New algorithm can predict diabetic kidney disease (Photo courtesy of Freepix)
Image: New algorithm can predict diabetic kidney disease (Photo courtesy of Freepix)

Diabetes is globally recognized as the main contributor to kidney failure. Notable advancements have been made in devising treatments for kidney disease in diabetic patients. Yet, evaluating an individual's risk for kidney disease based solely on clinical factors can be challenging. Consequently, identifying who is most susceptible to developing diabetic kidney disease is a vital clinical need. Now, scientists have created a computational method that predicts the likelihood of a person with type 2 diabetes developing kidney disease, a common yet severe diabetes complication. This could aid physicians in preventing or improving the management of kidney disease in type 2 diabetes patients.

The new algorithm developed by researchers from Sanford Burnham Prebys (La Jolla, CA, USA) and the Chinese University of Hong Kong (CUHK, Hong Kong) relies on measuring a process known as DNA methylation, which is the accumulation of subtle changes in the DNA. DNA methylation can provide essential insights into gene activation and deactivation and can be easily measured via blood tests.

Utilizing comprehensive data from over 1,200 type 2 diabetes patients registered in the Hong Kong Diabetes Register, the researchers constructed their model which they also tested on an independent group of 326 Native Americans with type 2 diabetes. This confirmed the model's predictive power for kidney disease across diverse populations. The researchers are presently fine-tuning their model and extending its application to address other health and disease-related inquiries, such as why some cancer patients do not respond favorably to certain treatments.

“This study provides a glimpse into the powerful future of predictive diagnostics,” said co-senior author Kevin Yip, Ph.D., a professor and director of Bioinformatics at Sanford Burnham Prebys. “Our team has demonstrated that by combining clinical data with cutting-edge technology, it’s possible to develop computational models to help clinicians optimize the treatment of type 2 diabetes to prevent kidney disease.”

“Our computational model can use methylation markers from a blood sample to predict both current kidney function and how the kidneys will function years in the future, which means it could be easily implemented alongside current methods for evaluating a patient’s risk for kidney disease,” added Yip.

Related Links:
Sanford Burnham Prebys
CUHK 

Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Magnetic Bead Separation Modules
MAG and HEATMAG
Anti-Cyclic Citrullinated Peptide Test
GPP-100 Anti-CCP Kit
New
Gold Member
Plasma Control
Plasma Control Level 1

Print article

Channels

Clinical Chemistry

view channel
Image: The 3D printed miniature ionizer is a key component of a mass spectrometer (Photo courtesy of MIT)

3D Printed Point-Of-Care Mass Spectrometer Outperforms State-Of-The-Art Models

Mass spectrometry is a precise technique for identifying the chemical components of a sample and has significant potential for monitoring chronic illness health states, such as measuring hormone levels... Read more

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.