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.

LabMedica

Download Mobile App
Recent News Expo Clinical Chem. Molecular Diagnostics Hematology Immunology Microbiology Pathology Technology Industry Focus

Protein Signatures in Blood Can Predict Risk of Developing More Than 60 Diseases

By LabMedica International staff writers
Posted on 23 Jul 2024
Print article
Image: Protein ‘signatures’ obtained via a blood sample can be used to predict the onset of 67 diseases (Photo courtesy of Queen Mary University of London)
Image: Protein ‘signatures’ obtained via a blood sample can be used to predict the onset of 67 diseases (Photo courtesy of Queen Mary University of London)

Measuring specific proteins to diagnose conditions like heart attacks, where troponin is tested, is a well-established clinical practice. Now, new research highlights the broader potential of protein measurements from a small blood sample to predict a variety of diseases.

In the research, published in Nature Medicine, which was carried out as part of an international partnership involving Queen Mary University of London (London, UK), the investigators used data from the UK Biobank Pharma Proteomics Project (UKB-PPP). This project represents the largest proteomic study to date, analyzing around 3,000 plasma proteins from over 40,000 randomly selected UK Biobank participants. These protein measurements are linked to detailed electronic health records. The researchers applied sophisticated analytical techniques to identify a specific 'signature' of 5 to 20 key proteins for predicting each disease. They discovered that these protein 'signatures' can predict the onset of 67 different diseases, including multiple myeloma, non-Hodgkin lymphoma, motor neuron disease, pulmonary fibrosis, and dilated cardiomyopathy.

The study found that protein prediction models outperformed the ones based on standard clinical information such as blood cell counts, cholesterol levels, kidney function, and diabetes indicators (glycated hemoglobin). While the benefits of measuring and discussing cardiovascular risks are well known, this research introduces new predictive possibilities for a broad spectrum of diseases, particularly rarer ones that often require prolonged periods to diagnose. These insights could lead to significantly faster and more timely diagnoses. However, these findings still need to be validated across different populations, including symptomatic and asymptomatic individuals, and across various ethnic groups.

“Several of our protein signatures performed similar or even better than proteins already trialed for their potential as screening tests, such a prostate-specific antigen for prostate cancer,” said Dr. Julia Carrasco Zanini Sanchez, first author and research student at GSK and the University of Cambridge at the time and now a postdoctoral researcher at PHURI. “We are therefore extremely excited about the opportunities that our protein signatures may have for earlier detection and ultimately improved prognosis for many diseases, including severe conditions such as multiple myeloma and idiopathic pulmonary fibrosis. We identified so many promising examples, the next step is to select high priority diseases and evaluate their proteomic prediction in a clinical setting.”

Related Links:
Queen Mary University of London

Gold Member
Flocked Fiber Swabs
Puritan® Patented HydraFlock®
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Cytomegalovirus Real-Time PCR Test
Quanty CMV Virus System
New
Benchtop Cooler
PCR-Cooler & PCR-Rack

Print article

Channels

Clinical Chemistry

view channel
Image: The GlycoLocate platform uses multi-omics and advanced computational biology algorithms to diagnose early-stage cancers (Photo courtesy of AOA Dx)

AI-Powered Blood Test Accurately Detects Ovarian Cancer

Ovarian cancer ranks as the fifth leading cause of cancer-related deaths in women, largely due to late-stage diagnoses. Although over 90% of women exhibit symptoms in Stage I, only 20% are diagnosed in... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: The new algorithms can help predict which patients have undiagnosed cancer (Photo courtesy of Adobe Stock)

Advanced Predictive Algorithms Identify Patients Having Undiagnosed Cancer

Two newly developed advanced predictive algorithms leverage a person’s health conditions and basic blood test results to accurately predict the likelihood of having an undiagnosed cancer, including ch... Read more

Industry

view channel
Image: The collaboration aims to leverage Oxford Nanopore\'s sequencing platform and Cepheid\'s GeneXpert system to advance the field of sequencing for infectious diseases (Photo courtesy of Cepheid)

Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions

Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more