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Ulster University Researchers Discover Novel Protein Markers for Early CKD Diagnosis and COVID-19 Severity Prediction

7 months ago3 min read

Key Insights

  • Researchers at Ulster University have identified protein markers in senescent cells for earlier diagnosis and more effective treatment of Chronic Kidney Disease (CKD).

  • The novel method allows healthcare providers to quickly determine which CKD patients are likely to maintain stable kidney function versus those who may worsen.

  • Specific proteins and genetic markers associated with severe COVID-19 cases were identified, aiding in predicting patients at risk of serious symptoms or long-term effects.

Researchers at Ulster University’s Personalised Medicine Centre in Derry have made a significant breakthrough by developing a faster method of diagnosing Chronic Kidney Disease (CKD) and predicting the severity of COVID-19. This pioneering research focuses on identifying specific protein markers in senescent cells—aged cells that stop dividing but don’t die—offering new opportunities for earlier diagnosis, more effective treatments, and potentially even disease prevention.

Novel Markers for CKD Diagnosis

Chronic Kidney Disease (CKD) is a widespread condition, with 79,098 people diagnosed in Northern Ireland in 2022/23. Currently, CKD is often detected through routine blood or urine tests conducted for unrelated health issues, meaning patients may not receive a diagnosis until the disease has significantly progressed. The Ulster University researchers have discovered a novel way to use cellular senescence to identify protein markers that indicate CKD severity.
"This is a huge step forward in our understanding of CKD," said Dr. Taranjit Singh Rai, Senior Lecturer at Ulster University’s School of Medicine. "Earlier diagnosis means patients can receive treatment sooner, reducing the number of those who require dialysis, which will ease the strain on NHS renal services."
These markers will allow healthcare providers to quickly determine which patients are likely to maintain stable kidney function and which may experience a worsening of their condition. This breakthrough could revolutionize how CKD is diagnosed and managed. The financial burden of dialysis treatment remains a challenge for the NHS, and this research has the potential to significantly reduce these costs by diagnosing CKD earlier, preventing the need for dialysis in many cases.

Predicting COVID-19 Severity

The team’s research also extends to COVID-19, where they have identified specific proteins and genetic markers associated with more severe cases of the virus. Their findings will help predict which patients are at risk of developing serious symptoms or long-term post-COVID syndrome. By detecting these markers early, healthcare providers will be able to offer better-targeted care, ensuring that the most vulnerable patients receive timely interventions.
"The ability to predict severe cases of COVID-19 at an earlier stage could transform how we manage the virus in the future," added Dr. Rai. "This research could play a key role in reducing hospital admissions and ICU pressures by guiding clinical care more effectively."

Impact on Healthcare

This breakthrough holds significant promise for healthcare systems. With the potential to diagnose CKD earlier, healthcare providers will be able to offer more effective management of the disease, helping to prevent its progression and reducing the number of patients requiring costly dialysis treatment. The research’s application to COVID-19 could also help alleviate pressures on intensive care units by ensuring that at-risk patients are identified early and given the care they need. This would result in more efficient use of resources and better patient outcomes.
The research was conducted at the Personalised Medicine Centre, part of the School of Medicine at Ulster University based at the Altnagelvin Hospital site in Derry’s C-TRIC building. The Centre is the largest dedicated research hub for personalised medicine in Ireland. Its work focuses on tailoring medical treatment to individual patients, ensuring that the right treatment is provided to the right person at the right time.
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