A fully automated, ultrasensitive luminescence cascade sensor to address hepatitis C diagnostic disparity

Public summary

* HCV infects 1.5 million people yearly, with American Indians and Alaska Natives most affected.

* Current two-step diagnostics are costly and slow and lead to high dropout rates among patients.

* Developed a sensitive, user-friendly, automated point-of-care antigen test based on bioluminescence imaging.

* In 71 AI/AN samples, the assay showed 97% sensitivity, 94% specificity, and 96% accuracy within 30 min.

* This technology enables early intervention and expands HCV screening in resource-limited settings.

Abstract

Viral hepatitis poses a significant global health burden, with chronic hepatitis B and C causing about 1 million annual deaths from liver cancer and cirrhosis. Over 1.5 million new hepatitis C virus (HCV) cases arise yearly, especially among vulnerable groups like American Indians and Alaska Natives (AI/AN). Despite effective direct-acting antivirals, early HCV diagnosis remains challenging, particularly in resource-limited settings. Current two-step testing methods are costly and prone to patient dropout. Point-of-care (POC) HCV antigen (Ag) testing offers a promising early detection approach, but no US Food and Drug Administration (FDA)-approved POC test meets the sensitivity and specificity needed for low viral loads. To address this, we developed a fully automated bioluminescence-based POC assay using a cascade-based signal amplification strategy. Evaluated on 71 AI/AN samples, it showed 97% sensitivity, 94% specificity, and 96% accuracy. This technology can improve health equity by enabling accessible and reliable HCV testing for disproportionately affected populations.