A novel biomarker signature based on circulating transfer RNA (tRNA) can detect and differentiate HIV-2 infection from HIV-1

Abstract

ABSTRACT HIV-1 and HIV-2 share transmission and replication characteristics, but require clinical differentiation. HIV-2 exhibits lower viral loads and slower disease progression, and most patients remain long-term non-progressors. Differentiation is crucial for selecting appropriate viral load monitoring tests and avoiding ineffective antiretroviral treatments, particularly non-nucleoside reverse transcriptase inhibitors, and certain protease inhibitors that do not work against HIV-2. Increased PrEP use may result in new infections testing negative for viral markers. This study aims to identify circulating tRNA expression profiles that could serve as non-viral biomarkers to detect and differentiate HIV-2 from HIV-1 infections. An initial pilot study analyzed 88 tRNAs in plasma samples from HIV-1- (n = 4) and HIV-2 (n = 4)-infected individuals, plus four healthy controls, using a tRNA-based PCR array for target identification. Eighteen selected tRNAs were further analyzed in a larger independent group of samples: HIV-1 (n = 20), HIV-2 (n = 20), and healthy controls (n = 20) for independent verification. A plasma tRNA diagnostic model was developed from these results and evaluated in 24 independent samples to detect and differentiate HIV-2 from HIV-1 infection. We identified a tRNA-based model (Model-II) containing six differentially expressed tRNAs (Leu-TAA, mt-Asp-GTC, mt-Ala-TGC, mt-Lys-TTT, mt-LeuT-AA, and Gly-CCC-1) that could detect HIV-2 infection and distinguish it from HIV-1 infection and healthy controls with 100% accuracy, sensitivity, and specificity. We also found that other blood-borne viruses such as HTLV, HBV, and HCV had no cross-reactivity with HIV-2, demonstrating that Model-II is specific for HIV-2 infection. This study establishes proof of concept for tRNA expression profiles as HIV diagnostic biomarkers. The tRNA-based Model-II represents a promising diagnostic tool for identifying HIV-2 infection and differentiating it from HIV-1. IMPORTANCE HIV-2 infection requires accurate differentiation from HIV-1 to guide appropriate antiretroviral therapy, as HIV-2 exhibits intrinsic resistance to non-nucleoside reverse transcriptase inhibitors and certain protease inhibitors. Current diagnostic challenges include the absence of FDA-approved HIV-2 RNA quantification assays and potential false-negative results in LEVI (low-level viremia with evolving viral infection) syndrome patients on pre-exposure prophylaxis (PrEP), in whom viral markers may be undetectable. We developed a novel diagnostic approach using circulating transfer RNA (tRNA) expression profiles as host-derived, non-viral biomarkers. Our six-tRNA panel (Model-II) achieved 100% accuracy, sensitivity, and specificity in detecting HIV-2 infection while distinguishing it from HIV-1 and other blood-borne viral infections (HTLV, HBV, and HCV). This represents the first tRNA-based diagnostic model for HIV, offering a promising complementary tool for early detection and accurate viral differentiation, particularly in clinical scenarios where traditional viral markers are absent or unreliable. HIV-2 infection requires accurate differentiation from HIV-1 to guide appropriate antiretroviral therapy, as HIV-2 exhibits intrinsic resistance to non-nucleoside reverse transcriptase inhibitors and certain protease inhibitors. Current diagnostic challenges include the absence of FDA-approved HIV-2 RNA quantification assays and potential false-negative results in LEVI (low-level viremia with evolving viral infection) syndrome patients on pre-exposure prophylaxis (PrEP), in whom viral markers may be undetectable. We developed a novel diagnostic approach using circulating transfer RNA (tRNA) expression profiles as host-derived, non-viral biomarkers. Our six-tRNA panel (Model-II) achieved 100% accuracy, sensitivity, and specificity in detecting HIV-2 infection while distinguishing it from HIV-1 and other blood-borne viral infections (HTLV, HBV, and HCV). This represents the first tRNA-based diagnostic model for HIV, offering a promising complementary tool for early detection and accurate viral differentiation, particularly in clinical scenarios where traditional viral markers are absent or unreliable.