Mid-ATR-FTIR Spectroscopic Profiling of HIV/AIDS Sera for Novel Systems Diagnostics in Global Health

Abstract

Abstract Global health, whether in developed or developing countries, is in need of robust systems diagnostics for major diseases, such as HIV/AIDS, impacting the world populations. Fourier transform Infrared (FTIR) spectroscopy of serum is a quick and reagent-free methodology with which to analyze metabolic alterations such as those caused by disease or treatment. In this study, Attenuated Total Reflectance Fourier-Transform (ATR-FTIR) Spectroscopy was investigated as a means of distinguishing HIV-infected treatment-experienced (HIV pos ART pos , n =39) and HIV-infected-treatment-naïve (HIV pos ART neg , n =16) subjects from uninfected control subjects ( n =30). Multivariate pattern recognition techniques, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), successfully distinguished sample classes, while univariate approaches identified significant differences ( p <0.05) after Benjamini-Hochberg corrections. OPLS-DA discriminated between all groups with sensitivity, specificity, and accuracy of >90%. Compared to uninfected controls, HIV pos ART pos and HIV pos ART neg subjects displayed significant differences in spectral regions linked to lipids/fatty acids (3010 cm −1 ), carbohydrates (1299 cm −1 ; 1498 cm −1 ), glucose (1035 cm −1 ), and proteins (1600 cm −1 ; 1652 cm −1 ). These are all molecules shown by conventional biochemical analysis to be affected by HIV/ART interference. The biofluid metabolomics approach applied here successfully differentiated global metabolic profiles of HIV-infected patients and uninfected controls and detected potential biomarkers for development into indicators of host response to treatment and/or disease progression. Our findings therefore contribute to ongoing efforts for capacity-building in global health for robust omics science and systems diagnostics towards major diseases impacting population health.