Assessment of non-invasive colorimetric methods for pH and glucose determination in human saliva

Abstract

Monitoring glycemic biomarkers such as glucose is essential for the management of metabolic diseases such as obesity and its associated comorbidities. Traditional methods for glucose monitoring are based on invasive blood tests, using other biological fluids like saliva could be an alternative. Point-Of-Care Tests (POCT) are widely used for saliva analysis using colorimetric enzyme-based methods. However, the influence of pH on enzymatic activity is often overlooked in the development of such analytical devices. This study aims to assess the effectiveness of non-invasive colorimetric methods for pH determination, and glucose quantification by microfluidic paper-based analytical devices (μPADs) for the analysis of human saliva samples. Colorimetric methods were developed for pH determination using spectrophotometry with bromothymol blue, image analysis of the color channel of test strips using a smartphone, and adaptation of this method to an App. The effect of pH on (μPADs) for glucose quantification was analyzed in buffer solutions, pH determination methods and the μPAD for glucose quantification were validated in saliva samples from 29 healthy subjects. Test strips and the App performed better than spectrophotometry when tested in saliva, yielding a mean of pH 7.58. NaOH was selected as the wet etching agent in the fabrication of the μPAD for glucose quantification (LOD of 0.14 mM), at a pH 6 device’s response was significantly affected. Although no correlation was found between pH and salivary glucose, pH may provide insight into oral health. In addition, a moderate positive correlation (r=0.53, p-value=0.0054) was found between salivary glucose and body mass index (BMI), suggesting a potential application in metabolic monitoring. Implementing colorimetric methods (pH and glucose quantification) could enhance saliva analysis tools for POCT and metabolic monitoring. Therefore, it is proposed that future implementation of these methods will serve as a useful auxiliary tool for point-of-care testing, such as glycemic biomarker detection.