Lysosomal storage disorders (LSDs) and adult neurodegenerative disorders like Alzheimer's disease (AD) share various clinical and pathophysiological features. LSDs are characterized by impaired lysosomal activity caused by mutations in key proteins and enzymes. While lysosomal dysfunction is also linked to AD pathogenesis, its precise role in disease onset or progression remains unclear. Lysosomal ionic homeostasis is recognized as a key feature of many LSDs, but it has not been clinically linked with AD pathology. Thus, investigating whether this regulation is disrupted in AD is important, as it could lead to new therapeutic targets and biomarkers for this multifactorial disease. Here, using two-ion mapping (2-IM) technology, we quantitatively profiled lysosomal pH and Ca2+ in blood-derived monocytes from AD patients and age-matched controls and correlated lysosome ionicity with age and key markers of AD pathology, namely, amyloid deposits, tauopathy, neurodegeneration, and inflammation. Together, the data show that the ionic milieu of lysosomes is dysregulated in monocytes of AD patients and correlates with key plasma biomarkers of AD. Using a machine learning model based on the above parameters, we describe a proof-of-concept combinatorial biomarker platform that accurately distinguishes between patients with AD and control participants with an area under the curve of >96%. Our study introduces a convenient, noninvasive platform with the potential to diagnose Alzheimer's disease based on fluid, cellular, and molecular biomarkers. Further, these findings highlight the potential for investigating therapeutic mechanisms capable of restoring lysosome ionic homeostasis to ameliorate AD.