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.