Alzheimer’s disease (AD) is one of the most prevalent and clinically challenging neurodegenerative disorders worldwide [1]. In 2024, it affects nearly 7 million Americans aged 65 and older, and as populations continue to age, U.S. care costs are expected to exceed $1 trillion annually by 2050 [2]. Globally, AD cases are projected to rise to 78 million by 2030 and 153 million by 2050, placing an immense socioeconomic and healthcare burden on societies [3]. Although the precise etiology of AD remains elusive, extensive evidence implicates amyloid-β (Aβ) misfolding, tau hyperphosphorylation, and their abnormal aggregation as key drivers of neuronal injury and death, ultimately leading to irreversible cognitive decline [4]. As a progressive and currently incurable condition, existing therapeutic strategies for AD are limited to symptomatic relief and modest delays in disease progression [5]. However, increasing evidence indicates that neuronal and synaptic dysfunction during the earliest stages of AD precedes irreversible neurodegeneration and may remain partially reversible [6]. In this context, identifying individuals at risk and intervening during this critical window could significantly slow disease progression, improve patient outcomes, and reduce the overwhelming burden on families and healthcare systems [7]. Nevertheless, early-stage AD often remains clinically silent; by the time patients exhibit noticeable symptoms, the optimal intervention window has usually closed, rendering timely treatment exceedingly challenging [8]. To address this, developing more accessible and scalable tools for early AD diagnosis and screening has become a central goal in both clinical practice and research.
Currently, numerous early diagnostic methods for AD have been developed, mainly including genetic testing [9], cognitive and neuropsychological assessment [10], neuroimaging techniques [11], and body fluid biomarker analysis [12]. Genetic testing is particularly effective for detecting familial AD cases, but it provides limited predictive value for sporadic AD, which constitutes the vast majority of cases. Cognitive assessments are non-invasive and cost-effective, yet they typically lack sufficient sensitivity to detect impairments at the preclinical stage. Neuroimaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), provide high-resolution insights into structural and functional brain changes, though they are often expensive and available only at specialized medical centers. Body fluid biomarker analysis, such as the measurement of Aβ and tau proteins in cerebrospinal fluid (CSF), can provide direct evidence of pathological changes but typically requires lumbar puncture (spinal tap). Collectively, these approaches provide complementary information, but their use for broad screening remains limited by cost, accessibility, procedural complexity, and, in some settings, suboptimal accuracy. Point-of-care testing (POCT) technologies have recently gained attention as a promising approach to addressing this gap [13]. By enabling decentralized, timely, and accessible biomarker assessment without reliance on specialized laboratory infrastructure, POCT offers a feasible and scalable solution to expand diagnostic reach and support large-scale screening efforts. Therefore, there is an urgent need for diagnostic tools that are accurate, rapid, cost-effective, scalable, and user-friendly, as well as for portable or home-testing devices that enable early AD detection and population-level screening, including among older adults and among middle-aged adults over 30 years old.
In this review, we outline the current understanding of AD pathogenesis and progression and summarize existing clinical approaches for early AD detection, highlighting their respective strengths and limitations. The core focus of this review is to systematically examine recent advances in POCT technologies for early diagnosis and large-scale population screening (Fig. 1). We categorize and compare representative POCT platforms with respect to their sensing mechanisms, analytical performance, and translational potential. Finally, we explore future directions in POCT development and present our perspectives on potential strategies to overcome existing barriers and enhance its clinical applicability for early AD diagnosis. The development of POCT technologies for AD has the potential to make a meaningful clinical impact on the aging population and to benefit public health and healthcare systems.