Advanced Biosensing Technologies: Leading Innovations in Alzheimer’s Disease Diagnosis

Abstract

Diagnosing Alzheimer’s disease (AD) remains a significant challenge due to its multifactorial nature and the limitations of traditional diagnostic methods, such as clinical assessments and neuroimaging, which often lack the specificity and sensitivity required for early detection. The urgent need for innovative diagnostic tools is further underscored by the potential of early intervention to improve treatment outcomes and slow disease progression. Recent advancements in biosensing technologies offer promising solutions for precise and non-invasive AD detection. Electrochemical and optical biosensors, in particular, provide high sensitivity, specificity, and real-time detection capabilities, making them valuable for identifying key biomarkers, including amyloid-β (Aβ) peptides and tau proteins. Additionally, integrating these biosensors with nanomaterials enhances their performance, stability, and detection limits, enabling improved diagnostic accuracy. Beyond nanomaterial-based sensors, emerging innovations in microfluidics, surface plasmon resonance (SPR), and artificial intelligence-assisted biosensing further contribute to the development of next-generation AD diagnostics. This review provides a comprehensive analysis of the latest advancements in biosensing technologies for AD, highlighting their mechanisms, advantages, and future perspectives in detecting biomarkers from biological fluids.

1. Introduction

The prevalence of dementia has shown a consistent upward trend over recent decades and is currently the fifth leading cause of death worldwide. Among its various subtypes, Alzheimer’s disease (AD) accounts for approximately 60% of all dementia cases, making it a critical global health concern. This growing prevalence underscores the urgent need for early and accurate diagnostic tools, particularly given the aging population. By 2050, the number of individuals affected by AD is projected to triple, reaching nearly 152 million cases globally—equivalent to 1 in every 85 people [1,2]. Additionally, the economic burden of AD is staggering, with annual treatment costs estimated at $1 trillion USD, a figure expected to double by 2030 [3]. Beyond its financial impact, AD profoundly diminishes the quality of life and presents significant social and healthcare challenges.

Current diagnostic approaches for AD involve a multimodal strategy that combines advanced neuroimaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI) with the analysis of cerebrospinal fluid (CSF) and plasma biomarkers. This integrative approach enables the detection of both structural and molecular changes associated with the disease, thereby improving diagnostic precision. While these methods are crucial for detecting AD, they are often expensive, limited in accessibility, and most effective only during the later stages of the disease. The lack of early diagnostic options remains a considerable obstacle to successful therapy, highlighting the critical importance of timely detection. Recent research suggests that early intervention, particularly with FDA-approved therapies like aducanumab (Aduhelm™) and lecanemab (Leqembi^®), can slow cognitive decline by targeting amyloid-beta (Aβ) plaques in the brain. However, these treatments have notable limitations, including side effects such as infusion-related reactions and amyloid-related imaging abnormalities (ARIA) [4].

Traditional approaches to diagnosing AD typically combine neuroimaging techniques, biomarker analysis, clinical assessments, and neuropsychological evaluations. Although the term “biomarkers” broadly includes physiological, histological, molecular, and radiographic indicators, current efforts increasingly emphasize molecular biomarkers present in biological fluids, which are well-suited for detection through chemical and biosensing methods. Key molecular biomarkers—such as amyloid-beta peptides (Aβ₄₂, Aβ₄₀), total tau (t-tau), phosphorylated tau (p-tau), and neurofilament light chain (NFL)—are essential for identifying AD, especially during its preclinical stages. Incorporating these biomarkers into diagnostic workflows enhances diagnostic precision, enables earlier therapeutic intervention, and supports more effective disease management. Electrochemical (EC) and optical biosensors have emerged as promising alternatives to traditional diagnostic methods due to their high sensitivity, selectivity, rapid detection capabilities, and cost-effectiveness. Advances in materials science, nanotechnology, and biosensing technologies have significantly improved sensor performance, enabling the precise detection of low-abundance AD biomarkers. Since their development in the late 1960s [4], electrochemical sensors have become widely studied for medical diagnostics, while optical biosensors leverage techniques such as surface plasmon resonance (SPR), fluorescence, and colorimetric detection to offer non-invasive, real-time monitoring of biomarkers. The integration of nanomaterials—including graphene, gold nanoparticles, carbon nanotubes, and quantum dots—has further enhanced biosensor sensitivity, stability, and biocompatibility, making them viable for clinical applications [5,6].

Among the most transformative developments in biosensor technology is the emergence of portable point-of-care (POC) biosensors, which enable on-site, real-time analysis with minimal resources. These devices are particularly valuable for diagnosing neurodegenerative diseases like AD, facilitating early detection, continuous monitoring, and personalized patient care. Given their potential for widespread clinical adoption, EL and optical biosensors, especially those enhanced with nanomaterials, represent a critical step toward improving AD diagnostics.

This review outlines recent advances in biosensors for Alzheimer’s disease diagnosis, focusing on electrochemical and optical platforms enhanced by nanomaterials. It discusses technological innovations and challenges that enable minimally invasive, highly sensitive, point-of-care detection of AD biomarkers. While key reviews have emphasized the clinical importance of molecular biomarkers for diagnosis and prognosis [7,8,9] our update broadens the scope by highlighting biosensing technologies that translate these biomarkers into improved, accessible diagnostic strategies.

1.1. Pathophysiology and Progression of Alzheimer’s Disease

AD is a progressive neurodegenerative disorder characterized by gradual cognitive decline and irreversible neuronal damage. Clinically, AD progresses through three main stages: preclinical AD, mild cognitive impairment (MCI), and Alzheimer’s dementia. The preclinical stage, which may last for decades, is marked by early pathological changes without noticeable symptoms. As the disease advances to MCI and dementia, patients exhibit memory loss, impaired judgment, language difficulties, and eventually a complete loss of functional independence [10]. At the molecular level, two hallmark pathologies define AD: the accumulation of amyloid-beta (Aβ) plaques and the formation of neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau protein. Aβ peptides, particularly Aβ₄₀ and Aβ₄₂, are derived from the amyloid precursor protein (APP) via β- and γ-secretase cleavage. Aβ₄₂ and Aβ₄₃ are more prone to aggregation and are considered more neurotoxic due to their role in synaptic dysfunction and inflammation [11,12,13]. Abnormal tau phosphorylation, primarily affecting tau181 and tau217 isoforms, leads to microtubule destabilization and intracellular tangle formation, which disrupts neuronal communication and function. These processes contribute synergistically to disease progression and symptom manifestation.

Clinically relevant biomarkers include Aβ₄₂, Aβ₄₀, total tau (t-tau), phosphorylated tau (p-tau), and neurofilament light chain (NFL). In 6, Aβ₄₂ levels drop below 500 pg/mL, and the Aβ₄₂/Aβ₄₀ ratio below 0.1 is indicative of increased AD risk. In plasma, Aβ₄₂ ranges from 10 to 50 pg/mL, with reductions correlating with disease progression [11]. Tau biomarkers are also crucial: CSF t-tau levels exceed 400 pg/mL in AD patients, while p-tau181 typically exceeds 60 pg/mL, distinguishing AD from other neurodegenerative diseases. Plasma tau levels, though lower (1–10 pg/mL), are emerging as promising non-invasive indicators. Imaging techniques such as MRI and PET play complementary roles in structural and functional assessment but are limited by cost, accessibility, and invasiveness. Consequently, growing research focuses on biosensor-based platforms that enable sensitive, real-time detection of Aβ and tau in biofluids. These technologies, particularly electrochemical and optical biosensors, offer scalable, point-of-care diagnostic alternatives that support earlier intervention and improved patient outcomes. Figure 1 illustrates the integrated approach to AD diagnosis, combining biomarkers, biosensors, and imaging techniques.

Table 1. Comparison of Electrochemical Biosensors for Alzheimer’s Disease Biomarkers.

Biomarker	Sensor Type	Transducer/Material	Detection Limit	Linear Range	Sample Type	Reference
Aβ1–42	Label-free immunosensor	Graphene/Pyr-NHS/SPE	2.398 pM	11 pM–55 nM	Human/mice plasma	[14]
Aβ1–42	Molecularly imprinted polymer	d-Ti3C2Tx MXene/MWCNTs	0.3 fg/mL	1–100 fg/mL	Human serum	[15]
Aβ1–42	Electrochemical peptide sensor	Microporous gold nanostructure (MGN-Au)	0.2 pg/mL	3–7000 pg/mL	Artificial CSF/serum	[16]
Aβ1–42	Impedimetric immunosensor	SnO2 nanofibers	0.638 fg/mL	1 fg/mL–1 ng/mL	Human plasma	[17]
Aβ oligomers (AβO)	Aptasensor	Ferrocene-encapsulated Zn ZIF-8	0.23 pM	0.3472–694.44 pM	Artificial CSF	[18]
AβO	Aptasensor	AuPt alloy nanoparticles	0.16 pg/mL	0.5–10,000 pg/mL	Human serum	[19]
Tau-381	Aptamer-antibody sandwich	Cysteamine-stabilized AuNPs	0.42 pM	0.5–100 pM	Human serum	[20]
Multiple biomarkers	Multiplexed immunosensor	Vertical graphene/carbon cloth (Au-VG/CC)	3.5 pM (Aβ)	10–2200 pM	Human serum	[21]

SPE: Screen-Printed Electrode; Pyr-NHS: Pyridine-N-hydroxysuccinimide; MWCNTs: Multi-Walled Carbon Nanotubes; d-Ti₃C₂T_x Mxene: Delaminated Titanium Carbide Mxene; MGN-Au Microporous: Gold Nanostructure; CSF: Cerebrospinal Fluid; SnO₂: Tin(IV) Oxide; GCE: Glassy Carbon Electrode; AuNPs: Gold Nanoparticles; ZIF-8: Zeolitic Imidazolate Framework-8; rGO: Reduced Graphene Oxide; 11-MUA:11-Mercaptoundecanoic Acid; PBS: Phosphate-Buffered Saline; AuPt: Gold-Platinum Alloy; VG/CC: Vertical Graphene on Carbon Cloth; MIP: Molecularly Imprinted Polymer.

summarizes key electrochemical biosensors reported for AD biomarkers, highlighting their detection capabilities and clinical relevance.

1.2. Biosensors

Biosensors are extensively utilized in medical diagnostics because of their ability to convert complex biological interactions into measurable signals. For Alzheimer’s disease, biosensors provide promising alternatives to traditional diagnostic tools by allowing non-invasive, rapid, and cost-effective detection of key biomarkers such as Aβ and tau proteins in biological fluids. Among various transduction strategies, electrochemical (EC) and optical techniques are the most widely implemented due to their high sensitivity, portability, and compatibility with miniaturized and point-of-care formats. Electrochemical biosensors are classified by signal detection mechanisms: amperometric, potentiometric, conductometric, and voltametric. These platforms convert redox reactions, ion concentration changes, or conductivity shifts into electrical outputs. They are especially suitable for detecting AD biomarkers in blood or plasma because of their sensitivity, low sample volume requirements, and ease of integration into compact devices [22]. The incorporation of nanomaterials further boosts sensor performance by enhancing surface binding, signal amplification, and stability. The following sections examine these biosensor platforms, organized by transduction principle and targeted biomarkers. Since AD-related brain damage begins decades before symptoms manifest, early detection is critical for intervention. Current diagnostic methods such as MRI and PET imaging are expensive, time-consuming, and not widely accessible. CSF analysis is invasive and impractical for routine screening. A biosensor capable of detecting AD biomarkers in blood offers a non-invasive, rapid, and cost-effective solution for early diagnosis. By identifying key biomarkers like Aβ₄₀ and Aβ₄₂ in the preclinical or MCI stage, biosensors could facilitate timely interventions to slow disease progression, potentially delaying the onset of severe dementia and improving patient outcomes.

1.2.1. Electrochemical Biosensors for Alzheimer’s Disease Diagnosis

EC sensors detect electrical signals generated during redox reactions, which occur when biological molecules undergo electron transfer processes. These sensors typically consist of a three-electrode system: working (W), reference (R), and counter (C) electrodes. The working electrode is a critical component, directly influencing the sensor’s sensitivity, selectivity, and durability. Various electrode types, such as carbon paper electrodes, interdigitated microelectrodes [23,24,25], screen-printed electrodes (SPE) [26,27,28], and glassy carbon electrodes (GCE) [29], have been developed to enhance the detection of biomarkers, improving the sensitivity and selectivity of EC sensors for AD. However, limitations commonly observed in unmodified working electrodes including relatively high production costs and low analytical sensitivity can be mitigated by applying specialized functional materials as additional layers on the electrode surface. These modifications significantly enhance the detection of amyloid-beta (Aβ) biomarkers at low concentrations in biological fluids such as CSF, serum, saliva, and plasma. Studies have demonstrated that EC detectors can detect Aβ at levels as low as picograms (pg) or femtograms (fg) per milliliter [14,15,27,30].

Innovative EC biosensors for AD biomarkers have been developed using advanced materials. For instance, a label-free EC immunosensor employing highly conductive graphene and electrochemically reduced graphene oxide (GO) has been designed for Aβ_1–42 detection. Functionalization with Pyr-NHS immobilizes the antibody H31L21, achieving a detection limit of 2.398 pM and a range of 11 pM to 55 nM [14]. Qin et al. [31] introduced a highly sensitive poly (curcumin-Ni foam)-based sensor capable of detecting Aβ oligomers (AβO) with a wide linear range of 0.001 to 10 nM, offering accurate and consistent results in clinical contexts. Similarly, Ding et al. developed an immunosensor for Aβ₄₂ peptides by modifying GCE with polysulfane-methylene blue and gold nanoparticles. Using a heme molecule covalently bound to Aβ₄₂, this device achieves a detection limit of 25.2 pM and a testing range of 0.056–13.7 nM [32].

Recent advancements also include noninvasive techniques for detecting Aβ in human tears. Lee et al. [33] developed a nanopillar-based immunoelectrochemical (NPA) sensor capable of detecting Aβ in artificial tears at concentrations as low as 0.1 ng/mL, with a sensitivity of 0.14 ng/mL and reproducibility marked by a standard deviation below 10%. Supraja et al. [17] designed an EC biosensor utilizing electrospun tin dioxide (SnO₂) nanofibers as the transducing material, further enhancing performance through electrochemical impedance spectroscopy (EIS). This biosensor demonstrated exceptional sensitivity, detecting Aβ₄₂ at 0.146 fg/mL in spiked buffer samples and 0.638 fg/mL in spiked plasma samples. Furthermore, the platform exhibited remarkable stability, maintaining functionality for up to 126 days.

These advancements in EC biosensors highlight their potential as accurate and effective diagnostic tools for AD, paving the way for early detection and better disease management. The integration of novel materials and innovative designs continues to push the boundaries of biomarker detection, offering promising prospects for future progress in this field.

1.2.2. Voltametric Biosensors

Voltametric techniques are widely utilized in biosensors due to their electrochemical properties, offering several technological advantages over other EC methods. These techniques measure current as a function of the electrode’s potential, providing a superior quantitative determination of ions and molecules compared to alternative approaches [34]. Voltametric methods have also been applied to detect exosomes, as will be discussed in detail below.

Wang et al. [35] recently developed an EC immunosensor incorporating EIS and CV to detect Aβ_1–42. The sensor utilizes conducting polymer (PANI) halloysite nanotubes (HNT) as a labeling material, with Ni/PdH/Py/mHNT preventing agglomeration and increasing the electroactive surface area. This innovative design also includes NH₂-PANI/eHNT as a substrate material, which enhances biomolecule stabilization during incubation, accelerates electron transfer on the electrode surface, and provides an effective platform for sensor development. The immunosensor demonstrated reliable detection of Aβ₄₂ in human blood samples, with a detection limit of 5.53 fg/mL across a range of 50 fg/mL to 100 ng/mL.

Similarly, Qin et al. [18] introduced a novel approach for detecting AβO using a ferrocene-encapsulated Zn zeolitic imidazole framework (ZIF-8). This method employs ferrocene for competitive coordination with AβO, enabling both qualitative and quantitative analysis. Additionally, a label-free colorimetric biosensor was developed to detect AβO through multiple DNA hybridization steps and dual-amplification signal processing. This sensor achieved a linear detection range of 0.3472 to 694.44 pM, with a detection limit of 0.23 pM, demonstrating its potential for AβO detection in artificial and CSF samples.

Cao et al. [36] advanced the field further with a Cu-Al₂O₃-g-C₃N₄-Pd-modified glassy carbon electrode (GCE) sandwich immunosensor for detecting Aβ protein. This nano-immunosensor achieved a limit of detection (LOD) of 3.3 fg/mL and a detection range of 10 fg/mL to 100 ng/mL. It demonstrated excellent selectivity for Aβ, minimal activity loss (8.1%) over one month, and recovery rates between 99% and 103% even in the presence of interfering substances. The sensor effectively identified AβO in both synthetic and authentic CSF samples.

Aptamers, sequence-based structures made of DNA, RNA, or peptide sequences, have emerged as a promising alternative to antibodies in voltametric assays for detecting exosomes. Due to their high affinity for specific targets, aptamers can detect a wide range of molecules, including proteins and ions, at a lower cost and with greater ease of use compared to antibodies. Aptasensors, which utilize aptamers, have proven particularly effective for exosome detection, outperforming antibody-based biosensors [37]. EC biosensors incorporating aptamers and metal–organic frameworks (MOFs) have also been widely employed to detect AβO [38]. For instance, Cu-MOFs and gold nanoparticles (AuNPs) combined with thionine nanocomposites significantly enhance sensor sensitivity. Despite these advancements, challenges persist in detecting low concentrations of AβO in human bodily fluids. Current aptasensors can detect AβO within a linear range of 1 nM to 2 μM, with a LOD of 0.45 nM in artificial CSF samples [39].

SAM-Support-Based Electrochemical Sensor

Self-assembled monolayers (SAMs) play a pivotal role in enhancing the performance of chemical and biosensors, batteries, and electronic devices. In EC sensors, SAMs improve selectivity and sensitivity by modifying electrode surfaces to immobilize enzymes and antibodies. A well-designed SAM significantly boosts sensor efficacy, enabling the detection of AD biomarkers at ultralow limits and demonstrating their potential for developing highly sensitive sensors [21].

Hanna Radecka et al. [40] reported an innovative EC immunosensor capable of selectively and sensitively monitoring Aβ_1–42 fibrils. The sensing platform features a gold surface coated with a SAM of 4,4′-thiobisbenzenethiol (TBBT) and covalent immobilization of AuNPs. The AuNPs were linked to half-antibody fragments of Anti-Amyloid Fibrils antibodies via S-Au covalent bonds. Characterized using CV and EIS, the sensor achieved a LOD of 0.6 pM for Aβ_1–42 fibrils.

Lien et al. [41] developed a highly sensitive label-free impedimetric immunosensor for amyloid beta detection using screen-printed carbon ink electrodes. Surface modifications with AuNPs and protein G further reduced the LOD to 0.57 nM. This sensor is cost-effective, simple to fabricate, and reproducible, with a relative standard deviation (RSD) of 2.5%. Its design also allows for potential adaptation to detect other antigens.

Another innovative EC biosensor for detecting the Aβ_1–42 peptide in human blood specimens employed a SAM-functionalized electrode with an interdigitated chain structure. The biosensor immobilized anti-Aβ antibodies and measured impedance changes during detection using EIS. The study demonstrated a broad detection range (10⁻³–10³ ng/mL) with a low detection value of 100 pg/mL in human serum samples [25].

1.2.3. Impedance Biosensors

Faradic and non-faradic sensors are the two main types of impedance-based biosensors. Faradic biosensors detect redox reactions by measuring electron transfer between a metal electrode and the solution, resulting in impedance changes at the electrode interface. In contrast, non-faradic biosensors operate on capacitive principles, utilizing electrode surfaces covered by an electrical field. These sensors measure small sine wave signals generated by analyte adsorption or desorption at the double-layer capacitance. Unlike faradic systems, non-faradic sensors do not require a redox probe in solution, enabling direct measurements without chemical reactions [42].

Biosensor systems rely on immobilizing diverse biorecognition molecules on the sensor substrate using various techniques. Impedance-based biosensors combine these molecules with cell-based systems to generate impedimetric signals as their output. These devices employ probes that bind to specific receptors, following the lock-and-key principle. The detection process involves two phases: (1) target binding (affinity step), and (2) signal detection after the target attaches to the surface (readout step). Affinity involves biomolecule surface chemistry and biological binding, while readout focuses on signal detection and processing. These two components must work simultaneously but optimizing them independently can impact the biosensor’s overall design.

Impedance-based biosensors can be either labeled or label-free. Labeled biosensors connect an analyte to a secondary ligand on the electrode, whereas label-free biosensors do not require such additional ligands. Among the impedimetric techniques, EIS is the most prominent approach in EC biological detection due to its ability to detect biomarkers without the need for labels [25,41].

Wang et al. [43] developed an EIS immunosensor capable of detecting the conformation of Aβ₄₂. This immunosensor utilized the monoclonal antibody 12F4, which binds to Aβ₄₂ monomers at a single site. By immobilizing 12F4 on the sensor surface, the immunosensor could capture both Aβ₄₂ monomers and oligomers. It distinguished between these forms by measuring resistance changes during re-immobilization of 12F4. The effective binding of the probe to Aβ₄₂ oligomers caused increased impedance values due to additional monomers and expanded binding surfaces. This sensor demonstrated a linear detection range from 10 pg/mL to 100 ng/mL and achieved a LOD of 113 fg/mL.

Chen et al. [44] improved the sensitivity of an EIS biosensor for detecting Aβ_1–42 by optimizing the immobilization process of 4-aminobenzoic acid (4-ABA), resulting in a denser and more uniform 4-ABA layer. This enhancement, along with improvements in antibody immobilization and blocking agents, extended the biosensor’s detection range from 1 fg/mL to 100 pg/mL, with a LOD of 3.84 fg/mL using EIS.

Vitusevich et al. [45] developed two highly sensitive biosensors for detecting the Aβ₄₀ biomarker. The first was an aptamer-functionalized capacitive EIS sensor, and the second was a silicon tunneling layer nanowire (Si TL NW)-based biosensor. Both demonstrated the ability to measure ultra-low quantities of Aβ₄₀ peptides. The field-effect transistor (FET) surface potential exhibited a linear change from 0.1 pg/mL to 10 μg/mL following peptide binding to the aptamer, highlighting the effectiveness of these technologies for detecting Aβ₄₀. Cho et al. [46] designed a capacitive sensor for detecting Aβ_1–40 in human blood samples, a critical biomarker for AD. This sensor utilized a β-cyclodextrin/reduced graphene oxide nanohybrid and functioned without a redox probe. It achieved an exceptionally low detection limit of 0.69 fg/mL, making it ideal for POC diagnostics. The dissociation constant for the binding interaction between anti-Aβ₄₀ and Aβ₄₀ in human blood was calculated at 2.9 × 10⁻⁷ nM, demonstrating a strong binding affinity and suitability for Aβ₄₀ protein detection.

1.2.4. Amperometric Biosensors

Amperometric biosensors measure the electrical current generated by an electrode during a biochemical reaction. These devices often incorporate enzymes such as horseradish peroxidase (HRP) and superoxide dismutase (SOD) due to their catalytic properties, which enhance the sensor’s sensitivity and specificity [47]. Chronoamperometry, a specific amperometric technique, involves measuring the current produced when potential steps are applied over a set period [48].The ability of these biosensors to detect analytes at extremely low concentrations arises from the use of enzymes, which act as biological catalysts and selectively bind to specific substrates [49]. The integration of biological elements into biosensing systems significantly improves their performance, making them suitable for diverse applications.

Recently, Wei et al. [50] developed a sandwich-type EC immunosensor utilizing a Au/rGO sensing platform and a AuCuxO/m-CeO₂ catalytic matrix. The incorporation of AuCuxO, with its unique catalytic activity, significantly enhanced the sensor’s performance. This immunosensor demonstrated the ability to detect amyloid-beta protein within a linear range of 100 fg/mL to 10 ng/mL.

In another advancement, Mayer et al. [51] designed a highly sensitive AβO aptasensor using alternating current voltammetry (ACV) and single-stranded DNA stem-loop probes. The aptasensor achieved an exceptionally low detection range in the femtomolar scale, detecting AβO concentrations from 0.1 pM to 1500 nM. By adjusting the ACV frequency, the detection range could be modified. Durability tests conducted over two weeks revealed that the aptasensor retained 80% of its original signal, indicating good stability.

Additionally, Wei et al. [30] developed a bifunctional, label-free immunosensor for detecting amyloid-beta protein using graphene oxide-supported Co₉S₈ polysulfide nanoparticles coated with Pd. These nanocomposites exhibited remarkable electrocatalytic activity, serving as both a matrix and a signal indicator in the immunosensor. The device demonstrated a broad linear detection range of 0.1 pg/mL to 50 ng/mL and an impressive detection limit of 41.4 fg/mL.

1.2.5. Potentiometric Biosensors

Molecularly Imprinted Polymer-Based Sensors

Potentiometric biosensors incorporating molecularly imprinted polymers (MIPs) offer high selectivity by mimicking natural molecular recognition, enabling precise detection of target analytes. These MIP-based sensors have potential applications in biomarker detection and disease diagnosis, offering enhanced sensitivity and stability. The fabrication of MIPs involves forming a highly crosslinked polymer matrix by combining a molecule template with monomers and a cross-linker. This process creates binding sites within the polymer that are complementary in size, shape, and functional groups to the template molecule, resulting in a material with specialized recognition capabilities [52]. While MIPs generally exhibit lower binding affinity and specificity than antibodies or aptamers, their cost-effectiveness and stability make them promising candidates for selective binding [53].

Significant advancements have been made in designing EC biosensors for detecting Aβ₄₂ using MIPs [15,54,55,56,57]. One notable development is a molecularly imprinted biosensor electrode fabricated using a composite of d-Ti₃C₂T_x MXene and multi-walled carbon nanotubes (MWCNTs). This design enhanced the EC catalytic performance for Aβ₄₂ detection. The resulting biosensor exhibited a linear detection range of 1–100 fg/mL with a LOD of 0.3 fg/mL, marking the first successful MIP biosensor for EC detection of Aβ₄₂ protein [15].

Another recent innovation is a highly sensitive MIP sensor developed to detect Aβ₄₂ using the protein as a template. This sensor employs a molecular imprint based on a poly-o-phenylenediamine-hydroquinone polymer. It demonstrated the ability to detect Aβ₄₂ in artificial cerebrospinal fluid (aCSF) and commercial fetal bovine serum (cFBS) with a detection limit of 0.018 ng/mL and a linear detection range of 0.12–10 μg/mL [58].

1.2.6. Immunosensor

Immunosensors are biosensors designed based on the specific recognition of antigens and antibodies [40].These sensors offer high specificity due to the antigen–antibody interaction, which minimizes nonspecific interference. Various types of transducers, including electrochemical, magnetic, thermometric, and optical, are employed to convert immunological responses into valid analytical signals. Additionally, advanced transducer technologies such as electrochemical, microfluidic [59], electrochemiluminescence (ECL) [38,60,61,62,63,64,65,66,67,68], and surface plasmon resonance (SPR) [69] have been used to construct sensitive immunosensors for detecting AD biomarkers. These electronic probes are distinguished by their exceptional sensitivity, user-friendly operation, cost-effectiveness, miniaturization capabilities, and potential for automation. The effectiveness of an EC immunosensor relies on the strong affinity between the antigen–antibody complex [70].

One example of an immunosensor is a label-free device designed to detect cis P-tau. This sensor was fabricated by immobilizing complementary antibodies on a gold (Au) electrode after appropriate pre-treatment. It was specifically developed to selectively detect cis P-tau while minimizing interference from non-specific targets. This immunosensor demonstrated a wide detection range for cis P-tau concentrations (0–300 pM), with detection limits of 0.02 pM and 0.05 pM. It showed practical applicability by effectively detecting cis P-tau in cerebrospinal fluid and blood serum samples from patients at various disease stages [71].

A recent advancement by Qin et al. [72] introduced a label- and antibody-free electrochemical biosensor for the specific detection of AβO. This innovative biosensor incorporated an electrically conductive poly (pyrrole-2-carboxylic acid) inking agent and a cellular prion protein (PrPC) receptor, enabling precise and accurate AβO detection. The sensor exhibited a remarkably low detection limit of 10⁻⁴ pM.

Chen et al. [73] designed an affordable, disposable, and user-friendly biosensor for detecting Aβ in tear samples, with a detection range of 1–100 pg/mL. Remarkably, the concentration of Aβ in tears is approximately 10 times higher than in blood, enhancing the diagnostic potential of this approach.A summary of this and other electrochemical biosensors designed for Alzheimer’s biomarkers is provided in

Table 2. List of reported electrochemical biosensors with their performance to detect AD biomarkers.

Biomarkers	Strategy	Transducer	Samples	LOD	Linearity	References
Aβ1–42	Vertical graphene nanosheets (VGS) functionalized with curcumin (CUR) honeycomb-derived vertical graphene nanosheets (HCVS)	CV/EIS	Buffer	0.1 μg/mL	0.1–10 μg/mL	[74]
Aβ1–42	EDC-NHS/6-mercaptohexanoic acid SAM, ICE electrode	EIS	PBS, serum	100 pg/mL	10−3–103 ng/mL	[25]
Aβ1–42	pDAN-modified SPGE with the anti-Aβ antibody	SWV/DPV	Plasma	1.4 pg/mL	1–103 pg/mL	[27]
Aβ1–42	Ab/AuNPs/PTH-MB[s]/Au/ GCE	CV	PBS Human serum Saliva	17.3 pM 25.2 pM 23.8 pM	0.508–13.7 nM 0.056–13.7 nM 0.056–41.2 nM	[32]
Aβ1–42	Electrochemical immunosensor, Halloysite nanotubes/polypyrrole	EIS	Human serum	5.53 fg/mL	50 fg mL−1–100 ng mL−1	[35]
Aβ	Electrochemical immunosensor, AuCuxO/m-CeO2	i–t	Artificial cerebrospinal fluid	0.036 pg/mL	0.0001–10 ng/mL	[50]
AβO	Electrochemical biosensor, CP4-Au	SWV	Buffer	0.6 nM	0.005–5 μM	[75]
AβO	Biosensor, Peptide probe-Au	EIS	Serum	<1 pg/mL	3.3~3300 pg/mL	[76]
AβO	Electrochemical biosensor, Ppy-2-COOH/Au	EIS	Rat CSF	10−4 pM	10−7–10 nM	[72]
AβO	Electrochemical sensor, Au dendrite-Ppy-3-COOH/Au	EIS	Mice brain	1 aM	10−9–10 nM	[77]
AβO	Electrochemical peptide sensor, AuNPs-E-PTAA AuNPs-E-Ppy-2-COOHAuNPs-E-Ppy-3-COOH	EIS	Rat CSF	10−6 nM 10−8 nM 10−9 nM	10−6–103 nM 10−9–10 nM 10−9–103 nM	[78]
AβO	Electrochemical aptasensor, bipedal DNA walker	EIS, DPV	Human serum	46 fM	0.1 pM–1 nM	[79]
AβO	GO/AuNPs-PrPC biosensor	EIS	Artificial CSF/blood	0.1 pM	0.1 pM–10 nM	[80]
AβO	CuNPs and AuNPs-modified vertical graphene/carbon cloth (Au-VG/CC)	DPV	Serum	3.5 pM	10–2200 pM	[81]
Multiple Biomarkers
miRNA-101; ApoE4; Tau; Aβ	Electrochemical sensor, gold nanodendrites	CV	Human serum	91.4 pM; 5.91 × 10−11; 7.14 × 10−11; 8.6 × 10−12 mg/mL	10−10–10−7 mg/mL	[82]
Aβ42, T-tau	Aluminum oxide (AAO) nanopore chip	Optical sensor	CSF	7.8 pg/mL 15.6 pg/mL	31.25–250 pg/mL (Aβ42) 125–2000 pg/mL (T-tau)	[83]
Ab1–40 Ab1–42	HRP-Carbon fiber, Electrochemical	SWV	Rat CSF	20.0 nM	20–50 nM 20–140 nM	[84]
Aβ1–40 Aβ1–42	NH2-functionalized rGO/SPE	CV/DPV	Plasma	Aβ40: 9.51 fM Aβ42: 8.65 fM	Aβ40: 10 fM–10 pM Aβ42: 10 fM–50 pM	[85]
Aβ40, Aβ42, t-tau441	Interdigitated microelectrode biosensor	DEP	Human plasma	85 fM, 133.64 fM, 14.27 fM	10−1–10−3 pg/mL	[13]
Aβ42, tau441, p-tau181	Electrochemical, fluorimeter	Fluorescence labeling	Saliva, urine	23 fM 14 fM 34 fM	0–2500 fM	[86]
t-tau, p-tau181, Aβ42, and Aβ40	Densed aligned CNT bio sensor	Resistance	Human plasma	2.13, 2.20, 2.4, 2.72 fM	101–104 fM	[87]
Aβ40, Aβ42, T-tau, and P-tau181	Electrochemical micro-workstation	DPV and chronoamperometry	Humam serum	0.125, 0.089 pg/mL, 0.142 pg/mL, 0.176 pg/mL	0.1–1000 pg/mL	[88]
Aβ40, Aβ42, T-tau, P-tau181	Electrochemical sensor, superwettable microdroplet array	DPV	Humam serum	0.064, 0.012, 0.039, 0.041 pg/mL	0.1–1000 pg/mL	[89]
Aβ40, Aβ42, T-tau, P-tau181	Electrochemical sensor, vertical graphene nano Au	DPV	Humam serum	0.072, 0.089, 0.071, 0.051 pg/mL	10 pg/mL–100 ng/mL	[28]

AuCuxO/m-CeO₂—Gold copper complex with cerium dioxide; BSA—Bovine serum albumin; CNT—Carbon nanotubes; CP4—Capture probe; CV/EIS—Cyclic voltammetry/Electrochemical Impedance Spectroscopy; DPV—Differential pulse voltammetry; EDC-NHS—1-ethyl-3-(-3-dimethylaminopropyl) carbodiimide-N-hydroxysuccinimide; HCR—Hybridization chain reaction; ICE—Interdigitated chain-shaped electrode; LSV—Linear sweep voltammetry; MGN-Au—Microporous gold nanostructure-gold disk; pDAN-SPGE—Polymerised 1,5-diaminonaphthalene-screen printed graphene electrode; Ppy-2-COOH—Pyrrole-2-carboxylic acid; Ppy-3-COOH—Pyrrole-3-carboxylic acid; PrPC—Thiolated cellular prion protein; PTAA—Poly(thiophene-3-acetic acid); PTH-MB—Polythionine-methylene blue; rGO/Pyr-NHS/SPE—Reduced Graphene oxide/1-pyrenebutyric acid N-hydroxysuccinimide ester/Screen Printed electrode; SAM—Self-assembled monolayer; SnO₂—Tin oxide; SWV—Square Wave Voltammetry.

.

Field-Effect Transistors (FETs)

Semiconductor-based field-effect transistors (FETs) have garnered significant attention for their high sensitivity in detecting specific proteins, offering the potential to replace costly hospital devices like Nuclear Magnetic Resonance for biosensing applications. Salehirozveh et al. [90] developed a cost-effective aptasensor using a reduced graphene oxide (rGO) FET method, demonstrating high sensitivity in detecting the Aβ₄₂ protein. The sensor’s surface, consisting of Si/SiO₂, was prepared and coated with rGO, followed by immobilization of an RNA aptamer specific to Aβ₄₂. Electrical measurements indicated a linear response ranging from 1 pg/mL to 1 ng/mL in phosphate-buffered saline (PBS), monitored through gate voltage (VTG) shifts. This aptasensor exhibited strong selectivity and suitability for serum sample measurements, showing promise for Aβ₄₂ detection.

Yoon et al. [91] introduced a highly sensitive and multiplexed method for detecting key AD biomarkers, including Aβ_1–42 and total tau (t-tau), in biofluids using an rGO-FET platform. This approach provided an extensive logarithmic linear detection range from 10⁻¹ to 10⁵ ng/mL and achieved a remarkable LOD at the femtomolar level. The rGO-FET sensor successfully detected these biomarkers in human plasma, aCSF, and PBS, making it an excellent candidate for AD diagnostics.

Chen et al. [92] proposed a novel technique utilizing aptamers as bio-amplifiers for ultra-sensitive detection of Aβ_1–42 in human serum samples. Their method employed mSAM-SiNWFET (mixed self-assembled monolayer silicon nanowire FET) immunosensors, which prevent biofouling and use mouse antibodies as bio-receptors. The SiNWFET acts as a transducer, enabling detection at a remarkable LOD of 100 fg/mL—outperforming other advanced sensing technologies for Aβ_1–42 detection. This study demonstrated a significant linear correlation between the aptamer-amplified signal and Aβ_1–42 concentrations, even under high ionic-strength conditions such as 150 mM bis-tris propane (BTP) and human blood. This innovative approach holds great promise for precise and cost-effective AD biomarker detection.

Electrochemiluminescence Immunosensor

A new electrochemiluminescence (ECL) immunosensor has been proposed for detecting Aβ_1–42. Tin disulfide nanoflowers (SnS₂ NFs) served as the substrate material, with palladium nanoparticles (Pd NPs) in situ reduced on SnS₂ NFs to form SnS₂-Pd. When combined with high concentrations of luminol, the SnS₂-Pd substrate material produced a robust ECL signal. Copper-doped mesoporous tungsten trioxide (Cu:WO₃) nanoparticles were introduced to suppress the ECL emission of luminol/SnS₂-Pd through resonance energy transfer. This quench-type ECL immunosensor demonstrated an impressive detection range of 0.1 pg/mL to 50 ng/mL, with a lower detection limit of 5.4 fg/mL in CSF samples [93].

Qin et al. [63] developed a dual-wavelength ratiometric (DWR) ECL sensor for highly sensitive detection of Aβ_1–42. The sensor utilizes Ru/TiO₂/Au nanomaterials as energy receivers and gold nanoparticle-modified graphitic carbon nitride nanosheets (AuNPs/g-C₃N₄NSs) as energy donors. This combination produces stable ECL signals with an emission center at 460 nm, which overlaps with the UV-vis absorption spectra of Ru/TiO₂/Au. This resonance promotes the emission of Ru(bpy)₃²⁺ at 620 nm through ECL resonance energy transfer (RET). The AuNPs functionalized on g-C₃N₄NSs provide an excellent substrate for immobilizing primary antibodies (Ab1) and enhancing electron transfer at the electrode surface. The ECL signal is further amplified by TiO₂ nanoparticles loaded with multiple Ru(bpy)₃²⁺ molecules and AuNPs conjugated to secondary antibodies (Ab2). The sensor exhibited a linear detection range for Aβ₄₂ between 1 × 10⁻⁵ and 200 ng/mL, with a limit of detection of 2.6 fg/mL.

A novel ECL analytical platform based on the ECL-RET mechanism has also been developed for the efficient detection of Aβ peptides. The platform involves depositing graphite-phase carbon nitride nanosheets on a glassy carbon electrode (GCE) and coating it with electrolyzed polyaniline (PANI). A peptide motif essential for preventing fouling and identifying full-length Aβ peptides with suppressive effects on Aβ aggregation and dissociation was immobilized onto the PANI-modified electrode. The interactions between the Aβ-specific peptide and Aβ aptamer-functionalized CdS quantum dots (CdS QDs) attached to the electrode enabled highly sensitive ECL detection. This biosensor achieved a detection limit of 16.1 fM and could detect Aβ concentrations ranging from 0.1 pM to 100 nM [68].

1.2.7. Optical Biosnsors

Optical biosensors have emerged as powerful tools for detecting and monitoring Alzheimer’s disease, offering exceptional specificity, sensitivity, and real-time analysis capabilities. These sensors provide a versatile and precise platform for label-free detection of chemical and biological compounds [94,95]. They operate by detecting changes in optical properties—such as absorbance, fluorescence, or surface plasmon resonance (SPR)—that occur when target molecules interact with the sensor surface. The ability to monitor molecular interactions in real time makes optical biosensors invaluable for identifying key biomarkers, facilitating early diagnosis, and enabling continuous assessment of disease progression.

Classification of Optical Biosensors

Fluorescence, SPR, and surface-enhanced Raman spectroscopy (SERS) are widely utilized techniques in optical biosensors for detecting bio-analytes. These sensors typically integrate a biorecognition element with an optical transducer, which generates an optical signal upon the interaction between the analyte and the biorecognition component. This interaction enables both qualitative and quantitative evaluation of the target analyte. While tau protein detection is achievable using various optical biosensors, fluorescence-based sensors have been particularly effective in identifying other biological analytes [96].

Table 3. List of reported optical sensors with their performance to detect AD biomarkers.

Technique	Target	Medium	Detection Strategy	Antibody	LOD	Reference
SPR	Tau 381	Buffer, Plasma	Sandwich	mAb	10 fM	[98]
	Ab1–40 Ab1–42	CSF	Sandwich	mAb	20.0 pM	[99]
	Ab1–42	Buffer	Direct	mAb	0.2 mM	[100]
	ADDLs	Buffer	Sandwich	mAb	280 nM	[101]
	ADDLs	Buffer	Direct	mAb	n.d.	[102]
LSPR	ADDLs	Human brain Cells and CSF	Sandwich	mAb	10.0 pM	[103]
	Tau	Buffer	Direct	mAb, protein G oriented	0.2 pM	[104]

summarizes recent optical biosensors and their analytical performance for the detection of AD biomarkers. Early development of fluorescent probes, however, faced significant challenges, including poor water solubility and limited stability, which hindered their effectiveness in biological environments. Recent advancements have overcome these limitations, resulting in more robust and reliable fluorescent probes. These innovations have expanded the applications of fluorescence-based biosensors, enhancing their reliability and suitability for diverse biosensing needs [97].

Fluorescence-Based Biosensors

Fluorescent biosensors play a vital role in quantifying, localizing, and monitoring the activity of biomolecules. These sensors function by capturing electromagnetic energy and converting it into a fluorescent signal. Typically, they consist of three primary components: an excitation light source, fluorophores that tag the target molecules, and a detector to measure fluorescence intensity [95,105,106]. Fluorophore compounds include quantum dots [107,108,109,110,111] and proteins, while excitation signals can be detected using advanced techniques such as fluorescence lifetime imaging, Förster resonance energy transfer (FRET) [112,113], fluorescence correlation spectroscopy (FCS) [114,115], and fluorescence intensity changes (FT).

Despite the advantages of optical fluorescence in diagnostics, including portability and effectiveness, its use as a point-of-care diagnostic approach has certain drawbacks. These include high costs, the need for specialized expertise, and limitations in measuring complex biological samples. In response, significant advancements have focused on developing fluorescent technologies that are compact, portable, multiplexed, and cost-effective. These innovations include smartphone-integrated platforms and fluorescent lateral flow assays, designed to address these challenges with improved efficiency and precision [116,117].

Jiang et al. [118] designed a fluorescent biosensor capable of detecting AβO in aCSF with exceptional sensitivity. The biosensor incorporated Fe₃O₄ nanoparticles (NPs) and BaYF₅:Yb, Er upconversion nanoparticles (UCNPs) as labels, combined with an AβO aptamer and its complementary oligonucleotide. It demonstrated a linear working range of 0.2–15 nM and a LOD of 36 pM. The synergy between UCNPs and Fe₃O₄ NPs enhanced the biosensor’s picomolar sensitivity, particularly under artificial physiological conditions. However, further studies are needed to evaluate its effectiveness in detecting AβO in biological specimens, such as CSF and blood plasma.

One challenge in using fluorescent probes to detect Aβ in biological samples arises from the low biomarker concentrations and the complex composition of biological materials. Small fluorescent probing molecules are often less effective in undiluted serum compared to buffer solutions or diluted serum [119]. As a result, the development of fluorescent probes based on small molecules with strong anti-interference capabilities has become a critical area of research. Recently, a zinc-based bioinspired approach was developed to quantify serum Aβ with a LOD of 3.22 nM using bi-ligand metal–organic frameworks (MOFs). The hydrophobic nature and size-exclusion properties of this probe allow for rapid and selective enrichment of Aβ, demonstrating its potential for precise and efficient detection [117].

SPR Biosensors

Surface plasmon resonance (SPR)-based biosensors are label-free, highly sensitive tools designed to detect and quantify biomolecular interactions in real time. These sensors operate by measuring shifts in the resonance angle, which occur when biomolecules interact with immobilized molecules on a metallic interface. To achieve optimal performance, the optical, electrical, and structural components of these biosensors must be appropriately configured, alongside the kinetic and chemical characteristics of the target biomolecules. SPR-based biosensors have been widely studied for detecting Aβ₄₂, a critical biomarker for Alzheimer’s disease [120].

An ingenious localized surface plasmon resonance (LSPR)-based biosensor incorporating AuNPs and antibodies has demonstrated remarkable sensitivity in detecting Aβ_1–40, Aβ_1–42, and tau proteins in blood under physiological conditions. This biosensor achieved detection limits of 34.9, 26, and 23.6 fM, respectively, corresponding to unique Rayleigh scattering peak shifts of approximately 1 nm, 2.23 nm, and 3.12 nm for each biomarker in spiked blood samples [121].Ly et al. further advanced this field by fabricating an LSPR sensor on thin films doped with AuNPs and polyethylene terephthalate, enabling Aβ_1–42 detection at an impressive limit of 1 pg/mL in CSF. This highlights its potential for early and precise AD diagnosis [122].

Recently, Cho et al. [123] designed a label-free, highly sensitive biosensor for real-time detection of Aβ_1–42 concentrations, which could revolutionize early-stage AD diagnosis and monitoring. This dual prism-assisted solution-immersed silicon (DP-SIS) biosensor uses a dual prism system made from SF10 and BK7 glass to effectively separate noise signals. The DP-SIS biosensor achieved a detection limit as low as 12.0 fg/mL in blood and a broad detection range from 0.1 pg/mL to 10 ng/mL. This innovation underscores the potential of SPR-based biosensors to enhance diagnostic accuracy and improve the early detection and management of AD.

Colorimetric Biosensors

Colorimetric biosensors detect specific analytes through visible color changes, offering a simple yet effective method for point-of-care diagnostics. By integrating a glassy carbon electrode with polysulfane-methylene blue and AuNPs, these sensors provide enhanced sensitivity. Their portability and the lack of a need for complex instrumentation make them ideal for delivering rapid and reliable results in diverse diagnostic settings [123,124].

Nanozymes, with their stability and tunable catalytic activity, show great promise in developing Aβ biosensors. A novel colorimetric method employing porous ZnO-Co₃O₄ nanocomposites (NCs) with peroxidase-like activity has been developed to monitor apolipoprotein and test amyloid formation. This assay achieved a detection value of 3.53 nM and has been used to quantify Aβ monomer levels in rat CSF [125]. Achieving high selectivity and sensitivity in colorimetric strategies for antibody detection requires precise control of AuNP aggregation. Enhancing selective antibody-AuNP binding is essential to maintain stable antibody-AuNP complexes. A common approach involves conjugating AuNPs with Aβ₄₂ antibodies at the C- and N-termini, enabling precise binding of Aβ₄₂’s C- and N-terminal regions and achieving a minimum detection value of 2.3 nM [126].

Colorimetric amyloid sensors remain in the early stages of development, with most proof-of-concept devices designed to evaluate pure Aβ solutions or mixtures of Aβ with other proteins, such as BSA, IgG, or thrombin. However, variables such as pH, temperature, and salt concentrations significantly impact colorimetric signals. Consequently, there is an urgent need for revolutionary colorimetric devices capable of delivering optical responses within a well-defined color spectrum for accurate detection of Aβ [127].

SERS Biosensors

Surface-enhanced Raman spectroscopy (SERS) is a powerful biosensing technology that amplifies Raman scattering signals of molecules adhered to transducer surfaces. This enhancement is achieved using surface-sensitive techniques where molecular vibrations are amplified as they approach metal surfaces or nanoparticles coated on those surfaces. The significant enhancement of SERS, compared to conventional Raman scattering, can be attributed to chemical or electromagnetic processes. A critical component of label-based SERS effectiveness is the adhesion of the labels to the target analyte. In contrast, label-free SERS relies directly on the interaction between the analyte and the substrate material. Raman vibrational interactions of the analyte retained on the surface enable the identification of small molecules. However, detecting small concentrations of hydrophobic target analytes that are hydrophilic presents a challenge for common SERS receptors like silver (Ag) and gold (Au) [128,129].

SERS technology has been extensively used in diagnosing chronic diseases, including early detection of Alzheimer’s disease. It enables the identification of ultralow levels of biomarkers, such as tau protein or Aβ peptides, in brain tissue, CSF, blood, or serum samples [130]. Jung’s team developed a highly advanced 3D SERS substrate called CGSS, functionalized with carboxylic acid and covered with a graphitic nanolayer. This substrate was specifically designed to measure secondary structural changes in AD biomarkers, including amyloid β and tau protein, based on their SERS spectra [131].

Song et al. [132] created a SiMoA (Single Molecule Array) digital ELISA method to detect Aβ_1–42 peptides in human plasma, achieving a detection limit of 0.3 ng/mL and a quantification range of 0.824–200 pg/mL. Similarly, Zhang and colleagues [133] developed a SERS detection method using AuNP nanoconjugates and poly-aptamer complexes to detect Aβ_1–42. This technique employed the plasmonic coupling effect to generate SERS signals from AuNP accumulations triggered by antigen-aptamer interactions. The detection limit was 167 pg/mL in CSF, demonstrating its potential for sensitive and reliable AD biomarker detection.

1.2.8. Nanomaterials-Enabled Biosensors

In recent decades, nanomaterials have revolutionized biosensor technology by enabling the development of transducers that exploit the unique properties of nanoscale materials. Due to quantum-size effects, these materials exhibit exceptional mechanical, electronic, thermal, and optical characteristics, making them invaluable for enhancing biosensor design and performance [134]. The integration of nanomaterials into biosensors significantly increases the surface area available for immobilizing biological recognition elements, improves electrical conductivity and catalytic activity, and enhances analyte accessibility [135].

Carbon-based materials, such as carbon nanotubes (CNTs) and graphene, have attracted considerable attention in developing biosensing tools for detecting AD biomarkers [14,80,136]. Functionalized CNTs integrated into microelectronic sensor devices (MEDs) have shown exceptional performance, reliably detecting AD biomarker antigens in PBS, aCSF, and CSF. These devices achieve remarkable detection limits below 100 femtomolar, providing a cost-effective and efficient tool for AD screening [137].

Furthermore, a variety of nanomaterials have been investigated for developing label-free Aβ₄₂ immunosensors. These include metal nanoparticles [138], carbon nanomaterials [136], conducting polymers [139], transition metal sulfides [140], and composite materials.

Table 4. List of reported various nanomaterials with their performance to detect AD biomarkers.

Nanomaterials	Technique	Detection Target	Linear Range	LOD	Sample Type	References
IrO2 NPs	Electrocatalytic WOR	APOE	100–1000 ng/mL	68 ng/mL	Human plasma	[141]
Au NPs	Chronoamperometry	Tau	50 and 750 ng/mL	63 ng/mL	Human serum	[142]
Au/Pt/Au NPs	Chronoamperometry	p53	50 and 1000 nM	66 nM	Human plasma	[143]
Au nanostructure	DPV	Aβ	0.002–1.28 ng/ mL	0.4 pg/mL	Human serum and artificial cerebrospinal fluid	[144]
Ag NPs	LSV	AβO	1 pM–10 nM	430 fM	AD patients and healthy person serum	[145]
CNTs	△i/i	Aβ40 and Aβ42	100–104 fM	55 aM and 45 aM	Human serum	[146]
MoS2	current-voltage (I-V)	TNF-a	10 Fm–1 nM	10 fM	Human serum	[147]
AuNPs	Colorimetric	Fetuin B	0.1–500 nmol/L	0.24 nmol/L	Blood	[148]
		Clusterin	0.1–250 nmol/L	0.12 nmol/L
Ag NTs	Colorimetric	Aβ40 and Aβ42	10–300 nM	20 nM	Rat CSF	[149]
CuCo-CeO2-Pd	Colorimetric DPV	Aβ	1.0 pM–100 nM	0.05 pM	CSF and Serum	[150]
Au NPs	Colorimetric	Aβ1–40	0 nM–10 nM	0.22 nM	Human serum	[151]
ZnO-Co3O4 nanocages	Colorimetric	Aβ	5–150 nM	3.5 nM	Rat CSF	[125]
Au NPs	Colorimetric SERs	p-tau396,404	100 ng/mL–1.5 pg/mL	1.5 pg/mL	Plasma and whole Blood	[152]
Au NRs	LSPR	tau	101 to 108 fM	103 fM	CSF	[153]
Au NPs	LSPR	Aβ	0.5–20 μM	-	Buffer	[154]
Au NPs	SERS	Aβ1–42 Tau protein	1 × 10–1 to 1 × 104 nM	4.2 × 10–4 pM and 3.7 × 10–2 nM	Artificial CSF	[133]
Au NPs/GO	SERS	Aβ1–42 monomer and fibrils	0.1–1 ng/mL	0.0232 ng/mL and 0.0192 ng/mL	CSF, blood	[155]
Ag NGSs	SERs	Aβ40 and Aβ42	0–1000 pg/mL	0.25 pg/mL 0.32 pg/mL	Human serum	[128]
Pt/Au TNRs	SERs	Aβ42 monomer and fibrils	0.1 to 1000 × 10−12 m	0.045 × 1012 M and 4 × 10−15 M	Human CSF	[156]
MoSe2	SERs	BD-tau	0.05–200.00 pM	0.028 pM	Mouse plasma samples	[157]
Au NPs	Multiplex	Aβ Tau	0.01–100 pg/mL 0.01–1000 pg/mL	2.2 fM 0.2 fM	AD patients and NCs plasma	[158]

AgNPs—Silver nanoparticles; CuCo-CeO₂-Pd—Copper cobalt with cerium dioxide with palladium; IrO₂ NPs—Iridium oxide nanoparticles; LSPR—Localized Surface Plasmon Resonance; MoS₂—Molybdenum disulfide; MoSe₂—Molybdenum diselenide; SERS—Surface-enhanced Raman scattering; TNRs—Triangular Nanorings; WOR—Water oxidation reaction; ZnO-Co₃O₄—Zinc oxide with cobalt oxide.

summarizes representative nanomaterials used in biosensors and their analytical performance in detecting AD biomarkers. These advancements highlight the significant potential of nanomaterial-based biosensors in improving the early diagnosis and ongoing monitoring of AD.

Gold Nanostructures-Enabled Biosensing

Gold nanoparticles (AuNPs) are extensively used in biosensor fabrication due to their exceptional electrochemical properties. Electrodes modified with AuNPs demonstrate significantly enhanced sensitivity compared to unmodified electrodes, making them highly effective for biosensing applications [19,159,160]. In AD research, the impact of gold nanoparticles is profound and multifaceted. Their exceptional physical and chemical properties offer significant promise for advancing diagnostic methods and biochemical sensing technologies in AD [161,162].

One of the most notable attributes of gold nanostructures is their ease of functionalization, as well as their ability to exhibit distinct colors based on shape, size, and aggregation state. These features make AuNPs particularly suited for the development of colorimetric biosensors [163]. Both gold nanoparticles and gold nanorods (AuNRs) have been successfully employed in immunoassays to accurately measure AβO, Aβ peptides, and Aβ aggregations, key biomarkers for AD.

In addition to AuNPs, other advanced materials, such as lanthanides and graphene nanoparticles, have also been explored for their biosensing capabilities. These materials complement the versatility of gold-based nanostructures, offering further potential for developing highly sensitive and reliable biosensors for AD diagnostics [151,154].

Lanthanide-Based Biosensors

Lanthanide metal–organic coordination polymers (LMOCPs) possess unique optical properties, making them highly valuable in analytical applications. These materials emit light with narrow peaks, exhibit high absorption coefficients, and resist fading, which makes them particularly suitable for designing fluorescent sensors. A newly developed LMOCP fluorescent sensor, Cu-BTC/Tb, has demonstrated the ability to detect Aβ at ultralow levels, with a detection limit of 0.3 nM [164]. However, this sensor relies on a single fluorescence intensity, which can be influenced by environmental factors, potentially leading to false positive signals. To enhance the precision and reliability of Aβ detection, it is imperative to explore methods that mitigate the effects of environmental variables.

Liu and colleagues [165] addressed this challenge by introducing a novel fluorescence probe utilizing a luminescent coordination polymer. This design incorporates Tb³⁺ cations as the metal center, Cu²⁺ ions to quench fluorescence, guanine monophosphate as the bridging linker, and luminol as an additional linker. The probe was specifically designed to detect Aβ levels associated with AD. It operates by measuring changes in the fluorescence intensity of Tb³⁺ and luminol. As Aβ levels increase, the fluorescence intensity of Tb³⁺ also increases, while the fluorescence intensity of luminol remains constant. This dual-intensity system enables the detection of Aβ with a sensitivity of 20 pM by comparing the fluorescence intensities of luminol and Tb³⁺.

In addition to its high sensitivity, this fluorescence probe exhibits excellent specificity, reusability, and stability, making it an ideal platform for detecting AβO. Such innovations underscore the potential of luminescent coordination polymers in advancing diagnostic tools for AD [164].

Graphene-Enabled Biosensing

Graphene, a carbon material arranged in a hexagonal grid, is renowned for its excellent electrical conductivity, with electron transfer occurring primarily at the edges of its basal plane. In contrast, graphite, composed of multiple stacked layers of graphene, exhibits superior stability and enhanced conductivity for both electricity and heat. The unique properties of both graphene and graphite make them ideal materials for constructing various EC devices [166].

Graphene-based materials also facilitate studying the process of Aβ_1–42 fibrilization. For instance, Li et al. [166] employed a reduced graphene oxide (rGO)-modified biosensor to detect structural alterations in Aβ₄₂ by monitoring changes in the oxidation current of Tyr10. The results showed strong alignment with fluorescence detection methods, suggesting that this platform could serve as a complementary tool for investigating amyloid aggregation and its implications in AD.

In another study, Sethi et al. [85] functionalized a sensor surface based on rGO using ammonia treatment to attach NH₂ groups, allowing immobilization of antibodies. This enabled the detection of both Aβ₄₀ and Aβ₄₂. The linear detection range for Aβ₄₀ was 10 fM to 10 pM, with a LOD of 9.51 fM. For Aβ₄₂, the linear range was 10 fM to 50 pM, with a LOD of 8.65 fM. The enhanced sensitivity and lower LODs achieved were attributed to the superior conductivity of rGO.

1.2.9. Peptide Biosensors

Biosensors can utilize peptides as biorecognition elements instead of proteins due to their structural similarity and versatility. Artificial peptides can be synthesized using conventional solid-phase synthesis methods to create desired sequences or screen peptide libraries. These peptide-based molecular biosensors have been developed to detect a wide range of analytes, including proteins, antibodies, DNA, and metal ions. Peptides are particularly effective in EC biosensors because they can encapsulate receptor elements or modify electrode surfaces to enhance EC properties. Their adaptability in modern biosensor design is remarkable, owing to their varied architectures, high selectivity, established synthesis methods, ease of modification, chemical variability, and accessibility [167].

Peptides are formed by the covalent bonding of carboxyl and amine groups in synthetic or natural amino acids. They exist in forms ranging from short oligopeptides to long polypeptide chains. Derived from the 20 natural amino acids, peptides share building blocks with proteins, allowing specific sequences to mimic protein target specificity. Due to their high affinity for analytes, peptides are excellent replacements for proteins in biological analyses. Artificially designed peptides can be rapidly produced using molecular biology and chemical techniques through peptide library screening and optimization. Peptides are also biocompatible, bioactive, and non-toxic, with minimal risk of adverse systemic or local responses when interacting with cells or tissues. Compared to proteins, peptides are more stable against mechanical and chemical stress and exhibit greater conformational stability [168].

In one study, Chung et al. [169] developed probe A-1 using the Aβ peptide to monitor metal binding and aggregation. This probe incorporates Aβ_1–21 and dual FRET (Förster Resonance Energy Transfer) donors and acceptors, enabling high sensitivity in detecting trace concentrations of Zn(II). Upon Zn(II) binding, the probe produces an amplified FRET signal; however, when Zn(II)-bound A-1 aggregates, the FRET intensity decreases. Additionally, A-1 can be used to screen chemical libraries for inhibitors that disrupt metal-Aβ interactions. Such inhibitors alter the FRET intensity of Zn(II)-added A-1, providing a platform for identifying potential therapeutic compounds.

Negahdary and Heli recently designed a highly accurate EC peptide-based nanobiosensor. This device employs a peptide sequence attached to a Au nanostructured microporous surface via a cysteine residue’s thiol group (-SH). The sensor demonstrates a high affinity for Aβ_1–42 and uses K₃[Fe(CN)₆]/K₄[Fe(CN)₆] as a redox couple to quantify Aβ_1–42 concentrations in clinical samples. The detection limit of this biosensor is approximately 0.2 pg/mL, highlighting its remarkable sensitivity [16].

Liu et al. [75] developed another innovative EC biosensor employing in situ peptide self-assembly signal amplification to detect AβO in artificial human serum samples. This method achieved a detection limit of 0.6 nM, representing an 8-fold improvement over unamplified strategies. Such advancements demonstrate the potential of peptide-based biosensors to enhance the sensitivity and specificity of diagnostic tools for AD.

1.2.10. Tau Protein

Tau proteins, such as p-tau-181, t-tau, and Aβ_40/42, are present in both CSF and blood specimens. Additionally, CSF contains neurotransmitters, including dopamine, acetylcholine, serotonin, glutamate, and norepinephrine, along with protein markers such as fetuin B, clusterin, prostate-specific antigen, pancreatic prohormone, and α1-antichymotrypsin. AD can be accurately identified by analyzing genetic markers, such as mutations in chromosomes 1, 14, and 21, as well as the presence of neurofilament light chain in the blood. Among these biomarkers, Aβ peptides, t-tau, and p-tau are the most indicative of AD. However, the hydrophobicity of amyloid-β peptides may lead to inaccurate analyses due to their binding to plasma proteins. Despite the significant potential of these biomarkers in detecting AD, further research remains necessary [170].

It is noteworthy that the asymptomatic phase of AD can last for decades, highlighting the importance of early detection and intervention. Physiological levels of Aβ₄₂ in the CSF of AD patients are typically below 500 pg/mL. Since AD is characterized by the production and deposition of amyloid-β oligomers in the brain, using this peptide as a biomarker shows promise for diagnosing and monitoring AD progression [170].

Advancements in biosensor technology have enabled innovative approaches for detecting tau proteins. Graphene-based nanomaterials [171], magnetic nanoparticles, label-free EC platforms [172], molecularly imprinted polymers (MIPs) [173], and gold nanoparticles [174] have demonstrated potential as recognition surfaces for t-Tau detection [55,91,171,175,176,177,178,179]. Table 5 summarizes reported electrochemical biosensors and their analytical performance for detecting Tau-related AD biomarkers.

Moreira et al. [177] created a biomimetic Tau-441 biosensor using Prussian blue nanocubes, achieving a detection limit of 0.01 pmol/L in spiked PBS and a linear range of 1.09–2.18 nmol/L. For instance, Patil et al. [180] developed a label-free biosensor using SPR technology to detect Tau-441 with remarkable sensitivity. This biosensor operates in a range of 5 fg/mL to 150 ng/mL, with a detection limit of 13.25 fg/mL.

Ziu et al. [181] designed a dip-and-read optical aptasensor using biolayer interferometry (BLI) for detecting Tau-441 protein, a critical AD biomarker. The BLI aptasensor demonstrated high specificity and selectivity, with a detection limit of 306.8 ng/mL and a dynamic range of 91.6 ng/mL to 25.1 µg/mL.

Dai et al. [182] introduced a technique for identifying t-tau protein in pure human serum and PBS using laser ablation to construct a biosensor from roll-to-roll materials. The biosensor utilized 3-mercaptopropionic acid (MPA) monolayers to immobilize anti-t-tau antibodies on a gold working electrode via carbodiimide coupling with EDC and NHS. This approach employed a t-tau protein ladder with six isoforms, with anti-t-tau at 500,000 pg/mL and t-tau at concentrations of 1000–100,000 pg/mL.

Guo et al. [20] developed an aptamer-antibody sandwich assay using an EC biosensor for tau-381 detection in human serum. The assay utilized cysteamine-stabilized gold nanoparticles to enhance the signal and tau-specific aptamers and antibodies as recognition elements. Tau-381 was detected at 0.42 pM with a linear range of 0.5–100 pM.

Similarly, Zeybekler et al. [183] developed a four-electrode EC biosensor using EIS for tau protein detection. This biosensor employed autonomous single layers and protein G over gold microband electrodes, achieving exceptional sensitivity and specificity even in complex matrices such as bovine or human serum Lastly, a label-free EC immunosensor for detecting t-tau in synthetic serum samples has been proposed. This immunosensor uses a nanocomposite structure of PDA and hexagonal boron nitride (HBN) modified with anti-t-tau antibodies. The HBN-PDA/anti-t-tau-modified SPCE demonstrated excellent electrochemical activity, with a broad linear detection range (1–30 pg/mL), high selectivity, and a trace detection limit of 0.42 pg/mL.

Table 5. List of reported electrochemical biosensors with their performance to detect Tau AD biomarkers.

Approach/Detection	Technique	Target	Linear Range Detection	Detection Limit	Samples	References
Sandwich immunoassay using HRP-DAb	Amperometry–0.20 V vs. Ag (HQ/H2O2)	Tau	~0.11–91 pM	1.7 pg/mL	Brain tissue, Blood	[174]
Electrochemical biosensor	EIS, CV	2N4R tau	0.01 pM–10 nM	0.03 pM	Human serum	[184]
Label-Freef Electrochemical Immunosensor	EIS, CV, DPV	cis P-tau	10 × 10−14–3.0 × 10−9 M	0.02 and 0.05 pM,	PBS Human serum	[71]
rGO-AuNP/11-MUA based biosensor ITO-coated PET	CV/EIS	Tau-441	1–500 pg/mL	0.091 pg/mL	Serum CSF	[171]
CeO2 NPs and nanocomposite of rGO (rGO-CeO2) via polyaniline (PANI)/GCE	CV/EIS	Tau	10 fM to 10 nM	1 fM	PBS	[185]
GO/LbL-AuNPs-Anti-tau-SPR	SPR sensogram	Tau-441	150 ng/mL to 5 fg/mL	13.25 fg/mL	Blood and saliva	[180]
Photoelectrochemical, FeOOH/Mo:BiVO4-PEC	LSV	Tau-5	100–104 fM	1.59 fM	Human plasma	[186]
label-free electrochemical aptasensor CG/TH/AuNPs	CV, EIS, DPV	Tau-381	1.0–100 pM	0.70 pM	Human serum	[172]
Enzyme-linked aptamer photoelectrochemical biosensor AuNPs/MoSe2	PEC	Tau-381	0.5 fM–1.0 nM	0.3 fM	Human serum	[187]
Electrochemical biosensor SPCE, MIP,3-aminophenol	CV.SWV, EIS	Tau-444	2.18 pM–2.18 nM	0.024 pM	Serum	[173]
Electrochemical biosensor Graphene oxide/Prussian blue nanocubes	EIS, SWV	Tau 441	1.09–2.18 nmol/L	0.01 pmol/L	Buffer	[177]
Immunosensor HPN-PDA	DPV	T-tau	1–30 pg/mL	0.42 pg/mL	Blood serum	[183]
Gold Nanostar, Carbon Nitride Nanosheets	ECL	Tau	0.1–100 ng/mL	0.034 ng/mL	Serum	[188]
Immunosensor SPCE, APTES	EIS	Tau-441	0.0064–0.8 ng/mL	0.0053 ng/mL	CSF	[189]

CG/TH/AuNPs—Carboxyl Graphene/Thionin/Gold Nanoparticles; FeOOH/Mo:BiVO₄-PEC—Iron oxyhydroxide/molybdenum:Bismuth vanadate; GO/LbL-AuNPs-Anti-Tau-SPR—Graphene oxide/Layer by layer-Gold nanoparticles-Surface plasma resonance; HPN-PDA—hexagonal boron nitride-polydopamine; HQ/H₂O₂—Hydroquinone/Hydrogen peroxide; HRP-Dab—Detector antibody labeled with horseradish peroxidase; MoSe₂—Molybdenum diselenide; rGO-AuNP/11-MUA—graphene oxide-gold nanoparticles-11-mercaptoundecanoic acid; SAM—Self-assembled monolayers; SPCE, MIP—Screen Printed Electrode, molecularly imprinted polymer.

Table 5. List of reported electrochemical biosensors with their performance to detect Tau AD biomarkers.

Approach/Detection	Technique	Target	Linear Range Detection	Detection Limit	Samples	References
Sandwich immunoassay using HRP-DAb	Amperometry–0.20 V vs. Ag (HQ/H2O2)	Tau	~0.11–91 pM	1.7 pg/mL	Brain tissue, Blood	[174]
Electrochemical biosensor	EIS, CV	2N4R tau	0.01 pM–10 nM	0.03 pM	Human serum	[184]
Label-Freef Electrochemical Immunosensor	EIS, CV, DPV	cis P-tau	10 × 10−14–3.0 × 10−9 M	0.02 and 0.05 pM,	PBS Human serum	[71]
rGO-AuNP/11-MUA based biosensor ITO-coated PET	CV/EIS	Tau-441	1–500 pg/mL	0.091 pg/mL	Serum CSF	[171]
CeO2 NPs and nanocomposite of rGO (rGO-CeO2) via polyaniline (PANI)/GCE	CV/EIS	Tau	10 fM to 10 nM	1 fM	PBS	[185]
GO/LbL-AuNPs-Anti-tau-SPR	SPR sensogram	Tau-441	150 ng/mL to 5 fg/mL	13.25 fg/mL	Blood and saliva	[180]
Photoelectrochemical, FeOOH/Mo:BiVO4-PEC	LSV	Tau-5	100–104 fM	1.59 fM	Human plasma	[186]
label-free electrochemical aptasensor CG/TH/AuNPs	CV, EIS, DPV	Tau-381	1.0–100 pM	0.70 pM	Human serum	[172]
Enzyme-linked aptamer photoelectrochemical biosensor AuNPs/MoSe2	PEC	Tau-381	0.5 fM–1.0 nM	0.3 fM	Human serum	[187]
Electrochemical biosensor SPCE, MIP,3-aminophenol	CV.SWV, EIS	Tau-444	2.18 pM–2.18 nM	0.024 pM	Serum	[173]
Electrochemical biosensor Graphene oxide/Prussian blue nanocubes	EIS, SWV	Tau 441	1.09–2.18 nmol/L	0.01 pmol/L	Buffer	[177]
Immunosensor HPN-PDA	DPV	T-tau	1–30 pg/mL	0.42 pg/mL	Blood serum	[183]
Gold Nanostar, Carbon Nitride Nanosheets	ECL	Tau	0.1–100 ng/mL	0.034 ng/mL	Serum	[188]
Immunosensor SPCE, APTES	EIS	Tau-441	0.0064–0.8 ng/mL	0.0053 ng/mL	CSF	[189]

CG/TH/AuNPs—Carboxyl Graphene/Thionin/Gold Nanoparticles; FeOOH/Mo:BiVO₄-PEC—Iron oxyhydroxide/molybdenum:Bismuth vanadate; GO/LbL-AuNPs-Anti-Tau-SPR—Graphene oxide/Layer by layer-Gold nanoparticles-Surface plasma resonance; HPN-PDA—hexagonal boron nitride-polydopamine; HQ/H₂O₂—Hydroquinone/Hydrogen peroxide; HRP-Dab—Detector antibody labeled with horseradish peroxidase; MoSe₂—Molybdenum diselenide; rGO-AuNP/11-MUA—graphene oxide-gold nanoparticles-11-mercaptoundecanoic acid; SAM—Self-assembled monolayers; SPCE, MIP—Screen Printed Electrode, molecularly imprinted polymer.

1.2.11. Aβ Monomers and Oligomers

Aβ peptides, consisting of 39–43 amino acid residues, are the main components of senile plaques. The amyloid precursor protein (APP) is broken down by β- and γ-secretase enzymes, producing these peptides. Naturally occurring Aβ monomers can aggregate to form small, soluble oligomers (AβOs). These oligomers may further reorganize into long, complex, and insoluble fibrils referred to as amyloid-β fibrils (AβFs). AβOs are particularly harmful to membrane functions, leading to significant neuronal damage in AD. Consequently, AβOs are considered highly reliable molecular biomarkers for the detection of AD [190,191].

Recently, Yin et al. [62] developed a user-friendly and cost-effective aptamer-based biosensor for detecting AβOs. This aptasensor accurately measures AβO concentrations within a range of 0.1–10 pM and achieves a remarkable LOD of 71 fM. It also exhibits high selectivity for AβOs and an exceptional recovery rate of 98.9–105.4% in human serum. Similarly, Wang et al. [192] designed an aptasensor employing a triple-helix aptamer switch for detecting AβOs. This EC assay demonstrates high sensitivity, with a LOD of 0.5 fM and a linear detection range of 1 fM to 10 pM.

Liao et al. [145] introduced an innovative label-free EC sensor for AβO detection, employing a hybridization chain reaction (HCR) to trigger polyadenine, which absorbs silver nanoparticles (AgNPs). This approach enhances the sensor’s accuracy and reliability by immobilizing AgNPs on the electrode surface through long polyadenine sequences in the HCR product. The sensor achieves a detection range of 1 pM to 10 nM, with a LOD of 430 fM.

Liu et al. [19] successfully developed an EC aptasensor for ultrasensitive AβO detection using gold-platinum (AuPt) alloy nanoparticles. These nanoparticles enhance the electroactive area and reduce nonspecific adsorption. The aptasensor can detect AβOs in a range of 0.5–10,000 pg/mL, with a LOD of 0.16 pg/mL in human serum samples.

Ning Xia et al. designed a biosensor employing linear sweep voltammetry to detect AβOs, using AgNPs as redox reporters and PrP (95–110) as the receptor. This method avoids the need for expensive and unstable antibodies or nanoparticle-modified analyte-binding receptors. The biosensor detects AβOs with a LOD of 8 pM and a linear detection range of 20–100 nM. As AβOs are neurotoxic in AD, this biosensor could serve as a reliable tool for early detection, outperforming other Aβ biomarkers. Additionally, it demonstrated the potential to enhance liquid-phase colorimetric measurements based on AgNPs through surface-tethered electrochemistry [191].

Hien T. Ngoc Le and colleagues designed a chain-like electrode using electrochemical impedance spectroscopy (EIS) to detect Aβ_1–42 peptides. This method achieved a LOD of 100 pg/mL with a linear detection range of 10⁻³–10³ ng/mL [25]. Similarly, Yun et al. [193] developed an EC sensor that detects Aβ oligomers by inhibiting peptide-induced aggregation of AgNPs. The sensor demonstrated a linear detection range of 0.01–200 nM, with a LOD of 6 pM.

Yuting Zhang and their team created an aptasensor using single-stranded DNA aptamers as receptors to capture AβOs. The aptasensor measures fluctuations in the charge-transfer resistance of redox probes via EIS. This design enables the detection of AβOs within an effective range of 0.03 nM and a concentration range of 0.1–500 nM [194].

1.2.12. POC Diagnosis

Currently, AD diagnostic methods, such as neuroimaging, ELISA, and PCR, are impractical for POC testing due to their reliance on expensive equipment, complex operational procedures, and often invasive sampling methods. However, novel POC techniques for identifying AD-related biomarkers have been developed, showcasing significant advancements in recent research.

Supraja et al. [195] introduced an innovative method for detecting the Aβ₄₀ and Aβ₄₂ biomarkers using a portable readout system. This method was integrated with an Android application designed for data analysis and POC applications. The approach employs polypyrrole nanoparticle-based chemiresistive biosensors, enabling label-free detection. Detection limits of 5.71 fg/mL for Aβ₄₀ and 9.09 fg/mL for Aβ₄₂ were achieved. The effectiveness of this novel method was validated using spiked plasma samples.

Sung et al. [196] developed a tool called Paper-based ELISA for detecting Aβ₄₂, which demonstrates great potential for analyzing human plasma samples. This method is simple, requiring only 3 μL of sample per well and a total analysis time of 90 min. The LOD achieved was 63.04 pg/mL.

2. Challenges, Limitations, and Aspects for Developing EC Biosensors for AD

EC immunosensors hold significant potential to revolutionize point-of-care testing (POCT) for AD diagnosis. However, several challenges must be addressed to fully realize their potential. Despite their advantages, including speed, affordability, sensitivity, and portability, the need for EC immunosensors with enhanced specificity and sensitivity remains critical for reliable diagnoses. One major challenge is the simultaneous detection of multiple AD biomarkers, which is essential for accurate disease diagnosis and prognosis. Given that a single biomarker may often be insufficient for clinical purposes, a suitable approach is necessary to improve the accuracy and overall efficiency of the diagnostic process.

The development of EC immunosensors faces several limitations and barriers. A primary concern is their inadequate sensitivity, which poses difficulties in detecting low analyte concentrations or analyzing complex biological samples. Interfering substances in biological samples can further compromise the reliability and precision of EC immunosensors. Additionally, issues such as electrode fouling, degradation of bioreceptors, and variability in fabrication processes contribute to challenges in achieving long-term stability and reproducibility. To address these challenges, developing miniaturized, integrated, and cost-effective EC immunosensors while maintaining efficacy is essential to make them practical and user-friendly for POCT. Furthermore, the lack of clinical validation and standardized protocols may delay the approval process for clinical use [170].

Selectivity is a pivotal parameter for the clinical effectiveness of immunosensors, as it ensures that target analytes are specifically recognized and accurately quantified, even in complex biological matrices containing potential interferents. Several factors can significantly affect the selectivity of immunosensors, including temperature, pH, humidity, non-specific binding, and cross-reactivity. Non-specific binding and cross-reactivity represent significant challenges in diagnostic assays, particularly in the context of AD diagnostics. Non-specific binding occurs when non-target molecules in a sample attach to the capture antibody, resulting in unreliable signal detection. Similarly, cross-reactivity happens when antibodies interact with unintended biomolecules, which can lead to false-positive results. These inaccuracies are especially concerning in AD diagnostics, as they can result in misdiagnosis and inappropriate clinical decisions. Ensuring the specificity and accuracy of these measurements is crucial for reliable diagnosis and treatment planning [197].

Various strategies can mitigate the interference in immunosensing techniques. These include the use of blocking materials to prevent non-specific binding, optimizing assay parameters to minimize cross-reactions, selecting appropriate binding frameworks, and pre-treating biological samples through processes such as extraction, filtration, or dilution. Additionally, choosing bioreceptors with high affinity and employing proper immobilization techniques can enhance immunosensor performance.

The methods used to immobilize antibodies onto electrode surfaces play a crucial role in determining the specificity, efficiency, and durability of immunosensors. Among these, covalent binding is widely recognized as the most effective strategy for enhancing both durability and selectivity. This technique utilizes the functional groups of bioreceptors to form strong covalent bonds between the antibody and the electrode surface. Compared to conventional immobilization methods, covalent binding offers significant advantages, particularly in terms of stability. It ensures that antibodies remain securely attached to the electrode surface even under challenging conditions, such as high temperatures, extreme pH levels, high ionic strength, or rigorous washing. This robust attachment greatly improves the long-term reliability and performance of immunosensors.

Covalent binding also optimizes the orientation of bioreceptors, ensuring their binding sites are appropriately exposed for interaction with target analytes. This minimizes non-specific binding and improves the immunosensor’s specificity and accuracy. Furthermore, this method is versatile, supporting the immobilization of various antibody types, including monoclonal, polyclonal, fragment, and engineered antibodies. Electrode modifications with functional groups such as thiol (-SH), amine (-NH₂), or carboxylic acid (-COOH) enable robust covalent attachment of antibodies. For instance, thiol groups can form strong Au-S bonds with gold surfaces, while surface chemistries such as aminopropyl triethoxy silane/glutaraldehyde (APTES/GA) and EDC/NHS activation facilitate covalent interactions between electrode surfaces and antibodies. Overall, covalent bonding remains the preferred method for creating EC immunosensors with high sensitivity and selectivity, making them suitable for advanced diagnostic applications.

3. Conclusions and Future Perspectives

While sensor-based molecular biomarker detection represents a promising approach for the early diagnosis of Alzheimer’s disease, it is essential to recognize the value of neuroimaging techniques. Rather than being alternatives, these modalities are complementary. Integrating biomarker-based sensors with imaging methods can enhance diagnostic accuracy, improve disease staging, and ultimately support more effective clinical decision-making. A multimodal diagnostic strategy that leverages both molecular and structural information offers the most robust approach to managing Alzheimer’s disease.

AD is a progressive neurological condition that affects millions globally, leading to significant declines in cognitive function, memory, and physical capacity, ultimately hindering daily activities. Early evaluation and treatment of AD can greatly enhance patients’ quality of life. However, proper diagnosis poses challenges due to the need for timely, reliable, and accurate diagnostic methods. There is a pressing need to develop sensitive, user-friendly, affordable, reliable, and precise diagnostic devices to facilitate the detection and treatment of AD. Blood-based biomarkers have emerged as a promising diagnostic alternative, as they are more cost-effective, accessible, and less invasive than CSF-based biomarkers, allowing for broader applicability across symptomatic and asymptomatic patients. Advanced EC immunosensors enable the detection of various AD-associated biomarkers, including Aβ proteins (1–40, 1–42) and tau proteins (t-tau, c-tau, p-tau181, p-tau 231, p-tau 381, and p-tau 441), in biofluids such as blood and CSF.

Extensive research has explored diverse techniques for early-stage AD diagnosis, including electrochemical, electrical, mechanical, and optical approaches. These methods aim to identify specific biomarkers associated with AD for prompt detection and efficient therapy. Despite their promise, each technique has unique advantages and limitations. EC biosensors stand out as a promising diagnostic tool due to their user-friendliness, portability, and cost-effectiveness. Incorporating such technologies into clinical care and testing procedures is crucial to ensure widespread adoption and effectiveness in managing AD.

Further research is needed to enhance the efficacy of EC biosensors and evaluate their clinical relevance in AD diagnosis. Research efforts focus on critical aspects of immunosensing technologies, including electrode materials, nanomaterials, biofunctionalization techniques, signal amplification, linearity, sensitivity, detection limits, and clinical viability. Addressing these issues is essential for advancing effective diagnostic tools.

A significant innovation in EC biosensor development is the integration of analytical capabilities into a single platform. EC biosensors capable of detecting multiple AD biomarkers simultaneously can improve sensitivity and reduce false-positive and false-negative outcomes. Employing biorecognition molecules with unique characteristics and optimized redox-active labeling can enhance the detection of AD-associated biomarkers. This approach facilitates the identification of multiple biomarkers, increasing diagnostic accuracy. One solution to the challenge of overlapping or interfering signals in EC methods is the use of redox-active labels. Moreover, biosensors for POC applications require designs that are highly effective, affordable, and accessible. The incorporation of nanomaterials, nanofabrication, and biomimetic materials plays a pivotal role in enhancing biomarker detection for AD.

EC immunosensors, known for their sensitivity, adaptability, and affordability, are emerging as a viable option for AD screening. This technology offers a non-invasive and reliable alternative to traditional diagnostic methods, making it a compelling avenue for future research. By detecting disease-associated biomarkers, EC immunosensors can significantly improve the early detection and management of AD. Integrating these technologies into healthcare and screening processes is vital to ensure broad usage and efficacy in disease management.

Developing EC biosensors for detecting multiple AD biomarkers can enhance precision and reduce the risk of inaccurate results. Portable EC biosensors may enable individuals in the early stages of AD to self-assess and monitor their disease progression from home. As cutting-edge medical devices, biosensors hold immense potential to revolutionize the healthcare industry, particularly through technologies enabling POC testing and remote monitoring. Easily obtainable specimens, such as blood and saliva, are frequently utilized in diagnostic tests, further simplifying their application. Integrating EC biosensors with cloud technologies can facilitate real-time diagnostic result communication, enhancing precision, accelerating treatment, and improving accessibility. Future EC biosensors could feature networked detection devices or interfaces such as smartphone firmware, USBs, or disks, enabling real-time cloud-based data uploads. However, many modern biosensors rely on large, inflexible electrodes, limiting their suitability for home use. Compact, durable devices with reliable EC cells specifically designed for portability are essential.

To meet practical demands, it is crucial to integrate EC detection technologies with device design, data collection and analysis, and telecommunication systems. Nanomaterials offer significant promise in improving biosensor sensitivity for POC and early diagnostic applications. Leveraging nanomaterials, advanced nanofabrication methods, and biomimetic surfaces can greatly enhance the detection accuracy of AD biomarkers. Further research is required to assess the effectiveness of EC biosensors in clinical settings. The design of biosensors employing EC sensors to detect Aβ₄₂, in particular, shows promise for improving AD detection and treatment. This review highlights the potential of biosensors to advance AD diagnosis and therapy, benefiting professionals in analytical chemistry, medical practice, and biological research.

The implementation of EC biosensors for detecting Aβ₄₂ offers a simple, rapid, and reliable method for identifying AD in its initial stages. This promising technology has the potential to revolutionize AD detection and management, sparking widespread interest within the scientific community.