Diagnostic accuracy of blood biomarkers for Alzheimer's disease and amnestic mild cognitive impairment: A meta-analysis

What Are the Reliable Plasma Biomarkers for Mild Cognitive Impairment? A Clinical 4D Proteomics Study and Validation

Objective

At present, Alzheimer's disease (AD) lacks effective treatment means, and early diagnosis and intervention are the keys to treatment. Therefore, for mild cognitive impairment (MCI) and AD patients, blood sample analysis using the 4D nonstandard (label-free) proteomic in-depth quantitative analysis, looking for specific protein marker expression differences, is important. These marker levels change as AD progresses, and the analysis of these biomarkers changes with this method, which has the potential to show the degree of disease progression and can be used for the diagnosis and preventive treatment of MCI and AD.

Materials and Methods

Patients were recruited according to the inclusion and exclusion criteria and divided into three groups according to scale scores. Elderly patients diagnosed with AD were selected as the AD group (n = 9). Patients diagnosed with MCI were classified into the MCI group (n = 10). Cognitively healthy elderly patients were included in the normal cognition control group (n = 10). Patients' blood samples were used for 4D label-free proteomic in-depth quantitative analysis to identify potential blood biomarkers. The sample size of each group was expanded (n = 30), and the selected biomarkers were verified by enzyme-linked immunosorbent assay (ELISA) to verify the accuracy of the proteomic prediction.

Results

Six specific blood markers, namely, APOE, MMP9, UBR5, PLA2G7, STAT5B, and S100A8, were detected by 4D label-free proteomic quantitative analysis. These markers showed a statistically significant upregulation trend in the MCI and AD groups compared with the normal cognition control group (P < 0.05). ELISA results showed that the levels of these six proteins in the MCI group were significantly higher than those in the normal cognition control group, and the levels of these six proteins in the AD group were significantly higher than those in the MCI group (P < 0.05).

Conclusion

The plasma levels of APOE, MMP9, UBR5, PLA2G7, STAT5B, and S100A8 in cognitively healthy elderly patients and patients with MCI and AD were significantly different and, more importantly, showed a trend of increasing expression. These results indicate that these six human plasma markers have important diagnostic and therapeutic potential in the identification of cognitive impairment and have value for in-depth research and clinical application.

Skin-brain axis in Alzheimer's disease - Pathologic, diagnostic, and therapeutic implications: A Hypothetical Review

The dynamic interaction between the brain and the skin is termed the 'skin-brain axis.' Changes in the skin not only reflect conditions in the brain but also exert direct and indirect effects on the brain. Interestingly, the connection between the skin and brain is crucial for understanding aging and neurodegenerative diseases. Several studies have shown an association between Alzheimer's disease (AD) and various skin disorders, such as psoriasis, bullous pemphigoid, and skin cancer. Previous studies have shown a significantly increased risk of new-onset AD in patients with psoriasis. In contrast, skin cancer may reduce the risk of developing AD. Accumulating evidence suggests an interaction between skin disease and AD; however, AD-associated pathological changes mediated by the skin-brain axis are not yet clearly defined. While some studies have reported on the diagnostic implications of the skin-brain axis in AD, few have discussed its potential therapeutic applications. In this review, we address the pathological changes mediated by the skin-brain axis in AD. Furthermore, we summarize (1) the diagnostic implications elucidated through the role of the skin-brain axis in AD and (2) the therapeutic implications for AD based on the skin-brain axis. Our review suggests that a potential therapeutic approach targeting the skin-brain axis will enable significant advances in the treatment of AD.

Neuropathology, Neuroimaging, and Fluid Biomarkers in Alzheimer's Disease

An improved understanding of the pathobiology of Alzheimer's disease (AD) should lead ultimately to an earlier and more accurate diagnosis of AD, providing the opportunity to intervene earlier in the disease process and to improve outcomes. The known hallmarks of Alzheimer's disease include amyloid-β plaques and neurofibrillary tau tangles. It is now clear that an imbalance between production and clearance of the amyloid beta protein and related Aβ peptides, especially Aβ42, is a very early, initiating factor in Alzheimer's disease (AD) pathogenesis, leading to aggregates of hyperphosphorylation and misfolded tau protein, inflammation, and neurodegeneration. In this article, we review how the AD diagnostic process has been transformed in recent decades by our ability to measure these various elements of the pathological cascade through the use of imaging and fluid biomarkers. The more recently developed plasma biomarkers, especially phosphorylated-tau217 (p-tau217), have utility for screening and diagnosis of the earliest stages of AD. These biomarkers can also be used to measure target engagement by disease-modifying therapies and the response to treatment.

Digital Marker for Early Screening of Mild Cognitive Impairment Through Hand and Eye Movement Analysis in Virtual Reality Using Machine Learning: First Validation Study

BACKGROUND

With the global rise in Alzheimer disease (AD), early screening for mild cognitive impairment (MCI), which is a preclinical stage of AD, is of paramount importance. Although biomarkers such as cerebrospinal fluid amyloid level and magnetic resonance imaging have been studied, they have limitations, such as high cost and invasiveness. Digital markers to assess cognitive impairment by analyzing behavioral data collected from digital devices in daily life can be a new alternative. In this context, we developed a "virtual kiosk test" for early screening of MCI by analyzing behavioral data collected when using a kiosk in a virtual environment.

OBJECTIVE

We aimed to investigate key behavioral features collected from a virtual kiosk test that could distinguish patients with MCI from healthy controls with high statistical significance. Also, we focused on developing a machine learning model capable of early screening of MCI based on these behavioral features.

METHODS

A total of 51 participants comprising 20 healthy controls and 31 patients with MCI were recruited by 2 neurologists from a university hospital. The participants performed a virtual kiosk test-developed by our group-where we recorded various behavioral data such as hand and eye movements. Based on these time series data, we computed the following 4 behavioral features: hand movement speed, proportion of fixation duration, time to completion, and the number of errors. To compare these behavioral features between healthy controls and patients with MCI, independent-samples 2-tailed t tests were used. Additionally, we used these behavioral features to train and validate a machine learning model for early screening of patients with MCI from healthy controls.

RESULTS

In the virtual kiosk test, all 4 behavioral features showed statistically significant differences between patients with MCI and healthy controls. Compared with healthy controls, patients with MCI had slower hand movement speed (t49=3.45; P=.004), lower proportion of fixation duration (t49=2.69; P=.04), longer time to completion (t49=-3.44; P=.004), and a greater number of errors (t49=-3.77; P=.001). All 4 features were then used to train a support vector machine to distinguish between healthy controls and patients with MCI. Our machine learning model achieved 93.3% accuracy, 100% sensitivity, 83.3% specificity, 90% precision, and 94.7% F1-score.

CONCLUSIONS

Our research preliminarily suggests that analyzing hand and eye movements in the virtual kiosk test holds potential as a digital marker for early screening of MCI. In contrast to conventional biomarkers, this digital marker in virtual reality is advantageous as it can collect ecologically valid data at an affordable cost and in a short period (5-15 minutes), making it a suitable means for early screening of MCI. We call for further studies to confirm the reliability and validity of this approach.

Application of Pt@ZIF-8 nanocomposite-based electrochemical biosensor for sensitive diagnosis of tau protein in Alzheimer's disease patients

Alzheimer's disease (AD) is a progressive brain disorder characterized by the ongoing decline of brain functions. Studies have revealed the detrimental effects of hyperphosphorylated tau (p-tau) protein fibrils in AD pathogenesis, highlighting the importance of this factor in the early-stage detection of AD conditions. We designed an electrochemical immunosensor for quantitative detection of the cis conformation of the p-tau protein (cis-p-tau) employing platinum nanoparticles (Pt NPs) supported on zeolitic imidazolate frameworks (ZIF) for modifying the glassy carbon electrode (GCE) surface. Under optimum conditions, the immunosensor selectively and sensitively detected cis-p-tau within the broad linear range of 1 fg mL-1 to 10 ng mL-1 and the low limit of detection (LOD) of 1 fg mL-1 with desired reproducibility and stability. Furthermore, the fabricated immunosensor's performance was examined for the cis-p-tau analysis in the serum of AD patients, indicating its accuracy and feasibility for real-sample analysis. Notably, this is the first application of Pt@ZIF-8 nanocomposite in fabricating a valid immunosensor for selective cis-p-tau detection, even in the presence of trans-p-tau. It is worth mentioning that the enzyme-linked immunosorbent assay (ELISA) reference technique is not able to evaluate pico- or femtomolar concentrations of cis-p-tau, making the fabricated immunosensor superior for early-stage measurement and screening of AD.

SERS-Based Optical Nanobiosensors for the Detection of Alzheimer's Disease

Alzheimer's disease (AD) is a leading cause of dementia, impacting millions worldwide. However, its complex neuropathologic features and heterogeneous pathophysiology present significant challenges for diagnosis and treatment. To address the urgent need for early AD diagnosis, this review focuses on surface-enhanced Raman scattering (SERS)-based biosensors, leveraging the excellent optical properties of nanomaterials to enhance detection performance. These highly sensitive and noninvasive biosensors offer opportunities for biomarker-driven clinical diagnostics and precision medicine. The review highlights various types of SERS-based biosensors targeting AD biomarkers, discussing their potential applications and contributions to AD diagnosis. Specific details about nanomaterials and targeted AD biomarkers are provided. Furthermore, the future research directions and challenges for improving AD marker detection using SERS sensors are outlined.

Methodological flaws in"diagnostic accuracy of blood biomarkers for Alzheimer's disease and amnestic mild cognitive impairment: A meta-analysis"

We read with interest the review by Chen et al. They intended to examine the diagnostic accuracy of blood-based biomarkers for detecting Alzheimer's disease and amnestic mild cognitive impairment. We believe that there were substantial methodological flaws in their meta-analysis. These methodological flaws included no comprehensive literature search details, neglect of the negative result research, no prespecified cut-off values, erroneous data input in their meta-analysis, and the issue of prevalence determined by the included studies. These factors potentially contributed to overestimation of the discriminative accuracy of blood-based biomarkers. Subsequently, the conclusion that blood-based biomarkers are effective tools for detecting Alzheimer's disease is debatable without correction of these methodological flaws and providing robust and trustworthy estimates.

The Role of Clinical Assessment in the Era of Biomarkers

Hippocratic Medicine revolved around the three main principles of patient, disease, and physician and promoted the systematic observation of patients, rational reasoning, and interpretation of collected information. Although these remain the cardinal features of clinical assessment today, Medicine has evolved from a more physician-centered to a more patient-centered approach. Clinical assessment allows physicians to encounter, observe, evaluate, and connect with patients. This establishes the patient-physician relationship and facilitates a better understanding of the patient-disease relationship, as the ultimate goal is to diagnose, prognosticate, and treat. Biomarkers are at the core of the more disease-centered approach that is currently revolutionizing Medicine as they provide insight into the underlying disease pathomechanisms and biological changes. Genetic, biochemical, radiographic, and clinical biomarkers are currently used. Here, we define a seven-level theoretical construct for the utility of biomarkers in neurodegenerative diseases. Level 1-3 biomarkers are considered supportive of clinical assessment, capable of detecting susceptibility or risk factors, non-specific neurodegeneration or dysfunction, and/or changes at the individual level which help increase clinical diagnostic accuracy and confidence. Level 4-7 biomarkers have the potential to surpass the utility of clinical assessment through detection of early disease stages and prediction of underlying pathology. In neurodegenerative diseases, biomarkers can potentiate, but cannot substitute, clinical assessment. In this current era, aside from adding to the discovery, evaluation/validation, and implementation of more biomarkers, clinical assessment remains crucial to maintaining the personal, humanistic, and sociocultural aspects of patient care. We would argue that clinical assessment is a custom that should never go obsolete.

Plasma Biomarkers of Alzheimer's Disease: A Review of Available Assays, Recent Developments, and Implications for Clinical Practice

Recently, low-sensitive plasma assays have been replaced by new ultra-sensitive assays such as single molecule enzyme-linked immunosorbent assay (Simoa), the Mesoscale Discovery (MSD) platform, and immunoprecipitation-mass spectrometry (IP-MS) with higher accuracy in the determination of plasma biomarkers of Alzheimer's disease (AD). Despite the significant variability, many studies have established in-house cut-off values for the most promising available biomarkers. We first reviewed the most used laboratory methods and assays to measure plasma AD biomarkers. Next, we review studies focused on the diagnostic performance of these biomarkers to identify AD cases, predict cognitive decline in pre-clinical AD cases, and differentiate AD cases from other dementia. We summarized data from studies published until January 2023. A combination of plasma Aβ_42/40 ratio, age, and APOE status showed the best accuracy in diagnosing brain amyloidosis with a liquid chromatography-mass spectrometry (LC-MS) assay. Plasma p-tau217 has shown the best accuracy in distinguishing Aβ-PET+ from Aβ-PET-even in cognitively unimpaired individuals. We also summarized the different cut-off values for each biomarker when available. Recently developed assays for plasma biomarkers have undeniable importance in AD research, with improved analytical and diagnostic performance. Some biomarkers have been extensively used in clinical trials and are now clinically available. Nonetheless, several challenges remain to their widespread use in clinical practice.

Sphingolipids in Cerebrospinal Fluid and Plasma Lipoproteins of APOE4 Homozygotes and Non-APOE4 Carriers with Mild Cognitive Impairment versus Subjective Cognitive Decline

Background: Alzheimer’s disease (AD) patients display alterations in cerebrospinal fluid (CSF) and plasma sphingolipids. The APOE4 genotype increases the risk of developing AD. Objective: To test the hypothesis that the APOE4 genotype affects common sphingolipids in CSF and in plasma of patients with early stages of AD. Methods: Patients homozygous for APOE4 and non-APOE4 carriers with mild cognitive impairment (MCI; n = 20 versus 20) were compared to patients with subjective cognitive decline (SCD; n = 18 versus 20). Sphingolipids in CSF and plasma lipoproteins were determined by liquid-chromatography-tandem mass spectrometry. Aβ42 levels in CSF were determined by immunoassay. Results: APOE4 homozygotes displayed lower levels of sphingomyelin (SM; p = 0.042), SM(d18:1/18:0) (p = 0.026), and Aβ 42 (p < 0.001) in CSF than non-APOE4 carriers. CSF-Aβ 42 correlated with Cer(d18:1/18:0), SM(d18:1/18:0), and SM(d18:1/18:1) levels in APOE4 homozygotes (r > 0.49; p < 0.032) and with Cer(d18:1/24:1) in non-APOE4 carriers (r = 0.50; p = 0.025). CSF-Aβ 42 correlated positively with Cer(d18:1/24:0) in MCI (p = 0.028), but negatively in SCD patients (p = 0.019). Levels of Cer(d18:1/22:0) and long-chain SMs were inversely correlated with Mini-Mental State Examination score among MCI patients, independent of APOE4 genotype (r< –0.47; p < 0.039). Nevertheless, age and sex are stronger determinants of individual sphingolipid levels in CSF than either the APOE genotype or the cognitive state. In HDL, ratios of Cer(d18:1/18:0) and Cer(d18:1/22:0) to cholesterol were higher in APOE4 homozygotes than in non-APOE4 carriers (p = 0.048 and 0.047, respectively). Conclusion: The APOE4 genotype affects sphingolipid profiles of CSF and plasma lipoproteins already at early stages of AD. ApoE4 may contribute to the early development of AD through modulation of sphingolipid metabolism.

Blood-based biomarkers in Alzheimer's disease: a mini-review

Alzheimer's disease (AD) is the most common cause of dementia and has far reaching consequences for patients and their caregivers. Early detection and treatment are key factors in limiting the impact of the disease. However, a definitive diagnosis of AD requires an examination of brain tissue during an autopsy. Although a plethora of biomarkers such as neuroimaging, electrophysiological, and cerebrospinal fluid (CSF) biomarkers are available, their utility is limited to research due to their poor reach and prohibitive cost. In order for biomarkers to be widely used, they need to be accessible, affordable, and conducive for the patient population or disease stage. Blood-based biomarkers may not only be less expensive and more accessible compared to neuroimaging or CSF tests, but they are also preferred by patients with AD as they are much less invasive. In this mini-review article, we expand on the rationale for the use of blood-based biomarkers, review currently available biomarkers and discuss the need for the standardization of these biomarkers. We contrast the blood-based biomarkers with other available biomarkers and discuss the advantages of using a panel of blood-based biomarkers to strengthen their accuracy.

Altered serum amyloid beta and cerebral perfusion and their associations with cognitive function in patients with subcortical ischemic vascular disease

Subcortical ischemic vascular disease (SIVD) is one of the important causes of cognitive dysfunction, altered amyloid-beta (Aβ) and cerebral perfusion may be involved in the pathophysiological mechanism of SIVD and are closely related to cognitive function. We aimed to investigate altered serum Aβ and cerebral perfusion in patients with SIVD and their correlation with cognitive function. Seventy-four healthy controls (HCs) and 74 SIVD patients, including 38 SIVD patients with no cognitive impairment (SIVD-NCI) and 36 SIVD patients with mild cognitive impairment (SIVD-MCI) underwent the measurement of serum Aβ40 and Aβ42 levels, pseudo-continuous arterial spin labeling MRI scanning, and cognitive evaluation. Compared to the healthy controls (HCs), the level of serum Aβ40 and Aβ40/42 ratio increased and Aβ42 decreased in SIVD patients. The serum Aβ40 level and Aβ40/42 ratio in patients with SIVD-MCI were significantly higher than those in the HCs and SIVD-NCI, and the level of Aβ42 in the SIVD-MCI was lower than the HCs. In addition, the serum Aβ40/42 ratio provided high diagnostic accuracy for SIVD and SIVD-MCI, it was further identified as an independent risk factor for cognitive impairment. Patients with SIVD-NCI and SIVD-MCI exhibited both increased and decreased cerebral blood flow (CBF) in regional. The Aβ40/42 ratio was associated with global CBF, while altered global and regional CBF was associated with cognitive deficits. In addition, white matter hyperintensities volume (WMHV) correlated with Aβ40/42 ratio, CBF, and cognition. The relationship between Aβ40/42 ratio and cognition was partially mediated by altered CBF. Based on these results, we conclude that the serum Aβ40/42 ratio may be a potential biomarker that can complement current methods for the prediction and diagnosis of cognitive impairment in SIVD patients. In addition, serum Aβ may play a role in cognitive function by regulating CBF, which provides new insights into the intervention, treatment, and prevention of cognitive impairment in SIVD.

Effect of acupuncture on brain regions modulation of mild cognitive impairment: A meta-analysis of functional magnetic resonance imaging studies

Background

As a non-pharmacological therapy, acupuncture has significant efficacy in treating Mild Cognitive Impairment (MCI) compared to pharmacological therapies. In recent years, advances in neuroimaging techniques have provided new perspectives to elucidate the central mechanisms of acupuncture for MCI. Many acupuncture brain imaging studies have found significant improvements in brain function after acupuncture treatment of MCI, but the underlying mechanisms of brain regions modulation are unclear.

Objective

A meta-analysis of functional magnetic resonance imaging studies of MCI patients treated with acupuncture was conducted to summarize the effects of acupuncture on the modulation of MCI brain regions from a neuroimaging perspective.

Methods

Using acupuncture, neuroimaging, magnetic resonance, and Mild Cognitive Impairment as search terms, PubMed, EMBASE, Web of Science, Cochrane Library, Cochrane Database of Systematic Reviews, Cochrane Database of Abstracts of Reviews of Effects (DARE), Google Scholar, China National Knowledge Infrastructure (CNKI), China Biology Medicine disk (CBM disk), Wanfang and Chinese Scientific Journal Database (VIP) for brain imaging studies on acupuncture on MCI published up to April 2022. Voxel-based neuroimaging meta-analysis of fMRI data was performed using voxel-based d Mapping with Permutation of Subject Images (SDM-PSI), allowing for Family-Wise Error Rate (FWER) correction correction for correction multiple comparisons of results. Subgroup analysis was used to compare the differences in brain regions between the acupuncture treatment group and other control groups. Meta-regression was used to explore demographic information and altered cognitive function effects on brain imaging outcomes. Linear models were drawn using MATLAB 2017a, and visual graphs for quality evaluation were produced using R software and RStudio software.

Results

A total of seven studies met the inclusion criteria, with 94 patients in the treatment group and 112 patients in the control group. All studies were analyzed using the regional homogeneity (ReHo) method. The experimental design of fMRI included six task state studies and one resting-state study. The meta-analysis showed that MCI patients had enhanced activity in the right insula, left anterior cingulate/paracingulate gyri, right thalamus, right middle frontal gyrus, right median cingulate/paracingulate gyri, and right middle temporal gyrus brain regions after acupuncture treatment. Further analysis of RCT and longitudinal studies showed that Reho values were significantly elevated in two brain regions, the left anterior cingulate/paracingulate gyrus and the right insula, after acupuncture. The MCI group showed stronger activity in the right supramarginal gyrus after acupuncture treatment compared to healthy controls. Meta-regression analysis showed that the right anterior thalamic projection ReHo index was significantly correlated with the MMSE score after acupuncture treatment in all MCI patients.

Conclusions

Acupuncture therapy has a modulating effect on the brain regions of MCI patients. However, due to the inadequate experimental design of neuroimaging studies, multi-center neuroimaging studies with large samples are needed better to understand the potential neuroimaging mechanisms of acupuncture for MCI. In addition, machine learning algorithm-based predictive models for evaluating the efficacy of acupuncture for MCI may become a focus of future research.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022287826, identifier: CRD 42022287826.

Diagnostic accuracy of the American College of Rheumatology-1997, the Systemic Lupus International Collaborating Clinics-2012, and the European League Against Rheumatism-2019 criteria for juvenile systemic lupus erythematosus: A systematic review and network meta-analysis

IMPORTANCE/BACKGROUND

Several diagnostic criteria have been developed to effectively diagnose systemic lupus erythematosus (SLE). Three criteria are most common, namely the American College of Rheumatology (ACR)-1997, the Systemic Lupus International Collaborating Clinics (SLICC)-2012, and the European League Against Rheumatism (EULAR/ACR)-2019. Whether they also apply to juvenile SLE is unclear.

OBJECTIVE

To examine the diagnostic accuracy of ACR-1997, SLICC-2012, and EULAR/ACR-2019 for juvenile SLE.

DATA SOURCES

A comprehensive search of PubMed, Cochrane, and Embase was conducted up to 26 March 2022.

STUDY SELECTION

We included all study designs in which patients had any index tests for ACR-1997, SLICC-2012, or EULAR/ACR-2019; both full-text papers and conference abstracts published in English were used. Exclusion criteria were as follows: (1) case reports; (2) adult subjects; or (3) did not report sufficient information to acquire true positive, false positive, true negative, and false negative values of diagnostic criteria.

DATA EXTRACTION AND SYNTHESIS

Two authors independently screened studies, extracted relevant data, and assessed the risk of bias.

MAIN OUTCOMES AND MEASURES

First, a meta-analysis of the diagnostic accuracy of EULAR/ACR-2019 and a hierarchical summary receiver operating characteristic (HSROC) model was performed to estimate sensitivity and specificity with 95% confidence intervals (CIs). We then carried out a network meta-analysis to compare the performances of these three diagnostic criteria.

RESULTS

In total, 17 relevant studies that included 2339 juvenile SLE patients were eligible to analyze pooled accuracy. In the meta-analysis, 10 studies (1613 cases) reported the diagnostic performance of EULAR/ACR-2019, showing a pooled sensitivity of 0.92 (95% CI, 0.89-0.95), pooled specificity of 0.89 (0.77-0.95), and area under HSROC of 0.96 (0.94-0.97). In the network meta-analysis, the SLICC-2012 (0.94, 0.92-0.96) had the highest sensitivity, followed by EULAR/ACR-2019 (0.93, 0.90-0.95), and ACR-1997 (0.78, 0.72-0.82); the ACR-1997 (0.96, 0.92-0.98) demonstrated the highest specificity. EULAR/ACR-2019 (0.92, 0.87-0.96) and SLICC-2012 (0.92, 0.86-0.96) had the similar specificity.

CONCLUSIONS AND RELEVANCE

We found that the applicability of the new EULAR/ACR-2019 criteria in juvenile SLE is not yet the best diagnostic tool.

TRIAL REGISTRATION

PROSPERO CRD42022321514.

A new generation of AD biomarkers: 2019 to 2021

Alzheimer's disease (AD) is the most common form of dementia and cases are rising worldwide. The effort to fight this disease is hampered by a lack of disease-modifying treatments and the absence of an early, accurate diagnostic tool. Neuropathology begins years or decades before symptoms occur and, upon onset of symptoms, diagnosis can take a year or more. Such delays postpone treatment and make research into the early stages of the disease difficult. Ideally, clinicians require a minimally invasive test that can detect AD in its early stages, before cognitive symptoms occur. Advances in proteomic technologies have facilitated the study of promising biomarkers of AD. Over the last two years (2019-2021) studies have identified and validated many species which can be measured in cerebrospinal fluid (CSF), plasma, or in both fluids, and which have a high predictive value for AD. We herein discuss proteins which have been highlighted as promising biomarkers of AD in the last two years, and consider implications for future research within the research framework of the amyloid (A), tau (T), neurodegeneration (N) scoring system. We review recently identified species of amyloid and tau which may improve diagnosis when used in combination with current measures such as amyloid-beta-42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau). In addition, several proteins have been identified as likely proxies for neurodegeneration, including neurofilament light (NfL), synaptosomal-associated protein 25 (SNAP-25) and neurogranin (NRGN). Finally, proteins originating from diverse processes such as neuroinflammation, lipid transport and mitochondrial dysfunction could aid in both AD diagnosis and patient stratification.

Patterns of Distribution of 18F-THK5351 Positron Emission Tomography in Alzheimer's Disease Continuum

BACKGROUND

Alzheimer's disease (AD) is conceptualized as a biological continuum encompassing the preclinical (clinically asymptomatic but with evidence of AD pathology) and clinical (symptomatic) phases.

OBJECTIVE

Using 18F-THK5351 as a tracer that binds to both tau and MAO-B, we investigated the changes in 18F-THK5351 accumulation patterns in AD continuum individuals with positive amyloid PET consisting of cognitively normal individuals (CNp), amnestic mild cognitive impairment (aMCI), and AD and cognitively normal individuals (CNn) with negative amyloid PET.

METHODS

We studied 69 individuals (32 CNn, 11 CNp, 9 aMCI, and 17 AD) with structural magnetic resonance imaging, 11C-Pittsburgh compound-B (PIB) and 18F-THK5351 PET, and neuropsychological assessment. 18F-THK5351 accumulation was evaluated with visual analysis, voxel-based analysis and combined region of interest (ROI)-based analysis corresponding to Braak neurofibrillary tangle stage.

RESULTS

On visual analysis, 18F-THK5351 accumulation was increased with stage progression in the AD continuum. On voxel-based analysis, there was no statistical difference in 18F-THK5351 accumulation between CNp and CNn. However, a slight increase of the bilateral posterior cingulate gyrus in aMCI and definite increase of the bilateral parietal temporal association area and posterior cingulate gyrus/precuneus in AD were detected compared with CNn. On ROI-based analyses, 18F-THK5351 accumulation correlated positively with supratentorial 11C-PIB accumulation and negatively with the hippocampal volume and neuropsychological assessment.

CONCLUSION

The AD continuum showed an increase in 18F-THK5351 with stage progression, suggesting that 18F-THK5351 has the potential to visualize the severity of tau deposition and neurodegeneration in accordance with the AD continuum.