Imaging Biomarkers in Alzheimer's Disease: A Practical Guide for Clinicians

The Importance of Subjective Cognitive Decline Recognition and the Potential of Molecular and Neurophysiological Biomarkers-A Systematic Review

Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are early stages of Alzheimer's disease (AD). Neurophysiological markers such as electroencephalography (EEG) and event-related potential (ERP) are emerging as alternatives to traditional molecular and imaging markers. This paper aimed to review the literature on EEG and ERP markers in individuals with SCD. We analysed 30 studies that met our criteria, with 17 focusing on resting-state or cognitive task EEG, 11 on ERPs, and two on both EEG and ERP parameters. Typical spectral changes were indicative of EEG rhythm slowing and were associated with faster clinical progression, lower education levels, and abnormal cerebrospinal fluid biomarkers profiles. Some studies found no difference in ERP components between SCD subjects, controls, or MCI, while others reported lower amplitudes in the SCD group compared to controls. Further research is needed to explore the prognostic value of EEG and ERP in relation to molecular markers in individuals with SCD.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

Weakly supervised learning analysis of Aβ plaque distribution in the whole rat brain

Alzheimer's disease (AD) is a great challenge for the world and hardly to be cured, partly because of the lack of animal models that fully mimic pathological progress. Recently, a rat model exhibiting the most pathological symptoms of AD has been reported. However, high-resolution imaging and accurate quantification of beta-amyloid (Aβ) plaques in the whole rat brain have not been fulfilled due to substantial technical challenges. In this paper, a high-efficiency data analysis pipeline is proposed to quantify Aβ plaques in whole rat brain through several terabytes of image data acquired by a high-speed volumetric imaging approach we have developed previously. A novel segmentation framework applying a high-performance weakly supervised learning method which can dramatically reduce the human labeling consumption is described in this study. The effectiveness of our segmentation framework is validated with different metrics. The segmented Aβ plaques were mapped to a standard rat brain atlas for quantitative analysis of the Aβ distribution in each brain area. This pipeline may also be applied to the segmentation and accurate quantification of other non-specific morphology objects.

Association Between Hippocampal Volume and African Neuropsychology Memory Tests in Adult Individuals with Probable Alzheimer's Disease in Democratic Republic of Congo

BACKGROUND

Western studies indicate potential associations between hippocampal volume and memory in the trajectory of Alzheimer's disease (AD). However, limited availability of neuroimaging technology and neuropsychological tests appropriate for sub-Saharan African (SSA) countries makes it difficult to establish neuroanatomical associations of hippocampus and memory in this locale.

OBJECTIVE

This study examined hippocampal volumes and memory in healthy control (HC) and probable AD groups in the Democratic Republic of Congo (DRC).

METHODS

Forty-six subjects with probable AD and 29 HC subjects were screened using the Community Instrument for Dementia and the Alzheimer Questionnaire. Participants underwent neuroimaging in Kinshasa, DRC, and memory was evaluated using the African Neuropsychology Battery (ANB). Multiple linear regression was used to determine associations between hippocampal volumes and memory.

RESULTS

Patients with probable AD performed significantly worse than HCs on ANB memory measures, and exhibited greater cerebral atrophy, which was significantly pronounced in the medial temporal lobe region (hippocampus, entorhinal cortex). Both AD and HC subjects exhibited high rates of white matter hyperintensities compared to international base rate prevalence, which was significantly worse for probable AD. Both also exhibited elevated rates of microhemorrhages. Regression analysis demonstrated a significant association between hippocampal volume and ANB memory tests. Hippocampal atrophy discriminated probable AD from the HC group.

CONCLUSIONS

This study establishes the feasibility of conducting neuroimaging research in the SSA, demonstrates many known neuroimaging findings in probable AD patients hold up using culturally appropriate memory tasks, and suggest cardiovascular problems are a greater issue in SSA than in Western countries.

Diagnostic yield of diffusion-weighted brain MR imaging in patients with cognitive impairment: Large cohort study with 3,298 patients

Objective

There is a paucity of large cohort-based evidence regarding the need and added value of diffusion-weighted imaging (DWI) in patients attending outpatient clinic for cognitive impairment. We aimed to evaluate the diagnostic yield of DWI in patients attending outpatient clinic for cognitive impairment.

Materials and methods

This retrospective, observational, single-institution study included 3,298 consecutive patients (mean age ± SD, 71 years ± 10; 1,976 women) attending outpatient clinic for cognitive impairment with clinical dementia rating ≥ 0.5 who underwent brain MRI with DWI from January 2010 to February 2020. Diagnostic yield was defined as the proportion of patients in whom DWI supported the diagnosis that underlies cognitive impairment among all patients. Subgroup analyses were performed by age group and sex, and the Chi-square test was performed to compare the diagnostic yields between groups.

Results

The overall diagnostic yield of DWI in patients with cognitive impairment was 3.2% (106/3,298; 95% CI, 2.6–3.9%). The diagnostic yield was 2.5% (83/3,298) for acute or subacute infarct, which included recent small subcortical infarct for which the diagnostic yield was 1.6% (54/3,298). The diagnostic yield was 0.33% (11/3,298) for Creutzfeldt-Jakob disease (CJD), 0.15% (5/3,298) for transient global amnesia (TGA), 0.12% (4/3,298) for encephalitis and 0.09% (3/3,298) for lymphoma. There was a trend towards a higher diagnostic yield in the older age group with age ≥ 70 years old (3.6% vs 2.6%, P = .12). There was an incremental increase in the diagnostic yield from the age group 60–69 years (2.6%; 20/773) to 90–99 years (8.0%; 2/25).

Conclusion

Despite its low overall diagnostic yield, DWI supported the diagnosis of acute or subacute infarct, CJD, TGA, encephalitis and lymphoma that underlie cognitive impairment, and there was a trend towards a higher diagnostic yield in the older age group.

Detrimental effects of hypercortisolism on brain structure and related risk factors

Brain structural abnormalities are often observed on magnetic resonance imaging (MRI) scans of Cushing's syndrome patients, but the pathogenesis is not fully understood. To understand the relationship between brain structural abnormalities and potential risk factors in active Cushing's disease (CD) patients, a total of 101 treatment-naïve CD patients and 95 sex-, age- and education matched controls with non-functioning adenomas (NFA) underwent clinical evaluation and MRI investigation, and the relative risk factors were analyzed. 14 patients in sustained remission after transsphenoidal surgery were followed. Compared with the NFA subjects, the patients with CD had more cortical (P < 0.01) and subcortical atrophy (P < 0.01) and a higher prevalence of white matter hyperintensity (WMH) (P < 0.01). WMH severity in CD patients positively correlated with age (r = 0.532, P = 0.000), disease course (r = 0.257, P = 0.009), postprandial glucose (r = 0.278, P = 0.005), frequency of left ventricular hypertrophy (r = 0.398, P = 0.001) and hypothyroidism (r = 0.246, P = 0.014). The markers of cortical and subcortical atrophy (sylvian fissure ratio, bifrontal ratio, bicaudate ratio and third ventricle width) were positively associated with the progression of WMH in the CD patients. In the follow-up of 14 patients with CD, brain atrophy and WMH was partially reversible after correction of hypercortisolism. In conclusions, brain atrophy and WMH were more likely to appear in CD patients and were possibly partially reversible following correction of hypercortisolism.

Advantages and Pitfalls in Fluid Biomarkers for Diagnosis of Alzheimer's Disease

Alzheimer’s disease (AD) is a commonly occurring neurodegenerative disease in the advanced-age population, with a doubling of prevalence for each 5 years of age above 60 years. In the past two decades, there has been a sustained effort to find suitable biomarkers that may not only aide with the diagnosis of AD early in the disease process but also predict the onset of the disease in asymptomatic individuals. Current diagnostic evidence is supportive of some biomarker candidates isolated from cerebrospinal fluid (CSF), including amyloid beta peptide (Aβ), total tau (t-tau), and phosphorylated tau (p-tau) as being involved in the pathophysiology of AD. However, there are a few biomarkers that have been shown to be helpful, such as proteomic, inflammatory, oral, ocular and olfactory in the early detection of AD, especially in the individuals with mild cognitive impairment (MCI). To date, biomarkers are collected through invasive techniques, especially CSF from lumbar puncture; however, non-invasive (radio imaging) methods are used in practice to diagnose AD. In order to reduce invasive testing on the patients, present literature has highlighted the potential importance of biomarkers in blood to assist with diagnosing AD.

The CNS-specific proteoglycan, brevican, and its ADAMTS4-cleaved fragment show differential serological levels in Alzheimer's disease, other types of dementia and non-demented controls: A cross-sectional study

Evidence indicate that the brain-specific protein, brevican, is proteolytically cleaved during neurodegeneration, hence positioning fragments of brevican as potential blood biomarkers of neurodegenerative diseases, such as dementia. We aimed to develop two assays capable of detecting the brevican N-terminal (N-Brev) and the ADAMTS4-generated fragment (Brev-A), cleaved at Ser401, in serum and to perform a preliminary assessment of their diagnostic potential in dementias. Monoclonal antibodies against N-Brev and Brev-A were used to develop two ELISAs detecting each epitope. A comparison of brevican fragments in serum from individuals with AD (n = 28), other dementia (OD) (n = 41), and non-dementia-related memory complaints (NDCs) (n = 48) was conducted. Anti-N-Brev and anti-Brev-A antibodies selectively recognized their targets and dilution and spike recoveries were within limits of ±20%. Intra- and inter-assay CVs were below limits of 10% and 15%, respectively. For the N-Brev biomarker, serum from patients with OD showed significantly lower levels than those with AD (p = 0.05) and NDCs (p < 0.01). The opposite pattern was evident for Brev-A: serum levels in patients with OD were significantly higher than for AD (p = 0.04) and NDCs (p = 0.01). For both N-Brev and Brev-A, levels did not differ between AD and NDCs. The ratio of N-Brev/Brev-A resulted in increased significant differences between OD and AD (p < 0.01) and between OD and NDCs (p < 0.0001). The ratio discriminated between NDCs and OD (AUC: 0.75, 95% CI: 0.65-0.85, p < 0.0001) and between OD and AD (AUC: 0.72, 95% CI: 0.59-0.85, p < 0.01). In conclusion, we developed the first assays detecting the N-terminal of brevican as well as an ADAMTS4-cleaved fragment of brevican in blood. Differential levels of N-Brev and Brev-A between AD and OD allow for these biomarkers to possibly distinguish between different forms of dementias.

White matter and its relationship with cognition in subjective cognitive decline

INTRODUCTION

Subjective cognitive decline (SCD) is the earliest stage on the continuum toward Alzheimer's disease. This study examined (1) differences in white matter integrity between individuals with SCD and healthy control subjects and (2) how white matter integrity related to memory and executive function.

METHODS

Diffusion tensor imaging and neuropsychological assessment data were retrieved from the Alzheimer's Disease Neuroimaging Initiative database for 30 individuals with SCD and 44 control subjects.

RESULTS

Results revealed significantly lower white matter integrity in individuals with SCD relative to control subjects in widespread regions, including the bilateral corticospinal tracts, superior and inferior longitudinal fasciculi, fronto-occipital fasciculi, corpus callosum, forceps major and minor, hippocampi, anterior thalamic radiations, and the cerebellum. There was a widespread relationship between diffusion tensor imaging metrics and executive function in SCD, but not healthy control subjects, and no relationship with memory for either group.

DISCUSSION

Relatively lower white matter integrity in SCD may be a useful early biomarker for risk of future cognitive decline. Future research should better characterize the SCD group longitudinally and in individuals at risk for Alzheimer's disease.

Plasma Levels of Soluble AβPPβ as a Biomarker for Alzheimer's Disease with Dementia

Cost- and time-effective markers of Alzheimer's disease (AD), reliable and feasible at the population level are urgently needed. Soluble amyloid-β protein precursor β (sAβPPβ) in plasma has attracted scientific attention as a potential AD biomarker candidate. Here we report that plasma sAβPPβ levels in patients with AD dementia and typical for AD cerebrospinal fluid (CSF) biomarker profiles (N = 33) are significantly lower (p < 0.01) than those of cognitively healthy elderly individuals without AD (N = 39), while CSF sAβPPβ levels did not differ between the studied groups. This provides further evidence for the potential of sAβPPβ in plasma as an AD biomarker candidate.

Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias

Neurodegenerative dementias are highly complex disorders driven by vicious cycles of intersecting pathophysiologies. While most can be definitively diagnosed by the presence of disease-specific pathology in the brain at postmortem examination, clinical disease presentations often involve substantially overlapping cognitive, behavioral, and functional impairment profiles that hamper accurate diagnosis of the specific disease. As global demographics shift towards an aging population in developed countries, clinicians need more sensitive and specific diagnostic tools to appropriately diagnose, monitor, and treat neurodegenerative conditions. This review is intended as an overview of how modern proteomic techniques (liquid chromatography mass spectrometry (LC-MS/MS) and advanced capture-based technologies) may contribute to the discovery and establishment of better biofluid biomarkers for neurodegenerative disease, and the limitations of these techniques. The review highlights some of the more interesting technical innovations and common themes in the field but is not intended to be an exhaustive systematic review of studies to date. Finally, we discuss clear reporting principles that should be integrated into all studies going forward to ensure data is presented in sufficient detail to allow meaningful comparisons across studies.