Current Role for Biomarkers in Clinical Diagnosis of Alzheimer Disease and Frontotemporal Dementia

Early-onset Alzheimer's disease with depression as the first symptom: a case report with literature review

Background

Alzheimer's disease is a common neurodegenerative disease, and patients with early-onset Alzheimer's disease (onset age < 65 years) often have atypical symptoms, which are easily misdiagnosed and missed. Multimodality neuroimaging has become an important diagnostic and follow-up method for AD with its non-invasive and quantitative advantages.

Case presentation

We report a case of a 59-year-old female with a diagnosis of depression at the age of 50 after a 46-year-old onset and a 9-year follow-up observation, who developed cognitive dysfunction manifested by memory loss and disorientation at the age of 53, and eventually developed dementia. Combined with neuropsychological scales (MMSE and MOCA scores decreased year by year and finally reached the dementia criteria) and the application of multimodal imaging. MRI showed that the hippocampus atrophied year by year and the cerebral cortex was extensively atrophied. 18F-FDG PET image showed hypometabolism in right parietal lobes, bilateral frontal lobes, bilateral joint parieto-temporal areas, and bilateral posterior cingulate glucose metabolism. The 18F-AV45 PET image showed the diagnosis of early-onset Alzheimer's disease was confirmed by the presence of Aβ deposits in the cerebral cortex.

Conclusion

Early-onset Alzheimer's disease, which starts with depression, often has atypical symptoms and is prone to misdiagnosis. The combination of neuropsychological scales and neuroimaging examinations are good screening tools that can better assist in the early diagnosis of Alzheimer's disease. Graphical Abstract.

Investigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort

The World Health Organization recently defined hypertension and type 2 diabetes (T2D) as modifiable comorbidities leading to dementia and Alzheimer's disease. In the United States (US), hypertension and T2D are health disparities, with higher prevalence seen for Black and Hispanic minority groups compared to the majority White population. We hypothesized that elevated prevalence of hypertension and T2D risk factors in Black and Hispanic groups may be associated with dementia disparities. We interrogated this hypothesis using a cross-sectional analysis of participant data from the All of Us (AoU) Research Program, a large observational cohort study of US residents. The specific objectives of our study were: (1) to compare the prevalence of dementia, hypertension, and T2D in the AoU cohort to previously reported prevalence values for the US population, (2) to investigate the association of hypertension, T2D, and race/ethnicity with dementia, and (3) to investigate whether race/ethnicity modify the association of hypertension and T2D with dementia. AoU participants were recruited from 2018 to 2019 as part of the initial project cohort (R2019Q4R3). Participants aged 40-80 with electronic health records and demographic data (age, sex, race, and ethnicity) were included for analysis, yielding a final cohort of 125,637 individuals. AoU participants show similar prevalence of hypertension (32.1%) and T2D (13.9%) compared to the US population (32.0% and 10.5%, respectively); however, the prevalence of dementia for AoU participants (0.44%) is an order of magnitude lower than seen for the US population (5%). AoU participants with dementia show a higher prevalence of hypertension (81.6% vs. 31.9%) and T2D (45.9% vs. 11.4%) compared to non-dementia participants. Dominance analysis of a multivariable logistic regression model with dementia as the outcome shows that hypertension, age, and T2D have the strongest associations with dementia. Hispanic was the only race/ethnicity group that showed a significant association with dementia, and the association of sex with dementia was non-significant. The association of T2D with dementia is likely explained by concurrent hypertension, since > 90% of participants with T2D also had hypertension. Black race and Hispanic ethnicity interact with hypertension, but not T2D, to increase the odds of dementia. This study underscores the utility of the AoU participant cohort to study disease prevalence and risk factors. We do notice a lower participation of aged minorities and participants with dementia, revealing an opportunity for targeted engagement. Our results indicate that targeting hypertension should be a priority for risk factor modifications to reduce dementia incidence.

Biosensor approaches on the diagnosis of neurodegenerative diseases: Sensing the past to the future

Early diagnosis of neurodegeneration-oriented diseases that develop with the aging world is essential for improving the patient's living conditions as well as the treatment of the disease. Alzheimer's and Parkinson's diseases are prominent examples of neurodegeneration characterized by dementia leading to the death of nerve cells. The clinical diagnosis of these diseases only after the symptoms appear, delays the treatment process. Detection of biomarkers, which are distinctive molecules in biological fluids, involved in neurodegeneration processes, has the potential to allow early diagnosis of neurodegenerative diseases. Studies on biosensors, whose main responsibility is to detect the target analyte with high specificity, has gained momentum in recent years with the aim of high detection of potential biomarkers of neurodegeneration process. This study aims to provide an overview of neuro-biosensors developed on the basis of biomarkers identified in biological fluids for the diagnosis of neurodegenerative diseases such as Alzheimer's disease (AD), and Parkinson's disease (PD), and to provide an overview of the urgent needs in this field, emphasizing the importance of early diagnosis in the general lines of the neurodegeneration pathway. In this review, biosensor systems developed for the detection of biomarkers of neurodegenerative diseases, especially in the last 5 years, are discussed.

Generating diagnostic profiles of cognitive decline and dementia using magnetoencephalography

Accurate identification of the underlying cause(s) of cognitive decline and dementia is challenging due to significant symptomatic overlap between subtypes. This study presents a multi-class classification framework for subjects with subjective cognitive decline, mild cognitive impairment, Alzheimer's disease, dementia with Lewy bodies, fronto-temporal dementia and cognitive decline due to psychiatric illness, trained on source-localized resting-state magnetoencephalography data. Diagnostic profiles, describing probability estimates for each of the 6 diagnoses, were assigned to individual subjects. A balanced accuracy rate of 41% and multi-class area under the curve value of 0.75 were obtained for 6-class classification. Classification primarily depended on posterior relative delta, theta and beta power and amplitude-based functional connectivity in the beta and gamma frequency band. Dementia with Lewy bodies (sensitivity: 100%, precision: 20%) and Alzheimer's disease subjects (sensitivity: 51%, precision: 90%) could be classified most accurately. Fronto-temporal dementia subjects (sensitivity: 11%, precision: 3%) were most frequently misclassified. Magnetoencephalography biomarkers hold promise to increase diagnostic accuracy in a noninvasive manner. Diagnostic profiles could provide an intuitive tool to clinicians and may facilitate implementation of the classifier in the memory clinic.

Ginsenosides attenuate bioenergetics and morphology of mitochondria in cultured PC12 cells under the insult of amyloid beta-peptide

BACKGROUND

Mitochondrial dysfunction is one of the significant reasons for Alzheimer's disease (AD). Ginsenosides, natural molecules extracted from Panax ginseng, have been demonstrated to exert essential neuroprotective functions, which can ascribe to its anti-oxidative effect, enhancing central metabolism and improving mitochondrial function. However, a comprehensive analysis of cellular mitochondrial bioenergetics after ginsenoside treatment under Aβ-oxidative stress is missing.

METHODS

The antioxidant activities of ginsenoside Rb1, Rd, Re, Rg1 were compared by measuring the cell survival and reactive oxygen species (ROS) formation. Next, the protective effects of ginsenosides of mitochondrial bioenergetics were examined by measuring oxygen consumption rate (OCR) in PC12 cells under Aβ-oxidative stress with an extracellular flux analyzer. Meanwhile, mitochondrial membrane potential (MMP) and mitochondrial dynamics were evaluated by confocal laser scanning microscopy.

RESULTS

Ginsenoside Rg1 possessed the strongest anti-oxidative property, and which therefore provided the best protective function to PC12 cells under the Aβ oxidative stress by increasing ATP production to 3 folds, spare capacity to 2 folds, maximal respiration to 2 folds and non-mitochondrial respiration to 1.5 folds, as compared to Aβ cell model. Furthermore, ginsenoside Rg1 enhanced MMP and mitochondrial interconnectivity, and simultaneously reduced mitochondrial circularity.

CONCLUSION

In the present study, these results demonstrated that ginsenoside Rg1 could be the best natural compound, as compared with other ginsenosides, by modulating the OCR of cultured PC12 cells during oxidative phosphorylation, in regulating MMP and in improving mitochondria dynamics under Aβ-induced oxidative stress.

National Dementia BioBank: A Strategy for the Diagnosis and Study of Neurodegenerative Diseases in México

We recently developed the National Dementia Biobank in México (BioBanco Nacional de Demencias, BND) as a unit for diagnosis, research, and tissue transfer for research purposes. BND is associated with the Facultad de Estudios Superiores Cuautitlán, Universidad Nacional Autónoma de Mexico (UNAM), Mexico. The donation of fluids, brain, and other organs of deceased donors is crucial for understanding the underlying mechanisms of neurodegenerative diseases and for the development of successful treatment. Our laboratory research focuses on 1) analysis of the molecular processing of the proteins involved in those neurodegenerative diseases termed tauopathies and 2) the search for biomarkers for the non-invasive and early diagnosis of Alzheimer's disease.

Relationship Between General Cognition, Visual Assessed Cortical Atrophy, and Cerebrospinal Fluid Biomarkers in Alzheimer's Disease: A Cross-Sectional Study from a Chinese PUMCH Cohort

BACKGROUND

Cerebrospinal fluid (CSF) biomarkers are widely accepted as manifestations of Alzheimer's disease (AD) pathogenesis and incorporated into biological definition of AD. However, the correlations between CSF and other biomarkers such as neuroimaging and neuropsychiatric evaluation are complicated and inconsistent.

OBJECTIVE

We aimed to better interpreting CSF biomarkers results accompanying with other indexes in improving accurate diagnosis of AD.

METHODS

112 AD patients and 30 cognitive normal controls were selected. Commercial accessible ELISA kits were introduced for measurement of CSF t-tau, p-tau181, Aβ1-42, and NfL based on standard protocol. MRI examinations were performed using a 3-T MRI scanner and visual rating scales including medial temporal atrophy score and Koedam's scale were used to evaluate medial temporal atrophy and posterior region atrophy.

RESULTS

CSF biomarkers' profile including decreased concentration of Aβ1-42, increased concentration of t-tau, p-tau181, t-tau/Aβ 1-42, and NfL were diagnostic between AD and control. CSF biomarkers profile was not influenced by the APOE genotype. Increased concentration of t-tau and NfL, as well as ratio of t-tau/Aβ 1-42 were related to decrease of Mini-Mental State Examination (MMSE) score while concentration of Aβ1-42 not. Visual assessed cortical atrophy was related to MMSE score, but most of the CSF biomarkers were not related to atrophy, except that increased concentration of p-tau181 was significantly associated with atrophy of posterior cortical region.

CONCLUSION

Our results supported CSF biomarkers were helpful in diagnosis of AD. However, CSF biomarkers were cross-sectional reflection of pathogenesis, which did not correlate well with clinical progression. CSF biomarkers should be interpreted in combination with MRI and cognitive evaluation in clinical use.

Using diffusion tensor imaging to detect cortical changes in fronto-temporal dementia subtypes

Fronto-temporal dementia (FTD) is a common type of presenile dementia, characterized by a heterogeneous clinical presentation that includes three main subtypes: behavioural-variant FTD, non-fluent/agrammatic variant primary progressive aphasia and semantic variant PPA. To better understand the FTD subtypes and develop more specific treatments, correct diagnosis is essential. This study aimed to test the discrimination power of a novel set of cortical Diffusion Tensor Imaging measures (DTI), on FTD subtypes. A total of 96 subjects with FTD and 84 healthy subjects (HS) were included in the study. A “selection cohort” was used to determine the set of features (measurements) and to use them to select the “best” machine learning classifier from a range of seven main models. The selected classifier was trained on a “training cohort” and tested on a third cohort (“test cohort”). The classifier was used to assess the classification power for binary (HS vs. FTD), and multiclass (HS and FTD subtypes) classification problems. In the binary classification, one of the new DTI features obtained the highest accuracy (85%) as a single feature, and when it was combined with other DTI features and two other common clinical measures (grey matter fraction and MMSE), obtained an accuracy of 88%. The new DTI features can distinguish between HS and FTD subgroups with an accuracy of 76%. These results suggest that DTI measures could support differential diagnosis in a clinical setting, potentially improve efficacy of new innovative drug treatments through effective patient selection, stratification and measurement of outcomes.

Analysis of Tau-441 protein in clinical samples using rGO/AuNP nanocomposite-supported disposable impedimetric neuro-biosensing platform: Towards Alzheimer's disease detection

Changes in isoforms of Tau protein, which are critical for microtubule functioning, are accepted as being responsible for diseases characterized by dementia, in particular Alzheimer's disease (AD). In this comprehensive study, a single-use neuro-biosensing probe for the determination of Tau-441 protein was developed by utilizing the power of nanocomposites consisting of reduced graphene oxide (rGO) and gold nanoparticles (AuNP) using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The nanocomposite surface (rGO-AuNP) was modified with 11-mercaptoundecanoic acid (11-MUA) act as covalent anchorer to increase the sensitivity of the assay. Surface coverage value and pinhole ratio were calculated using EIS data. Kramers-kronig data, which helps to interpret instrumental errors, are also calculated. The immunoreaction of Tau-441 with anti-Tau was monitored simultaneously with Single Frequency Impedance (SFI). The changes in surface morphology were evaluated with scanning electron microscopy (SEM), atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR). The designed immunosensor showed a linear response within the concentration range of 1-500 pg/mL for the target analyte Tau-441 and the limit of detection was found to be 0.091 pg/mL. The promising point of the study is that this neuro-biosensor system can capture the Tau-441 target protein in both serum fluid and cerebrospinal fluid (CSF) samples with recoveries ranging from 96% to 108%.

Correlation Between Hippocampal Volume and Autobiographical Memory Depending on Retrieval Frequency in Healthy Individuals and Patients with Alzheimer's Disease

The hippocampus plays an indispensable role in episodic memory, particularly during the consolidation process. However, its precise role in retrieval of episodic memory is still ambiguous. In this study, we investigated the correlation of hippocampal morphometry and the performance in an autobiographical memory task in 27 healthy controls and 24 patients suffering from Alzheimer's disease (AD). Most importantly, correlations were defined separately and comparatively for memory contents with different retrieval frequency in the past. In healthy subjects, memory performance for seldom retrieved autobiographical events was significantly associated with gray matter density in the bilateral hippocampus, whereas this correlation was not present for events with high retrieval frequency. This pattern of findings confirms that retrieval frequency plays a critical role in the consolidation of episodic autobiographical memories, thereby making them more independent of the hippocampal system. In AD patients, on the other hand, successful memory retrieval appeared to be related to hippocampal morphometry irrespective of the contents' retrieval frequency, comprising events with high retrieval frequency, too. The observed differences between patients and control subjects suggest that AD-related neurodegeneration not only impairs the function, but also decreases the functional specialization of the hippocampal memory system, which, thus, may be considered as marker for AD.

Education modulates brain maintenance in presymptomatic frontotemporal dementia

OBJECTIVE

Cognitively engaging lifestyles have been associated with reduced risk of conversion to dementia. Multiple mechanisms have been advocated, including increased brain volumes (ie, brain reserve) and reduced disease progression (ie, brain maintenance). In cross-sectional studies of presymptomatic frontotemporal dementia (FTD), higher education has been related to increased grey matter volume. Here, we examine the effect of education on grey matter loss over time.

METHODS

Two-hundred twenty-nine subjects at-risk of carrying a pathogenic mutation leading to FTD underwent longitudinal cognitive assessment and T1-weighted MRI at baseline and at 1 year follow-up. The first principal component score of the graph-Laplacian Principal Component Analysis on 112 grey matter region-of-interest volumes was used to summarise the grey matter volume (GMV). The effects of education on cognitive performances and GMV at baseline and on the change between 1 year follow-up and baseline (slope) were tested by Structural Equation Modelling.

RESULTS

Highly educated at-risk subjects had better cognition and higher grey matter volume at baseline; moreover, higher educational attainment was associated with slower loss of grey matter over time in mutation carriers.

CONCLUSIONS

This longitudinal study demonstrates that even in presence of ongoing pathological processes, education may facilitate both brain reserve and brain maintenance in the presymptomatic phase of genetic FTD.

Young-onset dementia: scoping review of key pointers to diagnostic accuracy

BACKGROUND

Routine psychiatric assessments tailored to older patients are often insufficient to identify the complexity of presentation in younger patients with dementia. Significant overlap between psychiatric disorders and neurodegenerative disease means that high rates of prior incorrect psychiatric diagnosis are common. Long delays to diagnosis, misdiagnosis and lack of knowledge from professionals are key concerns. No specific practice guidelines exist for diagnosis of young-onset dementia (YOD).

AIMS

The review evaluates the current evidence about best practice in diagnosis to guide thorough assessment of the complex presentations of YOD with a view to upskilling professionals in the field.

METHOD

A comprehensive search of the literature adopting a scoping review methodology was conducted regarding essential elements of diagnosis in YOD, over and above those in current diagnostic criteria for disease subtypes. This methodology was chosen because research in this area is sparse and not amenable to a traditional systematic review.

RESULTS

The quality of evidence identified is variable with the majority provided from expert opinion and evidence is lacking on some topics. Evidence appears weighted towards diagnosis in frontotemporal dementia and its subtypes and young-onset Alzheimer's disease.

CONCLUSIONS

The literature demonstrates that a clinically rigorous and systematic approach is necessary in order to avoid mis- or underdiagnosis for younger people. The advent of new disease-modifying treatments necessitates clinicians in the field to improve knowledge of new imaging techniques and genetics, with the goal of improving training and practice, and highlights the need for quality indicators and alignment of diagnostic procedures across clinical settings.

DECLARATION OF INTEREST

None.

[Big data and artificial intelligence for diagnostic decision support in atypical dementia]

The differential diagnosis of atypical dementia remains difficult. The use of positron emission tomography (PET) still represents the gold standard for imaging diagnostics. According to the current evidence, however, magnetic resonance imaging (MRI) is almost equal to fluorodeoxyglucose (FDG)-PET, but only when using new big data and machine learning methods. In cases of atypical dementia, especially in younger patients and for follow-up, MRI is preferable to computed tomography (CT). In the clinical routine, promising MRI procedures are e. g. the automated volumetry of anatomical 3D images, as well as a non-contrast-enhanced MRI perfusion method, called arterial spin labeling (ASL). Because of the rapidly growing amount of biomarker data, there is a need for computer-aided big data analyses and artificial intelligence. Based on fast analyses of the diverse and rapidly increasing amount of clinical, imaging, epidemiological, molecular genetic and economic data, new knowledge on the pathogenesis, prevention and treatment can be generated. Technical availability, homogenization of the underlying data and the availability of large reference data are the basis for the widespread establishment of promising analytical methods.

Functional Connectivity Changes in Behavioral, Semantic, and Nonfluent Variants of Frontotemporal Dementia

Frontotemporal dementia (FTD) affects behavior, language, and personality. This study aims to explore functional connectivity changes in three FTD variants: behavioral (bvFTD), semantic (svPPA), and nonfluent variant (nfvPPA). Seventy-six patients diagnosed with FTD by international criteria and thirty-two controls were investigated. Functional connectivity from resting functional magnetic resonance imaging (fMRI) was estimated for the whole brain. Two types of analysis were done: network basic statistic and topological measures by graph theory. Several hubs in the limbic system and basal ganglia were compromised in the behavioral variant apart from frontal networks. Nonfluent variants showed a major disconnection with respect to the behavioral variant in operculum and parietal inferior. The global efficiency had lower coefficients in nonfluent variants than behavioral variants and controls. Our results support an extensive disconnection among frontal, limbic, basal ganglia, and parietal hubs.