Amyloid brain-dedicated PET images can diagnose Alzheimer's pathology with Centiloid Scale.

PURPOSE: To evaluate whether the Centiloid Scale may be used to diagnose Alzheimer's Disease (AD) pathology effectively with the only use of amyloid PET imaging modality from a brain-dedicated PET scanner. METHODS: This study included 26 patients with amyloid PET images with 3 different radiotracers. All patients were acquired both on a PET/CT and a brain-dedicated PET scanner (CareMiBrain, CMB), from which 4 different reconstructions were implemented. A new pipeline was proposed and used for the PET image analysis based on the original Centiloid Scale processing pipeline, but with only PET images. The Youden's Index was employed to calculate the optimal cutoffs for diagnosis and evaluated by the AUC, accuracy, precision, and recall metrics. RESULTS: The Centiloid Scale (CL) processing pipeline was validated with and without the use of MR images. The CL cutoffs for AD pathology diagnosis on the PET/CT and the 4 CMB reconstructions were 34.4 ±â€¯2.2, 43.5 ±â€¯3.5, 51.9 ±â€¯12.5, 57.5 ±â€¯6.8 and 41.8 ±â€¯1.2 respectively. Overall, for these cutoffs all metrics obtained the maximum score. CONCLUSION: The Centiloid scale applied to PET images allows for AD pathology diagnosis. The CMB scanner can be used with the Centiloid scale to automatically assist in the diagnosis of AD pathology, relieving the large burden of neurodegenerative diseases on a traditional PET/CT.

Relationship between neuroimaging and emotion recognition in mild cognitive impairment patients.

OBJECTIVE: Dementia is a major public health problem with high needs for early detection, efficient treatment, and prognosis evaluation. Social cognition impairment could be an early dementia indicator and can be assessed with emotion recognition evaluation tests. The purpose of this study is to investigate the link between different brain imaging modalities and cognitive status in Mild Cognitive Impairment (MCI) patients, with the goal of uncovering potential physiopathological mechanisms based on social cognition performance. METHODS: The relationship between the Reading the Mind in the Eyes Test (RMET) and some clinical and biochemical variables ([18 F]FDG PET-CT and anatomical MR parameters, neuropsychological evaluation, and CSF biomarkers) was studied in 166 patients with MCI by using a correlational approach. RESULTS: The RMET correlated with neuropsychological variables, as well as with structural and functional brain parameters obtained from the MR and FDG-PET imaging evaluation. However, significant correlations between the RMET and CSF biomarkers were not found. DISCUSSION: Different neuroimaging parameters were found to be related to an emotion recognition task in MCI. This analysis identified potential minimally-invasive biomarkers providing some knowledge about the physiopathological mechanisms in MCI.

Early Alzheimer's Disease Screening Approach Using Plasma Biomarkers.

Alzheimer's disease (AD) is the most prevalent dementia, but it shows similar initial symptoms to other neurocognitive diseases (Lewy body disease (LBD) and frontotemporal dementia (FTD)). Thus, the identification of reliable AD plasma biomarkers is required. The aim of this work is to evaluate the use of a few plasma biomarkers to develop an early and specific AD screening method. Plasma p-Tau181, neurofilament light (NfL), and glial fibrillary acid protein (GFAP) were determined by Single Molecule Assay (SIMOA® Quanterix, Billerica, MA, USA) in patients with mild cognitive impairment due to AD (MCI-AD, n = 50), AD dementia (n = 10), FTD (n = 20), LBD (n = 5), and subjective cognitive impairment (SCI (n = 21)). Plasma p-Tau181 and GFAP showed the highest levels in AD dementia, and significant correlations with clinical AD characteristics; meanwhile, NfL showed the highest levels in FTD, but no significant correlations with AD. The partial least squares (PLS) diagnosis model developed between the AD and SCI groups showed good accuracy with a receiver operating characteristic (ROC) area under curve (AUC) of 0.935 (CI 95% 0.87-0.98), sensitivity of 86%, and specificity of 88%. In a first screen, NfL plasma levels could identify FTD patients among subjects with cognitive impairment. Then, the developed PLS model including p-Tau181 and GFAP levels could identify AD patients, constituting a simple, early, and specific diagnosis approach.

Assessment of COVID-19 lockdown effect on early Alzheimer Disease progression.

INTRODUCTION: Recently, many aspects of daily life have changed due to the COVID-19 pandemic. Patients with Alzheimer Disease (AD) could be more vulnerable to those daily life changes as experts expected. Mainly, the lockdown involved reduced social contact and cognitive stimulation. So, it could affect the AD expression, increasing the patients' disabilities development. OBJECTIVE: The aim of this study is to evaluate the effect of COVID-19 lockdown on cognitive impairment progression in early AD patients. METHODOLOGY: The participants were patients with mild cognitive impairment due to AD (MCI-AD) from the Neurology Unit (La Fe Hospital), who were neuropsychologically evaluated (cognitive impairment, daily activity tests) twice over 2 years. They were classified into a case group (n = 21), evaluated before and after lockdown condition, and a control group (n = 20), evaluated entirely before the lockdown condition. RESULTS: All the participants showed increasing cognitive impairment and functional deterioration over the 2-year period of evaluation (p < 0.05). However, a faster worsening was not observed as a consequence of the COVID-19 pandemic and the lockdown condition. In fact, the statistical significance observed between the two study groups for daily life activities showed that the worsening was even lesser in the group evaluated under the lockdown condition. CONCLUSION: Medium-term effects of COVID-19 lockdown could not involve an acceleration of the cognitive decline in MCI-AD patients in a 2-year evaluation period. In addition, the least worsening observed for daily living activities in the case group was probably due to the change in routines. Therefore, the common assumption of cognitive worsening of AD progression due to the lockdown in comparison with normal disease progression was not demonstrated in this study, at least for MCI-AD cases. However, more longitudinal studies are required to evaluate long-term effects in these patients.

Assessment of Plasma and Cerebrospinal Fluid Biomarkers in Different Stages of Alzheimer's Disease and Frontotemporal Dementia.

Alzheimer's disease (AD) is the primary type of dementia, followed by frontotemporal lobar degeneration (FTLD). They share some clinical characteristics, mainly at the early stages. So, the identification of early, specific, and minimally invasive biomarkers is required. In this study, some plasma biomarkers (Amyloid ß42, p-Tau181, t-Tau, neurofilament light (NfL), TAR DNA-binding protein 43 (TDP-43)) were determined by single molecule array technology (SIMOA®) in control subjects (n = 22), mild cognitive impairment due to AD (MCI-AD, n = 33), mild dementia due to AD (n = 12), and FTLD (n = 11) patients. The correlations between plasma and cerebrospinal fluid (CSF) levels and the accuracy of plasma biomarkers for AD early diagnosis and discriminating from FTLD were analyzed. As result, plasma p-Tau181 and NfL levels correlated with the corresponding CSF levels. Additionally, plasma p-Tau181 showed good accuracy for distinguishing between the controls and AD, as well as discriminating between AD and FTLD. Moreover, plasma NfL could discriminate dementia-AD vs. controls, FTLD vs. controls, and MCI-AD vs. dementia-AD. Therefore, the determination of these biomarkers in plasma is potentially helpful in AD spectrum diagnosis, but also discriminating from FTLD. In addition, the accessibility of these potential early and specific biomarkers may be useful for AD screening protocols in the future.

Clinical usefulness of cerebrospinal fluid biomarkers in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a complex disease that shares clinical features with other dementias. It is important to establish a specific and reliable diagnosis. Nowadays, AD diagnosis is based on cerebrospinal fluid (CSF) biomarkers. However, the corresponding cut-offs differ amongst studies. This study aims to evaluate the CSF biomarkers in the AD differential diagnosis. METHODS: Clinical relevant biomarkers (amyloid ß42 (Aß42), t-Tau, p-Tau, amyloid ß40 (Aß40), neurofilament light chain (NfL)) were determined in CSF samples from participants classified as AD (n = 124) and non-AD (n = 148) patients from the Neurology Unit. They were included and evaluated consecutively (August 2018-October 2020). The clinical utility of these biomarkers was evaluated by AUC-ROC curves and the corresponding cut-off points were defined. RESULTS: The results showed satisfactory accuracy (AUC-ROC 0.91 for Aß42, 0.890 for t-Tau and 0.933 for p-Tau); whilst Aß40 and NfL did not show good discriminatory capacity (AUC-ROC 0.557 and 0.738, respectively). The ratios Aß42/Aß40 and t-Tau/Aß42 improved the diagnosis indices of each individual biomarker, with AUC-ROC of 0.980 and 0.971, respectively. Also, elevated levels of NfL were found in the frontotemporal dementia group compared with the other participant groups. CONCLUSIONS: The ratio Aß42/Aß40 showed the highest discriminating capacity between AD and non-AD patients and might be useful in clinical practice. Regarding NfL, it is not a specific biomarker for AD; however, it might be helpful for the differential diagnosis of frontotemporal dementia. Nevertheless, further analysis in an external cohort is required in order to validate these results.

Discordant Amyloid Status Diagnosis in Alzheimer's Disease.

INTRODUCTION: Early and accurate Alzheimer's disease (AD) diagnosis has evolved in recent years by the use of specific methods for detecting its histopathological features in concrete cases. Currently, biomarkers in cerebrospinal fluid (CSF) and imaging techniques (amyloid PET) are the most used specific methods. However, some results between both methods are discrepant. Therefore, an evaluation of these discrepant cases is required. OBJECTIVE: The aim of this work is to analyze the characteristics of cases showing discrepancies between methods for detecting amyloid pathology. METHODOLOGY: Patients from the Neurology Department of La Fe Hospital (n = 82) were diagnosed using both methods (CSF biomarkers and amyloid-PET). Statistical analyses were performed using logistic regression, and sex and age were included as covariables. Additionally, results of standard neuropsychological evaluations were taken into account in our analyses. RESULTS: The comparison between CSF biomarker (Aß42) and amyloid PET results showed that around 18% of cases were discrepant-mainly CFS-negative and PET-positive cases had CSF levels close to the cut-off point. In addition, a correlation between the episodic memory test and CSF biomarkers levels was observed. However, the same results were not obtained for other neuropsychological domains. In general, CSF- and PET-discrepant cases showed altered episodic memory in around 66% of cases, while 33% showed normal performance. CONCLUSIONS: In common clinical practice at tertiary memory centers, result discrepancies between tests of amyloid status are far more common than expected. However, episodic memory tests remain an important support method for AD diagnosis, especially in cases with discrepant results between amyloid PET and CSF biomarkers.

Plasma Lipidomics Approach in Early and Specific Alzheimer's Disease Diagnosis.

BACKGROUND: The brain is rich in lipid content, so a physiopathological pathway in Alzheimer's disease (AD) could be related to lipid metabolism impairment. The study of lipid profiles in plasma samples could help in the identification of early AD changes and new potential biomarkers. METHODS: An untargeted lipidomic analysis was carried out in plasma samples from preclinical AD (n = 11), mild cognitive impairment-AD (MCI-AD) (n = 31), and healthy (n = 20) participants. Variables were identified by means of two complementary methods, and lipid families' profiles were studied. Then, a targeted analysis was carried out for some identified lipids. RESULTS: Statistically significant differences were obtained for the diglycerol (DG), lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC), monoglyceride (MG), and sphingomyelin (SM) families as well as for monounsaturated (MUFAs) lipids, among the participant groups. In addition, statistically significant differences in the levels of lipid families (ceramides (Cer), LPE, LPC, MG, and SM) were observed between the preclinical AD and healthy groups, while statistically significant differences in the levels of DG, MG, and PE were observed between the MCI-AD and healthy groups. In addition, 18:1 LPE showed statistically significant differences in the targeted analysis between early AD (preclinical and MCI) and healthy participants. CONCLUSION: The different plasma lipid profiles could be useful in the early and minimally invasive detection of AD. Among the lipid families, relevant results were obtained from DGs, LPEs, LPCs, MGs, and SMs. Specifically, MGs could be potentially useful in AD detection; while LPEs, LPCs, and SM seem to be more related to the preclinical stage, while DGs are more related to the MCI stage. Specifically, 18:1 LPE showed a potential utility as an AD biomarker.

Artificial Intelligence on FDG PET Images Identifies Mild Cognitive Impairment Patients with Neurodegenerative Disease.

The purpose of this project is to develop and validate a Deep Learning (DL) FDG PET imaging algorithm able to identify patients with any neurodegenerative diseases (Alzheimer's Disease (AD), Frontotemporal Degeneration (FTD) or Dementia with Lewy Bodies (DLB)) among patients with Mild Cognitive Impairment (MCI). A 3D Convolutional neural network was trained using images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The ADNI dataset used for the model training and testing consisted of 822 subjects (472 AD and 350 MCI). The validation was performed on an independent dataset from La Fe University and Polytechnic Hospital. This dataset contained 90 subjects with MCI, 71 of them developed a neurodegenerative disease (64 AD, 4 FTD and 3 DLB) while 19 did not associate any neurodegenerative disease. The model had 79% accuracy, 88% sensitivity and 71% specificity in the identification of patients with neurodegenerative diseases tested on the 10% ADNI dataset, achieving an area under the receiver operating characteristic curve (AUC) of 0.90. On the external validation, the model preserved 80% balanced accuracy, 75% sensitivity, 84% specificity and 0.86 AUC. This binary classifier model based on FDG PET images allows the early prediction of neurodegenerative diseases in MCI patients in standard clinical settings with an overall 80% classification balanced accuracy.

Novel Ultrasensitive Detection Technologies for the Identification of Early and Minimally Invasive Alzheimer's Disease Blood Biomarkers.

BACKGROUND: Single molecule array (SIMOA) and other ultrasensitive detection technologies have allowed the determination of blood-based biomarkers of Alzheimer's disease (AD) for diagnosis and monitoring, thereby opening up a promising field of research. OBJECTIVE: To review the published bibliography on plasma biomarkers in AD using new ultrasensitive techniques. METHODS: A systematic review of the PubMed database was carried out to identify reports on the use of blood-based ultrasensitive technology to identify biomarkers for AD. RESULTS: Based on this search, 86 works were included and classified according to the biomarker determined. First, plasma amyloid-ß showed satisfactory accuracy as an AD biomarker in patients with a high risk of developing dementia. Second, plasma t-Tau displayed good sensitivity in detecting different neurodegenerative diseases. Third, plasma p-Tau was highly specific for AD. Fourth, plasma NfL was highly sensitive for distinguishing between patients with neurodegenerative diseases and healthy controls. In general, the simultaneous determination of several biomarkers facilitated greater accuracy in diagnosing AD (Aß42/Aß40, p-Tau181/217). CONCLUSION: The recent development of ultrasensitive technology allows the determination of blood-based biomarkers with high sensitivity, thus facilitating the early detection of AD through the analysis of easily obtained biological samples. In short, as a result of this knowledge, pre-symptomatic and early AD diagnosis may be possible, and the recruitment process for future clinical trials could be more precise. However, further studies are necessary to standardize levels of blood-based biomarkers in the general population and thus achieve reproducible results among different laboratories.

Epigenomics and Lipidomics Integration in Alzheimer Disease: Pathways Involved in Early Stages.

BACKGROUND: Alzheimer Disease (AD) is the most prevalent dementia. However, the physiopathological mechanisms involved in its development are unclear. In this sense, a multi-omics approach could provide some progress. METHODS: Epigenomic and lipidomic analysis were carried out in plasma samples from patients with mild cognitive impairment (MCI) due to AD (n = 22), and healthy controls (n = 5). Then, omics integration between microRNAs (miRNAs) and lipids was performed by Sparse Partial Least Squares (s-PLS) regression and target genes for the selected miRNAs were identified. RESULTS: 25 miRNAs and 25 lipids with higher loadings in the sPLS regression were selected. Lipids from phosphatidylethanolamines (PE), lysophosphatidylcholines (LPC), ceramides, phosphatidylcholines (PC), triglycerides (TG) and several long chain fatty acids families were identified as differentially expressed in AD. Among them, several fatty acids showed strong positive correlations with miRNAs studied. In fact, these miRNAs regulated genes implied in fatty acids metabolism, as elongation of very long-chain fatty acids (ELOVL), and fatty acid desaturases (FADs). CONCLUSIONS: The lipidomic-epigenomic integration showed that several lipids and miRNAs were differentially expressed in AD, being the fatty acids mechanisms potentially involved in the disease development. However, further work about targeted analysis should be carried out in a larger cohort, in order to validate these preliminary results and study the proposed pathways in detail.

Assessment of apolipoprotein E genotype for ß-amyloid status prediction.

BACKGROUND: Apolipoprotein E (ApoE) is the major genetic risk factor for sporadic Alzheimer's Disease (AD). Some studies showed a relationship between ApoE4 genotype and the cerebrospinal fluid (CSF) biomarkers (ß-amyloid42, p-Tau, t-Tau), as well as with cognitive status. In this sense, it could be interesting to develop an approach to establish amyloid status in a minimally invasive way. METHODS: The present study assessed the ApoE genotype in different participant groups (mild cognitive impairment due to AD (MCI-AD), mild/moderate dementia due to AD, MCI not due to AD (MCI not AD), other neurological diseases, healthy participants) (n = 342). RESULTS: As expected, the ApoE4 allele was more prevalent in AD patients, characterized by impairment in CSF ß-amyloid42 levels (Aß +), than in the other groups (Aß -). In this sense, ApoE4-carrier subjects showed lower CSF levels for ß-amyloid42 and higher CSF levels for t-Tau and p-Tau. From this, a multivariate model to predict Aß status was developed by means of partial least square analysis (PLS) and predictive variables (ApoE genotype, cognitive score, sex, age). This model showed suitable AUC-ROC 0.792 (95% CI, 0.744-0.840) and predictive negative value (81.6%). CONCLUSION: ApoE genotype could be useful in detecting CSF ß-amyloid42 impairment associated with early AD development.

Assessment of Screening Approach in Early and Differential Alzheimer's Disease Diagnosis.

BACKGROUND: Alzheimer's disease (AD) is the leading cause of dementia in the elderly population. Currently, diagnosis is based on invasive and expensive techniques, so there is a growing need to look for other possible tests, as well as carry out clinical validation. Studies from the literature showed potential diagnosis models, including some AD risk factors (age, gender, ApoE-ε4 genotype) and other variables (biomarkers levels, neuroimaging). Specifically, a recent model was performed from lipid peroxidation compounds in plasma samples to identify patients with early AD. However, there is a lack of studies about clinical validation of these preliminary diagnosis models. METHODS: Plasma samples from participants classified into AD (n = 61), non-AD (n = 17), and healthy (n = 44) were analyzed. In fact, lipid peroxidation compounds were determined by liquid chromatography and mass spectrometry. Then, a previously developed diagnosis model was clinically validated, evaluating some diagnosis indexes. RESULTS: The validation of the preliminary diagnosis model showed satisfactory diagnosis indexes (accuracy 77%, sensitivity 89%, specificity 61%, diagnostic odds ratio 12.5, positive predictive value 76%). Next, a useful screening tool, including the ApoE genotype, was developed, identifying patients with a higher risk of developing AD and improving the corresponding diagnosis indexes (accuracy 82%, sensitivity 81%, specificity 85%, diagnostic odds ratio 23.2, positive predictive value 90.5%). CONCLUSION: A new screening approach could improve the early, minimally invasive, and differential AD diagnosis in the general population.

Lipid Peroxidation Assessment in Preclinical Alzheimer Disease Diagnosis.

BACKGROUND: Alzheimer disease (AD) is an increasingly common neurodegenerative disease, especially in countries with aging populations. Its diagnosis is complex and is usually carried out in advanced stages of the disease. In addition, lipids and oxidative stress have been related to AD since the earliest stages. A diagnosis in the initial or preclinical stages of the disease could help in a more effective action of the treatments. METHODS: Isoprostanoid biomarkers were determined in plasma samples from preclinical AD participants (n = 12) and healthy controls (n = 31) by chromatography and mass spectrometry (UPLC-MS/MS). Participants were accurately classified according to cerebrospinal fluid (CSF) biomarkers and neuropsychological examination. RESULTS: Isoprostanoid levels did not show differences between groups. However, some of them correlated with CSF biomarkers (t-tau, p-tau) and with cognitive decline. In addition, a panel including 10 biomarkers showed an area under curve (AUC) of 0.96 (0.903-1) and a validation AUC of 0.90 in preclinical AD prediction. CONCLUSIONS: Plasma isoprostanoids could be useful biomarkers in preclinical diagnosis for AD. However, these results would require a further validation with an external cohort.

Functional and structural changes in the visual pathway in multiple sclerosis.

INTRODUCTION: Multiple sclerosis (MS) is a heterogeneous disease with an unpredictable course. Visual pathway is a target of the disease and may reflect mechanisms that lead to disability. Structural and functional changes in the visual pathway may be studied by noninvasive techniques such as optical coherence tomography (OCT), visual evoked potentials (VEP), or B-mode transorbital sonography (TOS). OBJECTIVES: The aim is to assess changes in the visual pathway in eyes of MS patients with and without a history of optic neuritis over a 3-year period and to explore their relationship with disability. MATERIALS AND METHODS: In total, 112 eyes from 56 patients with relapsing MS were recruited: 29 with, and 83 without a history of ON (hON and nhON, respectively). Several parameters were measured by OCT, VEP, and TOS. Baseline measurements were also compared to 29 healthy controls. At 36 months, measurements were repeated in all eyes. RESULTS: At baseline, all tests showed significant differences in optic nerve structure and function in both patient cohorts in all the parameters studied, suggestive of more impairment of the visual pathway among the hON cohort. OCT showed significant differences between healthy controls and the nhON cohort. At 36 months, the nhON cohort showed significant changes by OCT, VEP, and TOS suggestive of further visual pathway impairment. OCT measurements also correlated with baseline EDSS among the nhON cohort. CONCLUSIONS: OCT is the most suitable technique and outperforms VEP and TOS to detect subclinical damage in the visual pathway. It discriminated MS patients from healthy controls and showed a progressive decline in optic nerve thickness over time among these patients.