Plasma lipidomics in early APP/PS1 female mouse model and its relationship with brain: Is it affected by the estrous cycle?

BACKGROUND: Alzheimer's disease (AD) is the most prevalent dementia, showing higher incidence in women. Besides, lipids play an essential role in brain, and they could be dysregulated in neurodegeneration. Specifically, impaired plasma lipid levels could predict early AD diagnosis. This work aims to identify the main plasma lipids altered in early AD female mouse model and evaluate their relationship with brain lipidome. Also, the possible involvement of the estrous cycle in lipid metabolism has been evaluated. METHODS: Plasma samples of wild-type (n = 10) and APP/PS1 (n = 10) female mice of 5 months of age were collected, processed, and analysed using a lipidomic mass spectrometry-based method. A statistical analysis involving univariate and multivariate approaches was performed to identify significant lipid differences related to AD between groups. Also, cytology tests were conducted to confirm estrous cycle phases. RESULTS: Three hundred thirty lipids were detected in plasma, 18 of them showed significant differences between groups; specifically, some triacylglycerols, cholesteryl esters, lysophosphatidylcholines, phosphatidylcholines, and ether-linked phosphatidylcholines, increased in early AD; while other phosphatidylcholines, phosphatidylethanolamines, ceramides, and ether-linked phosphatidylethanolamines decreased in early AD. A multivariate approach was developed from some lipid variables, showing high diagnostic indexes (70% sensitivity, 90% specificity, 80% accuracy). From brain and plasma lipidome, some significant correlations were observed, mainly in the glycerophospholipid family. Also, some differences were found in both plasma and brain lipids, according to the estrous cycle phase. CONCLUSIONS: Therefore, lipid alterations can be identified in plasma at early AD stages in mice females, with a relationship with brain lipid metabolism for most of the lipid subfamilies, suggesting some lipids as potential AD biomarkers. In addition, the estrous cycle monitoring could be relevant in female studies.

Insights from a 7-Year Dementia Cohort (VALCODIS): ApoE Genotype Evaluation.

Background: The VALCODIS (Valencian Cognitive Diseases Study) cohort was designed and studied at the Hospital Universitari i Politècnic La Fe (Valencia, Spain) for the research of cognitive diseases, especially in the search for new biomarkers of Alzheimer's disease (AD). Methods: Participants in the VALCODIS cohort had cerebrospinal fluid (CSF) and blood samples, neuroimaging, and neuropsychological tests. The ApoE genotype was evaluated to identify its relationship with CSF biomarkers and neuropsychological tests in AD and non-AD participants. Results: A total of 1249 participants were included. They were mainly AD patients (n = 547) but also patients with other dementias (frontotemporal lobar dementia (n = 61), Lewy body dementia without AD CSF signature (n = 10), vascular dementia (n = 24) and other specific causes of cognitive impairment (n = 442), and patients with subjective memory complaints (n = 165)). In the ApoE genotype evaluation, significant differences were found for Aß42 levels between genotypes in both AD and non-AD patients, as well as a negative correlation between tau values and a cognitive test in non-carriers and ε4 heterozygous. Conclusions: The VALCODIS cohort provides biologically diagnosed patients with demographical, clinical and biochemical data, and biological samples for further studies on early AD diagnosis. Also, the ApoE genotype evaluation showed correlations between CSF biomarkers and neuropsychological tests.

Relationship between Plasma Lipid Profile and Cognitive Status in Early Alzheimer Disease.

Alzheimer disease (AD) is a heterogeneous and complex disease in which different pathophysiological mechanisms are involved. This heterogenicity can be reflected in different atrophy patterns or clinical manifestations. Regarding biochemical pathways involved in early AD, lipid metabolism plays an important role; therefore, lipid levels have been evaluated as potential AD diagnosis biomarkers, and their levels could be related to different AD clinical manifestations. Therefore, the aim of this work is to study AD lipid profiles from early AD patients and evaluate their clinical significance. For this purpose, untargeted plasma lipidomic analysis was carried out in early AD patients (n = 31) diagnosed with cerebrospinal fluid (CSF) biomarkers. Cluster analysis was carried out to define early AD subgroups according to the lipid levels. Then, the clinical significance of each lipid profile subgroup was studied, analyzing differences for other variables (cognitive status, CSF biomarkers, medication, comorbidities, age, and gender). The cluster analysis revealed two different groups of AD patients. Cluster 1 showed higher levels of plasma lipids and better cognitive status than Cluster 2. However, no differences were found for the other variables (age, gender, medication, comorbidities, cholesterol, and triglycerides levels) between both groups. Plasma lipid levels could differentiate two early AD subgroups, which showed different cognitive statuses. However, further research with a large cohort and longitudinal study evaluating the clinical evolution of these patients is required. In general, it would involve a relevant advance in the knowledge of AD pathological mechanisms, potential treatments, and precision medicine.

New approach for early and specific Alzheimer disease diagnosis from different plasma biomarkers.

BACKGROUND: Alzheimer Disease (AD) is a complex pathology, in which several biochemical pathways could be involved. Therefore, the development of clinical studies combining different nature biomarkers in an AD diagnosis approach is required. Specifically, the present study evaluated blood biomarkers from different molecular pathways (epigenomics, lipid metabolism, lipid peroxidation), to obtain an early and specific AD diagnosis approach. METHODS: The participants were classified into early AD (n = 53), and non-AD (healthy controls, other dementias) (n = 83). Blood samples were collected and biochemical determinations (microRNAs, lipids, lipid peroxidation compounds) were carried out by quantitative PCR and liquid chromatography coupled to mass spectrometry, respectively. Then, a logistic regression model with a Bayesian variable selection procedure was developed. RESULTS: The Bayesian variable selection procedure for microRNAs did not show any relevant variable. Therefore, microRNA biomarkers were excluded. So, the developed model considered only lipids and lipid peroxidation compounds. The corresponding selected variables were age, 18:0 LPC, PGE2, isoprostanes and, isofurans. The validated model (by leave-one-out cross-validation) provided satisfactory diagnosis indexes (AUC 0.83, Sensitivity 87 %, Specificity 79 %). CONCLUSION: The developed model included biomarkers from different pathways (lipid metabolism, oxidative stress), achieving a promising approach to early, specific and, minimally invasive AD diagnosis. Nevertheless, further work to validate clinically these preliminary results with an external cohort is required. Also, the integration of different compounds coming from several biochemical pathways could constitute a relevant research field for the development of AD therapeutic targets.

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.

Brain areas lipidomics in female transgenic mouse model of Alzheimer's disease.

Lipids are the major component of the brain with important structural and functional properties. Lipid disruption could play a relevant role in Alzheimer's disease (AD). Some brain lipidomic studies showed significant differences compared to controls, but few studies have focused on different brain areas related to AD. Furthermore, AD is more prevalent in females, but there is a lack of studies focusing on this sex. This work aims to perform a lipidomic study in selected brain areas (cerebellum, amygdala, hippocampus, entire cortex) from wild-type (WT, n = 10) and APPswe/PS1dE9 transgenic (TG, n = 10) female mice of 5 months of age, as a model of early AD, to identify alterations in lipid composition. A lipidomic mass spectrometry-based method was optimized and applied to brain tissue. As result, some lipids showed statistically significant differences between mice groups in cerebellum (n = 68), amygdala (n = 49), hippocampus (n = 48), and the cortex (n = 22). In addition, some lipids (n = 15) from the glycerolipid, phospholipid, and sphingolipid families were statistically significant in several brain areas simultaneously between WT and TG. A selection of lipid variables was made to develop a multivariate approach to assess their discriminant potential, showing high diagnostic indexes, especially in cerebellum and amygdala (sensitivity 70-100%, sensibility 80-100%).

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.

Misfolded alpha-synuclein detection by RT-QuIC in dementia with lewy bodies: a systematic review and meta-analysis.

Introduction: Dementia with Lewy Bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimer's disease (AD), but the field is still lacking a specific biomarker for its core pathology: alpha synuclein (α-syn). Realtime quaking induced conversion (RT-QuIC) has recently emerged as a strong biomarker candidate to detect misfolded α-syn in DLB. However, the variability in the parameters of the technique and the heterogeneity of DLB patients make the reproducibility of the results difficult. Here, we provide an overview of the state-of-the-art research of α-syn RT-QuIC in DLB focused on: (1) the capacity of α-syn RT-QuIC to discriminate DLB from controls, Parkinson's disease (PD) and AD; (2) the capacity of α-syn RT-QuIC to identify prodromal stages of DLB; and (3) the influence of co-pathologies on α-syn RT-QuIC's performance. We also assessed the influence of different factors, such as technical conditions (e.g., temperature, pH, shaking-rest cycles), sample type, and clinical diagnosis versus autopsy confirmation. Methods: We conducted a systematic review following the PRISMA guidelines in August 2022, without any limits in publication dates. Search terms were combinations of "RT-QuIC" and "Lewy Bodies," "DLB" or "LBD". Results: Our meta-analysis shows that α-syn RT-QuIC reaches very high diagnostic performance in discriminating DLB from both controls (pooled sensitivity and specificity of 0.94 and 0.96, respectively) and AD (pooled sensitivity and specificity of 0.95 and 0.88) and is promising for prodromal phases of DLB. However, the performance of α-syn RT-QuIC to discriminate DLB from PD is currently low due to low specificity (pooled sensitivity and specificity of 0.94 and 0.11). Our analysis showed that α-syn RT-QuIC's performance is not substantially influenced by sample type or clinical diagnosis versus autopsy confirmation. Co-pathologies did not influence the performance of α-syn RT-QuIC, but the number of such studies is currently limited. We observed technical variability across published articles. However, we could not find a clear effect of technical variability on the reported results. Conclusion: There is currently enough evidence to test misfolded α-syn by RT-QuIC for clinical use. We anticipate that harmonization of protocols across centres and advances in standardization will facilitate the clinical establishment of misfolded α-syn detection by RT-QuIC.

Angiotensin II Receptor Blockers Reduce Tau/Aß42 Ratio: A Cerebrospinal Fluid Biomarkers' Case-Control Study.

(1) Background: The role of antihypertensives in Alzheimer's Disease (AD) prevention is controversial. This case-control study aims to assess whether antihypertensive medication has a protective role by studying its association with amyloid and tau abnormal levels. Furthermore, it suggests a holistic view of the involved pathways between renin-angiotensin drugs and the tau/amyloidß42 ratio (tau/Aß42 ratio); (2) Methods: The medical records of the participant patients were reviewed, with a focus on prescribed antihypertensive drugs and clinical variables, such as arterial blood pressure. The Anatomical Therapeutic Chemical classification was used to classify each drug. The patients were divided into two groups: patients with AD diagnosis (cases) and cognitively healthy patients (control); (3) Results: Age and high systolic blood pressure are associated with a higher risk of developing AD. In addition, combinations of angiotensin II receptor blockers are associated with a 30% lower t-tau/Aß42 ratio than plain angiotensin-converting enzyme inhibitor consumption; (4) Conclusions: Angiotensin II receptor blockers may play a potential role in neuroprotection and AD prevention. Likewise, several mechanisms, such as the PI3K/Akt/GSK3ß or the ACE1/AngII/AT1R axis, may link cardiovascular pathologies and AD presence, making its modulation a pivotal point in AD prevention. The present work highlights the central pathways in which antihypertensives may affect the presence of pathological amyloid and tau hyperphosphorylation.

Systematic review of brain and blood lipidomics in Alzheimer's disease mouse models.

Alzheimer's disease (AD) diagnosis is based on invasive and expensive biomarkers. Regarding AD pathophysiological mechanisms, there is evidence of a link between AD and aberrant lipid homeostasis. Alterations in lipid composition have been observed in blood and brain samples, and transgenic mouse models represent a promising approach. Nevertheless, there is great variability among studies in mice for the determination of different types of lipids in targeted and untargeted methods. It could be explained by the different variables (model, age, sex, analytical technique), and experimental conditions used. The aim of this work is to review the studies on lipid alteration in brain tissue and blood samples from AD mouse models, focusing on different experimental parameters. As result, great disparity has been observed among the reviewed studies. Brain studies showed an increase in gangliosides, sphingomyelins, lysophospholipids and monounsaturated fatty acids and a decrease in sulfatides. In contrast, blood studies showed an increase in phosphoglycerides, sterols, diacylglycerols, triacylglycerols and polyunsaturated fatty acids, and a decrease in phospholipids, lysophospholipids and monounsaturated fatty acids. Thus, lipids are closely related to AD, and a consensus on lipidomics studies could be used as a diagnostic tool and providing insight into the mechanisms involved in AD.

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 microRNAs as potential biomarkers in early Alzheimer disease expression.

The microRNAs (miRNAs) are potential biomarkers for complex pathologies due to their involvement in the regulation of several pathways. Alzheimer Disease (AD) requires new biomarkers in minimally invasive samples that allow an early diagnosis. The aim of this work is to study miRNAS as potential AD biomarkers and their role in the pathology development. In this study, participants (n = 46) were classified into mild cognitive impairment due to AD (MCI-AD, n = 19), preclinical AD (n = 8) and healthy elderly controls (n = 19), according to CSF biomarkers levels (amyloid ß42, total tau, phosphorylated tau) and neuropsychological assessment. Then, plasma miRNAomic expression profiles were analysed by Next Generation Sequencing. Finally, the selected miRNAs were validated by quantitative PCR (q-PCR). A panel of 11 miRNAs was selected from omics expression analysis, and 8 of them were validated by q-PCR. Individually, they did not show statistically significant differences among participant groups. However, a multivariate model including these 8 miRNAs revealed a potential association with AD for three of them. Specifically, relatively lower expression levels of miR-92a-3p and miR-486-5p are observed in AD patients, and relatively higher levels of miR-29a-3p are observed in AD patients. These biomarkers could be involved in the regulation of pathways such as synaptic transmission, structural functions, cell signalling and metabolism or transcription regulation. Some plasma miRNAs (miRNA-92a-3p, miRNA-486-5p, miRNA-29a-3p) are slightly dysregulated in AD, being potential biomarkers of the pathology. However, more studies with a large sample size should be carried out to verify these results, as well as to further investigate the mechanisms of action of these miRNAs.

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.

Assessment of Lipid Peroxidation in Alzheimer's Disease Differential Diagnosis and Prognosis.

Alzheimer's disease (AD) and other dementias are becoming increasingly common in the older population, and the number of people affected is expected to increase in a few years. Nowadays, biomarkers used in early AD diagnosis are expensive and invasive. Therefore, this research field is growing. In fact, peroxidation by-products derived from the oxidation of brain lipids (arachidonic (AA), docosahexanoic (DHA) and adrenic acid (AdA)) could be potential biomarkers, participating in the mechanisms of inflammation, neurotoxicity and cell death in AD pathology. Previous studies have shown specificity between lipid peroxidation compounds and other dementias (e.g., Lewy bodies (DLB), frontotemporal dementia (FTD)), but more research is required. Lipid peroxidation compounds (prostaglandins, isoprostanes, isofurans, neuroprostanes, neurofurans, dihomo-isoprostanes and dihomo-isofurans) were analysed by liquid chromatography and mass spectrometry in plasma samples from participants classified into a healthy group (n = 80), a mild cognitive impairment due to AD group (n = 106), a mild dementia due to AD group (n = 70), an advanced dementia due to AD group (n = 11) and a group of other non-AD dementias (n = 20). Most of these compounds showed statistically significant differences between groups (p < 0.05), showing higher levels for the healthy and non-AD groups than the AD groups. Then, a multivariate analysis was carried out on these compounds, showing good diagnosis indexes (AUC 0.77, sensitivity 81.3%, positive predictive value 81%). Moreover, evaluating AD disease prognosis, two compounds (15-F2t-IsoP and 14(RS)-14-F4t-NeuroP) and three total parameters (isoprostanes, isofurans and neurofurans) showed significant differences among groups. Some compounds derived from the oxidation of AA, DHA and AdA have demonstrated their potential use in differential AD diagnosis. Specifically, 15-F2t-IsoP, 14(RS)-14-F4t-NeuroP and the total parameters for isoprostanes, isofurans and neurofurans have shown prognostic value for AD from its earliest stages to its most severe form.