An Insertion Within SIRPß1 Shows a Dual Effect Over Alzheimer's Disease Cognitive Decline Altering the Microglial Response.

Background: Microglial dysfunction plays a causative role in Alzheimer's disease (AD) pathogenesis. Here we focus on a germline insertion/deletion variant mapping SIRPß1, a surface receptor that triggers amyloid-ß(Aß) phagocytosis via TYROBP. Objective: To analyze the impact of this copy-number variant in SIRPß1 expression and how it affects AD molecular etiology. Methods: Copy-number variant proxy rs2209313 was evaluated in GERALD and GR@ACE longitudinal series. Hippocampal specimens of genotyped AD patients were also examined. SIRPß1 isoform-specific phagocytosis assays were performed in HEK393T cells. Results: The insertion alters the SIRPß1 protein isoform landscape compromising its ability to bind oligomeric Aß and its affinity for TYROBP. SIRPß1 Dup/Dup patients with mild cognitive impairment show an increased cerebrospinal fluid t-Tau/Aß ratio (p = 0.018) and a higher risk to develop AD (OR = 1.678, p = 0.018). MRIs showed that Dup/Dup patients exhibited a worse initial response to AD. At the moment of diagnosis, all patients showed equivalent Mini-Mental State Examination scores. However, AD patients with the duplication had less hippocampal degeneration (p < 0.001) and fewer white matter hyperintensities. In contrast, longitudinal studies indicate that patients bearing the duplication allele show a slower cognitive decline (p = 0.013). Transcriptional analysis also shows that the SIRPß1 duplication allele correlates with higher TREM2 expression and an increased microglial activation. Conclusions: The SIRPß1 internal duplication has opposite effects over MCI-to-Dementia conversion risk and AD progression, affecting microglial response to Aß. Given the pharmacological approaches focused on the TREM2-TYROBP axis, we believe that SIRPß1 structural variant might be considered as a potential modulator of this causative pathway.

Unveiling the sound of the cognitive status: Machine Learning-based speech analysis in the Alzheimer's disease spectrum.

BACKGROUND: Advancement in screening tools accessible to the general population for the early detection of Alzheimer's disease (AD) and prediction of its progression is essential for achieving timely therapeutic interventions and conducting decentralized clinical trials. This study delves into the application of Machine Learning (ML) techniques by leveraging paralinguistic features extracted directly from a brief spontaneous speech (SS) protocol. We aimed to explore the capability of ML techniques to discriminate between different degrees of cognitive impairment based on SS. Furthermore, for the first time, this study investigates the relationship between paralinguistic features from SS and cognitive function within the AD spectrum. METHODS: Physical-acoustic features were extracted from voice recordings of patients evaluated in a memory unit who underwent a SS protocol. We implemented several ML models evaluated via cross-validation to identify individuals without cognitive impairment (subjective cognitive decline, SCD), with mild cognitive impairment (MCI), and with dementia due to AD (ADD). In addition, we established models capable of predicting cognitive domain performance based on a comprehensive neuropsychological battery from Fundació Ace (NBACE) using SS-derived information. RESULTS: The results of this study showed that, based on a paralinguistic analysis of sound, it is possible to identify individuals with ADD (F1 = 0.92) and MCI (F1 = 0.84). Furthermore, our models, based on physical acoustic information, exhibited correlations greater than 0.5 for predicting the cognitive domains of attention, memory, executive functions, language, and visuospatial ability. CONCLUSIONS: In this study, we show the potential of a brief and cost-effective SS protocol in distinguishing between different degrees of cognitive impairment and forecasting performance in cognitive domains commonly affected within the AD spectrum. Our results demonstrate a high correspondence with protocols traditionally used to assess cognitive function. Overall, it opens up novel prospects for developing screening tools and remote disease monitoring.

The first genome-wide association study in the Argentinian and Chilean populations identifies shared genetics with Europeans in Alzheimer's disease.

INTRODUCTION: Genome-wide association studies (GWAS) are fundamental for identifying loci associated with diseases. However, they require replication in other ethnicities. METHODS: We performed GWAS on sporadic Alzheimer's disease (AD) including 539 patients and 854 controls from Argentina and Chile. We combined our results with those from the European Alzheimer and Dementia Biobank (EADB) in a meta-analysis and tested their genetic risk score (GRS) performance in this admixed population. RESULTS: We detected apolipoprotein E ε4 as the single genome-wide significant signal (odds ratio  = 2.93 [2.37-3.63], P = 2.6 × 10-23 ). The meta-analysis with EADB summary statistics revealed four new loci reaching GWAS significance. Functional annotations of these loci implicated endosome/lysosomal function. Finally, the AD-GRS presented a similar performance in these populations, despite the score diminished when the Native American ancestry rose. DISCUSSION: We report the first GWAS on AD in a population from South America. It shows shared genetics modulating AD risk between the European and these admixed populations. HIGHLIGHTS: This is the first genome-wide association study on Alzheimer's disease (AD) in a population sample from Argentina and Chile. Trans-ethnic meta-analysis reveals four new loci involving lysosomal function in AD. This is the first independent replication for TREM2L, IGH-gene-cluster, and ADAM17 loci. A genetic risk score (GRS) developed in Europeans performed well in this population. The higher the Native American ancestry the lower the GRS values.

Harnessing acoustic speech parameters to decipher amyloid status in individuals with mild cognitive impairment.

Alzheimer's disease (AD) is a neurodegenerative condition characterized by a gradual decline in cognitive functions. Currently, there are no effective treatments for AD, underscoring the importance of identifying individuals in the preclinical stages of mild cognitive impairment (MCI) to enable early interventions. Among the neuropathological events associated with the onset of the disease is the accumulation of amyloid protein in the brain, which correlates with decreased levels of Aß42 peptide in the cerebrospinal fluid (CSF). Consequently, the development of non-invasive, low-cost, and easy-to-administer proxies for detecting Aß42 positivity in CSF becomes particularly valuable. A promising approach to achieve this is spontaneous speech analysis, which combined with machine learning (ML) techniques, has proven highly useful in AD. In this study, we examined the relationship between amyloid status in CSF and acoustic features derived from the description of the Cookie Theft picture in MCI patients from a memory clinic. The cohort consisted of fifty-two patients with MCI (mean age 73 years, 65% female, and 57% positive amyloid status). Eighty-eight acoustic parameters were extracted from voice recordings using the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), and several ML models were used to classify the amyloid status. Furthermore, interpretability techniques were employed to examine the influence of input variables on the determination of amyloid-positive status. The best model, based on acoustic variables, achieved an accuracy of 75% with an area under the curve (AUC) of 0.79 in the prediction of amyloid status evaluated by bootstrapping and Leave-One-Out Cross Validation (LOOCV), outperforming conventional neuropsychological tests (AUC = 0.66). Our results showed that the automated analysis of voice recordings derived from spontaneous speech tests offers valuable insights into AD biomarkers during the preclinical stages. These findings introduce novel possibilities for the use of digital biomarkers to identify subjects at high risk of developing AD.

A randomized, open-label clinical trial in mild cognitive impairment with EGb 761 examining blood markers of inflammation and oxidative stress.

Although beta-amyloid (Aß) and phosphorylated tau remain the preferred targets for disease-modifying treatments (DMT) against Alzheimer's disease (AD), part of the pathophysiological mechanisms of cognitive impairment are related to neuroinflammation and oxidative stress. In mild cognitive impairment (MCI), a prodromal stage of AD and other neurodegenerative conditions, the joint appearance of inflammation, oxidative stress, and metabolic alterations are the common pathways of neurotoxicity and neurodegeneration. The standardized extract of Ginkgo biloba EGb 761 interferes with the pathogenic mechanisms involved in both the development of cognitive impairment due to AD and that of vascular origin. The primary objective of this study is to compare changes in the levels of blood markers of inflammation and oxidative stress after treatment with EGb 761 in a cohort of 100 patients with MCI. In addition, we aim to assess changes in these blood markers during an additional 12-month extension phase in which patients in the control group will also receive EGb 761 and patients in the active group will extend their treatment duration. Secondary objectives include comparing changes in neuropsychiatric and cognitive test scores between the baseline (v0) and 12-month visits (v2). This study is a Phase IV, single-center, randomized, open-label, parallel-group clinical trial consisting of the 12-month follow-up of a cohort of participants with MCI [Global Deterioration Scale (GDS) = 3] and an extension with an additional 12-month follow-up. During the first 12 months, participants will be randomized into two arms: in one arm, patients will receive 1 daily tablet of EGb 761 240 mg orally (study group, n = 50), while in the other arm, patients will not receive EGb 761 and will undergo the same assessments as the treated group (control group, n = 50). After the first 12 months of the study, patients in the EGb 761-treated group will continue treatment, and patients in the control group will be offered one EGb 761 240 mg tablet per day orally. All participants will be monitored for an additional 12 months. A battery of blood markers of inflammation and oxidative stress will be quantified at v0, v1, v2, v3, and v4. The Olink Proteomics panel of inflammation markers ( https://www.olink.com/products/inflammation/ ) will be used to evaluate 92 proteins associated with inflammatory diseases and related biological processes. The second panel measures 92 proteins involved in neurological processes. At v0, v2, and v4, neuropsychological and neurological evaluations will be conducted in addition to vital signs and anthropometric studies using a body composition monitor with bioimpedance technology (Tanita). Sixty percent of the 100 MCI patients recruited were women. The mean age was 73.1 years, and the mean time between symptom onset and MCI diagnosis was 2.9 years. The mean Mini-Mental State Examination (MMSE) score was 26.7. Depressive and anxiety disorders, as well as vascular risk factors, were the most frequent comorbidities among the cohort. The study is still ongoing, and results for the first year of treatment (v0, v1, v2) are expected by 2023. Individuals with MCI have an elevated risk of developing dementia. EGb 761 is used worldwide for the symptomatic treatment of cognitive disorders due to its neuroprotective effects. In experimental models and clinical observational studies, EGb 761 has shown strong antioxidant and anti-inflammatory activity. As a result, this study has been proposed to evaluate the antioxidant and anti-inflammatory effects on plasma markers and their potential clinical correlation with the progression of cognitive decline in patients with MCI.Trial registration: Registro Español de estudios clínicos (REec) number 2020-003776-41, ClinicalTrials.gov Identifier: NCT05594355.

Macular vessel density in the superficial plexus is not associated to cerebrospinal fluid core biomarkers for Alzheimer's disease in individuals with mild cognitive impairment: The NORFACE cohort.

Background: Optical coherence tomography angiography (OCT-A) is a novel method in the dementia field that allows the detection of retinal vascular changes. The comparison of OCT-A measures with established Alzheimer's disease (AD)-related biomarkers is essential to validate the former as a marker of cerebrovascular impairment in the AD continuum. We aimed to investigate the association of macular vessel density (VD) in the superficial plexus quantified by OCT-A with the AT(N) classification based on cerebrospinal fluid (CSF) Aß1-42, p181-tau and t-tau measurements in individuals with mild cognitive impairment (MCI). Materials and methods: Clinical, demographic, ophthalmological, OCT-A and CSF core biomarkers for AD data from the Neuro-ophthalmology Research at Fundació ACE (NORFACE) project were analyzed. Differences in macular VD in four quadrants (superior, nasal, inferior, and temporal) among three AT(N) groups [Normal, Alzheimer and Suspected non-Alzheimer pathology (SNAP)] were assessed in a multivariate regression model, adjusted for age, APOE ε4 status, hypertension, diabetes mellitus, dyslipidemia, heart disease, chronic obstructive pulmonary disease and smoking habit, using the Normal AT(N) group as the reference category. Results: The study cohort comprised 144 MCI participants: 66 Normal AT(N), 45 Alzheimer AT(N) and 33 SNAP AT(N). Regression analysis showed no significant association of the AT(N) groups with any of the regional macular VD measures (all, p > 0.16). The interaction between sex and AT(N) groups had no effect on differentiating VD. Lastly, CSF Aß1-42, p181-tau and t-tau measures were not correlated to VD (all r < 0.13; p > 0.13). Discussion: Our study showed that macular VD measures were not associated with the AT(N) classification based on CSF biomarkers in patients with MCI, and did not differ between AD and other underlying causes of cognitive decline in our cohort.

Plasma extracellular vesicles reveal early molecular differences in amyloid positive patients with early-onset mild cognitive impairment.

In the clinical course of Alzheimer's disease (AD) development, the dementia phase is commonly preceded by a prodromal AD phase, which is mainly characterized by reaching the highest levels of Aß and p-tau-mediated neuronal injury and a mild cognitive impairment (MCI) clinical status. Because of that, most AD cases are diagnosed when neuronal damage is already established and irreversible. Therefore, a differential diagnosis of MCI causes in these prodromal stages is one of the greatest challenges for clinicians. Blood biomarkers are emerging as desirable tools for pre-screening purposes, but the current results are still being analyzed and much more data is needed to be implemented in clinical practice. Because of that, plasma extracellular vesicles (pEVs) are gaining popularity as a new source of biomarkers for the early stages of AD development. To identify an exosome proteomics signature linked to prodromal AD, we performed a cross-sectional study in a cohort of early-onset MCI (EOMCI) patients in which 184 biomarkers were measured in pEVs, cerebrospinal fluid (CSF), and plasma samples using multiplex PEA technology of Olink© proteomics. The obtained results showed that proteins measured in pEVs from EOMCI patients with established amyloidosis correlated with CSF p-tau181 levels, brain ventricle volume changes, brain hyperintensities, and MMSE scores. In addition, the correlations of pEVs proteins with different parameters distinguished between EOMCI Aß( +) and Aß(-) patients, whereas the CSF or plasma proteome did not. In conclusion, our findings suggest that pEVs may be able to provide information regarding the initial amyloidotic changes of AD. Circulating exosomes may acquire a pathological protein signature of AD before raw plasma, becoming potential biomarkers for identifying subjects at the earliest stages of AD development.

Correlations between the NMR Lipoprotein Profile, APOE Genotype, and Cholesterol Efflux Capacity of Fasting Plasma from Cognitively Healthy Elderly Adults.

Cholesterol efflux capacity (CEC) is of interest given its potential relationship with several important clinical conditions including Alzheimer's disease. The inactivation of the APOE locus in mouse models supports the idea that it is involved in determining the CEC. With that in mind, we examine the impact of the plasma metabolome profile and the APOE genotype on the CEC in cognitively healthy elderly subjects. The study subjects were 144 unrelated healthy individuals. The plasma CEC was determined by exposing cultured mouse macrophages treated with BODIPY-cholesterol to human plasma. The metabolome profile was determined using NMR techniques. Multiple regression was performed to identify the most important predictors of CEC, as well as the NMR features most strongly associated with the APOE genotype. Plasma 3-hydroxybutyrate was the variable most strongly correlated with the CEC (r = 0.365; p = 7.3 × 10-6). Male sex was associated with a stronger CEC (r = -0.326, p = 6.8 × 10-5). Most of the NMR particles associated with the CEC did not correlate with the APOE genotype. The NMR metabolomics results confirmed the APOE genotype to have a huge effect on the concentration of plasma lipoprotein particles as well as those of other molecules including omega-3 fatty acids. In conclusion, the CEC of human plasma was associated with ketone body concentration, sex, and (to a lesser extent) the other features of the plasma lipoprotein profile. The APOE genotype exerted only a weak effect on the CEC via the modulation of the lipoprotein profile. The APOE locus was associated with omega-3 fatty acid levels independent of the plasma cholesterol level.

Mendelian Randomisation Confirms the Role of Y-Chromosome Loss in Alzheimer's Disease Aetiopathogenesis in Men.

Mosaic loss of chromosome Y (mLOY) is a common ageing-related somatic event and has been previously associated with Alzheimer's disease (AD). However, mLOY estimation from genotype microarray data only reflects the mLOY degree of subjects at the moment of DNA sampling. Therefore, mLOY phenotype associations with AD can be severely age-confounded in the context of genome-wide association studies. Here, we applied Mendelian randomisation to construct an age-independent mLOY polygenic risk score (mloy-PRS) using 114 autosomal variants. The mloy-PRS instrument was associated with an 80% increase in mLOY risk per standard deviation unit (p = 4.22 × 10-20) and was orthogonal with age. We found that a higher genetic risk for mLOY was associated with faster progression to AD in men with mild cognitive impairment (hazard ratio (HR) = 1.23, p = 0.01). Importantly, mloy-PRS had no effect on AD conversion or risk in the female group, suggesting that these associations are caused by the inherent loss of the Y chromosome. Additionally, the blood mLOY phenotype in men was associated with increased cerebrospinal fluid levels of total tau and phosphorylated tau181 in subjects with mild cognitive impairment and dementia. Our results strongly suggest that mLOY is involved in AD pathogenesis.

The Synergic Effect of AT(N) Profiles and Depression on the Risk of Conversion to Dementia in Patients with Mild Cognitive Impairment.

Few studies have addressed the impact of the association between Alzheimer's disease (AD) biomarkers and NPSs in the conversion to dementia in patients with mild cognitive impairment (MCI), and no studies have been conducted on the interaction effect of these two risk factors. AT(N) profiles were created using AD-core biomarkers quantified in cerebrospinal fluid (CSF) (normal, brain amyloidosis, suspected non-Alzheimer pathology (SNAP) and prodromal AD). NPSs were assessed using the Neuropsychiatric Inventory Questionnaire (NPI-Q). A total of 500 individuals with MCI were followed-up yearly in a memory unit. Cox regression analysis was used to determine risk of conversion, considering additive and multiplicative interactions between AT(N) profile and NPSs on the conversion to dementia. A total of 224 participants (44.8%) converted to dementia during the 2-year follow-up study. Pathologic AT(N) groups (brain amyloidosis, prodromal AD and SNAP) and the presence of depression and apathy were associated with a higher risk of conversion to dementia. The additive combination of the AT(N) profile with depression exacerbates the risk of conversion to dementia. A synergic effect of prodromal AD profile with depressive symptoms is evidenced, identifying the most exposed individuals to conversion among MCI patients.

Establishing In-House Cutoffs of CSF Alzheimer's Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort.

BACKGROUND: Clinical diagnosis of Alzheimer's disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. METHODS: We quantified CSF Aß1-42, Aß1-40, t-Tau, and p181Tau with standard INNOTEST® ELISA and Lumipulse G® chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer's disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for Aß1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and Aß1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and Aß1-42/Aß1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). RESULTS: Cutoff values of Aß1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aß1-40 and 0.96 for p181TAU. Passing-Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aß1-40. Bland-Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the Aß1-42/Aß1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan-Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815-27). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. CONCLUSIONS: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects.

Automatized FACEmemory® scoring is related to Alzheimer's disease phenotype and biomarkers in early-onset mild cognitive impairment: the BIOFACE cohort.

BACKGROUND: FACEmemory® is the first computerized, self-administered verbal episodic memory test with voice recognition. It can be conducted under minimal supervision and contains an automatic scoring system to avoid administrator errors. Moreover, it is suitable for discriminating between cognitively healthy and amnestic mild cognitive impairment (MCI) individuals, and it is associated with Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers. This study aimed to determine whether FACEmemory scoring is related to performance on classical memory tests and to AD biomarkers of brain magnetic resonance imaging (MRI) and CSF in patients with early-onset MCI (EOMCI). METHODS: Ninety-four patients with EOMCI from the BIOFACE study completed FACEmemory, classical memory tests (the Spanish version of the Word Free and Cued Selective Reminding Test -FCSRT-, the Word List from the Wechsler Memory Scale, third edition, and the Spanish version of the Rey-Osterrieth Complex Figure Test), and a brain MRI. Eighty-two individuals also underwent a lumbar puncture. RESULTS: FACEmemory scoring was moderately correlated with FCSRT scoring. With regard to neuroimaging MRI results, worse execution on FACEmemory was associated with lower cortical volume in the right prefrontal and inferior parietal areas, along with the left temporal and associative occipital areas. Moreover, the total FACEmemory score correlated with CSF AD biomarkers (Aß1-42/Aß1-40 ratio, p181-tau, and Aß1-42/p181-tau ratio). When performance on FACEmemory was compared among the ATN classification groups, significant differences between the AD group and normal and SNAP groups were found. CONCLUSIONS: FACEmemory is a promising tool for detecting memory deficits sensitive to early-onset AD, but it also allows the detection of memory-impaired cases due to other etiologies. Our findings suggest that FACEmemory scoring can detect the AD endophenotype and that it is also associated with AD-related changes in MRI and CSF in patients with EOMCI. The computerized FACEmemory tool might be an opportunity to facilitate early detection of MCI in younger people than 65, who have a growing interest in new technologies.

Matrix metalloproteinase 10 is linked to the risk of progression to dementia of the Alzheimer's type.

Alzheimer's disease has a long asymptomatic phase that offers a substantial time window for intervention. Using this window of opportunity will require early diagnostic and prognostic biomarkers to detect Alzheimer's disease pathology at predementia stages, thus allowing identification of patients who will most probably progress to dementia of the Alzheimer's type and benefit from specific disease-modifying therapies. Consequently, we searched for CSF proteins associated with disease progression along with the clinical disease staging. We measured the levels of 184 proteins in CSF samples from 556 subjective cognitive decline and mild cognitive impairment patients from three independent memory clinic longitudinal studies (Spanish ACE, n = 410; German DCN, n = 93; German Mannheim, n = 53). We evaluated the association between protein levels and clinical stage, and the effect of protein levels on the progression from mild cognitive impairment to dementia of the Alzheimer's type. Mild cognitive impairment subjects with increased CSF level of matrix metalloproteinase 10 (MMP-10) showed a higher probability of progressing to dementia of the Alzheimer's type and a faster cognitive decline. CSF MMP-10 increased the prediction accuracy of CSF amyloid-ß 42 (Aß42), phospho-tau 181 (P-tau181) and total tau (T-tau) for conversion to dementia of the Alzheimer's type. Including MMP-10 to the [A/T/(N)] scheme improved considerably the prognostic value in mild cognitive impairment patients with abnormal Aß42, but normal P-tau181 and T-tau, and in mild cognitive impairment patients with abnormal Aß42, P-tau181 and T-tau. MMP-10 was correlated with age in subjects with normal Aß42, P-tau181 and T-tau levels. Our findings support the use of CSF MMP-10 as a prognostic marker for dementia of the Alzheimer's type and its inclusion in the [A/T/(N)] scheme to incorporate pathologic aspects beyond amyloid and tau. CSF level of MMP-10 may reflect ageing and neuroinflammation.

Mitochondrial DNA and Alzheimer's disease: a first case-control study of the Tunisian population.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disorder in humans and presents a major health problem throughout the world. The etiology of AD is complex, and many factors are implicated, including mitochondria. Mitochondrial alteration has been proposed as a possible cause of AD. Therefore, several studies have focused on finding an association between inherited mitochondrial DNA variants and AD onset. METHODS: In this study, we looked, for the first time, for a potential association between mitochondrial haplogroups or polymorphisms and AD in the Tunisian population. We also evaluated the distribution of the major genetic risk factor for AD, the apolipoprotein E epsilon 4 (APOE ε4), in this population. In total, 159 single-nucleotide polymorphisms (SNPs) of mitochondrial DNA haplogroups were genotyped in 254 individuals (58 patients and 196 controls). An additional genotyping of APOE ε4 was performed. RESULTS: No significant association between mitochondrial haplogroups and AD was found. However, two individual SNPs, A5656G (p = 0.03821, OR = 10.46) and A13759G (p = 0.03719, OR = 10.78), showed a significant association with AD. APOE 4 was confirmed as a risk factor for AD (p = 0.000014). CONCLUSION: Our findings may confirm the absence of a relation between mitochondrial haplogroups and AD and support the possible involvement of some inherited variants in the pathogenicity of AD.

Neuropsychiatric Profile as a Predictor of Cognitive Decline in Mild Cognitive Impairment.

Introduction: Mild cognitive impairment is often associated with affective and other neuropsychiatric symptoms (NPS). This co-occurrence might have a relevant impact on disease progression, from MCI to dementia. Objective: The aim of this study was to explore the trajectories of cognitive decline in an MCI sample from a memory clinic, taking into consideration a perspective of isolated cognitive functions and based on NPS clusters, accounting for the different comorbid symptoms collected at their baseline visit. Methods: A total of 2,137 MCI patients were monitored over a 2.4-year period. Four clusters of NPS (i.e., Irritability, Apathy, Anxiety/Depression and Asymptomatic) were used to run linear mixed models to explore the interaction of cluster with time on cognitive trajectories using a comprehensive neuropsychological battery (NBACE) administered at baseline and at the three subsequent follow-ups. Results: A significant interaction between cluster and time in cognitive decline was found when verbal learning and cued-recall were explored (p = 0.002 for both memory functions). For verbal learning, the Irritability cluster had the largest effect size (0.69), whereas the Asymptomatic cluster showed the smallest effect size (0.22). For cued-recall, the Irritability cluster had the largest effect size among groups (0.64), and Anxiety/Depression had the smallest effect size (0.21). Conclusions: In MCI patients, the Irritability and Apathy NPS clusters shared similar patterns of worsening in memory functioning, which could point to these NPS as risk factors of a faster cognitive decline, acting as early prognostic markers and helping in the diagnostic process.

Genomic Characterization of Host Factors Related to SARS-CoV-2 Infection in People with Dementia and Control Populations: The GR@ACE/DEGESCO Study.

Emerging studies have suggested several chromosomal regions as potential host genetic factors involved in the susceptibility to SARS-CoV-2 infection and disease outcome. We nested a COVID-19 genome-wide association study using the GR@ACE/DEGESCO study, searching for susceptibility factors associated with COVID-19 disease. To this end, we compared 221 COVID-19 confirmed cases with 17,035 individuals in whom the COVID-19 disease status was unknown. Then, we performed a meta-analysis with the publicly available data from the COVID-19 Host Genetics Initiative. Because the APOE locus has been suggested as a potential modifier of COVID-19 disease, we added sensitivity analyses stratifying by dementia status or by disease severity. We confirmed the existence of the 3p21.31 region (LZTFL1, SLC6A20) implicated in the susceptibility to SARS-CoV-2 infection and TYK2 gene might be involved in COVID-19 severity. Nevertheless, no statistically significant association was observed in the COVID-19 fatal outcome or in the stratified analyses (dementia-only and non-dementia strata) for the APOE locus not supporting its involvement in SARS-CoV-2 pathobiology or COVID-19 prognosis.

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.

Neuropsychiatric profiles and conversion to dementia in mild cognitive impairment, a latent class analysis.

Neuropsychiatric symptoms (NPS) have been recently addressed as risk factors of conversion to Alzheimer's disease (AD) and other dementia types in patients diagnosed with Mild Cognitive Impairment (MCI). Our aim was to determine profiles based on the prominent NPS in MCI patients and to explore the predictive value of these profiles on conversion to specific types of dementia. A total of 2137 MCI patients monitored in a memory clinic were included in the study. Four NPS profiles emerged (classes), which were defined by preeminent symptoms: Irritability, Apathy, Anxiety/Depression and Asymptomatic. Irritability and Apathy were predictors of conversion to dementia (HR = 1.43 and 1.56, respectively). Anxiety/depression class showed no risk effect of conversion when compared to Asymptomatic class. Irritability class appeared as the most discriminant neuropsychiatric condition to identify non-AD converters (i.e., frontotemporal dementia, vascular dementia, Parkinson's disease and dementia with Lewy Bodies). The findings revealed that consistent subgroups of MCI patients could be identified among comorbid basal NPS. The preeminent NPS showed to behave differentially on conversion to dementia, beyond AD. Therefore, NPS should be used as early diagnosis facilitators, and should also guide clinicians to detect patients with different illness trajectories in the progression of MCI.