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.

Huntingtin CAG repeats in neuropathologically confirmed tauopathies: Novel insights.

Previous studies have suggested a relationship between the number of CAG triplet repeats in the HTT gene and neurodegenerative diseases not related to Huntington's disease (HD). This study seeks to investigate whether the number of CAG repeats of HTT is associated with the risk of developing certain tauopathies and its influence as a modulator of the clinical and neuropathological phenotype. Additionally, it aims to evaluate the potential of polyglutamine staining as a neuropathological screening. We genotyped the HTT gene CAG repeat number and APOE-ℰ isoforms in a cohort of patients with neuropathological diagnoses of tauopathies (n=588), including 34 corticobasal degeneration (CBD), 98 progressive supranuclear palsy (PSP) and 456 Alzheimer's disease (AD). Furthermore, we genotyped a control group of 1070 patients, of whom 44 were neuropathologic controls. We identified significant differences in the number of patients with pathological HTT expansions in the CBD group (2.7%) and PSP group (3.2%) compared to control subjects (0.2%). A significant increase in the size of the HTT CAG repeats was found in the AD compared to the control group, influenced by the presence of the Apoliprotein E (APOE)-ℰ4 isoform. Post-mortem assessments uncovered tauopathy pathology with positive polyglutamine aggregates, with a slight predominance in the neostriatum for PSP and CBD cases and somewhat greater limbic involvement in the AD case. Our results indicated a link between HTT CAG repeat expansion with other non-HD pathology, suggesting they could share common neurodegenerative pathways. These findings support that genetic or histological screening for HTT repeat expansions should be considered in tauopathies.

FACEmemory®, an Innovative Online Platform for Episodic Memory Pre-Screening: Findings from the First 3,000 Participants.

BACKGROUND: The FACEmemory® online platform comprises a complex memory test and sociodemographic, medical, and family questions. This is the first study of a completely self-administered memory test with voice recognition, pre-tested in a memory clinic, sensitive to Alzheimer's disease, using information and communication technologies, and offered freely worldwide. OBJECTIVE: To investigate the demographic and clinical variables associated with the total FACEmemory score, and to identify distinct patterns of memory performance on FACEmemory. METHODS: Data from the first 3,000 subjects who completed the FACEmemory test were analyzed. Descriptive analyses were applied to demographic, FACEmemory, and medical and family variables; t-test and chi-square analyses were used to compare participants with preserved versus impaired performance on FACEmemory (cut-off = 32); multiple linear regression was used to identify variables that modulate FACEmemory performance; and machine learning techniques were applied to identify different memory patterns. RESULTS: Participants had a mean age of 50.57 years and 13.65 years of schooling; 64.07% were women, and 82.10% reported memory complaints with worries. The group with impaired FACEmemory performance (20.40%) was older, had less schooling, and had a higher prevalence of hypertension, diabetes, dyslipidemia, and family history of neurodegenerative disease than the group with preserved performance. Age, schooling, sex, country, and completion of the medical and family history questionnaire were associated with the FACEmemory score. Finally, machine learning techniques identified four patterns of FACEmemory performance: normal, dysexecutive, storage, and completely impaired. CONCLUSIONS: FACEmemory is a promising tool for assessing memory in people with subjective memory complaints and for raising awareness about cognitive decline in the community.

Automated Classification of Cognitive Decline and Probable Alzheimer's Dementia Across Multiple Speech and Language Domains.

BACKGROUND: Decline in language has emerged as a new potential biomarker for the early detection of Alzheimer's disease (AD). It remains unclear how sensitive language measures are across different tasks, language domains, and languages, and to what extent changes can be reliably detected in early stages such as subjective cognitive decline (SCD) and mild cognitive impairment (MCI). METHOD: Using a scene construction task for speech elicitation in a new Spanish/Catalan speaking cohort (N = 119), we automatically extracted features across seven domains, three acoustic (spectral, cepstral, and voice quality), one prosodic, and three from text (morpholexical, semantic, and syntactic). They were forwarded to a random forest classifier to evaluate the discriminability of participants with probable AD dementia, amnestic and nonamnestic MCI, SCD, and cognitively healthy controls. Repeated-measures analyses of variance and paired-samples Wilcoxon signed-ranks test were used to assess whether and how performance differs significantly across groups and linguistic domains. RESULTS: The performance scores of the machine learning classifier were generally satisfactorily high, with the highest scores over .9. Model performance was significantly different for linguistic domains (p < .001), and speech versus text (p = .043), with speech features outperforming textual features, and voice quality performing best. High diagnostic classification accuracies were seen even within both cognitively healthy (controls vs. SCD) and MCI (amnestic and nonamnestic) groups. CONCLUSION: Speech-based machine learning is powerful in detecting cognitive decline and probable AD dementia across a range of different feature domains, though important differences exist between these domains as well. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.23699733.

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.

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.

Differences in macular vessel density in the superficial plexus across cognitive impairment: the NORFACE cohort.

Optical coherence tomography angiography (OCT-A) allows the detection of retinal vessel density (VD) loss, which is a reflection of brain vascular pathology. We aimed to investigate differences in macular VD in the superficial plexus in a large cohort of individuals cognitively unimpaired (CU), with mild cognitive impairment due to Alzheimer´s disease (MCI-AD), MCI due to cerebrovascular pathology (MCI-Va), probable Alzheimer´s disease dementia (ADD) and Vascular Dementia (VaD). Clinical, demographical, ophthalmological and OCT-A data from the Neuro-ophthalmology Research at Fundació ACE (NORFACE) project were analyzed. Differences of macular VD in four quadrants (superior, nasal, inferior and temporal) among the five diagnostic groups were assessed in a multivariate regression model, adjusted by age, sex, education, hypertension, diabetes mellitus, heart disease and stroke. The study cohort comprised 672 participants: 128 CU, 120 MCI-AD, 111 MCI-Va, 257 ADD and 56 VaD. Regression analysis showed a significantly higher VD in the temporal quadrant in MCI-AD compared to CU participants (49.05 ± 4.91 vs 47.27 ± 4.17, p = 0.02, d = 0.40), and a significantly lower VD in the inferior quadrant in MCI-Va compared to CU participants (48.70 ± 6.57 vs 51.27 ± 6.39, p = 0.02, d = 0.40). Individuals with heart disease presented significantly lower VD in the inferior quadrant than those without (p = 0.01). The interaction of sex and diagnosis had no effect in differentiating VD. Mini-Mental State Examination (MMSE) scores were not correlated to VD (all r < 0.16; p > 0.07). In conclusion, our study showed that the MCI-AD and MCI-Va groups had significant differences in macular VD in opposite directions in the temporal and inferior quadrants, respectively, compared to CU participants, suggesting that macular VD might be able to differentiate two pathogenic pathways (AD- and cerebrovascular-related) in early stages of cognitive decline.

Sex, Neuropsychiatric Profiles, and Caregiver Burden in Alzheimer's Disease Dementia: A Latent Class Analysis.

BACKGROUND: Neuropsychiatric symptoms (NPS) in Alzheimer's disease (AD) can be disruptive for patients and their families. OBJECTIVE: We aimed to classify patients based on NPS and to explore the relationship of these classes with sex and with caregiver burden. METHODS: The study cohort comprised individuals with AD dementia diagnosed at Ace Alzheimer Center in Barcelona, Spain, between 2011-2020. NPS were ascertained by using the Neuropsychiatric Inventory-Questionnaire. Latent class analysis was used to identify clusters of individuals sharing a similar NPS profile. We evaluated the caregiver burden using the Zarit Burden Interview. Multivariable regression models were used to obtain adjusted estimates of the association between sex, NPS classes, and caregiver burden. RESULTS: A total of 1,065 patients with AD dementia and their primary caregivers were included. We classified patients into five different classes according to their NPS profile: "Affective", "High-behavioral-disturbance", "Negative-affect", "Affective/deliriant", and "Apathy". We found that age, sex, and type of AD diagnosis differed greatly across classes. We found that patients from the "High-behavioral-disturbance" (OR = 2.56, 95% CI: 1.00-6.56), "Negative-affect" (OR = 2.72, 95% CI: 1.26-3.64), and "Affective/deliriant" (OR = 2.14, 95% CI: 1.26-3.64) classes were over two times more likely to have a female caregiver than those in "Apathy" class. These three classes were also the ones associated to the greatest caregiver burden in the adjusted analyses, which seems to explain the increased burden observed among female caregivers. CONCLUSION: Caregiver burden is highly dependent on the patient's NPS profiles. Female caregivers provide care to patients that pose a greater burden, which makes them more susceptible to become overwhelmed.

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.

Intermediate and Expanded HTT Alleles and the Risk for α-Synucleinopathies.

BACKGROUND: Previous studies suggest a link between CAG repeat number in the HTT gene and non-Huntington neurodegenerative diseases. OBJECTIVE: The aim is to analyze whether expanded HTT CAG alleles and/or their size are associated with the risk for developing α-synucleinopathies or their behavior as modulators of the phenotype. METHODS: We genotyped the HTT gene CAG repeat number and APOE-Ɛ isoforms in a case-control series including patients with either clinical or neuropathological diagnosis of α-synucleinopathy. RESULTS: We identified three Parkinson's disease (PD) patients (0.30%) and two healthy controls (0.19%) carrying low-penetrance HTT repeat expansions whereas none of the dementia with Lewy bodies (DLB) or multisystem atrophy (MSA) patients carried pathogenic HTT expansions. In addition, a clear increase in the number of HTT CAG repeats was found among DLB and PD groups influenced by the male gender and also by the APOE4 allele among DLB patients. HTT intermediate alleles' (IAs) distribution frequency increased in the MSA group compared with controls (8.8% vs. 3.9%, respectively). These differences were indeed statistically significant in the MSA group with neuropathological confirmation. Two MSA HTT CAG IAs carriers with 32 HTT CAG repeats showed isolated polyQ inclusions in pons and basal nuclei, which are two critical structures in the neurodegeneration of MSA. CONCLUSIONS: Our results point to a link between HTT CAG number, HTT IAs, and expanded HTT CAG repeats with other non-HD brain pathology and support the hypothesis that they can share common neurodegenerative pathways. © 2022 International Parkinson and Movement Disorder Society.

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.

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.

From Face-to-Face to Home-to-Home: Validity of a Teleneuropsychological Battery.

BACKGROUND: Over the last decade, teleneuropsychology has increased substantially. There is a need for valid neuropsychological batteries to be administered home-to-home. Since 2006, the neuropsychological battery of Fundació ACE (NBACE) has been administered face-to-face in our clinical settings. Recently, we adapted the NBACE for teleneuropsychology use to be administered home-to-home (NBACEtn). OBJECTIVE: The aims of the present study are: 1) to determine the home-to-home NBACE equivalence compared to its original face-to-face version; and 2) to examine home-to-home NBACE discriminant capacity by differentiating among cognitively healthy, mild cognitive impairment, or mild dementia subjects and comparing it with the face-to-face version. METHODS: Data from 338 individuals assessed home-to-home (NBACEtn) were contrasted with 7,990 participants assessed with its face-to-face version (NBACE). Exploratory and confirmatory factorial structure, and invariance analysis of the two versions of the battery were performed. RESULTS: Exploratory and confirmatory factor analysis supported the four-factor model (attention, memory, executive, and visuospatial/constructional functions). Configural, metric, and scalar measurement invariance was found between home-to-home and face-to-face NBACE versions. Significant differences in most of the neuropsychological variables assessed were observed between the three clinical groups in both versions of administration. No differences were found between the technological devices used by participants (computer or tablet and mobile devices). CONCLUSION: For the first time, invariance analysis findings were addressed by determining a teleneuropsychological battery's equivalence in comparison with its face-to-face version. This study amplifies the neuropsychological assessment's applicability using a home-to-home format, maintaining the original measure's structure, interpretability, and discriminant capacity.

The role of sex and gender in the selection of Alzheimer patients for clinical trial pre-screening.

BACKGROUND: Alzheimer disease (AD) is a progressive neurodegenerative disorder affecting the elderly with a prevalence of 7.1% in women and 3.3% in men. Sex-related patterns have been reported in prognosis, biomarker status, and risk factors. Despite this, the interaction of sex has received limited attention, with AD trials persistently recruiting lower numbers of women than the population distribution and a lack of information on the sex-disaggregated effects of anti-dementia therapies. This is the first study aiming to identify the role of sex in the selection for screening in AD clinical trials. METHODS: This cross-sectional study provides a comprehensive analysis of screening eligibility according to a set of pre-selection criteria currently applied at Fundació ACE memory clinic for a more efficient trial screening process. A cohort of 6667 women and 2926 men diagnosed with AD dementia (55%) or mild cognitive impairment (45%) was analyzed. We also assessed the frequencies of men and women effectively screened for trial enrolment over a period of 10 years. Additionally, data from AddNeuroMed study was used to explore trends in eligibility based on the education criteria. RESULTS: Women showed a significantly lower chance of being eligible for screening than men (OR = 1.26; p < 0.01). This imbalance was confirmed by a lower frequency of women screened for enrolment compared to the study population (63.0% vs. 69.5%). Education was revealed as the key criterion contributing to this unbalance, with men showing over twice the chance of being screened compared with women (OR = 2.25, p < 0.01). Education-based differences were greater in earlier born patients, but the gap narrowed and achieved balance with increasing year of birth. This observation was replicated using data from other European populations included in AddNeuroMed study. Comorbidity was the most limiting criterion with sex differences in frequencies and significant discrimination against the selection of men (OR = 0.86, p < 0.01). CONCLUSIONS: The large number of low-educated elderly women with AD demands for a sex-focused approach in clinical research. New assessment tools insensitive to education level should be developed to enable a proportional representation of women. Although this gender education gap is mostly inexistent in developed countries, economic or cultural factors may lead to different scenarios in other regions. Overlooking the impact of sex may lead to a handicap in AD research with a direct adverse impact on women's health.

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.

Biomarker-Based Risk Prediction of Alzheimer's Disease Dementia in Mild Cognitive Impairment: Psychosocial, Ethical, and Legal Aspects.

BACKGROUND: Today, a growing number of individuals with mild cognitive impairment (MCI) wish to assess their risk of developing Alzheimer's disease (AD) dementia. The expectations as well as the effects on quality of life (QoL) in MCI patients and their close others through biomarker-based dementia risk estimation are not well studied. OBJECTIVE: The PreDADQoL project aims at providing empirical data on effects of such prediction on QoL and at developing an ethical and legal framework of biomarker-based dementia risk estimation in MCI. METHODS: In the empirical study, 100 MCI-patients and their close others will be recruited from two sites (Germany and Spain). They receive standardized counselling on cerebrospinal fluid (CSF) biomarker-based prediction of AD dementia and a risk disclosure based on their AD biomarker status. A mixed methods approach will be applied to assess outcomes. RESULTS: The pilot-study yielded a specification of the research topics and newly developed questionnaires for the main assessment. Within this binational quantitative and qualitative study, data on attitudes and expectations toward AD risk prediction, QoL, risk communication, coping strategies, mental health, lifestyle changes, and healthcare resource utilization will be obtained. Together with the normative part of the project, an empirically informed ethical and legal framework for biomarker-based dementia risk estimation will be developed. CONCLUSION: The empirical research of the PreDADQoL study together with the ethical and legal considerations and implications will help to improve the process of counselling and risk disclosure and thereby positively affect QoL and health of MCI-patients and their close others in the context of biomarker-based dementia risk estimation.

Interaction of neuropsychiatric symptoms with APOE ε4 and conversion to dementia in MCI patients in a Memory Clinic.

To date, very few studies have been focused on the impact of the convergence of neuropsychiatric symptoms (NPS) and APOE ε4 on the conversion to dementia in patients with Mild Cognitive Impairment patients (MCI), and none has been based in a clinical setting. The objective of the study is to determine the predictive value of additive and multiplicative interactions of NPS and APOE ε4 status on the prediction of incident dementia among MCI patients monitored in a Memory Clinic. 1512 patients (aged 60 and older) with prevalent MCI were followed for a mean of 2 years. Neuropsychiatric symptoms were assessed at baseline using the Neuropsychiatric Inventory Questionnaire. Cox proportional hazards models were calculated. Additive interactions for depression, apathy, anxiety, agitation, appetite, or irritability and a positive ε4 carrier status were obtained, significantly increasing the hazard ratios of incident dementia (HR range 1.3-2.03). Synergistic interactions between NPS and APOE ε4 are identified among MCI patients when predicting incident dementia. The combination of the behavioral status and the genetic trait could be considered a useful strategy to identify the most vulnerable MCI patients to dementia conversion in a Memory Clinic.