Presenilin-1 mutation position influences amyloidosis, small vessel disease, and dementia with disease stage.

INTRODUCTION: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages. METHODS: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition. RESULTS: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures. DISCUSSION: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials. HIGHLIGHTS: Mutation position influences Aß burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aß burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage.

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways.

Background: To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies. Methods: We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models. Findings: We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aß42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89). Interpretation: Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs. Funding: Proteomic data generation was supported by NIH: RF1AG044546.

Prevalence and Trajectories of Post-COVID-19 Neurological Manifestations: A Systematic Review and Meta-Analysis.

INTRODUCTION: The aim of this systematic review and meta-analysis was to evaluate the prevalence of thirteen neurological manifestations in people affected by COVID-19 during the acute phase and at 3, 6, 9 and 12-month follow-up time points. METHODS: The study protocol was registered with PROSPERO (CRD42022325505). MEDLINE (PubMed), Embase, and the Cochrane Library were used as information sources. Eligible studies included original articles of cohort studies, case-control studies, cross-sectional studies, and case series with ≥5 subjects that reported the prevalence and type of neurological manifestations, with a minimum follow-up of 3 months after the acute phase of COVID-19 disease. Two independent reviewers screened studies from January 1, 2020, to June 16, 2022. The following manifestations were assessed: neuromuscular disorders, encephalopathy/altered mental status/delirium, movement disorders, dysautonomia, cerebrovascular disorders, cognitive impairment/dementia, sleep disorders, seizures, syncope/transient loss of consciousness, fatigue, gait disturbances, anosmia/hyposmia, and headache. The pooled prevalence and their 95% confidence intervals were calculated at the six pre-specified times. RESULTS: 126 of 6,565 screened studies fulfilled the eligibility criteria, accounting for 1,542,300 subjects with COVID-19 disease. Of these, four studies only reported data on neurological conditions other than the 13 selected. The neurological disorders with the highest pooled prevalence estimates (per 100 subjects) during the acute phase of COVID-19 were anosmia/hyposmia, fatigue, headache, encephalopathy, cognitive impairment, and cerebrovascular disease. At 3-month follow-up, the pooled prevalence of fatigue, cognitive impairment, and sleep disorders was still 20% and higher. At six- and 9-month follow-up, there was a tendency for fatigue, cognitive impairment, sleep disorders, anosmia/hyposmia, and headache to further increase in prevalence. At 12-month follow-up, prevalence estimates decreased but remained high for some disorders, such as fatigue and anosmia/hyposmia. Other neurological disorders had a more fluctuating occurrence. DISCUSSION: Neurological manifestations were prevalent during the acute phase of COVID-19 and over the 1-year follow-up period, with the highest overall prevalence estimates for fatigue, cognitive impairment, sleep disorders, anosmia/hyposmia, and headache. There was a downward trend over time, suggesting that neurological manifestations in the early post-COVID-19 phase may be long-lasting but not permanent. However, especially for the 12-month follow-up time point, more robust data are needed to confirm this trend.

Sex and Socioeconomic Disparities in Dementia Risk: A Population Attributable Fractions Analysis in Argentina.

INTRODUCTION, twelve modifiable risk factors (RF) account for 40% of dementia cases worldwide. However, limited data exists on such factors in middle- and low-income countries. We aimed to estimate the population-attributable fractions (PAFs) for the 12 RF in Argentina, assessing changes over a decade, and exploring socioeconomic and sex influences. METHODS, we conducted cross-sectional analyses of the 12 RF from Argentinian surveys conducted in 2009, 2015, and 2018, including 96,321 people. We calculated PAFs, and stratified estimates based on sex and income. RESULTS, we estimated an overall PAF of 59.6%(95%CI=58.9%-60.3%). The largest PAFs were hypertension=9.3%(8.7%-9.9%), physical inactivity=7.4%(6.8%-8.2%), and obesity=7.4%(6.8%-7.9%). Men were more impacted by excessive alcohol, while women by isolation and smoking. Lower income linked to higher PAFs in education, hypertension, and obesity. DISCUSSION, Argentina has a higher PAF for dementia than the world population, with distinct RF distribution. PAF varied by sex and economic status, advocating tailored prevention strategies.

Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease.

BACKGROUND: "Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology. METHODS: We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-ß-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE Îµ4 carrier status, sex, and education. RESULTS: Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG. CONCLUSIONS: We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI.

Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer's disease.

Approximately 5% of Alzheimer's disease cases have an early age at onset (<65 years), with 5-10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer's disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer's disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer's disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer's disease enrolled at the University of California San Francisco Alzheimer's Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer's disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P < 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P < 0.001), Trail Making Test Part B (P < 0.001) and digit span (P < 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer's disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer's disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.

Evaluation and treatment approaches for neurological post-acute sequelae of COVID-19: A consensus statement and scoping review from the global COVID-19 neuro research coalition.

Post-acute neurological sequelae of COVID-19 affect millions of people worldwide, yet little data is available to guide treatment strategies for the most common symptoms. We conducted a scoping review of PubMed/Medline from 1/1/2020-4/1/2023 to identify studies addressing diagnosis and treatment of the most common post-acute neurological sequelae of COVID-19 including: cognitive impairment, sleep disorders, headache, dizziness/lightheadedness, fatigue, weakness, numbness/pain, anxiety, depression and post-traumatic stress disorder. Utilizing the available literature and international disease-specific society guidelines, we constructed symptom-based differential diagnoses, evaluation and management paradigms. This pragmatic, evidence-based consensus document may serve as a guide for a holistic approach to post-COVID neurological care and will complement future clinical trials by outlining best practices in the evaluation and treatment of post-acute neurological signs/symptoms.

Etiology of White Matter Hyperintensities in Autosomal Dominant and Sporadic Alzheimer Disease.

Importance: Increased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors. Objective: To estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes. Design, Setting, and Participants: This cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers-the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer's Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019). Main Outcome and Measures: The main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH. Results: Data from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = -3.1 [P = .002]; ADNI: t = -5.6 [P < .001]; HABS: t = -2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P < .001]; ADNI: t = 9.1 [P < .001]; HABS: t = 5.4 [P < .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P < .001). Conclusions and Relevance: The findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.

Effectiveness of cognitive rehabilitation on mild cognitive impairment using teleneuropsychology.

The COVID-19 pandemic has affected the continuity of cognitive rehabilitation worldwide. However, the use of teleneuropsychology to provide cognitive rehabilitation has contributed significantly to the continuity of the treatment. Objectives: To measure the effects of cognitive telerehabilitation on cognition, neuropsychiatric symptoms, and memory strategies in a cohort of patients with mild cognitive impairment. Methods: A sample of 60 patients with mild cognitive impairment according to Petersen's criteria was randomly divided into two groups: 30 treatment cases and 30 controls (waiting list group). Subjects were matched by age, sex, and Montreal Cognitive Assessment. The treatment group received ten cognitive telerehabilitation sessions of 45 minutes duration once a week. Pre-treatment (week 0) and post-treatment (week 10) measures were assessed for both groups. Different linear mixed models were estimated to test treatment effect (cognitive telerehabilitation vs. controls) on each outcome of interest over time (pre/post-intervention). Results: A significant group (control/treatment) x time (pre/post) interaction revealed that the treatment group at week 10 had better scores in cognitive variables: memory (RAVLT learning trials p=0.030; RAVLT delayed recall p=0.029), phonological fluency (p=0.001), activities of daily living (FAQ p=0.001), satisfaction with memory performance (MMQ satisfaction p=0.004) and use of memory strategies (MMQ strategy p=0.000), as well as, and a significant reduction of affective symptomatology: depression (GDS p=0.000), neuropsychiatric symptoms (NPI-Q p=0.045), forgetfulness (EDO-10 p=0.000), and stress (DAS stress p=0.000). Conclusions: Our study suggests that CTR is an effective intervention.

A pandemia do COVID-19 afetou a continuidade da reabilitação cognitiva em todo o mundo. No entanto, o uso de tele neuropsicologia para a reabilitação cognitiva tem contribuído significativamente para a continuidade do tratamento. Objetivos: Medir os efeitos da tele reabilitação cognitiva na cognição, nos sintomas neuropsiquiátricos e nas estratégias de memória em uma coorte de pacientes com comprometimento cognitivo leve. Métodos: Uma amostra de 60 pacientes com comprometimento cognitivo leve de acordo com os critérios de Petersen foi dividida aleatoriamente em dois grupos: 30 casos de tratamento e 30 controles (grupo de lista de espera). Os assuntos foram pareados por idade, sexo e Avaliação Cognitiva de Montreal. O grupo de tratamento recebeu dez sessões de tele reabilitação cognitiva de 45 minutos de duração uma vez por semana. As medidas pré-tratamento (semana 0) e pós-tratamento (semana 10) foram avaliadas para ambos os grupos. Diferentes modelos lineares mistos foram estimados para testar o efeito do tratamento (tele reabilitação cognitiva vs. controles) em cada desfecho de interesse ao longo do tempo (pré-/pós-intervenção). Resultados: Uma interação significativa grupo (controle/tratamento) x tempo (pré/pós) revelou que o grupo de tratamento teve melhores pontuações em variáveis cognitivas na semana 10: memória (ensaios de aprendizagem RAVLT p = 0,030; RAVLT recordação tardia p=0,029), fluência fonológica (p=0,001), atividades da vida diária (FAQ p=0,001), satisfação com o desempenho da memória (satisfação MMQ p=0,004) e uso de estratégias de memória (estratégia MMQ p=0,000), bem como uma significativa redução da sintomatologia afetiva: depressão (GDS p=0,000), sintomas neuropsiquiátricos (NPI-Q p=0,045), esquecimento (EDO-10 p=0,000) e estresse (DAS estresse p=0,000). Conclusões: Nosso estudo sugere que a CTR é uma intervenção eficaz.

A task force for diagnosis and treatment of people with Alzheimer's disease in Latin America.

Alzheimer's disease (AD) represents a substantial burden to patients, their caregivers, health systems, and society in Latin America and the Caribbean (LAC). This impact is exacerbated by limited access to diagnosis, specialized care, and therapies for AD within and among nations. The region has varied geographic, ethnic, cultural, and economic conditions, which create unique challenges to AD diagnosis and management. To address these issues, the Americas Health Foundation convened a panel of eight neurologists, geriatricians, and psychiatrists from Argentina, Brazil, Colombia, Ecuador, Guatemala, Mexico, and Peru who are experts in AD for a three-day virtual meeting to discuss best practices for AD diagnosis and treatment in LAC and create a manuscript offering recommendations to address identified barriers. In LAC, several barriers hamper diagnosing and treating people with dementia. These barriers include access to healthcare, fragmented healthcare systems, limited research funding, unstandardized diagnosis and treatment, genetic heterogeneity, and varying social determinants of health. Additional training for physicians and other healthcare workers at the primary care level, region-specific or adequately adapted cognitive tests, increased public healthcare insurance coverage of testing and treatment, and dedicated search strategies to detect populations with gene variants associated with AD are among the recommendations to improve the landscape of AD.

Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN).

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.

Acute and subacute clinical markers after sport-related concussion in rugby union players.

OBJECTIVES: The purpose of this study was to investigate the relationship between on-field post-concussion symptoms reported by athletes, on-field neurological signs reported by a trainer or physician, and/or post-concussion symptoms 72 h after brain injury in male rugby players. DESIGN: Cross-sectional study in a Sports Concussion Clinic setting. METHODS: We enrolled 92 adult rugby union players, within the first 72 h after sport concussion. Four scales were measured. Immediate Concussion Sign Checklist (sideline); Immediate Concussion Symptom Checklist (24 h after concussion); Post-Concussion Symptoms Scale and Beck Depression Inventory (in-office 72 h after concussion). RESULTS: Odds ratios revealed that overtly symptomatic athletes were over 2.6 times more likely (p = 0.047) to exhibit post-traumatic amnesia than asymptomatic athletes. There were no differences in terms of on-field loss of consciousness or confusion. Immediate symptoms reported by athletes retrospectively were associated with symptoms reported on the Beck Depression Inventory (odds ratio 2.8; 95 % confidence interval 1.14-6.88), headache (odds ratio 4.9; 95 % confidence interval 1.92-12.79), memory concerns (odds ratio 3.15; 95 % confidence interval 1.06-9.34), pressure in the head (odds ratio 2.8; 95 % confidence interval 1.03-8.08), and visual disturbances (odds ratio 3.9; 95 % confidence interval 1.05-14.50) reported 72 h after sports concussion. CONCLUSIONS: Athletes who were overtly symptomatic after sports concussion were significantly more likely to experience post-traumatic amnesia and two or more on-field concussion signs relative to those athletes who were asymptomatic. Also, players with immediate symptoms reported higher depressive symptoms, somatic symptoms (headache and visual disturbances), and cognitive symptoms.

Location of pathogenic variants in PSEN1 impacts progression of cognitive, clinical, and neurodegenerative measures in autosomal-dominant Alzheimer's disease.

Although pathogenic variants in PSEN1 leading to autosomal-dominant Alzheimer disease (ADAD) are highly penetrant, substantial interindividual variability in the rates of cognitive decline and biomarker change are observed in ADAD. We hypothesized that this interindividual variability may be associated with the location of the pathogenic variant within PSEN1. PSEN1 pathogenic variant carriers participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study were grouped based on whether the underlying variant affects a transmembrane (TM) or cytoplasmic (CY) protein domain within PSEN1. CY and TM carriers and variant non-carriers (NC) who completed clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF) as part of their participation in DIAN were included in this study. Linear mixed effects models were used to determine differences in clinical, cognitive, and biomarker measures between the NC, TM, and CY groups. While both the CY and TM groups were found to have similarly elevated Aß compared to NC, TM carriers had greater cognitive impairment, smaller hippocampal volume, and elevated phosphorylated tau levels across the spectrum of pre-symptomatic and symptomatic phases of disease as compared to CY, using both cross-sectional and longitudinal data. As distinct portions of PSEN1 are differentially involved in APP processing by γ-secretase and the generation of toxic ß-amyloid species, these results have important implications for understanding the pathobiology of ADAD and accounting for a substantial portion of the interindividual heterogeneity in ongoing ADAD clinical trials.

Design of a Non-Interventional Study to Assess Neurologists' Perspectives and Pharmacological Treatment Decisions in Early Alzheimer's Disease.

INTRODUCTION: The current therapeutic landscape of Alzheimer's disease (AD) is evolving rapidly. Our treatment options include new anti-amyloid-ß protein disease-modifying therapies (DMTs) that decrease cognitive decline in patients with early AD (prodromal and mild AD dementia). Despite these advances, we have limited information on how neurologists would apply the results of recent DMT trials to make treatment decisions. Our goal is to identify factors associated with the use of new AD DMTs among neurologists applying concepts from behavioral economics. METHODS: This non-interventional, cross-sectional, web-based study will assess 400 neurologists with expertise in AD from across Spain. Participants will start by completing demographic information, practice settings, and a behavioral battery to address their tolerance to uncertainty and risk preferences. Participants will then be presented with 10 simulated case scenarios or vignettes of common encounters in patients with early AD to evaluate treatment initiation with anti-amyloid-ß DMTs (e.g., aducanumab, lecanemab, etc.). The primary outcomes will be therapeutic inertia and suboptimal decisions. Discrete choice experiments will be used to determine the weight of factors influencing treatment choices. RESULTS: The results of this study will provide new insights into a better understanding of the most relevant factors associated with therapeutic decisions on the use of DMTs, assessing how neurologists handle uncertainty when making treatment choices, and identifying the prevalence of therapeutic inertia in the management of early AD.

Change in Cerebrospinal Fluid Tau Microtubule Binding Region Detects Symptom Onset, Cognitive Decline, Tangles, and Atrophy in Dominantly Inherited Alzheimer's Disease.

OBJECTIVE: Identifying cerebrospinal fluid measures of the microtubule binding region of tau (MTBR-tau) species that reflect tau aggregation could provide fluid biomarkers that track Alzheimer's disease related neurofibrillary tau pathological changes. We examined the cerebrospinal fluid (CSF) MTBR-tau species in dominantly inherited Alzheimer's disease (DIAD) mutation carriers to assess the association with Alzheimer's disease (AD) biomarkers and clinical symptoms. METHODS: Cross-sectional and longitudinal CSF from 229 DIAD mutation carriers and 130 mutation non-carriers had sequential characterization of N-terminal/mid-domain phosphorylated tau (p-tau) followed by MTBR-tau species and tau positron emission tomography (tau PET), other soluble tau and amyloid biomarkers, comprehensive clinical and cognitive assessments, and brain magnetic resonance imaging of atrophy. RESULTS: CSF MTBR-tau species located within the putative "border" region and one species corresponding to the "core" region of aggregates in neurofibrillary tangles (NFTs) increased during the presymptomatic stage and decreased during the symptomatic stage. The "border" MTBR-tau species were associated with amyloid pathology and CSF p-tau; whereas the "core" MTBR-tau species were associated stronger with tau PET and CSF measures of neurodegeneration. The ratio of the border to the core species provided a continuous measure of increasing amounts that tracked clinical progression and NFTs. INTERPRETATION: Changes in CSF soluble MTBR-tau species preceded the onset of dementia, tau tangle increase, and atrophy in DIAD. The ratio of 4R-specific MTBR-tau (border) to the NFT (core) MTBR-tau species corresponds to the pathology of NFTs in DIAD and change with disease progression. The dynamics between different MTBR-tau species in the CSF may serve as a marker of tau-related disease progression and target engagement of anti-tau therapeutics. ANN NEUROL 2023;93:1158-1172.

Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study.

Background: Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. Methods: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. Results: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. Conclusions: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. Funding: This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer's Association (SG-20-690363-DIAN).

The brains of people with advanced Alzheimer's disease often look older than expected based on the patients' actual age. This 'brain age gap' (how old a brain appears compared to the person's chronological age) can be calculated thanks to machine learning algorithms which analyse images of the organ to detect changes related to aging. Traditionally, these models have relied on images of the brain structure, such as the size and thickness of various brain areas; more recent models have started to use activity data, such as how different brain regions work together to form functional networks. While the brain age gap is a useful measure for researchers who investigate aging and disease, it is not yet helpful for clinicians. For example, it is unclear whether the machine learning algorithm could detect changes in the brains of individuals in the initial stages of Alzheimer's disease, before they start to manifest cognitive symptoms. Millar et al. explored this question by testing whether models which incorporate structural and activity data could be more sensitive to these early changes. Three machine learning algorithms (relying on either structural data, activity data, or combination of both) were used to predict the brain ages of participants with no sign of disease; with biological markers of Alzheimer's disease but preserved cognitive functions; and with marked cognitive symptoms of the condition. Overall, the combined model was slightly better at predicting the brain age of healthy volunteers, and all three models indicated that patients with dementia had a brain which looked older than normal. For this group, the model based on structural data was also able to make predictions which reflected the severity of cognitive decline. Crucially, the algorithm which used activity data predicted that, in individuals with biological markers of Alzheimer's disease but no cognitive impairment, the brain looked in fact younger than chronological age. Exactly why this is the case remains unclear, but this signal may be driven by neural processes which unfold in the early stages of the disease. While more research is needed, the work by Millar et al. helps to explore how various types of machine learning models could one day be used to assess and predict brain health.

Cross-sectional and longitudinal comparisons of biomarkers and cognition among asymptomatic middle-aged individuals with a parental history of either autosomal dominant or late-onset Alzheimer's disease.

BACKGROUND: Comparisons of late-onset Alzheimer's disease (LOAD) and autosomal dominant AD (ADAD) are confounded by age. METHODS: We compared biomarkers from cerebrospinal fluid (CSF), magnetic resonance imaging, and amyloid imaging with Pittsburgh Compound-B (PiB) across four groups of 387 cognitively normal participants, 42 to 65 years of age, in the Dominantly Inherited Alzheimer Network (DIAN) and the Adult Children Study (ACS) of LOAD: DIAN mutation carriers (MCs) and non-carriers (NON-MCs), and ACS participants with a positive (FH+) and negative (FH-) family history of LOAD. RESULTS: At baseline, MCs had the lowest age-adjusted level of CSF Aß42 and the highest levels of total and phosphorylated tau-181, and PiB uptake. Longitudinally, MC had similar increase in PiB uptake to FH+, but drastically faster decline in hippocampal volume than others, and was the only group showing cognitive decline. DISCUSSION: Preclinical ADAD and LOAD share many biomarker signatures, but cross-sectional and longitudinal differences may exist.

Biomarkers for dementia in Latin American countries: Gaps and opportunities.

Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we reported a survey to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The results show that neuroimaging is the most used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, the region holds a great potential to advance dementia biomarkers research. Considering the unique contributions that LAC could make to this growing field, we highlight the urgent need to expand biomarker research. These insights allowed us to propose an action plan that addresses the recommendations for a biomarker framework recently proposed by regional experts.

Pattern and implications of neurological examination findings in autosomal dominant Alzheimer disease.

INTRODUCTION: As knowledge about neurological examination findings in autosomal dominant Alzheimer disease (ADAD) is incomplete, we aimed to determine the frequency and significance of neurological examination findings in ADAD. METHODS: Frequencies of neurological examination findings were compared between symptomatic mutation carriers and non mutation carriers from the Dominantly Inherited Alzheimer Network (DIAN) to define AD neurological examination findings. AD neurological examination findings were analyzed regarding frequency, association with and predictive value regarding cognitive decline, and association with brain atrophy in symptomatic mutation carriers. RESULTS: AD neurological examination findings included abnormal deep tendon reflexes, gait disturbance, pathological cranial nerve examination findings, tremor, abnormal finger to nose and heel to shin testing, and compromised motor strength. The frequency of AD neurological examination findings was 65.1%. Cross-sectionally, mutation carriers with AD neurological examination findings showed a more than two-fold faster cognitive decline and had greater parieto-temporal atrophy, including hippocampal atrophy. Longitudinally, AD neurological examination findings predicted a significantly greater decline over time. DISCUSSION: ADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs.