Alzheimer's Disease Dementia Research Articles

Incidence and Prevalence of Alzheimer's Disease in Medicare Beneficiaries.

The availability of anti-amyloid therapy for mild cognitive impairment (MCI) due to Alzheimer's disease and mild Alzheimer's dementia (AD) has underscored the need for realistic estimates of the population with AD/MCI within the healthcare system to assure adequate preparedness. We hypothesize that administrative databases can provide real-world epidemiologic estimates reflecting the population with diagnosed (known) MCI and AD. This study was conducted to estimate diagnostic incidence and prevalence of AD and all-cause MCI among the Medicare fee-for-service (FFS) and Medicare Advantage (MA) beneficiaries in the United States. This was a retrospective analysis of Medicare beneficiaries (aged 65 and older) with identified diagnoses of AD/MCI based on ≥2 diagnostic codes ≥30 days apart. Incidence/prevalence estimates were reported per 10,000 person-years. In FFS, AD incidence (2008-2018) decreased (138 to 104); MCI incidence increased (8 to 47), but the sum (MCI+AD) was relatively stable (146 to 151). Prevalence (2008-2017) increased for AD (318 to 354), and MCI (13 to 99). In MA (2016) epidemiological estimates were consistent with FFS. In 2017, older age, female sex and the Northeastern region were consistently associated with higher AD/MCI prevalence among FFS beneficiaries. In FFS, AD/MCI diagnostic prevalence increased over 10 years, especially for MCI; prevalence estimates in MA (2016) were comparable. Diagnostic prevalence in 2016 (FFS+MA) was 3.4% for AD and 0.85% for MCI. Our findings address the reality of Alzheimer's disease in clinical practice in the United States that is confronted by healthcare professionals, payors, healthcare decision-makers, patients, and caregivers, and may offer a realistic gauge for patient triage for treatment, healthcare resource allocation, and health-systems' operational prioritization. With the availability of anti-amyloid treatments, we anticipate that the population with diagnosed MCI/AD within the Medicare database may rise over time; therefore, periodic updates of incidence/prevalence estimates may provide support for timely healthcare decision-making.

Advancements in Immunity and Dementia Research: Highlights from the 2023 AAIC Advancements: Immunity Conference.

The immune system is a key player in the onset and progression of neurodegenerative disorders. While brain resident immune cell-mediated neuroinflammation and peripheral immune cell (eg, T cell) infiltration into the brain have been shown to significantly contribute to Alzheimer's disease (AD) pathology, the nature and extent of immune responses in the brain in the context of AD and related dementias (ADRD) remain unclear. Furthermore, the roles of the peripheral immune system in driving ADRD pathology remain incompletely elucidated. In March of 2023, the Alzheimer's Association convened the Alzheimer's Association International Conference (AAIC), Advancements: Immunity, to discuss the roles of the immune system in ADRD. A wide range of topics were discussed, such as animal models that replicate human pathology, immune-related biomarkers and clinical trials, and lessons from other fields describing immune responses in neurodegeneration. This manuscript presents highlights from the conference and outlines avenues for future research on the roles of immunity in neurodegenerative disorders. HIGHLIGHTS: The immune system plays a central role in the pathogenesis of Alzheimer's disease. The immune system exerts numerous effects throughout the brain on amyloid-beta, tau, and other pathways. The 2023 AAIC, Advancements: Immunity, encouraged discussions and collaborations on understanding the role of the immune system.

Curation and validation of electronic medical record-based dementia diagnoses in the VA Million Veteran Program.

The age distribution and diversity of the VA Million Veteran Program (MVP) cohort make it a valuable resource for studying the genetics of Alzheimer's disease (AD) and related dementias (ADRD). We present and evaluate the performance of several International Classification of Diseases (ICD) code-based classification algorithms for AD, ADRD, and dementia for use in MVP genetic studies and other studies using VA electronic medical record (EMR) data. These were benchmarked relative to existing ICD algorithms and AD-medication-identified cases. We used chart review of n = 103 MVP participants to evaluate diagnostic utility of the algorithms. Suitability for genetic studies was examined by assessing association with APOE ε4, the strongest genetic AD risk factor, in a large MVP cohort (n = 286 K). The newly developed MVP-ADRD algorithm performed well, comparable to the existing PheCode dementia algorithm (Phe-Dementia) in terms of sensitivity (0.95 and 0.95) and specificity (0.65 and 0.70). The strongest APOE ε4 associations were observed in cases identified using MVP-ADRD and Phe-Dementia augmented with medication-identified cases (MVP-ADRD or medication, p = 3.6 ×10-290; Phe-Dementia or medication, p = 1.4 ×10-290). Performance was improved when cases were restricted to those with onset age ≥60. We found that our MVP-developed ICD-based algorithms had good performance in chart review and generated strong genetic signals, especially after inclusion of medication-identified cases. Ultimately, our MVP-derived algorithms are likely to have good performance in the broader VA, and their performance may also be suitable for use in other large-scale EMR-based biobanks in the absence of definitive biomarkers such as amyloid-PET and cerebrospinal fluid biomarkers.

Dancing through neurocognitive changes: dance/movement therapy supporting caregivers and people living with Alzheimer's and other dementias

Dancing through neurocognitive changes: dance/movement therapy supporting caregivers and people living with Alzheimer's and other dementias

Health Disparities in Hospice-Home Health Transitions in Hispanic Older Adults With Co-occurring Dementia and Cardiovascular Disease.

In the US, nearly one-third of skilled home health (HH) patients and nearly one-half of hospice patients live with Alzheimer's disease and related dementias (ADRD). Hispanic older adults are more likely to live with ADRD than white non-Hispanic older adults. Persons with ADRD, compared to their counterparts without ADRD, have a prolonged trajectory of decline and experience multiple care transitions between health care settings, bringing risks for poor outcomes. Little is known about patients transitioning between skilled HH and hospice. We aimed to determine if there were demographic and/or diagnostic variables associated with the frequency of transitions between skilled HH and hospice. In a cross-sectional study, we used Medicare claims data from 2020 and descriptive statistics including Chi-Square to determine demographic and diagnostic differences in frequency of care transitions between skilled HH and hospice for older adults with ADRD. In N = 272,323 hospice episodes, Hispanic older adult beneficiaries with ADRD and co-occurring cardiovascular disease (CVD) had significantly higher rates of care transitions from hospice to skilled HH (P = 0.037) than other racial and ethnic groups with both diagnoses. Our findings provide evidence of disparities in care transitions from hospice to skilled HH for Hispanic older adults living with ADRD and CVD. Multiple factors may impact this result: Hospice low quality scores, insufficient advance care planning and understanding of hospice philosophy, and policies affecting eligibility. Implications include policy change and greater coordination of care for older adults with co-occurring ADRD and CVD, with attention to health equity.

LD-informed deep learning for Alzheimer's gene loci detection using WGS data.

The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk. The Deep-Block was applied to a large-scale whole genome sequencing (WGS) dataset from the Alzheimer's Disease Sequencing Project (ADSP), comprising 7,416 non-Hispanic white participants (3,150 cognitively normal older adults (CN), 4,266 AD). 30,218 LD blocks were identified and then ranked based on their relevance with Alzheimer's disease. Subsequently, the Deep-Block identified novel SNPs within the top 1,500 LD blocks and confirmed previously known variants, including APOE rs429358 and rs769449. Expression Quantitative Trait Loci (eQTL) analysis across 13 brain regions provided functional evidence for the identified variants. The results were cross-validated against established AD-associated loci from the European Alzheimer's and Dementia Biobank (EADB) and the GWAS catalog. The Deep-Block framework effectively processes large-scale high throughput sequencing data while preserving SNP interactions during dimensionality reduction, minimizing bias and information loss. The framework's findings are supported by tissue-specific eQTL evidence across brain regions, indicating the functional relevance of the identified variants. Additionally, the Deep-Block approach has identified both known and novel genetic variants, enhancing our understanding of the genetic architecture and demonstrating its potential for application in large-scale sequencing studies. Keywords: Alzheimer's disease, Whole-Genome Sequencing, Linkage Disequilibrium, Deep Learning, Genetic Loci, Imputation Methods.

White matter hyperintensities and cholinergic degeneration as Lewy body disease.

Although basal forebrain (BF) cholinergic degeneration and white matter hyperintensities (WMHs) are important in neurodegeneration in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), their relationships with dopaminergic degeneration and clinical manifestations remain unclear. A total of 407 patients with cognitive impairment meeting the diagnostic criteria for AD, DLB, or both (AD+DLB) were assessed. All participants underwent 3T MRI, dopamine transporter (DAT) positron emission tomography, neuropsychological tests, and assessments for parkinsonism, cognitive fluctuation, visual hallucination, and rapid eye movement sleep behavior disorder (RBD). General linear and logistic regression models were used to investigate the relationships among BF volume, DAT uptake in the anterior caudate (DAT-AC), WMH volumes in anterior, posterior, periventricular, and deep regions, and clinical manifestations. DAT-AC was positively associated with BF volume and negatively associated with anterior periventricular WMH volume, but not with deep WMHs. Both deep and periventricular WMHs volumes were associated with hypertension and the number of microbleeds and lacunae. Lower BF volume and DAT-AC were independently associated with increased risk of cognitive fluctuation and visual hallucination, whereas lower DAT-AC was additionally associated with increased risk of RBD and greater parkinsonian severity. Both lower BF volume and DAT-AC were independently associated with widespread cognitive impairment, whereas higher anterior periventricular WMH volume was associated with executive dysfunction. BF cholinergic degeneration and anterior periventricular WMHs are closely associated with dopaminergic degeneration. Anterior periventricular WMHs may represent axonal alterations caused by the interplay between Lewy body-related degeneration and vascular pathologies.

Communicative and Methodological Challenges Related to Collecting Data with Older Adults with Dementia in Senior Living Communities During the COVID-19 Pandemic.

The COVID-19 pandemic presented significant challenges to researchers collecting data with older adults, particularly older adults with Alzheimer's disease and related dementias (ADRD). The goal of this article is to articulate the communicative and methodological challenges and lessons learned from collecting data with older adults in senior living communities with mild cognitive impairment and ADRD and their adult children (who were geographically separated) during the pandemic. Communication was much more than what we were studying; it was essential to the success and ethical implementation of our research. We were working with a vulnerable population during a pandemic where recruitment, consent, and data collection required heightened and adapted communication strategies to reduce confusion, promote safety, and ensure data could be collected in an effective manner. The way we communicated with the participants, their networks, and the senior living communities was crucial to establishing strong human connections and subsequently successful data collection.

Association between dietary inflammatory index score and incident dementia.

We evaluated whether higher Dietary Inflammatory Index (DII) scores were associated with increased incidence of all-cause dementia and Alzheimer's disease (AD) dementia over 22.3 years of follow-up in the community-based Framingham Heart Study Offspring cohort. One thousand four hundred eighty-seven participants (mean±standard deviation, age in years 69±6) completed food frequency questionnaires (FFQs) and had incident all-cause dementia and AD surveillance data available. Two hundred forty-six participants developed all-cause dementia (including AD, n=187) over a median follow-up time of 13.1 years. Higher DII scores, averaged across a maximum of three timepoints, were associated with an increased incidence of all-cause dementia and AD after adjustment for demographic, lifestyle, and clinical covariates (hazard ratio [HR] 1.21, 95% confidence interval [CI] 1.10-1.33, P<0.001; HR 1.20, 95% CI: 1.07-1.34d, P=0.001, respectively). Higher DII scores were associated with a higher risk of incident all-cause dementia and AD. Although these promising findings need to be replicated and further validated, our results suggest that diets that correlate with low DII scores may prevent late-life dementia. Higher Dietary Inflammatory Index (DII) scores were associated with an increased incidence of all-cause dementia. Higher DII scores were associated with an increased incidence of Alzheimer's disease dementia. Diets that correlate with low DII scores may prevent late-life dementia.

Developing and applying potentially scalable recruitment strategies to accelerate ADRD research participation of Black adults.

More than 2 million older Americans from underrepresented racial and ethnic minority groups (URGs) have early-stage Alzheimer's disease and related dementias (ADRD). There are very few scalable recruitment strategies, particularly for Black older adults, to accelerate participation in ADRD research. The Indiana Alzheimer's Disease Research Center (IADRC) and its Community Advisory Board developed and implemented the innovative RAAISE-D Framework. This Framework informed the creation of community-first recruitment strategies designed to accelerate participation of Black older adults in ADRD research. Preliminary outcomes from its implementation included the doubling of Black adult enrollment (46, 13.4% to 101, 26.9%) from April 2020 to April 2024. Black adults were more likely to have normal cognition, be female, and ≤12 years of education than non-Hispanic White adults. The RAAISE-D Framework identified key concepts for URG focused recruitment strategies which successfully accelerated enrollment of Black adults in ADRD research and could be generalized to other URGs. HIGHLIGHTS: RAAISE-D Framework provides adaptable URG recruitment strategies. IADRC CAB-researcher partnership was the foundation of community-first methodology. RAAISE-D Framework doubled the Black enrollment in the IADRC in 4 years.

Articulatory precision from connected speech as a marker of cognitive decline in Alzheimer's disease risk-enriched cohorts.

Mild cognitive impairment (MCI) has been recognized as a possible precursor to Alzheimer's disease (AD). Recent research focusing on connected speech has uncovered various features strongly correlated with MCI due to AD and related dementias. Despite these advancements, the impact of early cognitive decline on articulatory precision has not been thoroughly investigated. This study introduced the phoneme log-likelihood ratio (PLLR) to assess the articulatory precision of speakers across different cognitive status levels and compared its effectiveness to existing well-studied acoustic features. The study utilized speech recordings from a picture description task, which included data from 324 cognitively unimpaired participants with low amyloid-β burden (CU, Aβ()), 47 cognitively unimpaired participants with high amyloid-β burden (CU, Aβ()), 69 participants with MCI, and 20 participants with dementia. Nine acoustic features were extracted from the speech recordings, covering three categories: speech fluency, speech pace, and articulatory precision. Welch's -test and Hedge's were adopted to assess their discriminative ability. A reduction in speech fluency and pace was observed among participants in the MCI and dementia groups. The PLLR shows large effect sizes in distinguishing between cognitively unimpaired participants with low Aβ burden and those diagnosed with MCI or dementia. Additionally, the test-retest reliability experiment indicated moderate repeatability of the features under study. The study reveals PLLR as a sensitive indicator capable of detecting subtle articulatory variations across groups, while also providing further support for the association between reduced articulatory precision and early cognitive decline.

Telemedicine in Alzheimer's disease and other dementias: Where we are?

The prevalence and global health burden of dementia including Alzheimer's disease (AD) is rising, while patients living in remote and underserved areas face significant challenges in reaching specialized care. Telemedicine offers a valuable solution in bridging this widening gap, by providing equal and timely access to tertiary-specialized centers. Accumulating evidence highlights that most parts of the remote neuropsychological and neurological evaluation are feasible, with patients, healthcare professionals and caregivers being generally satisfied with this means of care. Herein, we provide an updated overview of the available evidence on the use of telemedicine for patients with cognitive disorders, focusing on the different applications and settings, the remote, video-based neurological and neuropsychological assessment, current recommendations, non-pharmacological interventions, as well as legal and ethical considerations. Based on the literature review and our three-year experience in the "Specialized Outpatient Clinic of Memory, Dementia and Parkinson's disease through the National Telemedicine Network" in the Aiginition University Hospital of Athens, we propose a brief guide for assessing patients with cognitive impairment via telemedicine and suggest future research directions for the more effective and appropriate use of telemedicine in dementia assessment and care.

Utilization and perceived usefulness of monitoring technology for family caregivers of people living with Alzheimer's disease and related dementias.

Caregivers of people living with dementia (PLWD) often experience burden based on their care recipients' symptoms of wandering, disorientation, and agitation. To examine the utilization and perceived value of technology-based solutions for caregiving among caregivers of PLWD. In collaboration with three Texas sites, PLWD and family caregiver dyads were recruited from clinical and community sites to assess the feasibility of a caregiving technology. PLWDs were asked to wear a GPS-based wearable device, which was paired with caregivers' smartphone application, that enabled location monitoring and was equipped with call functions. After three months, researchers called caregivers to ask about their utilization of the "system" (i.e., wearable paired with smartphone application) and the perceived value of this technology. Forty-one caregivers completed follow-up telephone interviews. About 70% of caregivers reported their care recipient wore the wearable device daily, and 39.1% used the smartphone application daily. Approximately 31% of caregivers reported daily use of the tracking feature, 30.8% reported daily use of the "safe zone" feature (i.e., geo-fencing), and 17.1% reported daily use of the two-way calling feature. About 39% of caregivers were extremely satisfied with the "system," 43.6% found it extremely easy to use, and 46.2% found it extremely useful for caregiving. On average, caregivers with higher baseline Zarit Burden Interview scores found the "system" to be more useful with their caregiving (f = 5.97, p = 0.006) and were more satisfied with the "system" (f = 3.75, p = 0.034). Findings suggest caregiver burden may drive the perceived usefulness of, and satisfaction with, technology-based solutions.

The pharmacoeconomic assessment of the rationality of the use of memantine and its combinations with acetylcholinesterase inhibitors in the treatment of dementia in Alzheimer’s disease in Ukraine

Aim. To conduct the pharmacoeconomic assessment of the rationality of using memantine and its combinations with acetylcholinesterase inhibitors in the treatment of dementia in Alzheimer’s disease in Ukraine. Materials and methods. Historical, analytical and comparative, systematic, graphic, logical, hypothetical-deductive, as well as marketing, pharmacoeconomic, and mathematical and statistical methods of analysis were used. The pharmacoeconomic studies were conducted using the cost-effectiveness method. CER and ICER indicators were calculated for dementia treatment regimens in Alzheimer’s disease containing memantine and its combinations with acetylcholinesterase inhibitors (donepezil, galantamine, rivastigmine) in the period of 12 and 24 weeks of their use. The pharmacoeconomic analysis used data on the clinical effectiveness of dementia treatment regimens in Alzheimer’s disease presented in the Sochrane library (ID Number: CN-01071444; Accession Number: PUBMED 25932260e). Results. It was found that despite the clinical advantages of using the memantine+galantamine regimen proven by scientists according to the MMSE scale, the use of the memantine+rivastigmine regimen seemed to be rational (CER1 = 23.13 and CER2 = 34.57 USD/unit of increased efficiency). The clinical and economic benefits of using the memantine+galantamine regimen in the treatment of dementia patients with Alzheimer’s disease were proven in the 12- and 24-week regimen (MMSE scale). In the case of using the AADL scale, it was rational, from the point of view of economical use of resources, in the 12-week regimen of treating patients, the use of the memantine + rivastigmine regimen was less expensive (CER1 = 18.30 $/unit of AADL score reduction), while in the 24-week regime it was the memantine + placebo regimen (CER2 = $37.58 $/ unit of AADL score reduction). Conclusions. The research results presented can be used in forming drug purchases carried out by specialized healthcare institutions under the conditions of limited budget funding and growing needs of psychoneurological patients in effective medical and pharmaceutical care.

Recent advances in portable, low-field magnetic resonance imaging in cerebrovascular disease.

This review aims to describe recent advances in low-field (0.064 T) magnetic resonance imaging (LF-MRI) of cerebrovascular disease, including ischemic and hemorrhagic stroke and white matter hyperintensities. Since 2023, several studies have highlighted the rapidly changing landscape of portable, low-field MRI (LF-MRI) and its applications in stroke and cerebrovascular disease. The advantages of using LF-MRI in these settings are multifold: cheaper and dynamic imaging of this patient population confers closer observation during the acute and chronic stages of cerebrovascular disease. Initial deployments of the device span a variety of acute and emergency settings, including imaging around thrombolytic administration, endovascular reperfusion, intracerebral hemorrhage management, and cardiovascular intensive care. LF-MRI also has an important role in cerebrovascular disease monitoring and prevention, namely white matter hyperintensity (WMH) progression and vascular and Alzheimer's dementia. Early studies suggest reliable sensitivity and specificity for these pathologies. With further improvements to LF-MRI hardware, software and postprocessing on the horizon, we anticipate the device's ability to provide inexpensive and flexible neuroimaging to a wide array of healthcare settings that treat, prevent, and manage cerebrovascular disease. Recent studies indicate that LF-MRI promotes rapid, cost-effective, and clinically useful neuroimaging at various clinical timepoints throughout stroke and cerebrovascular disease progression and management.

The Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT) intervention: A personalized approach to dementia risk reduction.

Addressing modifiable risk factors such as physical inactivity and social isolation could reduce risk of Alzheimer's disease and all-cause dementia, but little is known about which factors individuals are most willing to address or how they prefer to address them. To examine and describe behavior change goals set by participants during the Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT). In SMARRT, older adults worked with a health coach and nurse over 2 years to set incremental, personalized goals to reduce dementia risk. We performed quantitative analyses to summarize the numbers of goals per risk factor and qualitative content analyses of health coach and nurse notes to describe types of goals and useful strategies. 82 dementia-free adults (70 to 89 years) with at least two dementia risk factors participated in the SMARRT intervention arm (mean age, 76 ± 5 years; 72% women; 11% Black/African American, 4% Asian, 3% Hispanic, 7% another non-White race). Participants set a median of 12 health coach goals and 1 nurse goals. The risk factors participants chose to work on most frequently were physical activity (95%), hypertension (72%), and cognitive activity (60%). Participants reported that the most useful strategies included support and accountability from the health coach/nurse, setting small goals, and learning to manage setbacks. When given support, older adults at increased risk for dementia set a wide range of goals to reduce dementia risk. A flexible, personalized approach that focuses on setting feasible goals and managing setbacks provides a useful framework for dementia risk reduction.

Classifying cognitive impairment based on FDG-PET and combined T1-MRI and rs-fMRI: An ADNI study.

Mild cognitive impairment (MCI) refers to a memory impairment among non-demented adults. It is a condition that increases the risk of dementia, notably due to Alzheimer's disease (AD). MCI is heterogeneous and there is a need for novel diagnostic approaches. Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging provides robust AD biomarker characteristics, while anatomical and functional magnetic resonance imaging (MRI) offer complementary information. Classify MCI and cognitively normal (CN) adults using FDG-PET images; predict individuals with MCI that convert to AD dementia; determine if MRI can achieve comparable performance to FDG-PET classification. Four ADNI cohorts were created. Cohort 1: 805 participants (MCI n = 455; CN n = 350) that underwent FDG-PET. FDG-PET images were inputs to a one-channel 3-dimensional (3D) DenseNet deep learning model. Cohort 2: 348 participants (MCI n = 174; CN n = 174) with MRI and functional MRI. Cohort 3: overlapping cases from cohorts 1 and 2 (MCI n = 70; CN n = 70). Cohort 4: 336 participants (MCI-converters n = 168; MCI-stable n = 168) with FDG-PET from cohort 1. The one/two-channel models' inputs were T1-weighted MRI and/or amplitude of low-frequency fluctuations images, with classification metrics evaluated through 10-fold cross-validation. The FDG-PET model achieved 88.02%±3.82 accuracy for MCI versus CN classification, with 88.70%±4.70 sensitivity and 87.14%±5.03 specificity. Neither MRI model outperformed the FDG-PET model, as the highest MRI-based accuracy was 76.86%±1.95. The FDG-PET model achieved 63.23%±4.68 accuracy in classifying MCI-converters versus MCI-stable. FDG-PET images produced the highest accuracy in classifying MCI versus CN. While MRI-based approaches were inferior to FDG-PET, multi-contrast MRI still offers value for neurodegeneration classification.

Ten Reasons Why Neurologists Should Refer Patients With Alzheimer Dementia to Music Therapy.

Alzheimer dementia (AD) constitutes a major societal problem with devastating neuropsychiatric involvement. Pharmaceutical interventions carry a heightened risk of side effects; thus, nonpharmacological interventions such as music-based interventions (MBIs), including music therapy, are recommended. The 2023 Neurology release of the Music Based Intervention Toolkit for Brain Disorders of Aging showcased music's emerging role as an intervention to manage symptoms of various brain disorders while defining the building blocks of MBIs to guide research in the exploration of music's therapeutic potential. This study extends beyond the research aspects of the MBI Toolkit to clinical applications by providing neurologists with a summary of MBIs, the MBI Toolkit, how board-certified music therapists (MT-BCs) administered music therapy is a unique MBI, and 10 reasons why they should make referrals to music therapy for their patients with AD.

Utility of Tau PET in the diagnostic work up of neurodegenerative dementia among Indian patients

Background and objectivesTau PET is being increasingly appraised as a novel diagnostic modality for dementia work up. Given limited data among South Asians, we assessed the frequency, patterns, phenotypic associations and incremental value of positive Tau PET scans in clinically diagnosed neurodegenerative dementia. MethodsThis cross-sectional study recruited consecutive patients of Alzheimer's disease (AD) and non-AD syndromes (September 2021 to October 2022, India). Participants underwent clinical interview, cognitive assessment, MRI brain and tau PET scan ([F-18]ML-104). Visual read in a priori regions of interest was used to identify patterns of tau deposition in the brain. ResultsWe recruited 54 participants (mean age: 63.2 ± 9.2 years, 70.4 % men, 77.8 % dementia, 70.4 % early onset cases, 37.8 % APOE4+). The analysis identified abnormal tau uptake in 40/54 (74.1 %) participants; with uptake in AD signature areas in 27/40 (67.5 %) cases [cortical subtype (74.1 %), limbic (14.8 %), combined cortical/limbic (11.1 %)], and patterns not conforming to AD in 13/40 (32.5 %) cases. Tau PET substantiated the diagnosis of AD among 17/19 (89.5 %) cases with clinically diagnosed AD dementia, 8/23 (34.8 %) cases with suspected non-AD cause, and 2/12 (16.7 %) cases with mild cognitive impairment. A trend for increasing proportion of early onset cases, and worsening cognition, behavior and functional ability was seen, from ‘limbic’ to ‘combined cortical/limbic’ to ‘cortical’ subgroups. ConclusionTau PET is a useful modality to differentiate AD dementia from other neurodegenerative causes in the Indian setting where amyloid biomarkers are not widely available. Biological subtypes of AD map well onto clinical phenotypes and need study in larger cohorts.

Baseline-dependent enhancement of working memory by memantine in male rats: Involvement of NMDA receptor subunits and CaMKII signaling

N-methyl-d-aspartate (NMDA) receptors, activated by glutamate, play a crucial role in learning and memory. Memantine (MEM), a non-competitive NMDA receptor antagonist, is currently prescribed for the treatment of Alzheimer's disease or dementia, which meanwhile simultaneously promotes a need to clarify its potential pro-cognitive effects that exist in normal healthy individuals. However, the neurobehavioral mechanisms underlying the cognitive improvement by MEM in normal individuals remain to be elucidated. This study aimed to assess the effects of MEM on working memory, measured by a discrete paired-trial delay alternation task in a T-maze in normal male rats. The impacts of MEM were hypothesized to vary depending on different baseline levels of working memory performance. Neurochemical examination of the levels of calcium/calmodulin-dependent kinase 2 (CaMKII) and NMDA receptor subunits within five targeted brain regions was conducted after behavioral tests. The results showed that acute administration of MEM enhanced working memory performance, with 2.5, 5.0, and 10 mg/kg doses increasing task accuracy compared to the vehicle, particularly in low performers. Neurochemically, the protein expression of CaMKII in the amygdala and that of the glutamate (Glu) N2A subunit in the dorsal striatum were greater in the low-performance group than in the high-performance group. Additionally, the protein expression of the GluN2A subunit in the dorsal striatum was negatively associated with task performance at baseline. The expression of GluN1 and GluN2B in the nucleus accumbens was negatively associated with task performance in the retest three weeks after drug treatment. These findings underscore the baseline-dependent improvement of working memory resulting from MEM administration, with observed drug effects associated with alterations in the levels of NMDA receptor subunits in striatal subareas and CaMKII in the amygdala.