Mild Stage Dementia Research Articles

18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis

BackgroundPrecisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology.MethodsLongitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer’s Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535–62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer’s Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777–88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels.ResultsAmong the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers.ConclusionA normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term.Trial registrationClinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.

Identification of profiles associated with conversions between the Alzheimer’s disease stages, using a machine learning approach

BackgroundThe identification of factors involved in the conversion across the different Alzheimer’s disease (AD) stages is crucial to prevent or slow the disease progression. We aimed to assess the factors and their combination associated with the conversion across the AD stages, from mild cognitive impairment to dementia, at a mild, moderate or severe stage and to identify profiles associated with earliest/latest conversion across the AD stages.MethodsIn this study conducted on the real-life MEMORA cohort data collected from January 1, 2013, and December 31, 2019, three cohorts were selected depending on the baseline neurocognitive stage from a consecutive sample of patients attending a memory center, aged between 50 and 90 years old, with a diagnosis of AD during the follow-up, and with at least 2 visits at 6 months to 1 year of interval. A machine learning approach was used to assess the relationship between factors including socio-demographic characteristics, comorbidities and history of diseases, prescription of drugs, and geriatric hospitalizations, and the censored time to conversion from mild cognitive impairment to AD dementia, from the mild stage of dementia to the moderate or severe stages of AD dementia, and from the moderate stage of AD dementia to the severe stage. Profiles of earliest/latest conversion compared to median time to conversion across stages were identified. The median time to conversion was estimated with a Kaplan-Meier estimator.ResultsOverall, 2891 patients were included (mean age 77±9 years old, 65% women). The median time of follow-up was 28 months for mild cognitive impairment (MCI) patients, 33 months for mild AD dementia and 30 months for moderate AD dementia. Among the 1264 patients at MCI stage, 61% converted to AD dementia (median time to conversion: 25 months). Among the 1142 patients with mild AD dementia, 59% converted to moderate/severe stage (median time: 23 months) and among the 1332 patients with moderate AD dementia, 23% converted to severe stage (Q3 time to conversion: 22 months). Among the studied factors, cardiovascular comorbidities, anxiety, social isolation, osteoporosis, and hearing disorders were identified as being associated with earlier conversion across stages. Symptomatic treatment i.e. cholinesterase inhibitors for AD was associated with later conversion from mild stage of dementia to moderate/severe stages.ConclusionThis study based on a machine learning approach allowed to identify potentially modifiable factors associated with conversion across AD stages for which timely interventions may be implemented to delay disease progression.

Borderline-DEMNET: A Workflow for Detecting Alzheimer’s and Dementia Stage by Solving Class Imbalance Problem

Alzheimer’s Disease (AD) is the leading cause of dementia, a broad term encompassing memory loss and other cognitive impairments. Although there is no known cure for dementia, managing specific symptoms associated with it can be effective. Mild dementia stages, including AD, can be treated, and computer-based techniques have been developed to aid in early diagnosis. This paper presents a new workflow called Borderline-DEMNET, designed to classify various stages of Alzheimer’s/dementia with more than three classes. Borderline-SMOTE is employed to address the issue of imbalanced datasets. A comparison is made between the proposed Borderline-DEMNET workflow and the existing DEMNET model, which focuses on classifying different dementia and AD stages. The evaluation metrics specified in the paper are used to assess the results. The framework is trained, tested, and validated using the Kaggle dataset, while the robustness of the work is checked using the ADNI dataset. The proposed workflow achieves an accuracy of 99.17% for the Kaggle dataset and 99.14% for the ADNI dataset. In conclusion, the proposed workflow outperforms previously identified models, particularly in terms of accuracy. It also proves that selecting a proper class balancing technique will increase accuracy.

Borderline-DEMNET: A Workflow for Detecting Alzheimer’s and Dementia Stage by Solving Class Imbalance Problem

Alzheimer’s Disease (AD) is the leading cause of dementia, a broad term encompassing memory loss and other cognitive impairments. Although there is no known cure for dementia, managing specific symptoms associated with it can be effective. Mild dementia stages, including AD, can be treated, and computer-based techniques have been developed to aid in early diagnosis. This paper presents a new workflow called Borderline-DEMNET, designed to classify various stages of Alzheimer’s/dementia with more than three classes. Borderline-SMOTE is employed to address the issue of imbalanced datasets. A comparison is made between the proposed Borderline-DEMNET workflow and the existing DEMNET model, which focuses on classifying different dementia and AD stages. The evaluation metrics specified in the paper are used to assess the results. The framework is trained, tested, and validated using the Kaggle dataset, while the robustness of the work is checked using the ADNI dataset. The proposed workflow achieves an accuracy of 99.17% for the Kaggle dataset and 99.14% for the ADNI dataset. In conclusion, the proposed workflow outperforms previously identified models, particularly in terms of accuracy. It also proves that selecting a proper class balancing technique will increase accuracy.

Generating real-world evidence in Alzheimer's disease: Considerations for establishing a core dataset.

Ongoing assessment of patients with Alzheimer's disease (AD) in postapproval studies is important for mapping disease progression and evaluating real-world treatment effectiveness and safety. However, interpreting outcomes in the real world is challenging owing to variation in data collected across centers and specialties and greater heterogeneity of patients compared with trial participants. Here, we share considerations for observational postapproval studies designed to collect harmonized longitudinal data from individuals with mild cognitive impairment or mild dementia stage of disease who receive therapies targeting the underlying pathological processes of AD in routine practice. This paper considers key study design parameters, including proposed aims and objectives, study populations, approaches to data collection, and measures of cognition, functional abilities, neuropsychiatric status, quality of life, health economics, safety, and drug utilization. Postapproval studies that capture these considerations will be important to provide standardized data on AD treatment effectiveness and safety in real-world settings.

Mechanism of action and clinical trial results of Lecanemab (Leqembi® 200 ‍mg, 500 ‍mg for Intravenous Infusion), a novel treatment for Alzheimer's disease

Lecanemab is a humanized monoclonal antibody directed against human soluble amyloid-β aggregates. It was developed for the treatment of early Alzheimer's disease (mild cognitive impairment or mild dementia stage of Alzheimer's disease). Among the amyloid-β (Aβ) involved in Alzheimer's disease, Lecanemab selectively binds to the highly neurotoxic Aβ protofibrils, and is thought to reduce Aβ protofibrils and amyloid plaques (Aβ plaques) in the brain. The efficacy and safety of Lecanemab in early Alzheimer's disease were investigated in an international Phase II placebo-controlled study (Study 201) and an international Phase III placebo-controlled study (Study 301). Both studies included Japanese subjects. Lecanemab was given accelerated approval in the United States in January 2023, followed by traditional approval in July 2023. In Japan, it was approved for "control of the progression of mild cognitive impairment or mild dementia stage of Alzheimer's disease" in September 2023, and was added to the NHI drug price list in December 2023.

Different Splice Isoforms of Peripheral Triggering Receptor Expressed on Myeloid Cells 2 mRNA Expressions are Associated With Cognitive Decline in Mild Dementia Due to Alzheimer's Disease and Reflect Central Neuroinflammation.

Triggering receptor expressed on myeloid cells 2 (TREM2) is upregulated in activated microglia and may be related to cognitive decline in patients with Alzheimer's disease (AD). There is conflicting evidence regarding the association of peripheral TREM2 mRNA expression/soluble TREM2 (the extracellular domain of TREM2) with cognitive function/neuroinflammation in patients with AD. Herein, we studied the TREM2 and TREM2alt mRNA expression and their association with the cognitive performance in subjects with mild dementia due to AD and healthy controls. In a subgroup of patients with AD, magnetic resonance spectroscopy was used to measure the myo-inositol level in the posterior cingulate cortex, a surrogate marker for neuroinflammation. The results showed that increased TREM2 and TREM2alt mRNA expression is associated with AD pathogenesis at the mild dementia stage, thereby serving as a potential biomarker for early symptomatic stage of AD. TREM2 may exert protective effects on both cognition and central neuroinflammation.

Music and humanoid robots aid in performing daily living activities in people affected with advance stage dementia

AbstractBackgroundAs the disease progresses the ability to perform daily living activities is gradually reduced. As dementia progresses music is one of the last things to go(Foo et al.2017, Beatty et al., 1988). Additionally many studies have shown music to be an effective tool to help people affected with dementia(Baird, & Samson, 2015). In order to help residents in nursing homes to perform their daily living activities we programmed a humanoid robot to sing, perform the daily living activity and instruct the resident to follow them in performing specific daily living activities. The activities that are performed are brushing teeth, washing face, putting on clothes and going from point A to point B.MethodHumanoid robots are programmed to sing the instructions to perform a daily living activity and also act out the activity. The robots are programmed to perform simple activities of daily living that the people affected with dementia are forgetting to perform. The music is composed and lyrics are written by Professors Rudy Perrault and Rachel Inselman.ResultThe robots have been successfully helping people affected with dementia in a short trial. There were three participants chosen for this case study where one person was in the advanced stage of dementia, one person was in the moderate stage of dementia and the third person was in the mild stage of dementia. Each of the participants was able to successfully perform the activities of daily living by mimicking the robots.ConclusionAs soon as the robot started to sing and enact the daily living activity the participants started to move to the music and follow the robot.

Music and humanoid robots aid in performing daily living activities in people affected with advance stage dementia

AbstractBackgroundAs the disease progresses the ability to perform daily living activities is gradually reduced. As dementia progresses music is one of the last things to go(Foo et al.2017, Beatty et al., 1988). Additionally many studies have shown music to be an effective tool to help people affected with dementia(Baird, & Samson, 2015). In order to help residents in nursing homes to perform their daily living activities we programmed a humanoid robot to sing, perform the daily living activity and instruct the resident to follow them in performing specific daily living activities. The activities that are performed are brushing teeth, washing face, putting on clothes and going from point A to point B.MethodHumanoid robots are programmed to sing the instructions to perform a daily living activity and also act out the activity. The robots are programmed to perform simple activities of daily living that the people affected with dementia are forgetting to perform. The music is composed and lyrics are written by Professors Rudy Perrault and Rachel Inselman.ResultThe robots have been successfully helping people affected with dementia in a short trial. There were three participants chosen for this case study where one person was in the advanced stage of dementia, one person was in the moderate stage of dementia and the third person was in the mild stage of dementia. Each of the participants was able to successfully perform the activities of daily living by mimicking the robots.ConclusionAs soon as the robot started to sing and enact the daily living activity the participants started to move to the music and follow the robot.

Head‐to‐head comparisons of cognitive screening tests administered in primary care centers

AbstractBackgroundCognitive screening tests are often used in primary care to aid in the decision whether further investigation is needed. The most widely used tests, MMSE and the Clock Drawing Test (CDT), were developed more than 40 years ago and there is a need to update the primary care neuropsychological toolbox. The objective for this pilot study was to examine the diagnostic accuracy of AD for different cognitive tests administered at primary care centers.MethodThe BioFINDER Primary Care Study consecutively recruits patients with cognitive complaints (SCD, MCI, or mild dementia) at different primary care centers in Sweden. Cognitive tests are examined as well as plasma AD‐biomarkers. A test battery including MMSE, MoCA, CDT, Verbal fluency tests, TMT A and B, Symbol Digit Test, ADAS 10‐wordlist and Recall of Picture Test (RPT) are administered to all patients at their respective primary care center. Patients are then referred to a memory clinic where they undergo a full clinical work‐up (including neuropsychological assessment, lumbar puncture or Aβ‐PET, MRI and an examination by a physician specialized in dementia diseases) after which a diagnosis is made (blinded to the tests done in primary care). A clinical diagnosis of AD is supported by CSF or PET findings. The diagnosis of AD, either at the MCI or mild dementia stage, was here used as the dependent variable in logistic regression models with the different cognitive tests as predictors (adjusted for age, sex, education). Comparisons of AUC were performed using DeLong statistics.ResultIn this pilot study the first 276 recruited patients were analyzed (Table 1). Four tests, MMSE (AUC = 0.73, P <0.01), MoCA (AUC = 0.71, P <0.05), ADAS 10‐wordlist (AUC = 0.80, P <0.001) and RPT (AUC = 0.79, P <0.001), performed significantly better than the basic model (age, sex, education) in predicting a diagnosis of AD. Both the ADAS 10‐wordlist and RPT performed significantly better than MMSE (P <0.05). Adding the CDT to MMSE did not improve the AUC (0.73).ConclusionIn a diverse population, as seen at primary care centers, brief tests of memory may provide better accuracy in detecting AD than standard of care tests as MMSE and MoCA.

Stimulation of Cerebral Angiogenesis and Neurogenesis with Transcatheter Intracerebral Laser Photobiomodulation Therapy in Alzheimer’s Disease and Vascular Parkinsonism Aggravated by Dementia

AbstractBackgroundThe research is focused on the stimulation of cerebral angiogenesis and neurogenesis using Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) in patients with dementia in Alzheimer’s disease (AD) and patients with vascular parkinsonism (VP).MethodThe examination of 155 patients included assessment of CDR, The Tomography Dementia Rating scale (TDR), MMSE, cerebral CT, MRI, SG, rheoencephalography (REG) and cerebral MUGA.85 patients were selected, of whom:• 48 (30.97%) people suffering from AD, aged 34‐80 (mean age 67.5), men ‐ 17 (35.42%), women ‐ 31 (54.58%). According to dementia severity, patients were subdivided: preclinical stage (TDR‐0) ‐ 4, mild stage (TDR‐1) ‐ 16, moderately severe stage (TDR‐2) ‐ 21, severe stage (TDR‐3) ‐ 7 patients.• 37 (23.87%) people suffering from VP, aged 58‐80 (mean age 77), men 28 (75.68%), women ‐ 9 (24.32%). 19 (51.35%) had a mild dementia stage (CDR‐1).In hospital conditions, in a specialized cath lab, all patients underwent Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) (wavelength 632.8 nanometers).ResultAll 48 (100%) patients with AD underwent angiogenesis stimulation resulting in cerebral collateral capillary revascularization and closure of atreriovenous shunts.Simultaneously, patients showed a 10‐20% increase in cerebral temporal lobes volume, which indicates cerebral neurogenesis development and tissue regeneration. The process was accompanied by dementia level decrease and cognitive functions restoration. Consequently, patients were transferred to a milder TDR group. Depending on the initial dementia severity, the resulting positive effect was observed from 2 to 15 years.All 37 (100%) patients with VP underwent angiogenesis stimulation resulting in cerebral microcirculation improvement and cerebral involutive changes decrease, which indicates the neurogenesis development and tissue regeneration. The process was accompanied by decreased dementia and cognitive functions restoration. The resulting positive effect was observed over 10 years.ConclusionDespite the differences in AD and VP etiology, Transcatheter Intracerebral Laser Photobiomodulation Therapy (PBMT) is an effective treatment for dementia in these diseases. The method stimulates angiogenesis and improves blood supply to the brain, it stimulates neurogenesis and the restoration of normal tissue structures, which leads to improved mental and cognitive functions. The resulting effect persists for a long time.

PP125 Why Understanding The Burden Of The Population Is Fundamental

IntroductionDespite intense efforts in development of new treatments over the last two decades, symptomatic treatments remain the only option for the vast majority patients diagnosed with dementia due to Alzheimer’s disease (AD). There remains a significant unmet need for disease modifying therapies (DMTs) to slow or stop AD progression. DMTs in development are targeting early stages of AD (pre-clinical, mild cognitive impairment and mild dementia stages), thereby creating an entirely new treatment paradigm for patients, clinicians, and payers. A key challenge will be in identifying the appropriate patient for treatment in a very heterogenous population. We have performed a literature review to better understand and define the AD population, with a view to enabling more targeted treatment in future.MethodsEmbase, MEDLINE and the Cochrane Library were searched to identify publications between 2010-2021 on observational studies reporting evidence on prevalence and subgroup identification, including clinical feasibility of identification. The search was restricted to English language.ResultsWe identified 45 studies, mostly from Europe, USA and Asia. Populations were primarily grouped based on generic demographic factors (e.g., age, sex, gender), AD staging, comorbidities or biomarkers. Prevalence data was available for six subpopulations: pre-dementia stage, mild dementia, age, Apolipoprotein E (APOE) genotype, comorbid obesity and hypertension. Across these, data on prevalence were heterogenous depending on study design and country of origin, and ranging between 66 million to 102 million for people with mild AD dementia, or as another example, ranging between 46 million to 92 million for APOE genotype carriers worldwide.ConclusionsThe heterogeneity and the uncertainty in prevalence of the AD population represent big challenges to clinicians and payers. Future discussions on target patient identification for new treatments should be aligned and integrated with current clinical practice e.g. leveraging validated biomarkers as diagnostic tools. Additional research on an integrated approach to identify patients who would benefit the most from DMTs will be needed.

Validation of the European Cross‐Cultural Neuropsychological Test Battery (CNTB) for the assessment of mild cognitive impairment due to Alzheimer’s disease and Parkinson’s disease in Spain

AbstractBackgroundThe Cross‐Cultural Neuropsychological Test Battery (CNTB) is a novel comprehensive neuropsychological battery developed from a multicultural approach. We aimed to validate the CNTB in patients from the majority population with Alzheimer’s disease (AD), including mild cognitive impairment (MCI) and mild dementia stages, and Parkinson’s disease with MCI (PD‐MCI).MethodsThirty patients with AD‐MCI, 30 with AD‐dementia (AD‐D), and 30 with PD‐MCI were enrolled. Each clinical group had a specific healthy control group (HC) with no differences in sex, age, or years of education. We performed intergroup comparisons, ROC analysis, and calculated the corresponding cut‐off points based on Youden’s index.ResultsAD‐MCI showed lower scores than HC in those subtests associated with episodic memory and verbal fluency, while AD‐D also scored lower in executive function and visuospatial tests with large effect sizes. Participants with PD‐MCI showed lower performance in memory and executive function, particularly on error scores, with large effect sizes, compared with HC. While AD‐MCI showed lower memory scores, PD‐MCI had a lower performance in executive functions, comparing both groups. We found evidence of convergent validity with standardized neuropsychological tests measuring the same cognitive domains. Cut‐off scores were similar to previous studies conducted in other cultures.ConclusionsThe CNTB showed appropriate diagnostic properties and convergent validity in AD and PD, including the early stages of the disease. This supports the utility of the CNTB for the early detection of cognitive impairment in AD and PD.

P142: Dementia diagnosis: the potential onset of suicidal risk

Objective:Being diagnosed with dementia can be a hectic and critical period. While severe dementia may act as a shield when it comes to suicidal risk, mild and early dementia stages may still preserve cognitive functions to elaborate a suicidal plan. Having insight may lead to feelings of despair and sadness that patients find unbearable to deal with. The aim of this article is to review the current literature regarding suicidal risk after a dementia diagnosis.Methods:Review of the most recent literature regarding the risk of suicide among patients with a recent dementia diagnosis. The research was carried out through the PubMed and UptoDate databases, using the terms “dementia”, “diagnosis” and “suicidal risk”.Results:Previous research showed inconclusive findings, with some authors suggesting a higher risk of an early suicide attempt in patients recently diagnosed with dementia, and others suggesting otherwise. Nowadays, the literature mainly reports that older adults with recent dementia diagnoses are at increased risk of endeavoring suicide. There is an important requirement to offer appropriate support to patients and their families, at the time, or as soon as possible, when a dementia diagnosis is made, to diminish the risk of suicide attempts in these patients.Conclusion:Patients with recent diagnosis of dementia, or diagnosed at an earlier age, seem to have higher suicidal risk. The period immediately after diagnosis is when individuals need greater support, so these results demand for better assistance for those experiencing such intellectual decline.

Recent advances in understanding Alzheimer's Disease: diagnosis and management strategies.

As the rates of Alzheimer's Disease (AD) increase in the world due to the aging of the population, research has made tremendous advances to target the two hallmark pathologies of AD: amyloid-β (Aβ) plaque deposition and neurofibrillary tangles of hyperphosphorylated tau. Here, we discuss recent advances in the clinical evaluation and management of AD, with a focus on new hypotheses related to the etiology of AD and new evidence related to AD-mimicking neurodegenerative diseases. Though recent clinical studies suggest anti-amyloid disease modifying agents may slow the progression of AD, there is currently no medication that stops it. Moreover, slowing the progression will result in more individuals in the mild cognitive impairment (MCI) and mild dementia stages of AD. Given this reality, we evaluate the development of non-pharmacological strategies to help sustain cognitive function and quality of life.

Alteration of metabolic profile during the progression of Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of how altered metabolism involves AD pathology are poorly understood. This study intends to provide novel insights into the role of metabolic alteration in the pathology and identify potential metabolic biomarkers for AD diagnosisMethodThe Gas chromatography‐mass spectrometry (GC‐MS) was used to measure the concentrations of serum metabolites in a cohort of subjects with AD (n = 88) and cognitively normal control (CN) (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). Serum metabolic profiles were analyzed by multivariate (principal component analysis) and univariate approaches (t‐tests, false discovery, receiver operating characteristic curves, and correlation analysis). The artificial neural network model (ANN) was applied to identify potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes.ResultThe results revealed considerable separation between the AD and CN patients. Edetic acid, (S)‐3,4‐Dihydroxybutyric acid, and arachidonic acid were identified as potential AD diagnostic biomarkers using an ANN model. And the classification model could predict the risk for AD with high accuracy (AUC = 0.93). The most significant changes in the metabolite’s composition occur during the very mild to the mild stage. The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and disturbance of amino acids, fatty acids, and lipids metabolism are involved in AD progression. Especially, pathway analysis highlighted that l−glutamate participated in four crucial nervous system pathways (including GABAergic synapse, glutamatergic synapse, retrograde endocannabinoid signaling and synaptic vesicle cycle).ConclusionSerum metabolomic analysis demonstrated that the metabolic alterations had already arisen at the very mild stages of dementia. Disrupt energy metabolism may be the core of the vicious cycle in AD, resulting in a wide range of metabolic disorders, including abnormal glucose metabolism, TCA cycle impairments, amino acids, fatty acids, and lipids dysregulation. Furthermore, a metabolic diagnostic model of AD was constructed using ANN, which could robustly differentiate AD patients from CN. Our study identified new markers for AD diagnosis and highlighted the roles of metabolic changes on the progression of AD.

CSF Synaptic Biomarkers in AT(N)-Based Subgroups of Lewy Body Disease.

Patients with Lewy body disease (LBD) often show a co-occurring Alzheimer disease (AD) pathology. CSF biomarkers allow the detection in vivo of AD-related pathologic hallmarks included in the amyloid-tau-neurodegeneration (AT(N)) classification system. Here, we aimed to investigate whether CSF biomarkers of synaptic and neuroaxonal damage are correlated with the presence of AD copathology in LBD and can be useful to differentiate patients with LBD with different AT(N) profiles. We retrospectively measured CSF levels of AD core biomarkers (Aβ42/40 ratio, phosphorylated tau protein, and total tau protein) and of synaptic (β-synuclein, α-synuclein, synaptosomal-associated protein 25 [SNAP-25], and neurogranin) and neuroaxonal proteins (neurofilament light chain [NfL]) in 28 cognitively unimpaired participants with nondegenerative neurologic conditions and 161 participants with a diagnosis of either LBD or AD (at both mild cognitive impairment, AD-MCI, and dementia stages, AD-dem). We compared CSF biomarker levels in clinical and AT(N)-based subgroups. CSF β-synuclein, α-synuclein, SNAP-25, neurogranin, and NfL levels did not differ between LBD (n = 101, age 67.2 ± 7.8 years, 27.7% females) and controls (age 64.8 ± 8.6 years, 39.3% females) and were increased in AD (AD-MCI: n = 30, AD-dem: n = 30, age 72.3 ± 6.0 years, 63.3% females) compared with both groups (p < 0.001 for all comparisons). In LBD, we found increased levels of synaptic and neuroaxonal degeneration biomarkers in patients with A+T+ (LBD/A+T+) than with A-T- profiles (LBD/A-T-) (p < 0.01 for all), and β-synuclein showed the highest discriminative accuracy between the 2 groups (area under the curve 0.938, 95% CI 0.884-0.991). CSF β-synuclein (p = 0.0021), α-synuclein (p = 0.0099), and SNAP-25 concentrations (p = 0.013) were also higher in LBD/A+T+ than in LBD/A+T- cases, which had synaptic biomarker levels within the normal range. CSF α-synuclein was significantly decreased only in patients with LBD with T- profiles compared with controls (p = 0.0448). Moreover, LBD/A+T+ and AD cases did not differ in any biomarker level. LBD/A+T+ and AD cases showed significantly increased CSF levels of synaptic and neuroaxonal biomarkers compared with LBD/A-T- and control subjects. Patients with LBD and AT(N)-based AD copathology showed, thus, a distinct signature of synaptic dysfunction from other LBD cases. This study provides Class II evidence that CSF levels of β-synuclein, α-synuclein, SNAP-25, neurogranin, and NfL are higher in patients with AD than in patients with LBD.

Validation of the European Cross-Cultural Neuropsychological Test Battery (CNTB) for the assessment of mild cognitive impairment due to Alzheimer's disease and Parkinson's disease.

The Cross-Cultural Neuropsychological Test Battery (CNTB) is a novel test battery specifically designed to reduce the impact of multiculturality in cognitive assessment. We aimed to validate the CNTB in Spaniards in patients with Alzheimer's disease (AD), including patients at mild cognitive impairment (MCI) and mild dementia stages, and Parkinson's disease with MCI (PD-MCI). Thirty patients with AD-MCI, 30 with AD-dementia (AD-D), and 30 with PD-MCI were recruited. Each clinical group was compared against a healthy control group (HC) with no differences in sex, age, or years of education. Intergroup comparisons, ROC analysis, and cut-off scores were calculated. AD-MCI scored lower than HC in those subtests associated with episodic memory and verbal fluency. AD-D also showed lower scores in executive functions and visuospatial tests. Effect sizes for all the subtests were large. PD-MCI showed lower performance than HC in memory and executive functions, particularly on error scores, with large effect sizes. Comparing AD-MCI and PD-MCI, AD-MCI had lower memory scores, while PD-MCI showed the worst performance in executive functions. CNTB showed appropriate convergent validity with standardized neuropsychological tests measuring the same cognitive domains. We obtained similar cut-off scores to previous studies performed in other populations. The CNTB showed appropriate diagnostic properties in AD and PD, including those stages with mild cognitive impairment. This supports the utility of the CNTB for the early detection of cognitive impairment in AD and PD.

Neuropharmacology of Lecanemab-irmb: A new drug granted in the treatment of Alzheimer's disease

United state food and drug administration approved on 6 January 2023, Lecanemab-irmb via the accelerated approval pathway for the treatment of Alzheimer’s disease. Researchers evaluated Lecanemab-irmb’s efficacy in a double-blind, placebo-controlled, parallel-group, dose-finding study of 856 patients with Alzheimer’s disease. Treatment was initiated in patients with mild cognitive impairment or mild dementia stage of disease and confirmed the presence of amyloid beta pathology. Patients receiving the treatment had significant dose and time-dependent reduction of amyloid beta plaque, with patients receiving the approved dose of lecanemab, 10 milligram/kilogram every two weeks, having a statistically significant reduction in brain amyloid plaque from baseline to Week 79 compared to the placebo arm, which had no reduction of amyloid beta plaque. These results support the accelerated approval of Lecanemab-irmb, which is based on the observed reduction of amyloid beta plaque, a marker of Alzheimer’s disease. The amyloid beta plaque was quantified using positron emission tomography (PET) imaging to estimate the brain levels of amyloid beta plaque in a composite of brain regions expected to be widely affected by Alzheimer’s disease pathology compared to a brain region expected to be spared of such pathology.

Validation study of “Santé-Cerveau”, a digital tool for early cognitive changes identification

BackgroundThere is a need for a reliable, easy-to-use, widely available, and validated tool for timely cognitive impairment identification. We created a computerized cognitive screening tool (Santé-Cerveau digital tool (SCD-T)) including validated questionnaires and the following neuropsychological tests: 5 Word Test (5-WT) for episodic memory, Trail Making Test (TMT) for executive functions, and a number coding test (NCT) adapted from the Digit Symbol Substitution Test for global intellectual efficiency. This study aimed to evaluate the performance of SCD-T to identify cognitive deficit and to determine its usability.MethodsThree groups were constituted including 65 elderly Controls, 64 patients with neurodegenerative diseases (NDG): 50 AD and 14 non-AD, and 20 post-COVID-19 patients. The minimum MMSE score for inclusion was 20. Association between computerized SCD-T cognitive tests and their standard equivalent was assessed using Pearson's correlation coefficients. Two algorithms (a simple clinician-guided algorithm involving the 5-WT and the NCT; and a machine learning classifier based on 8 scores from the SCD-T tests extracted from a multiple logistic regression model, and data from the SCD-T questionnaires) were evaluated. The acceptability of SCD-T was investigated through a questionnaire and scale.ResultsAD and non-AD participants were older (mean ± standard deviation (SD): 72.61 ± 6.79 vs 69.91 ± 4.86 years old, p = 0.011) and had a lower MMSE score (Mean difference estimate ± standard error: 1.74 ± 0.14, p < 0.001) than Controls; post-COVID-19 patients were younger than Controls (mean ± SD: 45.07 ± 11.36 years old, p < 0.001). All the computerized SCD-T cognitive tests were significantly associated with their reference version. In the pooled Controls and NDG group, the correlation coefficient was 0.84 for verbal memory, -0.60 for executive functions, and 0.72 for global intellectual efficiency. The clinician-guided algorithm demonstrated 94.4% ± 3.8% sensitivity and 80.5% ± 8.7% specificity, and the machine learning classifier 96.8% ± 3.9% sensitivity and 90.7% ± 5.8% specificity. The acceptability of SCD-T was good to excellent.ConclusionsWe demonstrate the high accuracy of SCD-T in screening cognitive disorders and its good acceptance even in individuals with prodromal and mild dementia stages. SCD-T would be useful in primary care to faster refer subjects with significant cognitive impairment (and limit unnecessary referrals) to specialized consultation, improve the AD care pathway and the pre-screening in clinical trials.