Unraveling the Potential Underlying Mechanisms of Mild Behavioral Impairment: Focusing on Amyloid and Tau Pathology.

The emergence of sustained neuropsychiatric symptoms (NPS) among non-demented individuals in later life, defined as mild behavioral impairment (MBI), is linked to a higher risk of cognitive decline. However, the underlying pathophysiological mechanisms remain largely unexplored. A growing body of evidence has shown that MBI is associated with alterations in structural and functional neuroimaging studies, higher genetic predisposition to clinical diagnosis of Alzheimer's disease (AD), as well as amyloid and tau pathology assessed in the blood, cerebrospinal fluid, positron-emission tomography (PET) imaging and neuropathological examination. These findings shed more light on the MBI-related potential neurobiological mechanisms, paving the way for the development of targeted pharmacological approaches. In this review, we aim to discuss the available clinical evidence on the role of amyloid and tau pathology in MBI and the potential underlying pathophysiological mechanisms. Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, disruption of neurotrophic factors, such as the brain-derived neurotrophic factor (BDNF), abnormal neuroinflammatory responses including the kynurenine pathway, dysregulation of transforming growth factor beta (TGF-ß1), epigenetic alterations including micro-RNA (miR)-451a and miR-455-3p, synaptic dysfunction, imbalance in neurotransmitters including acetylcholine, dopamine, serotonin, gamma-aminobutyric acid (GABA) and norepinephrine, as well as altered locus coeruleus (LC) integrity are some of the potential mechanisms connecting MBI with amyloid and tau pathology. The elucidation of the underlying neurobiology of MBI would facilitate the design and efficacy of relative clinical trials, especially towards amyloid- or tau-related pathways. In addition, we provide insights for future research into our deeper understanding of its underlying pathophysiology of MBI, and discuss relative therapeutic implications.

Tau-PET in early cortical Alzheimer brain regions in relation to mild behavioral impairment in older adults with either normal cognition or mild cognitive impairment.

Mild Behavioral Impairment (MBI) leverages later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a high-risk group for incident dementia. Phosphorylated tau (p-tau) is a hallmark biological manifestation of Alzheimer disease (AD). We investigated associations between MBI and tau accumulation in early-stage AD cortical regions. In 442 Alzheimer's Disease Neuroimaging Initiative participants with normal cognition or mild cognitive impairment, MBI status was determined alongside corresponding p-tau and Aß. Two meta-regions of interest were generated to represent Braak I and III neuropathological stages. Multivariable linear regression modelled the association between MBI as independent variable and tau tracer uptake as dependent variable. Among Aß positive individuals, MBI was associated with tau uptake in Braak I (ß=0.45(0.15), p<.01) and Braak III (ß=0.24(0.07), p<.01) regions. In Aß negative individuals, MBI was not associated with tau in the Braak I region (p=0.11) with a negative association in Braak III (p=.01). These findings suggest MBI may be a sequela of neurodegeneration, and can be implemented as a cost-effective framework to help improve screening efficiency for AD.

Longitudinal trajectories of cognitive reserve in hypometabolic subtypes of Alzheimer's disease.

Previous studies have demonstrated resilience to AD-related neuropathology in a form of cognitive reserve (CR). In this study we investigated a relationship between CR and hypometabolic subtypes of AD, specifically the typical and the limbic-predominant subtypes. We analyzed data from 59 Aß-positive cognitively normal (CN), 221 prodromal Alzheimer's disease (AD) and 174 AD dementia participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) from ADNI and ADNIGO/2 phases. For replication, we analyzed data from 5 Aß-positive CN, 89 prodromal AD and 43 AD dementia participants from ADNI3. CR was estimated as standardized residuals in a model predicting cognition from temporoparietal grey matter volumes and covariates. Higher CR estimates predicted slower cognitive decline. Typical and limbic-predominant hypometabolic subtypes demonstrated similar baseline CR, but the results suggested a faster decline of CR in the typical subtype. These findings support the relationship between subtypes and CR, specifically longitudinal trajectories of CR. Results also underline the importance of longitudinal analyses in research on CR.

Impairments in sleep and brain molecular clearance in people with cognitive deterioration and biological evidence of AD: a report of four cases.

BACKGROUND: Recent evidence suggests that the failure of the glymphatic system - the brain's waste clearance system, which is active during sleep - plays a key role in the pathophysiology of Alzheimer's Disease (AD). Glymphatic function can be investigated using serial MRIs after intrathecal gadobutrol injection. This technique can reveal the health of the glymphatic system, but has not yet been used in participants with cognitive impairment due to AD. CASE REPORT: This report describes the sleep and gadobutrol tracer clearance patterns of four participants diagnosed with mild to moderate cognitive impairment with evidence of AD pathology (pathological levels of Ab and p-tau in cerebrospinal fluid). We performed polysomnography and MRI studies before tracer injection and MRI scans at 1.5-2 h, 5-6 h, and 48 h after injection. Despite participants reporting no sleep problems, polysomnography revealed that all participants had moderate to severe sleep disturbances, including reduced sleep efficiency during the study and obstructive sleep apnea. Severe side-effects related to tracer administration were observed, impeding the completion of the protocol in two participants. Participants who finished the protocol displayed delayed and persistent tracer enrichment in the cortex and white matter, even 48 h after injection. These outcomes have not been observed in previous studies in participants without AD. CONCLUSION: The findings suggest that brains with sleep impairment and AD pathology have poor glymphatic function, and therefore cannot clear the contrast tracer efficiently. This is likely to have caused the severe side effects in our participants, that have not been reported in healthy individuals. Our results may therefore represent the only available data acquired with this technique in participants with AD pathology.

Disease severity and mortality in Alzheimer's disease: an analysis using the U.S. National Alzheimer's Coordinating Center Uniform Data Set.

BACKGROUND: Evidence on the relative risk of death across all stages of Alzheimer's disease (AD) is lacking but greatly needed for the evaluation of new interventions. We used data from the Uniform Data Set (UDS) of the National Alzheimer's Coordinating Center (NACC) to assess the expected survival of a person progressing to a particular stage of AD and the relative risk of death for a person in a particular stage of AD compared with cognitively normal (CN) people. METHODS: This was a retrospective observational cohort study of mortality and its determinants in participants with incident mild cognitive impairment (MCI) due to AD or AD dementia compared with CN participants. Overall survival and hazard ratios of all-cause mortality in participants ≥ 50 years of age with clinically assessed or diagnosed MCI due to AD, or mild, moderate, or severe AD dementia, confirmed by Clinical Dementia Rating scores, versus CN participants were estimated, using NACC UDS data. Participants were followed until death, censoring, or until information to determine disease stage was missing. RESULTS: Aged between 50 and 104 years, 12,414 participants met the eligibility criteria for the study. Participants progressing to MCI due to AD or AD dementia survived a median of 3-12 years, with higher mortality observed in more severe stages. Risk of death increased with the severity of AD dementia, with the increase significantly higher at younger ages. Participants with MCI due to AD and CN participants had a similar risk of death after controlling for confounding factors. CONCLUSIONS: Relative all-cause mortality risk increases with AD severity, more so at younger ages. Mortality does not seem to be higher for those remaining in MCI due to AD. Findings might imply potential benefit of lower mortality if preventing or delaying the progression of AD is successful, and importantly, this potential benefit might be greater in relatively younger people. Future research should replicate our study in other samples more representative of the general US population as well as other populations around the world.

The affordability of lecanemab, an amyloid-targeting therapy for Alzheimer's disease: an EADC-EC viewpoint.

Lecanemab, an anti-amyloid antibody with effects on biomarker and clinical endpoints in early Alzheimer's Disease (AD), was granted accelerated approval by the FDA in 2023 and regulatory review in Europe is ongoing. We estimate the population potentially eligible for treatment with lecanemab in the 27 EU countries to 5.4 million individuals. Treatment costs would exceed 133 billion EUR per year if the drug is priced similarly as in the United States, amounting to over half of the total pharmaceutical expenditures in the EU. This pricing would be unsustainable; the ability to pay for high-priced therapies varies substantially across countries. Pricing similarly to what has been announced for the United States may place the drug out of reach for patients in some European countries. Disparities in access to novel amyloid-targeting agents may further deepen the inequalities across Europe in health outcomes. As representatives of the European Alzheimer's Disease Consortium Executive Committee, we call for pricing policies that allow eligible patients across Europe to access important innovations, but also continued investments in research and development. Infrastructure to follow up the usage of new therapies in routine care and new payment models may be needed to address affordability and inequalities in patient access.

A Case of Minimally Progressive Prodromal Alzheimer's Disease.

Prodromal Alzheimer's disease (AD) is a neurodegenerative condition typically progressing to dementia within 3 years. We describe a case of a mild cognitive impairment (MCI) patient with biomarker evidence for amyloidosis, tau, and neurodegeneration who had minimal changes in clinical phenotype during an 11-year period. AD biomarkers were obtained with cerebrospinal fluid analysis and amyloid PET imaging, both of which supported a biological diagnosis of AD. However, the patient's neuropsychological profile remained stable over 11 years except for mild memory-retrieval changes. This case provides evidence that MCI with supportive AD biomarkers may have an atypically minimal progression.

Low Subicular Volume as an Indicator of Dementia-Risk Susceptibility in Old Age.

Introduction: Hippocampal atrophy is an established Alzheimer's Disease (AD) biomarker. Volume loss in specific subregions as measurable with ultra-high field magnetic resonance imaging (MRI) may reflect earliest pathological alterations. Methods: Data from positron emission tomography (PET) for estimation of cortical amyloid ß (Aß) and high-resolution 7 Tesla T1 MRI for assessment of hippocampal subfield volumes were analyzed in 61 non-demented elderly individuals who were divided into risk-categories as defined by high levels of cortical Aß and low performance in standardized episodic memory tasks. Results: High cortical Aß and low episodic memory interactively predicted subicular volume [F(3,57) = 5.90, p = 0.018]. The combination of high cortical Aß and low episodic memory was associated with significantly lower subicular volumes, when compared to participants with high episodic memory (p = 0.004). Discussion: Our results suggest that low subicular volume is linked to established indicators of AD risk, such as increased cortical Aß and low episodic memory. Our data support subicular volume as a marker of dementia-risk susceptibility in old-aged non-demented persons.

Methodological Issues in Randomized Clinical Trials for Prodromal Alzheimer's and Parkinson's Disease.

Alzheimer's disease (AD) and Parkinson's disease (PD) are the first and second most common neurodegenerative disorders, respectively. Both are proteinopathies with inexorable courses and no approved disease-modifying therapies. A substantial effort has been made to identify interventions that could slow down the progression of AD and PD; to date, with no success. The advances in biomarker research improved the identification of individuals at risk for these disorders before symptom onset, recognizing the pre-clinical stage, in which there is abnormal protein accumulation but no clinical symptoms of the disease, and the prodromal stage, in which mild symptoms are present but the clinical diagnostic criteria for disease cannot be fulfilled. The ability to detect pre-clinical and prodromal stages of these diseases has encouraged clinical trials for disease-modification at earlier phases, seeking to slow or prevent phenoconversion into clinical disease. Clinical trials at these stages have several challenges, such as the identification of the eligible population, the appropriate choice of biomarkers, the definition of clinical endpoints, the duration of follow-up, and the statistical analysis. This article aims to discuss some of the methodological challenges in the design of trials for pre-clinical and prodromal phases of AD and PD, to critically review the recent studies, and to discuss methodological approaches to mitigate these challenges in trial design.

On the horizon-the value and promise of the global pipeline of Alzheimer's disease therapeutics.

INTRODUCTION: The recent failure of several late-stage Alzheimer's disease (AD) clinical trials focused on amyloid beta (Aß) highlights the challenges of finding effective disease-modifying therapeutics. Despite major advances in our understanding of the genetic risk factors of disease and the development of clinical biomarkers, and that not all Aß-based approaches are equivalent, these failures may engender skepticism regarding the value of the AD pipeline. METHODS: To investigate these concerns, we compiled a database of current Phase 2 and 3 trials based on disease-modifying targets through a query of the National Institutes of Health's ClinicalTrials.gov. We then assessed the financial value of the pipeline. Financial modeling utilized risk-adjusted net present value (rNPV) measurements and included sensitivity analyses to help inform the drug development process. RESULTS: Results indicate that the preponderance of current Phase 3 trials were indeed targeting Aß, with only 15% addressing other targets. In contrast, the pipeline of Phase 2 trials was more diverse. The estimated rNPV of Phase 2 and 3 therapeutics was estimated to be $338 billion over 10 years. This figure increased to a theoretical cumulative value of $788 billion when incorporating the assumption that diagnostics will be developed to identify individuals at high risk for developing AD. Results from model sensitivity analyses showed that speed of market penetration and patient access contributed the most weight to financial value. In contrast, decreasing drug development costs had minimal impact on rNPV. DISCUSSION: These findings argue in favor of conducting thorough biomarker-driven Phase 2 proof of concept studies to avoid prematurely advancing assets into Phase 3. Insights from these analyses are also discussed in the context of the financial ecosystem needed to maintain a healthy AD pipeline.

The effect of ApoE ε 4 on clinical and structural MRI markers in prodromal Alzheimer's disease.

BACKGROUND: Apolipoprotein E (ApoE) ε 4 has been identified as the strongest genetic risk factor for Alzheimer's disease (AD). However, the importance of ApoE ε 4 on clinical and biological heterogeneity of AD is still to be determined, particularly at the prodromal stage. Here, we evaluate the association of ApoE ε 4 with clinical cognition and neuroimaging regions in mild cognitive impairment (MCI) participants based on the AT (N) system, which is increasingly essential for developing a precise assessment of AD. METHODS: We stratified 178 A+T+MCI participants (prodromal AD) into ApoE ε 4 (+) and ApoE ε 4 (-) according to ApoE genotype from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We determined Aß-positivity (A+) by the standardized uptake values ratios (SUVR) means of florbetapir-PET-AV45 (the cut-off value of 1.1) and fibrillar tau-positivity (T+) by cerebrospinal fluid (CSF) phosphorylated-tau at threonine 181 position (p-Tau) (cut-off value of 23 pg/mL). We evaluated the effect of ApoE ε 4 status on cognitive conditions and brain atrophy from structural magnetic resonance imaging (MRI) scans. A multivariate analysis of variance was used to compare the differences of cognitive scores and brain atrophy from structural MRI regions of interest (ROIs) between both groups. Furthermore, we performed a linear regression model to assess the correlation between signature ROIs of structural MRI and cognitive scores in the prodromal AD participants. RESULTS: ApoE ε 4 (+) prodromal AD participants had lower levels of CSF Aß 1-42, higher levels of t-Tau, more memory and global cognitive impairment, and faster decline of global cognition, compared to ApoE ε 4 (-) prodromal AD. ApoE ε 4 (+) prodromal AD participants had a thinner cortical thickness of bilateral entorhinal, smaller subcortical volume of the left amygdala, bilateral hippocampus, and left ventral diencephalon (DC) relative to ApoE ε 4 (-) prodromal AD. Furthermore, the cortical thickness average of bilateral entorhinal was highly correlated with memory and global cognition. CONCLUSIONS: ApoE ε 4 status in prodromal AD participants has an important effect on clinical cognitive domains. After ascertaining the ApoE ε 4 status, specific MRI regions can be correlated to the cognitive domain and will be helpful for precise assessment in prodromal AD.

Neuropsychological Contribution to Predict Conversion to Dementia in Patients with Mild Cognitive Impairment Due to Alzheimer's Disease.

BACKGROUND: Diagnosis of Alzheimer's disease (AD) confirmed by biomarkers allows the patient to make important life decisions. However, doubt about the fleetness of symptoms progression and future cognitive decline remains. Neuropsychological measures were extensively studied in prediction of time to conversion to dementia for mild cognitive impairment (MCI) patients in the absence of biomarker information. Similar neuropsychological measures might also be useful to predict the progression to dementia in patients with MCI due to AD. OBJECTIVE: To study the contribution of neuropsychological measures to predict time to conversion to dementia in patients with MCI due to AD. METHODS: Patients with MCI due to AD were enrolled from a clinical cohort and the effect of neuropsychological performance on time to conversion to dementia was analyzed. RESULTS: At baseline, converters scored lower than non-converters at measures of verbal initiative, non-verbal reasoning, and episodic memory. The test of non-verbal reasoning was the only statistically significant predictor in a multivariate Cox regression model. A decrease of one standard deviation was associated with 29% of increase in the risk of conversion to dementia. Approximately 50% of patients with more than one standard deviation below the mean in the z score of that test had converted to dementia after 3 years of follow-up. CONCLUSION: In MCI due to AD, lower performance in a test of non-verbal reasoning was associated with time to conversion to dementia. This test, that reveals little decline in the earlier phases of AD, appears to convey important information concerning conversion to dementia.

Use of mild cognitive impairment and prodromal AD/MCI due to AD in clinical care: a European survey.

INTRODUCTION: The diagnosis of mild cognitive impairment (MCI) refers to cognitive impairment not meeting dementia criteria. A survey among members of the American Association of Neurology (AAN) showed that MCI was considered a useful diagnosis. Recently, research criteria have been proposed for the diagnosis of Alzheimer's disease (AD) in MCI based on AD biomarkers (prodromal AD/MCI due to AD). The aim of this study was to investigate the attitudes of clinicians in Europe on the clinical utility of MCI and prodromal AD/MCI due to AD criteria. We also investigated whether the prodromal AD/MCI due to AD criteria impacted management of MCI patients. METHODS: An online survey was performed in 2015 among 102 members of the European Academy of Neurology (EAN) and the European Alzheimer's Disease Consortium (EADC). Questions were asked on how often criteria were used, how they were operationalized, how they changed patient management, and what were considered advantages and limitations of MCI and prodromal AD/MCI due to AD. The questionnaire consisted of 47 questions scored on a Likert scale. RESULTS: Almost all respondents (92%) used the MCI diagnosis in clinical practice. Over 80% of the EAN/EADC respondents found a MCI diagnosis useful because it helped to label the cognitive problem, involve patients in planning for the future, and start risk reduction activities. These findings were similar to those reported in the AAN survey. Research criteria for prodromal AD/MCI due to AD were used by 68% of the EAN/EADC respondents. The most common reasons to use the criteria were increased certainty of diagnosis (86%), increased possibilities to provide counseling (51%), facilitation of follow-up planning (48%), start of medical intervention (49%), and response to patients' wish for a diagnosis (41%). Over 70% of the physicians considered that a diagnosis of prodromal AD/MCI due to AD had an added value over the MCI diagnosis. CONCLUSIONS: The diagnostic criteria of MCI and prodromal AD/MCI due to AD are commonly used among EAN/EADC members. The prodromal AD/MCI due to AD were considered clinically useful and impacted patient management and communication.

Machine Learning Algorithm Helps Identify Non-Diagnosed Prodromal Alzheimer's Disease Patients in the General Population.

BACKGROUND: Recruiting patients for clinical trials of potential therapies for Alzheimer's disease (AD) remains a major challenge, with demand for trial participants at an all-time high. The AD treatment R and D pipeline includes around 112 agents. In the United States alone, 150 clinical trials are seeking 70,000 participants. Most people with early cognitive impairment consult primary care providers, who may lack time, diagnostic skills and awareness of local clinical trials. Machine learning and predictive analytics offer promise to boost enrollment by predicting which patients have prodromal AD, and which will go on to develop AD. OBJECTIVES: The authors set out to develop a machine learning predictive model that identifies prodromal AD patients in the general population, to aid early AD detection by primary care physicians and timely referral to expert sites for biomarker confirmation of diagnosis and clinical trial enrollment. DESIGN: The authors use a classification machine learning algorithm to extract patterns within healthcare claims and prescription data three years prior to AD diagnosis/AD drug initiation. SETTING: The study focused on subjects included within proprietary IQVIA US data assets (claims and prescription databases). Patient information was extracted from January 2010 to July 2018, for cohorts aged between 50 and 85 years. PARTICIPANTS: A total of 88,298,289 subjects aged between 50 and 85 years were identified. For the positive cohort, 667,288 subjects were identified who had 24 months of medical history and at least one record with AD or AD treatment. For the negative cohort, 3,670,254 patients were selected who had a similar length of medical history and who were matched to positive cohort subjects based on the prevalence rate. The scoring cohort was selected based on availability of recent medical data of 2-5 years and included 72,670,283 subjects between the ages of 50 and 85 years. Intervention (if any): None. MEASUREMENTS: A list of clinically-relevant and interpretable predictors was generated and extracted from the data sets for each subject, including pharmacological treatments (NDC/product), office/specialist visits (specialty), tests and procedures (HCPCS and CPT), and diagnosis (ICD). The positive cohort was defined as patients who have AD diagnosis/AD treatment with a 3 years offset as an estimate for prodromal AD diagnosis. Supervised ML techniques were used to develop algorithms to predict the occurrence of prodromal AD cases. The sample dataset was divided randomly into a training dataset and a test dataset. The classification models were trained and executed in the PySpark framework. Training and evaluation of LogisticRegression, DecisionTreeClassifier, RandomForestClassifier, and GBTClassifier were executed using PySpark's mllib module. The area under the precision-recall curve (AUCPR) was used to compare the results of the various models. RESULTS: The AUCPRs are 0.426, 0.157, 0.436, and 0.440 for LogisticRegression, DecisionTreeClassifier, RandomForestClassifier, and GBTClassifier, respectively, meaning that GBTClassifier (Gradient Boosted Tree) outperforms the other three classifiers. The GBT model identified 222,721 subjects in the prodromal AD stage with 80% precision. Some 76% of identified prodromal AD patients were in the primary care setting. CONCLUSIONS: Applying the developed predictive model to 72,670,283 U.S. residents, 222,721 prodromal AD patients were identified, the majority of whom were in the primary care setting. This could drive major advances in AD research by enabling more accurate and earlier prodromal AD diagnosis at the primary care physician level , which would facilitate timely referral to expert sites for in-depth assessment and potential enrolment in clinical trials.

Alzheimer's disease Archimedes condition-event simulator: Development and validation.

INTRODUCTION: Several advances have been made in Alzheimer's Disease (AD) modeling, however, there remains a need for a simulator that represents the full scope of disease progression and can be used to study new disease-modifying treatments for early-stage and even prodromal AD. METHODS: We developed AD Archimedes condition-event simulator, a patient-level simulator with a focus on simulating the effects of early interventions through changes in biomarkers of AD. The simulator incorporates interconnected predictive equations derived from longitudinal data sets. RESULTS: The results of external validations on AD Archimedes condition-event simulator showed that it provides reasonable estimates once compared to literature results on transition to dementia AD, institutionalization, and mortality. A case study comparing a disease-modifying treatment and a symptomatic treatment also showcases the benefits of early treatment. DISCUSSION: The AD Archimedes condition-event simulator is designed to perform economic evaluation on various interventions through close tracking of disease progression and the related clinical outcomes.

European Prevention of Alzheimer's Dementia Registry: Recruitment and prescreening approach for a longitudinal cohort and prevention trials.

INTRODUCTION: It is a challenge to find participants for Alzheimer's disease (AD) prevention trials within a short period of time. The European Prevention of Alzheimer's Dementia Registry (EPAD) aims to facilitate recruitment by preselecting subjects from ongoing cohort studies. This article introduces this novel approach. METHODS: A virtual registry, with access to risk factors and biomarkers for AD through minimal data sets of ongoing cohort studies, was set up. RESULTS: To date, ten cohorts have been included in the EPAD. Around 2500 participants have been selected, using variables associated with the risk for AD. Of these, 15% were already recruited in the EPAD longitudinal cohort study, which serves as a trial readiness cohort. DISCUSSION: This study demonstrates that a virtual registry can be used for the preselection of participants for AD studies.

Temporal unfolding of declining episodic memory on the Free and Cued Selective Reminding Test in the predementia phase of Alzheimer's disease: Implications for clinical trials.

INTRODUCTION: Free and Cued Selective Reminding Test (FCSRT) performance identifies patients with preclinical disease at elevated risk for developing Alzheimer's dementia, predicting diagnosis better than other memory tests. METHODS: Based on literature mapping FCSRT performance to clinical outcomes and biological markers, and on longitudinal preclinical data from the Baltimore Longitudinal Study of Aging, we developed the Stages of Objective Memory Impairment (SOMI) model. Five sequential stages of episodic memory decline are defined by Free Recall (FR) and Total Recall (TR) score ranges and years prior to dementia diagnosis. We sought to replicate the SOMI model using longitudinal assessments of 142 Einstein Aging Study participants who developed AD over 10 years. RESULTS: Time to diagnosis was at least seven years if FR was intact, at least four years if TR was intact, and two years if TR was impaired, consistent with SOMI model predictions. The SOMI identified incipient dementia with excellent sensitivity and specificity. DISCUSSION: The SOMI model provides an efficient approach for clinical trial cognitive screening in advance of more costly biomarker studies and ultimately in clinical practice, and provides a vocabulary for understanding AD biomarker patterns and for re-analysis of existing clinical trial data.

The structural MRI markers and cognitive decline in prodromal Alzheimer's disease: a 2-year longitudinal study.

BACKGROUND: Being clinically diagnosed with a mild cognitive impairment (MCI) due to Alzheimer's disease (AD) is widely studied. Yet, the clinical and structural neuroimaging characteristics for prodromal AD, which are defined as A+T+MCI based on the AT (N) system are still highly desirable. This study evaluates the differences of the cognitive assessments and structural magnetic resonance imaging (MRI) between the early MCI (EMCI) and late MCI (LMCI) participants based on the AT (N) system. The potential clinical value of the structural MRI as a predictor of cognitive decline during follow-up in prodromal AD is further investigated. METHODS: A total of 406 MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were chosen and dichotomized into EMCI and LMCI groups according to the Second Edition (Logical Memory II) Wechsler Memory Scale. Multiple markers' data was collected, including age, sex, years of education, ApoE4 status, cerebrospinal fluid (CSF) biomarkers, standardized uptake values ratios (SUVR) means of florbetapir-PET-AV45, cognitive measures, and structural MRI. We chose 197 A+T+MCI participants (prodromal AD) with positive biomarkers of Aß plaques (labeled "A") and fibrillar tau (labeled "T"). We diagnosed Aß plaques positive by the SUVR means of florbetapir-PET-AV45 (cut-off >1.1) and fibrillar tau positive by CSF phosphorylated-tau at threonine 181 (p-tau) (cut-off >23 pg/mL). The differences of cognitive assessments and regions of interest (ROIs) defined on the MRI template between EMCI and LMCI were compared. Furthermore, the potential clinical utility of the MRI as the predictor of cognitive decline in prodromal AD was evaluated by investigating the relationship between baseline MRI markers and cognition decline at the follow-up period, through a linear regression model. RESULTS: The LMCI participants had a significantly more amyloid burden and CSF levels of total t-tau than the EMCI participants. The LMCI participants scored a lower result than the EMCI group in the global cognition scales and subscales which included tests for memory, delayed recall memory, executive function, language, attention and visuospatial skills. The cognition levels declined faster in the LMCI participants during the 12- and 24-month follow-up. There were significant differences in ROIs on the structural MRI between the two groups, including a bilateral entorhinal, a bilateral hippocampus, a bilateral amygdala, a bilateral lateral ventricle and cingulate, a corpus callosum, and a left temporal. The thickness average of the left entorhinal, the left middle temporal, the left superior temporal, and the right isthmus cingulate was a main contributor to the decreased global cognition levels. The thickness average of the left superior temporal and bilateral entorhinal played a key role in the memory domain decline. The thickness average of the left middle temporal, and the right isthmus cingulate was significantly associated with an executive function decline. CONCLUSIONS: Based on the AT (N) system, surely, both the EMCI and LMCI diagnoses presented significant differences in multiple cognition domains. Signature ROIs from the structural MRI tests had correlated a cognitive decline, and could act as one potential predictive marker.

Alzheimer's disease drug development pipeline: 2017.

INTRODUCTION: There is an urgent need to develop new treatments for Alzheimer's disease (AD) and to understand the drug development process for new AD therapies. METHODS: We assessed the agents in the AD pipeline as documented in clinicaltrials.gov for phase I, phase II, and phase III, accessed 1/5/2017. RESULTS: There are 105 agents in the AD treatment development pipeline, of which 25 agents are in 29 trials in phase I, 52 agents are in 68 trials in phase II, and 28 agents are in 42 trials in phase III. Seventy percent of drugs in the AD pipeline are disease-modifying therapies (DMTs). Fourteen percent are symptomatic cognitive enhancers, and 13% are symptomatic agents addressing neuropsychiatric and behavioral changes (2% have undisclosed mechanisms). Most trials are sponsored by the biopharmaceutical industry. Trials include patients with preclinical AD (cognitively normal with biomarker evidence of AD), prodromal AD (mild cognitive symptoms and biomarker evidence of AD), and AD dementia. Biomarkers are included in many drug development programs particularly those for DMTs. Thirteen of 46 phase II DMT trials have amyloid imaging as an entry criterion, and 10 of 28 phase III trials incorporate amyloid imaging for diagnosis and entry. A large number of participants are needed for AD clinical trials; in total, 54,073 participants are required for trials spanning preclinical AD to AD dementia. When compared with the 2016 pipeline, there are eight new agents in phase I, 16 in phase II, and five in phase III. DISCUSSION: The AD drug development pipeline has 105 agents divided among phase I, phase II, and phase III. The trials include a wide range of clinical trial populations, many mechanisms of action, and require a substantial number of clinical trial participants. Biomarkers are increasingly used in patient identification and as outcome measures, particularly in trials of DMTs.

Electroencephalography-driven approach to prodromal Alzheimer's disease diagnosis: from biomarker integration to network-level comprehension.

Decay of the temporoparietal cortex is associated with prodromal Alzheimer's disease (AD). Additionally, shrinkage of the temporoparietal cerebral area has been connected with an increase in α3/α2 electroencephalogram (EEG) power ratio in prodromal AD. Furthermore, a lower regional blood perfusion has been exhibited in patients with a higher α3/α2 proportion when contrasted with low α3/α2 proportion. Furthermore, a lower regional blood perfusion and reduced hippocampal volume has been exhibited in patients with higher α3/α2 when contrasted with lower α3/α2 EEG power ratio. Neuropsychological evaluation, EEG recording, and magnetic resonance imaging were conducted in 74 patients with mild cognitive impairment (MCI). Estimation of cortical thickness and α3/α2 frequency power ratio was conducted for each patient. A subgroup of 27 patients also underwent single-photon emission computed tomography evaluation. In view of α3/α2 power ratio, the patients were divided into three groups. The connections among cortical decay, cerebral perfusion, and memory loss were evaluated by Pearson's r coefficient. Results demonstrated that higher α3/α2 frequency power ratio group was identified with brain shrinkage and cutdown perfusion inside the temporoparietal projections. In addition, decay and cutdown perfusion rate were connected with memory shortfalls in patients with MCI. MCI subgroup with higher α3/α2 EEG power ratio are at a greater risk to develop AD dementia.