Alzheimer's disease is a heterogenous disorder with multiple phenotypes and genotypes, although they eventually converge to a final common clinicopathological endpoint. However, Alzheimer's disease ...drug trials do not account for the heterogeneity of the disease in trial design, impeding development of effective drugs.
Alzheimer's disease drug trials commonly have wide inclusion criteria that subsume multiple subtypes of the condition, with varying genotypes, phenotypes, and clinical courses. The outcome variables used in many trials may not be sensitive for the particular disease subtype and trials may not follow patients for the appropriate length of time necessary for the subtype of disease. Methods of stratifying treatment trial design to account for disease heterogeneity using algorithms incorporating demographics, neuroimaging, genetics, and clinical phenotypes, as well as more tailored outcome measures, are proposed to allow for personalized, precision medicine in Alzheimer's disease therapeutics development. Approaching Alzheimer's disease as a heterogenous disorder will likely improve yield in the search for effective treatments for the condition.
There is a high rate of failure in Alzheimer's disease (AD) drug development with 99% of trials showing no drug-placebo difference. This low rate of success delays new treatments for patients and ...discourages investment in AD drug development. Studies across drug development programs in multiple disorders have identified important strategies for decreasing the risk and increasing the likelihood of success in drug development programs. These experiences provide guidance for the optimization of AD drug development. The "rights" of AD drug development include the right target, right drug, right biomarker, right participant, and right trial. The right target identifies the appropriate biologic process for an AD therapeutic intervention. The right drug must have well-understood pharmacokinetic and pharmacodynamic features, ability to penetrate the blood-brain barrier, efficacy demonstrated in animals, maximum tolerated dose established in phase I, and acceptable toxicity. The right biomarkers include participant selection biomarkers, target engagement biomarkers, biomarkers supportive of disease modification, and biomarkers for side effect monitoring. The right participant hinges on the identification of the phase of AD (preclinical, prodromal, dementia). Severity of disease and drug mechanism both have a role in defining the right participant. The right trial is a well-conducted trial with appropriate clinical and biomarker outcomes collected over an appropriate period of time, powered to detect a clinically meaningful drug-placebo difference, and anticipating variability introduced by globalization. We lack understanding of some critical aspects of disease biology and drug action that may affect the success of development programs even when the "rights" are adhered to. Attention to disciplined drug development will increase the likelihood of success, decrease the risks associated with AD drug development, enhance the ability to attract investment, and make it more likely that new therapies will become available to those with or vulnerable to the emergence of AD.
Timely diagnosis of Alzheimer's disease (AD) refers to a diagnosis at the stage when patients come to the attention of clinicians because of concerns about changes in cognition, behavior, or ...functioning and can be still free of dementia and functionally independent.
To comprehensively review existing scientific evidence on the benefits and potential challenges of making a timely diagnosis of AD.
Relevant studies were identified by searching electronic databases (Medline, Embase) and bibliographies for studies published in English between 1 January 2000 and 2 June 2014 on the consequences of a timely diagnosis of AD.
Nine studies were identified that investigated the consequences of diagnosing AD at the initial stages; none were specifically focused on prodromal AD. A timely diagnosis potentially offers the opportunities of early intervention, implementation of coordinated care plans, better management of symptoms, patient safety, cost savings, and postponement of institutionalization. Barriers to making a timely diagnosis include stigma, suicide risk, lack of training, diagnostic uncertainty, shortage of specialized diagnostic services, and the reluctance of healthcare providers to make a diagnosis when no effective disease-modifying options are available.
Despite its potential benefits, few published studies have explored the advantages or risks of a timely diagnosis of AD. In light of the cultural shift toward diagnosis at the initial stage of the disease continuum, when the patient does not yet have dementia, more investigations are needed to evaluate the benefits and address the barriers that may impede making a timely AD diagnosis.
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with a complex and heterogeneous pathophysiology. The number of people living with AD is predicted to increase; however, there are ...no disease-modifying therapies currently available and none have been successful in late-stage clinical trials. Fluid biomarkers measured in cerebrospinal fluid (CSF) or blood hold promise for enabling more effective drug development and establishing a more personalized medicine approach for AD diagnosis and treatment. Biomarkers used in drug development programmes should be qualified for a specific context of use (COU). These COUs include, but are not limited to, subject/patient selection, assessment of disease state and/or prognosis, assessment of mechanism of action, dose optimization, drug response monitoring, efficacy maximization, and toxicity/adverse reactions identification and minimization. The core AD CSF biomarkers Aβ42, t-tau, and p-tau are recognized by research guidelines for their diagnostic utility and are being considered for qualification for subject selection in clinical trials. However, there is a need to better understand their potential for other COUs, as well as identify additional fluid biomarkers reflecting other aspects of AD pathophysiology. Several novel fluid biomarkers have been proposed, but their role in AD pathology and their use as AD biomarkers have yet to be validated. In this review, we summarize some of the pathological mechanisms implicated in the sporadic AD and highlight the data for several established and novel fluid biomarkers (including BACE1, TREM2, YKL-40, IP-10, neurogranin, SNAP-25, synaptotagmin, α-synuclein, TDP-43, ferritin, VILIP-1, and NF-L) associated with each mechanism. We discuss the potential COUs for each biomarker.
Neuronal network dysfunction is increasingly recognized as an early symptom in Alzheimer's disease (AD) and may provide new entry points for diagnosis and intervention. Here, we show that ...amyloid-beta-induced hyperexcitability of hippocampal inhibitory parvalbumin (PV) interneurons importantly contributes to neuronal network dysfunction and memory impairment in APP/PS1 mice, a mouse model of increased amyloidosis. We demonstrate that hippocampal PV interneurons become hyperexcitable at ~16 weeks of age, when no changes are observed yet in the intrinsic properties of pyramidal cells. This hyperexcitable state of PV interneurons coincides with increased inhibitory transmission onto hippocampal pyramidal neurons and deficits in spatial learning and memory. We show that treatment aimed at preventing PV interneurons from becoming hyperexcitable is sufficient to restore PV interneuron properties to wild-type levels, reduce inhibitory input onto pyramidal cells, and rescue memory deficits in APP/PS1 mice. Importantly, we demonstrate that early intervention aimed at restoring PV interneuron activity has long-term beneficial effects on memory and hippocampal network activity, and reduces amyloid plaque deposition, a hallmark of AD pathology. Taken together, these findings suggest that early treatment of PV interneuron hyperactivity might be clinically relevant in preventing memory decline and delaying AD progression.
Objective
We investigated the association of plasma amyloid beta (Abeta)40, Abeta42, and total tau (tTau) with the presence of Alzheimer pathological changes in cognitively normal individuals with ...subjective cognitive decline (SCD).
Methods
We included 248 subjects with SCD (61 ± 9 years, 42% female, Mini‐Mental State Examination = 28 ± 2) from the SCIENCe project and Amsterdam Dementia Cohort. Subjects were dichotomized as amyloid abnormal by cerebrospinal fluid (CSF) and positron emission tomography (PET). Baseline plasma Abeta40, Abeta42, and tTau were measured using Simoa technology. Associations between plasma levels and amyloid status were assessed using logistic regression analyses and receiver operating characteristic analyses. Association of plasma levels with risk of clinical progression to mild cognitive impairment (MCI) or dementia was assessed using Cox proportional hazard models.
Results
Fifty‐seven (23%) subjects were CSF‐amyloid abnormal. Plasma Abeta42/Abeta40 ratio and plasma Abeta42 alone, but not tTau, identified abnormal CSF‐amyloid status (plasma ratio: area under the curve AUC = 77%, 95% confidence interval CI = 69–84%; plasma Abeta42: AUC = 66%, 95% CI: 58–74%). Combining plasma ratio with age and apolipoprotein E resulted in AUC = 83% (95% CI = 77–89%). The Youden cutoff of the plasma ratio gave a sensitivity of 76% and specificity of 75%, and applying this as a prescreener would reduce the number of lumbar punctures by 51%. Using PET as outcome, a comparable reduction in number of PET scans would be achieved when applying the plasma ratio as prescreener. In addition, low plasma ratio was associated with clinical progression to MCI or dementia (hazard ratio = 2.0, 95% CI = 1.4–2.3).
Interpretation
Plasma Abeta42/Abeta40 ratio has potential as a prescreener to identify Alzheimer pathological changes in cognitively normal individuals with SCD. Ann Neurol 2018;84:656–666
Background and Purpose- Cerebral small vessel disease is characterized by a wide range of focal and global brain changes. We used a magnetic resonance imaging segmentation tool to quantify multiple ...types of small vessel disease-related brain changes and examined their individual and combined predictive value on cognitive and functional abilities. Methods- Magnetic resonance imaging scans of 560 older individuals from LADIS (Leukoaraiosis and Disability Study) were analyzed using automated atlas- and convolutional neural network-based segmentation methods yielding volumetric measures of white matter hyperintensities, lacunes, enlarged perivascular spaces, chronic cortical infarcts, and global and regional brain atrophy. The subjects were followed up with annual neuropsychological examinations for 3 years and evaluation of instrumental activities of daily living for 7 years. Results- The strongest predictors of cognitive performance and functional outcome over time were the total volumes of white matter hyperintensities, gray matter, and hippocampi (
<0.001 for global cognitive function, processing speed, executive functions, and memory and
<0.001 for poor functional outcome). Volumes of lacunes, enlarged perivascular spaces, and cortical infarcts were significantly associated with part of the outcome measures, but their contribution was weaker. In a multivariable linear mixed model, volumes of white matter hyperintensities, lacunes, gray matter, and hippocampi remained as independent predictors of cognitive impairment. A combined measure of these markers based on
scores strongly predicted cognitive and functional outcomes (
<0.001) even above the contribution of the individual brain changes. Conclusions- Global burden of small vessel disease-related brain changes as quantified by an image segmentation tool is a powerful predictor of long-term cognitive decline and functional disability. A combined measure of white matter hyperintensities, lacunar, gray matter, and hippocampal volumes could be used as an imaging marker associated with vascular cognitive impairment.
Abstract The interrelationships between pathological processes and emerging clinical phenotypes in Alzheimer's disease (AD) are important yet complicated to study, because the brain is a complex ...network where local disruptions can have widespread effects. Recently, properties in brain networks obtained with neuroimaging techniques have been studied in AD with tools from graph theory. However, the interpretation of graph alterations remains unclear, because the definition of connectivity depends on the imaging modality used. Here we examined which graph properties have been consistently reported to be disturbed in AD studies, using a heuristically defined “graph space” to investigate which theoretical models can best explain graph alterations in AD. Findings from structural and functional graphs point to a loss of highly connected areas in AD. However, studies showed considerable variability in reported group differences of most graph properties. This suggests that brain graphs might not be isometric, which complicates the interpretation of graph measurements. We highlight confounding factors such as differences in graph construction methods and provide recommendations for future research.
The concept of the right temporal variant of frontotemporal dementia (rtvFTD) is still equivocal. The syndrome accompanying predominant right anterior temporal atrophy has previously been described ...as memory loss, prosopagnosia, getting lost and behavioural changes. Accurate detection is challenging, as the clinical syndrome might be confused with either behavioural variant FTD (bvFTD) or Alzheimer's disease. Furthermore, based on neuroimaging features, the syndrome has been considered a right-sided variant of semantic variant primary progressive aphasia (svPPA). Therefore, we aimed to demarcate the clinical and neuropsychological characteristics of rtvFTD versus svPPA, bvFTD and Alzheimer's disease. Moreover, we aimed to compare its neuroimaging profile against svPPA, which is associated with predominant left anterior temporal atrophy. Of 619 subjects with a clinical diagnosis of frontotemporal dementia or primary progressive aphasia, we included 70 subjects with a negative amyloid status in whom predominant right temporal lobar atrophy was identified based on blinded visual assessment of their initial brain MRI scans. Clinical symptoms were assessed retrospectively and compared with age- and sex-matched patients with svPPA (n = 70), bvFTD (n = 70) and Alzheimer's disease (n = 70). Prosopagnosia, episodic memory impairment and behavioural changes such as disinhibition, apathy, compulsiveness and loss of empathy were the most common initial symptoms, whereas during the disease course, patients developed language problems such as word-finding difficulties and anomia. Distinctive symptoms of rtvFTD compared to the other groups included depression, somatic complaints, and motor/mental slowness. Aside from right temporal atrophy, the imaging pattern showed volume loss of the right ventral frontal area and the left temporal lobe, which represented a close mirror image of svPPA. Atrophy of the bilateral temporal poles and the fusiform gyrus were associated with prosopagnosia in rtvFTD. Our results highlight that rtvFTD has a unique clinical presentation. Since current diagnostic criteria do not cover specific symptoms of the rtvFTD, we propose a diagnostic tree to be used to define diagnostic criteria and call for an international validation.
Alzheimer's disease (AD) is a heterogeneous disorder with complex underlying neuropathology that is still not completely understood. For better understanding of this heterogeneity, we aimed to ...identify cognitive subtypes using latent class analysis (LCA) in a large sample of patients with AD dementia. In addition, we explored the relationship between the identified cognitive subtypes, and their demographical and neurobiological characteristics.
We performed LCA based on neuropsychological test results of 938 consecutive probable patients with AD dementia using Mini-Mental State Examination as the covariate. Subsequently, we performed multinomial logistic regression analysis with cluster membership as dependent variable and dichotomised demographics, APOE genotype, cerebrospinal fluid biomarkers and MRI characteristics as independent variables.
LCA revealed eight clusters characterised by distinct cognitive profile and disease severity. Memory-impaired clusters-mild-memory (MILD-MEM) and moderate-memory (MOD-MEM)-included 43% of patients. Memory-spared clusters mild-visuospatial-language (MILD-VILA), mild-executive (MILD-EXE) and moderate-visuospatial (MOD-VISP) -included 29% of patients. Memory-indifferent clusters mild-diffuse (MILD-DIFF), moderate-language (MOD-LAN) and severe-diffuse (SEV-DIFF) -included 28% of patients. Cognitive clusters were associated with distinct demographical and neurobiological characteristics. In particular, the memory-spared MOD-VISP cluster was associated with younger age, APOE e4 negative genotype and prominent atrophy of the posterior cortex.
Using LCA, we identified eight distinct cognitive subtypes in a large sample of patients with AD dementia. Cognitive clusters were associated with distinct demographical and neurobiological characteristics.
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