In the next 15 years, Canada is predicted to face a doubling in its population affected by dementia. By 2038, an estimated 1.1 million Canadians will be experiencing dementia, with unprecedented impact on social, economic and health landscapes. In September 2015, the Canadian Academy of Health Sciences convened a Forum, with the specific thematic goals of reviewing progress towards effective dementia treatment and prevention, improved systems of care, advanced living and built environments, and impactful technology developments. The orientation of the Forum was to focus on potential solutions and advances in these areas. These areas are integral to the goal of a national end-to-end program, where all affected Canadians can be optimally supported in their communities and receive quality of care - regardless of where they live or who they are.

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.

A majority of patients with Alzheimer's disease (AD) experience some form of sleep disruption, including nocturnal sleep fragmentation, increased daytime napping, decreased slow-wave sleep (SWS, stage N3), and decreased rapid-eye-movement sleep (REM). Clinical studies are investigating whether such sleep disturbances are a consequence of the underlying disease, and whether they also contribute to the clinical and pathological manifestations of AD. Emerging research has provided a direct link between several of these sleep disruptions and AD pathophysiology, suggesting that treating sleep disorders in this population may target basic mechanisms of the disease. Here, we provide a comprehensive review of sleep disturbances associated with the spectrum of AD, ranging from the preclinical stages through dementia. We discuss how sleep interacts with AD pathophysiology and, critically, whether sleep impairments can be targeted to modify the disease course in a subgroup of affected AD patients. Ultimately, larger studies that fully utilize new diagnostic and experimental tools will be required to better define the most relevant sleep disturbance to target in AD, the interventions that best modulate this target symptom, and whether successful early intervention can modify AD risk and prevent dementia.

We performed case-control studies using 2 Canadian cohorts to examine the role of 10 promising Alzheimer's disease (AD) loci identified in recent genomewide association studies. Patients age 65 years and older diagnosed with AD at baseline (prevalent cases) or who developed AD during follow-up assessments (incident cases) were compared with control subjects with no cognitive impairment. Our prevalent case study comparing prevalent AD cases (n = 428) with participants with no cognitive impairment (n = 524) revealed a significant association of rs6656401 and rs3818361 (CR1), rs2075650 (TOMM40), rs7561528 (BIN1), and rs3865444 (CD33) with late-onset AD that were robust to adjustment with age and apolipoprotein E ε4 genotype. The incident case study comparing patients who developed AD during longitudinal observation (n = 152) with participants with no cognitive impairment found that rs2075650 (TOMM40) and rs3865444 (CD33) influence the risk of developing AD in this population. In addition, pooled analysis of our AD patients confirmed that CR1, TOMM40, BIN1, and CD33 contribute to late-onset AD susceptibility, in addition to apolipoprotein E.

Behavioral-variant frontotemporal dementia (bvFTD) is challenging to recognize, and often misdiagnosed as depression (DEP). Evidence suggests changes in social cognition (SoCog) precede general cognitive decline in bvFTD. Currently, there are no screening measures of social cognition. 17 bvFTD, 16 DEP, and 18 control participants underwent 6 SoCog tests measuring: emotion recognition; theory of mind; empathy; insight. We used χ 2 , Wilcoxon rank sum, Kruskal-Wallis tests to compare groups, with decision tree analysis to identify items that best differentiated bvFTD from DEP. bvFTD performed significantly worse on all SoCog tasks compared with other groups. Decision tree analysis yielded a 5-item test with ROC area under the curve of 0.973 (95% CI: 0.928, 1.0) for differentiating bvFTD versus depression. These results suggest that it may be feasible to develop a screening measure of social cognition.

Cerebrospinal fluid (CSF) biomarkers amyloid-β and tau have been validated for the antemortem diagnosis of Alzheimer disease (AD) and are included in the AT(N) research framework for AD. Recently, an AT(N) CSF profile has been described for dementia with Lewy bodies (DLB), a disorder which is difficult to distinguish clinically from AD, particularly early in the disease course. Herein we describe a 71-year old male who presented with an atypical dementia syndrome including years of stability after an initial abrupt decline, marked visuospatial dysfunction, and relative sparing of memory. CSF biomarkers combined with the pattern of cognitive symptoms made AD unlikely and were consistent with DLB. This classification was confirmed clinically, with the emergence of classic DLB symptoms, and at postmortem pathologic examination. This case highlights the role for AD CSF biomarkers in facilitating earlier diagnosis of non-Alzheimer neurodegenerative dementias.

Introduction

Cognitive composite scales constructed by combining existing neuropsychometric tests are seeing wide application as endpoints for clinical trials and cohort studies of Alzheimer's disease (AD) predementia conditions. Preclinical Alzheimer's Cognitive Composite (PACC) scales are composite scores calculated as the sum of the component test scores weighted by the reciprocal of their standard deviations at the baseline visit. Reciprocal standard deviation is an arbitrary weighting in this context, and may be an inefficient utilization of the data contained in the component measures. Mathematically derived optimal composite weighting is a promising alternative.

Methods

Sample size projections using standard power calculation formulas were used to describe the relative performance of component measures and their composites when used as endpoints for clinical trials. Power calculations were informed by (n=1,333) amnestic mild cognitive impaired participants in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set.

Results

A composite constructed using PACC reciprocal standard deviation weighting was both less sensitive to change than one of its component measures and less sensitive to change than its optimally weighted counterpart. In standard sample size calculations informed by NACC data, a clinical trial using the PACC weighting would require 38% more subjects than a composite calculated using optimal weighting.

Discussion

These findings illustrate how reciprocal standard deviation weighting can result in inefficient cognitive composites, and underscore the importance of component weights to the performance of composite scales. In the future, optimal weighting parameters informed by accumulating clinical trial data may improve the efficiency of clinical trials in AD.

As our understanding of the neurobiology of Alzheimer Disease deepens, it has become evident that early intervention is critical to achieving successful therapeutic impact. The availability of diagnostic criteria for preclinical Alzheimer Disease adds momentum to research directed at this goal and even to prevention. The landscape of therapeutic research is thus poised to undergo a dramatic shift in the next 5-10 years, with clinical trials involving subjects at risk for Alzheimer Disease who have few or no symptoms. These trials will also likely rely heavily on genetics, biomarkers, and or risk factor stratification to identify individuals at risk for Alzheimer Disease. Here, we propose a conceptual framework to guide this next generation of pharmacological and non-pharmacological clinical pursuit, and discuss some of the foreseeable ethical considerations that may accompany them.

Background

There are currently no treatments for empathy deficits in neuropsychiatric disorders. Acute administration of the hormone oxytocin has been associated with symptomatic improvements across animal models and several neuropsychiatric disorders, but results of the majority of oxytocin randomised controlled trials (RCTs) of longer duration have been negative or inconclusive. This lack of efficacy of may be due to rapid habituation to oxytocin with chronic dosing. The objective of the present study is to describe the design of a phase 2 adaptive randomised controlled crossover trial of intranasal oxytocin in frontotemporal dementia (FOXY) as an efficient model for future investigations of symptomatic treatments in neuropsychiatric and neurodegenerative disorders.

Methods

Stage 1 will identify which of three dose schedules is most promising based on change in the primary outcome measure, the Neuropsychiatric Inventory apathy/indifference domain score, over 6 weeks of treatment. In stage 2, additional patients are enrolled at the most promising dose for preliminary efficacy analysis when combined with stage 1 to determine if a phase 3 trial is warranted. Objective measures include facial expression recognition, cerebrospinal fluid (CSF) oxytocin levels, and behavioural ratings of videotaped interactions.

Results

A total of 20 patients per arm will be entered into stage 1 for a total of 60 patients. In stage 2, an additional 40 patients will be enrolled in the most promising dose arm.

Conclusions

The use of adaptive, crossover designs and inclusion of objective measures of change in CSF oxytocin levels and social behaviour will improve the efficiency and conclusiveness of RCTs of oxytocin and other symptomatic treatments in neuropsychiatric disorders.

Trial registration

ClinicalTrials.gov, NCT03260920 . Registered on August 24, 2017.