The DIAN-TU Next Generation Alzheimer's prevention trial: Adaptive design and disease progression model

Gantenerumab: an anti-amyloid monoclonal antibody with potential disease-modifying effects in early Alzheimer's disease

BACKGROUND

This review describes the research and development process of gantenerumab, a fully human anti-amyloid monoclonal antibody in development to treat early symptomatic and asymptomatic Alzheimer's disease (AD). Anti-amyloid monoclonal antibodies can substantially reverse amyloid plaque pathology and may modify the course of the disease by slowing or stopping its clinical progression. Several molecules targeting amyloid have failed in clinical development due to drug-related factors (e.g., treatment-limiting adverse events, low potency, poor brain penetration), study design/methodological issues (e.g., disease stage, lack of AD pathology confirmation), and other factors. The US Food and Drug Administration's approval of aducanumab, an anti-amyloid monoclonal antibody as the first potential disease-modifying therapy for AD, signaled the value of more than 20 years of drug development, adding to the available therapies the first nominal success since cholinesterase inhibitors and memantine were approved. BODY: Here, we review over 2 decades of gantenerumab development in the context of scientific discoveries in the broader AD field. Key learnings from the field were incorporated into the gantenerumab phase 3 program, including confirmed amyloid positivity as an entry criterion, an enriched clinical trial population to ensure measurable clinical decline, data-driven exposure-response models to inform a safe and efficacious dosing regimen, and the use of several blood-based biomarkers. Subcutaneous formulation for more pragmatic implementation was prioritized as a key feature from the beginning of the gantenerumab development program.

CONCLUSION

The results from the gantenerumab phase 3 programs are expected by the end of 2022 and will add critical information to the collective knowledge on the search for effective AD treatments.

The European Prevention of Alzheimer's Dementia Programme: An Innovative Medicines Initiative-funded partnership to facilitate secondary prevention of Alzheimer's disease dementia

INTRODUCTION

Tens of millions of people worldwide will develop Alzheimer's disease (AD), and only by intervening early in the preclinical disease can we make a fundamental difference to the rates of late-stage disease where clinical symptoms and societal burden manifest. However, collectively utilizing data, samples, and knowledge amassed by large-scale projects such as the Innovative Medicines Initiative (IMI)-funded European Prevention of Alzheimer's Dementia (EPAD) program will enable the research community to learn, adapt, and implement change.

METHOD

In the current article, we define and discuss the substantial assets of the EPAD project for the scientific community, patient population, and industry, describe the EPAD structure with a focus on how the public and private sector interacted and collaborated within the project, reflect how IMI specifically supported the achievements of the above, and conclude with a view for future.

RESULTS

The EPAD project was a €64-million investment to facilitate secondary prevention of AD dementia research. The project recruited over 2,000 research participants into the EPAD longitudinal cohort study (LCS) and included over 400 researchers from 39 partners. The EPAD LCS data and biobank are freely available and easily accessible via the Alzheimer's Disease Data Initiative's (ADDI) AD Workbench platform and the University of Edinburgh's Sample Access Committee. The trial delivery network established within the EPAD program is being incorporated into the truly global offering from the Global Alzheimer's Platform (GAP) for trial delivery, and the almost 100 early-career researchers who were part of the EPAD Academy will take forward their experience and learning from EPAD to the next stage of their careers.

DISCUSSION

Through GAP, IMI-Neuronet, and follow-on funding from the Alzheimer's Association for the data and sample access systems, the EPAD assets will be maintained and, as and when sponsors seek a new platform trial to be established, the learnings from EPAD will ensure that this can be developed to be even more successful than this first pan-European attempt.

Evaluation of dose-dependent treatment effects after mid-trial dose escalation in biomarker, clinical, and cognitive outcomes for gantenerumab or solanezumab in dominantly inherited Alzheimer's disease

Introduction

While the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) was ongoing, external data suggested higher doses were needed to achieve targeted effects; therefore, doses of gantenerumab were increased 5-fold, and solanezumab was increased 4-fold. We evaluated to what extent mid-trial dose increases produced a dose-dependent treatment effect.

Methods

Using generalized linear mixed effects (LME) models, we estimated the annual low- and high-dose treatment effects in clinical, cognitive, and biomarker outcomes.

Results

Both gantenerumab and solanezumab demonstrated dose-dependent treatment effects (significant for gantenerumab, non-significant for solanezumab) in their respective target amyloid biomarkers (Pittsburgh compound B positron emission tomography standardized uptake value ratio and cerebrospinal fluid amyloid beta 42), with gantenerumab demonstrating additional treatment effects in some downstream biomarkers. No dose-dependent treatment effects were observed in clinical or cognitive outcomes.

Conclusions

Mid-trial dose escalation can be implemented as a remedy for an insufficient initial dose and can be more cost effective and less burdensome to participants than starting a new trial with higher doses, especially in rare diseases.

Highlights

We evaluated the dose-dependent treatment effect of two different amyloid-specific immunotherapies.Dose-dependent treatment effects were observed in some biomarkers.No dose-dependent treatment effects were observed in clinical/cognitive outcomes, potentially due to the fact that the modified study may not have been powered to detect such treatment effects in symptomatic subjects at a mild stage of disease exposed to high (or maximal) doses of medication for prolonged durations.

Comparison of plasma and CSF biomarkers in predicting cognitive decline

OBJECTIVES

Concentrations of amyloid-β peptides (Aβ42/Aβ40) and neurofilament light (NfL) can be measured in plasma or cerebrospinal fluid (CSF) and are associated with Alzheimer's disease brain pathology and cognitive impairment. This study directly compared plasma and CSF measures of Aβ42/Aβ40 and NfL as predictors of cognitive decline.

METHODS

Participants were 65 years or older and cognitively normal at baseline with at least one follow-up cognitive assessment. Analytes were measured with the following types of assays: plasma Aβ42/Aβ40, immunoprecipitation-mass spectrometry; plasma NfL, Simoa; CSF Aβ42/Aβ40, automated immunoassay; CSF NfL plate-based immunoassay. Mixed effects models evaluated the global cognitive composite score over a maximum of 6 years as predicted by the fluid biomarkers.

RESULTS

Analyses included 371 cognitively normal participants, aged 72.7 ± 5.2 years (mean ± standard deviation) with an average length of follow-up of 3.9 ± 1.6 years. Standardized concentrations of biomarkers were associated with annualized cognitive change: plasma Aβ42/Aβ40, 0.014 standard deviations (95% confidence intervals 0.002 to 0.026); CSF Aβ42/Aβ40, 0.020 (0.008 to 0.032); plasma Nfl, -0.018 (-0.030 to -0.005); and CSF NfL, -0.024 (-0.036 to -0.012). Power analyses estimated that 266 individuals in each treatment arm would be needed to detect a 50% slowing of decline if identified by abnormal plasma measures versus 229 for CSF measures.

INTERPRETATION

Both plasma and CSF measures of Aβ42/Aβ40 and NfL predicted cognitive decline. A clinical trial that enrolled individuals based on abnormal plasma Aβ42/Aβ40 and NfL levels would require only a marginally larger cohort than if CSF measures were used.

Amyloid-Related Imaging Abnormalities in the DIAN-TU-001 Trial of Gantenerumab and Solanezumab: Lessons from a Trial in Dominantly Inherited Alzheimer Disease

OBJECTIVE

To determine the characteristics of participants with amyloid-related imaging abnormalities (ARIA) in a trial of gantenerumab or solanezumab in dominantly inherited Alzheimer disease (DIAD).

METHODS

142 DIAD mutation carriers received either gantenerumab SC (n = 52), solanezumab IV (n = 50), or placebo (n = 40). Participants underwent assessments with the Clinical Dementia Rating® (CDR®), neuropsychological testing, CSF biomarkers, β-amyloid positron emission tomography (PET), and magnetic resonance imaging (MRI) to monitor ARIA. Cross-sectional and longitudinal analyses evaluated potential ARIA-related risk factors.

RESULTS

Eleven participants developed ARIA-E, including 3 with mild symptoms. No ARIA-E was reported under solanezumab while gantenerumab was associated with ARIA-E compared to placebo (odds ratio [OR] = 9.1, confidence interval [CI][1.2, 412.3]; p = 0.021). Under gantenerumab, APOE-ɛ4 carriers were more likely to develop ARIA-E (OR = 5.0, CI[1.0, 30.4]; p = 0.055), as were individuals with microhemorrhage at baseline (OR = 13.7, CI[1.2, 163.2]; p = 0.039). No ARIA-E was observed at the initial 225 mg/month gantenerumab dose, and most cases were observed at doses >675 mg. At first ARIA-E occurrence, all ARIA-E participants were amyloid-PET+, 60% were CDR >0, 60% were past their estimated year to symptom onset, and 60% had also incident ARIA-H. Most ARIA-E radiologically resolved after dose adjustment and developing ARIA-E did not significantly increase odds of trial discontinuation. ARIA-E was more frequently observed in the occipital lobe (90%). ARIA-E severity was associated with age at time of ARIA-E.

INTERPRETATION

In DIAD, solanezumab was not associated with ARIA. Gantenerumab dose over 225 mg increased ARIA-E risk, with additional risk for individuals APOE-ɛ4(+) or with microhemorrhage. ARIA-E was reversible on MRI in most cases, generally asymptomatic, without additional risk for trial discontinuation. ANN NEUROL 2022;92:729-744.

Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology

The extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of 'sporadic' late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease. We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer's Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset. Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants. These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.

Design and analysis of umbrella trials: Where do we stand?

Background

The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted in their consideration in non-oncology settings. Umbrella trials are one class of master protocol design that evaluates multiple targeted therapies in a single disease setting. Despite the existence of several reviews of master protocols, the statistical considerations of umbrella trials have received more limited attention.

Methods

We conduct a systematic review of the literature on umbrella trials, examining both the statistical methods that are available for their design and analysis, and also their use in practice. We pay particular attention to considerations for umbrella designs applied outside of oncology.

Findings

We identified 38 umbrella trials. To date, most umbrella trials have been conducted in early phase settings (73.7%, 28/38) and in oncology (92.1%, 35/38). The quality of statistical information available about conducted umbrella trials to date is poor; for example, it was impossible to ascertain how sample size was determined in the majority of trials (55.3%, 21/38). The literature on statistical methods for umbrella trials is currently sparse.

Conclusions

Umbrella trials have potentially great utility to expedite drug development, including outside of oncology. However, to enable lessons to be effectively learned from early use of such designs, there is a need for higher-quality reporting of umbrella trials. Furthermore, if the potential of umbrella trials is to be realized, further methodological research is required.

The Bayesian Time Machine: Accounting for temporal drift in multi-arm platform trials

BACKGROUND

Multi-arm platform trials investigate multiple agents simultaneously, typically with staggered entry and exit of experimental treatment arms versus a shared control arm. In such settings, there is considerable debate whether to limit analyses for a treatment arm to concurrent randomized control subjects or to allow comparisons to both concurrent and non-concurrent (pooled) control subjects. The potential bias from temporal drift over time is at the core of this debate.

METHODS

We propose time-adjusted analyses, including a "Bayesian Time Machine," to model potential temporal drift in the entire study population, such that primary analyses can incorporate all randomized control subjects from the platform trial. We conduct a simulation study to assess performance relative to utilizing concurrent or pooled controls.

RESULTS

In multi-arm platform trials with staggered entry, analyses adjusting for temporal drift (either Bayesian or frequentist) have superior estimation of treatment effects and favorable testing properties compared to analyses using either concurrent or pooled controls. The Bayesian Time Machine generally provides estimates with greater precision and smaller mean square error than alternative approaches, at the risk of small bias and small Type I error inflation.

CONCLUSIONS

The Bayesian Time Machine provides a compromise between bias and precision by smoothing estimates across time and leveraging all available data for the estimation of treatment effects. Prior distributions controlling the behavior of dynamic smoothing across time must be pre-specified and carefully calibrated to the unique context of each trial, appropriately accounting for the population, disease, and endpoints.

Engineering antibody and protein therapeutics to cross the blood-brain barrier

Diseases in the central nervous system (CNS) are often difficult to treat. Antibody- and protein-based therapeutics hold huge promises in CNS disease treatment. However, proteins are restricted from entering the CNS by the blood-brain barrier (BBB). To achieve enhanced BBB crossing, antibody-based carriers have been developed by utilizing the endogenous macromolecule transportation pathway, known as receptor-mediated transcytosis. In this report, we first provided an overall review on key CNS diseases and the most promising antibody- or protein-based therapeutics approved or in clinical trials. We then reviewed the platforms that are being explored to increase the macromolecule brain entry to combat CNS diseases. Finally, we have analyzed the lessons learned from past experiences and have provided a perspective on the future engineering of novel delivery vehicles for antibody- and protein-based therapies for CNS diseases.

Temporal order of clinical and biomarker changes in familial frontotemporal dementia

Unlike familial Alzheimer's disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.

Calabria as a Genetic Isolate: A Model for the Study of Neurodegenerative Diseases

Although originally multi-ethnic in its structure, nowadays the Calabria region of southern Italy represents an area with low genetic heterogeneity and a high level of consanguinity that allows rare mutations to be maintained due to the founder effect. A complex research methodology—ranging from clinical activity to the genealogical reconstruction of families/populations across the centuries, the creation of databases, and molecular/genetic research—was modelled on the characteristics of the Calabrian population for more than three decades. This methodology allowed the identification of several novel genetic mutations or variants associated with neurodegenerative diseases. In addition, a higher prevalence of several hereditary neurodegenerative diseases has been reported in this population, such as Alzheimer’s disease, frontotemporal dementia, Parkinson’s disease, Niemann–Pick type C disease, spinocerebellar ataxia, Creutzfeldt–Jakob disease, and Gerstmann–Straussler–Scheinker disease. Here, we summarize and discuss the results of research data supporting the view that Calabria could be considered as a genetic isolate and could represent a model, a sort of outdoor laboratory—similar to very few places in the world—useful for the advancement of knowledge on neurodegenerative diseases.

Optimizing a Bayesian hierarchical adaptive platform trial design for stroke patients

BACKGROUND

Platform trials are well-known for their ability to investigate multiple arms on heterogeneous patient populations and their flexibility to add/drop treatment arms due to efficacy/lack of efficacy. Because of their complexity, it is important to develop highly optimized, transparent, and rigorous designs that are cost-efficient, offer high statistical power, maximize patient benefit, and are robust to changes over time.

METHODS

To address these needs, we present a Bayesian platform trial design based on a beta-binomial model for binary outcomes that uses three key strategies: (1) hierarchical modeling of subgroups within treatment arms that allows for borrowing of information across subgroups, (2) utilization of response-adaptive randomization (RAR) schemes that seek a tradeoff between statistical power and patient benefit, and (3) adjustment for potential drift over time. Motivated by a proposed clinical trial that aims to find the appropriate treatment for different subgroup populations of ischemic stroke patients, extensive simulation studies were performed to validate the approach, compare different allocation rules, and study the model operating characteristics.

RESULTS AND CONCLUSIONS

Our proposed approach achieved high statistical power and good patient benefit and was also robust against population drift over time. Our design provided a good balance between the strengths of both the traditional RAR scheme and fixed 1:1 allocation and may be a promising choice for dichotomous outcomes trials investigating multiple subgroups.

Novel clinical trial design and analytic methods to tackle challenges in therapeutic development in rare diseases

While only a fraction of the worldwide population may have a particular rare disorder, millions of people worldwide are affected across the over 6,000 rare disorders and do not have a safe and effective approved therapy to help them live or manage complications from the disorder. Challenges to clinical development of new therapies in rare disorders include difficulty in powering and recruiting into a study in small and often heterogenous population, scarcity of natural history data informing critical design elements such as endpoint selection and study duration, and ethical and recruitment challenges in randomizing patients to a placebo arm. In this review, we describe some existing and novel strategies to tackle these challenges, by efficient utilization of available resources. We discuss the role of natural history studies and endpoint selection as they remain critical features that apply across designs and disorders. We also review some novel clinical trial designs including incorporating external control and/or longitudinal measures, master protocol designs, and adaptive designs. Additionally, we review some analytic strategies that are often associated with these designs, such as the use of causal inference methods, and Bayesian methods. We hope this review will raise awareness of these novel approaches and encourage their use in studies of rare diseases.

Challenges and progress in research, diagnostics, and therapeutics in Alzheimer's disease and related dementias

The health, well-being, and financial security of Americans are greatly impacted by Alzheimer's disease. The forecast paints an upward trajectory with the number of Americans suffering from Alzheimer's disease and related dementia. To discuss the Alzheimer's crisis, The Senate Committee on Finance, Subcommittee on Health Care, held a hearing titled, "The Alzheimer's Crisis: Examining, Testing, and Treatment Pipelines and Fiscal Implications," on December 16, 2020. Here, we summarize and expand on the discussion of the panel and its review of recent progress, ongoing challenges associated with Alzheimer's disease, and potential initiatives that promise to speed progress in developing treatments and improving care.

Avoid or Embrace? Practice Effects in Alzheimer's Disease Prevention Trials

Demonstrating a slowing in the rate of cognitive decline is a common outcome measure in clinical trials in Alzheimer's disease (AD). Selection of cognitive endpoints typically includes modeling candidate outcome measures in the many, richly phenotyped observational cohort studies available. An important part of choosing cognitive endpoints is a consideration of improvements in performance due to repeated cognitive testing (termed "practice effects"). As primary and secondary AD prevention trials are comprised predominantly of cognitively unimpaired participants, practice effects may be substantial and may have considerable impact on detecting cognitive change. The extent to which practice effects in AD prevention trials are similar to those from observational studies and how these potential differences impact trials is unknown. In the current study, we analyzed data from the recently completed DIAN-TU-001 clinical trial (TU) and the associated DIAN-Observational (OBS) study. Results indicated that asymptomatic mutation carriers in the TU exhibited persistent practice effects on several key outcomes spanning the entire trial duration. Critically, these practice related improvements were larger on certain tests in the TU relative to matched participants from the OBS study. Our results suggest that the magnitude of practice effects may not be captured by modeling potential endpoints in observational studies where assessments are typically less frequent and drug expectancy effects are absent. Using alternate instrument forms (represented in our study by computerized tasks) may partly mitigate practice effects in clinical trials but incorporating practice effects as outcomes may also be viable. Thus, investigators must carefully consider practice effects (either by minimizing them or modeling them directly) when designing cognitive endpoint AD prevention trials by utilizing trial data with similar assessment frequencies.

CSF Tau phosphorylation at Thr205 is associated with loss of white matter integrity in autosomal dominant Alzheimer disease

BACKGROUND

Hyperphosphorylation of tau leads to conformational changes that destabilize microtubules and hinder axonal transport in Alzheimer's disease (AD). However, it remains unknown whether white matter (WM) decline due to AD is associated with specific Tau phosphorylation site(s).

METHODS

In autosomal dominant AD (ADAD) mutation carriers (MC) and non-carriers (NC) we compared cerebrospinal fluid (CSF) phosphorylation at tau sites (pT217, pT181, pS202, and pT205) and total tau with WM measures, as derived from diffusion tensor imaging (DTI), and cognition. A WM composite metric, derived from a principal component analysis, was used to identify spatial decline seen in ADAD.

RESULTS

The WM composite explained over 70% of the variance in MC. WM regions that strongly contributed to the spatial topography were located in callosal and cingulate regions. Loss of integrity within the WM composite was strongly associated with AD progression in MC as defined by the estimated years to onset (EYO) and cognitive decline. A linear regression demonstrated that amyloid, gray matter atrophy and phosphorylation at CSF tau site pT205 each uniquely explained a reduction in the WM composite within MC that was independent of vascular changes (white matter hyperintensities), and age. Hyperphosphorylation of CSF tau at other sites and total tau did not significantly predict WM composite loss.

CONCLUSIONS

We identified a site-specific relationship between CSF phosphorylated tau and WM decline within MC. The presence of both amyloid deposition and Tau phosphorylation at pT205 were associated with WM composite loss. These findings highlight a primary AD-specific mechanism for WM dysfunction that is tightly coupled to symptom manifestation and cognitive decline.

Bayesian model of disease progression in mucopolysaccaridosis IIIA

Mucopolysaccaridosis IIIA (MPS IIIA) is a rare genetic disease that afflicts children and leads to neurocognitive degeneration. We develop a Bayesian disease progression model (DPM) of MPS IIIA that characterizes the pattern of cognitive growth and decline in this disease. The DPM is a repeated measures model that incorporates a nonlinear developmental trajectory and shape-invariant random effects. This approach quantifies the pattern of cognitive development in MPS IIIA and addresses differences in biological age, length of follow-up, and clinical outcomes across natural history subjects. The DPM can be used in clinical trials to estimate the percent slowing in disease progression for treatment relative to natural history. Simulations demonstrate that the DPM provides substantial improvements in power relative to alternative analyses.

Application of Bayesian methods to accelerate rare disease drug development: scopes and hurdles

Background

Design and analysis of clinical trials for rare and ultra-rare disease pose unique challenges to the practitioners. Meeting conventional power requirements is infeasible for diseases where sample sizes are inherently very small. Moreover, rare disease populations are generally heterogeneous and widely dispersed, which complicates study enrollment and design. Leveraging all available information in rare and ultra-rare disease trials can improve both drug development and informed decision-making processes.

Main text

Bayesian statistics provides a formal framework for combining all relevant information at all stages of the clinical trial, including trial design, execution, and analysis. This manuscript provides an overview of different Bayesian methods applicable to clinical trials in rare disease. We present real or hypothetical case studies that address the key needs of rare disease drug development highlighting several specific Bayesian examples of clinical trials. Advantages and hurdles of these approaches are discussed in detail. In addition, we emphasize the practical and regulatory aspects in the context of real-life applications.

Conclusion

The use of innovative trial designs such as master protocols and complex adaptive designs in conjunction with a Bayesian approach may help to reduce sample size, select the correct treatment and population, and accurately and reliably assess the treatment effect in the rare disease setting.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02342-5.

Combination Therapy in Alzheimer’s Disease: Is It Time?

Alzheimer’s disease (AD) is the most common cause of dementia globally. There is increasing evidence showing AD has no single pathogenic mechanism, and thus treatment approaches focusing only on one mechanism are unlikely to be meaningfully effective. With only one potentially disease modifying treatment approved, targeting amyloid-β (Aβ), AD is underserved regarding effective drug treatments. Combining multiple drugs or designing treatments that target multiple pathways could be an effective therapeutic approach. Considering the distinction between added and combination therapies, one can conclude that most trials fall under the category of added therapies. For combination therapy to have an actual impact on the course of AD, it is likely necessary to target multiple mechanisms including but not limited to Aβ and tau pathology. Several challenges have to be addressed regarding combination therapy, including choosing the correct agents, the best time and stage of AD to intervene, designing and providing proper protocols for clinical trials. This can be achieved by a cooperation between the pharmaceutical industry, academia, private research centers, philanthropic institutions, and the regulatory bodies. Based on all the available information, the success of combination therapy to tackle complicated disorders such as cancer, and the blueprint already laid out on how to implement combination therapy and overcome its challenges, an argument can be made that the field has to move cautiously but quickly toward designing new clinical trials, further exploring the pathological mechanisms of AD, and re-examining the previous studies with combination therapies so that effective treatments for AD may be finally found.

Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease

Introduction

Clinical trials for sporadic Alzheimer's disease generally use mixed models for repeated measures (MMRM) or, to a lesser degree, constrained longitudinal data analysis models (cLDA) as the analysis model with time since baseline as a categorical variable. Inferences using MMRM/cLDA focus on the between-group contrast at the pre-determined, end-of-study assessments, thus are less efficient (eg, less power).

Methods

The proportional cLDA (PcLDA) and proportional MMRM (pMMRM) with time as a categorical variable are proposed to use all the post-baseline data without the linearity assumption on disease progression.

Results

Compared with the traditional cLDA/MMRM models, PcLDA or pMMRM lead to greater gain in power (up to 20% to 30%) while maintaining type I error control.

Discussion

The PcLDA framework offers a variety of possibilities to model longitudinal data such as proportional MMRM (pMMRM) and two-part pMMRM which can model heterogeneous cohorts more efficiently and model co-primary endpoints simultaneously.

Early-stage Alzheimer disease: getting trial-ready

Slowing the progression of Alzheimer disease (AD) might be the greatest unmet medical need of our time. Although one AD therapeutic has received a controversial accelerated approval from the FDA, more effective and accessible therapies are urgently needed. Consensus is growing that for meaningful disease modification in AD, therapeutic intervention must be initiated at very early (preclinical or prodromal) stages of the disease. Although the methods for such early-stage clinical trials have been developed, identification and recruitment of the required asymptomatic or minimally symptomatic study participants takes many years and requires substantial funds. As an example, in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease Trial (the first phase III trial to be performed in preclinical AD), 3.5 years and more than 5,900 screens were required to recruit and randomize 1,169 participants. A new clinical trials infrastructure is required to increase the efficiency of recruitment and accelerate therapeutic progress. Collaborations in North America, Europe and Asia are now addressing this need by establishing trial-ready cohorts of individuals with preclinical and prodromal AD. These collaborations are employing innovative methods to engage the target population, assess risk of brain amyloid accumulation, select participants for biomarker studies and determine eligibility for trials. In the future, these programmes could provide effective tools for pursuing the primary prevention of AD. Here, we review the lessons learned from the AD trial-ready cohorts that have been established to date, with the aim of informing ongoing and future efforts towards efficient, cost-effective trial recruitment.

Consensus is growing that intervention in the very early stages of Alzheimer disease is necessary for disease modification. Here, the authors discuss the challenges of recruiting asymptomatic or mildly symptomatic participants for clinical trials, focusing on ‘trial-ready’ cohorts as a potential solution.

Trial-ready cohorts are an effective strategy for the identification of participants eligible for clinical trials in early-stage Alzheimer disease (AD).

Building these cohorts requires considerable planning and technological infrastructure to facilitate recruitment, remote longitudinal assessment, data management and data storage.

Trial-ready cohorts exist for genetically determined populations at risk of AD, such as those with familial AD and Down syndrome; the longitudinal data from these cohorts is improving our understanding of the disease progression in early stages, informing clinical trial design and accelerating recruitment to intervention studies.

So far, the challenges experienced by trial-ready cohorts for early-stage AD have included difficulties recruiting an ethnically and racially representative cohort; and for online cohorts, difficulty retaining participants.

The results of ongoing work will reveal the success of strategies to improve cohort diversity and retention, and the rates of referral to clinical trials.

Soluble TREM2 in CSF and its association with other biomarkers and cognition in autosomal-dominant Alzheimer's disease: a longitudinal observational study

BACKGROUND

Therapeutic modulation of TREM2-dependent microglial function might provide an additional strategy to slow the progression of Alzheimer's disease. Although studies in animal models suggest that TREM2 is protective against Alzheimer's pathology, its effect on tau pathology and its potential beneficial role in people with Alzheimer's disease is still unclear. Our aim was to study associations between the dynamics of soluble TREM2, as a biomarker of TREM2 signalling, and amyloid β (Aβ) deposition, tau-related pathology, neuroimaging markers, and cognitive decline, during the progression of autosomal dominant Alzheimer's disease.

METHODS

We did a longitudinal analysis of data from the Dominantly Inherited Alzheimer Network (DIAN) observational study, which includes families with a history of autosomal dominant Alzheimer's disease. Participants aged over 18 years who were enrolled in DIAN between Jan 1, 2009, and July 31, 2019, were categorised as either carriers of pathogenic variants in PSEN1, PSEN2, and APP genes (n=155) or non-carriers (n=93). We measured amounts of cleaved soluble TREM2 using a novel immunoassay in CSF samples obtained every 2 years from participants who were asymptomatic (Clinical Dementia Rating [CDR]=0) and annually for those who were symptomatic (CDR>0). CSF concentrations of Aβ40, Aβ42, total tau (t-tau), and tau phosphorylated on threonine 181 (p-tau) were measured by validated immunoassays. Predefined neuroimaging measurements were total cortical uptake of Pittsburgh compound B PET (PiB-PET), cortical thickness in the precuneus ascertained by MRI, and hippocampal volume determined by MRI. Cognition was measured using a validated cognitive composite (including DIAN word list test, logical memory delayed recall, digit symbol coding test [total score], and minimental status examination). We based our statistical analysis on univariate and bivariate linear mixed effects models.

FINDINGS

In carriers of pathogenic variants, a high amyloid burden at baseline, represented by low CSF Aβ42 (β=-4·28 × 10-2 [SE 0·013], p=0·0012), but not high cortical uptake in PiB-PET (β=-5·51 × 10-3 [0·011], p=0·63), was the only predictor of an augmented annual rate of subsequent increase in soluble TREM2. Augmented annual rates of increase in soluble TREM2 were associated with a diminished rate of decrease in amyloid deposition, as measured by Aβ42 in CSF (r=0·56 [0·22], p=0·011), in presymptomatic carriers of pathogenic variants, and with diminished annual rate of increase in PiB-PET (r=-0·67 [0·25], p=0·0060) in symptomatic carriers of pathogenic variants. Presymptomatic carriers of pathogenic variants with annual rates of increase in soluble TREM2 lower than the median showed a correlation between enhanced annual rates of increase in p-tau in CSF and augmented annual rates of increase in PiB-PET signal (r=0·45 [0·21], p=0·035), that was not observed in those with rates of increase in soluble TREM2 higher than the median. Furthermore, presymptomatic carriers of pathogenic variants with rates of increase in soluble TREM2 above or below the median had opposite associations between Aβ42 in CSF and PiB-PET uptake when assessed longitudinally. Augmented annual rates of increase in soluble TREM2 in presymptomatic carriers of pathogenic variants correlated with decreased cortical shrinkage in the precuneus (r=0·46 [0·22]), p=0·040) and diminished cognitive decline (r=0·67 [0·22], p=0·0020).

INTERPRETATION

Our findings in autosomal dominant Alzheimer's disease position the TREM2 response within the amyloid cascade immediately after the first pathological changes in Aβ aggregation and further support the role of TREM2 on Aβ plaque deposition and compaction. Furthermore, these findings underpin a beneficial effect of TREM2 on Aβ deposition, Aβ-dependent tau pathology, cortical shrinkage, and cognitive decline. Soluble TREM2 could, therefore, be a key marker for clinical trial design and interpretation. Efforts to develop TREM2-boosting therapies are ongoing.

FUNDING

German Research Foundation, US National Institutes of Health.

Preventing amyotrophic lateral sclerosis: insights from pre-symptomatic neurodegenerative diseases

Significant progress has been made in understanding the pre-symptomatic phase of amyotrophic lateral sclerosis. While much is still unknown, advances in other neurodegenerative diseases offer valuable insights. Indeed, it is increasingly clear that the well-recognized clinical syndromes of Alzheimer's disease, Parkinson's disease, Huntington's disease, spinal muscular atrophy and frontotemporal dementia are also each preceded by a pre-symptomatic or prodromal period of varying duration, during which the underlying disease process unfolds, with associated compensatory changes and loss of inherent system redundancy. Key insights from these diseases highlight opportunities for discovery in amyotrophic lateral sclerosis. The development of biomarkers reflecting amyloid and tau has led to a shift in defining Alzheimer's disease based on inferred underlying histopathology. Parkinson's disease is unique among neurodegenerative diseases in the number and diversity of non-genetic biomarkers of pre-symptomatic disease, most notably REM sleep behaviour disorder. Huntington's disease benefits from an ability to predict the likely timing of clinically manifest disease based on age and CAG-repeat length alongside reliable neuroimaging markers of atrophy. Spinal muscular atrophy clinical trials have highlighted the transformational value of early therapeutic intervention, and studies in frontotemporal dementia illustrate the differential role of biomarkers based on genotype. Similar advances in amyotrophic lateral sclerosis would transform our understanding of key events in pathogenesis, thereby dramatically accelerating progress towards disease prevention. Deciphering the biology of pre-symptomatic amyotrophic lateral sclerosis relies on a clear conceptual framework for defining the earliest stages of disease. Clinically manifest amyotrophic lateral sclerosis may emerge abruptly, especially among those who harbour genetic mutations associated with rapidly progressive amyotrophic lateral sclerosis. However, the disease may also evolve more gradually, revealing a prodromal period of mild motor impairment preceding phenoconversion to clinically manifest disease. Similarly, cognitive and behavioural impairment, when present, may emerge gradually, evolving through a prodromal period of mild cognitive impairment or mild behavioural impairment before progression to amyotrophic lateral sclerosis. Biomarkers are critically important to studying pre-symptomatic amyotrophic lateral sclerosis and essential to efforts to intervene therapeutically before clinically manifest disease emerges. The use of non-genetic biomarkers, however, presents challenges related to counselling, informed consent, communication of results and limited protections afforded by existing legislation. Experiences from pre-symptomatic genetic testing and counselling, and the legal protections against discrimination based on genetic data, may serve as a guide. Building on what we have learned-more broadly from other pre-symptomatic neurodegenerative diseases and specifically from amyotrophic lateral sclerosis gene mutation carriers-we present a road map to early intervention, and perhaps even disease prevention, for all forms of amyotrophic lateral sclerosis.

Association of CSF Aβ38 Levels With Risk of Alzheimer Disease-Related Decline

BACKGROUND AND OBJECTIVE

Experimental studies suggest that the balance between short and long β-amyloid (Aβ) species might modulate the toxic effects of Aβ in Alzheimer disease (AD), but clinical evidence is lacking. We studied whether Aβ38 levels in CSF relate to risk of AD dementia and cognitive decline.

METHODS

CSF Aβ38 levels were measured in 656 individuals across 2 clinical cohorts: the Swedish BioFINDER study and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cox regression models were used to evaluate the association between baseline Aβ38 levels and risk of AD dementia in AD biomarker-positive individuals (AD+; determined by CSF phosphorylated tau [P-tau]/Aβ42 ratio) with subjective cognitive decline (SCD) or mild cognitive impairment (MCI). Linear mixed-effects models were used to evaluate the association between baseline Aβ38 levels and cognitive decline as measured by the Mini-Mental State Examination (MMSE) in AD+ participants with SCD, MCI, or AD dementia.

RESULTS

In the BioFINDER cohort, high Aβ38 levels were associated with slower decline in MMSE score (β = 0.30 points per SD, p = 0.001) and with lower risk of conversion to AD dementia (hazard ratio 0.83 per SD, p = 0.03). In the ADNI cohort, higher Aβ38 levels were associated with less decline in MMSE score (β = 0.27, p = 0.01) but not risk of conversion to AD dementia (p = 0.66). Aβ38 levels in both cohorts were significantly associated with both cognitive and clinical outcomes when further adjusted for CSF P-tau or CSF Aβ42 levels.

DISCUSSION

Higher CSF Aβ38 levels are associated with lower risk of AD-related changes in 2 independent clinical cohorts. These findings suggest that γ-secretase modulators could be effective as disease-altering therapy.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT03174938.

Pharmacotherapeutic combinations for the treatment of Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is the most common form of dementia, and four medications are currently available as symptomatic therapies: three cholinesterase inhibitors (ChEI) and memantine. In June 2021, aducanumab was approved in the United States under an accelerated approval pathway as the first novel putative disease-modifying therapy (p-DMT) targeting the β-amyloid (Aβ) cascade in the brain. The combination of several monotherapies to address the multifactorial pathogenesis of neurodegenerative diseases is an anticipated next step.

AREAS COVERED

The cholinergic hypothesis and the amyloid cascade hypothesis have been proposed as explanations for the pathogenesis of AD. Given the limited effectiveness of monotherapies based on these hypotheses, approaches using combination therapy are attempting to address the complexity of AD pathogenesis, including putative causative proteins-related neurodegeneration, neurotransmitters, and neuroinflammation, in a comprehensive manner.

EXPERT OPINION

The efficacy of an initial or add-on combination approach to counteracting neurodegenerative processes and functional deterioration has been investigated. The combination of symptomatic therapies with approved anti-dementia medicines (one ChEI and memantine) has been found to be functionally effective for a moderately severe disease stage. Furthermore, combination strategies involving p-DMTs, symptomatic therapies, and neuro-regeneration may be useful in the future.

Predicting Symptom Onset in Sporadic Alzheimer's Disease: "How Long Do I Have?"

Predicting not just if but when cognitively normal individuals will develop the onset of Alzheimer's disease (AD) dementia seems increasingly feasible, as evidenced by converging findings from several approaches and cohorts. These estimates may improve the efficiency of clinical trials by better identifying cognitively normal individuals at high risk of developing AD symptoms. As models are refined, the implications of disclosing estimates of the age of AD symptom onset must be examined, since telling a cognitively normal individual the age they are expected to develop AD symptoms may have different implications than disclosing increased risk for AD dementia.

The amyloid hypothesis in Alzheimer disease: new insights from new therapeutics

Many drugs that target amyloid-β (Aβ) in Alzheimer disease (AD) have failed to demonstrate clinical efficacy. However, four anti-Aβ antibodies have been shown to mediate the removal of amyloid plaque from brains of patients with AD, and the FDA has recently granted accelerated approval to one of these, aducanumab, using reduction of amyloid plaque as a surrogate end point. The rationale for approval and the extent of the clinical benefit from these antibodies are under intense debate. With the aim of informing this debate, we review clinical trial data for drugs that target Aβ from the perspective of the temporal interplay between the two pathognomonic protein aggregates in AD - Aβ plaques and tau neurofibrillary tangles - and their relationship to cognitive impairment, highlighting differences in drug properties that could affect their clinical performance. On this basis, we propose that Aβ pathology drives tau pathology, that amyloid plaque would need to be reduced to a low level (~20 centiloids) to reveal significant clinical benefit and that there will be a lag between the removal of amyloid and the potential to observe a clinical benefit. We conclude that the speed of amyloid removal from the brain by a potential therapy will be important in demonstrating clinical benefit in the context of a clinical trial.

Disease-Modifying Therapies for Alzheimer's Disease: More Questions than Answers

Scientific advances over the last four decades have steadily infused the Alzheimer's disease (AD) field with great optimism that therapies targeting Aβ, amyloid, tau, and innate immune activation states in the brain would provide disease modification. Unfortunately, this optimistic scenario has not yet played out. Though a recent approval of the anti-Aβ aggregate binding antibody, Aduhelm (aducanumab), as a "disease-modifying therapy for AD" is viewed by some as a breakthrough, many remain unconvinced by the data underlying this approval. Collectively, we have not succeeded in changing AD from a largely untreatable, inevitable, and incurable disease to a treatable, preventable, and curable one. Here, I will review the major foci of the AD "disease-modifying" therapeutic pipeline and some of the "open questions" that remain in terms of these therapeutic approaches. I will conclude the review by discussing how we, as a field, might adjust our approach, learning from our past failures to ensure future success.

Systems Biology to Address Unmet Medical Needs in Neurological Disorders

Neurological diseases are highly prevalent and constitute a significant cause of mortality and disability. Neurological disorders encompass a heterogeneous group of neurodegenerative conditions, broadly characterized by injury to the peripheral and/or central nervous system. Although the etiology of neurological diseases varies greatly, they share several characteristics, such as heterogeneity of clinical presentation, non-cell autonomous nature, and diversity of cellular, subcellular, and molecular pathways. Systems biology has emerged as a valuable platform for addressing the challenges of studying heterogeneous neurological diseases. Systems biology has manifold applications to address unmet medical needs for neurological illness, including integrating and correlating different large datasets covering the transcriptome, epigenome, proteome, and metabolome associated with a specific condition. This is particularly useful for disentangling the heterogeneity and complexity of neurological conditions. Hence, systems biology can help in uncovering pathophysiology to develop novel therapeutic targets and assessing the impact of known treatments on disease progression. Additionally, systems biology can identify early diagnostic biomarkers, to help diagnose neurological disease preceded by a long subclinical phase, as well as define the exposome, the collection of environmental toxicants that increase risk of certain neurological diseases. In addition to these current applications, there are numerous potential emergent uses, such as precision medicine.

Adaptive Platform Trials to Transform ALS Therapy Development

Current therapeutic development in ALS relies on individual randomized clinical trials to test a specific investigational product in a single patient population. This approach has intrinsic limitations including cost, time, and lack of flexibility. Adaptive platform trials represent a novel approach to investigate several interventions for a single disease in a continuous manner. Already in use in oncology, this approach is now being employed more often in neurology. Here, we describe a newly launched, platform trial for amyotrophic lateral sclerosis (ALS). The HEALEY ALS Platform Trial is testing multiple investigational products concurrently in people with ALS, with the goal of rapidly identifying novel treatments, biomarkers, and trial endpoints. This article is protected by copyright. All rights reserved.

Current landscape of clinical development and approval of advanced therapies

Advanced therapy medicinal products (ATMPs) are innovative therapies that mainly target orphan diseases and high unmet medical needs. The uncertainty about the product's benefit-risk balance at the time of approval, the limitations of nonclinical development, and the complex quality aspects of those highly individualized advanced therapies are playing a key role in the clinical development, approval, and post-marketing setting for these therapies. This article reviews the current landscape of clinical development of advanced therapies, its challenges, and some of the efforts several stakeholders are conducting to move forward within this field. Progressive iteration of the science, methodologically sound clinical developments, establishing new standards for ATMPs development with the aim to ensure consistency in clinical development, and the reproducibility of knowledge is required, not only to increase the evidence generation for approval but to set principles to achieve translational success in this field.

Revisiting the grammar of Tau aggregation and pathology formation: how new insights from brain pathology are shaping how we study and target Tauopathies

Converging evidence continues to point towards Tau aggregation and pathology formation as central events in the pathogenesis of Alzheimer's disease and other Tauopathies. Despite significant advances in understanding the morphological and structural properties of Tau fibrils, many fundamental questions remain about what causes Tau to aggregate in the first place. The exact roles of cofactors, Tau post-translational modifications, and Tau interactome in regulating Tau aggregation, pathology formation, and toxicity remain unknown. Recent studies have put the spotlight on the wide gap between the complexity of Tau structures, aggregation, and pathology formation in the brain and the simplicity of experimental approaches used for modeling these processes in research laboratories. Embracing and deconstructing this complexity is an essential first step to understanding the role of Tau in health and disease. To help deconstruct this complexity and understand its implication for the development of effective Tau targeting diagnostics and therapies, we firstly review how our understanding of Tau aggregation and pathology formation has evolved over the past few decades. Secondly, we present an analysis of new findings and insights from recent studies illustrating the biochemical, structural, and functional heterogeneity of Tau aggregates. Thirdly, we discuss the importance of adopting new experimental approaches that embrace the complexity of Tau aggregation and pathology as an important first step towards developing mechanism- and structure-based therapies that account for the pathological and clinical heterogeneity of Alzheimer's disease and Tauopathies. We believe that this is essential to develop effective diagnostics and therapies to treat these devastating diseases.

Predicting Symptom Onset in Sporadic Alzheimer Disease With Amyloid PET

BACKGROUND AND OBJECTIVES

To predict when cognitively normal individuals with brain amyloidosis will develop symptoms of Alzheimer disease (AD).

METHODS

Brain amyloid burden was measured by amyloid PET with Pittsburgh compound B. The mean cortical standardized uptake value ratio (SUVR) was transformed into a timescale with the use of longitudinal data.

RESULTS

Amyloid accumulation was evaluated in 236 individuals who underwent >1 amyloid PET scan. The average age was 66.5 ± 9.2 years, and 12 individuals (5%) had cognitive impairment at their baseline amyloid PET scan. A tipping point in amyloid accumulation was identified at a low level of amyloid burden (SUVR 1.2), after which nearly all individuals accumulated amyloid at a relatively consistent rate until reaching a high level of amyloid burden (SUVR 3.0). The average time between levels of amyloid burden was used to estimate the age at which an individual reached SUVR 1.2. Longitudinal clinical diagnoses for 180 individuals were aligned by the estimated age at SUVR 1.2. In the 22 individuals who progressed from cognitively normal to a typical AD dementia syndrome, the estimated age at which an individual reached SUVR 1.2 predicted the age at symptom onset (R ² = 0.54, p < 0.0001, root mean square error [RMSE] 4.5 years); the model was more accurate after exclusion of 3 likely misdiagnoses (R ² = 0.84, p < 0.0001, RMSE 2.8 years).

CONCLUSION

The age at symptom onset in sporadic AD is strongly correlated with the age at which an individual reaches a tipping point in amyloid accumulation.

Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia

We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 415) we assessed predictive performance of ATN classification using empirical knowledge-based cut-offs for each component of ATN and compared it to two data-driven approaches, logistic regression and RUSBoost machine learning classifiers, which used continuous clinical or biomarker scores. In data-driven approaches, we identified ATN features that distinguish normals from individuals with dementia and used them to classify persons with MCI into dementia-like and normal groups. Both data-driven classification methods performed better than the empirical cut-offs for ATN biomarkers in predicting conversion to dementia. Classifiers that used clinical features performed as well as classifiers that used ATN biomarkers for prediction of progression to dementia. We discuss that data-driven modeling approaches can improve our ability to predict disease progression and might have implications in future clinical trials.

Platform Trials to Expedite Drug Development in Alzheimer's Disease: A Report from the EU/US CTAD Task Force

A diverse range of platforms has been established to increase the efficiency and speed of clinical trials for Alzheimer's disease (AD). These platforms enable parallel assessment of multiple therapeutics, treatment regimens, or participant groups; use uniform protocols and outcome measures; and may allow treatment arms to be added or dropped based on interim analyses of outcomes. The EU/US CTAD Task Force discussed the lessons learned from the Dominantly Inherited Alzheimer's Network Trials Unit (DIAN-TU) platform trial and the challenges addressed by other platform trials that have launched or are in the planning stages. The landscape of clinical trial platforms in the AD space includes those testing experimental therapies such as DIAN-TU, platforms designed to test multidomain interventions, and those designed to streamline trial recruitment by building trial-ready cohorts. The heterogeneity of the AD patient population, AD drugs, treatment regimens, and analytical methods complicates the design and execution of platform trials, yet Task Force members concluded that platform trials are essential to advance the search for effective AD treatments, including combination therapies.

Clinical care and therapeutic trials in PLS

Primary lateral sclerosis (PLS) is an extremely rare central nervous system degenerative disorder characterized by slowly progressive upper motor neuron loss leading to severe limb and bulbar dysfunction and disability. Although not necessarily life-shortening, PLS disease burden is substantial and improved symptomatic treatments are a major unmet need, especially for the often refractory spasticity that is a core feature of the syndrome. In Section 1, we describe clinical care needs and emphasize a highly personalized approach that can be best attained through multidisciplinary management. In Section 2, we describe progress in clinical trials in PLS that includes advances in symptomatic treatment, disease-modifying therapy, and emerging innovative trials.

Deconstructing Alzheimer's Disease: How to Bridge the Gap between Experimental Models and the Human Pathology?

Discovered more than a century ago, Alzheimer's disease (AD) is not only still present in our societies but has also become the most common dementia, with 50 million people worldwide affected by the disease. This number is expected to double in the next generation, and no cure is currently available to slow down or stop the disease progression. Recently, some advances were made due to the approval of the aducanumab treatment by the American Food and Drug Administration. The etiology of this human-specific disease remains poorly understood, and the mechanisms of its development have not been completely clarified. Several hypotheses concerning the molecular mechanisms of AD have been proposed, but the existing studies focus primarily on the two main markers of the disease: the amyloid β peptides, whose aggregation in the brain generates amyloid plaques, and the abnormally phosphorylated tau proteins, which are responsible for neurofibrillary tangles. These protein aggregates induce neuroinflammation and neurodegeneration, which, in turn, lead to cognitive and behavioral deficits. The challenge is, therefore, to create models that best reproduce this pathology. This review aims at gathering the different existing AD models developed in vitro, in cellulo, and in vivo. Many models have already been set up, but it is necessary to identify the most relevant ones for our investigations. The purpose of the review is to help researchers to identify the most pertinent disease models, from the most often used to the most recently generated and from simple to complex, explaining their specificities and giving concrete examples.

Advances in Genetic and Molecular Understanding of Alzheimer's Disease

Alzheimer's disease (AD) has become a common disease of the elderly for which no cure currently exists. After over 30 years of intensive research, we have gained extensive knowledge of the genetic and molecular factors involved and their interplay in disease. These findings suggest that different subgroups of AD may exist. Not only are we starting to treat autosomal dominant cases differently from sporadic cases, but we could be observing different underlying pathological mechanisms related to the amyloid cascade hypothesis, immune dysfunction, and a tau-dependent pathology. Genetic, molecular, and, more recently, multi-omic evidence support each of these scenarios, which are highly interconnected but can also point to the different subgroups of AD. The identification of the pathologic triggers and order of events in the disease processes are key to the design of treatments and therapies. Prevention and treatment of AD cannot be attempted using a single approach; different therapeutic strategies at specific disease stages may be appropriate. For successful prevention and treatment, biomarker assays must be designed so that patients can be more accurately monitored at specific points during the course of the disease and potential treatment. In addition, to advance the development of therapeutic drugs, models that better mimic the complexity of the human brain are needed; there have been several advances in this arena. Here, we review significant, recent developments in genetics, omics, and molecular studies that have contributed to the understanding of this disease. We also discuss the implications that these contributions have on medicine.

Challenging the Established Order: Innovating Clinical Trials for Amyotrophic Lateral Sclerosis

Development of effective treatments for amyotrophic lateral sclerosis (ALS) has been hampered by disease heterogeneity, a limited understanding of underlying pathophysiology, and methodologic design challenges. We have evaluated 2 major themes in the design of pivotal, phase 3 clinical trials for ALS—(1) patient selection and (2) analytical strategy—and discussed potential solutions with the European Medicines Agency. Several design considerations were assessed using data from 5 placebo-controlled clinical trials (n = 988), 4 population-based cohorts (n = 5,100), and 2,436 placebo-allocated patients from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. The validity of each proposed design modification was confirmed by means of simulation and illustrated for a hypothetical setting. Compared to classical trial design, the proposed design modifications reduce the sample size by 30.5% and placebo exposure time by 35.4%. By making use of prognostic survival models, one creates a potential to include a larger proportion of the population and maximize generalizability. We propose a flexible design framework that naturally adapts the trial duration when inaccurate assumptions are made at the design stage, such as enrollment or survival rate. In case of futility, the follow-up time is shortened and patient exposure to ineffective treatments or placebo is minimized. For diseases such as ALS, optimizing the use of resources, widening eligibility criteria, and minimizing exposure to futile treatments and placebo is critical to the development of effective treatments. Our proposed design modifications could circumvent important pitfalls and may serve as a blueprint for future clinical trials in this population.

A trial of gantenerumab or solanezumab in dominantly inherited Alzheimer's disease

Dominantly inherited Alzheimer's disease (DIAD) causes predictable biological changes decades before the onset of clinical symptoms, enabling testing of interventions in the asymptomatic and symptomatic stages to delay or slow disease progression. We conducted a randomized, placebo-controlled, multi-arm trial of gantenerumab or solanezumab in participants with DIAD across asymptomatic and symptomatic disease stages. Mutation carriers were assigned 3:1 to either drug or placebo and received treatment for 4-7 years. The primary outcome was a cognitive end point; secondary outcomes included clinical, cognitive, imaging and fluid biomarker measures. Fifty-two participants carrying a mutation were assigned to receive gantenerumab, 52 solanezumab and 40 placebo. Both drugs engaged their Aβ targets but neither demonstrated a beneficial effect on cognitive measures compared to controls. The solanezumab-treated group showed a greater cognitive decline on some measures and did not show benefits on downstream biomarkers. Gantenerumab significantly reduced amyloid plaques, cerebrospinal fluid total tau, and phospho-tau181 and attenuated increases of neurofilament light chain. Amyloid-related imaging abnormalities edema was observed in 19.2% (3 out of 11 were mildly symptomatic) of the gantenerumab group, 2.5% of the placebo group and 0% of the solanezumab group. Gantenerumab and solanezumab did not slow cognitive decline in symptomatic DIAD. The asymptomatic groups showed no cognitive decline; symptomatic participants had declined before reaching the target doses.

Therapy for Alzheimer's disease: Missing targets and functional markers?

The development of the next generation therapy for Alzheimer's disease (AD) presents a huge challenge given the number of promising treatment candidates that failed in trials, despite recent advancements in understanding of genetic, pathophysiologic and clinical characteristics of the disease. This review reflects some of the most current concepts and controversies in developing disease-modifying and new symptomatic treatments. It elaborates on recent changes in the AD research strategy for broadening drug targets, and potentials of emerging non-pharmacological treatment interventions. Established and novel biomarkers are discussed, including emerging cerebrospinal fluid and plasma biomarkers reflecting tau pathology, neuroinflammation and neurodegeneration. These fluid biomarkers together with neuroimaging findings can provide innovative objective assessments of subtle changes in brain reflecting disease progression. A particular emphasis is given to neurophysiological biomarkers which are well-suited for evaluating the brain overall neural network integrity and function. Combination of multiple biomarkers, including target engagement and outcome biomarkers will empower translational studies and facilitate successful development of effective therapies.

What can heart failure trialists learn from oncology trialists?

Globally, there has been little change in mortality rates from cardiovascular (CV) diseases or cancers over the past two decades (1997-2018). This is especially true for heart failure (HF) where 5-year mortality rates remain as high as 45-55%. In the same timeframe, the proportion of drug revenue, and regulatory drug approvals for cancer drugs, far out paces those for CV drugs. In 2018, while cancer drugs made 27% of Food and Drug Administration drug approvals, only 1% of drug approvals was for a CV drug, and over this entire 20 year span, only four drugs were approved for HF in the USA. Cardiovascular trialists need to reassess the design, execution, and purpose of CV clinical trials. In the area of oncology research, trials are much smaller, follow-up is shorter, and targeted therapies are common. Cardiovascular diseases and cancer are the two most common causes of death globally, and although they differ substantially, this review evaluates whether some elements of oncology research may be applicable in the CV arena. As one of the most underserved CV diseases, the review focuses on aspects of cancer research that may be applicable to HF research with the aim of streamlining the clinical trial process and decreasing the time and cost required to bring safe, effective, treatments to patients who need them. The paper is based on discussions among clinical trialists, industry representatives, regulatory authorities, and patients, which took place at the Cardiovascular Clinical Trialists Workshop in Washington, DC, on 8 December 2019 (https://www.globalcvctforum.com/2019 (14 September 2020)).

Practical Considerations and Recommendations for Master Protocol Framework: Basket, Umbrella and Platform Trials

Master protocol, categorized as basket trial, umbrella trial or platform trial, is an innovative clinical trial framework that aims to expedite clinical drug development, enhance trial efficiency, and eventually bring medicines to patients faster. Despite a clear uptake on the advantages in the concepts and designs, master protocols are still yet to be widely used. Part of that may be due to the fact that the master protocol framework comes with the need for new statistical designs and considerations for analyses and operational challenges. In this article, we provide an overview of the master protocol framework, unify the definitions with some examples, review the statistical methods for the designs and analyses, and focus our discussions on some practical considerations and recommendations of master protocols to help practitioners better design and implement such studies.

APP, PSEN1, and PSEN2 Variants in Alzheimer's Disease: Systematic Re-evaluation According to ACMG Guidelines

The strategies of classifying APP, PSEN1, and PSEN2 variants varied substantially in the previous studies. We aimed to re-evaluate these variants systematically according to the American college of medical genetics and genomics and the association for molecular pathology (ACMG-AMP) guidelines. In our study, APP, PSEN1, and PSEN2 variants were collected by searching Alzforum and PubMed database with keywords “PSEN1,” “PSEN2,” and “APP.” These variants were re-evaluated based on the ACMG-AMP guidelines. We compared the number of pathogenic/likely pathogenic variants of APP, PSEN1, and PSEN2. In total, 66 APP variants, 323 PSEN1 variants, and 63 PSEN2 variants were re-evaluated in our study. 94.91% of previously reported pathogenic variants were re-classified as pathogenic/likely pathogenic variants, while 5.09% of them were variants of uncertain significance (VUS). PSEN1 carried the most prevalent pathogenic/likely pathogenic variants, followed by APP and PSEN2. Significant statistically difference was identified among these three genes when comparing the number of pathogenic/likely pathogenic variants (P < 2.2 × 10^–16). Most of the previously reported pathogenic variants were re-classified as pathogenic/likely pathogenic variants while the others were re-evaluated as VUS, highlighting the importance of interpreting APP, PSEN1, and PSEN2 variants with caution according to ACMG-AMP guidelines.

Fifteen Years of the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study: Progress and Observations from 2,359 Older Adults Spanning the Spectrum from Cognitive Normality to Alzheimer's Disease

Background:

The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer’s disease dementia (AD)) as an ‘Inception cohort’ who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an ‘Enrichment cohort’ (as of 10 April 2019).

Objective:

Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation.

Methods:

Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations.

Results:

AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression.

Conclusion:

This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims.

ADAMANT: a placebo-controlled randomized phase 2 study of AADvac1, an active immunotherapy against pathological tau in Alzheimer's disease

Alzheimer's disease (AD) pathology is partly characterized by accumulation of aberrant forms of tau protein. Here we report the results of ADAMANT, a 24-month double-blinded, parallel-arm, randomized phase 2 multicenter placebo-controlled trial of AADvac1, an active peptide vaccine designed to target pathological tau in AD (EudraCT 2015-000630-30). Eleven doses of AADvac1 were administered to patients with mild AD dementia at 40 μg per dose over the course of the trial. The primary objective was to evaluate the safety and tolerability of long-term AADvac1 treatment. The secondary objectives were to evaluate immunogenicity and efficacy of AADvac1 treatment in slowing cognitive and functional decline. A total of 196 patients were randomized 3:2 between AADvac1 and placebo. AADvac1 was safe and well tolerated (AADvac1 n = 117, placebo n = 79; serious adverse events observed in 17.1% of AADvac1-treated individuals and 24.1% of placebo-treated individuals; adverse events observed in 84.6% of AADvac1-treated individuals and 81.0% of placebo-treated individuals). The vaccine induced high levels of IgG antibodies. No significant effects were found in cognitive and functional tests on the whole study sample (Clinical Dementia Rating-Sum of the Boxes scale adjusted mean point difference -0.360 (95% CI -1.306, 0.589)), custom cognitive battery adjusted mean z-score difference of 0.0008 (95% CI -0.169, 0.172). We also present results from exploratory and post hoc analyses looking at relevant biomarkers and clinical outcomes in specific subgroups. Our results show that AADvac1 is safe and immunogenic, but larger stratified studies are needed to better evaluate its potential clinical efficacy and impact on disease biomarkers.

Who funds Alzheimer's disease drug development?

INTRODUCTION

Despite the increase in Alzheimer's disease (AD) cases in the United States, no new treatments have been approved in the United States since 2003. The costs associated with drug development programs are high and serve as a significant deterrent to AD therapeutic investigations. In this study, we analyze the sponsorship data for AD clinical trials conducted since 2016 to assess the fiscal support for AD clinical trials.

METHODS

We analyzed the funding sources of all AD trials over the past 5 years as reported on ClinicalTrials.gov.

RESULTS

There were 136 trials being conducted for treatments in the US AD therapeutic pipeline on the index date of this study. Among non-prevention trials, disease-modifying therapies (DMT) in Phase 3 were almost entirely sponsored by the biopharmaceutical industry; Phase 2 DMT trials were split between the biopharmaceutical industry and funding from the National Institutes of Health (NIH) to academic medical centers (AMCs). The majority of prevention trials received sponsorship from public-private partnerships (PPP). Trials of symptomatic agents are equally likely to have biopharmaceutical or NIH/AMC sponsorship. Most trials with repurposed agents had NIH/AMC funding (89%). Since 2016, there has been consistent growth in the number of trials sponsored both in part and fully by NIH/AMC sources and in PPP, and there has been a reduction in biopharmaceutical company-sponsored trials.

DISCUSSION

The number of trials supported by the biopharmaceutical industry has decreased over the past 5 years; trials supported from federal sources and PPP have increased. Repurposed compounds are mostly in Phase 2 trials and provide critical mechanistic information.

Alzheimer's disease

In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies.

Emerging genetic complexity and rare genetic variants in neurodegenerative brain diseases

Knowledge of the molecular etiology of neurodegenerative brain diseases (NBD) has substantially increased over the past three decades. Early genetic studies of NBD families identified rare and highly penetrant deleterious mutations in causal genes that segregate with disease. Large genome-wide association studies uncovered common genetic variants that influenced disease risk. Major developments in next-generation sequencing (NGS) technologies accelerated gene discoveries at an unprecedented rate and revealed novel pathways underlying NBD pathogenesis. NGS technology exposed large numbers of rare genetic variants of uncertain significance (VUS) in coding regions, highlighting the genetic complexity of NBD. Since experimental studies of these coding rare VUS are largely lacking, the potential contributions of VUS to NBD etiology remain unknown. In this review, we summarize novel findings in NBD genetic etiology driven by NGS and the impact of rare VUS on NBD etiology. We consider different mechanisms by which rare VUS can act and influence NBD pathophysiology and discuss why a better understanding of rare VUS is instrumental for deriving novel insights into the molecular complexity and heterogeneity of NBD. New knowledge might open avenues for effective personalized therapies.