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The Alzheimer's disease drug development pipeline to be reviewed in this lecture is comprised of all drugs in phase 1, phase 2, or phase 3 of trials for drugs in development for any stage of Alzheimer's disease (AD) including primary prevention, secondary prevention, prodromal AD, or dementia due to AD. The specific number of drugs and of trials in progress will be presented. The Common Alzheimer's Disease Research Ontology (CADRO) is used to identify the targets of AD drug development and the distribution of drugs across these targets and their related mechanisms will be discussed. Recent trends in the pipeline include the increased number of biological compounds and the growth of agents targeting aspects of inflammation or synaptic plasticity. The approval of monoclonal antibodies has drawn attention to this approach to AD treatment and amyloid-directed monoclonal antibodies are in all phases of AD drug development. The use of accelerated approval based on biomarkers considered reasonably likely to predict clinical benefit has increased interest in biomarker-based or biomarker-supported drug development. Most agents in the pipeline are directed at prodromal AD or mild AD dementia. More drugs directed at AD prevention and at AD dementia are needed. Eighty to 90% of drugs in the pipeline have the goal of disease modification; there are few cogntive enhancers or drugs for neuropsychiatric symptoms. Twenty to 30% of the drugs in the pipeline are repurposed agents approved for treatment of another disorder. Review of pipeline trials reveal challenges in timely recruitment and in attracting diverse populations into trials. The drugs in the development pipeline have a broad range of targets and mechanisms; trial conduct is improving; and biomarkers play a larger role in guiding drug development.

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Where do we go from here in Alzheimer’s disease? After the approval of the first disease modifying therapies in Alzheimer’s disease by the FDA and the pending approvals by other regulatory bodies around the globe, one may wonder; is this the beginning or the end?

In the current talk we will argue that having these therapies available still leaves room for many alternatives that are cheaper, easier to use, more effective and most of all safer. In our view there is a need for:

-alternative approaches to the main pathologies of Alzheimer’s disease by small molecules, antisense therapies, RNA interference, gene therapy and active immunization

-symptomatic therapies aimed at restoring or improving memory, language, spatial orientation, visuoperception and executive functions, as well as accompanying issues such as sleep disorders, anxiety, agitation and delusions, to name a few.

-alternative targets outside of amyloid and tau, such as lysosomal and mitochondrial function, inflammation, synaptic function, sleep architecture and many others, as depicted below

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The prospect of effective blood-based biomarkers in Alzheimer’s disease is promising. Most of the research has been generated in referral clinics. We evaluated the performance of mass spectrometry (MS) plasma Aβ42/40 ratio, phosphorylated-to-non-phosphorylated tau217 ratio (%p-tau217), and the Amyloid Probability Score 2 (APS2)(PrecivityAD2™ test result), a score generated by C₂N Diagnostics via a statistical algorithm using both Aβ42/40 and %p-tau217, in the population-based Mayo Clinic Study of Aging. We included 412 cognitively unimpaired (CU) individuals who had MS plasma measures and either progressed to mild cognitive impairment (MCI, n=93) or remained CU (n=319) over a median duration of 8 years (range 1-14). Associations between plasma biomarkers and progression from CU to MCI MCI or annual decline in memory and global cognitive z scores were assessed using Cox proportional hazard models and linear mixed effects models adjusting for age, sex, and education. Participants were a median of 74 years (range 60-94), 45% female, and 30% APOE4 carriers. APS2 was associated with progression from CU to (HR 1.3 for a 25-unit increase, p<0.01), with or without APOE in the model. A 0.02 lower Aβ42/40 was associated with a −0.02 z/year decline in the global cognition z score (without APOE, p<0.01 and with APOE, p=0.02). A doubling of the %p-tau217 value was associated with a −0.02 z/year annual decline in memory or global cognition z scores with or without APOE (p<0.01). Similarly, a 25-unit higher APS2 was associated with a −0.03 z/year annual decline in memory or −0.04 z/year global cognition (p<0.01) with or without APOE. These data suggest that APS2 in the cognitively unimpaired community residents may be informative about subsequent progression to MCI and a meaningful decline in cognitive function.

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The National Institute on Aging and the Alzheimer’s Association (NIA-AA) convened three separate work groups in 2011 and a single work group in 2018 to create recommendations for the diagnosis and characterization of Alzheimer’s disease (AD). Several fundamental principles emerged from these efforts. These include, AD should be defined biologically, not by clinical syndromes. The disease is a continuum that is first evident with the appearance of brain pathologic changes in asymptomatic individuals and progresses through stages of increasing pathologic burden eventually leading to appearance/progression of clinical symptoms.

The NIA-AA Revised Criteria for Diagnosis and Staging of Alzheimer's Disease document updates the 2018 research framework document in response to several recent developments. First, since 2018, for the first time, treatments that target core disease pathology have received regulatory approval. Second, accepted biomarkers in 2018 were either CSF assays or imaging. Since then, plasma-based biomarkers were developed, and some (but not all) demonstrate excellent diagnostic performance. Third, research studies have demonstrated that imaging and fluid biomarkers within a category are not interchangeable for many intended uses.

The Alzheimer’s Association is the sponsoring organization for this revision. The work group was initiated in late 2022. Two draft versions of the document were posted for public comment in 2023. Draft documents were revised in response to comments received. The final version of the revised criteria will be presented at ADPD.

The objective of the work group is to propose objective criteria for diagnosis and staging AD to serve as a bridge between research and clinical care. We point out that these are not intended to be specific clinical practise guidelines, but rather criteria for diagnosis and staging of AD that reflect current science.

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Cognitive ability among older individuals differs markedly, with some people succumbing to dementia while others do not experience cognitive decline even into late life, referred to as successful aging (SA). Two general methods for selecting people with SA can be used: identifying those performing at the top of the distribution of cognitive scores, which we refer to as exceptional agers (EA), or selecting people who do not show evidence of cognitive decline, which we refer to as cognitive maintainers (CM). The EA and CM approaches to SA require cross-sectional and longitudinal cognitive data, respectively. Here we define EAs using a machine learning technique with partial least squares regression to estimate cognitive age based on a battery of neuropsychological tests. Participants were assigned a cognitive age gap (CAG), the difference between chronological age and predicted cognitive age. We find that individuals who are in the “youngest” 20 percent of CAG have larger hippocampal volume, thicker anterior cingulate cortex, and lower PET measurements of tau in entorhinal cortex, but similar PET measured β-amyloid. Furthermore, individuals with a younger cognitive age (lower CAG) show slower decline in memory and global cognitive function and they also show less longitudinal atrophy in the anterior cingulate cortex. To define CM, we used longitudinal data and selected CM individuals as those with a slope on a composite memory score ≥ 0. Compared to decliners, these individuals did not differ on baseline memory ability but did show lower PET measures of both Aβ (globally) and tau (entorhinal cortex and temporal meta-ROI) and larger hippocampal volumes. Taken together, these findings show that different definitions of SA are associated with preserved brain volume and lower levels of AD pathology.

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BACKGROUND: Precision medicine is customization of healthcare to tailor treatments to patients, and involves classifying subpopulations differing by susceptibility, biology, prognosis, and therapeutic response. Alzheimer’s disease and related dementia (ADRD) are complex neurodegenerative diseases that entail multiple clinical presentations, pathogenic mechanisms, genetic markers, along with the challenge of studying these factors in individuals living with ADRD. Unlike oncology, we generally do not biopsy the brain, rather deep phenotypic characterization of clinical-cognitive-functional-behavioral factors, imaging, plasma biomarkers, and genetics can be exploited to develop precision medicine approaches to ADRD treatment and prevention.

METHODS: The Health Brain Initiative (HBI) is a longitudinal, observational cohort study of deeply-phenotyped participants from diverse ethnic/racial backgrounds with annual visits to collect, analyze, and store clinical, cognitive, behavioral, functional, genetic, and neuroimaging data and biospecimens.

RESULTS: As of October 2023, HBI includes 189 individuals with comprehensive clinical-cognitive-functional-behavioral data, social determinants of health, volumetric MRI, plasma ADRD biomarkers, genetics with complete Amyloid-Tau-Neurodegeneration staging with individuals returning for Year 2 follow-up visits. Participants had a mean age of 68.3+10.1y, 16.4+3.4y of education, 66.5% female, and 23% racial/ethnic minorities. Using biomarker status as measures of ADRD pathology, the cohort includes True Controls, Preclinical AD, MCI due to AD, and MCI due to non-AD causes, each with differential patterns of progression and response to precision medicine approaches one year later.

CONCLUSION: HBI has focused on deep phenotyping individuals to examine small deviations from normal or expected structure, function, and behavior. Using this detailed and comprehensive picture, we can characterize factors that make individuals (a) more likely to develop disease (i.e., vulnerability) or less likely to develop disease (i.e., resilience) and create precision medicine approaches to build a better brain as we age.

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The pattern of failures and success in Alzheimer’s disease (AD) clinical trials led to the recent successes with monoclonal antibodies targeting amyloid, which opens up many new directions for research into treatment for AD in the future. Gaining greater understanding from these successes and failures will help researchers to focus their efforts on avenues that have the highest potential benefit.

We performed a meta-analysis of 106 studies of 72 AD treatments. In order to assess the success or failure of these studies, a global statistical test was used that combined the ADAS-cog, ADCS-ADL and CDR-sb. This approach emphasizes the overall treatment effect over effects on just one or another outcome out of the important domains. One of the things that has contributed to the recent successes is use of composite scores targeting true disease progression in the phase 2 studies for both lecanemab and donanemab. A similar approach would have possibly blunted much of the controversy surrounding the aducanumab approval.

We present results of a meta-analysis across 106 studies of 72 AD treatments. These results are based on global statistical tests that are also converted to time savings demonstrating clear successes and failures in studies that were originally harder to interpret. We also present results of meta-analyses combining similar treatments across programs to help illuminate overlooked mechanisms as well as more conclusive failures

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OBJECTIVES: ADNI celebrates 20 years with impacts on clinical trials and over 5,000 publications. However, one major limitation of Alzheimer’s disease (AD) research and ADNI has been oversampling of well-educated non-Latino white people. The goal of ADNI4 is to have 50% of new in-clinic enrollments be composed of individuals who self-identify as underrepresented persons (URPs; defined as ethnocultural diversity and/or those with 12 years of education or less).

METHODS: A digital marketing campaign was designed with a community-engaged and culturally-informed approach, with an initial focus on enrolling individuals from Black and Latino communities. Individualized marketing campaigns and tailored websites were developed to help recruit participants for each clinical site. Marketing drove interested viewers to an ADNI website, individuals provided informed consent, answered questions concerning demographics, exclusionary issues, and completed self-administered cognitive assessments: 12-item ECog and Novoic’s Storyteller, an automated speech-based test.

RESULTS: Participant selection oversampled URPs as well as those with suspected memory impairments (from ECog and Novoic). Selected participants were subsequently asked to provide a blood sample at a Quest Diagnostics phlebotomy center near their home. Plasma was analyzed for amyloid 42/40, species of phosphorylated tau, and other analytes. Participants who appeared likely to be amyloid positive were referred to an ADNI4 clinic.

CONCLUSIONS: ADNI has had a high impact on the AD field, leading to important discoveries and successful clinical trials. ADNI4’s digital recruitment efforts that include culturally-engaged approaches can provide another avenue to increase enrollment of individuals from diverse backgrounds into clinical research. Using online questionnaires and cognitive tests, coupled with AD plasma biomarker results, allows more detailed pre-screening of participants and subsequently refined selection of individuals for referral to clinical trials.