Abstract Body

Aging is the main risk factor for Alzheimer disease (AD) and other neurodegenerative disorders such as Lewy body dementia (LBD), vascular dementia and frontotemporal dementia (FTD). As a result, close to fifty million people live with dementia over the World. Most efforts indicate that abnormal accumulation and cell to cell propagation of Abeta, Tau, a-synuclein, TDP43 and other proteins in the brain is a key mechanism that explains the neurotoxicity underlying these age-related disorders in the field of neurodegeneration; however very little is known about the molecular mechanisms through which the aging process might lead to selective neurodegeneration in AD and related dementias. Aging is characterized by the progressive accumulation of cellular and molecular damage and represents a delicate balance between resilience, resistance, repair and damage. Mechanisms involved in aging include alterations in DNA repair, proteostasis, inflammation, stem cells turn-around, mitochondrial function and cell senescence among others. The mechanism by which these aging mechanisms are linked to neurodegeneration in AD and related dementias is not understood. How these events -DNA damage, cell senescence, proteostasis and neurodegeneration- influence each other during aging? Is protein aggregation in combination with aging mechanisms responsible for neurodegeneration or are they independent? These are important questions to consider. We review the evidences of the role of aging mechanisms driving protein aggregation and neurodegeneration and address the role of genetic risk factors such as ApoE. Finally, we discuss new therapeutic venues to target aging mechanisms as promising option for future treatment of AD and related dementias.

Aims

We review the evidences of the role of aging mechanisms driving protein aggregation and neurodegeneration and discuss new therapeutic venues to target aging mechanisms.

Methods

The mechanism by which these aging mechanisms are linked to neurodegeneration in AD and related dementias is not understood. How these events -DNA damage, cell senescence, proteostasis and neurodegeneration- influence each other during aging? Is protein aggregation in combination with aging mechanisms responsible for neurodegeneration or are they independent? These are important questions to consider.

Results

Aging is the main risk factor for Alzheimer disease (AD) and other neurodegenerative disorders such as Lewy body dementia (LBD) and vascular dementia and frontotemporal dementia (FTD). As a result, close to fifty million people live with dementia over the World. Most efforts indicate that abnormal accumulation and cell to cell propagation of Abeta, Tau, a-synuclein, TDP43 and other proteins in the brain is a key mechanism that explains the neurotoxicity underlying these age-related disorders in the field of neurodegeneration; however very little is known about the molecular mechanisms through which the aging process might lead to selective neurodegeneration in AD and related dementias. Aging is characterized by the progressive accumulation of cellular and molecular damage and represents a delicate balance between resilience, resistance, repair and damage. Mechanisms involved in aging include alterations in DNA repair, proteostasis, inflammation, stem cells turn-around, mitochondrial function and cell senescence among others.

Conclusions

Understanding the role of aging mechanisms in AD is critical at developing novel therapeuticals combining anti-aging apporaches with drugs targeting the proteinopathy.

Abstract Body

It is largely unknown when and what kind of molecular events initiate Alzheimer’s disease pathology. We asked this question by comprehensive mass analysis detecting 70,000-100,000 phosphopeptides (confidence>95%) from cerebral cortex tissues of four AD mouse models at multiple time points together with human AD brains, and discovered several proteins whose phosphorylation states were changed before appearance of extracellular Abeta aggregates.

The first one was pSer46-MARCKS, which was mainly localized in degenerative neurites. Antibody against pSer46-MARCKS was very sensitive and detected a single necrotic neuron with intracellular Abeta accumulation surrounded by degenerative neurites. Chronological changes of morphology suggested that residual Abeta after primary necrosis became the seed for extracellular Abeta aggregates and induced secondary necrosis of surrounding neurons.

Intracellular Abeta interacted with YAP, an essential molecule for cell survival, deprived it from nucleus, suppressed TEAD-YAP-dependent transcription, and finally induced necrosis. Gene therapy with AAV expressing YAPdeltaC, a neuron-specific isoform lacking the binding domain for p73 but able to interact with TEAD, suppressed necrosis and decreased extracellular Abeta aggregates in mouse models at later time points.

Secondary necrosis was mediated by Abeta and HMGB1 both released from necrotic neurons as DAMPs, while the ability of HMGB1 to induce neurite degeneration was higher than Abeta. HMGB1 is also well known as a ligand of TLR2/4, and triggers brain inflammation. In this regard, we have developed anti-HMGB1 antibody that effectively inhibits secondary necrosis and neurite degeneration in mouse models.

We revealed the ultra-early phase pathology and molecular targets for tacking the initial molecular branches.

Aims

There is a compelling need for the very early treatment of Alzheimer’s disease (AD) at the asymptomatic stage. The Anti-Amyloid Treatment in Asymptomatic AD (A4) Study is a secondary prevention trial of solanezumab in amyloid-PET positive, clinically normal older individuals being conducted at 67 sites in the North America, Australia and Japan. Furthermore, trial ready cohorts for preclinical and prodromal AD are being established to maximize the efficiency of recruitment for the emerging preclinical AD trials.

Abstract Body

Methods

We report the screening data results of the A4 study conducted in Japan, as well as the current status of the Japanese Trial-Ready Cohort for preclinical and prodromal AD (J-TRC).

Results

In Japan, 161 volunteers were screened for A4, 100 underwent florbetapir amyloid PET, and 20 were characterized as Aβ+. The age (mean: 75.5 y in Aβ+) and APOE4 positivity (45% in Aβ+, 18% in Aβ-) were significantly higher in Aβ+. In Aβ+, PACC at screening showed a trend of worsening and CFI-Participant was significantly higher. These results were consistent with those from the whole cohort including North America and Australia. The J-TRC has a similar structure to that of US-TRC-PAD, consisting of the J-TRC webstudy and an in-person, J-TRC on-site study, having recruited ~4500 and ~40 participants, respectively, as of Sep 2020. Machine-learning algorithms based on the A4 screen data were useful in the prediction of Aβ+ individuals in the J-TRC candidates.

Conclusions

Treating AD at the asymptomatic stage would be vital to its prevention, which will be facilitated by the establishment of trial-ready cohorts for preclinical AD.

Abstract Body

The diagnosis of Alzheimer’s disease (AD) is evolving through the use of refined clinical and biomarker techniques. The NIA-AA AD Research Framework proposes that AD be defined on its biological basis, i.e., the presence of amyloid and tau. As such, the role of biomarkers is becoming increasingly important. From a clinical perspective, the clinical staging scheme proposed by the Framework adds an element of granularity to the clinical continuum of AD. While neuroimaging and cerebrospinal fluid biomarkers have been the mainstay of documenting the presence of AD pathophysiology for many years, more recently, plasma markers for Aβ42, Aβ42/40, p-tau 181, 217 and 231 have become of central interest. While combinations of these analytes are being evaluated, there is no consensus on the specific platforms that should be used to assess these markers. Various prediction formulas involving Aβ42/40, Apolipoprotein E4, p-tau 181, 217 and cognitive markers have been proposed to predict the presence of amyloid and clinical progression. The performance of these algorithms along with clinical staging will need to be validated in the general community to determine if they are applicable for clinical purposes and for the design of randomized controlled trials. The role of these biomarkers may revolutionize the design of studies and eventually be applicable in the clinic.

Abstract Body

There is increasing agreement that anatomical changes in the retina may provide an opportunity for identifying and quantifying central nervous system (CNS) amyloid levels. Additionally, when compared with healthy age-matched controls, patients with AD have reduced numbers of ganglion cell axons, and they are three times more likely to have increased optic nerve cup-to-disc ratio, a potential consequence of ganglion cell and nerve fiber loss. Further, peripapillary retinal nerve fiber layer (RNFL) thickness appears to be reduced (suggestive of optic atrophy) in patients with mild cognitive impairment (MCI) and mild-to-moderate AD when compared with age-matched controls. We have recently shown that individuals with likely preclinical AD have corresponding thinning of the macular RNFL. Finally, several groups have reported decreased retinal vascular bed complexity, blood flow and oxygen consumption in MCI and AD, in comparison to matched control participants. A number of these retinal changes are also the result of effects of normal aging, and there is generally a paucity of data describing longitudinal changes over time within the same subjects, with respect to the retinal layers, the retinal microvasculature, and aggregation of inclusion bodies that may contain fibrillar beta-amyloid (Aβ) from the earliest, preclinical stage of AD. The purpose of this presentation will be to present an update on what we can conclude from available literature, new trends and developments in this field, and what questions remain open and uncertain, with respect to the development of retinal biomarkers of AD.

Abstract Body

RACIAL DIFFERENCES IN MOLECULAR BIOMARKERS FOR AD

John C. Morris, MD; Suzanne Schindler, MD; Chengjie Xiong, PhD; on behalf of the Knight ADRC, Washington University School of Medicine, St. Louis, Missouri, USA

Objectives:

The possibility of racial differences in molecular biomarkers for Alzheimer disease (AD) has been minimally explored, in part because few research participants from under-represented groups are included in biomarker studies.

Methods:

Using a cohort of 1255 community living adults (including 173 self-identified Blacks), both those who were cognitively normal and those with symptomatic AD, who had completed at least 1 brain magnetic resonance imaging (MRI) study, and/or amyloid positron emission tomography (PET) scan, and/or 1 lumbar puncture to obtain cerebrospinal fluid (CSF), we compared cross-sectional biomarker modalities in Black versus White participants.

Results:

There were no racial differences in mean cortical standardized uptake value ratios for Pittsburgh Compound B or for CSF Aβ42. However, mean CSF concentrations of tau and p-tau₁₈₁ were lower in Black versus White participants; there was a race by APOE ε4 interaction. Moreover, Black participants had more coding variants for TREM2 that were associated with lower CSF soluble TREM2 concentrations than were found for Whites.

Conclusions:

Identifying racial differences in molecular biomarkers for AD is important for the understanding of AD pathophysiology, diagnosis, and treatment. Interpreting these differences will require the appreciation of the effects of systemic racism and other social determinants of health as they relate to observed biomarker disparities in AD.

Abstract Body

The ATN framework clearly paves the way for a diagnosis before the stage of AD-dementia. In clinical practice, a diagnosis in predementia stages in fact entails a prognosis, as patients want to know what they can expect. Using ATN biomarkers, individualized risk profiling for MCI patients becomes feasible. A clinical encounter study evaluating doctor-patient communication in memory clinics revealed however that clinicians are quite reluctant to share specific prognostic information with MCI patients. In the context of predementia diagnosis, Subjective Cognitive Decline (SCD) is even more challenging. A recent point of view paper provides a clinical characterization of SCD, and attempts to provide directions for clinicians. Although on a group level, ATN biomarkers clearly predict incident dementia in SCD, individualized risk modeling remains challenging, as current models have suboptimal generalizability, due to the lack of truly longitudinal data.Yet, the number of people wanting to know the status of their brain health with the ambition to maintain or improve their own brain health rapidly increases. In a Delphi study to identify topics most relevant to discuss in the diagnostic process, patients and caregivers indicated they value precise and specific information, even when that does not provide complete certainty.Tools to support both clinicians and patients/families in decision making and communicating about AD diagnosis are therefore urgently needed. ADappt (www.adappt.health) is a first attempt at providing such a tool.

Aims

Objective: Visual system measures may represent potential biomarkers for Alzheimer’s disease (AD). Our goal was to investigate the relationship of two potential visual system biomarkers, retinal nerve fiber layer thickness (RNFL) and visual contrast sensitivity (CS), with neuroimaging biomarkers of amyloid (A), tau (T), and neurodegeneration (N).

Methods

Methods: 52 participants (25 cognitively normal, 14 subjective cognitive decline (SCD), 9 mild cognitive impairment (MCI), and 4 AD) underwent OCT to measure RNFL, frequency doubling technology to measure CS, amyloid PET, and MRI. A subset (n=44) underwent tau PET. A/T/N was measured continuously and dichotomously (cortical Centiloid (CL)/Aβ+ (CL>21), lateral temporal tau SUVR/tau+ (Braak stage>3), hippocampal volume (HV)/neurodegeneration+ (w-score<-1.5)). Continuous relationships were assessed using partial Pearson correlation, covaried for age, sex, and race/ethnicity, as well as ICV (MRI only). Stepwise logistic regression was used to predict dichotomous A/T/N positivity. Analyses were done in the full sample and in at-risk individuals only (SCD/MCI).

Results

Results: In continuous analyses, amyloid was associated with both CS and RNFL thickness (r_p=-0.38, p=0.008; r_p=-0.29, p=0.044, respectively), tau was associated with CS (r_p=-0.59, p<0.001), and HV was associated with only RNFL (r_p=0.32, p=0.028). Dichotomous analyses indicated that CS was associated with Aβ+ and tau+ (p=0.030, p=0.013, respectively), while RNFL showed a trend association associated with neurodegeneration+ (p=0.057). Similar results for A/T, but not N, were found when only including SCD/MCI (p<0.05).

Conclusions

Conclusion: Visual measures are promising biomarkers for A/T/N, with a combination of multiple visual measures may provide comprehensive prediction across pathologies. Future studies in larger samples are needed.