Neuropathologic Correlates of Human Cortical Proteins in Alzheimer Disease and Related Dementias

Cellular communities reveal trajectories of brain ageing and Alzheimer's disease

Alzheimer's disease (AD) has recently been associated with diverse cell states1-11, yet when and how these states affect the onset of AD remains unclear. Here we used a data-driven approach to reconstruct the dynamics of the brain's cellular environment and identified a trajectory leading to AD that is distinct from other ageing-related effects. First, we built a comprehensive cell atlas of the aged prefrontal cortex from 1.65 million single-nucleus RNA-sequencing profiles sampled from 437 older individuals, and identified specific glial and neuronal subpopulations associated with AD-related traits. Causal modelling then prioritized two distinct lipid-associated microglial subpopulations-one drives amyloid-β proteinopathy while the other mediates the effect of amyloid-β on tau proteinopathy-as well as an astrocyte subpopulation that mediates the effect of tau on cognitive decline. To model the dynamics of cellular environments, we devised the BEYOND methodology, which identified two distinct trajectories of brain ageing, each defined by coordinated progressive changes in certain cellular communities that lead to (1) AD dementia or (2) alternative brain ageing. Thus, we provide a cellular foundation for a new perspective on AD pathophysiology that informs personalized therapeutic development, targeting different cellular communities for individuals on the path to AD or to alternative brain ageing.

Controversial Past, Splendid Present, Unpredictable Future: A Brief Review of Alzheimer Disease History

Background: The concept of Alzheimer disease (AD)-since its histological discovery by Alzheimer to the present day-has undergone substantial modifications. Methods: We conducted a classical narrative review of this field with a bibliography selection (giving preference to Medline best match). Results: The following subjects are reviewed and discussed: Alzheimer's discovery, Kraepelin's creation of a new disease that was a rare condition until the 1970's, the growing interest and investment in AD as a major killer in a society with a large elderly population in the second half of the 20th century, the consolidation of the AD clinicopathological model, and the modern AD nosology based on the dominant amyloid hypothesis among many others. In the 21st century, the development of AD biomarkers has supported a novel biological definition of AD, although the proposed therapies have failed to cure this disease. The incidence of dementia/AD has shown a decrease in affluent countries (possibly due to control of risk factors), and mixed dementia has been established as the most frequent etiology in the oldest old. Conclusions: The current concept of AD lacks unanimity. Many hypotheses attempt to explain its complex physiopathology entwined with aging, and the dominant amyloid cascade has yielded poor therapeutic results. The reduction in the incidence of dementia/AD appears promising but it should be confirmed in the future. A reevaluation of the AD concept is also necessary.

Autophagy Markers Are Altered in Alzheimer's Disease, Dementia with Lewy Bodies and Frontotemporal Dementia

The accumulation of protein aggregates defines distinct, yet overlapping pathologies such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). In this study, we investigated ATG5, UBQLN2, ULK1, and LC3 concentrations in 66 brain specimens and 120 plasma samples from AD, DLB, FTD, and control subjects (CTRL). Protein concentration was measured with ELISA kits in temporal, frontal, and occipital cortex specimens of 32 AD, 10 DLB, 10 FTD, and 14 CTRL, and in plasma samples of 30 AD, 30 DLB, 30 FTD, and 30 CTRL. We found alterations in ATG5, UBQLN2, ULK1, and LC3 levels in patients; ATG5 and UBQLN2 levels were decreased in both brain specimens and plasma samples of patients compared to those of the CTRL, while LC3 levels were increased in the frontal cortex of DLB and FTD patients. In this study, we demonstrate alterations in different steps related to ATG5, UBQLN2, and LC3 autophagy pathways in DLB and FTD patients. Molecular alterations in the autophagic processes could play a role in a shared pathway involved in the pathogenesis of neurodegeneration, supporting the hypothesis of a common molecular mechanism underlying major neurodegenerative dementias and suggesting different potential therapeutic targets in the autophagy pathway for these disorders.

Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis

Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease.

Moving beyond amyloid and tau to capture the biological heterogeneity of Alzheimer's disease

Alzheimer's disease (AD) manifests along a spectrum of cognitive deficits and levels of neuropathology. Genetic studies support a heterogeneous disease mechanism, with around 70 associated loci to date, implicating several biological processes that mediate risk for AD. Despite this heterogeneity, most experimental systems for testing new therapeutics are not designed to capture the genetically complex drivers of AD risk. In this review, we first provide an overview of those aspects of AD that are largely stereotyped and those that are heterogeneous, and we review the evidence supporting the concept that different subtypes of AD are important to consider in the design of agents for the prevention and treatment of the disease. We then dive into the multifaceted biological domains implicated to date in AD risk, highlighting studies of the diverse genetic drivers of disease. Finally, we explore recent efforts to identify biological subtypes of AD, with an emphasis on the experimental systems and data sets available to support progress in this area.

Open drug discovery in Alzheimer's disease

Alzheimer's disease (AD) drug discovery has focused on a set of highly studied therapeutic hypotheses, with limited success. The heterogeneous nature of AD processes suggests that a more diverse, systems-integrated strategy may identify new therapeutic hypotheses. Although many target hypotheses have arisen from systems-level modeling of human disease, in practice and for many reasons, it has proven challenging to translate them into drug discovery pipelines. First, many hypotheses implicate protein targets and/or biological mechanisms that are under-studied, meaning there is a paucity of evidence to inform experimental strategies as well as high-quality reagents to perform them. Second, systems-level targets are predicted to act in concert, requiring adaptations in how we characterize new drug targets. Here we posit that the development and open distribution of high-quality experimental reagents and informatic outputs-termed target enabling packages (TEPs)-will catalyze rapid evaluation of emerging systems-integrated targets in AD by enabling parallel, independent, and unencumbered research.

Cellular dynamics across aged human brains uncover a multicellular cascade leading to Alzheimer's disease

Alzheimer's Disease (AD) is a progressive neurodegenerative disease seen with advancing age. Recent studies have revealed diverse AD-associated cell states, yet when and how they impact the causal chain leading to AD remains unknown. To reconstruct the dynamics of the brain's cellular environment along the disease cascade and to distinguish between AD and aging effects, we built a comprehensive cell atlas of the aged prefrontal cortex from 1.64 million single-nucleus RNA-seq profiles. We associated glial, vascular and neuronal subpopulations with AD-related traits for 424 aging individuals, and aligned them along the disease cascade using causal modeling. We identified two distinct lipid-associated microglial subpopulations, one contributed to amyloid-β proteinopathy while the other mediated the effect of amyloid-β in accelerating tau proteinopathy, as well as an astrocyte subpopulation that mediated the effect of tau on cognitive decline. To model the coordinated dynamics of the entire cellular environment we devised the BEYOND methodology which uncovered two distinct trajectories of brain aging that are defined by distinct sequences of changes in cellular communities. Older individuals are engaged in one of two possible trajectories, each associated with progressive changes in specific cellular communities that end with: (1) AD dementia or (2) alternative brain aging. Thus, we provide a cellular foundation for a new perspective of AD pathophysiology that could inform the development of new therapeutic interventions targeting cellular communities, while designing a different clinical management for those individuals on the path to AD or to alternative brain aging.

A Pragmatic, Data-Driven Method to Determine Cutoffs for CSF Biomarkers of Alzheimer Disease Based on Validation Against PET Imaging

BACKGROUND AND OBJECTIVES

To elaborate a new algorithm to establish a standardized method to define cutoffs for CSF biomarkers of Alzheimer disease (AD) by validating the algorithm against CSF classification derived from PET imaging.

METHODS

Low and high levels of CSF phosphorylated tau were first identified to establish optimal cutoffs for CSF β-amyloid (Aβ) peptide biomarkers. These Aβ cutoffs were then used to determine cutoffs for CSF tau and phosphorylated tau markers. We compared this algorithm to a reference method, based on tau and amyloid PET imaging status (ADNI study), and then applied the algorithm to 10 large clinical cohorts of patients.

RESULTS

A total of 6,922 patients with CSF biomarker data were included (mean [SD] age: 70.6 [8.5] years, 51.0% women). In the ADNI study population (n = 497), the agreement between classification based on our algorithm and the one based on amyloid/tau PET imaging was high, with Cohen's kappa coefficient between 0.87 and 0.99. Applying the algorithm to 10 large cohorts of patients (n = 6,425), the proportion of persons with AD ranged from 25.9% to 43.5%.

DISCUSSION

The proposed novel, pragmatic method to determine CSF biomarker cutoffs for AD does not require assessment of other biomarkers or assumptions concerning the clinical diagnosis of patients. Use of this standardized algorithm is likely to reduce heterogeneity in AD classification.