Experimental evidence for temporal uncoupling of brain Aβ deposition and neurodegenerative sequelae

Trial Analysis of Brain Activity Information for the Presymptomatic Disease Detection of Rheumatoid Arthritis

This study presents a trial analysis that uses brain activity information obtained from mice to detect rheumatoid arthritis (RA) in its presymptomatic stages. Specifically, we confirmed that F759 mice, serving as a mouse model of RA that is dependent on the inflammatory cytokine IL-6, and healthy wild-type mice can be classified on the basis of brain activity information. We clarified which brain regions are useful for the presymptomatic detection of RA. We introduced a matrix completion-based approach to handle missing brain activity information to perform the aforementioned analysis. In addition, we implemented a canonical correlation-based method capable of analyzing the relationship between various types of brain activity information. This method allowed us to accurately classify F759 and wild-type mice, thereby identifying essential features, including crucial brain regions, for the presymptomatic detection of RA. Our experiment obtained brain activity information from 15 F759 and 10 wild-type mice and analyzed the acquired data. By employing four types of classifiers, our experimental results show that the thalamus and periaqueductal gray are effective for the classification task. Furthermore, we confirmed that classification performance was maximized when seven brain regions were used, excluding the electromyogram and nucleus accumbens.

Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease

INTRODUCTION

Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double-blind phase 3 DIAN-TU-001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab.

METHODS

We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker.

RESULTS

LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid-no-change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid-reduction class exhibited reductions in the annual decline rates compared to the amyloid-growth class across multiple biomarker, clinical, and cognitive outcomes.

DISCUSSION

LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials.

HIGHLIGHTS

We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker. Despite similar baseline characteristics, the amyloid-reduction class exhibited remarkably better outcomes compared to the amyloid-growth class across multiple measures. LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects.

Protein aggregates containing wild-type and mutant NOTCH3 are major drivers of arterial pathology in CADASIL

Loss of arterial smooth muscle cells (SMCs) and abnormal accumulation of the extracellular domain of the NOTCH3 receptor (Notch3ECD) are the 2 core features of CADASIL, a common cerebral small vessel disease caused by highly stereotyped dominant mutations in NOTCH3. Yet the relationship between NOTCH3 receptor activity, Notch3ECD accumulation, and arterial SMC loss has remained elusive, hampering the development of disease-modifying therapies. Using dedicated histopathological and multiscale imaging modalities, we could detect and quantify previously undetectable CADASIL-driven arterial SMC loss in the CNS of mice expressing the archetypal Arg169Cys mutation. We found that arterial pathology was more severe and Notch3ECD accumulation greater in transgenic mice overexpressing the mutation on a wild-type Notch3 background (TgNotch3R169C) than in knockin Notch3R170C/R170C mice expressing this mutation without a wild-type Notch3 copy. Notably, expression of Notch3-regulated genes was essentially unchanged in TgNotch3R169C arteries. We further showed that wild-type Notch3ECD coaggregated with mutant Notch3ECD and that elimination of 1 copy of wild-type Notch3 in TgNotch3R169C was sufficient to attenuate Notch3ECD accumulation and arterial pathology. These findings suggest that Notch3ECD accumulation, involving mutant and wild-type NOTCH3, is a major driver of arterial SMC loss in CADASIL, paving the way for NOTCH3-lowering therapeutic strategies.

Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease

BACKGROUND

"Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology.

METHODS

We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-β-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE ε4 carrier status, sex, and education.

RESULTS

Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG.

CONCLUSIONS

We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI.

14-3-3 [Formula: see text]-reported early synaptic injury in Alzheimer's disease is independently mediated by sTREM2

INTRODUCTION

Synaptic loss is closely associated with tau aggregation and microglia activation in later stages of Alzheimer's disease (AD). However, synaptic damage happens early in AD at the very early stages of tau accumulation. It remains unclear whether microglia activation independently causes synaptic cleavage before tau aggregation appears.

METHODS

We investigated 104 participants across the AD continuum by measuring 14-3-3 zeta/delta ([Formula: see text]) as a cerebrospinal fluid biomarker for synaptic degradation, and fluid and imaging biomarkers of tau, amyloidosis, astrogliosis, neurodegeneration, and inflammation. We performed correlation analyses in cognitively unimpaired and impaired participants and used structural equation models to estimate the impact of microglia activation on synaptic injury in different disease stages.

RESULTS

14-3-3 [Formula: see text] was increased in participants with amyloid pathology at the early stages of tau aggregation before hippocampal volume loss was detectable. 14-3-3 [Formula: see text] correlated with amyloidosis and tau load in all participants but only with biomarkers of neurodegeneration and memory deficits in cognitively unimpaired participants. This early synaptic damage was independently mediated by sTREM2. At later disease stages, tau and astrogliosis additionally mediated synaptic loss.

CONCLUSIONS

Our results advertise that sTREM2 is mediating synaptic injury at the early stages of tau accumulation, underlining the importance of microglia activation for AD disease propagation.

Alzheimer's disease: From immunotherapy to immunoprevention

Recent Aβ-immunotherapy trials have yielded the first clear evidence that removing aggregated Aβ from the brains of symptomatic patients can slow the progression of Alzheimer's disease. The clinical benefit achieved in these trials has been modest, however, highlighting the need for both a deeper understanding of disease mechanisms and the importance of intervening early in the pathogenic cascade. An immunoprevention strategy for Alzheimer's disease is required that will integrate the findings from clinical trials with mechanistic insights from preclinical disease models to select promising antibodies, optimize the timing of intervention, identify early biomarkers, and mitigate potential side effects.

Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer's disease

Alzheimer's disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes-aggregation of the amyloid-β (Aβ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)-are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of Aβ plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with Aβ plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than Aβ and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with Aβ and tau.