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Results for “Glymphatic clearance”

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PubMed2026

Glymphatic dysfunction mediates inflammation-driven vascular burden and cognitive decline in cerebral small vessel disease.

BACKGROUND: Cerebral small vessel disease (CSVD) is increasingly recognized as a disorder involving microvascular dysfunction, impaired perivascular clearance, and inflammatory processes. However, how systemic inflammatory burden, neurovascular coupling (NVC), glymphatic MRI markers, vascular lesion burden, and cognition are interrelated remains unclear. MATERIALS AND METHODS: In this prospective study, 155 patients with CSVD and 70 healthy controls (HCs) underwent multimodal MRI. NVC was quantified using the cerebral blood flow/fractional amplitude of low-frequency fluctuations ratio. Glymphatic function was assessed via the diffusion tensor image analysis along the perivascular space (ALPS) index, choroid plexus volume (CPV), and perivascular space (PVS) fractions. Structural equation modeling (SEM) was employed to evaluate the direct and indirect effects of inflammatory markers on vascular burden and cognitive performance. RESULTS: Patients with CSVD exhibited significantly diminished NVC (specifically in the right median cingulate and left frontal gyri) and impaired glymphatic function (lower ALPS-index; higher CPV and PVS fractions) compared to HCs. SEM revealed that inflammatory biomarkers exerted both a direct effect on vascular burden and a substantial indirect effect (accounting for 66.3% of the total effect) mediated through two pathways: a single-mediation path via glymphatic function (42.8%) and a serial-mediation path via NVC and glymphatic function (23.5%). Increased vascular burden was significantly associated with poorer cognitive performance. CONCLUSION: Inflammation drives CSVD progression and cognitive decline primarily through the disruption of NVC and glymphatic clearance mechanisms. These findings highlight glymphatic dysfunction as a critical mediator of inflammation-related structural brain damage.

Humans↗

PubMed2026

The TyrRS cascade: circadian gating of neuronal DNA repair and its collapse in aging.

Age-related neurodegenerative diseases are characterized by progressive DNA damage in post-mitotic neurons against a backdrop of deteriorating circadian rhythms, yet the molecular link between these conjoined features of brain aging remains unclear. We propose the TyrRS cascade as that link: a signaling architecture in which the noncanonical nuclear functions of tyrosyl-tRNA synthetase (TyrRS/YARS1) schedule neuronal genome maintenance across the day through three coregulated streams, PARP1-mediated damage sensing, TRIM28/NuRD heterochromatin maintenance, and LIN9/DREAM control of a 67-gene repair archive. The model's central commitment is that the operative variable is oscillation amplitude rather than mean activity. We argue that as serum tyrosine rises with age and circadian amplitude flattens, these insults compound into a double-hit collapse that traps the cascade in a frozen-intermediate state, which bulk-tissue assays misread as elevated mean activity when the oscillation has merely lost its excursion. Placed in dialogue with oscillatory-clearance models of sleep, the cascade and the glymphatic system emerge as complementary, compartment-separated arms of a single sleep-dependent maintenance program that fail together through amplitude collapse, yielding a signature of preserved phase architecture with reduced dynamic range. Reframing neurodegeneration as a scheduling failure rather than a capacity failure carries three translational consequences: Pulsatile, phase-aligned dosing should outperform sustained-release pharmacology, which is predicted to flatten the rhythm it aims to restore; demonstrating target engagement will require phase-resolved rather than single-timepoint measurement; and because both arms fail together, combined restoration of intracellular repair and extracellular clearance should outperform single-arm intervention.

Alzheimer’s disease↗

PubMed2026

A comparative evaluation of multiple enlarged perivascular space segmentation tools.

BACKGROUND: Enlarged perivascular spaces (ePVS) are a marker of cerebral small vessel disease, potentially reflecting reduced waste clearance. Because manual quantification is unfeasible in large datasets, we developed and evaluated an automated tool. METHODS: Detection Of Regions of Enlarged perivascular Spaces (DORES), a 3D nnU-Net-based deep learning algorithm was developed for ePVS segmentation using T1-weighted and fluid-attenuated inversion recovery magnetic resonance imaging (MRI). DORES was developed in two stages: an initial model trained on 35 manually segmented scans and a final model on 1460 pseudo-labeled sessions from the Vanderbilt Memory and Aging Project (VMAP). A subset of VMAP participants with 3 T brain MRI underwent whole-brain manual ePVS tracing (n = 35, 73 ± 9 years, 51% male) and visual rating (n = 388, 71 ± 8 years, 54% male) by a neuroradiologist. DORES was evaluated and compared against three other segmentation tools using Dice and F1 scores, absolute volume and element differences, correlation, and agreement. External validation used an Alzheimer's Disease Neuroimaging Initiative 3 subset with manual tracings (ADNI3, n = 18, 73 ± 9 years, 67% female). RESULTS: DORES achieved Dice scores of 0.61 ± 0.16 (white matter) and 0.72 ± 0.08 (basal ganglia) in VMAP, with strong correlations and agreement for ePVS count and volume. Performances modestly declined in ADNI3 across algorithms. Scanner-stratified analyses showed stronger correlations for Philips versus Siemens images in the basal ganglia, indicating scanner-dependent differences in measurement consistency. CONCLUSIONS: DORES provides a multimodal nnU-Net-based pipeline for ePVS segmentation in older adults. The model demonstrates robust within-cohort performance and reasonable external validity, though scanner-related effects limit application across sites.

Humans↗