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Chertavian, C.

Publications and source records attributed to Chertavian, C..

2 recordsLinked to original sources

TRPML1 loss drives lysosomal calcium failure and astrocyte dysfunction across Alzheimer's Disease progression

Astrocytes are among the earliest cells to exhibit dysfunction in Alzheimers disease (AD), developing profound calcium signalling deficits before amyloid plaques have formed, yet the underlying mechanisms remain unknown. Lysosomal dysfunction is a hallmark of AD, but whether it initiates this early functional impairment or arises as a consequence of established pathology remains unresolved. Here, we find that astrocytic cytosolic calcium activity is suppressed prior to amyloid plaque deposition and is accompanied by reduced lysosomal acidification in vivo. Using a lysosome-targeted calcium indicator selectively expressed in astrocytes, we directly visualise lysosomal calcium dynamics in vivo and reveal a profound early loss of lysosomal calcium release, identifying lysosomal failure as an initiating event in astrocyte dysfunction in AD. Reduced expression of the lysosomal calcium channel TRPML1 provides the mechanistic basis for this deficit. Astrocyte-specific restoration of TRPML1 expression rescues lysosomal homeostasis and cytosolic calcium signalling and prevents astrocyte reactivity and morphological hypertrophy. Strikingly, early TRPML1 restoration prevents both the initial calcium hypoactivity observed before plaque formation and the later hyperactivity that characterises post-plaque disease, demonstrating that lysosomal calcium homeostasis stabilises astrocyte function across the disease trajectory. TRPML1 restoration also reduces amyloid plaque burden, indicating that astrocytic lysosomal competence directly shapes disease pathology. These findings identify lysosomal calcium failure as an early organelle-level mechanism linking amyloid stress to astrocyte dysfunction in AD, and position TRPML1-mediated lysosomal calcium signalling as a tractable target for limiting disease progression.

neuroscience↗

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure. Furthermore, we provide open resources to support future advances towards adoption of brain charts as standards for quantitative benchmarking of typical or atypical brain MRI scans.

neuroscience↗