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Replicative senescence dictates the emergence of disease-associated microglia and contributes to Aβ pathology
The sustained proliferation of microglia is a key hallmark of Alzheimer’s disease (AD), accelerating its progression. Here, we sought to understand the long-term impact of the early and prolonged microglial proliferation observed in AD, hypothesising that extensive and repeated cycling would engender a distinct transcriptional and phenotypic trajectory. We found that the early and sustained microglial proliferation seen in an AD-like model promotes replicative senescence, characterised by increased bgal activity, a senescence-associated transcriptional signature and telomere shortening, correlating with the appearance of disease-associated microglia (DAM) and senescent microglial profiles in human post-mortem AD cases. Prevention of early microglial proliferation hindered the development of senescence and DAM, impairing the accumulation of Aβ, as well as associated neuritic and synaptic damage. Overall, our results support that excessive microglial proliferation leads to the generation of senescent DAM, which contribute to early Abpathology in AD.
Spatiotemporal dynamics of microglia across the human lifespan
Microglia, the brain’s resident macrophages, shape neural development and wiring, and are key neuroimmune hubs in the pathological signature of neurodevelopmental disorders. In the human brain, microglial development has not been carefully examined yet, and most of our knowledge derives from rodents. We established an extensive collection of 97 post-mortem tissues enabling quantitative, sex-matched, detailed analysis of microglia across the human lifespan. We identify the dynamics of these cells in the human telencephalon, describing novel waves in microglial density across gestation and infancy, controlled by a balance of proliferation and apoptosis, which track key neurodevelopmental milestones. These profound changes in microglia are also observed in bulk RNAseq and single-cell RNAseq datasets. This study provides insight and detail into the spatiotemporal dynamics of microglia across the human lifespan. Our findings serve as a solid foundation for elucidating how microglia contribute to shaping neurodevelopment in humans.
The Effects of Xenon Gas Inhalation on Neuropathology in a Placental-Induced Brain Injury Model in Neonates: A Pilot Study.
Improved obstetric and neonatal care have reduced the prevalence of severe hypoxic-ischemic-encephalopathy (HIE), however 1-3/1000 newborns in the developed world(1) suffer death or neurodevelopmental disability from HIE. The normal development of the brain during gestation can also be altered by placental reprogramming under oxidative stress. Under these conditions, the placenta releases DNA damaging molecules, bone morphogenic proteins, microRNAs, and glutamate(2). At present, one is unable to diagnose or treat these factors.
Microglial Dynamics across the Human Lifespan
Microglial cells appear in the brain rudiment at about 4 postconceptional weeks (pcw) (Carnegie stage (CS) 10) and are thought to derive from yolk-sac progenitors similarly to the rodent. By 22 pcw, colonisation of the brain is speculated to be complete. In the adult, these cells turnover at a slow rate (reported between 0.08% and 2% at any one time). Microglial spatiotemporal dynamics have not been carefully examined in the human developing brain particularly in the context of co-occurring developmental processes. It is also unclear when their regional heterogeneity is first established nor how their developmental dynamics contribute to the adult pool. We also do not have a baseline characterisation of microglial cells in old age in the absence of overt pathology. With the appropriate ethical approval, we have obtained frontal and temporal tissues from 10 participating centres in the UK and Europe to study microglial cell dynamics across the human lifespan. 145 individuals aged between the 4th pcw and 90 years are being studied. Transcriptomic data available from the early and mid-fetal periods made it possible to examine the spatiotemporal establishment of the transcriptional signature of microglia in the human. In this presentation we will report on the preliminary findings of our study and how these inform our understanding of microglial function in the developing human brain.
Microglial contribution to the pathology of neurodevelopmental disorders in humans
AbstractMicroglia are the brain’s resident macrophages, which guide various developmental processes crucial for brain maturation, activity, and plasticity. Microglial progenitors enter the telencephalic wall by the 4th postconceptional week and colonise the fetal brain in a manner that spatiotemporally tracks key neurodevelopmental processes in humans. However, much of what we know about how microglia shape neurodevelopment comes from rodent studies. Multiple differences exist between human and rodent microglia warranting further focus on the human condition, particularly as microglia are emerging as critically involved in the pathological signature of various cognitive and neurodevelopmental disorders. In this article, we review the evidence supporting microglial involvement in basic neurodevelopmental processes by focusing on the human species. We next concur on the neuropathological evidence demonstrating whether and how microglia contribute to the aetiology of two neurodevelopmental disorders: autism spectrum conditions and schizophrenia. Next, we highlight how recent technologies have revolutionised our understanding of microglial biology with a focus on how these tools can help us elucidate at unprecedented resolution the links between microglia and neurodevelopmental disorders. We conclude by reviewing which current treatment approaches have shown most promise towards targeting microglia in neurodevelopmental disorders and suggest novel avenues for future consideration.
Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics.
Mapping cellular organization in the developing brain presents significant challenges due to the multidimensional nature of the data, characterized by complex spatial patterns that are difficult to interpret without high-throughput tools. Here, we present DeepCellMap, a deep-learning-assisted tool that integrates multi-scale image processing with advanced spatial and clustering statistics. This pipeline is designed to map microglial organization during normal and pathological brain development and has the potential to be adapted to any cell type. Using DeepCellMap, we capture the morphological diversity of microglia, identify strong coupling between proliferative and phagocytic phenotypes, and show that distinct spatial clusters rarely overlap as human brain development progresses. Additionally, we uncover an association between microglia and blood vessels in fetal brains exposed to maternal SARS-CoV-2. These findings offer insights into whether various microglial phenotypes form networks in the developing brain to occupy space, and in conditions involving haemorrhages, whether microglia respond to, or influence changes in blood vessel integrity. DeepCellMap is available as an open-source software and is a powerful tool for extracting spatial statistics and analyzing cellular organization in large tissue sections, accommodating various imaging modalities. This platform opens new avenues for studying brain development and related pathologies.
The mouse motor system contains multiple premotor areas and partially follows human organizational principles.
While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher-order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we show that axonal tracer, functional connectivity, myelin mapping, gene expression, and optogenetics data contradict this notion. Our analyses reveal three premotor areas in the mouse, anterior-lateral motor cortex (ALM), anterior-lateral M2 (aM2), and posterior-medial M2 (pM2), with distinct structural, functional, and behavioral properties. By using the same techniques across mice and humans, we show that ALM has strikingly similar functional and microstructural properties to human anterior ventral premotor areas and that aM2 and pM2 amalgamate properties of human pre-SMA and cingulate cortex. These results provide evidence for the existence of multiple premotor areas in the mouse and chart a comparative map between the motor systems of humans and mice.
Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia.
Cervical dystonia is a non-degenerative movement disorder characterized by dysfunction of both motor and sensory cortico-basal ganglia networks. Deep brain stimulation targeted to the internal pallidum is an established treatment, but its specific mechanisms remain elusive, and response to therapy is highly variable. Modulation of key dysfunctional networks via axonal connections is likely important. Fifteen patients underwent preoperative diffusion-MRI acquisitions and then progressed to bilateral deep brain stimulation targeting the posterior internal pallidum. Severity of disease was assessed preoperatively and later at follow-up. Scans were used to generate tractography-derived connectivity estimates between the bilateral regions of stimulation and relevant structures. Connectivity to the putamen correlated with clinical improvement, and a series of cortical connectivity-based putaminal parcellations identified the primary motor putamen as the key node (r = 0.70, P = 0.004). A regression model with this connectivity and electrode coordinates explained 68% of the variance in outcomes (r = 0.83, P = 0.001), with both as significant explanatory variables. We conclude that modulation of the primary motor putamen-posterior internal pallidum limb of the cortico-basal ganglia loop is characteristic of successful deep brain stimulation treatment of cervical dystonia. Preoperative diffusion imaging contains additional information that predicts outcomes, implying utility for patient selection and/or individualized targeting.