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Updated: Jul 4, 2026

Quantitative 3D In Silico Modeling (q3DISM) of Cerebral Amyloid-beta Phagocytosis in Rodent Models of Alzheimer's Disease
Published on: December 26, 2016
Microglial checkpoint collapse in Alzheimer's disease: a tri-axial framework for biomarker-informed neuroimmune
Jiahao Zhang1, Ning Yang1, Peibin Zou1
1Department of Neurology, Institute for Cerebrovascular and Neuroregeneration Research (ICNR), Louisiana State University Health Sciences Center, 1501 Kings Highway, Shreveport, LA, 71103, USA.
Background:
Anti-amyloid antibodies have validated amyloid-β (Aβ) as a disease-relevant target in Alzheimer's disease (AD), but their modest clinical effect, efficacy largely restricted to early disease, and amyloid-related imaging abnormalities (ARIA) indicate that Aβ removal alone does not resolve the glial, lipid, and inflammatory programmes that sustain neurodegeneration. Microglia sit at the centre of this therapeutic gap. Single-nucleus and spatial profiling has resolved several AD-associated microglial states, yet state labels remain descriptive and do not explain why adaptive engagement becomes maladaptive.
Main Body:
We frame AD-relevant microglial dysfunction as checkpoint collapse: progressive failure of regulatory nodes that coordinate lipid sensing, lysosomal competence, neuronal restraint, and inflammatory threshold control. The central nodes are TREM2-mediated lipid and apolipoprotein sensing, progranulin-associated lysosomal regulation, CX3CR1-dependent neuron-microglia restraint, and CD33/Siglec-3 inhibitory tone. When these controls destabilise, downstream pathology can be organised around three coupled effector axes: a lipid axis centred on APOE-biased cholesterol trafficking, ACSL1/DGAT2-driven lipid-droplet accumulation, and impaired lysosomal flux; an iron/ferroptosis axis involving labile iron, phospholipid peroxidation, and insufficient GPX4/FSP1 defences; and an inflammation/complement axis linking NLRP3 activation, type-I interferon signalling, and C1q/C3-dependent synaptic engulfment to tau pathology and synapse loss. White-matter injury, astrocyte-microglia crosstalk, and cGAS-STING-linked senescence are integrated as cross-axis amplifiers.
Conclusions:
This framework is proposed as a hypothesis-generating scaffold for biomarker-informed translational studies, rather than as a validated clinical stratification system. It may help organise stage-aware therapeutic hypotheses, including regulatory-node preservation in early disease, lipid-handling restoration and ferroptosis control at intermediate stages, and complement- or senescence-directed modulation in later disease. Current glial, iron, inflammatory, and imaging biomarkers remain insufficiently specific to assign individual patients reliably to discrete pathological axes in clinical practice.
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