Neurodegenerative diseases arise from interactions among pathogenic proteins, immune responses, and diverse environmental or age-related stressors that disrupt CNS homeostasis. CNS resident microglia detect self-derived danger signals through pattern recognition receptors, and their activation can promote clearance of aberrant proteins, including amyloid-β, tau, α-synuclein, and TAR DNA-binding protein 43. However, microglial activation may also drive maladaptive states that amplify neuroinflammation. Microglial transitions are further shaped by receptor-mediated signaling and antigen presentation pathways that integrate environmental cues with functional responses. Adaptive immune cells contribute additional layers of regulation, with CD8+ and CD4+ T cells exerting neuroprotective or neurotoxic effects depending on disease context, activation state, and antigen specificity. The identification of granzyme K–expressing CD8+ T cells in several neurodegenerative conditions highlights the growing recognition that distinct T cell subsets may have specialized roles in disease. Aging, repetitive head injury, and viral infection further alter microglial phenotypes, weaken barrier integrity, promote T cell recruitment, and prime the CNS for chronic inflammation. In this review, we synthesize current knowledge of innate and adaptive immune mechanisms in neurodegeneration, examine how external factors influence these responses, and consider how these insights may guide future therapeutic strategies.
Yvonne L. Latour, Dorian B. McGavern
Usage data is cumulative from April 2026 through May 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 2,390 | 0 |
| 581 | 0 | |
| Figure | 419 | 0 |
| Citation downloads | 76 | 0 |
| Totals | 3,466 | 0 |
| Total Views | 3,466 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.