Aging is the predominant risk factor for neurodegenerative disorders such as Alzheimer’s and Parkinson’s disease. However, not all neurons age at the same rate. Some neuronal populations degenerate earlier, whereas others remain relatively resilient over time. It remains unclear whether this selective vulnerability reflects differences in the biological age of individual neurons rather than their chronological age.
In a recent study published in Nature Aging, researchers applied molecular aging clocks to individual types of neurons to determine whether neurons within the same organism age at different rates. The study was conducted using the nematode Caenorhabditis elegans, which has a fully mapped nervous system comprising 302 neurons. The objectives were to identify neurons that are more susceptible to aging, examine links between biological aging and neurodegeneration, and explore potential protective interventions.
Neuron-specific RNA sequencing and in vivo imaging were performed in C. elegans from the late larval (L4) stage through adulthood. BitAge and Stochastic aging clocks were used to estimate biological age. Neuronal degeneration, behavioural outcomes, and gene expression features were determined, and the potential neuroprotective compounds were discovered through in silico drug screening and subsequently validated in vivo.
A total of six neuron types were selected for detailed analysis. Three were classified as biologically young (I2, OLL, PHC) and 3 as biologically old (ASI, ASJ, ASK). Neuronal degeneration from the L4 stage through day 7 of adulthood was systematically graded. Behavioral assays were used to assess functional consequences of degeneration, including pathogen avoidance (mediated by URY neurons) and salt-aversive learning (mediated by ASE neurons). Computational drug screening was used to identify compounds with the potential to slow neuronal aging.
Prediction of aging clocks showed substantial variation in the biological age among neurons of the same chronological age. BitAge estimated neuronal ages ranging from approximately 98 to 177 hours, nearly a twofold difference in biological aging. Similar trends were observed using the Stochastic aging clock, which showed a strong correlation with BitAge predictions (Pearson r = 0.65, P < 0.0001).
Neurons predicted to be biologically older exhibited earlier onset and greater severity of degeneration. By the L4 stage, more than 45% of the animals showed damage in ASI, ASJ, and ASK neurons, and by day 7 of adulthood, these neurons had fully degenerated. In contrast, neurons predicted to be biologically young showed minimal early damage and slower degeneration. Notably, neuronal degeneration was associated with functional impairment. Animals with degenerated URY neurons failed to avoid the pathogenic bacteria Serratia marcescens, and the degeneration of ASE neurons impaired salt-aversive learning. The neurons predicted to be the oldest were predominantly ciliated sensory neurons, particularly amphid neurons, whose cilia are directly exposed to the environment, rendering them especially vulnerable.
Transcriptomic analyses revealed that rapidly aging neurons showed higher expression of genes involved in protein synthesis and neuropeptide signaling. Pharmacological inhibition of translation significantly reduced neuronal degeneration. In silico drug screening identified syringic acid, a plant-derived metabolite, and vanoxerine, a piperazine derivative, both of which were previously shown to slow neuronal degeneration in vivo.
Overall, this study demonstrates substantial heterogeneity in biological aging among neurons within the same organism and shows that these differences predict neuronal degeneration and functional decline. The heightened vulnerability of environmentally exposed, ciliated sensory neurons suggests that increased metabolic demand and signaling activity may accelerate neuronal aging. By integrating molecular aging clocks with functional assays and pharmacological screening, the researchers identified candidate compounds capable of mitigating neuronal degeneration.
These findings provide a conceptual framework for understanding the selective vulnerability of neurons and establish biological aging as a central driver of neurodegeneration. This strategy offers promising directions for future efforts aimed at slowing neuronal aging and reducing the risk of neurodegenerative diseases.
Reference: Gallrein C, Meyer DH, Woitzat Y, et al. Aging clocks delineate neuron types vulnerable or resilient to neurodegeneration and identify neuroprotective interventions. Nat Aging. 2026. doi:10.1038/s43587-026-01067-5
