Role of Basal Forebrain Neurons in Adrenomyeloneuropathy in Mice and Humans.

OBJECTIVE: X-linked adrenoleukodystrophy is caused by mutations in the peroxisomal half-transporter ABCD1. The most common manifestation is adrenomyeloneuropathy, a hereditary spastic paraplegia of adulthood. The present study set out to understand the role of neuronal ABCD1 in mice and humans with adrenomyeloneuropathy. METHODS: Neuronal expression of ABCD1 during development was assessed in mice and humans. ABCD1-deficient mice and human brain tissues were examined for corresponding pathology. Next, we silenced ABCD1 in cholinergic Sh-sy5y neurons to investigate its impact on neuronal function. Finally, we tested adeno-associated virus vector-mediated ABCD1 delivery to the brain in mice with adrenomyeloneuropathy. RESULTS: ABCD1 is highly expressed in neurons located in the periaqueductal gray matter, basal forebrain and hypothalamus. In ABCD1-deficient mice (Abcd1-/y), these structures showed mild accumulations of α-synuclein. Similarly, healthy human controls had high expression of ABCD1 in deep gray nuclei, whereas X-ALD patients showed increased levels of phosphorylated tau, gliosis, and complement activation in those same regions, albeit not to the degree seen in neurodegenerative tauopathies. Silencing ABCD1 in Sh-sy5y neurons impaired expression of functional proteins and decreased acetylcholine levels, similar to observations in plasma of Abcd1-/y mice. Notably, hind limb clasping in Abcd1-/y mice was corrected through transduction of ABCD1 in basal forebrain neurons following intracerebroventricular gene delivery. INTERPRETATION: Our study suggests that the basal forebrain-cortical cholinergic pathway may contribute to dysfunction in adrenomyeloneuropathy. Rescuing peroxisomal transport activity in basal forebrain neurons and supporting glial cells might represent a viable therapeutic strategy. ANN NEUROL 2024;95:442-458.

Peroxisome Metabolism Contributes to PIEZO2-Mediated Mechanical Allodynia.

Mutations in the peroxisomal half-transporter ABCD1 cause X-linked adrenoleukodystrophy, resulting in elevated very long-chain fatty acids (VLCFA), progressive neurodegeneration and an associated pain syndrome that is poorly understood. In the nervous system of mice, we found ABCD1 expression to be highest in dorsal root ganglia (DRG), with satellite glial cells (SGCs) displaying higher expression than neurons. We subsequently examined sensory behavior and DRG pathophysiology in mice deficient in ABCD1 compared to wild-type mice. Beginning at 8 months of age, Abcd1-/y mice developed persistent mechanical allodynia. DRG had a greater number of IB4-positive nociceptive neurons expressing PIEZO2, the mechanosensitive ion channel. Blocking PIEZO2 partially rescued the mechanical allodynia. Beyond affecting neurons, ABCD1 deficiency impacted SGCs, as demonstrated by high levels of VLCFA, increased glial fibrillary acidic protein (GFAP), as well as genes disrupting neuron-SGC connectivity. These findings suggest that lack of the peroxisomal half-transporter ABCD1 leads to PIEZO2-mediated mechanical allodynia as well as SGC dysfunction. Given the known supportive role of SGCs to neurons, this elucidates a novel mechanism underlying pain in X-linked adrenoleukodystrophy.

Evidence-Based Pediatric Outcome Predictors to Guide the Allocation of Critical Care Resources in a Mass Casualty Event.

OBJECTIVE: ICU resources may be overwhelmed by a mass casualty event, triggering a conversion to Crisis Standards of Care in which critical care support is diverted away from patients least likely to benefit, with the goal of improving population survival. We aimed to devise a Crisis Standards of Care triage allocation scheme specifically for children. DESIGN: A triage scheme is proposed in which patients would be divided into those requiring mechanical ventilation at PICU presentation and those not, and then each group would be evaluated for probability of death and for predicted duration of resource consumption, specifically, duration of PICU length of stay and mechanical ventilation. Children will be excluded from PICU admission if their mortality or resource utilization is predicted to exceed predetermined levels ("high risk"), or if they have a low likelihood of requiring ICU support ("low risk"). Children entered into the Virtual PICU Performance Systems database were employed to develop prediction equations to assign children to the exclusion categories using logistic and linear regression. Machine Learning provided an alternative strategy to develop a triage scheme independent from this process. SETTING: One hundred ten American PICUs SUBJECTS: : One hundred fifty thousand records from the Virtual PICU database. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The prediction equations for probability of death had an area under the receiver operating characteristic curve more than 0.87. The prediction equation for belonging to the low-risk category had lower discrimination. R for the prediction equations for PICU length of stay and days of mechanical ventilation ranged from 0.10 to 0.18. Machine learning recommended initially dividing children into those mechanically ventilated versus those not and had strong predictive power for mortality, thus independently verifying the triage sequence and broadly verifying the algorithm. CONCLUSION: An evidence-based predictive tool for children is presented to guide resource allocation during Crisis Standards of Care, potentially improving population outcomes by selecting patients likely to benefit from short-duration ICU interventions.