Abstract
PURPOSE: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. Progressive loss of motor neuron function and disruption of the blood-brain barrier are key features of ALS. Under the influence of chemokines, peripheral immune cells migrate into the central nervous system, thereby affecting the neuronal microenvironment. The aim of this study is to classify ALS based on the immune characteristics of peripheral blood in patients with the disease, and to construct prognostic models. PATIENTS AND METHODS: A total of 397 ALS patients and 645 healthy controls (GSE112676 and GSE112680) were included. ALS chemotactic subtypes were constructed based on differentially expressed genes of chemokine and chemokine receptors (CCRs). The Cibersort algorithm was used to investigate the abundance of immune cells in peripheral blood. Univariate Cox regression analysis was performed to screen for CCRs genes, clinical characteristics, and immune cells associated with prognosis. Prognostic models were constructed based on these variables. Finally, external validation was conducted using samples from ALS patients diagnosed at the First Affiliated Hospital of Sun Yat-sen University. RESULTS: There were significant differences in the abundance of peripheral immune cells between ALS patients and healthy controls. 17 CCRs genes were identified as differentially expressed. CCL23, CCR8, CXCR4, site of onset, age of onset, and "CD4 naive T cells" were demonstrated to be significantly correlated with survival time. Two chemotactic subtypes were established. Eight prognostic models could distinguish between high-risk and low-risk ALS patients. At year five, the areas under the receiver operating characteristic curves for the PlsRcox, Coxboost, and Xgboost algorithms were 0.747, 0.733, and 0.728, respectively. External test sets successfully validated these results. CONCLUSION: ALS patients exhibit peripheral immune abnormalities. Peripheral immune status could be used to distinguish ALS subtypes and construct prognostic models. Understanding peripheral immune changes in ALS patients may inform potential immunotherapies.