Caracterización multimodal de biomarcadores del espectro ELA/DFT: un análisis de datos clínicos del mundo real

Diagnosis and prognosis of the amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD) spectrum remain largely dependent on clinical assessments due to a lack of established fluid biomarkers. While neurofilaments and the cerebrospinal fluid (CSF) phosphorylated-tau/total-tau ratio (pTau:tTau) have been studied, their limitations, including their lack of clinical implementation and low specificity, necessitate multimodal approaches. This study aimed to characterize the biological features of the ALS/FTD spectrum through integration of clinically available parameters. We conducted a retrospective, single-center, cross-sectional study analyzing routinely collected clinical, neuroimaging, CSF, and serum data from 229 samples, including 45 from patients with ALS, 26 from patients with FTD, 158 from patients with other neurodegenerative diseases, and 29 from cognitively healthy controls. We implemented propensity score-weighted comparisons, an F1 score-based optimal cut-point determination for the pTau:tTau ratio, and a regularized XGBoost-based multimodal feature modeling approach. The biomarker and model performance was evaluated by the area under the precision-recall curve (AUC-PR). Feature importance analysis identified characteristic indicators of the ALS/FTD spectrum. Consistent with the prior literature, the pTau:tTau ratio was significantly reduced in ALS/FTD, but the classification performance was modest (AUC-PR 0.32). A multimodal model integrating clinical, biofluid, and neuroimaging features achieved a notably better performance (AUC-PR 0.75). Feature importance analysis revealed an ALS/FTD signature beyond the pTau:tTau ratio characterized by higher global cognition, younger age, an altered Aβ42/pTau ratio, and immunoglobulin changes (CSF IgG:IgA, serum IgG). Integration of clinical routine data centered on tau, amyloid, and immunological pathophysiology as well as temporal disease dynamics provide a contextualized biological characterization of the ALS/FTD spectrum. This approach offers a foundation for hypothesis generation regarding ALS/FTD pathophysiology and biomarker-supported diagnosis.