Proteomic profiling of CSF reveals stage-specific changes in Amyotrophic lateral sclerosis patients
Skotte, N. H.; Cankar, N.; Qvist, F. L.; Frahm, A. S.; Pilely, K.; Svenstrup, K.; Kjaeldgaard, A.-L.; Garred, P.; Petersen, S. W.
Show abstract
Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease with a heterogeneous clinical presentation, complicating early diagnosis and therapeutic monitoring. To identify disease-specific biomarkers, we performed an unbiased cerebrospinal fluid (CSF) proteomic analysis in 87 ALS patients, 89 healthy controls, and 61 neurological controls using data-independent mass spectrometry. Across all quantified proteins, 399 were significantly dysregulated in ALS, including established neurodegeneration (NEFL, NEFM, UCHL1) and neuroinflammatory (CHIT1, CHI3L1, CHI3L2) markers. Correlation and pathway analyses uncovered dysregulation of immune, synaptic, and metabolic processes, with aberrant complement activation emerging as a hallmark. Complement proteins increased progressively with declining ALS Functional Rating Scale-Revised and longer disease duration, whereas early-stage markers (CLSTN3, CHAD, RELN) indicated pre-symptomatic neuronal and synaptic disruptions. Machine learning identified a minimal five-protein CSF panel (MB, ITLN1, YWHAG, FCGR3A, PGAM1) that accurately distinguished ALS patients from healthy controls, capturing disease-specific pathophysiology beyond general neurodegeneration. Our findings define a robust ALS-specific CSF proteomic signature, reveal prognostic protein candidates across disease stages, and provide a framework for diagnostic biomarker development, enabling earlier intervention and monitoring.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A Microglial Activity State Biomarker Panel Differentiates Ftd-Granulin And Ad From Control Cases 96%
- Network Analysis of the Cerebrospinal Fluid Proteome Reveals Shared and Unique Differences Between Sporadic and Familial Forms of Amyotrophic Lateral Sclerosis 95%
- Decoding distinctive features of plasma extracellular vesicles in amyotrophic lateral sclerosis 93%
Similar papers in this journal
- Image-based deep learning reveals the responses of human motor neurons to stress and ALS 94%
- miRNA biomarkers for diagnosis of ALS and FTD, developed by a nonlinear machine learning approach 94%
- Transcriptional Signatures of Synaptic Vesicle Genes Define Myotonic Dystrophy Type I Neurodegeneration 92%
Similar papers in this journal
- Skeletal muscle biomarkers of amyotrophic lateral sclerosis: a large-scale, multi-cohort proteomic study 96%
- Elevated plasma phosphorylated tau 181 in amyotrophic lateral sclerosis relates to lower motor neuron dysfunction 92%
- MS-driven metabolic alterations are recapitulated in iPSC-derived astrocytes 92%
Similar papers in this journal
- Similar neuronal imprint and absence of cross-seeded partner fibrils in α-synuclein aggregates from MSA and Parkinson's disease brains 94%
- Neither alpha-synuclein-preformed fibrils derived from patients with GBA1 mutations nor the host murine genotype significantly influence seeding efficacy in the mouse olfactory bulb. 93%
- SNCA triplication disrupts proteostasis and extracellular architecture prior to neurodegeneration in human midbrain organoids 93%
Similar papers in this journal
- Translocator protein is a marker of activated microglia in rodent models but not human neurodegenerative diseases 95%
- Expression of ALS-PFN1 impairs vesicular degradation in iPSC-derived microglia 94%
- Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.