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Network analysis of the CSF proteome characterises convergent pathways of cellular dysfunction in ALS

ABSTRACT: Amyotrophic lateral sclerosis is a clinical syndrome with complex biological determinants, but which in most cases is characterised by TDP-43 pathology. The identification in CSF of a protein signature of TDP-43 network dysfunction would have the potential to inform the identification of new biomarkers and therapeutic targets. We compared CSF proteomic data from patients with ALS (n=41), Parkinson's disease (n=19) and healthy control participants (n=20). Weighted correlation network analysis was used to identify modules within the CSF protein network and combined with gene ontology enrichment analysis to functionally annotate module proteins. Analysis of module eigenproteins and differential correlation analysis of the CSF protein network was used to compare ALS and Parkinson's disease protein co-correlation with healthy controls. In order to monitor temporal changes in the CSF proteome, we performed longitudinal analysis of the CSF proteome in a subset of ALS patients. Alterations in the co-correlation network in CSF samples identified a set of pathways known to be associated with TDP-43 dysfunction in the pathogenesis of ALS, with important implications for therapeutic targeting and biomarker development.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cerebrospinal Fluid

SUBMITTER: Philip Charles

LAB HEAD: Martin Turner

PROVIDER: PXD024219 | Pride | 2021-03-16

REPOSITORIES: Pride

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			Action	DRS
	20170503_HF233_MSQ984_AlexanderThompson_100317_PROG1.mgf	Mgf
	20170503_HF233_MSQ984_AlexanderThompson_100317_PROG2.mgf	Mgf
	20170503_HF233_MSQ984_AlexanderThompson_100317_PROG3.mgf	Mgf
	20170503_HF233_MSQ984_AlexanderThompson_100317_PROG4.mgf	Mgf
	F278397.mzid.gz	Mzid

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Project description:Unbiased proteomics of human cerebrospinal fluid (CSF) has been used successfully to identify biomarkers of Amyotrophic Lateral Sclerosis (ALS). However, high abundance proteins mask the presence of lower abundance proteins that may hold valuable diagnostic and prognostic use. Developments in mass spectrometry proteomic data acquisition methods therefore hold promise for improved protein depth and more sensitive biomarker discovery. In this study, mass spectrometry with library-free data-independent acquisition (DIA) was used to compare the CSF proteome of 40 people with ALS, 15 healthy controls and 8 people with mimicking conditions. Qthen quantified protein groups were subsequently correlated with clinical variables. Univariate analysis identified 7 proteins significantly upregulated in ALS vs healthy controls, and 9 with altered abundance in ALS vs mimicking conditions (FDR <0.1). Elevated Chitotriosidase 1 (CHIT1) was common to both comparisons and showed strong correlation with disease progression rate (Pearson r =0.41, FDR-adjusted p = 0.035), but no association with survival (Pearson correlation and Kaplan-Meier survival analysis). Ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1; upregulated in ALS vs healthy controls) showed a stronger correlation with disease progression rate (Pearson r = 0.53, FDR-adjusted p = 0.003) and significant association with survival in Kaplan Meier analysis (log rank p = 0.013) but no independent effect in proportional hazards models. Weighted correlation network analysis was then used to identify functionally relevant modules of proteins. One module, enriched for inflammatory functions, was strongly associated with age at disease onset (Pearson r = 0.58, FDR-adjusted p = 0.005) and survival (Hazard Ratio 1.78, FDR = 0.065), and a second module, enriched for endoplasmic reticulum proteins, negatively correlated with disease progression rate (r = -0.42, FDR-adjusted p =0.109). This study confirms that UCHL1 is strongly associated with disease progression and survival, and highlights potential of inflammatory and endoplasmic reticulum proteins to provide prognostic biomarker potential.

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Network analysis of the CSF proteome characterises convergent pathways of cellular dysfunction in ALS

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