Dataset Information

Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis

ABSTRACT:

Molecular networks in neurological diseases are complex. Despite this fact, contemporary biomarkers are in most cases interpreted in isolation, leading to a significant loss of information and power. We present an analytical approach to scrutinize and combine information from biomarkers originating from multiple sources with the aim of discovering a condensed set of biomarkers that in combination could distinguish the progressive degenerative phenotype of multiple sclerosis (SPMS) from the relapsing-remitting phenotype (RRMS).

METHODS: Clinical and magnetic resonance imaging (MRI) data were integrated with data from protein and metabolite measurements of cerebrospinal fluid, and a method was developed to sift through all the variables to establish a small set of highly informative measurements. This prospective study included 16 SPMS patients, 30 RRMS patients and 10 controls. Protein concentrations were quantitated with multiplexed fluorescent bead-based immunoassays and ELISA. The metabolome was recorded using liquid chromatography-mass spectrometry. Clinical follow-up data of the SPMS patients were used to assess disease progression and development of disability.

RESULTS: Eleven variables were in combination able to distinguish SPMS from RRMS patients with high confidence superior to any single measurement. The identified variables consisted of three MRI variables: the size of the spinal cord and the third ventricle and the total number of T1 hypointense lesions; six proteins: galectin-9, monocyte chemoattractant protein-1 (MCP-1), transforming growth factor alpha (TGF-α), tumor necrosis factor alpha (TNF-α), soluble CD40L (sCD40L) and platelet-derived growth factor AA (PDGF-AA); and two metabolites: 20β-dihydrocortisol (20β-DHF) and indolepyruvate.

The proteins myelin basic protein (MBP) and macrophage-derived chemokine (MDC), as well as the metabolites 20β-DHF and 5,6-dihydroxyprostaglandin F1a (5,6-DH-PGF1), were identified as potential biomarkers of disability progression.

CONCLUSION: Our study demonstrates, in a limited but well-defined and data-rich cohort, the importance and value of combining multiple biomarkers to aid diagnostics and track disease progression.

Cohort 2 assays are reported in the current study MTBLS558.

Cohort 1 assays are reported in MTBLS1464.

OTHER RELATED OMICS DATASETS IN: PXD018322PXD006154

INSTRUMENT(S): Exactive (Thermo Scientific)

SUBMITTER: Stephanie Herman

PROVIDER: MTBLS558 | MetaboLights | 2018-08-13

REPOSITORIES: MetaboLights

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Publications

Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis.

Herman Stephanie S Khoonsari Payam Emami PE Tolf Andreas A Steinmetz Julia J Zetterberg Henrik H Åkerfeldt Torbjörn T Jakobsson Per-Johan PJ Larsson Anders A Spjuth Ola O Burman Joachim J Kultima Kim K

Theranostics 20180807 16

PMID: 30214633

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Project description:Human T-lymphotropic virus type 1 (HTLV-1)-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is an inflammatory neurodegenerative disease that affects motor, urinary, intestinal, and sensory functions. Typically, HAM/TSP is slowly progressive, but it may vary from limited motor disability after decades (very slow progression) to loss of motor function in a few years from disease onset (rapid). In this study, we aimed to identify prognostic biomarkers for HAM/TSP to support patient management. Thus, proteomic analysis of the cerebrospinal fluid (CSF) was performed with samples from HTLV-1 asymptomatic carriers (AC) (n=13) and HAM/TSP patients (n=21) with rapid, typical, and very slow progression using quantitative label-free liquid chromatography/tandem mass spectrometry. Enrichment analyses were also carried out to identify key biological processes associated with distinct neurological conditions in HTLV-1 infection. Candidate biomarkers were validated by ELISA in paired CSF and serum samples, and samples from HTLV-1-seronegative individuals (n=9) were used as controls. CSF analysis identified 602 proteins. Leukocyte/cell activation, immune response processes and neurodegeneration pathways were enriched in rapid progressors. Conversely, HTLV-1 AC and HAM/TSP patients with typical and very slow progression had enriched processes for nervous system development. Differential expression analysis showed that soluble vascular cell adhesion molecule 1 (sVCAM-1), chitotriosidase 1 (CHIT1), and cathepsin C (CTSC) were upregulated in HAM/TSP. However, only CHIT1 was significantly elevated after validation, particularly in HAM/TSP rapid progressors. In contrast, none of these biomarkers were altered in serum. Additionally, CSF CHIT1 levels in HAM/TSP patients positively correlated with the speed of HAM/TSP progression, defined as points in the IPEC-2 HAM/TSP disability scale per year of disease, and with CSF levels of phosphorylated neurofilament heavy chain, neopterin, CXCL5, CXCL10, and CXCL11. In conclusion, higher CSF levels of CHIT1 were associated with HAM/TSP rapid progression and correlated with other biomarkers of neuroinflammation and neurodegeneration. Therefore, we propose CHIT1 as a surrogate CSF biomarker to identify HAM/TSP patients with a worse prognosis.

Dataset Information

Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis

Publications

Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis.

Similar Datasets

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