Cerebrospinal Fluid Biomarkers Link Toxic Astrogliosis and - - PowerPoint PPT Presentation

Cerebrospinal Fluid Biomarkers Link Toxic Astrogliosis and Microglial Activation to Multiple Sclerosis Severity

Ruturaj R. Masvekar, PhD Neuroimmunological Diseases Section (NDS) National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health (NIH)

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The efficacy of immunomodulatory treatments in MS decreases with age and disease evolution

Front Neurol. 2017; 8:577.

2 Age (years)

Alternative intrathecal processes underlying disability progression during late stages of MS

• Mitochondrial dysfunction, ER stress, hypoxia etc.
• Aberrant microglial and astroglial activation
• Degeneration of oligodendrocytes
• Axonal damage and neuronal apoptosis

Currently we lack the biomarkers that could measure these CNS cell-specific intrathecal processes in living subjects

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Objectives

• 1. Identify and validate CSF biomarkers reflective of CNS cell-specific

intrathecal processes

• 2. Assemble related biomarkers into clusters to decrease

dimensionality and to better understand biology behind them

• 3. Investigate whether such CNS cell type-enriched clusters differ in

MS patients during disease evolution

• 4. Investigate whether these clusters correlate with clinical measures
• f disability, CNS tissue destruction and MS severity

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Identification of CNS cell type-enriched biomarkers

Primary Human Neurons (ScienCell) Primary Human Astrocytes (ScienCell) Oligodendrocytes differentiated from hPSCs Human Microglia Cell Line (CHME5) Human Brain Endothelial Cell Line (HCMEC/D3) 24 hours cell-culture supernatants

Slow Off-rate Modified DNA Aptamers assay (SOMAscan; measuring 1,302 proteins) Cell type-enriched biomarker: absolute release of this protein by a specific cell type was at least 5-fold higher than the release by any other cell types 40 neuron-, 73 astrocyte-, 81 oligodendrocyte-, 18 microglia-, and 38 endothelial cell type-enriched biomarkers

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Identification of CNS cell type-enriched biomarker clusters

CNS cell type-enriched biomarkers Patients’ CSF SOMAscan (n = 431; HD = 42, NIND = 57, CIS = 20, RR-MS = 127, SP-MS = 72 and PP-MS = 113) Variable cluster analysis CNS cell type-enriched biomarker clusters 7 neuron-, 20 astrocyte-, 19 oligodendrocyte-, 7 microglia-, and 11 endothelial cell type-enriched biomarker clusters Cluster score (principal component score)

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• Proteins that are secreted together by identical CNS cell types under identical

physiological or pathological conditions will have strong correlations in the CSF samples collected from diverse group of individuals

Analysis of differences in cluster scores across disease diagnostic subgroups

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All Patients (n = 431) Training Cohort (n = 217) Validation Cohort (n = 214) Age-adjusted cluster scores compared among disease diagnostic subgroups Statistically significant differences (ANOVA; p < 0.05) Only statistically significant differences assessed in independent validation cohort

Astrocyte cluster 8 and microglia cluster 2 significantly elevated in all MS subgroups

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Astrocyte Cluster 8

MMP7 Matrix Metalloproteinase 7 SERPINA3 Serpin Family A Member 3 GZMA Granzyme A CLIC1 Chloride Intracellular Channel Protein 1

Microglia Cluster 2

DSG2 Desmoglein 2 TNFRSF25 Tumor Necrosis Factor Receptor Superfamily Member 25 Age-Adjusted Cluster Score

Validation Cohort

Astrocyte Cluster 8 Microglia Cluster 2

Selected clinical measures of disability, CNS tissue destruction and MS severity

• Disability:
• EDSS: Expanded Disability Status Scale (Discrete, 0-10)
• CombiWISE: Combinatorial Weight-Adjusted Disability Scale

(Continuous 0-100; Front Neurol. 2016; 7:131)

• CNS tissue destruction
• COMRIS-CTD: Composite MRI scale of CNS tissue destruction

(Mult Scler Relat Disord. 2015; 4(6):526-35)

• MS severity
• MSSS: Multiple Sclerosis Severity Score (EDSS-based)
• ARMSS: Age Related Multiple Sclerosis Severity (EDSS-based)
• MS-DSS: Multiple Sclerosis Disease Severity Scale (CombiWISE-based)

(Developed using machine-learning, can predict future rates of disability progression; Front Neurol. 2017; 8:598)

• CombiWISE, COMRIS-CTD and MS-DSS available free at: https://bielekovalab.shinyapps.io/msdss/

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Courtesy of Multiple Sclerosis Association of America

MS Severity: how fast disability progresses

Correlation analysis between cluster scores and selected clinical measures

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Only MS Patients (n = 312) Training Cohort (n = 160) Validation Cohort (n = 152) Analyze correlations between age-adjusted cluster scores and selected clinical measures Statistically significant correlations (Spearman correlations; p < 0.01) Only statistically significant correlations assessed in independent validation cohort

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Astrocyte cluster 8 and microglial cluster 2 significantly correlated with selected clinical measures

Disability CNS tissue destruction MS severity

Age-Adjusted Cluster Score

Validation Cohort

CombiWISE COMRIS-CTD MS-DSS CombiWISE COMRIS-CTD MS-DSS

Age-Adjusted Cluster Score Age-Adjusted Cluster Score r = 0.26 p = 0.0002 r = 0.36 p < 0.0001 r = 0.19 p = 0.0082 r = 0.27 p = 0.0002 r = 0.36 p < 0.0001 r = 0.28 p = 0.0001

Astrocyte Cluster 8

MMP7 Matrix Metalloproteinase 7 SERPINA3 Serpin Family A Member 3 GZMA Granzyme A CLIC1 Chloride Intracellular Channel Protein 1

Microglia Cluster 2

DSG2 Desmoglein 2 TNFRSF25 Tumor Necrosis Factor Receptor Superfamily Member 25

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• Immunity. 2017; 46(6):957-967.
• Nature. 2017; 541(7638):481-487.

Abnormally activated microglia induce toxic (A1) astrocytes & both are associated with MS lesions

Conclusions & Future Directions

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Abnormally Activated Microglia Quiescent (Resting) Astrocytes Toxic (A1) Astrocytes Pro-Inflammatory Cytokines

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Disability, CNS Tissue Destruction and MS Severity Drug Library Screening

STOP STOP

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Acknowledgements

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Neuroimmunological Diseases Section (NDS)

Chief: Bibi Bielekova Lab: Chris Barbour Paav Hannikainen Kayla Jackson Peter Kosa Ruturaj Masvekar Linh Pham Jon Phillips Elena Romm Mihael Varosanec Clinical: Tiffany Hauser Mary Sandford Alison Wichman Michelle Woodland Special thanks to NDS patients and their families https://www.niaid.nih.gov/research/bibi-bielekova-md

Questions

• Poster: P281; Friday, March 1, 2019; 11:15 AM – 1:00 PM
• Contacts:
• Ruturaj R. Masvekar: ruturaj.masvekar@nih.gov
• Bibi Bielekova: bibi.bielekova@nih.gov
• Article:

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