The proteome of neurofilament-containing heteroaggregates in blood as source of biomarkers for neurodegeneration

PhD thesisThe lack of effective disease-modifying treatments and of means to achieve an early diagnosis strongly support the search for reliable neurochemical biomarkers in neurological conditions like Amyotrophic Lateral Sclerosis (ALS), a fatal neurodegenerative disorder. In ALS, the accumulation of protein aggregates containing neurofilaments (Nf), the building blocks of axons, leads to motor neuron death. Here we investigate the presence of neurofilaments (Nf) in protein aggregates in blood, studying a hallmark of neurodegeneration systemically. We explore the hypothesis that these circulating protein assemblies may function as biomarkers for neurodegeneration in accessible biofluids, which may have future application in clinical practice. In this thesis, I developed a protocol based on ultracentrifugation for the enrichment of protein aggregates from blood and confirmed their enrichment in Nf. Using Mass Spectrometry (MS)-based proteomics, I have obtained data on the protein composition and functional relevance of Nf-Containing Hetero-aggregates (NCHs) in plasma samples from ALS patients, healthy controls (HC) and from ALS brains. I have then applied quantitative proteomics analysis using a TMTcalibrator™ workflow on plasma samples from ALS patients and HC using brain tissue as an internal calibrator. Additional experiments were undertaken to evaluate NCHs resistance to proteases digestion and to characterise the specific conformation of these macromolecular structures by Transmission Electron Microscopy (TEM). Our fluid-brain tissue investigation using a multi-modal approach suggests that NCHs may represent a systemic readout of biochemical changes identified in neurodegenerative brain pathology and suggest that they may acquire altered biochemical properties like protease resistance. The changes in NCHs identified in ALS compared to HC are a promising biological substrate for the future development of next generation biomarkers of neurodegeneration.Medical Research Council, MRC Industry Case Studentship - MR/M015882/1

Plasma neurofilament light chain concentration in the inherited peripheral neuropathies.

OBJECTIVE: To perform a cross-sectional study to determine whether plasma neurofilament light chain (NfL) concentration is elevated in patients with Charcot-Marie-Tooth disease (CMT) and if it correlates with disease severity. METHODS: Blood samples were collected from 75 patients with CMT and 67 age-matched healthy controls over a 1-year period. Disease severity was measured using the Rasch modified CMT Examination and neuropathy scores. Plasma NfL concentration was measured using an in-house-developed Simoa assay. RESULTS: Plasma NfL concentration was significantly higher in patients with CMT (median 26.0 pg/mL) compared to healthy controls (median 14.6 pg/mL, p < 0.0001) and correlated with disease severity as measured using the Rasch modified CMT examination (r = 0.43, p < 0.0001) and neuropathy (r = 0.37, p = 0.044) scores. Concentrations were also significantly higher when subdividing patients by genetic subtype (CMT1A, SPTLC1, and GJB1) or into demyelinating or axonal forms compared to healthy controls. CONCLUSION: There are currently no validated blood biomarkers for peripheral neuropathy. The significantly raised plasma NfL concentration in patients with CMT and its correlation with disease severity suggest that plasma NfL holds promise as a biomarker of disease activity, not only for inherited neuropathies but for peripheral neuropathy in general.Wellcome Trust (110043/Z/15/Z); Medical Research Council (G0601943); National Institutes of Neurologic Diseases and Stroke and Office of Rare Diseases (U54NS065712); Swedish Research Council; European Research Council; Swedish State Support for Clinical Research. A.M.R. is funded by a Wellcome Trust Postdoctoral Fellowship for Clinicians (110043/Z/15/Z). M.M.R. is supported by the Medical Research Council (MRC), MRC Centre grant (G0601943), and the National Institutes of Neurologic Diseases and Stroke and Office of Rare Diseases (U54NS065712). The INC (U54NS065712) is a part of the NCATS Rare Diseases Clinical Research Network (RDCRN). RDCRN is an initiative of the Office of Rare Diseases Research (ORDR), NCATS, funded through a collaboration between NCATS and the NINDS

The Refinement of Genetic Predictors of Multiple Sclerosis

Medical Research Council [GRANT NUMBER G0801976], a research fellowship FISM-Fondazione Italiana Sclerosi Multipla-Cod.: [2010/B/5 to GD] and an MS Society of Great Britain and Northern Ireland Clinical Research Fellowship [GRANT NUMBER 940/10 to RD]

Tissue-enhanced plasma proteomic analysis for disease stratification in amyotrophic lateral sclerosis

Motor Neurone Disease Association (Malaspina/Apr13/817–791). Wellcome Trust support to a parallel study (Pathfinder Award, grant number 103208)

Author Correction: The potential of neurofilaments analysis using dry-blood and plasma spots

An amendment to this paper has been published and can be accessed via a link at the top of the paper

GWAS statistics (OR and risk allele frequencies) were used to simulate a population of 100,000 individuals under different models considering: only HLA-DRB1, HLA-DRB1 + MS associations known in 2011 and HLA-DRB1 + all currently known MS associations.

<p><i>Categories of risk were defined based on the 95%CI of risk of each individual (see methods). Green = reduced risk, blue = average risk, yellow = elevated risk, red = high risk.</i></p

Predictive performance of the wGRS assessed using receiver operating characteristic (ROC) curves when considering only HLA-DRB1, HLA-DRB1 + MS associations known in 2011 and HLA-DRB1 + all currently known MS associations.

<p><i>The wGRS threshold providing the best predictive performance is also shown (specificity and sensitivity within brackets).</i></p

Proportion of MS patients and HC in different risk categories and median wGRS with interquartile range (IQR) of MS and HC in each model (only HLA-DRB1, HLA-DRB1 + MS associations known in 2011 and HLA-DRB1 + all currently known MS associations).

<p>In brief, the genotype at MS associated loci was used to assign each individual to the categories of risk identified using the simulated population from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096578#pone-0096578-t001" target="_blank">table 1</a>. Furthermore, a weighted genetic risk (wGRS) was calculated by multiplying the number of risk alleles by the weight of each SNP and then taking the sum across all associations (see methods).</p

Boxplots of weighted genetic risk score (wGRS) in MS patients and HC considering only HLA-DRB1, HLA-DRB1 + MS associations known in 2011 and HLA-DRB1 + all currently known MS associations.

<p><i>The wGRS was calculated by multiplying the number of risk alleles by the weight of each SNP and then taking the sum across all associations (see methods). The whiskers extend to the most extreme data point which is no more than 1.5 times the IQR from the box.</i></p

Proportion of population and 95%CIs for each category of risk considering only HLA-DRB1, HLA-DRB1 + MS associations known in 2011 and HLA-DRB1 + all currently known MS associations.

<p>In brief, GWAS statistics (OR and risk allele frequencies) are used to simulate a population of 100,000 individuals. An overall genetic risk of MS is calculated for each individual and scaled by the mean risk profile. Categories of risk are defined based on the 95%CI of risk of each individual (see methods).</p