Novel diagnostic cerebrospinal fluid biomarkers for pathologic subtypes of frontotemporal dementia identified by proteomics

Introduction: Reliable cerebrospinal fluid (CSF) biomarkers enabling identification of frontotemporal dementia (FTD) and its pathologic subtypes are lacking. Methods: Unbiased high-resolution mass spectrometry-based proteomics was applied on CSF of FTD patients with TAR DNA-binding protein 43 (TDP-43, FTD-TDP, n = 12) or tau pathology (FTD-tau, n = 8), and individuals with subjective memory complaints (SMC, n = 10). Validation was performed by applying enzyme-linked immunosorbent assay (ELISA) or enzymatic assays, when available, in a larger cohort (FTLD-TDP, n = 21, FTLD-tau, n = 10, SMC, n = 23) and in Alzheimer's disease (n = 20), dementia with Lewy bodies (DLB, n = 20), and vascular dementia (VaD, n = 18). Results: Of 1914 identified CSF proteins, 56 proteins were differentially regulated (fold change >1.2, P <.05) between the different patient groups: either between the two pathologic subtypes (10 proteins), or between at least one of these FTD subtypes and SMC (47 proteins). We confirmed the differential expression of YKL-40 by ELISA in a partly independent cohort. Furthermore, enzyme activity of catalase was decreased in FTD subtypes compared with SMC. Further validation in a larger cohort showed that the level of YKL-40 was twofold increased in both FTD pathologic subtypes compared with SMC and that the levels in FTLD-tau were higher compared to Alzheimer's dementia (AD), DLB, and VaD patients. Clinical validation furthermore showed that the catalase enzyme activity was decreased in the FTD subtypes compared to SMC, AD and DLB. Discussion: We identified promising CSF biomarkers for both FTD differential diagnosis and pathologic subtyping. YKL-40 and catalase enzyme activity should be validated further in similar pathology defined patient cohorts for their use for FTD diagnosis or treatment development

Identification of biomarkers for diagnosis and progression of MS by MALDI-TOF mass spectrometry

Introduction: Body fluid biomarkers for clinical subtyping and monitoring of disease progression are of considerable interest in multiple sclerosis (MS). Proteomics tools are optimal for the unbiased simultaneous detection of large series of peptides and proteins. Objectives: To identify novel candidate biomarkers discriminating patients with MS from patients with other neurological diseases (OND), and for subtyping of relapsing–remitting (RR), secondary progressive (SP) and primary progressive (PP) MS patients using a high-throughput MALDI-TOF-based mass spectrometry method. Methods: Paired cerebrospinal fluid (CSF) and serum samples of 41 RRMS, 30 SPMS, 13 PPMS patients and 25 patients with OND were analysed. Results: Out of a total of 100 detected peptides in CSF and 200 peptides in serum, 11 peptides were differentially regulated in serum and two in CSF between patients with MS and the OND control group. Eleven peptides were differentially regulated in both serum and CSF between relapse-onset MS and PPMS patients. Lastly, four peptides were differentially regulated in serum and two in CSF between RRMS and SPMS patients. Specific peaks regulated in MS were tentatively identified as fragments of secretogranin III and complement C3. The peak intensity of the CSF peptide ion with m/z value 8607.7 correlated to atrophy (r = −0.27, p < 0.005), black hole volumes (r = 0.31, p < 0.008) and total lesion load (r = 0.34, p < 0.003). A serum peptide with m/z value of 872.4 elevated in SPMS correlated to Expanded Disability Status Scale (r = 0.341, p < 0.005) and atrophy (r = −0.286, p < 0.028). Conclusions: Using high-throughput body fluid profiling by MALDI-TOF mass spectrometry, small proteins and peptides were detected as promising candidate biomarkers for diagnosis and disease progression of MS

N-Acetylaspartate and neurofilaments as biomarkers of axonal damage in patients with progressive forms of multiple sclerosis

Primary and secondary progressive forms of multiple sclerosis (PPMS and SPMS) have different path- ological characteristics. However, it is unknown whether neurodegenerative mechanisms are shared. We measured cerebrospinal fluid (CSF) levels of neurofilament (Nf) light and heavy isoforms and N-acetylaspartic acid (NAA) in 21 PP, 10 SPMS patients and 15 non-inflammatory neuro- logical disease controls (NINDC). Biomarkers were related to Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Severity Score (MSSS) over a long period of follow-up [median (interquartile range) 9 (5.5–12.5) years] in 19 PPMS and 4 SPMS patients, and to T2 lesion load, T1 lesion load, and brain parenchymal fraction at the time of lumbar puncture. Nf light was higher in PPMS (p<0.005)and Nf heavy was increased in both SPMS and PPMS (p<0.05 and p<0.01) compared to NINDC, but were comparable between the two MS subtypes. Nf heavy was a predictor of the ongoing disability measured by MSSS (R2 = 0.17, b = 0.413; p<0.05). Conversely, Nf light was the only predictor of the EDSS annual increase (R2 = 0.195, b = 0.441; p<0.05). The frequency of abnormal biomarkers did not differ between the two MS progressive subtypes. Our data suggest that PP and SPMS likely share similar mechanisms of axonal damage. Moreover, Nf heavy can be a biomarker of ongoing axonal damage. Conversely, Nf light can be used as a prognostic marker for accumulating disability suggesting it as a good tool for possible treatment monitoring in the progressive MS forms

Identification of novel cerebrospinal fluid biomarker candidates for dementia with Lewy bodies: a proteomic approach

BACKGROUND: Diagnosis of dementia with Lewy bodies (DLB) is challenging, largely due to a lack of diagnostic tools. Cerebrospinal fluid (CSF) biomarkers have been proven useful in Alzheimer's disease (AD) diagnosis. Here, we aimed to identify novel CSF biomarkers for DLB using a high-throughput proteomic approach. METHODS: We applied liquid chromatography/tandem mass spectrometry with label-free quantification to identify biomarker candidates to individual CSF samples from a well-characterized cohort comprising patients with DLB (n = 20) and controls (n = 20). Validation was performed using (1) the identical proteomic workflow in an independent cohort (n = 30), (2) proteomic data from patients with related neurodegenerative diseases (n = 149) and (3) orthogonal techniques in an extended cohort consisting of DLB patients and controls (n = 76). Additionally, we utilized random forest analysis to identify the subset of candidate markers that best distinguished DLB from all other groups. RESULTS: In total, we identified 1995 proteins. In the discovery cohort, 69 proteins were differentially expressed in DLB compared to controls (p < 0.05). Independent cohort replication confirmed VGF, SCG2, NPTX2, NPTXR, PDYN and PCSK1N as candidate biomarkers for DLB. The downregulation of the candidate biomarkers was somewhat more pronounced in DLB in comparison with related neurodegenerative diseases. Using random forest analysis, we identified a panel of VGF, SCG2 and PDYN to best differentiate between DLB and other clinical groups (accuracy: 0.82 (95%CI: 0.75-0.89)). Moreover, we confirmed the decrease of VGF and NPTX2 in DLB by ELISA and SRM methods. Low CSF levels of all biomarker candidates, except PCSK1N, were associated with more pronounced cognitive decline (0.37 < r < 0.56, all p < 0.01). CONCLUSION: We identified and validated six novel CSF biomarkers for DLB. These biomarkers, particularly when used as a panel, show promise to improve diagnostic accuracy and strengthen the importance of synaptic dysfunction in the pathophysiology of DLB

Neurofilament ELISA validation

Contains fulltext : 89601.pdf (publisher's version ) (Closed access)BACKGROUND: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. METHODS: The UmanDiagnostics NF-light (R)enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories' accuracy and preparation of standards were documented and used for the statistical analyses. RESULTS: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R=0.60, p<0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R=0.98, p<0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss' multi-rater kappa and Gwet's AC1 statistics. CONCLUSION: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online

Neurofilament ELISA validation

Background: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. Methods: The UmanDiagnostics NF-light ®enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68 kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories&apos; accuracy and preparation of standards were documented and used for the statistical analyses. Results: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R = 0.60, p &lt; 0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R = 0.98, p &lt; 0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss&apos; multi-rater kappa and Gwet&apos;s AC1 statistics. Conclusion: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online. © 2009 Elsevier B.V