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Additional file 1: A. Pre-analytic study. Four plasma samples (healthy controls) were analyzed repeatedly at baseline and each time after three transfers (upper left), three freeze-thaw cycles (room temperature/minus 80��C, upper right), one to four and eight days storage at 4��C (lower left), as well as room temperature (lower right). Comparisons of Lipocalin 2 concentrations were calculated with ANOVA followed by Bonferroni correcture. Differences are indicated when p was < 0.05 (*) and < 0.001 (***), respectively. B. Results from linear regression models and post hoc Tests in Fig. 1. Estimates, standard errors, t-values, and p-values were calculated through pairwise comparisons of means of log-transferred values by Tukey contrasts, HC: healthy controls, ND-Dem: non-neurodegenerative neurological diseases with dementia syndrome, AD: Alzheimer���s disease, CJD: Creutzfeldt-Jakob disease, LBD: Lewy body diseases (dementia with Lewy bodies and Parkinson���s disease dementia), FTD: fronto-temporal dementia, and VaD: vascular dementia. C. Results from linear regression models and post hoc Tests in Figs. 2 and 3. Estimates, standard errors, t-values, and p-values were calculated through pairwise comparisons of means of log-transferred values by Tukey contrasts, HC: healthy controls, AD: Alzheimer���s disease, MCI-AD: mild cognitive impairment with positive AD biomarker, VaD: vascular dementia, VCI-MCI: mild vascular cognitive impairment, spAD: slowly progressive AD; rpAD: rapidly progressive AD. D. Results from linear regression models using only A+/T+ AD-patients. Estimates, standard errors, t-values, and p-values were calculated through pairwise comparisons of means of log-transferred values by Tukey contrasts, HC: healthy controls, ND-Dem: non-neurodegenerative neurological diseases with dementia syndrome, AD: Only patients with diagnosis of Alzheimer���s disease based on pathologic CSF abeta 1-42 and also pathologic phosphorylated tau protein (A+/T+, n = 39), CJD: Creutzfeldt-Jakob disease, LBD: Lewy body diseases (dementia with Lewy bodies and Parkinson���s disease dementia), FTD: fronto-temporal dementia, and VaD: vascular dementia. E. Correlation of plasma and CSF LCN2. Association of plasma and CSF lipocalin 2 (LCN2) in paired samples from the AD group in the study cohort. Correlation coefficient (rho), 95% confidence interval (95% CI) and p-values from non-parametric spearman correlation is indicated. F. Correlation of plasma LCN2 and ARWMC in AD. Scatter plot of the association between age-related white matter changes scale (ARWMC) scores and plasma lipocalin LCN2 concentrations. Spearman coefficients (cc) with 95% confidence interval (CI) and corresponding p-values are indicated.

Additional file 1. Plasma Nfl and t-tau correlations in the study population. A. Correlation analysis between plasma Nfl and t-tau concentrations in the study population stratified by disease group. Correlation coefficients with 95% CI and associated p values derived from Spearman test analysis are indicated for each comparison. Statistically significant differences are shown in bold. B. Scatter plot with plasma Nfl and t-tau concentrations in CJD. HC: healthy controls, NND: neurological diseases without dementia, NND-Dem: neurological diseases with dementia, AD: Alzheimer’s disease, CJD: Creutzfeldt-Jakob disease, DLB/PDD: dementia with Lewy bodies/Parkinson’s disease dementia, FTD: fronto-temporal dementia and VaD: vascular dementia, cc: correlation coefficient, 95% CI: 95% confidence interval. C. Correlation analysis in CJD cases between plasma Nfl and plasma t-tau concentrations with CSF Nfl, CSF t-tau, CSF Aβ42, plasma YKL-40, plasma t-PrP concentrations. Correlation coefficients with 95% CI and associated p values derived from Spearman test analysis are indicated for each comparison. Association between plasma NFl and t-tau with CSF 14-3-3 positivity was analyzed using the Mann-Whitney U test. Number of paired cases used in the analysis is indicated. Statistically significant differences are shown in bold. D. Scatter plots with plasma Nfl vs. CSF Nfl and E. plasma t-tau vs. CSF t-tau concentrations in CJD. cc: correlation coefficient, 95% CI: 95% confidence interval, n: number. Nfl: neurofilament light, t-tau: total-tau, Aβ42: amyloid beta 42.

Alpha-synucleinopathies, such as Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), are a class of neurodegenerative diseases. A diagnosis may be challenging because clinical symptoms partially overlap, and there is currently no reliable diagnostic test available. Therefore, we aimed to identify a suitable marker protein in cerebrospinal fluid (CSF) to distinguish either between different types of alpha-synucleinopathies or between alpha-synucleinopathies and controls. In this study, the regulation of different marker protein candidates, such as alpha-synuclein (a-Syn), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and total tau (tau) in different types of alpha-synucleinopathies, had been analyzed by using an ultrasensitive test system called single-molecule array (SIMOA). Interestingly, we observed that CSF-NfL was significantly elevated in patients with DLB and MSA compared to patients with PD or control donors. To differentiate between groups, receiver operating characteristic (ROC) curve analysis resulted in a very good diagnostic accuracy as indicated by the area under the curve (AUC) values of 0.87-0.92 for CSF-NfL. Furthermore, we observed that GFAP and tau were slightly increased either in DLB or MSA, while a-Syn levels remained unregulated. Our study suggests NfL as a promising marker to discriminate between different types of alpha-synucleinopathies or between DLB/MSA and controls.

Additional file 2 Relationship between plasma t-tau and disease duration in CJD. A. Resultant hazard ratios (HR) and associated p-values from Cox PH models, in which disease duration was the response variable and the biomarker (in pg/mL) was the predictor, performed as explained in Statistical analysis. B. When allowing for non-linear relationships (using the multivariable fractional polynomial method), the best fit considering disease duration from disease onset was obtained with the logarithmic transformation of the biomarker data. The Cox PH model rendered a concordance of 0.6098 (SE = 0.0301).C. When disease duration was measured from blood uptake, the best fit model was obtained without the logarithmic transformation, and the resultant Cox PH model offered a concordance of 0.6080 (SE = 0.0359).