Background: Parkinson's disease (PD) and atypical parkinsonisms (APD) have overlapping symptoms challenging an early diagnosis. Diagnostic accuracy is important because PD and APD have different prognosis and response to treatment. We aimed to identify diagnostic inflammatory biomarkers of PD and APD in cerebrospinal fluid (CSF) using the multiplex proximity extension assay (PEA) technology and to study possible correlations of biomarkers with disease progression. Methods: CSF from a longitudinal cohort study consisting of PD and APD patients (PD, n = 44; multiple system atrophy (MSA), n = 14; vascular parkinsonism (VaP), n = 9; and PD with VaP, n = 7) and controls (n = 25) were analyzed. Results: Concentrations of CCL28 were elevated in PD compared to controls (p = 0.0001). Five other biomarkers differentiated both MSA and PD from controls (p < 0.05) and 10 biomarkers differentiated MSA from controls, of which two proteins, i.e. beta nerve growth factor (β-NGF) and Delta and Notch like epidermal growth factor-related receptor (DNER), were also present at lower levels in MSA compared to PD (both p = 0.032). Two biomarkers (MCP-1 and MMP-10) positively correlated with PD progression (rho > 0.650; p < 0.01). Conclusions: PEA technique identified potential new CSF biomarkers to help to predict the prognosis of PD. Also, we identified new candidate biomarkers to distinguish MSA from PD.

Background and Purpose-In computed tomographic imaging of acute intracerebral hemorrhage spot sign on computed tomographic angiography has been established as a marker for hematoma expansion and poor clinical outcome. Although, magnetic resonance imaging (MRI) can accurately visualize acute intracerebral hemorrhage, a corresponding MRI marker is lacking to date. Methods-We prospectively examined 50 consecutive patients with acute intracerebral hemorrhage within 24 hours of symptom onset. The MRI protocol consisted of a standard stroke protocol and dynamic contrast-enhanced T1-weighted imaging with a time resolution of 7.07 s/batch. Stroke scores were assessed at admission and at time of discharge. Volume measurements of hematoma size and spot sign were performed with MRIcron. Results-Contrast extravasation within sites of the hemorrhage (MRI spot sign) was seen in 46% of the patients. Patients with an MRI spot sign had a significantly shorter time to imaging than those without (P<0.001). The clinical outcome measured by the modified Rankin Scale was significantly worse in patients with spot sign compared with those without (P≤0.001). Hematoma expansion was observed in the spot sign group compared with the nonspot sign group, although the differences were not significant. Conclusions-Spot sign can be detected using MRI on postcontrast T1-weighted and dynamic T1-weighted images. It is associated with worse clinical outcome. The time course of contrast extravasation in dynamic T1 images indicates that these spots represent ongoing bleeding.

Parkinson's disease (PD) and multiple system atrophy (MSA) have overlapping symptoms, challenging a correct early diagnosis. Prognostic information is needed to predict disease progression and provide appropriate counseling. Neuroinflammation plays a role in the pathology of both disorders, as shown in genetic and postmortem tissue studies. Monocyte chemoattractant protein 1 (MCP-1) and neuroleukin (NLK) are two inflammatory proteins with potential to serve as biomarkers of the neuroinflammatory process. Here, we aimed to study the biomarker potential of both MCP-1 and NLK protein levels in cerebrospinal fluid (CSF) from a longitudinal cohort study (Radboudumc, Nijmegen, The Netherlands), consisting of PD patients (n = 46), MSA patients (n = 17) and control subjects (n = 52) using ELISA. We also correlated MCP-1 and NLK levels in CSF to several parameters of disease. We showed that MCP-1 levels in CSF positively correlate with PD progression (ρ = 0.363; p = 0.017) but could not differentiate between PD, MSA, and controls. NLK levels in CSF neither differentiated between PD, MSA, and controls, nor correlated with disease progression. Our results indicate that MCP-1 levels in CSF cannot distinguish between PD, MSA, and controls but correlate with disease progression in PD patients, suggesting that neuroinflammation is associated with clinical progression in PD. The correlation with disease progression was only moderate, so MCP-1 levels in CSF should be included in a larger battery of prognostic biomarkers that also tackle different pathophysiological processes.

Background: Parkinson’s disease (PD) and atypical parkinsonisms (APD) have overlapping symptoms challenging an early diagnosis. Diagnostic accuracy is important because PD and APD have different prognosis and response to treatment. We aimed to identify diagnostic inflammatory biomarkers of PD and APD in cerebrospinal fluid (CSF) using the multiplex proximity extension assay (PEA) technology and to study possible correlations of biomarkers with disease progression. Methods: CSF from a longitudinal cohort study consisting of PD and APD patients (PD, n = 44; multiple system atrophy (MSA), n = 14; vascular parkinsonism (VaP), n = 9; and PD with VaP, n = 7) and controls (n = 25) were analyzed. Results: Concentrations of CCL28 were elevated in PD compared to controls (p = 0.0001). Five other biomarkers differentiated both MSA and PD from controls (p < 0.05) and 10 biomarkers differentiated MSA from controls, of which two proteins, i.e. beta nerve growth factor (β-NGF) and Delta and Notch like epidermal growth factor-related receptor (DNER), were also present at lower levels in MSA compared to PD (both p = 0.032). Two biomarkers (MCP-1 and MMP-10) positively correlated with PD progression (rho > 0.650; p < 0.01). Conclusions: PEA technique identified potential new CSF biomarkers to help to predict the prognosis of PD. Also, we identified new candidate biomarkers to distinguish MSA from PD.

Background : Parkinson’s disease (PD) and atypical parkinsonisms (APD) have overlapping symptoms challenging an early diagnosis. Diagnostic accuracy is important because PD and APD have different prognosis and response to treatment. We aimed to identify inflammatory biomarkers in cerebrospinal fluid (CSF) using the multiplex proximity extension assay (PEA) technology to identify diagnostic biomarkers of PD and APD and to study possible correlations of biomarkers with disease progression. Methods : CSF from a longitudinal cohort study consisting of PD and APD patients (PD, n = 46; multiple system atrophy (MSA) , n = 15; vascular parkinsonism (VaP) , n = 9; and PD with VaP, n = 7) and controls (n = 25) were analyzed. Results : Concentrations of CCL28 were elevated in PD compared to controls (p < 0.05). Five other biomarkers differentiated both MSA and PD from controls (p < 0.05) and 10 biomarkers differentiated MSA from controls, of which two proteins, i.e. beta nerve growth factor (β-NGF) and Delta and Notch like epidermal growth factor-related receptor (DNER) , were also present at lower levels in MSA compared to PD (both p = 0.032). Two biomarkers (MCP-1 and MMP-10) positively correlated with PD progression (rho > 0.600; p < 0.01). Conclusions : PEA technique identified potential new CSF biomarkers to help to predict the prognosis of PD. Also, we identified new candidate biomarkers to distinguish MSA from PD.