Cerebrospinal Fluid Iron-Ferritin Ratio as a Potential Progression Marker for Parkinson's Disease.

Longitudinal PD CSF samples were subjected to ICP-MS and the total amount of iron and other bioelements was quantified. Additionally, ferritin and protein biomarkers of neurodegeneration were measured. Over time, mean iron levels significantly increased while levels of ferritin decreased.

Setup of Capillary Electrophoresis-Inductively Coupled Plasma Mass Spectrometry (CE-ICP-MS) for Quantification of Iron Redox Species (Fe(II), Fe(III)).

Dyshomeostasis of iron metabolism is accounted in the pathophysiological framework of numerous diseases, including cancer and several neurodegenerative conditions. Excessive iron results in free redox-active Fe(II) and can cause devastating effects within the cell like oxidative stress (OS) and death by lipid peroxidation known as ferroptosis (FPT). Therefore, quantitative measurements of ferrous (Fe(II)) and ferric (Fe(III)) iron rather than total Fe-determination is the key for closer insight into these detrimental processes. Since Fe(II)/(III) determinations can be hampered by fast redox-state shifts and low concentrations in relevant samples, like cerebrospinal fluid (CSF), methods should be available that analyze quickly and provide low limits of quantification (LOQ). Capillary electrophoresis (CE) offers the advantage of fast Fe(II)/Fe(III) separation and works without a stationary phase, which could interfere with the redox balance or cause analyte sticking. CE combined with inductively coupled plasma mass spectrometry (ICP-MS) as a detector offers further improvement of detection sensitivity and selectivity. The presented method uses 20 mM HCl as a background electrolyte and a voltage of +25 kV. Peak shapes and concentration detection limits are improved by conductivity-pH-stacking. For reduction of 56[ArO]+, ICP-MS was operated in the dynamic reaction cell (DRC) mode with NH3 as a reaction gas. The method achieves a limit of detection (LOD) of 3 µg/L. Due to stacking, higher injection volumes were possible without hampering separation but improving LOD. Calibrations related to peak area were linear up to 150 µg/L. Measurement precision was 2.2% (Fe(III)) to 3.5% (Fe(II)). Migration time precision was <3% for both species, determined in 1:2 diluted lysates of human neuroblastoma (SH-SY5Y) cells. Recovery experiments with standard addition revealed accuracy of 97% Fe(III) and 105 % Fe(II). In real-life bio-samples like CSF, migration time can vary according to varying conductivity (i.e., salinity). Thus, peak identification is confirmed by standard addition.

Selenium speciation analysis in the cerebrospinal fluid of patients with Parkinson's disease.

BACKGROUND: The aim of the study was to investigate if speciation analysis by liquid chromatography coupled to mass spectrometry could be used to detect organic and inorganic binding forms of selenium in the cerebrospinal fluid (CSF) of patients with Parkinson's disease (PD) and age-matched control subjects (AMC). METHODS: PD patients and control subjects were enrolled from three different neurological departments. CSF samples were collected according to standardized biomarker protocols and subjected to inductively coupled plasma mass spectrometry (ICP-MS) for total selenium determination and ion exchange chromatography (IEC) hyphenated to ICP-MS for selenium speciation analysis. RESULTS: 75 PD patients and 68 age-matched controls were enrolled for speciation analysis. 8 different species could be detected, but only selenoprotein P (SELENOP), human serum albumin-bound Se (Se-HSA), selenomethionine (Se-Met) and an unidentified Se-compound (U2) presented with more than 50% values above the limit of quantification, without showing significant differences between both groups (p > 0.05). The Se-HSA / Se-Met ratio yielded a significant difference between PD and AMC (p = 0.045). The inorganic species Se-IV and Se-VI were only detectable in a minor part of PD and AMC samples. A highly significant correlation between total selenium levels and SELENOP (PD p < 0.0001; AMC p < 0.0001) and Se-HSA (PD p < 0.0001; AMC p < 0.0001) could be demonstrated, respectively. CONCLUSIONS: Speciation analysis yielded new insight into selenium homeostasis in PD but cannot be used to establish a diagnostic biomarker. The small number of detectable values for Se-IV and Se-VI suggests an inferior role of these potentially neurotoxic binding forms in PD pathology in contrast to other neurodegenerative disorders.

Elemental fingerprint: Reassessment of a cerebrospinal fluid biomarker for Parkinson's disease.

The aim of the study was to validate a predictive biomarker machine learning model for the classification of Parkinson's disease (PD) and age-matched controls (AMC), based on bioelement abundance in the cerebrospinal fluid (CSF). For this multicentric trial, participants were enrolled from four different centers. CSF was collected according to standardized protocols. For bioelement determination, CSF samples were subjected to inductively coupled plasma mass spectrometry. A predefined Support Vector Machine (SVM) model, trained on a previous discovery cohort was applied for differentiation, based on the levels of six different bioelements. 82 PD patients, 68 age-matched controls and 7 additional Normal Pressure Hydrocephalus (NPH) patients were included to validate a predefined SVM model. Six differentiating elements (As, Fe, Mg, Ni, Se, Sr) were quantified. Based on their levels, SVM was successfully applied to a new local cohort (AUROC 0.76, Sensitivity 0.80, Specificity 0.83), without taking any additional features into account. The same model did not discriminate PD and AMCs / NPH from three external cohorts, likely due to center effects. However, discrimination was possible in cohorts with a full elemental data set, now using center-specific discovery cohorts and a cross validated approach (AUROC 0.78 and 0.88, respectively). Pooled PD CSF iron levels showed a clear correlation with disease duration (p = .0001). In summary, bioelemental CSF patterns, obtained by mass spectrometry and integrated into a predictive model yield the potential to facilitate the differentiation of PD and AMC. Center-specific biases interfere with application in external cohorts. This must be carefully addressed using center-defined, local reference values and models.

Assessment of copper, iron, zinc and manganese status and speciation in patients with Parkinson's disease: A pilot study.

BACKGROUND: The objective of this pilot study was to assess iron (Fe), copper (Cu), zinc (Zn), and manganese (Mn) status (hair, serum, and urine) and speciation (serum) in Parkinson's disease (PD) patients. METHODS: A pilot study involving a total of 27 subjects (13 PD patients, 14 controls) was performed. Serum, urine, and hair metal content was assessed using ICP-MS. Speciation analysis of Cu, Zn, Fe, and Mn was performed using a hybrid HPLC-ICP-MS system. RESULTS: Group comparisons did not reveal any significant group difference in serum Cu, Zn, Fe, and Mn total metal level between PD patients and controls. Speciation analysis revealed a significant decrease in Cu/ceruloplasmin copper in association with elevation of low-molecular weight species (amino acids)-bound copper. It is proposed that in PD, binding of Cu(II) ions to ceruloplasmin is reduced and free copper ions coordinate with low molecular weight ligands. The level of Mn-albumin complexes in PD patients was more than 4-fold higher as compared to the respective value in the control group. The observed difference may be considered as a marker of redistribution between high and low molecular weight ligands. CONCLUSIONS: Metal speciation is significantly affected in serum of PD-patients. These findings are indicative of the potential role of metal metabolism and PD pathogenesis, although the exact mechanisms of such associations require further detailed studies.

Integrative Metabolomic and Metallomic Analysis in a Case-Control Cohort With Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disease with a complex etiology. Several factors are known to contribute to the disease onset and its progression. However, the complete underlying mechanisms are still escaping our understanding. To evaluate possible correlations between metabolites and metallomic data, in this research, we combined a control study measured using two different platforms. For the different data sources, we applied a Block Sparse Partial Least Square Discriminant Analysis (Block-sPLS-DA) model that allows for proving their relation, which in turn uncovers alternative influencing factors that remain hidden otherwise. We found two groups of variables that trace a strong relationship between metallomic and metabolomic parameters for disease development. The results confirmed that the redox active metals iron (Fe) and copper (Cu) together with fatty acids are the major influencing factors for the PD. Additionally, the metabolic waste product p-cresol sulfate and the trace element nickel (Ni) showed up as potentially important factors in PD. In summary, the data integration of different types of measurements emphasized the results of both stand-alone measurements providing a new comprehensive set of information and interactions, on PD disease, between different variables sources.

Iron Redox Speciation Analysis Using Capillary Electrophoresis Coupled to Inductively Coupled Plasma Mass Spectrometry (CE-ICP-MS).

Neuronal iron dyshomeostasis occurs in multiple neurodegenerative diseases. Changes in the Fe(II)/Fe(III) ratio toward Fe(II) is closely related to oxidative stress, lipid peroxidation, and represents a hallmark feature of ferroptosis. In particular for body fluids, like cerebrospinal fluid (CSF), reliable quantitative methods for Fe(II)/(III) redox-speciation analysis are needed to better assess the risk of Fe(II)-mediated damage in brain tissue. Currently in the field of metallomics, the most direct method to analyze both iron species is via LC-ICP-MS. However, this Fe(II)/(III) speciation analysis method suffers from several limitations. Here, we describe a unique method using capillary electrophoresis (CE)-ICP-MS for quantitative Fe(II)/(III) speciation analysis that can be applied for cell lysates and biofluid samples. Compared to LC, CE offers various advantages: (1) Capillaries have no stationary phase and do not depend on batch identity of stationary phases; (2) Replacement of aged or blocked capillaries is quick with no performance change; (3) Purge steps are effective and short; (4) Short sample analysis time. The final method employed 20 mM HCl as background electrolyte and a separation voltage of +25 kV. In contrary to the LC-method, no complexation of Fe-species with pyridine dicarboxylic acid (PDCA) was applied, since it hampered separation. Peak shapes and concentration detection limits were improved by combined conductivity-pH-stacking achieving 3 µg/L detection limit (3σ) at 13 nL injection volume. Calibrations from LOD-150 µg/L were linear [r 2 [Fe(II)] = 0.9999, r 2 [Fe(III)] = 0.9951]. At higher concentrations Fe(II) curve flattened significantly. Measurement precision was 3.5% [Fe(II) at 62 µg/L] or 2.2% [Fe(III) at 112 µg/L] and migration time precision was 2% for Fe(III) and 3% for Fe(II), each determined in 1:2 diluted lysates of human neuroblastoma cells. Concentration determination accuracy was checked by parallel measurements of SH-SY5Y cell lysates with validated LC-ICP-MS method and by recovery experiments after standard addition. Accuracy (n = 6) was 97.6 ± 3.7% Fe(III) and 105 ± 6.6%Fe(II). Recovery [(a) +33 µg/L or (b) +500 µg/L, addition per species] was (a): 97.2 ± 13% [Fe(II)], 108 ± 15% [Fe(III)], 102.5 ± 7% (sum of species), and (b) 99±4% [Fe(II)], 101 ± 6% [Fe(III)], 100 ± 5% (sum of species). Migration time shifts in CSF samples were due to high salinity, but both Fe-species were identified by standard addition.

Metabolomic investigations in cerebrospinal fluid of Parkinson's disease.

The underlying mechanisms of Parkinson´s disease are not completely revealed. Especially, early diagnostic biomarkers are lacking. To characterize early pathophysiological events, research is focusing on metabolomics. In this case-control study we investigated the metabolic profile of 31 Parkinson´s disease-patients in comparison to 95 neurologically healthy controls. The investigation of metabolites in CSF was performed by a 12 Tesla SolariX Fourier transform-ion cyclotron resonance-mass spectrometer (FT-ICR-MS). Multivariate statistical analysis sorted the most important biomarkers in relation to their ability to differentiate Parkinson versus control. The affected metabolites, their connection and their conversion pathways are described by means of network analysis. The metabolic profiling by FT-ICR-MS in CSF yielded in a good group separation, giving insights into the disease mechanisms. A total number of 243 metabolites showed an affected intensity in Parkinson´s disease, whereas 15 of these metabolites seem to be the main biological contributors. The network analysis showed a connection to the tricarboxylic cycle (TCA cycle) and therefore to mitochondrial dysfunction and increased oxidative stress within mitochondria. The metabolomic analysis of CSF in Parkinson´s disease showed an association to pathways which are involved in lipid/ fatty acid metabolism, energy metabolism, glutathione metabolism and mitochondrial dysfunction.

Manganese causes neurotoxic iron accumulation via translational repression of amyloid precursor protein and H-Ferritin.

For more than 150 years, it is known that occupational overexposure of manganese (Mn) causes movement disorders resembling Parkinson's disease (PD) and PD-like syndromes. However, the mechanisms of Mn toxicity are still poorly understood. Here, we demonstrate that Mn dose- and time-dependently blocks the protein translation of amyloid precursor protein (APP) and heavy-chain Ferritin (H-Ferritin), both iron homeostatic proteins with neuroprotective features. APP and H-Ferritin are post-transcriptionally regulated by iron responsive proteins, which bind to homologous iron responsive elements (IREs) located in the 5'-untranslated regions (5'-UTRs) within their mRNA transcripts. Using reporter assays, we demonstrate that Mn exposure repressed the 5'-UTR-activity of APP and H-Ferritin, presumably via increased iron responsive proteins-iron responsive elements binding, ultimately blocking their protein translation. Using two specific Fe2+ -specific probes (RhoNox-1 and IP-1) and ion chromatography inductively coupled plasma mass spectrometry (IC-ICP-MS), we show that loss of the protective axis of APP and H-Ferritin resulted in unchecked accumulation of redox-active ferrous iron (Fe2+ ) fueling neurotoxic oxidative stress. Enforced APP expression partially attenuated Mn-induced generation of cellular and lipid reactive oxygen species and neurotoxicity. Lastly, we could validate the Mn-mediated suppression of APP and H-Ferritin in two rodent in vivo models (C57BL6/N mice and RjHan:SD rats) mimicking acute and chronic Mn exposure. Together, these results suggest that Mn-induced neurotoxicity is partly attributable to the translational inhibition of APP and H-Ferritin resulting in impaired iron metabolism and exacerbated neurotoxic oxidative stress. OPEN SCIENCE BADGES: This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/.

Species fractionation in a case-control study concerning Parkinson's disease: Cu-amino acids discriminate CSF of PD from controls.

BACKGROUND: Parkinson's disease is affecting about 1% of the population above 65 years. Improvements in medicine support prolonged lifetime which increases the total concentration of humans affected by the disease. It is suggested that occupational and environmental exposure to metals like iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn) can influence the risk for Parkinson's disease. These metals play a key role as cofactors in many enzymes and proteins. METHODS: In this case-control study, we investigated the Mn-, Fe-, Cu- and Zn-species in cerebrospinal fluid (CSF) by size-exclusion chromatography hyphenated to inductively coupled plasma mass spectrometry (SEC-ICP-MS) and the total concentration of these metals by inductively coupled plasma sector field mass spectrometry (ICP-sf-MS). RESULTS: The investigation of total metal concentration and speciation provided only minor changes, but it produced strong significance for a number of ratios. The analysis revealed a strong change in the ratio between total concentration of Fe and the amino acid-fraction of Cu. This could be observed when analyzing both the respective element concentrations of the fraction (which also depends on individual variation of the total element concentration) as well as when being expressed as percentage of total concentration (normalization) which more clearly shows changes of distribution pattern independent of individual variation of total element concentrations. CONCLUSION: Speciation analysis, therefore, is a powerful technique to investigate changes in a case-control study where ratios of different species play an important role.