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Delayed diagnosis and misdiagnosis are frequent in people with amyotrophic lateral sclerosis (ALS), the most common form of motor neuron disease (MND). Neurofilament light chain (NFL) and phosphorylated neurofilament heavy chain (pNFH) are elevated in ALS patients. We retrospectively quantified cerebrospinal fluid (CSF) NFL, CSF pNFH and plasma NFL in stored samples that were collected at the diagnostic work-up of ALS patients (n = 234), ALS mimics (n = 44) and controls (n = 9). We assessed the diagnostic performance, prognostication value and relationship to the site of onset and genotype. CSF NFL, CSF pNFH and plasma NFL levels were significantly increased in ALS patients compared to patients with neuropathies & myelopathies, patients with myopathies and controls. Furthermore, CSF pNFH and plasma NFL levels were significantly higher in ALS patients than in patients with other MNDs. Bulbar onset ALS patients had significantly higher plasma NFL levels than spinal onset ALS patients. ALS patients with C9orf72HRE mutations had significantly higher plasma NFL levels than patients with SOD1 mutations. Survival was negatively correlated with all three biomarkers. Receiver operating characteristics showed the highest area under the curve for CSF pNFH for differentiating ALS from ALS mimics and for plasma NFL for estimating ALS short and long survival. All three biomarkers have diagnostic value in differentiating ALS from clinically relevant ALS mimics. Plasma NFL levels can be used to differentiate between clinical and genetic ALS subgroups.

Mutations in the superoxide dismutase (SOD1) gene have been linked to amyotrophic lateral sclerosis (ALS). A 50 base pair (bp) deletion of SOD1 has been suggested to reduce transcription and to be associated with later disease onset in ALS. This study was aimed to reveal if the 50bp deletion influenced SOD1 enzymatic activity, occurrence and phenotype of the disease in a Swedish ALS/control cohort. Blood samples from 512 Swedish ALS patients and 354 Swedish controls without coding SOD1 mutations were analysed for the 50bp deletion allele. The enzymatic activity of SOD1 in erythrocytes was analysed and genotype-phenotype correlations were assessed. Results demonstrated that the genotype frequencies of the 50bp deletion were all found to be in Hardy-Weinberg equilibrium. No significant differences were found for age of onset, disease duration or site of onset. SOD1 enzymatic activity showed a statistically significant decreasing trend in the control group, in which the allele was associated with a 5% reduction in SOD1 activity. The results suggest that the 50bp deletion has a moderate reducing effect on SOD1 synthesis. No modulating effects, however, were found on ALS onset, phenotype and survival in the Swedish population.

A method for predictive metabolite profiling based on resolution of GC-MS data followed by multivariate data analysis is presented and applied to three different biofluid data sets (rat urine, aspen leaf extracts, and human blood plasma). Hierarchical multivariate curve resolution (H-MCR) was used to simultaneously resolve the GC-MS data into pure profiles, describing the relative metabolite concentrations between samples, for multivariate analysis. Here, we present an extension of the H-MCR method allowing treatment of independent samples according to processing parameters estimated from a set of training samples. Predictions or inclusion of the new samples, based on their metabolite profiles, into an existing model could then be carried out, which is a requirement for a working application within, e.g., clinical diagnosis. Apart from allowing treatment and prediction of independent samples the proposed method also reduces the time for the curve resolution process since only a subset of representative samples have to be processed while the remaining samples can be treated according to the obtained processing parameters. The time required for resolving the 30 training samples in the rat urine example was approximately 13 h, while the treatment of the 30 test samples according to the training parameters required only approximately 30 s per sample (approximately 15 min in total). In addition, the presented results show that the suggested approach works for describing metabolic changes in different biofluids, indicating that this is a general approach for high-throughput predictive metabolite profiling, which could have important applications in areas such as plant functional genomics, drug toxicity, treatment efficacy and early disease diagnosis.

Analytical drift is a major source of bias in mass spectrometry based metabolomics confounding interpretation and biomarker detection. So far, standard protocols for sample and data analysis have not been able to fully resolve this. We present a combined approach for minimizing the influence of analytical drift on multivariate comparisons of matched or dependent samples in mass spectrometry based metabolomics studies. The approach is building on a randomization procedure for sample run order, constrained to independent randomizations between and within dependent sample pairs (e.g. pre/post intervention). This is followed by a novel multivariate statistical analysis strategy allowing paired or dependent analyses of individual effects named OPLS-effect projections (OPLS-EP). We show, using simulated data that OPLS-EP gives improved interpretation over existing methods and that constrained randomization of sample run order in combination with an appropriate dependent statistical test increase the accuracy and sensitivity and decrease the false omission rate in biomarker detection. We verify these findings and prove the strength of the suggested approach in a clinical data set consisting of LC/MS data of blood plasma samples from patients before and after radical prostatectomy. Here OPLS-EP compared to traditional (independent) OPLS-discriminant analysis (OPLS-DA) on constrained randomized data gives a less complex model (3 versus 5 components) as well a higher predictive ability (Q2 = 0.80 versus Q2 = 0.55). We explain this by showing that paired statistical analysis detects 37 unique significant metabolites that were masked for the independent test due to bias, including analytical drift and inter-individual variation.

Inflammatory mediators have crucial roles in leukocyte recruitment and subsequent central nervous system (CNS) neuroinflammation. The extent of neuronal injury and axonal loss are associated with the degree of CNS inflammation and determine physical disability in multiple sclerosis (MS). The aim of this study was to explore possible associations between a panel of selected cerebrospinal fluid biomarkers and robust clinical and demographic parameters in a large cohort of patients with MS and controls (n = 1066) using data-driven multivariate analysis. Levels of matrix metalloproteinase 9 (MMP9), chemokine (C-X-C motif) ligand 13 (CXCL13), osteopontin (OPN) and neurofilament-light chain (NFL) were measured by ELISA in 548 subjects comprising different MS subtypes (relapsing-remitting, secondary progressive and primary progressive), clinically isolated syndrome and persons with other neurological diseases with or without signs of inflammation/infection. Principal component analyses and orthogonal partial least squares methods were used for unsupervised and supervised interrogation of the data. Models were validated using data from a further 518 subjects in which one or more of the four selected markers were measured. There was a significant association between increased patient age and lower levels of CXCL13, MMP9 and NFL. CXCL13 levels correlated well with MMP9 in the younger age groups, but less so in older patients, and after approximately 54 years of age the levels of CXCL13 and MMP9 were consistently low. CXCL13 and MMP9 levels also correlated well with both NFL and OPN in younger patients. We demonstrate a strong effect of age on both inflammatory and neurodegenerative biomarkers in a large cohort of MS patients. The findings support an early use of adequate immunomodulatory disease modifying drugs, especially in younger patients, and may provide a biological explanation for the relative inefficacy of such treatments in older patients at later disease stages.

Phosphatidylethanol (PEth) is a recently introduced biomarker with high specificity, high sensitivity, and response correlating with alcohol consumption. It has the potential to be a valuable biomarker in population studies on the health effects of alcohol, however its stability in long-term stored blood is not known. We used LCMS/MS to assess the stability of PEth-16:0/18:1 in blood samples (packed erythrocytes) that were stored between 1 and 19 years at -80 degrees C in a biobank from a large population survey. The participants answered a lifestyle questionnaire that included questions on alcohol consumption. For analysis, we selected blood samples from seven homogenous ethanol consumption cohorts collected at intervals from 1997 to 2015. Despite the narrow stated alcohol consumption range, 10-15 g/day, there were large differences in PEth values between individuals in the cohorts, from below the limit of detection of 0.005 mu mol/L to 1.40 mu mol/L. The median was 0.08 mu mol/L. Neither generalized linear modeling, nor principal component analysis revealed a statistically significant association between time of storage and PEth levels. The PEth results indicate that the participants had, on average, under-reported their alcohol consumption several-fold. The findings suggest that PEth in blood has a sufficient long-term stability for use as an alcohol biomarker in prospective case-control studies. Analysis of blood stored in biobanks could significantly improve the validity of assessments exploring the health effects of alcohol.

A large GGGGCC-repeat expansion mutation (HREM) in C9orf72 is the most common known cause of ALS and FTD in European populations. Sequence variations immediately downstream of the HREM region have previously been observed and have been suggested to be one reason for difficulties in interpreting RP-PCR data. Our objective was to determine the properties of these sequence variations with regard to prevalence, the range of variation, and effect on disease prognosis. We screened a multi-national cohort (n = 6981) for the HREM and samples with deviant RP-PCR curves were identified. The deviant samples were subsequently sequenced to determine sequence alteration. Our results show that in the USA and European cohorts (n = 6508) 10.7% carried the HREM and 3% had a sequence variant, while no HREM or sequence variants were observed in the Japanese cohort (n = 473). Sequence variations were more common on HREM alleles; however, certain population specific variants were associated with a non-expanded allele. In conclusion, we identified 38 different sequence variants, most located within the first 50 bp downstream of the HREM region. Furthermore, the presence of an HREM was found to be coupled to a lower age of onset and a shorter disease survival, while sequence variation did not have any correlation with these parameters.

A GGGGCC-repeat expansion in C9orf72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) among Caucasians. However, little is known about the variability of the GGGGCC expansion in different tissues and whether this correlates with the observed phenotype. Here, we used Southern blotting to estimate the size of hexanucleotide expansions in C9orf72 in neural and non-neural tissues from 18 autopsied ALS and FTD patients with repeat expansion in blood. Digitalization of the Southern blot images allowed comparison of repeat number, smear distribution and expansion band intensity between tissues and between patients. We found marked intra-individual variation of repeat number between tissues, whereas there was less variation within each tissue group. In two patients, the size variation between tissues was extreme, with repeat numbers below 100 in all studied non-neural tissues, whereas expansions in neural tissues were 20-40 times greater and in the same size range observed in neural tissues of the other 16 patients. The expansion pattern in different tissues could not distinguish between diagnostic groups and no correlation was found between expansion size in frontal lobe and occurrence of cognitive impairment. In ALS patients, a less number of repeats in the cerebellum and parietal lobe correlated with earlier age of onset and a larger number of repeats in the parietal lobe correlated with a more rapid progression. In 43 other individuals without repeat expansion in blood, we find that repeat sizes up to 15 are stable, as no size variation between blood, brain and spinal cord was found.

Objective: To investigate inflammatory cytokines in patients with motor neuron disease (MND) evaluating the putative contribution of amyotrophic lateral sclerosis (ALS)-causing gene variants.

Methods: This study is a retrospective case series with prospective follow-up (1994–2016) of 248 patients with MND, of whom 164 had ALS who were screened for mutations in the genes for SOD1 and C9orf72. Paired CSF and plasma were collected at the diagnostic evaluation before treatment. A panel of cytokines were measured blindly via digital ELISA on the Simoa platform.

Results: Time from disease onset to death was longer for patients with ALS-causing SOD1 mutations (mSOD1, n = 24) than those with C9orf72 hexanucleotide repeat expansion (C9orf72HRE) ALS (n = 19; q = 0.001) and other ALS (OALS) (n = 119; q = 0.0008). Patients with OALS had higher CSF tumor necrosis factor alpha (TNF-α) compared with those with C9orf72HRE ALS (q = 0.014). Patients with C9orf72HRE ALS had higher CSF interferon alpha compared with those with OALS and mSOD1 ALS (q = 0.042 and q = 0.042). In patients with ALS, the survival was negatively correlated with plasma interleukin (IL) 10 (hazard ratio [HR] 1.17, 95% CI 1.05–1.30). Plasma TNF-α, IL-10, and TNF-related apoptosis-inducing ligand (TRAIL) (HR 1.01 [1.00–1.02], 1.15 [1.02–1.30], and 1.01 [1.00–1.01], respectively) of patients with OALS, plasma IL-1β (HR 5.90 [1.27–27.5]) of patients with C9orf72HRE ALS, and CSF TRAIL (10.5 [1.12–98.6]) of patients with mSOD1 ALS all correlated negatively with survival.

Conclusions: Differences in survival times in ALS subtypes were correlated with cytokine levels, suggesting specific immune responses related to ALS genetic variants.

Despite major advances in deciphering the neuropathological hallmarks of amyotrophic lateral sclerosis (ALS), validated neurochemical biomarkers for monitoring disease activity, earlier diagnosis, defining prognosis and unlocking key pathophysiological pathways are lacking. Although several candidate biomarkers exist, translation into clinical application is hindered by small sample numbers, especially longitudinal, for independent verification. This review considers the potential routes to the discovery of neurochemical markers in ALS, and provides a consensus statement on standard operating procedures that will facilitate multicenter collaboration, validation and ultimately clinical translation.

Background: Parkinson's disease (PD) is a progressive, multi-focal neurodegenerative disease for which there is no effective disease modifying treatment. A critical requirement for designing successful clinical trials is the development of robust and reproducible biomarkers identifying PD in preclinical stages. Objective: To investigate the potential for a cluster of biomarkers visualized with multiple analytical platforms to provide a clinically useful tool. Methods: Gas Chromatography-Mass Spectrometry (GC-TOFMS) based metabolomics and immunoassay-based protein/peptide analyses on samples from patients with PD diagnosed in Northern Sweden. Low molecular weight compounds from both plasma and cerebrospinal fluid (CSF) from 20 healthy subjects (controls) and 20 PD patients at the time of diagnosis (baseline) were analyzed. Results: In plasma, we found a significant increase in several amino acids and a decrease in C16-C18 saturated and unsaturated fatty acids in patients as compared to control subjects. We also observed an increase in plasma levels of pyroglutamate and 2-oxoisocaproate (ketoleucine) that may be indicative of increased metabolic stress in patients. In CSF, there was a generally lower level of metabolites in PD as compared to controls, with a specific decrease in 3-hydroxyisovaleric acid, tryptophan and creatinine. Multivariate analysis and modeling of metabolites indicates that while the PD samples can be separated from control samples, the list of detected compounds will need to be expanded in order to define a robust predictive model. CSF biomarker immunoassays of candidate peptide/protein biomarkers revealed a significant decrease in the levels of A beta-38 and A beta-42, and an increase in soluble APP alpha in CSF of patients. Furthermore, these peptides showed significant correlations to each other, and positive correlations to the CSF levels of several 5- and 6-carbon sugars. However, combining these metabolites and proteins/peptides into a single model did not significantly improve the statistical analysis. Conclusions: Together, this metabolomics study has detected significant alterations in plasma and CSF levels of a cluster of amino acids, fatty acids and sugars based on clinical diagnosis and levels of known protein and peptide biomarkers.

Introduction: Amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) are two severe neurodegenerative disorders for which the disease mechanisms are poorly understood and reliable biomarkers are absent.

Objectives: To identify metabolite biomarkers for ALS and PD, and to gain insights into which metabolic pathways are involved in disease.

Methods: Nuclear magnetic resonance (NMR) metabolomics was utilized to characterize the metabolite profiles of cerebrospinal fluid (CSF) and plasma from individuals in three age, gender, and sampling-date matched groups, comprising 22 ALS, 22 PD and 28 control subjects.

Results: Multivariate analysis of NMR data generated robust discriminatory models for separation of ALS from control subjects. ALS patients showed increased concentrations of several metabolites in both CSF and plasma, these are alanine (CSF fold change = 1.22, p = 0.005), creatine (CSF-fc = 1.17, p = 0.001), glucose (CSF-fc = 1.11, p = 0.036), isoleucine (CSF-fc = 1.24, p = 0.002), and valine (CSF-fc = 1.17, p = 0.014). Additional metabolites in CSF (creatinine, dimethylamine and lactic acid) and plasma (acetic acid, glutamic acid, histidine, leucine, pyruvate and tyrosine) were also important for this discrimination. Similarly, panels of CSF-metabolites that discriminate PD from ALS and control subjects were identified.

Conclusions: The results for the ALS patients suggest an affected creatine/creatinine pathway and an altered branched chain amino acid (BCAA) metabolism, and suggest links to glucose and energy metabolism. Putative metabolic markers specific for ALS (e.g. creatinine and lactic acid) and PD (e.g. 3-hydroxyisovaleric acid and mannose) were identified, while several (e.g. creatine and BCAAs) were shared between ALS and PD, suggesting some overlap in metabolic alterations in these disorders.

High plasma levels of cholesterol have been suggested to be neuroprotective for the degenerative disease amyotrophic lateral sclerosis (ALS) and to be associated with increased survival time. The gene encoding cholesterol 27-hydroxylase, CYP27A1, was recently identified as a susceptibility gene for sporadic ALS. A product of this enzyme is 27-hydroxycholesterol. We investigated plasma samples from 52 ALS patients and 40 control subjects (spouses) regarding cholesterol homeostasis, lipid profiles, and coenzyme Q. Eleven of the patients carried mutations in C9orf72 and seven in SOD1. Plasma levels of 27-hydroxycholesterol were significantly lower in male patients with ALS than in controls. It was not possible to link the reduced levels to any specific mutation, and there was no significant correlation between 27-hydroxycholesterol and survival. With normalization for diet using the spouses, a correlation was found between survival and total cholesterol, very low density lipoprotein cholesterol, low density lipoprotein cholesterol, and coenzyme Q. We conclude that cholesterol, 24S-hydroxycholesterol, 25-hydroxycholesterol, 27-hydroxycholesterol and lipid profiles in plasma are of limited prognostic value in individual ALS patients.

There is a need for biomarkers for early diagnosis, development and evaluation of treatment efficacy in amyotrophic lateral sclerosis (ALS). We aimed to investigate if pre-analytical factors induce artefacts in metabolomic data of cerebrospinal fluid (CSF) from patients with ALS. CSF from 16 patients was studied using a statistical experimental design protocol with the following parameters: storage temperature (-80 degrees C/ - 20 degrees C), type of collection tube (polypropylene/polystyrene), and time delay from collecting to freezing (0, 10, 30, 90, 150 min). Gas chromatography-mass spectrometry was used to analyse CSF from 12 of the patients while CSF from one patient was analysed with nuclear magnetic resonance spectroscopy. The extent of CO(2) evaporization from CSF collected in tubes of different sizes at different temperatures and with/without lid were studied in three addtional patients. We found that alterations in storage temperature affect the metabolite composition of CSF more than any other studied pre-analytical parameter. CO(2) evaporization may induce artefacts in the metabolome by increasing the pH. In conclusion, minimization of evaluated artefacts can be obtained by collecting the CSF directly into tubes with tightly sealed lids in N(2)(l) and after freezing transfer of the tubes to -80 degrees C to minimize evaporation of CO(2).

Amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) are protein-aggregation diseases that lack clear molecular etiologies. Biomarkers could aid in diagnosis, prognosis, planning of care, drug target identification and stratification of patients into clinical trials. We sought to characterize shared and unique metabolite perturbations between ALS and PD and matched controls selected from patients with other diagnoses, including differential diagnoses to ALS or PD that visited our clinic for a lumbar puncture. Cerebrospinal fluid (CSF) and plasma from rigorously age-, sex- and sampling-date matched patients were analyzed on multiple platforms using gas chromatography (GC) and liquid chromatography (LC)-mass spectrometry (MS). We applied constrained randomization of run orders and orthogonal partial least squares projection to latent structure-effect projections (OPLS-EP) to capitalize upon the study design. The combined platforms identified 144 CSF and 196 plasma metabolites with diverse molecular properties. Creatine was found to be increased and creatinine decreased in CSF of ALS patients compared to matched controls. Glucose was increased in CSF of ALS patients and alpha-hydroxybutyrate was increased in CSF and plasma of ALS patients compared to matched controls. Leucine, isoleucine and ketoleucine were increased in CSF of both ALS and PD. Together, these studies, in conjunction with earlier studies, suggest alterations in energy utilization pathways and have identified and further validated perturbed metabolites to be used in panels of biomarkers for the diagnosis of ALS and PD.

We here present our predictive metabolomics approach for screening and comparing metabolomics data from human cerebrospinal fluid (CSF) generated by gas chromatography-time of flight mass spectrometry (GC-TOFMS). The approach is based on a combination of hierarchical multivariate curve resolution (HMCR) and manual integration of the GC–TOFMS data for quantification and identification of metabolites in multiple CSF samples. Chemometric data analysis, orthogonal partial least squares (OPLS), for multiple CSF sample comparisons. We show how the predictive feature of both HMCR and OPLS can be used for biomarker detection and verification as well as for diagnostic modelling. To exemplify the capability of the method we have used human CSF from two test subjects aliquoted into 44 tubes stored at either -80 °C or -20 °C as a model system. A total of 170 potential metabolites were resolved from the GC-TOFMS data using HMCR. OPLS modelling revealed a clear separation of the samples according to storage temperature, with a prediction accuracy of 100% using a test set.

A specific biochemical marker for early diagnosing and for monitoring disease progression in amyotrophic lateral sclerosis (ALS) will have important clinical applications. ALS is a heterogeneous syndrome with multiple subtypes with ill-defined borders. A minority of patients carries mutations in the Cu/Zn-superoxide dismutase (SOD1) gene but the disease mechanism remains unknown for all types of ALS. Using a GC-TOFMS platform we studied the cerebrospinal fluid (CSF) metabolome in 16 ALS patients with six different mutations in the SOD1 gene and compared with ALS-patients without such mutations. OPLS-DA was used for classification modeling. We find that patients with a SOD1 mutation have a distinct metabolic profile in the CSF. In particular, the eight patients homozygous for the D90A SOD1 mutation showed a distinctively different signature when modeled against ALS patients with other SOD1 mutations and sporadic and familial ALS patients without a SOD1 gene mutation. This was found irrespective of medication with riluzole and survival time. Among the metabolites that contributed most to the CSF signature were arginine, lysine, ornithine, serine, threonine and pyroglutamic acid, all found to be reduced in patients carrying a D90A SOD1 mutation. ALS-patients with a SOD1 gene mutation appear as a distinct metabolic entity in the CSF, in particular in patients with the D90A mutation, the most frequently identified cause of ALS. The findings suggest that metabolomic profiling using GC-TOFMS and multivariate data analysis may be a future tool for diagnosing and monitoring disease progression, and may cast light on the disease mechanisms in ALS.

Background: The composition of the metabolome in the cerebrospinal fluid of patients with amyotrophic lateral sclerosis is unknown. Previous studies of single metabolites have shown conflicting results.

Methods: Using GC-TOFMS and multivariate statistical modeling, we studied the metabolome signature of ~120 compounds in the cerebrospinal fluid of ALS patients stratified according to hereditary disposition and clinical subtypes of the disease.

Findings: Sporadic ALS has a heterogeneous metabolite signature in the CSF, in some patients being almost identical to controls. Familial ALS without SOD1 gene mutation is less heterogeneous than sporadic ALS. The metabolome of the CSF of the 17 ALS patients with a SOD1 gene mutation appeared as a separate homogeneous group. Analysis of single metabolites revealed that glutamate, pyroglutamate and glutamine were all reduced, in particular in patients with a familial disposition.

Interpretation: There are significant differences in the metabolite profile and composition among patients with familial ALS, sporadic ALS and patients carrying a mutation in the SOD1 gene suggesting that the neurodegenerative process in different subtypes of ALS may be different. Patients with a genetic predisposition to ALS have a more distinct signature than patients with a sporadic disease.

Background/Aim: The changes in the cerebrospinal fluid (CSF) metabolome associated with the fatal neurodegenerative disease amyotrophic lateral sclerosis (ALS) are poorly understood and earlier smaller studies have shown conflicting results.The metabolomic methodology is suitable for screening large cohorts of samples. Global metabolomics can be used for detecting changes of metabolite concentrations in samples of fluids such as CSF.

Methodology: Using gas chromatography coupled to mass spectrometry (GC/TOFMS) and multivariate statistical modeling, we simultaneously studied the metabolome signature of, 120 small metabolites in the CSF of patients with ALS, stratified according to hereditary disposition and clinical subtypes of ALS in relation to controls.

Principal Findings: The study is the first to report data validated over two sub-sets of ALS vs. control patients for a large set of metabolites analyzed by GC/TOFMS. We find that patients with sporadic amyotrophic lateral sclerosis (SALS) have a heterogeneous metabolite signature in the cerebrospinal fluid, in some patients being almost identical to controls. However, familial amyotrophic lateral sclerosis (FALS) without superoxide dismutase-1 gene (SOD1) mutation is less heterogeneous than SALS. The metabolome of the cerebrospinal fluid of 17 ALS patients with a SOD1 gene mutation was found to form a separate homogeneous group. Analysis of metabolites revealed that glutamate and glutamine were reduced, in particular in patients with a familial predisposition. There are significant differences in the metabolite profile and composition among patients with FALS, SALS and patients carrying a mutation in the SOD1 gene suggesting that the neurodegenerative process in different subtypes of ALS may be partially dissimilar.

Conclusions/Significance: patients with a genetic predisposition to amyotrophic lateral sclerosis have a more distinct and homogeneous signature than patients with a sporadic disease.

The neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) share some common molecular deficits including disruption of protein homeostasis leading to disease-specific protein aggregation. While insoluble protein aggregates are the defining pathological confirmation of diagnosis, patient stratification based on early molecular etiologies may identify distinct subgroups within a clinical diagnosis that would respond differently in therapeutic development programs. We are developing targeted multiple reaction monitoring (MRM) mass spectrometry methods to rigorously quantify CSF proteins from known disease genes involved in lysosomal, ubiquitin-proteasomal, and autophagy pathways. Analysis of CSF from 21 PD, 21 ALS, and 25 control patients, rigorously matched for gender, age, and age of sample, revealed significant changes in peptide levels between PD, ALS, and control. In patients with PD, levels of two peptides for chromogranin B (CHGB, secretogranin 1) were significantly reduced. In CSF of patients with ALS, levels of two peptides from ubiquitin carboxy-terminal hydrolase like protein 1 (UCHL1) and one peptide each for glycoprotein non-metastatic melanoma protein B (GPNMB) and cathepsin D (CTSD) were all increased. Analysis of patients with ALS separated into two groups based on length of survival after CSF sampling revealed that the increases in GPNMB and UCHL1 were specific for short-lived ALS patients. While analysis of additional cohorts is required to validate these candidate biomarkers, this study suggests methods for stratification of ALS patients for clinical trials and identifies targets for drug efficacy measurements during therapeutic development.