Abstract

Introduction

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disorder of unknown cause arising from progressive degeneration of motor neurons and resulting in paralysis and death, usually within 2–4 years from diagnosis. Its incidence is between 1.5 and 2.5 per 100.000 per year: approximately 90% of cases are sporadic and the remaining 10% are familial. The diagnosis is mostly based on clinical assessment with a history of progression of symptoms and is thus made with a delay of about a year from symptom onset, quite likely beyond the therapeutic window of a disease-modifying drug. Moreover, the clinical course varies widely. No ALS biomarkers are currently in clinical use, but they would be valuable to support early diagnosis, monitor disease progression, and assess the efficacy of any new treatment [1].

The pathological process in ALS is now recognized as extending beyond motor neurons [2]–[8], so it can be regarded as a multi-cellular/multi-systemic disease. In particular, peripheral blood mononuclear cells (PBMC) display traits of the disease such as down-regulation of Bcl-2 [9], [10], increased nitrative stress [11], intracellular calcium dysregulation [4] and glutamatergic dysfunction [12], suggesting that they can be a useful source of disease biomarkers.

In a complex disorder it is unlikely that an individual molecule may serve as a clinically useful biomarker. Therefore, proteomic approaches and multiple measurements are likely to be necessary to identify ALS subjects with a worthwhile degree of accuracy. In fact, the most promising candidate biomarkers have been so far combinations of proteins identified in cerebrospinal fluid (CSF) [13]–[15]. However, when the same proteins were searched in plasma either were not present or were not significantly different in comparison with controls [13], [16]. Whereas CSF is considered the ideal source for identifying biomarkers in neurological diseases because of its proximity to the affected tissue, it involves an invasive sampling, that limits large-scale validation studies and thus introduction into clinical practice. PBMC are readily accessible clinical samples and offer a series of advantages over serum/plasma and CSF. Bio-fluids have wide inter-individual variability and a broad range of protein abundance, which make them difficult to analyze by proteomic approaches [17], [18]. The cellular proteome is relatively stable, less complex to analyze and gives direct information on alterations of cellular pathways, hence insights into possible pathogenic mechanisms.

We here reported a proteome-based strategy to identify and validate disease biomarkers in PBMC. By using this procedure we found a panel of proteins that are closely associated with ALS and have high potential in clinical applications and translational medicine. Moreover, our results support the use of PBMC of sporadic ALS (sALS) patients for mechanistic studies.

Results

Proteomic analysis and validation

Figure 1 schematically shows the proteome-based strategy used to identify and validate protein biomarkers of ALS in PBMC. In the first phase, PBMC of healthy controls and sALS patients with two levels of disease severity (Table S1), low, with a ALS functional rating scale revised (ALSFRS-R) score>24 (ALS>24), and high, with a ALSFRS-R score≤24 (ALS≤24), were analyzed by 2D DIGE (Fig. 1A). The analysis, done with 11 pooled samples for each group, detected a total of 129 differential protein spots in the three experimental groups (Table S2). From these spots we used mass spectrometry to identify 71 corresponding proteins (Fig. 1B) that were the candidate protein biomarkers (Tables S3, S4). We classified these proteins in different categories based on their most recognized function (Table 1). Some of the proteins were identified in multiple spots, at lower Mw or different pI than the ones expected (Table S3). These are fragments of the protein or post-translationally modified isoforms.

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Figure 1

Proteome-based strategy to identify and validate specific biomarkers of ALS in PBMC.

(A) PBMC of healthy controls and sALS patients with two levels of disease severity, low, ALS>24, or a high one, ALS≤24, were analyzed by 2D DIGE. Samples were pooled for analysis (n=11 for each group). The candidate biomarkers, 71 differentially expressed proteins, were identified by mass spectrometry (MS). Validation was done on 14 proteins by dot blot analysis with single samples from an independent set of sALS patients, healthy and non-ALS neurological disorder controls. We obtained five protein biomarkers that significantly distinguish ALS patients from healthy and non ALS neurological controls and three proteins that associate with disease progression. The 14 PBMC protein biomarkers were also measured in G93A SOD1 rats: 5 of them were similarly regulated in the patients and animal model (translational biomarkers). (B) Representative Sypro-Ruby stained 2D gel of the PBMC proteome. The numbered spots correspond to the differentially expressed proteins listed in Table 1; (C) Validation by dot blot analysis was done with commercially available antibodies except for the in-house developed anti-actin^NT antibody (Figures S1 and S2). A representative dot blot with the anti-actin^NT antibody and quantification of the immunoreactive signals are shown. The box-plot shows relative immunoreactivity (IR) in ALS>24 (n=30) (yellow box), ALS 24 (n=30) (red box) patients and healthy controls (n=30) (white box). The bottom and top of the boxes are the lower and upper quartiles, respectively, the lines inside the boxes indicate the median and the ends of the whiskers represent the minimum and maximum of all the data. *p<0.05 versus controls as assessed by univariate logistic regression.

Table 1

The candidate protein biomarkers.

Spot	Protein name	Uniprot1
Energy metabolism
1	ATP synthase subunit beta	P06576
2	Triosephosphate isomerase	P60174
3–6	Phosphoglycerate kinase 1	P00558
7–10	Alpha-enolase	Q8WU71
11–13	Fructose-bisphosphate aldolase A	P04075
14	Glyceraldehyde-3-phosphate dehydrogenase	P04406
15	L- Lactate dehydrogenase A chain	P00338
16	L-Lactate dehydrogenase B chain	P07195
Redox regulation
17	Flavin reductase	P30043
18	Peroxiredoxin-2 (PRDX2) 2	P32119
19	Peroxiredoxin-6	P30041
20	Glutathione S-transferase omega-1 (GSTO1)	P78417
21	Superoxide dismutase [Mn]	P04179
22	Protein DJ-1	Q99497
23	Chloride intracellular channel protein 1 (CLIC1)	O00299
Protein folding and degradation
24–25	Heat shock cognate 71 kDa protein (HSC70)	P11142
26	78 kDa glucose-regulated protein	P11021
27	Peptidyl-prolyl cis-trans isomerase A (CypA)	P62937
28	Protein disulfide-isomerase (PDI)	P07237
29–32	Protein disulfide-isomerase A3 (ERp57)	P30101
33–34	Endoplasmic reticulum protein ERp29	P30040
35	Calreticulin (CALR)	P27797
36	Proteasome activator complex subunit 1 (PA28a)	Q06323
Cytoskeleton-associated
37–43	Actin	P60709
44–48	Vinculin	P18206
49–51	Moesin	P26038
52	Tropomyosin alpha-4 chain	P67936
53	Alpha-actinin-1	P12814
54–55	Actin-regulatory protein CAP-G	P40121
56	F-actin capping protein subunit-alpha 1	P52907
57–58	Talin-1	Q9Y490
59	Transgelin-2	P37802
60	Filamin-A	P21333
61	Giantin	Q14789
Inflammatory response
62	Group XIIA secretory phospholipase A2	Q9BZM1
63	Annexin A2	P07355
64	Leukocyte elastase inhibitor	P30740
65	Interleukin-1 receptor-associated kinase 4 (IRAK4)	Q9NWZ3
DNA/RNA binding
66–67	Far upstream element-binding protein 1 (FUBP1)	Q96AE4
68	Heterogeneous nuclear ribonucleoproteins A2/B1 (ROA2)	P22627
69	Probable ATP-dependent RNA helicase DDX41	Q9UJV9
Others
70	AH receptor-interacting protein	O00170
71	Spindle and kinetochore-associated protein 1	Q96BD8

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Fold changes and mass spectrometry data are reported in Tables S3, S4.

¹Entry from the Uniprot Knowledgebase database;

²In bold are the proteins selected for further validations.

We then validated selected proteins by dot blot analysis on single samples of an independent set of 60 sALS patients, ALS>24 (n=30) and ALS≤24 (n=30), and healthy controls (n=30) (Table S5). From the panel of the candidate biomarkers we validated 12 proteins (PRDX2, GSTO1, CLIC1, HSC70, CypA, PDI, ERp57, CALR, PA28a, IRAK4, FUBP1, ROA2) for the following reasons: they are also expressed in the central nervous system (CNS), they are associated with neurodegenerative processes, some of them specifically with ALS [11], [19]–[24], and are easily detectable by commercially available specific antibodies. In the same validation analysis we also measured actin^NT, whose level was already found high in PBMC of a small cohort of sALS patients and G93A SOD1 transgenic rats [11] as well as in the spinal cord of the G93A SOD1 mouse model of familial ALS [25]; and TDP-43 identified as the major component of ubiquitinated inclusions in brains of patients with ALS and frontotemporal lobar degeneration [26] and found accumulated in the cytoplasm of PBMC in a group of ALS patients [27]. We confirmed that all 14 proteins can significantly distinguish healthy controls from sALS patients (Fig. 2A, Table 2, Tables S6, S7). As a negative control for the dot blot assay we used SOD1, that was one of the protein spot that did not change in the 2D DIGE analysis. Multivariate logistic analysis showed that CLIC1, actin^NT and ROA2 were the proteins most associated with ALS in comparison with healthy controls, with 98% discriminatory power (AUC 0.981) (Fig. 2A). For the combination of these three proteins, the most convenient cut-off generated a sensitivity of 91% and a specificity of 96%. In all 60 sALS patients the levels of the 14 protein biomarkers were independent of sex and age.

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Figure 2

Validation of the 14 selected protein biomarkers versus healthy controls and non-ALS neurological controls: statistical analysis.

Validation on single PBMC samples from ALS patients, healthy and non-ALS neurological controls was done by dot blot analysis. Receiver operating characteristics (ROC) curves and analysis of the area under the curve (AUC) were used to find the discriminatory power for proteins showing a significant association with ALS (A,C) or with disease severity (B). Results were expressed as odds ratios (OR) and 95% confidence intervals (95% CI). A 95% CI not including the value of 1 indicates a statistically significant result. All probability values were two-sided and p<0.05 was considered significant. (A) Univariate logistic regression: healthy controls (n=30) versus ALS, ALS>24 (n=30) and ALS≤24 (n=30). All 14 proteins were significantly associated with ALS (p values in bold type). CLIC1, actin^NT and ROA2 were significant in multivariate analysis (highlighted in grey): a ROC curve for the combination of the three proteins and relative AUC is shown; (B) Univariate logistic regression: ALS>24 (n=20) versus non-ALS neurological controls (n=23). CALR, CLIC1, IRAK4, GSTO1, CypA had significant associations with ALS (in bold type). IRAK4 and CypA were significant in multivariate analysis (highlighted in grey): a ROC curve for the combination of the two proteins and relative AUC is shown.

Table 2

Validation of 14 selected protein biomarkers in patients and healthy controls.

Protein	controls	ALS>24	ALS≤24	ALS>24 vs controls*	ALS≤24 vs controls*	ALS≤24 vs ALS>24*
CALR	2.8±0.7	4.9±2.8	4.4±2.3	1.8	1.6	−1.1
TDP-43	4.1±1.6	5.2±2.1	6.8±2.6	1.3	1.7	1.3
PRDX2	0.9±0.5	1.4±0.7	2.0±1.1	1.6	2.2	1.4
PDI	1.0±0.3	1.6±0.7	1.8±0.7	1.6	1.8	1.1
ERp57	2.5±0.7	3.8±1.4	4.7±2.4	1.5	1.9	1.2
PA28a	4.1±4.5	1.4±1.1	1.6±1.6	−2.9	−2.6	1.1
CLIC1	0.4±0.3	0.8±0.4	0.9±0.5	2.0	2.3	1.1
IRAK4	1.0±0.5	2.2±1.5	2.4±1.5	2.2	2.4	1.1
FUBP1	1.7±1.5	0.6±0.6	0.9±1.0	−2.8	−1.9	1.5
GSTO1	1.2±0.7	0.7±0.5	0.6±0.4	−1.7	−2.0	−1.2
HSC70	0.8±0.5	1.7±1.2	2.3±2.3	2.1	2.9	1.4
CypA	1.4±0.7	3.4±2.7	2.0±1.2	2.4	1.4	−1.7
ActinNT	0.7±0.3	1.5±0.8	1.6±0.6	2.1	2.3	1.1
ROA2	2.9±1.8	5.7±2.7	6.4±3.0	2.0	2.2	1.1
SOD1	0.3±0.1	0.3±0.2	0.3±0.1	1.0	1.0	1.0

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Validation was done by dot blot assay with the specific antibodies on single PBMC samples from ALS patients, ALS>24 (n=30) and ALS≤24 (n=30), and healthy controls (n=30); mean ± SD of the relative immunoreactivity of the specific antibody normalized to the actual amount of proteins loaded on the membrane as detected after Red Ponceau staining;

*, -fold change as the mean increase (positive) and decrease (negative) in protein concentration in samples from ALS patients in comparison with healthy controls or between the two levels of disease severity.

CALR, CLIC1, IRAK4, GSTO1 and CypA are ALS-specific biomarkers

We verified the specificity of the 14 biomarkers with PBMC samples from patients with neurological disorders that in some cases may resemble ALS, e.g. some peripheral neuropathies (Table S8). We analyzed our multiprotein biomarkers by dot blot in ALS>24 patients (n=20) and controls with neurological disorders (n=23) (Table 3). Univariate logistic analysis showed that CALR, CLIC1, IRAK4, GSTO1 and CypA were associated with ALS (Fig. 2B). Multivariate logistic analysis showed that IRAK4 and CypA were the proteins most associated with ALS rather than neurological disorders, with 91% discriminatory power (AUC 0.905) (Fig. 2B). For the combination of these two proteins, the most convenient cut-off generated a sensitivity of 96% and a specificity of 79%. It is interesting to note that an equally high level of TDP-43 was also detected in patients with neurological disorders (Table 3).

Table 3

Validation of the 14 biomarkers in patients and non-ALS neurological controls.

Protein	controls	ALS>24	ALS>24 vs NC*
CALR	4.9±2.8	3.2±1.3	−1.5
TDP-43	2.2±0.6	2.0±0.5	−1.1
PRDX2	0.5±0.2	0.6±0.2	1.2
PDI	0.9±0.4	0.8±0.4	−1.1
ERp57	0.1±0.1	0.1±0.1	1.0
PA28a	0.3±0.2	0.3±0.2	1.0
CLIC1	2.9±2.1	1.5±0.8	−1.9
IRAK4	0.7±0.2	1.0±0.4	1.4
FUBP1	2.0±1.3	2.8±2.0	1.4
GSTO1	0.8±0.6	0.5±0.3	−1.6
HSC70	3.4±2.6	2.3±2.2	−1.5
CypA	4.5±2.2	2.6±1.0	−1.7
ActinNT	2.8±1.3	3.0±1.2	1.1
ROA2	1.9±0.9	1.7±1.0	−1.1

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Validation was done by dot blot assay with the specific antibodies on single PBMC samples from ALS patients, ALS>24 (n=20), and non-ALS neurological controls (NC) (n=23); mean ± SD of the relative immunoreactivity of the specific antibody normalized to the actual amount of proteins loaded on the membrane as detected after Red Ponceau staining;

*, -fold change as the mean increase (positive) and decrease (negative) in protein concentration in samples from ALS patients in comparison with neurological controls.

CypA, TDP-43 and ERp57 as biomarkers for disease progression

We found that CypA, TDP-43 and ERp57 levels significantly differed in ALS>24 and ALS≤24 patients (Figure 3, Table 2), indicating that these proteins can discriminate between patients with high and low disease severity. Multivariate logistic analysis showed that ERp57 was the most associated with more severe ALS, with 89% discriminatory power (AUC 0.893) (Fig. 3). For ERp57, a threshold of 2.7 relative immunoreactivity generated a sensitivity of 93% and a specificity of 70%. We next examined in a pilot longitudinal study whether CypA, TDP-43 and ERp57 changed over time. We collected three longitudinal PBMC samples from an independent set of 13 sALS patients over a period of six months and used a statistical model for repeated measures to assess the effect of time on protein levels, detected by dot blot assay. The patients had on average a disease duration of 21±10 months, a 33±5 ALSFRS-R score at the first draw and a 28±7 ALSFRS-R score at the third draw (Table S9). The level of all the three protein biomarkers showed a significant increase within six months from the first PBMC collection and for TDP-43 already within 3 months (Fig. 4). As a negative control, in the same set of samples we measured SOD1, which did not significantly change over time (Fig. 4).

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Figure 3

Protein biomarkers that associate with disease severity.

Analyses of the 14-protein biomarkers were done on single PBMC samples from ALS patients, ALS>24 (n=30) and ALS≤24 (n=30), by dot blot analysis. ROC curves and analysis of the area under the curve (AUC) were used to find the discriminatory power for proteins showing a significant association with disease severity. Results were expressed as odds ratios (OR) and 95% confidence intervals (95% CI). A 95% CI not including the value of 1 indicates a statistically significant result. All probability values were two-sided and p<0.05 was considered significant. Univariate logistic regression: TDP-43, ERp57 and CypA gave a significant association with disease severity (in bold type). Multivariate analysis indicated that ERp57 was the protein most closely associated with disease severity (highlighted in grey). A ROC curve for ERp57 is shown.

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Figure 4

Longitudinal analysis of protein biomarkers CypA, ERp57 and TDP-43.

Graphs show relative immunoreactivity (IR) for the indicated proteins measured by dot blot assay in PBMC of sALS patients (n=13) over a period of six months. PBMC were collected at t=0 (T1, white column), at t=3 months (T2, grey column) and at t=6 months (T3, black column). SOD1 was used as a negative control. Immunoreactivity was normalized to the actual amount of protein loaded, detected after Red Ponceau staining. Data are the means ± SEM of relative immunoreactivity. *, significantly different (p<0.05) from T1 as assessed by repeated measures ANOVA followed by Tukey's multiple comparison test; #, significantly different (p<0.05) from T2 as assessed by repeated measures ANOVA followed by Tukey's multiple comparison test.

CypA, GSTO1, FUBP1, CLIC1 and actin^NT are translational biomarkers of ALS

Translational biomarkers are molecules that can be assessed in both human and animal models. To test whether our 14 PBMC proteins were translational biomarkers, their level was measured in PBMC of a transgenic G93A SOD1 rat model of ALS, at pre-symptomatic and symptomatic stages of the disease, in comparison with samples from non transgenic rats by immunoblotting. Five out of fourteen protein biomarkers, CypA, GSTO1, FUBP1, CLIC1 and actin^NT, showed similar changes in PBMC of sALS patients and transgenic rats (Fig. 5). It is interesting to note that FUBP1 was one of the least specific ALS biomarkers in PBMC of sporadic patients. It is possible that this protein is more associated with SOD1 mutation-induced alterations and is more informative for the mutant SOD1 fALS forms. The translational biomarkers were also investigated in the rat spinal cord at a presymptomatic and symptomatic stages of the disease (Fig. 5). Lumbar spinal cords were sectioned in ventral and dorsal horns to investigate whether proteins alterations were associated or not with motor neuron dysfunction and degeneration. In ventral horns, all of them changed similarly to PBMC already at a presymptomatic stage except for CLIC1, up-regulated only at a symptomatic stage. In dorsal horns, the proteins did not change with the progression of the disease and if compared with controls (Figure S3), indicating that protein alterations observed in ventral horns are specifically associated with motor neuron pathology. In conclusion, CypA, GSTO1, FUBP1, CLIC1 and actin^NT are translational biomarkers that might be markers of multi-cellular/multi-systemic alterations underlining pathogenic events both in the human sporadic and animal mutant SOD1-linked disease forms.

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Figure 5

Analysis of protein biomarkers in the G93A SOD1 transgenic rat model: comparison with sALS patients.

Human PBMC (left column): box-plot shows relative immunoreactivity for the indicated proteins measured by dot blot assay in ALS>24 (n=30) (grey box) and ALS≤24 (n=30) (dark grey box) patients as percentage of healthy controls (control) (n=30) (white box). *, significantly different (p<0.05) from control (univariate logistic regression). Rat PBMC (middle column): box-plot shows relative immunoreactivity for the indicated proteins measured by WB (except for actin^NT, measured by dot blot) in PBMC lysates (15 µg) of presymptomatic (pres) (n=6) and symptomatic (symp) G93A SOD1 (n=6) rats as percentage of non transgenic (control) (n=8) rats. Protein level values were normalized to actin loading control. *, significantly different (p<0.05) from controls (one-way ANOVA followed by Newman-Keuls multiple comparison test). Rat spinal cord (right column): box-plot shows relative immunoreactivity for the indicated proteins measured by dot blot in ventral horn tissue lysates of presymptomatic (pres) (n=6) and (symp) G93A SOD1 (n=6) rats as percentage of non transgenic (control) (n=8) rats. Immunoreactivity was normalized to the actual amount of protein loaded, detected after Red Ponceau staining. *, significantly different (p<0.05) from control (one-way ANOVA followed by Newman-Keuls multiple comparison test).

Discussion

A number of gene expression studies have demonstrated the utility of PBMC as a source of biomarkers in neurological disorders [28]–[30]. This is the first study that describes a highly feasible strategy to identify and validate multiprotein biomarkers in PBMC, potentially applicable to several neurological/neurodegenerative diseases. Protein profiles are directly connected to changes in molecular pathways related to health and disease, therefore have the potential to accurately monitor the progression of the disease or the response to a treatment.

We have previously shown that PBMC undergo immunophenotypic changes in sALS patients [10]. We have now identified a panel of protein biomarkers in these cells that are associated with sALS with high discriminatory power. These PBMC proteins are easily measurable in large-scale immunoassays aimed at developing diagnostic/prognostic tests for clinical use. The great advantages of such an in vitro test is low invasiveness for the patient compared to CSF tests, the consequent greater availability of samples for large clinical studies, including longitudinal ones, and the simple laboratory procedures involved.

The ideal diagnostic marker should detect disease before clinical diagnosis, which is highly challenging for a rare and sporadic disease. ALS patients very often see the specialized neurologist only months after the first symptoms, when they are unquestionably ill. It is therefore very difficult to test and validate the applicability of biomarkers in preclinical diagnosis. Our PBMC protein biomarkers seems to be promising to support prompt clinical diagnosis, since all the 14 validated proteins can distinguish with high significance ALS patients with low disability from healthy controls (Table S6). PBMC biomarkers could be measured on patients after as early as 5 months up to 108 months from symptom onset, and with high (from 45) and low (up to 10) ALSFRS-R scores (Table S5, S8, S9). Now large-scale validations are needed, in which data will be verified in a prospective cohort with analysis of the biomarkers at the time of symptom presentation. In the G93A SOD1 rat model of ALS, alterations of the level of CypA, GSTO1, FUBP1, CLIC1 and actin^NT are detected before disease onset. It is possible that some of these biomarkers may predict the onset of SOD1-linked familial ALS. This potential application will be also considered in future analysis.

Up to 10% of patients initially diagnosed as having ALS are false positive [31], [32]. A similar percentage is false negative and undergoes inappropriate medical or surgical procedures [33], [34]. Thus, there is a need for biomarkers that distinguish ALS with high accuracy from neurological disorders that in some cases may resemble it, e.g. some peripheral neuropathies that are treatable and do not have a fatal prognosis. We found that there are PBMC protein biomarkers that significantly distinguish ALS from the group of neurological disorders considered in our study. These are chaperones (CALR, CypA), proteins involved in redox homeostasis (GSTO1, CLIC1) and immune responses (IRAK4). IRAK4, which has no previous association with ALS, has a central function in innate immunity [35].

Finally, multivariate analysis helped us in defining the most convenient combination of protein biomarkers that could be potentially used in clinics (i) to support diagnosis (CLIC1, actin^NT and ROA2), (ii) to contribute to differential diagnosis of ALS from other neurological conditions (CypA and IRAK4), and (iii) to determine disease severity (ERp57).

There are no precise measures of ALS disease progression that allow for short-term monitoring of the disease and assessment of treatment efficacy. In clinical trials survival time is therefore used as the primary measure of outcome. This requires large number of patients followed over a long period of time making ALS clinical trials very expensive. A panel of biomarkers that can reliably assess disease progression would enable a substantial reduction of the costs of the clinical trial and accelerate therapy development in ALS. ERp57, CypA and TDP-43, that were able to discriminate between patients with high and low disease severity, were selected for a pilot longitudinal study and proved to be good candidates for such applications. Large longitudinal studies are now needed to further validate the use of these proteins in clinical practice.

The pathogenesis of sALS is largely unknown. The concept of PBMC as a window into the CNS has been already proposed for several neurological disease states [28]–[30], [36], [37]. CNS and immune cells communicate through multiple mechanisms and have several similarities in receptor expression and transduction processes [38]. We therefore hypothesized that PBMC protein profiles could help to elucidate pathways underlying ALS etiology. Indeed, some of the protein biomarkers identified in PBMC of sALS patients were previously found as hallmarks of disease in CNS. Studies in spinal cord tissues of sALS patients showed that PDI and ERp57 were up-regulated [20], CypA and HSC70 were accumulated in the detergent-insoluble fraction [39], HSC70 was present in hyaline inclusions [24], and TDP-43 was identified as the major component of the ubiquitinated inclusions [26].

The protein profile changes detected in PBMC of ALS patients are suggestive of possible pathogenic mechanisms. For instance, up-regulation of endoplasmic reticulum (ER) chaperones (PDI, ERp57, CALR) is a typical cellular response to ER stress that triggers the unfolded protein response leading eventually to cell death [40]. The increased level of a nitrotyrosine-linked protein, actin^NT, is indicative of nitrative stress [41]. Alterations in CypA, GSTO1, PRDX2 suggest disturbances in cellular redox regulation [42]–[45]. It is important to note that all these pathogenic alterations were previously reported in the spinal cord of sALS patients and mutant SOD1 animal models [19], [20], [25], [46]–[49]. ROA2 belongs to the family of heterogeneous nuclear ribonucleoproteins that participates to several RNA-related biological processes such as transcription, pre-mRNA processing, mRNA transport to the cytoplasm and translation [50]. It is also a binding partner of TDP-43 and seems to be crucial for at least one of its putative functions [51]. The up-regulation of ROA2 and TDP-43 in PBMC of both ALS>24 and ALS≤24 patients may underline aberrant RNA processing events that are now emerging as central in ALS and other neurological disorders [52]. These specific intracellular alterations would not be detectable from the protein profiles of CSF or plasma. Neuroinflammation, which is characterized by activated microglia and infiltrating peripheral blood immune cells, is a prominent pathological feature in ALS [53]. It is possible to speculate that such consistent protein profile changes in immune cells may influence their infiltration and/or interaction with microglia and neurons, thus upsetting the delicate balance between neuroprotection and neurotoxicity. In summary, all these data endorse the use of PBMC for further in vitro mechanistic studies. Experimental models for the sporadic form are not available and all mechanistic studies are done with transgenic cells and animals expressing one of the mutant genes linked to familial ALS. Studies with PBMC would have the advantage to consider the influence of the genetic background of the patient.

Translational biomarkers, that link responses between human and animal model, are of particular interest because their role in the pathogenesis can be investigated in detail in the animal model where they can also offer important preliminary information for clinical trials. We found that CypA, GSTO1, FUBP1, CLIC1 and actin^NT are translational biomarkers. Moreover, all of them except for CLIC1 are altered in the ventral horn spinal cord of SOD1 G93A rats before disease onset, suggesting a possible involvement in pathways that trigger the disease. Further mechanistic studies in the animal models with these proteins are now warranted.

In conclusion, we identified and verified a panel of highly promising protein biomarkers of ALS in PBMC that may be useful in clinical studies, helping elucidate pathogenic mechanisms and pin-pointing pathways to tackle for future therapeutic interventions. The fact that our protein biomarkers are easily measurable in accessible clinical samples using straightforward immunoassays makes them attractive candidates for true multi-centric large-scale validations and eventually introduction into clinical practice.

Materials and Methods

Supporting Information

Acknowledgments

Footnotes

References