Background
Currently, the diagnosis of Parkinson’s disease (PD) is based mainly on clinical criteria [
1]. In addition the evaluation of the clinical status and evolution of PD are based on examination of symptoms, utilizing structured scoring systems (Unified Parkinson’s Disease Rating Scale, (UPDRS) [
2], Short Parkinson Evaluation Scale, (SPES), SCales for Outcomes in PArkinson’s diseases– (SCOPA) [
3,
4] and the Hoehn and Yahr (H&Y) staging scale [
5]. Although PD can be accurately diagnosed in patients with a typical presentation and positive response to levodopa with a sensitivity of 93% [
6], differential diagnosis from other entities presenting parkinsonism (e.g. essential tremor, progressive supranuclear palsy (PSP), multisystem atrophy (MSA), corticobasal degeneration (CBD)) may be challenging. Imaging studies using positron emission tomography (PET) with
18 F]-Dopa, single photon emission tomography (SPECT) with
123I]-β-CIT or diffusion-weighted MRI could improve differential diagnosis of parkinsonism [
7‐
9], but cost-effectiveness remains a problem.
Furthermore, these tools do not provide a specific and sensitive enough PD diagnosis [
10]
. The discovery of mutations linked to familial PD and the implementation of microarray-based gene expression profiling during the past decade, has provided additional clues for the pathophysiology of sporadic PD as well as potential molecular targets that may be of relevance to the disease [
11‐
16]. Our previous gene expression study conducted in post-mortem substantia nigra (SN) obtained from sporadic PD patients identified a cluster of genes that were most differentially expressed in sporadic parkinsonian SN, by a factor of ≥1.5, compared to non-diseases controls [
11]. The transcripts were mainly related to DA transmission and metabolism, and protein handling/degradation mechanisms previously known to be involved in the pathophysiology of the disease. Examples include
SKP1A (p19, S phase kinase-associated protein 1A), a component of the largest class of E3 ubiquitin ligases, SCF (
Skp1,
Cullin 1, a substrate recognizing
F-box protein and Rbx1) [
17,
18],
HSPA8 (heat shock 70-kDa protein 8, encoding chaperone Hsc-70) [
19], and 19 S proteasomal protein
PSMC4/
S6b/
TBP7, whose levels were decreased in PD. Also, aldehyde dehydrogenase family 1, subfamily A1 (
ALDH1A1) involved in the degradation of aldehyde derivatives of DA, and vesicular monoamine member 2 (VMAT2) were down-regulated.
Recent studies have shown the feasibility of studying peripheral (cerebrospinal fluid (CSF), blood and urine) signatures or biomarkers for potential diagnosis and early detection of PD [
20] such as alpha-synuclein and DJ-1 protein in the CSF [
21‐
23]. Serum uric acid appears to be the first molecular factor linked to a decreased risk of PD [
24,
25] and to inversely correlate with clinical and radiographic progression of typical PD [
26]. Furthermore, increasing evidence indicates that peripheral tissue shares significant protein/gene expression similarities to inaccessible central nervous system (CNS) tissues [
27,
28] and thus may offer valuable surrogate markers for neuropsychiatric disorders. For instance, a recent large serum proteomic study with psychiatric patients has identified a number of proteins belonging to pathways previously shown to be involved in the pathophysiology of either depression or schizophrenia, such as growth factors, cytokines and neurotrophins [
29]. In a microarray gene profiling study with blood PD tissue, it was demonstrated a panel of genes associated with PD risk, some of them involved in pathobiologically relevant disease processes of the ubiquitin– proteasome pathway system (UPS), mitochondrial function, and apoptosis [
27]. More recently, a genome-wide pathway meta-analysis (meta-GSEA) with PD tissues has particularly identified a set of genes controlling cellular bioenergetics and mitochondria biogenesis that were shared by both brain and blood [
30]. Using a similar, but less comprehensive approach of integrating openly available and new PD microarray data, a panel of genes was identified to be commonly expressed in brain and blood samples [
31]. These findings suggest that blood and brain neuronal cells might have a common regulatory mechanism for gene expression.
The seven genes chosen for the study form part of the core of 20 gene transcripts most significantly altered in PDSN from sporadic PD patients [
11]. Here we analyze their expression in peripheral blood from early PD patients to identify a signature that could support the diagnosis of the disease.
Discussion
The results of this study support our hypothesis that there are blood gene biomarkers that can distinguish early PD patients from normal control subjects. Notably, 38 out of the 62 Parkinson cases in the mild/early cohort were
de novo and so, not treated with any antiparkinsonism drug when the blood samples were obtained while the rest were collected during the first year of medication. This suggests that the genetic signature could be an early diagnostic marker for PD. In support, the classifier model performed equally well in early stage
de novo PD samples, producing a similar ROC AUC value to that obtained with the entire early PD cohort (de novo and medicated), indicating that patient medication had no significant effect on the PP of the classifier for PD risk and that the model is stable throughout the two PD groups. Supporting this concept, it was recently shown in a population of asymptomatic LRRK2 mutation carriers, that reduced CSF amyloid β and tau species correlated with lower striatal dopaminergic function as determined by PET [
32], suggesting that they may serve as potential biomarkers even in asymptomatic phases of the disease. The performance of the gene model was validated in an independent cohort of patients at advanced PD stage where all individuals were correctly classified as PD, while it fully discriminated PD from a group of individuals affected with AD (considered the most common neurodegenerative disease). Giving that misdiagnosis occurs normally at the initial PD stage, the 100% sensitivity obtained with the long-term PD cohort support the feasibility of the biomarker panel to differentiate with certainty between PD and non-PD. Further studies will determine the ability of the panel to differentially diagnose idiopathic PD from patients with other forms of Parkinsonism, such as PSP and MSA.
One main challenge in the development of biological markers is to minimize the number of genes in the classification model while still achieving a high classification rate. The present biomarker signature identified a minimal set of transcripts in blood that has a high discriminating power to categorize the PD early group and to positively/negatively classify the advanced PD and AD cohorts.
A model with fewer genes is likely to yield better generalization (less number of free variables) and optimization of diagnosis. We have found that five out of the seven gene transcripts previously reported to have been changed in sporadic PDSN [
11], were found altered in blood of mild/early PD. Our findings argue in support of the view that changes in peripheral blood may have relevance to mechanisms occurring in brain of PD patients and indicate that at least some of the gene expression alterations occurring in PD are not exclusive to the brain, but are expressed also in peripheral blood tissue. Indeed, a large proportion of the genes encoded in the human genome have detectable levels of transcripts in circulating blood cells [
33]; When coming into contact with brain tissue, circulating blood cells may provide information concerning the pathological environment of the PD brain.
Gene expression correlation analysis indicates a significant association in blood from healthy control individuals between
SKP1A and five gene transcripts:
HIP2, ALDH1A1 PSMC4 HSPA8 and
EGLN1, while it was absent in early PD, suggesting a functional coordinative role for Skp1. Skp1 takes part in the ubiquitin-proteasome/E3-ligase SCF complex, acting in a module-like manner: Skp1 can interact with several F-box proteins, which play an indispensable role in the selection of target proteins for degradation [
17]. Thus, a reduced activity of Skp1 may play a role in the development of PD by impairing the timely degradation of a wide array of proteins, promote their deposition and affect the function of dopaminergic (DAergic) neurons. Skp1, together with the chaperone Hsc-70 encoded by
HSPA8, the proteasomal ATPase subunit PSMC4, the EGLN1-encoded prolyl hydroxylase and the huntingtin-interacting protein Hip2, are intimately connected to processing/degradation of proteins by UPS/lysosomal- mediated degradation [
17‐
19,
34‐
37]. Further evidence for a possible functional connection between the panel genes is provided by our recent finding showing that silencing
SKP1A in the SN-derived murine cell line SN4741 induced a parallel down-regulation in the transcripts of
ALDH1A1 and
HSPA8[
38]. Aldh1 was found to be expressed highly and specifically in DA cells of the SN and ventral tegmental area (VTA) [
39] having a role in the neutralization of toxic aldehyde derivatives of DA [
34]. These highly reactive, neurotoxic aldehydes can accumulate in case of decreased levels of Aldh1, as occurs in SNpc of PD [
39,
40], and can promote neuronal death. The fact that the five genes comprising the signature, as a group, play important roles in PD neuropathology and are significantly correlated in blood form healthy subjects, add a biological significance to the findings.
Supporting the rationale of identifying molecular changes in peripheral blood that may respond to the pathology in the brain of sporadic PD, Grunblatt et al. [
41] recently reported a cluster of four genes in blood tissue that discriminated between PD and healthy controls. One of them,
ALDH1A1 was also detected in our gene signature, independently confirming part of our results. Further support comes from Scherzer et al. [
27] who demonstrated a panel of eight genes involved in relevant PD processes such as the UPS, mitochondrial function and apoptosis in whole blood tissue from a heterogeneous cohort of relatively early-staged PD individuals, that correlated with PD risk. It is worth noting that despite the difference in the study design, e.g., the use of large-scale microarrays comprising the whole genome, the restricted eight-gene signature included
HIP2, also found by us, as a surrogate for PD. In our study, we have performed multi-step logistic regression analysis, which is commonly applied in biomarker research. This procedure recruits in each step the most significant gene discriminating between PD and control in relation to the prior step, thus taking into consideration the cumulative impact of the gene group on the PD risk. In Scherzer’s study, the genes were individually rank-ordered according to the absolute value of their correlation coefficient with PD, disregarding the correlation between their expression levels.
Another major discovery of this investigation is that the PP values of the five-gene signature were accentuated in patients at late PD stage, suggesting a potential for the model to assess disease severity. One relevant point is what could be the biological meaning of this observation. It can be conjectured that the peripheral gene transcriptional changes may reflect evolution of pathogenic processes during PD progression. In analogy, Shi et al. [
42] have described a panel of seven CSF proteins that could aid in PD diagnosis and differential diagnosis. Among these, an increase in CSF fractalkine, along with decreased Aβ1–42 levels, correlated with a higher UPDRS score in cross-sectional samples and in a set of longitudinally collected PD samples from the DATATOP study.
When examining the relative quantity of each gene individually at the cross-sectional level, we demonstrated a similar transcriptional pattern for SKP1A, ALDH1A, PSMC4 and HSPA8 in the two PD cohorts compared to normal controls or AD groups, suggesting that these transcripts are altered at early stages of the disease and not affected by disease progression. However, at this stage, we cannot determine whether the selective elevation of HIP2 demonstrated only in PD patients at advanced stage of disease, can reflect a disease evolution. Despite the strength of the present findings, there are some issues yet to be addressed. At this point the cross-sectional nature of this study does not allow making a correlation between gene expression and clinical symptoms that may point to the clinical state. Longitudinal studies will establish whether the gene panel can serve as a marker for PD risk or its progression. Although we have initially focused on seven out of the 20 gene transcripts most altered in sporadic PD brains, it is likely that the other risk genes could be also relevant.
Competing interests
MBY received royalties from TEVA pharmaceutical for the development of rasagiline. EG institution received grant funds from Verein Zur Durchfhurung Neurowissensschftlicher Tagungenand and from Hirnliga.
Authors’ contributions
LM, JMR, MBH and SAM designed the study and prepared the statistical analysis plan. SAM wrote the manuscript with assistance from LM, JMR and MBY. LM, JMR, MBY and SAM contributed to data analyses. YB assisted with technical methods. JMR, ED, UB, RC, DF, EG, PR, CJ and JA identified patients or controls and were responsible for collecting data from them. The authors wish it to be known that, in their opinion, the first 2 authors should be regarded as joint first authors. All authors read and approved the final manuscript.