Inflammation and regulatory T cell genes are differentially expressed in peripheral blood mononuclear cells of Parkinson’s disease patients

Our aim was to identify the differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMC) of Parkinson’s disease (PD) patients and healthy controls by microarray technology and analysis of related molecular pathways by functional annotation. Thirty PD patients and 30 controls were enrolled. Agilent Human 8X60 K Oligo Microarray was used for gene level expression identification. Gene ontology and pathway enrichment analyses were used for functional annotation of DEGs. Protein–protein interaction analyses were performed with STRING. Expression levels of randomly selected DEGs were quantified by real time quantitative polymerase chain reaction (RT-PCR) for validation. Flow cytometry was done to determine frequency of regulatory T cells (Tregs) in PBMC. A total of 361 DEGs (143 upregulated and 218 downregulated) were identified after GeneSpring analysis. DEGs were involved in 28 biological processes, 12 cellular components and 26 molecular functions. Pathway analyses demonstrated that upregulated genes mainly enriched in p53 (CASP3, TSC2, ATR, MDM4, CCNG1) and PI3K/Akt (IL2RA, IL4R, TSC2, VEGFA, PKN2, PIK3CA, ITGA4, BCL2L11) signaling pathways. TP53 and PIK3CA were identified as most significant hub proteins. Expression profiles obtained by RT-PCR were consistent with microarray findings. PD patients showed increased proportions of CD49d+ Tregs, which correlated with disability scores. Survival pathway genes were upregulated putatively to compensate neuronal degeneration. Bioinformatics analysis showed an association between survival and inflammation genes. Increased CD49d+ Treg ratios might signify the effort of the immune system to suppress ongoing neuroinflammation.

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease and affects 1% of the population above 60 year-old 1 . Accumulation of α-synuclein in intracellular deposits named Lewy bodies and loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) are the core pathological features of the disease 2 . Depletion of dopamine causes dysfunction of basal ganglia and leads to the classical motor symptoms of PD including bradykinesia, rigidity, resting tremor and postural instability. PD is also associated with numerous non-motor symptoms that might precede motor symptoms 3 . Although diagnosis of PD mainly relies on clinical findings, moderate to severe dopaminergic neuron loss occurs before the onset of motor symptoms 4 . Thus, it is crucial to diagnose the disease at early stages and develop disease-modifying treatments that will reduce neurodegeneration. Understanding of cellular mechanisms leading to loss of dopaminergic neurons might provide a basis for identification of diagnostic biomarkers and improvement of new therapeutic strategies for PD. Etiopathogenesis of PD is not fully understood but environmental factors like pesticides, toxins, metals, head injury and certain drugs have received great attention for years 5 . However recent studies revealed that genetic susceptibility has a key role in PD pathogenesis and complex interactions of genetic and environmental factors are necessary for development of PD 6 . Monogenic forms of PD constitute < 10% of all cases but identification of these genes provides insight into molecular mechanisms underlying the disease 7 . Several studies established that oxidative stress, mitochondrial dysfunction and impairment of protein homeostasis contribute to disease mechanisms 8 . Neuroinflammation also seems to play a role in PD, but whether it induces harmful effects due to release of proinflammatory cytokines or has a protective role in terms of clearance of extracellular debris and production of trophic factors has not yet been established 9 . Evidence of CD4 + T cell infiltration in postmortem studies of PD brain specimens and increased expression of inflammatory cytokines have strengthened the idea that inflammation could be a prominent feature of PD 10,11 .
Microarray technology allows comparison of numerous gene expression profiles between healthy subjects and patients and thus provides a common strategy for analysis of neurodegenerative diseases. Several microarray studies have been carried out using both brain tissue and peripheral blood to date and gene expression profiles of PD have been established [12][13][14][15][16][17] . Blood-based gene expression analyses revealed altered expression of genes associated with ubiquitination/proteasomal system, mitochondrial function, oxidation and metabolism in PD patients as compared to controls 15 . Blood transcriptomics of drug-naïve sporadic PD showed increased expression of genes that are involved in leukocyte activation and epigenetic alterations that regulate chromatin remodelling 16 . Comparison of PD patients with LRRK2 mutation idiopathic PD cases and controls revealed altered expression of genes that are associated with Akt signaling pathway and B cell differentiation 18 . Tumor necrosis factor (TNF) signaling pathway was also found to be a key pathway involved in PD pathogenesis 19 . Analyses of differentially expressed gene profiles in experimental mouse model of MPTP induced PD revealed increased expression of systemic inflammation and programmed cell death genes 20 Zhang et al. reported decreased expression of complex I transcripts and increased expression of heat shock proteins and some anti-apoptotic gene groups in PD patients 21 . Durrenberger et al. showed upregulation of P2X7 and NOS pathways thereby emphasizing that extracellular ATP and reactive astrocytes are responsible of microglial activation and subsequent release of proinflammatory cytokines that contribute to dopaminergic cell death 22 . In another microarray study, expression levels of neuro-immune signaling related transcripts were found to be increased in nucleated blood cells of PD patients 23 . Overall, these results indicate importance of neuroinflammation in PD pathogenesis.
To bring light to possible pathological mechanisms underlying PD and discover biomarkers associated with progression of motor symptoms in PD, we identified differentially expressed genes through microarray and transcriptome studies. Our results pinpointed expression alterations particularly in inflammation and survival genes. Notably, peripheral blood ratios of a subset of regulatory T cells (Tregs) showed association with altered disability scores of PD.

Materials and methods
Patient selection. Thirty consecutive idiopathic PD patients who were diagnosed by movement disorders specialists according to the United Kingdom Parkinson's Disease Society Brain Bank Criteria and 30 controls with no prior history of neurological and inflammatory disease were enrolled ( Table 2). All patients were under dopaminergic drug treatment. Exclusion criteria were presence of accompanying inflammatory or autoimmune diseases and being under immunosuppressive treatment. Included patients were evaluated by a neurologist, and each patient received the Unified Parkinson Disease Rating Scale (UPDRS) and the Hoehn and Yahr (H&Y) Scale.
Microarray expression profiling and DEGs screening. Eighteen PD patients (12 males, mean age ± SD was 58.28 ± 9.45) and 18 control subjects (15 males, mean age ± SD was 48.54 ± 8.22) from the original group were enrolled for transcriptome studies. Mean years of disease duration of patients ± SD was 6.87 ± 4.08, mean total UPDRS scores ± SD was 34.94 ± 18.09, mean UPDRS III score ± SD was 17.50 ± 12.08 and mean H&Y score ± SD was 2.05 ± 0.64. Total RNA was extracted from whole blood samples by using Qiagen RNeasy (CatNo: 74104) kit according to the manufacturer's protocol. Assessment of total RNA quality was performed by the Agilent 2100 Validation of expression levels of DEGs. Expression levels of DEGs were confirmed by real time quantitative polymerase chain reaction (RT-PCR) studies for randomly selected 5 genes (PRKACB, TSC2, GATA2, PI3KCA, CASP3). Venous blood samples were collected in 10 ml EDTA containing tubes that were obtained from 8 randomly selected PD patients (3 males, mean age ± SD was 59.00 ± 3.62) and 8 age and sex matched healthy controls (4 males, mean age ± SD was 60.00 ± 3.46). Mean years of disease duration ± SD of patients was 6.86 ± 3.34, mean total UPDRS scores ± SD was 39.25 ± 22.64, mean UPDRS III score ± SD was 22.75 ± 17.17, mean H&Y score ± SD was 2.25 ± 0.65. Peripheral blood mononuclear cells (PBMCs) were isolated from whole blood by using Ficoll density gradient centrifugation and cryopreserved within FBS and 10% DMSO at liquid nitrogen until assayed. RNA was isolated from frozen PBMCs by using RNA isolation commercial kit (Jena Bioscience, Total RNA Purification Kit, PP-210L). Purity assessment was determined by O.D. ratios of 260/280 and 260/230 and concentrations of isolated RNAs were detected with Thermo Scientific Nanodrop 2000. cDNA was synthesized with a transcription kit (Jena Bioscience, PCR511) from 2 µl RNA with the concentration of 100 ng/ ml by using Bio-Rad Thermal Cycler according to the manufacturer's protocol. The quantitative real time PCR (qRT-PCR) assay was performed on an Agilent Stratagene 3005P system. Each reaction was run in 10 μl reaction mixture containing 1 μl of cDNA (50 ng/μl), 10 pmol/µl of forward and reverse primer sets for each specific gene (Table 1) by using Sybr green method (PCR master kit, Jena Bioscience, qPCR GreenMaster with UNG/lowROX kit, PCR306). Beta-actin (ACTB) was used as a normalization reference gene for quantitating the relative levels of gene expressions. Relative gene expressions were analyzed by 2 −ΔΔCt method 27 .
Immunophenotyping by flow cytometry. To validate the findings of microarray study, a flow cytometry study was conducted in order to determine peripheral immune cell phenotype in PD patients. Frozen PBMCs obtained from 20 PD patients (mean age ± SD was 55.36 ± 5.41 mean age, 12 males) and 20 age and sex matched healthy controls (p = 0.111 and p = 0.744 respectively) from the original group (mean age ± SD 53.55 ± 7.63, 13 males) (8 PD and 8 controls were selected from subjects that were enrolled in RT-PCR study). Mean years of disease duration ± SD of patients was 7.17 ± 2.73, mean total UPDRS scores ± SD was 45.15 ± 19.04, mean UPDRS III score ± SD was 26.15 ± 14.63 mean H&Y score ± SD was 2.1 ± 0.55. Frozen PBMCs were used for extracellular

PPI network construction. PPI network of proteins that were encoded by most significantly upregulated
DEGs were involved in p53 and PI3K/Akt signaling pathways. TP53 and PIK3CA were identified to be most significant hub proteins (Figs. 1 and 2).

Validation of gene expressions with RT-PCR.
For validation of the microarray data, expression levels of 5 genes (PRKACB, TSC2, GATA2, PI3KCA, CASP3) that were randomly selected among the upregulated DEGs were quantified by RT-PCR analysis using peripheral blood samples of randomly selected 8 PD patients and 8 healthy controls. In consistency with microarray data, expression levels of selected genes were elevated 14.31 ± 1.12) were comparable between PD and control groups. Percentage of CD3 + CD4 + CD25 + T cells and CD3 + CD8 + CD25 + T cells were slightly increased in PD group without attaining statistical significance. Frequency of Tregs, which were defined as CD4 + CD25 + CD127 low T cells 28 , showed no differences among patient and control groups. For further evaluation of effects of CD49 expression on suppressive capacity of Tregs, subpopulations of CD49d positive and negative cells were evaluated within CD4 + CD25 + CD127 low Tregs. Frequency of CD49d + Tregs were significantly higher in PD patients than in controls (51.33 ± 5.187 vs 35.33 ± 4.035, p = 0.002). To assess functional immunosuppressive capacity of Tregs, we compared frequencies of IL-10 producing cells within CD4 + CD25 + CD127 low and CD4 + CD25 + CD127 low/-CD49d + subtypes between PD and controls. There were no differences between two groups in terms of frequencies of IL-10 producing cells for both subtypes (Fig. 3). Proportions of CD4 + CD25 + CD127 low CD49d + Tregs were found to be negatively correlated with total   www.nature.com/scientificreports/   www.nature.com/scientificreports/ www.nature.com/scientificreports/ UPDRS score in PD patients (p = 0.028, r = -0.491) (Fig. 4). There was no correlation between CD49d + Treg frequencies versus age or disease duration.

Discussion
PD is an important health care problem that causes serious impairment in daily life quality especially in elderly population. The disease can only be treated symptomatically with the current treatment strategies and the degenerative process cannot be prevented. An important reason for this is that significant loss of neurons has already occurred at the stage of diagnosis. Improved understanding of the pathophysiology of PD and the mechanisms underlying neuronal loss are crucial for early diagnosis and development of disease-specific treatments. Our results revealed that genes that are most differentially expressed between PD patients and healthy controls are particularly associated with survival pathways and inflammation. p53 and PI3K/Akt pathways were the most profoundly affected survival-associated pathways. Apoptosis is crucially involved in physiological and pathological conditions such as oxidative stress and severe DNA damage. Genotoxic stress in the cell is recognized by ataxia telangiectasia mutated (ATM) kinase and ATM-and Rad3-related (ATR) kinase proteins, which provide phosphorylation of murine double minute gene 2 (MDM2), a ubiquitin-ligase that enhances p53 degradation 29,30 . This posttranslational change causes inactivation of MDM2 while activating p53 31 . Activated p53 stops the cell cycle in order to eliminate DNA damage. In cases that the DNA damage cannot be corrected, p53 initiates programmed cell death. p53-induced proapoptotic genes cause release of cytochrome-c from the mitochondrial membrane. Cytochrome-c also interacts with p53-induced APAF-1 protein to activate the caspase cascade 32 . p53 suppresses the Akt/mTOR pathway both by enhancing tuberous sclerosis complex 2 (TSC2) transcription and inducing synthesis of PTEN protein that degrades PIP3 33,34 . In postmortem studies and experimental models of PD, apoptosis has been shown as an important mediator of dopaminergic cell death 35 . p53, an important tumor suppressor gene, plays a critical role in the process of apoptosis by transcriptional control of the genes associated with cell death and Bcl2 family interaction 36 . SNpc of PD brains shows increased p53 expression 37 , deletion of DJ1 causes p53-mediated loss of dopaminergic neurons in experimental models, p53 inhibition has a neuroprotective effect and p53 activates transcription of the alpha synuclein gene (33)(34). Thus, overexpression of the p53 pathway might be one of the essential factors involved in the pathogenesis of sporadic PD.
PI3K-Akt signaling pathway is a highly conserved cascade that promotes cell survival and proliferation and plays important role in synaptic plasticity. Numerous growth factors and cytokines carry out their intracellular effects via PI3K pathway 38 . In our study, PPI analysis showed that phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PI3KCA) protein has a central role in this network. The PI3K enzyme catalyzes the synthesis of an important secondary messenger phosphatidylinositol (3,4,5)-trisphosphate (PIP3) molecule from the phosphatidylinositol 4,5-bisphosphate (PIP2). PIP3 activates phosphorylation of the serine threonine kinase Akt 39 . mTORC1, one of the downstream proteins of this signaling pathway, is a protein kinase complex that acts as a sensor for metabolic status of the cell and plays an important role in decision-making in the direction of survival or apoptosis 40 . Akt eliminates inhibition of mTORC1 by phosphorylating the TSC2 protein, which has an inhibitory effect on mTORC1. Activation of mTORC1 increases anabolic activity in the cell and suppresses autophagy. Defects in this pathway have been associated with neurodegeneration in diseases such as Alzheimer and Huntington disease [40][41][42] . In an experimental study, TSC2 expression was shown to be increased in response to synuclein accumulation in the transgenic mouse model, but no significant difference was found between TSC2 expression levels in the brain of human PD cases and controls 43 . In another study, it has been shown that proteins regulating autophagy prevent the ubiquitination of TSC2 in the neurotoxin-induced animal model and cause autophagy in dopaminergic neurons through this mechanism 44 . Activation of autophagic mechanisms may protect dopaminergic neurons from synuclein toxicity by increasing synuclein degradation 45 . In our study TSC2 gene expression was increased in the PD group and this upregulation might be due to the effort to activate the autophagy process and could be a therapeutic target, especially in the early stage of the disease. www.nature.com/scientificreports/ Other members of the PI3K pathway that are upregulated in PD patients are also profoundly associated with the disease. Akt regulates the expression of Bcl-2 like 11 (BCL2L11) through phosphorylation of forkhead phosphorylation of transcription factors (FOXO) 46 . BCL2L11, also known as Bim (Bcl 2-interacting mediator of cell death), is a potent pro-apoptotic protein that can bind anti-apoptotic proteins with high affinity 47 . In the MPTP-induced PD mouse model, Bim expression is increased regionally in the midbrain and remains high during dopaminergic neuron death 48 . VEGFA is the biologically most active isoform of VEGF growth factor family that potently promotes proliferation and migration of vascular endothelial cells and controls vascular permeability 49,50 . Although VEGFA is primarily identified as an angiogenesis factor, recent studies have implied neurotrophic, neuroprotective and chemoattractant roles, as well 51 . Upregulated expression of VEGF gene has been reported in reactive astrocytes within substantia nigra of PD patients 52 . This upregulation is likely to have occurred as a compensatory mechanism to enhance neurogenesis and to maintain microcirculation.
In this study, we found increased expression levels of several inflammation-related genes. Proteomics analysis suggested that upregulation of at least some of the inflammation genes (e.g. IL-2RA and IL-4R) was by virtue of the enhanced expression of the PI3K/Akt pathway, which is intimately associated with inflammatory pathways. Early evidence of involvement of inflammation in PD pathogenesis has come from the studies that revealed presence of human leukocyte antigen DR (HLA-DR) positive reactive microglia in SNc of PD patients. Subsequent studies showed that increased expression of proinflammatory cytokines released from activated microglia contributes to the degeneration of dopaminergic neurons and activation of nuclear factor kappa B (NF-κB) pathway in PD patients and experimental models of PD [53][54][55][56][57] . Consistent with these findings increased expression of genes encoding proinflammatory cytokines has been found in SN of PD patients 58 .
Inflammatory factors may display both hazardous and neuroprotective roles in PD. As an example, IL-4, an anti-inflammatory cytokine, may both suppress microglial activity and modulate neurogenesis 59,60 . In the lipopolysaccharide-treated rat model, increased endogenous IL-4 synthesis caused elevation of pro-inflammatory cytokines of microglial origin thereby contributing to degeneration of vulnerable dopaminergic neurons 61 . By contrast, infiltrating IL-4 producing CD4 + T cells in the CNS have been shown to improve neuronal survival and achieve axonal healing through the Akt signaling pathway 62 . Similarly, in experimental autoimmune encephalitis models, externally administered IL-4 has been shown to improve axonal damage via IL-4 receptor (IL-4R)mediated signaling pathway 63 . While PD is typified with Th1-type inflammation 64 , IL-4 may shift the balance in favor of Th2-type inflammation and thus may regulate neuroinflammation in PD. IL-4 also prevents neuronal death and induces neuronal growth through binding IL-4 receptor alpha (IL4-Rα) on neurons 62 . Thus overexpression of IL4-R in PD might be a compensating countermeasure to suppress the ongoing neuroinflammation.
Although the role of the peripheral immune system in PD-related neuroinflammation has not yet been entirely elucidated, infiltrating CD4 + and CD8 + T lymphocytes have been suggested to contribute to neurodegeneration 65 . CD3 + T cells, which have been found in close proximity to glial cells in brains of DLB patients and α-synuclein transgenic mice, have been suggested to participate in activation of glial cells 66 . In vitro studies suggested that CD4 + /CD25 − effector T cells promote microglial activation and contribute to neurodegeneration while CD4 + / CD25 + Tregs might be inhibiting microgliosis 67 . Furthermore, adoptive transfer of CD3 activated Tregs to mice with MPTP-induced PD has provided greater than 90% protection of the nigrostriatal system 68 . It is thought that dysfunction of Tregs may contribute to PD pathogenesis by enhancement of neuroinflammation or by impairment of tolerance to neuronal antigens 69 . However, the underlying mechanisms of decreased effectiveness of regulatory T cells in PD patients have not been elucidated.
IL2RA (CD25) gene encodes the alpha chain of the receptor complex of IL-2, an important cytokine associated with immune homeostasis and self-tolerance. IL-2 acts as a growth factor for T cells 70 . CD25 + Tregs suppress the inflammatory response and autoimmunity presumably by competing for and consuming the IL-2 cytokine. The effector CD4 + T cell apoptosis induced by Treg cells through cytokine deprivation has been shown to require the presence of BIM proapoptotic protein 71 , which was upregulated in our study. Dopaminergic cell damage induced by 1-methyl-4-phenylpyridinium (MPP+) is prevented by Tregs. Suppression of microglial oxidative stress and inflammation by Tregs might likely be responsible for this protective mechanism.
There are controversial results for proportion of Tregs in PD. While in some studies Tregs were found to be increased in PD, some other researchers reported that Tregs were decreased or not altered in PD patients [72][73][74] . Saunder et al. found that Tregs from PD patients had reduced ability to suppress effector T cells while proliferative capacity of CD4 + T cells did not change. Besides, α4β1 + CD4 + T cells were elevated slightly but not significantly in PD patients 75 . α4β1 integrin is an adhesion molecule that facilitates the migration of immune system cells into the central nervous system. The alpha chain of α4β1 integrin is encoded by ITGA4 (CD49d) gene. The ability of CD49d + Tregs to suppress effector T cells was found to be weaker compared to CD49d negative T cells in vitro 76 . In our study, CD49d expression was increased in PD and also PD patients displayed higher frequencies of CD49d + Tregs in the peripheral blood. Notably, PD patients with higher frequencies of CD49d + Tregs showed trends towards displaying lower UPDRS scores, indicating a neuroprotective role of this Treg subset in PD presumably through suppression of infiltrating T cells in the brain. These results could also be explained by reduction of CD49d + Tregs by increased age and disease duration. However, no correlation could be found between these factors ruling out this assumption.
It is known that neuroinflammation induced by activation of astrocytes and microglia with subsequent dysfunction of endotelhial cells contributes to PD pathogenesis. Besides central inflammation, peripheral proinflammatory profile with altered CD4 + /CD8 + T cells ratios and Treg cells might facilitate neurodegeneration 77 . Several transcriptome studies that were performed in different platforms with different tissues have highlighted the importance of inflammatory pathways in PD pathogenesis 78 . These studies have also shown that even different regions of PD brain may show altered immune gene expression profiles 79 . Highly diverse DEG profiles have been obtained in previous transcriptome studies that were recently conducted with peripheral blood samples of sporadic PD patients with a special emphasis on immune system-related genes ( Table 7) 16 80 By contrast, immune-related genes that were significantly altered in our study and not reported in previous studies were VEGFA and ITGA4.
To further understand the mechanism, by which CD49d + Tregs might be suppressing neuroinflammation in PD, we assessed Tregs with anti-inflammatory IL-10 production and could not find difference between PD patients and controls. Nevertheless, Tregs might be operating through TGF-β rather than IL-10 production in PD and this assertion should be further investigated in future studies. Another limitation of our study in this context was not assessing pro-inflammatory cytokine-producing T cell subtypes and thus the inflammation status of our PD patients and suppression capacity of CD49d + Tregs could not be duly investigated. Other limitations of our study were the low sample size for both gene expression analyses and validation studies. Although there were numerous gene expression studies with larger cohorts that revealed possible role of immune system in the pathogenesis of PD, the data we have obtained with a limited number of samples may provide a basis for discussing Treg-PD relationship in functional terms.

Conclusion
In brief, we detected altered expression levels of genes involved in survival, apoptosis and inflammation related pathways in PD patients. We also found clues indicating the functionality of a subset of Tregs. Our results emphasize once again the complex interactions between neuronal apoptosis and inflammation in neurodegeneration. The exaggerated proinflammatory responses and/or insufficient anti-inflammatory mechanisms may result in the loss of vulnerable dopaminergic neurons. The increased detection of CD49d expression, which is expected to be low in Tregs with high suppressive capacity, suggested that dysfunctional Tregs may participate in PD pathogenesis. Nevertheless, increased CD49 expression may be a factor that positively affects the prognosis of the disease in the advanced stages through as yet unknown mechanisms.

Data availability
All data generated or analysed during this study are included in this published article and its supplementary information files. www.nature.com/scientificreports/