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Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease
Parkinsonism and Related Disorders xxx (2015) 1e6
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Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease Haixia Ding a, 1, Zhen Huang b, 1, Mengjie Chen b, Cheng Wang b, Xi Chen b, Jiangning Chen b, c, *, Junfeng Zhang b, c, ** a
Department of Geriatric, Nanjing Medical University First Affiliated Hospital, No. 300, Guangzhou Road, Nanjing, China State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China State Key Laboratory of Analytical Chemistry for Life Sciences and Collaborative Innovation Center of Chemistry for Life Sciences, Nanjing University, Nanjing, China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 23 July 2015 Received in revised form 30 October 2015 Accepted 16 November 2015
Background and objective: Parkinson's disease (PD) is the second most common age-related neurodegenerative disorder after Alzheimer's disease. The aim of this work was to determine whether the differences of serum miRNAs profiling could distinguish PD patients from healthy individuals. Methods: We collected serum samples from 106 sporadic PD patients and 91 age/gender-matched healthy controls. Serum miRNAs were analysed by Solexa sequencing followed by a qRT-PCR examination. The qRT-PCR assay, which was divided into two phases, was used to validate the expression of miRNAs screened by Solexa sequencing. Receiver operating characteristic (ROC) curve analysis and clustering analysis were performed to determine the diagnostic usefulness of the selected miRNAs for PD. Results: In this study, we generated a profile of 5 serum miRNAs: miR-195 was up-regulated, and miR185, miR-15b, miR-221 and miR-181a were down-regulated. Conclusion: This group of five miRNAs can precisely distinguish PD patients from health individuals and may be used as a potential serum-based biomarker for the diagnosis of PD. © 2015 Elsevier Ltd. All rights reserved.
Keywords: Parkinson's disease Serum miRNA
1. Introduction Parkinson's Disease (PD), which is characterized by resting tremor, bradykinesia, rigidity and postural instability, is the second most common age-related neurodegenerative disorder [1]. Currently, a PD diagnosis mainly depends on neuroimaging and clinical manifestations using the UK PDS Brain Bank Criteria, Unified Parkinson's Disease Rating Scale and the modified HoehneYahr stage [2].These diadynamic criteria are subjective and can be applied only when motor features appear. However, PD clinical manifestations do not appear until 50%e70% of the dopaminergic neurons have been lost, causing patients to lose the opportunity for
* Corresponding author. School of Life Sciences, Nanjing University, Nanjing, 210093, China. ** Corresponding author. School of Life Sciences, Nanjing University, Nanjing, 210093, China. E-mail addresses: [email protected] (J. Chen), [email protected] (J. Zhang). 1 The two authors contributed equally to this work.
early treatment [3]. Therefore, seeking novel biomarkers that are objective and can be quantified may contribute to the diagnosis of PD, especially at the early stages of the disease process. MicroRNA (miRNA), an abundant class of small non-coding RNA, primarily cause the degradation or translational suppression of target mRNAs. It is reported that PD patients and patients with other neurodegenerative diseases have significantly different tissue miRNA profiles [4]. Several miRNAs (miR-133b, miR-34c, miR-107, miR-433 and miR-205) have been observed to be aberrantly expressed in the brain tissue and are involved in neuron differentiation, apoptosis and neurite outgrowth [5]. Therefore, these miRNAs are considered as novel biomarkers and potential therapy targets. The brain tissues from patients with neurodegenerative disorders are normally collected at autopsy; however, this invasive technique makes sample collection from living patients impossible. Recent reports have also demonstrated that miRNAs remain stable in the blood and may be used as novel non-invasive biomarkers for several types of diseases; thus, we supposed that there was a unique serum miRNA expression profile in PD patients that could be a new indicator [6]. The aim of this study was to investigate the
http://dx.doi.org/10.1016/j.parkreldis.2015.11.014 1353-8020/© 2015 Elsevier Ltd. All rights reserved.
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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H. Ding et al. / Parkinsonism and Related Disorders xxx (2015) 1e6
profile of serum miRNAs and to explore its clinical value as a novel biomarker for PD.
we used a combination of let-7d/g/i as an endogenous reference gene for the normalization of serum miRNAs. The relative levels of miRNAs were calculated using the 2DDCq method.
2. Methods 2.1. Study population and blood sampling The present study included 106 PD patients and 91 healthy individuals. All PD patients were diagnosed at the Jiangsu province hospital and the Nanjing brain hospital. Patients with cancer, significant cardiac dysfunction or diabetes were excluded from this study. UPDRS-III scores and a modified HoehneYahr scale were used to evaluate the disease stages and the living quality of the PD patients. Ninety-one individuals from a large pool of individuals seeking a routine health checkup at the Jiangsu province people's hospital and showing no evidence of disease were selected as healthy controls. All samples were collected from consenting individuals according to protocols approved by the ethics committee of each participating institution. The controls were matched to the patients by age and sex (Supplementary Tables 1e2). The persons who performed the following experiments were blinded to the diagnostic result. All blood samples were collected, centrifuged and then stored according to previous report [7]. 2.2. RNA isolation For the Solexa sequencing of the serum samples, equal volumes of serum from each sample (6 mL each) were pooled separately to form patient and control sample pools (each pool contained 90 mL), and total RNA was extracted with TRIzol reagent (Life Technologies, Carlsbad, CA, USA) according to a previous report. The resulting RNA pellet was dissolved in 20 mL of RNase-free water and then stored at 80 C for following examination. For the qRT-PCR assay, total RNA was extracted from 100 mL of the serum sample with a one-step phenol/chloroform purification protocol as previously described [8].
2.5. Data analysis All of the statistical analyses were performed using the Statistical Analysis System software SPSS 19.0. The data were presented as the mean ± SEM for miRNAs or mean 6 SD for other variables. A Student's t-test or two-sided c2 test was used to compare the differences in variables between the two groups. A P value 0.05 was considered as statistically significant. For miRNAs, we constructed Receiver operating characteristic (ROC) curves and calculated the area under the ROC curves (AUC) to evaluate the predictive power of the candidate miRNA for PD. 3. Results 3.1. Solexa screening of serum miRNAs in PD A multiphase case-control study was constructed to find markedly changed levels of serum miRNAs for PD patients (Fig. 1). In the initial biomarker screening stage, two pooled serum samples from 15 PD patients and 15 controls underwent Solexa sequencing to identify miRNAs that showed significant differences between the PD cases and matched controls. Supplementary Table 1 summarizes the demographic and clinical features of the patients for Solexa sequencing. According to the miRbase 16.0 version,a total of 1123 miRNAs were screened by Solexa sequencing. 138 and 159 miRNAs could be detected in healthy controls and PD patients, respectively
2.3. Solexa sequencing technology Solexa sequencing was performed according to a previous report. Briefly, after PAGE purification of small RNA molecules (<30 nucleotides) and ligation of a pair of Solexa adaptors to the 50 and 30 RNA ends, the RNA molecules were amplified using primers to the adaptor regions for 17 cycles. Fragments that were approximately 90 bp (small RNA þ adaptors) were isolated from an agarose gel. Purified DNA was used for cluster generation and sequencing analysis using Illumina's Solexa sequencer according to the manufacturer's instructions. Image files were generated by the sequencer and were processed to produce digital-quality data. After masking the adaptor sequences and removing the contaminated reads, clean reads were processed for in silico analysis as previously reported [8]. 2.4. Individual qRT-PCR assay of serum miRNAs A TaqMan probe-based qRT-PCR assay was performed to quantify the serum miRNA levels according to the manufacturer's instructions (7500 Sequence Detection System, Applied Biosystems) as described previously [8]. All reactions, including no-template controls, were performed in triplicate. It was proved that let-7d, let-7g and let-7i (let-7d/g/i) were more stable than other reference genes (U6, miR-16, RNU48 and RNU44) and the more accurate data could be obtained after normalization to a combination of let7d/g/i [9]. We also observed the low variability of let-7d/g/i between PD patients and healthy controls (Supplementary Fig. 1), so
Fig. 1. The overview of the experiment design.
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
H. Ding et al. / Parkinsonism and Related Disorders xxx (2015) 1e6
(Supplementary Table 3). In term of the sensitivity and accuracy, the cutoff point for miRNA fold change was set at 1.5 fold. The miRNAs that met two criteria (Solexa sequencing detected 300 copies in the patient or control group and a minimum 1.5-fold change observed between PD patients and healthy individuals) were selected for further qRT-PCR testing. Based on these criteria, we built a list of 15 differentially expressed miRNAs (Supplementary Table 4). 3.2. Validation of different expressed miRNAs via RT-PCR assay As the Solexa sequencing assay was performed on pooled samples from PD patients and healthy controls, the individual differences might have influenced the accuracy of the Solexa sequencing. Thus, the selected miRNAs from the Solexa sequencing assay were further validated by the qRT-PCR assay. In the training set, the miRNAs were examined in a separated group of individual serum samples from 45 PD patients and 36 healthy individuals (Supplementary Table 5). Only miRNAs with a mean change 1.5, a P value < 0.001 and a negative control CT > 32 were selected. Based on these criteria, a list of 5 miRNAs (miR-195, miR-15b, miR-221, miR-181a and miR-185) was generated that showed a significant change between the PD patients and the healthy controls. These 5 miRNAs were further examined by qRT-PCR in a larger group consisting of 61 patients and 55 matched controls. Consistent with the results from the training set, the serum level of miR-195 was significantly higher in the PD patients than in the control individuals; meanwhile, the levels of the other 4 miRNAs (miR-15b, miR-221, miR-181a and miR-185) were lower in the PD patients than in the healthy controls (Table 1). The results in Fig. 2 show the different levels of the 5 miRNAs in the 106 PD patients and 91 healthy individuals belonging to the training and validation sets. 3.3. Unsupervised clustering analysis An unsupervised clustering method that was unbiased to the clinical annotations was used to investigate the different concentration patterns for several miRNA panels in the PD and control serum samples. We observed that the 5-member panel (miR-195, miR-15b, miR-221, miR-181a and miR-185) (Supplementary Fig. 1) could reliably discriminate the PD samples from the control samples. The serum miRNA profile correctly classified 41 (91.1%) of 45 PD cases (abbreviated as P) and 32 (88.9%) of 36 control samples (abbreviated as C) in the training set (Supplementary Fig. 1). In the validation set, 58 PD cases and 48 controls were correctly divided into 2 main groups; only 3 PD cases and 7 controls were misclassified (Supplementary Fig. 2). 3.4. ROC curve analysis The ROC curves that were constructed to compare the relative levels of the 5 miRNAs for the PD patients and the healthy controls yielded the following AUCs: miR-195, 0.733 (95% CI, 0.611e0.804); miR-15b, 0.897 (95%CI, 0.854e0.940); miR-221, 0.854 (95% CI, 0.798e0.911); miR-181a, 0.822 (95% CI, 0.762e0.881); miR-185,
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0.820 (95% CI, 0.760e0.879). Using the optimal cutoff value, we obtained the following sensitivity and specificity values, respectively: miR-195, 68.9% and 75.8%; miR-15b, 76.9% and 86.8%; miR221, 75.8% and 85.8%; miR-181a, 70.3% and 84.0%; miR-185, 70.0% and 83.0%. As shown in Fig. 3, we also used the ROC curves to evaluate the diagnostic value of the 5-member miRNA profiling system. The AUC for the miRNAs panel was 0.919 (95% CI, 0.877e0.961). With an optimal cutoff value in which the sum of the sensitivity and specificity was maximal, the specificity was 77.4%, and the sensitivity was 93.4%. 4. Discussion In the present study, we performed the profiling of serum miRNA of PD patients through Solexa sequencing from pooled serum samples as the initial stage of analysis. Based on the qRT-PCR assay, 5 differentially expressed miRNAs were identified, and the combination of these miRNAs could effectively separate the PD patients from the healthy individuals, which achieved the highest predictive biomarker performances. Currently, physicians diagnose PD primarily based on neurological examination and neuroimaging, and both of these examination standards are subjective and lacking in sensitivity. Meanwhile, the observation of Lewy bodies in the midbrain by histopathological analysis can confirm a diagnosis of Parkinson's disease, but brain tissue cannot be obtained from living people [10]. Cerebrospinal fluid (CSF) can reflect some of the pathophysiological changes that occur in the brain, and number of CSF biomarkers (ɑsynuclein and DJ-1) are being used in clinical trials to monitor the progression of PD [11]. However, CSF can be collected only via lumbar puncture, and the inconvenience of this invasive collection process restricts its use and influences the examination accuracy. In contrast, blood is an ideal candidate for biomarker detection as special types of biological substances are released from the tissues under pathologic conditions. Moreover, blood sampling is fast, easy, more cost-effective and minimally invasive. Several studies using various techniques including metabolomics, proteomics and gene expression profiling are underway to explore blood-based markers in PD patients [12]. Therefore, the feasibility of using blood-based biomarkers is one of the most promising methods for PD diagnosis. Our laboratory and other groups were the first to demonstrate that miRNAs are quite stable in serum and consistent among individuals in the same species [6,13]. The stability of miRNAs in blood may be attributed by the protection of binding proteins or microvehicles. It has been indicated that both circulating blood cells and other cells from different tissues secrete microvehicles, which encapsulate miRNAs [14]. Pathological conditions may influence the secretion of microvehicles and change internal miRNA content. Thus, the pathophysiological condition of the body can be quickly reflected by the alternation in the blood miRNA profile. As miRNA in the blood can be directly detected, it may serve as a sensitive indicator of various diseases. Several studies have already begun to analyse the miRNA levels in body fluids (including serum, plasma and cerebrospinal fluid) or cells circulating in the fluid of PD patients. The earliest study
Table 1 miRNA levels in serum samples from PD patients compared to healthy controls in the validation set. miRNA
Control CT (n ¼ 55)
hsa-miR-195 hsa-miR-185 hsa-miR-221 hsa-miR-15b hsa-miR-181a
29.17 27.65 26.58 30.12 27.59
± ± ± ± ±
1.66 1.41 1.38 1.34 1.38
PD CT (n ¼ 61) 30.91 31.36 30.44 35.27 31.92
± ± ± ± ±
1.15 1.74 1.70 2.14 2.47
Fold change of CT (PD/control) relative to let-7d/g/i
P-value
1.65 0.41 0.34 0.27 0.35
2.61 8.12 1.51 6.62 1.39
104 1019 1017 1024 1016
Negative control CT 32 39 35 39 38
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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H. Ding et al. / Parkinsonism and Related Disorders xxx (2015) 1e6
Fig. 2. The relative levels of 5 identified serum miRNAs in PD cases by qRT- PCR. The levels of the miRNAs were normalized to let-7d/g/i and calculated using the 2DDCq method. Each point represents the mean of triplicate samples. *P < 0.05, **P < 0.01, ***P < 0.001.
Fig. 3. The ROC curve analysis for discriminative ability between PD patients and healthy controls. ROC curves for the 5 individual miRNAs and the 5-miRNA panel to differentiate 106 PD cases from 91 controls.
conducted miRNA profiling in peripheral blood mononuclear cells (PBMCs) of 19 PD patients and 13 controls using microarrays, where 18 miRNAs were observed to be differentially expressed [15].
Subsequently, a small-scale project using qRT-PCR was performed in the whole blood samples from 15 PD patients and 8 healthy individuals, where 6 miRNAs were identified [16]. Both of the
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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reports mentioned above examined the miRNAs in the blood cells, which strictly speaking is not an examination of the miRNA levels in a body fluid. The following studies were then performed with plasma or serum samples from PD patients. One report used 74 PD patients and 62 healthy people to determine the plasma miRNA expression profile [17]. The levels of serum miRNAs in idiopathic and LRRK2 PD patients were also identified [18]. Another study found the decreased miR-133b level in serum of PD patients [19]. Recently, all biofluid-based miRNAs as molecular biomarkers for PD patients were summarized [20,21]. However, only miR-181a was found to be decreased in the serum of idiopathic PD patients when compared with healthy controls, other 4 significantly changed serum miRNAs found in our studies were not mentioned in the previous reports [18]. This difference may be explained by several reasons. First, a different miRNA analysis platform for high throughput screening was used in the initial stages (Solexa sequencing vs TaqMan Low Density Assay). Moreover, the Solexa used in the present study can screen 1123 miRNAs, whereas only 337 miRNAs were analysed by the TaqMan Low Density Assay; a larger screen may contribute to the identification of a greater number of significant changes in the miRNAs. Second, the procedures of sample processing, such as blood anticoagulant treatment, may disturb the extracellular miRNAs levels in the blood. Third, population differences and life style variability may also affect the circulating miRNA levels. Finally, we used different miRNAs as an internal control for serum miRNAs. U6 RNA and 5S rRNA, which are normally used as a housekeeping miRNAs for tissue miRNA normalization, are degraded in serum samples. miR16 has been recently used in the normalization of serum miRNAs, including PD-related circulating miRNA detection [22]. However, one of our previous studies also found that serum miR-16 itself was changed under certain pathological conditions [8]. In another work, we have shown that the combination of let-7d, let-7g and let-7i is statistically superior to the commonly used reference genes U6, RNU44, RNU48 and miR-16 for the normalization of serum miRNAs [9]. Therefore, the let-7d/g/i combination was used as the internal reference for this study. The differences in internal controls may also lead to the different identified miRNAs in this study. As other neurological diseases may also affect the serum miRNA levels, we searched the studies which investigated the circulating miRNA profiling in these neurological disorders, including Alzheimer's disease, Amyotrophic lateral sclerosis, Spinocerebellar ataxia and multiple sclerosis. miR-15b was decreased in the plasma of Alzheimer's disease and in the serum of multiple sclerosis patients, which is consistent with our present study [23,24]. Other miRNAs (miR-195, miR-185, miR-221 and miR-181a) exhibited no significant change in the serum from patients with the above mentioned neurological disorders. Therefore, the 5-member serum miRNA panel could distinguish PD patients from other neurological disorders. Functional studies of miRNAs in neurons may be beneficial for evaluating serum miRNAs as indicators of neurodegenerative disorder. Of the 5 serum miRNAs identified in PD patients, miR-195 family members, including miR-195 and miR-15b, have been observed to be differentially expressed in distinct areas of human Alzheimer's disease (AD) brain tissue [25]. miR-181a is enriched in the brain, and applying miR-181a inhibitors can reduce evidence of astrocyte dysfunction [26]. A decrease in miR-185 levels contributes to dendritic and spine development deficits in hippocampal neurons, which are key foci in schizophrenia research [27]. Besides, we further searched the validated gene targets of 5 miRNAs via a tool named mirwalk2.0 (http://zmf.umm.uni-heidelberg.de/apps/ zmf/mirwalk2/). The common targets of 5 miRNAs were listed as Supplementary Table 6. Among these targets, BCL2, CDC42, VEGFA, CDKN1B were closely related to the neuronal apoptosis,
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regeneration, development and growth. We also pay attention to the unique target of these miRNAs. miR-195 could directly suppress ARL2 (ADP-ribosylation factor-like protein 2) and Methyl-CpG binding protein 1 (MBD1), could affect the apoptosis of neural progenitor cells and modulate the proliferation of neural stem cell [28,29]. miR-221 decreased expression of Foxo3a and Apaf-1 and plays a critical role in neuronal differentiation as well as protection against apoptosis [30]. All of the 5 miRNAs seem to be closely related to the nervous system, and the neurodegenerative process may lead to the alternation of these miRNA levels in the brain and ultimately to the change in the serum miRNAs concentrations. Therefore, further work is necessary to indicate the biological function of circulating miRNAs in the PD process. In summary, this work generated a distinctive serum miRNA profile and identified 5 differentially expressed miRNAs. This 5member serum miRNA panel could precisely discriminate PD patients from healthy people, which has potential to serve as a noninvasive biomarker for PD diagnosis. Author's contribution HD and ZH performed the experiment and wrote the manuscript; MC and CW performed the experiment; XC performed the statistical analysis; JC and JZ designed the experiment and wrote the manuscript. Conflicts of interest None. Acknowledgments This work was supported by the National Basic Research Program of China (2012CB517603), the National High Technology Research and Development Program of China (2014AA020707), the National Natural Science Foundation of China (81100835, 31170751, 81072329, 31400671, 31571458 and 51173076), the Ph.D. Programs Foundation of the Ministry of Education of China (20130091110037), China Postdoctoral Science Foundation funded project (2014M551555, 2015T80536). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.parkreldis.2015.11.014. References [1] J.M. Shulman, P.L. De Jager, M.B. Feany, Parkinson's disease: genetics and pathogenesis, Annu. Rev. Pathol. 6 (2011) 193e222. [2] J. Massano, K.P. Bhatia, Clinical approach to Parkinson's disease: features, diagnosis, and principles of management, Cold Spring Harb. Perspect. Med. 2 (2012) a008870. [3] A.J. Hughes, S.E. Daniel, Y. Ben-Shlomo, A.J. Lees, The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service, Brain 125 (2002) 861e870. [4] L. Ma, L. Wei, F. Wu, Z. Hu, Z. Liu, W. Yuan, Advances with microRNAs in Parkinson's disease research, Drug Des. Devel Ther. 7 (2013) 1103e1113. [5] L. Qiu, W. Zhang, E.K. Tan, L. Zeng, Deciphering the function and regulation of microRNAs in Alzheimer's disease and Parkinson's disease, ACS Chem. Neurosci. 5 (2014) 884e894. [6] X. Chen, Y. Ba, L. Ma, X. Cai, Y. Yin, K. Wang, et al., Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases, Cell Res. 18 (2008) 997e1006. [7] C. Wang, J. Hu, M. Lu, H. Gu, X. Zhou, X. Chen, et al., A panel of five serum miRNAs as a potential diagnostic tool for early-stage renal cell carcinoma, Sci. Rep. 5 (2015) 7610. [8] C. Zhang, C. Wang, X. Chen, C. Yang, K. Li, J. Wang, et al., Expression profile of microRNAs in serum: a fingerprint for esophageal squamous cell carcinoma, Clin. Chem. 56 (2010) 1871e1879.
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Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease Haixia Ding a, 1, Zhen Huang b, 1, Mengjie Chen b, Cheng Wang b, Xi Chen b, Jiangning Chen b, c, *, Junfeng Zhang b, c, ** a
Department of Geriatric, Nanjing Medical University First Affiliated Hospital, No. 300, Guangzhou Road, Nanjing, China State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China State Key Laboratory of Analytical Chemistry for Life Sciences and Collaborative Innovation Center of Chemistry for Life Sciences, Nanjing University, Nanjing, China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 23 July 2015 Received in revised form 30 October 2015 Accepted 16 November 2015
Background and objective: Parkinson's disease (PD) is the second most common age-related neurodegenerative disorder after Alzheimer's disease. The aim of this work was to determine whether the differences of serum miRNAs profiling could distinguish PD patients from healthy individuals. Methods: We collected serum samples from 106 sporadic PD patients and 91 age/gender-matched healthy controls. Serum miRNAs were analysed by Solexa sequencing followed by a qRT-PCR examination. The qRT-PCR assay, which was divided into two phases, was used to validate the expression of miRNAs screened by Solexa sequencing. Receiver operating characteristic (ROC) curve analysis and clustering analysis were performed to determine the diagnostic usefulness of the selected miRNAs for PD. Results: In this study, we generated a profile of 5 serum miRNAs: miR-195 was up-regulated, and miR185, miR-15b, miR-221 and miR-181a were down-regulated. Conclusion: This group of five miRNAs can precisely distinguish PD patients from health individuals and may be used as a potential serum-based biomarker for the diagnosis of PD. © 2015 Elsevier Ltd. All rights reserved.
Keywords: Parkinson's disease Serum miRNA
1. Introduction Parkinson's Disease (PD), which is characterized by resting tremor, bradykinesia, rigidity and postural instability, is the second most common age-related neurodegenerative disorder [1]. Currently, a PD diagnosis mainly depends on neuroimaging and clinical manifestations using the UK PDS Brain Bank Criteria, Unified Parkinson's Disease Rating Scale and the modified HoehneYahr stage [2].These diadynamic criteria are subjective and can be applied only when motor features appear. However, PD clinical manifestations do not appear until 50%e70% of the dopaminergic neurons have been lost, causing patients to lose the opportunity for
* Corresponding author. School of Life Sciences, Nanjing University, Nanjing, 210093, China. ** Corresponding author. School of Life Sciences, Nanjing University, Nanjing, 210093, China. E-mail addresses: [email protected] (J. Chen), [email protected] (J. Zhang). 1 The two authors contributed equally to this work.
early treatment [3]. Therefore, seeking novel biomarkers that are objective and can be quantified may contribute to the diagnosis of PD, especially at the early stages of the disease process. MicroRNA (miRNA), an abundant class of small non-coding RNA, primarily cause the degradation or translational suppression of target mRNAs. It is reported that PD patients and patients with other neurodegenerative diseases have significantly different tissue miRNA profiles [4]. Several miRNAs (miR-133b, miR-34c, miR-107, miR-433 and miR-205) have been observed to be aberrantly expressed in the brain tissue and are involved in neuron differentiation, apoptosis and neurite outgrowth [5]. Therefore, these miRNAs are considered as novel biomarkers and potential therapy targets. The brain tissues from patients with neurodegenerative disorders are normally collected at autopsy; however, this invasive technique makes sample collection from living patients impossible. Recent reports have also demonstrated that miRNAs remain stable in the blood and may be used as novel non-invasive biomarkers for several types of diseases; thus, we supposed that there was a unique serum miRNA expression profile in PD patients that could be a new indicator [6]. The aim of this study was to investigate the
http://dx.doi.org/10.1016/j.parkreldis.2015.11.014 1353-8020/© 2015 Elsevier Ltd. All rights reserved.
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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profile of serum miRNAs and to explore its clinical value as a novel biomarker for PD.
we used a combination of let-7d/g/i as an endogenous reference gene for the normalization of serum miRNAs. The relative levels of miRNAs were calculated using the 2DDCq method.
2. Methods 2.1. Study population and blood sampling The present study included 106 PD patients and 91 healthy individuals. All PD patients were diagnosed at the Jiangsu province hospital and the Nanjing brain hospital. Patients with cancer, significant cardiac dysfunction or diabetes were excluded from this study. UPDRS-III scores and a modified HoehneYahr scale were used to evaluate the disease stages and the living quality of the PD patients. Ninety-one individuals from a large pool of individuals seeking a routine health checkup at the Jiangsu province people's hospital and showing no evidence of disease were selected as healthy controls. All samples were collected from consenting individuals according to protocols approved by the ethics committee of each participating institution. The controls were matched to the patients by age and sex (Supplementary Tables 1e2). The persons who performed the following experiments were blinded to the diagnostic result. All blood samples were collected, centrifuged and then stored according to previous report [7]. 2.2. RNA isolation For the Solexa sequencing of the serum samples, equal volumes of serum from each sample (6 mL each) were pooled separately to form patient and control sample pools (each pool contained 90 mL), and total RNA was extracted with TRIzol reagent (Life Technologies, Carlsbad, CA, USA) according to a previous report. The resulting RNA pellet was dissolved in 20 mL of RNase-free water and then stored at 80 C for following examination. For the qRT-PCR assay, total RNA was extracted from 100 mL of the serum sample with a one-step phenol/chloroform purification protocol as previously described [8].
2.5. Data analysis All of the statistical analyses were performed using the Statistical Analysis System software SPSS 19.0. The data were presented as the mean ± SEM for miRNAs or mean 6 SD for other variables. A Student's t-test or two-sided c2 test was used to compare the differences in variables between the two groups. A P value 0.05 was considered as statistically significant. For miRNAs, we constructed Receiver operating characteristic (ROC) curves and calculated the area under the ROC curves (AUC) to evaluate the predictive power of the candidate miRNA for PD. 3. Results 3.1. Solexa screening of serum miRNAs in PD A multiphase case-control study was constructed to find markedly changed levels of serum miRNAs for PD patients (Fig. 1). In the initial biomarker screening stage, two pooled serum samples from 15 PD patients and 15 controls underwent Solexa sequencing to identify miRNAs that showed significant differences between the PD cases and matched controls. Supplementary Table 1 summarizes the demographic and clinical features of the patients for Solexa sequencing. According to the miRbase 16.0 version,a total of 1123 miRNAs were screened by Solexa sequencing. 138 and 159 miRNAs could be detected in healthy controls and PD patients, respectively
2.3. Solexa sequencing technology Solexa sequencing was performed according to a previous report. Briefly, after PAGE purification of small RNA molecules (<30 nucleotides) and ligation of a pair of Solexa adaptors to the 50 and 30 RNA ends, the RNA molecules were amplified using primers to the adaptor regions for 17 cycles. Fragments that were approximately 90 bp (small RNA þ adaptors) were isolated from an agarose gel. Purified DNA was used for cluster generation and sequencing analysis using Illumina's Solexa sequencer according to the manufacturer's instructions. Image files were generated by the sequencer and were processed to produce digital-quality data. After masking the adaptor sequences and removing the contaminated reads, clean reads were processed for in silico analysis as previously reported [8]. 2.4. Individual qRT-PCR assay of serum miRNAs A TaqMan probe-based qRT-PCR assay was performed to quantify the serum miRNA levels according to the manufacturer's instructions (7500 Sequence Detection System, Applied Biosystems) as described previously [8]. All reactions, including no-template controls, were performed in triplicate. It was proved that let-7d, let-7g and let-7i (let-7d/g/i) were more stable than other reference genes (U6, miR-16, RNU48 and RNU44) and the more accurate data could be obtained after normalization to a combination of let7d/g/i [9]. We also observed the low variability of let-7d/g/i between PD patients and healthy controls (Supplementary Fig. 1), so
Fig. 1. The overview of the experiment design.
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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(Supplementary Table 3). In term of the sensitivity and accuracy, the cutoff point for miRNA fold change was set at 1.5 fold. The miRNAs that met two criteria (Solexa sequencing detected 300 copies in the patient or control group and a minimum 1.5-fold change observed between PD patients and healthy individuals) were selected for further qRT-PCR testing. Based on these criteria, we built a list of 15 differentially expressed miRNAs (Supplementary Table 4). 3.2. Validation of different expressed miRNAs via RT-PCR assay As the Solexa sequencing assay was performed on pooled samples from PD patients and healthy controls, the individual differences might have influenced the accuracy of the Solexa sequencing. Thus, the selected miRNAs from the Solexa sequencing assay were further validated by the qRT-PCR assay. In the training set, the miRNAs were examined in a separated group of individual serum samples from 45 PD patients and 36 healthy individuals (Supplementary Table 5). Only miRNAs with a mean change 1.5, a P value < 0.001 and a negative control CT > 32 were selected. Based on these criteria, a list of 5 miRNAs (miR-195, miR-15b, miR-221, miR-181a and miR-185) was generated that showed a significant change between the PD patients and the healthy controls. These 5 miRNAs were further examined by qRT-PCR in a larger group consisting of 61 patients and 55 matched controls. Consistent with the results from the training set, the serum level of miR-195 was significantly higher in the PD patients than in the control individuals; meanwhile, the levels of the other 4 miRNAs (miR-15b, miR-221, miR-181a and miR-185) were lower in the PD patients than in the healthy controls (Table 1). The results in Fig. 2 show the different levels of the 5 miRNAs in the 106 PD patients and 91 healthy individuals belonging to the training and validation sets. 3.3. Unsupervised clustering analysis An unsupervised clustering method that was unbiased to the clinical annotations was used to investigate the different concentration patterns for several miRNA panels in the PD and control serum samples. We observed that the 5-member panel (miR-195, miR-15b, miR-221, miR-181a and miR-185) (Supplementary Fig. 1) could reliably discriminate the PD samples from the control samples. The serum miRNA profile correctly classified 41 (91.1%) of 45 PD cases (abbreviated as P) and 32 (88.9%) of 36 control samples (abbreviated as C) in the training set (Supplementary Fig. 1). In the validation set, 58 PD cases and 48 controls were correctly divided into 2 main groups; only 3 PD cases and 7 controls were misclassified (Supplementary Fig. 2). 3.4. ROC curve analysis The ROC curves that were constructed to compare the relative levels of the 5 miRNAs for the PD patients and the healthy controls yielded the following AUCs: miR-195, 0.733 (95% CI, 0.611e0.804); miR-15b, 0.897 (95%CI, 0.854e0.940); miR-221, 0.854 (95% CI, 0.798e0.911); miR-181a, 0.822 (95% CI, 0.762e0.881); miR-185,
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0.820 (95% CI, 0.760e0.879). Using the optimal cutoff value, we obtained the following sensitivity and specificity values, respectively: miR-195, 68.9% and 75.8%; miR-15b, 76.9% and 86.8%; miR221, 75.8% and 85.8%; miR-181a, 70.3% and 84.0%; miR-185, 70.0% and 83.0%. As shown in Fig. 3, we also used the ROC curves to evaluate the diagnostic value of the 5-member miRNA profiling system. The AUC for the miRNAs panel was 0.919 (95% CI, 0.877e0.961). With an optimal cutoff value in which the sum of the sensitivity and specificity was maximal, the specificity was 77.4%, and the sensitivity was 93.4%. 4. Discussion In the present study, we performed the profiling of serum miRNA of PD patients through Solexa sequencing from pooled serum samples as the initial stage of analysis. Based on the qRT-PCR assay, 5 differentially expressed miRNAs were identified, and the combination of these miRNAs could effectively separate the PD patients from the healthy individuals, which achieved the highest predictive biomarker performances. Currently, physicians diagnose PD primarily based on neurological examination and neuroimaging, and both of these examination standards are subjective and lacking in sensitivity. Meanwhile, the observation of Lewy bodies in the midbrain by histopathological analysis can confirm a diagnosis of Parkinson's disease, but brain tissue cannot be obtained from living people [10]. Cerebrospinal fluid (CSF) can reflect some of the pathophysiological changes that occur in the brain, and number of CSF biomarkers (ɑsynuclein and DJ-1) are being used in clinical trials to monitor the progression of PD [11]. However, CSF can be collected only via lumbar puncture, and the inconvenience of this invasive collection process restricts its use and influences the examination accuracy. In contrast, blood is an ideal candidate for biomarker detection as special types of biological substances are released from the tissues under pathologic conditions. Moreover, blood sampling is fast, easy, more cost-effective and minimally invasive. Several studies using various techniques including metabolomics, proteomics and gene expression profiling are underway to explore blood-based markers in PD patients [12]. Therefore, the feasibility of using blood-based biomarkers is one of the most promising methods for PD diagnosis. Our laboratory and other groups were the first to demonstrate that miRNAs are quite stable in serum and consistent among individuals in the same species [6,13]. The stability of miRNAs in blood may be attributed by the protection of binding proteins or microvehicles. It has been indicated that both circulating blood cells and other cells from different tissues secrete microvehicles, which encapsulate miRNAs [14]. Pathological conditions may influence the secretion of microvehicles and change internal miRNA content. Thus, the pathophysiological condition of the body can be quickly reflected by the alternation in the blood miRNA profile. As miRNA in the blood can be directly detected, it may serve as a sensitive indicator of various diseases. Several studies have already begun to analyse the miRNA levels in body fluids (including serum, plasma and cerebrospinal fluid) or cells circulating in the fluid of PD patients. The earliest study
Table 1 miRNA levels in serum samples from PD patients compared to healthy controls in the validation set. miRNA
Control CT (n ¼ 55)
hsa-miR-195 hsa-miR-185 hsa-miR-221 hsa-miR-15b hsa-miR-181a
29.17 27.65 26.58 30.12 27.59
± ± ± ± ±
1.66 1.41 1.38 1.34 1.38
PD CT (n ¼ 61) 30.91 31.36 30.44 35.27 31.92
± ± ± ± ±
1.15 1.74 1.70 2.14 2.47
Fold change of CT (PD/control) relative to let-7d/g/i
P-value
1.65 0.41 0.34 0.27 0.35
2.61 8.12 1.51 6.62 1.39
104 1019 1017 1024 1016
Negative control CT 32 39 35 39 38
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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Fig. 2. The relative levels of 5 identified serum miRNAs in PD cases by qRT- PCR. The levels of the miRNAs were normalized to let-7d/g/i and calculated using the 2DDCq method. Each point represents the mean of triplicate samples. *P < 0.05, **P < 0.01, ***P < 0.001.
Fig. 3. The ROC curve analysis for discriminative ability between PD patients and healthy controls. ROC curves for the 5 individual miRNAs and the 5-miRNA panel to differentiate 106 PD cases from 91 controls.
conducted miRNA profiling in peripheral blood mononuclear cells (PBMCs) of 19 PD patients and 13 controls using microarrays, where 18 miRNAs were observed to be differentially expressed [15].
Subsequently, a small-scale project using qRT-PCR was performed in the whole blood samples from 15 PD patients and 8 healthy individuals, where 6 miRNAs were identified [16]. Both of the
Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014
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reports mentioned above examined the miRNAs in the blood cells, which strictly speaking is not an examination of the miRNA levels in a body fluid. The following studies were then performed with plasma or serum samples from PD patients. One report used 74 PD patients and 62 healthy people to determine the plasma miRNA expression profile [17]. The levels of serum miRNAs in idiopathic and LRRK2 PD patients were also identified [18]. Another study found the decreased miR-133b level in serum of PD patients [19]. Recently, all biofluid-based miRNAs as molecular biomarkers for PD patients were summarized [20,21]. However, only miR-181a was found to be decreased in the serum of idiopathic PD patients when compared with healthy controls, other 4 significantly changed serum miRNAs found in our studies were not mentioned in the previous reports [18]. This difference may be explained by several reasons. First, a different miRNA analysis platform for high throughput screening was used in the initial stages (Solexa sequencing vs TaqMan Low Density Assay). Moreover, the Solexa used in the present study can screen 1123 miRNAs, whereas only 337 miRNAs were analysed by the TaqMan Low Density Assay; a larger screen may contribute to the identification of a greater number of significant changes in the miRNAs. Second, the procedures of sample processing, such as blood anticoagulant treatment, may disturb the extracellular miRNAs levels in the blood. Third, population differences and life style variability may also affect the circulating miRNA levels. Finally, we used different miRNAs as an internal control for serum miRNAs. U6 RNA and 5S rRNA, which are normally used as a housekeeping miRNAs for tissue miRNA normalization, are degraded in serum samples. miR16 has been recently used in the normalization of serum miRNAs, including PD-related circulating miRNA detection [22]. However, one of our previous studies also found that serum miR-16 itself was changed under certain pathological conditions [8]. In another work, we have shown that the combination of let-7d, let-7g and let-7i is statistically superior to the commonly used reference genes U6, RNU44, RNU48 and miR-16 for the normalization of serum miRNAs [9]. Therefore, the let-7d/g/i combination was used as the internal reference for this study. The differences in internal controls may also lead to the different identified miRNAs in this study. As other neurological diseases may also affect the serum miRNA levels, we searched the studies which investigated the circulating miRNA profiling in these neurological disorders, including Alzheimer's disease, Amyotrophic lateral sclerosis, Spinocerebellar ataxia and multiple sclerosis. miR-15b was decreased in the plasma of Alzheimer's disease and in the serum of multiple sclerosis patients, which is consistent with our present study [23,24]. Other miRNAs (miR-195, miR-185, miR-221 and miR-181a) exhibited no significant change in the serum from patients with the above mentioned neurological disorders. Therefore, the 5-member serum miRNA panel could distinguish PD patients from other neurological disorders. Functional studies of miRNAs in neurons may be beneficial for evaluating serum miRNAs as indicators of neurodegenerative disorder. Of the 5 serum miRNAs identified in PD patients, miR-195 family members, including miR-195 and miR-15b, have been observed to be differentially expressed in distinct areas of human Alzheimer's disease (AD) brain tissue [25]. miR-181a is enriched in the brain, and applying miR-181a inhibitors can reduce evidence of astrocyte dysfunction [26]. A decrease in miR-185 levels contributes to dendritic and spine development deficits in hippocampal neurons, which are key foci in schizophrenia research [27]. Besides, we further searched the validated gene targets of 5 miRNAs via a tool named mirwalk2.0 (http://zmf.umm.uni-heidelberg.de/apps/ zmf/mirwalk2/). The common targets of 5 miRNAs were listed as Supplementary Table 6. Among these targets, BCL2, CDC42, VEGFA, CDKN1B were closely related to the neuronal apoptosis,
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regeneration, development and growth. We also pay attention to the unique target of these miRNAs. miR-195 could directly suppress ARL2 (ADP-ribosylation factor-like protein 2) and Methyl-CpG binding protein 1 (MBD1), could affect the apoptosis of neural progenitor cells and modulate the proliferation of neural stem cell [28,29]. miR-221 decreased expression of Foxo3a and Apaf-1 and plays a critical role in neuronal differentiation as well as protection against apoptosis [30]. All of the 5 miRNAs seem to be closely related to the nervous system, and the neurodegenerative process may lead to the alternation of these miRNA levels in the brain and ultimately to the change in the serum miRNAs concentrations. Therefore, further work is necessary to indicate the biological function of circulating miRNAs in the PD process. In summary, this work generated a distinctive serum miRNA profile and identified 5 differentially expressed miRNAs. This 5member serum miRNA panel could precisely discriminate PD patients from healthy people, which has potential to serve as a noninvasive biomarker for PD diagnosis. Author's contribution HD and ZH performed the experiment and wrote the manuscript; MC and CW performed the experiment; XC performed the statistical analysis; JC and JZ designed the experiment and wrote the manuscript. Conflicts of interest None. Acknowledgments This work was supported by the National Basic Research Program of China (2012CB517603), the National High Technology Research and Development Program of China (2014AA020707), the National Natural Science Foundation of China (81100835, 31170751, 81072329, 31400671, 31571458 and 51173076), the Ph.D. Programs Foundation of the Ministry of Education of China (20130091110037), China Postdoctoral Science Foundation funded project (2014M551555, 2015T80536). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.parkreldis.2015.11.014. References [1] J.M. Shulman, P.L. De Jager, M.B. Feany, Parkinson's disease: genetics and pathogenesis, Annu. Rev. Pathol. 6 (2011) 193e222. [2] J. Massano, K.P. Bhatia, Clinical approach to Parkinson's disease: features, diagnosis, and principles of management, Cold Spring Harb. Perspect. Med. 2 (2012) a008870. [3] A.J. Hughes, S.E. Daniel, Y. Ben-Shlomo, A.J. Lees, The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service, Brain 125 (2002) 861e870. [4] L. Ma, L. Wei, F. Wu, Z. Hu, Z. Liu, W. Yuan, Advances with microRNAs in Parkinson's disease research, Drug Des. Devel Ther. 7 (2013) 1103e1113. [5] L. Qiu, W. Zhang, E.K. Tan, L. Zeng, Deciphering the function and regulation of microRNAs in Alzheimer's disease and Parkinson's disease, ACS Chem. Neurosci. 5 (2014) 884e894. [6] X. Chen, Y. Ba, L. Ma, X. Cai, Y. Yin, K. Wang, et al., Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases, Cell Res. 18 (2008) 997e1006. [7] C. Wang, J. Hu, M. Lu, H. Gu, X. Zhou, X. Chen, et al., A panel of five serum miRNAs as a potential diagnostic tool for early-stage renal cell carcinoma, Sci. Rep. 5 (2015) 7610. [8] C. Zhang, C. Wang, X. Chen, C. Yang, K. Li, J. Wang, et al., Expression profile of microRNAs in serum: a fingerprint for esophageal squamous cell carcinoma, Clin. Chem. 56 (2010) 1871e1879.
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Please cite this article in press as: H. Ding, et al., Identification of a panel of five serum miRNAs as a biomarker for Parkinson's disease, Parkinsonism and Related Disorders (2015), http://dx.doi.org/10.1016/j.parkreldis.2015.11.014