Rev. Neurosci. 2014; 25(5): 653–662

Feng Zhanga, Jianwen Chena, Li Zhao and Chunbo Dong*

Candidate biomarkers of multiple system atrophy in cerebrospinal fluid Abstract: Multiple system atrophy (MSA) is a neurodegenerative disease that presents as an autonomic dysfunction in combination with varying degrees of parkinsonism and cerebellar ataxia. It comprises a pathologically widespread neuronal loss accompanied by gliosis in the basal ganglia, cerebellum, pons, inferior olivary nuclei, and spinal cord. As a rapidly progressive disorder, MSA develops with autonomic dysfunction and mobility problems in several years. These autonomic and motor function impairments severely disrupt the patients’ daily lives. Currently, the therapeutic management of this disease is only symptomatic. An early and accurate diagnosis is helpful not only in the clinical field but also in the research for new therapies. The biomarkers in cerebrospinal fluid (CSF) and serum facilitate the differential diagnosis of MSA when the disease is difficult to recognize based on the clinical features or even presymptomatic. This review will summarize the biomarkers present in CSF that are potential candidates to accurately differentiate MSA from other similar neurodegenerative disorders. Keywords: biomarker; differential diagnosis; multiple system atrophy; proteomics. DOI 10.1515/revneuro-2014-0023 Received March 12, 2014; accepted April 25, 2014; previously published online May 27, 2014

Introduction Multiple system atrophy (MSA) is a rapidly progressive neurodegenerative disease presenting with varying degrees of parkinsonism, autonomic dysfunction, and cerebellar ataxia (Dickson et al., 1999; Ubhi et al., 2011). Based on the dominant symptoms, MSA can be classified

Feng Zhang and Jianwen Chen contributed equally to this article. *Corresponding author: Chunbo Dong, Department of Neurology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China, e-mail: [email protected] Feng Zhang, Jianwen Chen and Li Zhao: Department of Neurology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China a

into two categories: (1) MSA with predominant parkinsonism featuring extrapyramidal symptoms (MSA-P) and (2) MSA with predominant cerebellar ataxia featuring cerebellar ataxia (MSA-C) (Pfeiffer, 2007; Ubhi et  al., 2011). The pathological hallmark of MSA is the presence of abundant argyrophilic filamentous glial cytoplasmic inclusions (GCIs), which are composed of α-synuclein (α-syn), τ, tubulin, ubiquitin, αB-crystallin, cyclin-dependent kinase 5, transferrin, Leu-7, and microtubule-associated protein 5 (Papp et  al., 1989; Nakazato et  al., 1990; Kato et al., 1991; Arima et al., 1992). The misfolded, hyperphosphorylated, fibrillary α-syn that is the key component of these inclusions accounts for the classification of MSA as an α-synucleinopathy, as are Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). The underlying mechanisms that explain how α-syn induces cellular dysfunction and neuronal loss remain unclear. The studies of human GCIs in transgenic mice showed similar pathological changes involving axonal α-syn aggregation and axonal degeneration, mitochondrial dysfunction, microgliosis, or environmental oxidative stress (Stefanova et al., 2009). Clinical investigations frequently fail to distinguish the early stage of MSA from PD, progressive supranuclear palsy (PSP), DLB, and other disorders; therefore, the biomarkers of MSA can be a new approach to make the differential diagnosis. Accordingly, the principal focus of this article is to present an overview of the various cerebrospinal fluid (CSF) candidate biomarkers of MSA. We briefly summarize the research approaching these potential candidates, from brain-specific proteins to blood-brain barrier (BBB)-related biomarkers. The proteomic studies of CSF in MSA are also discussed.

Biomarkers Brain-specific proteins τ protein The τ protein is a microtubule-associated protein that stabilizes microtubules in neurons and other cell types. It

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

654      F. Zhang et al.: Biomarkers of multiple system atrophy is also one of the abnormally deposited proteins that are found in the brain of patients with Alzheimer’s disease (AD) (Mandelkow and Mandelkow, 2012). MSA, as one of the neurodegenerative diseases, is also associated with τ. Abdo et  al. (2004) observed that MSA is characterized by a relatively higher concentration of τ in the CSF when compared to PD, which offered the best combination of sensitivity (95%) and specificity (77%). This result also implies the presence of a more widespread axonal degeneration in MSA than in PD. However, no significant differences were found between the MSA-P and MSA-C groups in those analyses. The authors suggested that τ, 3-methoxy-4-hydroxyphenylethyleneglycol (MHPG), and myelin basic protein (MBP) might discriminate MSA from PD. Accordingly, MHPG levels were lower in MSA groups, while MBP was observed to be elevated when compared to PD. Another study (Shi et al., 2011) indicated that a combination of α-syn and p-τ%, which measures the ratio of phosphorylated τ and total τ in CSF, could achieve a high sensitivity (90%) and a reasonable specificity (71%) when differentiating MSA from PD. The combination of DJ-1 and p-τ% achieved 90% sensitivity and 70% specificity in the differentiation of MSA from controls.

NF protein The neurofilament (NF) protein is the most abundant cytoskeletal component of myelinated axons in the central and peripheral nervous systems. The correct formation of the NF network is integral to the axonal caliber of myelinated axons and consequently their conduction velocity. The abnormal metabolism and organization of NF is frequently associated with neurodegenerative diseases (Perrot et al., 2008). A study by Brettschneider et  al. (2006) found that the levels of CSF NfHSMI35, the NF heavy chain, were significantly elevated in MSA relative to both PD patients and controls. Abdo et al. (2007a) suggested the NF protein as a candidate biomarker for the degeneration of axons. NF light chain (NF-L) and phosphorylated NF heavy chain (NfHp35) were significantly increased in the CSF of MSA-P compared to PD. Another study (Hall et al., 2012) showed that the CSF levels of NF-L were present at normal levels in PD and increased in PD with dementia (PDD), DLB, AD, PSP, corticobasal degeneration (CBD), and MSA patients when compared with controls; atypical parkinsonian disorders such as PSP, MSA, and CBD had higher levels, but the CSF NF-L level was associated with severity and not with the duration of those diseases. The results of these and a number of other studies (Holmberg et al., 1998, 2001;

Abdo et  al., 2007b; Constantinescu et  al., 2009, 2010a) suggest that NF-L could serve as a potential biomarker to differentiate PD and atypical parkinsonian disorders (PSP, MSA, and CBD) but could not reliably distinguish PD from controls, MSA-P from MSA-C, and MSA from PSP.

α-syn The α-syn protein is normally present in the presynaptic terminals of the human brain and participates in the regulation of synaptic plasticity and neural differentiation under physiological conditions. Misfolded α-syn is the major constituent of Lewy bodies and plays a central role in the pathogenesis of PD and DLB (George et  al., 2013; Saracchi et al., 2014). Additionally, with respect to MSA, α-syn is the key component of GCIs and correlates significantly with neuronal deterioration and disease duration. Abnormal α-syn inclusions are also found in neuronal cytoplasm, nuclei, neurites, and autonomic neurons in MSA (Pfeiffer, 2007). Moreover, α-syn is found in the amyloid plaques of AD as the nonamyloid component (Hashimoto and Masliah, 1999). Mollenhauer et  al. (2011) conducted a cohort study that found lower CSF α-syn concentrations in PD, MSA, and DLB than those in AD and other neurological disorders. The decreased CSF levels of α-syn separated α-synucleinopathies from other disorders and implied the abnormal accumulation of α-syn. CSF α-syn discriminated DLB from AD, PD, and DLB from PSP but failed to distinguish MSA from PD. As such, it may be beneficial in the diagnosis of PD but not for MSA. Also, Foulds et  al. (2012) detected levels of total and oligomeric forms of α-syn as well as phosphorylated and phosphorylated oligomeric forms of α-syn in CSF samples from patients with PD, MSA, DLB, and PSP and healthy controls. They found that, of the four forms of α-syn, only the oligomeric phosphorylated forms of α-syn in CSF could differentiate MSA from PD. Interestingly, other research studies (Aerts et al., 2012; Hall et al., 2012) indicated that α-syn was not a viable candidate biomarker of MSA.

Aβ-42 Aβ-42, the 42-amino acid isoform of β-amyloid, has been found to accumulate in the senile plaques of AD. However, some studies have identified a decreased CSF level of Aβ-42 in AD and other diseases, such as frontotemporal dementia, vascular dementia, and Creutzfeldt-Jakob disease, even without the senile plaques (Tamaoka et al.,

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

F. Zhang et al.: Biomarkers of multiple system atrophy      655

1994; Otto et  al., 2000; Sjogren et  al., 2000; Andreasen and Blennow, 2002). The research by Holmberg et  al. (2003) found a significantly decreased concentration of Aβ-42 in the CSF of MSA patients, whereas the levels in PD and PSP did not differ from the controls either due to less production or more consumption of Aβ-42 in MSA. These authors defined a CSF Aβ-42 concentration below 415 ng/l as a proposed clinical MSA diagnosis criterion. In contrast, Verbeek et  al. (2004) found no obvious decrease in the levels of CSF Aβ-42 among the MSA, PD, PSP, and control groups. They did not observe any CSF Aβ-42 levels below 415 ng/l in MSA, PD, and PSP patients. Therefore, these researchers concluded that CSF Aβ-42 could not be used as a pathophysiological indicator in movement disorders. A subsequent study (Shi et al., 2011) supported the conclusions of Verbeek et al. In conclusion, among those brain-specific proteins found in CSF, which are prioritized from blood-derived proteins, only the τ protein and NF protein are considered underlying biomarkers of MSA. The τ protein alone has a sensitivity of 95% and a specificity of 77% in differentiating MSA from PD. The NF protein (NfHSMI35, NF-L, and NfHp35) was elevated in MSA relative to PD, and NF-L showed a higher level in MSA from controls. Although α-syn plays a key role in the pathology of MSA, its levels cannot yet be used to distinguish MSA from PD. The potential status of Aβ-42 as a biomarker, however, remains unclear because of conflicting findings.

Growth factors and hormones IGF-I The role of growth factors in neurodegeneration is widely recognized. Numerous growth factors, including insulinlike growth factor (IGF), have neuroprotective and/or neurotrophic actions. IGF-I, which is abundantly expressed in developing brains and functions as a modulator of neuronal growth and angiogenesis, also broadly affects neuron-specific synaptic plasticity in neural systems (Loddick and Rothwell, 1999; Urban et al., 2012). Pellecchia et al. (2010) measured serum levels of IGF-I, IGF-II, insulin, IGF-binding protein 1 (IGF-BP1), and IGFbinding protein 3 (IGF-BP3) in MSA and control groups. They indicate that MSA has increased levels of IGF-I and insulin in circulation but normal concentration of IGF-II and IGF-BP. In a further study (Numao et  al., 2014), significantly elevated serum levels of IGF-I were observed in MSA patients when compared with PD, PSP, and controls.

More interestingly, IGF-I levels were found to increase as the disease progressed in MSA, whereas the serum IGF-I levels decreased with disease progression in PD and PSP. These findings suggest that IGF-I may be a candidate of biomarker to differentiate MSA.

Flt3 ligand The Flt3 ligand belongs to a small family of hematopoietic cytokines for class III tyrosine kinase receptors and plays an important role in hematopoiesis (Lyman and Jacobsen, 1998; Wodnar-Filipowicz, 2003). CSF Flt3 ligand concentration was significantly lower in MSA than in AD, PD, and control groups. It differentiated MSA from PD with an excellent sensitivity of 99% and specificity of 95% and MSA from controls with 95% sensitivity and 90% specificity (Shi et al., 2011).

GH The secretion of growth hormone (GH) is controlled by a complex neuroendocrine regulatory system. The hypothalamic hormones GH-releasing hormone (GHRH) and somatostatin exert primary stimulatory and inhibitory controls, respectively, on GH secretion. These two hypothalamic neurohormones are modulated by a host of neurotransmitters, particularly the noradrenergic and cholinergic ones. GH release can be induced by the activation of hypothalamic α2-adrenergic and muscarinic cholinergic receptors through the regulatory interplay of GHRH and somatostatin, which could be altered in some pathological conditions (Frohman et  al., 1992; Muller et al., 1999; Pellecchia et al., 2006). Pellecchia et  al. (2005) compared the GH levels of MSA, PD, and control groups in response to clonidine and arginine. Following the administration of clonidine, an α2-adrenergic agonist, and arginine, GH levels increased in PD and controls but not in MSA. The arginine GH test (AGHT), with 100% sensitivity and specificity, was thought to be more accurate than the clonidine GH test (CGHT), with a sensitivity of 80% and a specificity of 75%, when distinguishing MSA from PD. Further, they found that AGHT differentiated MSA-P from PSP, with 78% sensitivity and 96% specificity, and MSA-P from PD, with 92% sensitivity and 96% specificity (Pellecchia et  al., 2008). Zhang et al. (2010) held the opposite opinion that the sensitivity and the specificity were higher in the CGHT than in the AGHT. Therefore, a combination of the two tests is recommended. However, a different study (Gardner and

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

656      F. Zhang et al.: Biomarkers of multiple system atrophy Schmahmann, 2010) showed that the AGHT was not a reliable method to differentiate MSA-C from idiopathic lateonset cerebellar ataxias, genetic ataxias, or even healthy controls. When measured in the absence of the various stimuli, serum GH levels are not significantly different among the MSA, PD, PSP, and control groups (Numao et al., 2014).

Biomarkers associated with oxidative stress

Atrophy Rating Scale changes were remarkably lower in patients with high uric acid. Uric acid may have a neuroprotective effect against MSA progression due to its antioxidative properties. However, the serum levels of urate were found to be significantly lower in MSA and PD when compared to PSP and CBD, and there might be a gender disparity in such differences. In contrast, the CSF levels of urate were similar between those diseases (Chen et al., 2009; Winquist et al., 2010; Constantinescu et al., 2013).

C3 and FH

Metabolites of neurotransmitters

Complement 3 (C3) plays an important role in the complement cascade, and its proteolytic fragments facilitate the stimulation of inflammatory responses. In the complement cascade, C3 acts as a C5 convertase, whereas complement factor H (FH) regulates the formation and function of C3 and C5 convertase enzymes (Ingram et al., 2010). A study by Wang et al. (2011) indicated that the C3/FH ratio could be a potential biomarker to differentiate MSA from control, AD, and PD. The authors reported that this ratio had a high sensitivity and specificity when distinguishing among those groups (MSA from control: 85% sensitivity and 81% specificity, MSA from PD: 80% sensitivity and 87% specificity, and MSA from AD: 70% sensitivity and 95% specificity).

Neurotransmitters function as chemical messengers that transfer signals between neurons and are also involved in the development, plasticity, neurodegeneration, and neuroprotection of the nervous system (Leonelli et al., 2009). The levels of their metabolites may reflect the neurons’ metabolism and function. A study by Botez and Young (2001) identified a striatal dopamine reduction in MSA-C (also known as olivopontocerebellar atrophy or OPCA). The CSF levels of the dopamine metabolite homovanillic acid (HVA), the noradrenaline metabolite MHPG, and thiamine were significantly lower in MSA-C patients. The decrease in CSF levels of the serotonin metabolite 5-hydroxindoleacetic acid (5-HIAA) was not remarkable; however, there are still conflicts about these metabolites. An earlier study (Kish et  al., 1992) found normal 5-hydroxytryptamine (5-HT) but elevated 5-HIAA levels in the cerebellar cortex of MSA-C patients. Another study (Abdo et al., 2004) discovered that the CSF levels of 5-HIAA and MHPG were significantly lower in MSA patients when compared with PD patients, whereas the difference in HVA was modest. HVA was associated with the progress of MSA, but 5-HIAA and MHPG were associated with the autonomic dysfunction in the patients. Abdo et al. (2007a) found that MHPG differentiated MSA-P from PD with a high sensitivity and specificity ( > 80%). Moreover, a recent study (Goldstein et  al., 2012) showed that the CSF level of dihydroxyphenylacetic acid (DOPAC) might be a good indicator of brain tissue dopamine metabolism, which was able to distinguish PD from controls with 100% sensitivity and 89% specificity but was of no value in distinguishing PD from MSA. For those metabolites, only MHPG discriminated MSA from PD at a lower CSF level with a high sensitivity and specificity. MBP showed a decreased CSF concentration in MSA vs. PD. DOPAC failed to distinguish MSA from PD. The changes in CSF levels of HVA and 5-HIAA in MSA compared to PD remain uncertain.

Cystatin C Cystatin C is a cysteine protease inhibitor that is involved in the pathophysiological process of neurodegenerative disorders. Evidence has revealed that cystatin C binds to β-amyloid, resulting in the inhibition of β-amyloid deposition in senile plaques of AD (Sastre et al., 2004; Kaeser et al., 2007; Kanhai et al., 2014). The CSF level of cystatin C was found to be significantly lower in MSA when compared to controls, which indicated that a protease inhibitor, such as cystatin C, might be involved in the neurodegenerative process of MSA (Yamamoto-Watanabe et al., 2010).

Uric acid and urate Uric acid and urate levels in serum are closely linked to the risk of PD and MSA. In one study, higher serum levels of uric acid were found to be associated with a lower risk and slower progress of PD and MSA (Lee et  al., 2011). The researchers found that the Unified Multiple System

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

F. Zhang et al.: Biomarkers of multiple system atrophy      657

BBB-related biomarkers The BBB regulates the transport of molecules and cells in and out of the brain, which keeps the brain functioning normally and protected from bloodborne toxins, pathogenic proteins, and cells. A compromised BBB is a complicating factor for a number of neurological diseases (Wolburg and Lippoldt, 2002; Kim et  al., 2012). In PD, a loss of BBB integrity is associated with the infiltration of cytotoxic factors, such as tumor necrosis factor-α (TNF-α), which are involved in the progression of the disease (Qin et al., 2007). Abdo et  al. (2004) found that the ratio between albumin in the CSF and serum (the CSF/serum albumin index, CSF-AI) was remarkably higher in MSA when compared to PD, but there were no differences between MSA-C and MSA-P. This elevated ratio implies the impairment of the BBB in MSA patients. Song et  al. (2011) evaluated BBB impairment in MSA patients using the CSF-AI and the volume transfer coefficient (Ktrans), a permeability parameter in magnetic resonance imaging (MRI), and found that both worsened significantly in MSA according to the clinical severity. Another research study (Lee et al., 2013) observed the BBB status according to CSF-AI in patients with MSA. They indicated that the index correlates closely with the disease progression and therefore could potentially act as a biomarker for the development of MSA.

Proteomics of CSF Ishigami et  al. (2012) developed a proteomic profiling strategy for parkinsonian diseases. CSF peptides/proteins from 37 PD patients, 32 MSA patients, and 26 patients with other neurological diseases were purified with C8 magnetic beads, and spectra were obtained by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The statistical methods of principal component analysis (PCA) and support vector machines (SVM) were used in dimension reduction and pattern classification. The results of these analyses indicated that the proteomic patterns of PD and MSA were significantly different from controls; however, the difference between PD and MSA was not that remarkable. SVM showed that the peak at m/z 6250 was highly expressed in controls, less so in PD, and at the lowest level in MSA, which could be regarded as a potential biomarker to differentiate PD and MSA in the early stages when these diseases are nearly indistinguishable according to the clinical features. The peak at m/z 6250 was considered as secretogranin 1 (chromogranin B)

fragment II. Chromogranin B is a neuron-specific protein that has been associated with the stimulation of neurite outgrowth. The underlying mechanism for the decrease of chromogranin B fragments in parkinsonian diseases remains unspecified but may be related to synaptic or neuronal loss (Constantinescu et al., 2010b).

Summary The diagnosis of MSA is now based on clinical investigations: symptoms, physical examinations, and imaging. According to a consensus (Gilman et  al., 2008), three levels of certainty of the diagnosis were established: possible, probable, and definite MSA, with the definite diagnosis requiring an autopsy confirmation. The two categories of MSA have their specific clinical features. MSA-P is characterized by a rapidly progressive parkinsonism that responds poorly to levodopa treatment. MSA-C is distinguished by cerebellar ataxia with atrophy of the putamen, middle cerebellar peduncle, or pons on MRI. However, these features are atypical in the early stages of the disease. A diagnosis of MSA can be confused with PD, hereditary or nonhereditary cerebellar ataxia, and other atypical parkinsonism, such as PSP, CBD, and DLB. The CSF biomarkers for MSA represent the expected new approach to making an early and precise diagnosis or even for predicting the progression of this disease before the manifestation of observable symptoms. The National Institutes of Health Biomarkers Definitions Working Group defined a biomarker as ‘a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention’ (Biomarkers Definitions Working Group, 2001). An ideal biomarker of a disease must have high sensitivity and specificity and an easy and economic measurement and should be obtainable through a procedure that is harmless to the patients. A number of candidate peptides, proteins, and metabolites have been discussed above, and their properties for differentiating MSA from other diseases are summarized in Table 1. Compared to PD, we believe that the τ protein, NF-L, Flt3 ligand, the C3/FH ratio, and MHPG all have promise for being the candidate biomarker of MSA. The application of imaging methods to MSA diagnosis has identified two features, the ‘cross sign’ and ‘putaminal slit’, which are exhibited in the MRI scans of MSA patients. However, the ‘cross sign’ presents in MSA-C primarily before 5 years and later in MSA-P. Moreover, the ‘putaminal slit’ exhibits

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

658      F. Zhang et al.: Biomarkers of multiple system atrophy Table 1 Biomarkers for differentiation of MSA (with sensitivity/specificity). Biomarkers

 

MSA from PD

 

MSA from PSP 

MSA from AD  

CSF τ protein   α-syn and   p-τ% DJ-1 and p-τ%   CSF NfHSMI35   CSF NF-L   CSF NfHp35   CSF α-syn   Oligo pS α-syn  CSF Aβ-42   CSF Flt3 ligand  CSF C3/FH   CSF cystatin C   CSF HVA   CSF MHPG   CSF MBP   CSF 5-HIAA   CSF DOPAC   Serum IGF-I   Serum urate   CSF-AI   AGHT   CGHT  

↑ (95%/77%) (90%/71%)

   

   

   

        –  ↑   ↓/–   ↓ (99%/95%)   ↓ (80%/87%)     ↓/–   ↓ ( > 80%/ > 80%)   ↓   ↑/↓/–   –  ↑     ↑     (92%/96%)a (80%/75%)a  

    –        ↓/–                   ↑   ↓ (in men)     (78%/96%)    

              ↓   ↓ (90%/95%)                        

↑ ↑ ↑

MSA from controls

 

MSA-P vs. MSA-C

   

–

(90%/70%)

    ↑↑         –  ↓ (95%/90%)   ↓ (85%/81%)   ↓             ↑   –       

–

–

There are conflicts about the sensitivity and specificity of those tests.

a

mainly within 3 to 6  years in MSA-P and takes at least 4 years to show even a unilateral change in MSA-C (Horimoto et al., 2002; Abe et al., 2006). The differences in CSF levels of the biomarkers appear much earlier than these structural changes and are more precise and objective measures than either imaging or clinical assessments.

However, clinical assessments are more reliable when distinguishing from controls. We believe that the assessments of levels of NF-L, Flt3 ligand, and the C3/FH ratio could be helpful in the differential diagnosis of MSA vs. controls (Figure 1). The CSF C3/FH ratio might be beneficial for discriminating MSA from AD, which is also

Figure 1 Candidate biomarkers of MSA vs. PD and controls. In CSF, we believe that the τ protein, NF-L, Flt3 ligand, the C3/FH ratio, and MHPG could be the candidate biomarkers of MSA vs. PD and that the NF-L, Flt3 ligand, and C3/FH ratio are suitable when compared to controls. In serum, IGF-I would be helpful in recognizing MSA from both PD and controls.

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

F. Zhang et al.: Biomarkers of multiple system atrophy      659

characterized by cognitive impairment and progressive dementia (Blennow et al., 2010). PSP patients present with symptoms including postural instability, supranuclear vertical gaze palsy, retrocollis, frontal lobe symptoms, and dementia (Rehman, 2000). Serum IGF-I and AGHT would be the candidate biomarkers for distinguishing MSA from this disorder. Here, we have briefly summarized the candidate biomarkers that can differentiate MSA from other neurological disorders. A number of studies have elucidated the underlying pathways and mechanisms of MSA, such as oxidative stress (Stefanova et al., 2005; Ubhi et al., 2009) and abnormal modifications of α-syn (Beyer, 2006; Oueslati et al., 2010). A further investigation of these pathways is likely to uncover additional indicators with ideal levels of accuracy. The biomarkers that can be used in the clinical field promise to become an earlier and more precise method of diagnosis of the disease and will also aid in the progress toward a deeper understanding of the pathology of MSA and the development of potential therapeutics to treat this disease. Conflict of interest statement: There are no any real or perceived conflicts of interest to disclose.

References Abdo, W.F., De Jong, D., Hendriks, J.C., Horstink, M.W., Kremer, B.P., Bloem, B.R., and Verbeek, M.M. (2004). Cerebrospinal fluid analysis differentiates multiple system atrophy from Parkinson’s disease. Mov. Disord. 19, 571–579. Abdo, W.F., Bloem, B.R., Van Geel, W.J., Esselink, R.A., and Verbeek, M.M. (2007a). CSF neurofilament light chain and tau differentiate multiple system atrophy from Parkinson’s disease. Neurobiol. Aging 28, 742–747. Abdo, W.F., van de Warrenburg, B.P., Kremer, H.P., Bloem, B.R., and Verbeek, M.M. (2007b). CSF biomarker profiles do not differentiate between the cerebellar and parkinsonian phenotypes of multiple system atrophy. Parkinsonism Relat. Disord. 13, 480–482. Abe, K., Hikita, T., Yokoe, M., Mihara, M., and Sakoda, S. (2006). The “cross” signs in patients with multiple system atrophy: a quantitative study. J. Neuroimaging 16, 73–77. Aerts, M.B., Esselink, R.A., Abdo, W.F., Bloem, B.R., and Verbeek, M.M. (2012). CSF alpha-synuclein does not differentiate between parkinsonian disorders. Neurobiol. Aging 33, 430, e1–e3. Andreasen, N. and Blennow, K. (2002). Beta-amyloid (Abeta) protein in cerebrospinal fluid as a biomarker for Alzheimer’s disease. Peptides 23, 1205–1214. Arima, K., Murayama, S., Mukoyama, M., and Inose, T. (1992). Immunocytochemical and ultrastructural studies of neuronal and oligodendroglial cytoplasmic inclusions in multiple system

atrophy. 1. Neuronal cytoplasmic inclusions. Acta Neuropathol. 83, 453–460. [PubMed: 1320321]. Beyer, K. (2006). Alpha-synuclein structure, posttranslational modification and alternative splicing as aggregation enhancers. Acta Neuropathol. 112, 237–251. Biomarkers Definitions Working Group (2001). Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69, 89–95. Blennow, K., Hampel, H., Weiner, M., and Zetterberg, H. (2010). Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat. Rev. Neurol. 6, 131–144. Botez, M.I. and Young, S.N. (2001). Biogenic amine metabolites and thiamine in cerebrospinal fluid in heredo-degenerative ataxias. Can. J. Neurol. Sci. 28, 134–140. Brettschneider, J., Petzold, A., Süssmuth, S.D., Landwehrmeyer, G.B., Ludolph, A.C., Kassubek, J., and Tumani, H. (2006). Neurofilament heavy-chain NfH(SMI35) in cerebrospinal fluid supports the differential diagnosis of parkinsonian syndromes. Mov. Disord. 21, 2224–2227. Chen, H., Mosley, T.H., Alonso, A., and Huang, X. (2009). Plasma urate and Parkinson’s disease in the Atherosclerosis Risk in Communities (ARIC) study. Am. J. Epidemiol. 169, 1064–1069. Constantinescu, R., Zetterberg, H., Holmberg, B., and Rosengren, L. (2009). Levels of brain related proteins in cerebrospinal fluid: an aid in the differential diagnosis of parkinsonian disorders. Parkinsonism Relat. Disord. 15, 205–212. Constantinescu, R., Rosengren, L., Johnels, B., Zetterberg, H., and Holmberg, B. (2010a). Consecutive analyses of cerebrospinal fluid axonal and glial markers in Parkinson’s disease and atypical parkinsonian disorders. Parkinsonism Relat. Disord. 16, 142–145. Constantinescu, R., Andreasson, U., Li, S., Podust, V.N., Mattsson, N., Anckarsäter, R., Anckarsäter, H., Rosengren, L., Holmberg, B., Blennow, K., et al. (2010b). Proteomic profiling of cerebrospinal fluid in parkinsonian disorders. Parkinsonism Relat. Disord. 16, 545–549. Constantinescu, R., Andreasson, U., Holmberg, B., and Zetterberg, H. (2013). Serum and cerebrospinal fluid urate levels in synucleinopathies versus tauopathies. Acta Neurol. Scand. 127, e8–e12. Dickson, D.W., Lin, W., Liu, W.K., and Yen, S.H. (1999). Multiple system atrophy: a sporadic synucleinopathy. Brain Pathol. 9, 721–732. Foulds, P.G., Yokota, O., Thurston, A., Davidson, Y., Ahmed, Z., Holton, J., Thompson, J.C., Akiyama, H., Arai, T., Hasegawa, M., et al. (2012). Post mortem cerebrospinal fluid alpha-synuclein levels are raised in multiple system atrophy and distinguish this from the other alpha-synucleinopathies, Parkinson’s disease and dementia with Lewy bodies. Neurobiol. Dis. 45, 188–195. Frohman, L.A., Downs, T.R., and Chomczynski, P. (1992). Regulation of growth hormone secretion. Front. Neuroendocrinol. 13, 344–405. Gardner, R.C. and Schmahmann, J.D. (2010). Arginine test is not reliable for diagnosing cerebellar multiple system atrophy. Ann. Neurol. 67, 404–408. George, S., Rey, N.L., Reichenbach, N., Steiner, J.A., and Brundin, P. (2013). Alpha-synuclein: the long distance runner. Brain Pathol. 23, 350–357.

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

660      F. Zhang et al.: Biomarkers of multiple system atrophy Gilman, S., Wenning, G.K., Low, P.A., Brooks, D.J., Mathias, C.J., Trojanowski, J.Q., Wood, N.W., Colosimo, C., Dürr, A., Fowler, C.J., et al. (2008). Second consensus statement on the diagnosis of multiple system atrophy. Neurology 71, 670–676. Goldstein, D.S., Holmes, C., and Sharabi, Y. (2012). Cerebrospinal fluid biomarkers of central catecholamine deficiency in Parkinson’s disease and other synucleinopathies. Brain 135, 1900–1913. Hall, S., Ö hrfelt, A., Constantinescu, R., Andreasson, U., Surova, Y., Bostrom, F., Nilsson, C., Håkan, W., Decraemer, H., Någga, K., et al. (2012). Accuracy of a panel of 5 cerebrospinal fluid biomarkers in the differential diagnosis of patients with dementia and/or parkinsonian disorders. Arch. Neurol. 69, 1445–1452. Hashimoto, M. and Masliah, E. (1999). Alpha-synuclein in Lewy body disease and Alzheimer’s disease. Brain Pathol. 9, 707–720. Holmberg, B., Rosengren, L., Karlsson, J.E., and Johnels, B. (1998). Increased cerebrospinal fluid levels of neurofilament protein in progressive supranuclear palsy and multiple-system atrophy compared with Parkinson’s disease. Mov. Disord. 13, 70–77. Holmberg, B., Johnels, B., Ingvarsson, P., Eriksson, B., and Rosengren, L. (2001). CSF-neurofilament and levodopa tests combined with discriminant analysis may contribute to the differential diagnosis of parkinsonian syndromes. Parkinsonism Relat. Disord. 8, 23–31. Holmberg, B., Johnels, B., Blennow, K., and Rosengren, L. (2003). Cerebrospinal fluid Abeta42 is reduced in multiple system atrophy but normal in Parkinson’s disease and progressive supranuclear palsy. Mov. Disord. 18, 186–190. Horimoto, Y., Aiba, I., Yasuda, T., Ohkawa, Y., Katayama, T., Yokokawa, Y., Goto, A., and Ito, Y. (2002). Longitudinal MRI study of multiple system atrophy – when do the findings appear, and what is the course? J. Neurol. 249, 847–854. Ingram, G., Hakobyan, S., Hirst, C.L., Harris, C.L., Pickersgill, T.P., Cossburn, M.D., Loveless, S., Robertson, N.P., and Morgan, B.P. (2010). Complement regulator factor H as a serum biomarker of multiple sclerosis disease state. Brain 133, 1602–1611. Ishigami, N., Tokuda, T., Ikegawa, M., Komori, M., Kasai, T., Kondo, T., Matsuyama, Y., Nirasawa, T., Thiele, H., Tashiro, K., et al. (2012). Cerebrospinal fluid proteomic patterns discriminate Parkinson’s disease and multiple system atrophy. Mov. Disord. 27, 851–857. Kaeser, S.A., Herzig, M.C., Coomaraswamy, J., Kilger, E., Selenica, M.L., Winkler, D.T., Staufenbiel, M., Levy, E., Grubb, A., and Jucker, M. (2007). Cystatin C modulates cerebral b-amyloidosis. Nat. Genet. 39, 1437–1439. Kanhai, D.A., de Kleijn, D.P., Kappelle, L.J., Uiterwaal, C.S., van der Graaf, Y., Pasterkamp, G., Geerlings, M.I., Visseren, F.L.; SMART Study Group. (2014). Extracellular vesicle protein levels are related to brain atrophy and cerebral white matter lesions in patients with manifest vascular disease: the SMART-MR study. BMJ Open 4, e003824. Kato, S., Nakamura, H., Hirano, A., Ito, H., Llena, J.F., and Yen, SH. (1991). Argyrophilic ubiquitinated cytoplasmic inclusions of Leu-7-positive glial cells in olivopontocerebellar atrophy (multiple system atrophy). Acta Neuropathol. 82, 488–493. Kim, S.Y., Buckwalter, M., Soreq, H., Vezzani, A., and Kaufer, D. (2012). Blood-brain barrier dysfunction-induced inflammatory signaling in brain pathology and epileptogenesis. Epilepsia 53, 37–44.

Kish, S.J., Robitaille, Y., Schut, L., el-Awar, M., Ball, M.J., and Shannak, K. (1992). Normal serotonin but elevated 5-hydroxyindoleacetic acid concentration in cerebellar cortex of patients with dominantly-inherited olivopontocerebellar atrophy. Neurosci. Lett. 144, 84–86. Lee, J.E., Song, S.K., Sohn, Y.H., and Lee, P.H. (2011). Uric acid as a potential disease modifier in patients with multiple system atrophy. Mov. Disord. 26, 1533–1536. Lee, J.E., Song, S.K., Hong, J.Y., Sunwoo, M.K., Park, H.J., Sohn, Y.H., and Lee, P.H. (2013). Changes in the blood-brain barrier status closely correlate with the rate of disease progression in patients with multiple system atrophy: a longitudinal study. Parkinsonism Relat. Disord. 19, 450–452. Leonelli, M., Torrao, A.S., and Britto, L.R. (2009). Unconventional neurotransmitters, neurodegeneration and neuroprotection. Braz. J. Med. Biol. Res. 42, 68–75. Loddick, S.A. and Rothwell, N.J. (1999). Mechanisms of tumor necrosis factor alpha action on neurodegeneration: interaction with insulin-like growth factor-1. Proc. Natl. Acad. Sci. USA 96, 9449–9451. Lyman, S.D. and Jacobsen, S.E. (1998). c-kit ligand and Flt3 ligand: stem/progenitor cell factors with overlapping yet distinct activities. Blood 91, 1101–1134. Mandelkow, E.M. and Mandelkow, E. (2012). Biochemistry and cell biology of tau protein in neurofibrillary degeneration. Cold Spring Harb. Perspect. Med. 2, a006247. Mollenhauer, B., Locascio, J.J., Schulz-Schaeffer, W., Sixel-Döring, F., Trenkwalder, C., and Schlossmacher, M.G. (2011). Alphasynuclein and tau concentrations in cerebrospinal fluid of patients presenting with parkinsonism: a cohort study. Lancet Neurol. 10, 230–240. Muller, E.E., Locatelli, V., and Cocchi, D. (1999). Neuroendocrine control of growth hormone secretion. Physiol. Rev. 79, 511–607. Nakazato, Y., Yamazaki, H., Hirato, J., Ishida, Y., and Yamaguchi, H. (1990). Oligodendroglial microtubular tangles in olivopontocerebellar atrophy. J. Neuropathol. Exp. Neurol. 49, 521–530. Numao, A., Suzuki, K., Miyamoto, M., Miyamoto, T., and Hirata, K. (2014). Clinical correlates of serum insulin-like growth factor-1 in patients with Parkinson’s disease, multiple system atrophy and progressive supranuclear palsy. Parkinsonism Relat. Disord. 20, 212–216. Otto, M., Esselmann, H., Schulz-Shaeffer, W., Neumann, M., Schröter, A., Ratzka, P., Cepek, L., Zerr, I., Steinacker, P., Windl, O., et al. (2000). Decreased beta-amyloid1-42 in cerebrospinal fluid of patients with Creutzfeldt-Jakob disease. Neurology 54, 1099–1102. Oueslati, A., Fournier, M., and Lashuel, H.A. (2010). Role of posttranslational modifications in modulating the structure, function and toxicity of a-synuclein: implications for Parkinson’s disease pathogenesis and therapies. Prog. Brain Res. 183, 115–145. Papp, M.I., Kahn, J.E., and Lantos, P.L. (1989). Glial cytoplasmic inclusions in the CNS of patients with multiple system atrophy (striatonigral degeneration, olivopontocerebellar atrophy and Shy-Drager syndrome). J. Neurol. Sci. 94, 79–100. Pellecchia, M.T., Pivonello, R., Salvatore, E., Faggiano, A., Barone, P., De Michele, G., Lombardi, G., Colao, A., and Filla, A. (2005). Growth hormone response to arginine test distinguishes

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

F. Zhang et al.: Biomarkers of multiple system atrophy      661 multiple system atrophy from Parkinson’s disease and idio­ pathic late-onset cerebellar ataxia. Clin. Endocrinol. (Oxf.) 62, 428–433. Pellecchia, M.T., Pivonello, R., Colao,A., and Barone, P. (2006). Growth hormone stimulation tests in the differential diagnosis of Parkinson’s disease. Clin. Med. Res. 4, 322–325. Pellecchia, M.T., Longo, K., Manfredi, M., Lucetti, C., Cossu, G., Petrone, A., Marconi, R., Sensi, M., Epifanio, A., Eleopra, R., et al. (2008). The arginine growth hormone stimulation test in bradykinetic-rigid parkinsonisms. Mov. Disord. 23, 190–194. Pellecchia, M.T., Pivonello, R., Longo, K., Manfredi, M., Tessitore, A., Amboni, M., Pivonello, C., Rocco, M., Cozzolino, A., Colao, A., et al. (2010). Multiple system atrophy is associated with changes in peripheral insulin-like growth factor system. Mov. Disord. 25, 2621–2626. Perrot, R., Berges, R., Bocquet, A., and Eyer, J. (2008). Review of the multiple aspects of neurofilament functions, and their possible contribution to neurodegeneration. Mol. Neurobiol. 38, 27–65. Pfeiffer, R.F. (2007). Multiple system atrophy. Handb. Clin. Neurol. 84, 305–326. Qin, L., Wu, X., Block, M.L., Liu, Y., Breese, G.R., Hong, J.S., Knapp, D.J., and Crews, F.T. (2007). Systemic LPS causes chronic neuroinflammation and progressive neurodegeneration. Glia 55, 453–462. Rehman, H.U. (2000). Progressive supranuclear palsy. Postgrad. Med. J. 76, 333–336. Saracchi, E., Fermi, S., and Brighina, L. (2014). Emerging candidate biomarkers for Parkinson’s disease: a review. Aging Dis. 5, 27–34. Sastre, M., Calero, M., Pawlik, M., Mathews, P.M., Kumar, A., Danilov, V., Schmidt, S.D., Nixon, R.A., Frangione, B., and Levy, E. (2004). Binding of cystatin C to Alzheimer’s amyloid beta inhibits in vitro amyloid fibril formation. Neurobiol. Aging 25, 1033–1043. Shi, M., Bradner, J., Hancock, A.M., Chung, K.A., Quinn, J.F., ­Peskind, E.R., Galasko, D., Jankovic, J., Zabetian, C.P., Kim, H.M., et al. (2011). Cerebrospinal fluid biomarkers for Parkinson disease diagnosis and progression. Ann. Neurol. 69, 570–580. Sjögren, M., Minthon, L., Davidsson, P., Granérus, A.-K., Clarberg, A., Vanderstichele, H., Vanmechelen, E., Wallin, A., and Blennow, K. (2000). CSF levels of tau, beta-amyloid(1-42) and GAP-43 in frontotemporal dementia, other types of dementia and normal aging. J. Neural Transm. 107, 563–579. Song, S.K., Lee, S.K., Lee, J.J., Lee, J.E., Choi, H.S., Sohn, Y.H., and Lee, P.H. (2011). Blood-brain barrier impairment is functionally correlated with clinical severity in patients of multiple system atrophy. Neurobiol. Aging 32, 2183–2189. Stefanova, N., Reindl, M., Neumann, M., Haass, C., Poewe, W., Kahle, P.J., and Wenning, G.K. (2005). Oxidative stress in transgenic mice with oligodendroglial alpha-synuclein overexpres-

sion replicates the characteristic neuropathology of multiple system atrophy. Am. J. Pathol. 166, 869–876. Stefanova, N., Bücke, P., Duerr, S., and Wenning, G.K. (2009). Multiple system atrophy: an update. Lancet Neurol. 8, 1172–1178. Tamaoka, A., Kondo, T., Odaka, A., Sahara, N., Sawamura, N., Ozawa, K., Suzuki, N., Shoji, S., and Mori, H. (1994). Biochemical evidence for the long-tail form (Abeta1-42/43) of amyloid beta protein as a seed molecule in cerebral deposits of Alzheimer’s disease. Biochem. Biophys. Res. Commun. 205, 834–842. Ubhi, K., Lee, P.H., Adame, A., Inglis, C., Mante, M., Rockenstein, E., Stefanova, N., Wenning, G.K., and Masliah E. (2009). Mitochondrial inhibitor 3-nitroproprionic acid enhances oxidative modification of alpha-synuclein in a transgenic mouse model of multiple system atrophy. J. Neurosci. Res. 87, 2728–2739. Ubhi, K., Low, P., and Masliah, E. (2011). Multiple system atrophy: a clinical and neuropathological perspective. Trends Neurosci. 34, 581–590. Urban, M.J., Dobrowsky, R.T., and Blagg, B.S. (2012). Heat shock response and insulin-associated neurodegeneration. Trends Pharmacol. Sci. 33, 129–137. Verbeek, M.M., Abdo, W.F., De Jong, D., Horstink, M.W., Kremer, B.P., and Bloem, B.R. (2004). Cerebrospinal fluid Abeta42 levels in multiple system atrophy. Mov. Disord. 19, 238–240; author reply 240–241. Wang, Y., Hancock, A.M., Bradner, J., Chung, K.A., Quinn, J.F., Peskind, E.R., Galasko, D., Jankovic, J., Zabetian, C.P., Kim, H.M., et al. (2011). Complement 3 and factor H in human cerebrospinal fluid in Parkinson’s disease, Alzheimer’s disease, and multiple-system atrophy. Am. J. Pathol. 178, 1509–1516. Winquist, A., Steenland, K., and Shankar, A. (2010). Higher serum uric acid associated with decreased Parkinson’s disease prevalence in a large community-based survey. Mov. Disord. 25, 932–936. Wodnar-Filipowicz, A. (2003). Flt3 ligand: role in control of hematopoietic and immune functions of the bone marrow. News Physiol. Sci. 18, 247–251. Wolburg, H. and Lippoldt, A. (2002). Tight junctions of the bloodbrain barrier: development, composition and regulation. Vasc. Pharmacol. 38, 323–337. Yamamoto-Watanabe, Y., Watanabe, M., Jackson, M., Akimoto, H., Sugimoto, K., Yasujima, M., Wakasaya, Y., Matsubara, E., Kawarabayashi, T., Harigaya, Y., et al. (2010). Quantification of cystatin C in cerebrospinal fluid from various neurological disorders and correlation with G73A polymorphism in CST3. Brain Res. 1361, 140–145. Zhang, K., Zeng, Y., Song, C., Fu, Y., and Wan, Q. (2010). The comparison of clonidine, arginine and both combined: a growth hormone stimulation test to differentiate multiple system atrophy from idiopathic Parkinson’s disease. J. Neurol. 257, 1486–1491.

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM

662      F. Zhang et al.: Biomarkers of multiple system atrophy

Feng Zhang is a master’s candidate in the Department of Neurology of the First Affiliated Hospital of Dalian Medical University, Dalian. His research interests include neurodegenerative diseases and movement disorders.

Jianwen Chen is a master’s candidate in the Department of Neurology of the First Affiliated Hospital of Dalian Medical University, Dalian. Her research interests include neurodegenerative diseases and movement disorders.

Li Zhao received her MD in Dalian Medical University, Dalian. She is currently associate Professor in the Department of Neurology of the First Affiliated Hospital of Dalian Medical University. Her research interests include neuropsychology, counseling and clinical neurology.

Chunbo Dong received her MD in Dalian Medical University, Dalian. She is currently Professor and Chair in the Department of Neurology of the First Affiliated Hospital of Dalian Medical University. Her research interests include neurodegenerative diseases, neurological genetic diseases and movement disorders.

Brought to you by | HEC Bibliotheque Maryriam ET J. Authenticated Download Date | 6/19/15 12:51 AM