Multiple system atrophy (MSA) is a progressive neurodegenerative disorder characterized by parkinsonism, cerebellar ataxia and autonomic dysfunction. Pathogenic mechanisms remain obscure but the neuropathological hallmark is the presence of α-synuclein-immunoreactive glial cytoplasmic inclusions. Genetic variants of the α-synuclein gene, SNCA, are thus strong candidates for genetic association with MSA. One follow-up to a genome-wide association of Parkinson's disease has identified association of a SNP in SNCA with MSA.
We evaluated 32 SNPs in the SNCA gene in a European population of 239 cases and 617 controls recruited as part of the Neuroprotection and Natural History in Parkinson Plus Syndromes (NNIPPS) study. We used 161 independently collected samples for replication. Two SNCA SNPs showed association with MSA: rs3822086 (P = 0.0044), and rs3775444 (P = 0.012), although only the first survived correction for multiple testing. In the MSA-C subgroup the association strengthened despite more than halving the number of cases: rs3822086 P = 0.0024, OR 2.153, (95% CI 1.3–3.6); rs3775444 P = 0.0017, OR 4.386 (95% CI 1.6–11.7). A 7-SNP haplotype incorporating three SNPs either side of rs3822086 strengthened the association with MSA-C further (best haplotype, P = 8.7×10−4). The association with rs3822086 was replicated in the independent samples (P = 0.035).
We report a genetic association between MSA and α-synuclein which has replicated in independent samples. The strongest association is with the cerebellar subtype of MSA.
ClinicalTrials.gov NCT00211224. [NCT00211224]
Citation: Al-Chalabi A, Dürr A, Wood NW, Parkinson MH, Camuzat A, Hulot J-S, et al. (2009) Genetic Variants of the α-Synuclein Gene SNCA Are Associated with Multiple System Atrophy. PLoS ONE 4(9): e7114. doi:10.1371/journal.pone.0007114
Editor: Prof. Peter Heutink, VU University Medical Center and Center for Neurogenomics and Cognitive Research; VU University Medical Center and VU University, Amsterdam, the Netherlands, Netherlands
Received: March 19, 2009; Accepted: August 18, 2009; Published: September 22, 2009
Copyright: © 2009 Al-Chalabi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: NNIPPS was an academic-led study with core funding from the European Union 5th Framework Programme (QLG1-CT-2000-01262); support from French Health Ministry, Programme Hospitalier de Recherche Clinique (AOM97073, AOM01125) and from Sanofi-Aventis affiliates in the UK, France and Germany, providing an unconditional research grant and drug supply throughout the study. Genetic analysis was supported by the French Programme Hospitalier de Recherche Clinique (P040410). Three academic institutions (Institute of Psychiatry, King's College London; Assistance Publique-Hopitaux de Paris; and University of Ulm) were sponsors of the NNIPPS study in each country, and jointly own the data. We thank the Parkinson's Disease Society, Medical Research Council, the French and UK PSP Associations, the Sarah Matheson Trust, UCL Institute of Genetics and Health, the Department of Health via the National Institute for Health Research (NIHR) Specialist Biomedical Research Centre for Mental Health award to South London and Maudsley NHS Foundation Trust (SLaM) and the Institute of Psychiatry at King's College London, and the UK Parkinson's Disease Research Group for their help and support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Multiple system atrophy (MSA) is a rare progressive neurodegenerative disease characterized by parkinsonism, cerebellar dysfunction and dysautonomia corresponding to previous diagnostic appellations of striatonigral degeneration, olivopontocerebellar atrophy and Shy-Drager syndrome. Estimates of age-adjusted prevalence vary between 1.9 and 4.4 per 100,000 persons although this may represent an underestimate as post-mortem studies have suggested that as many as 5% of cases of clinically diagnosed Parkinson's disease may in fact have MSA. The converse is also true however, and in those recruited as part of the Neuroprotection and Natural History in Parkinson's Plus Syndromes (NNIPPS) study, about 7% of patients diagnosed with MSA at the start had a different diagnosis by the end .
Pathologically, the hallmark of MSA is α-synuclein-immunoreactive glial cytoplasmic inclusions in oligodendrocytes throughout the brain, associated with neuronal loss, loss of myelin, astrocytosis and a marked microglial reaction most prominent in brain regions involved in motor and supraspinal autonomic control. The presence of α-synuclein-immunoreactive pathology, which places MSA amongst the broad category of synucleinopathies including Parkinson's disease and dementia with Lewy bodies, suggests that an abnormality of α-synuclein may play a role in the mechanisms of cell death in MSA.
MSA is generally considered a sporadic condition. Indeed, the diagnostic consensus criteria for MSA specifically mention a family history of parkinsonism or ataxia as a feature not supportive of the diagnosis . Nonetheless, a few apparently familial cases have been described –. There have been few studies on genetic sequence variants in sporadic MSA – and no environmental risk factors have been consistently identified in large samples. A genetic association has now been identified between a gene variant in the α-synuclein gene (SNCA, OMIM accession *163890; Ensembl ENSG00000145335) and MSA .
We examined the association between SNCA variants and MSA using the DNA Bank of the NNIPPS cohort . This cohort has a nearly 50% autopsy rate for MSA so that the criteria for diagnosis can be validated pathologically, and in individual cases we can be certain of the diagnosis. The NNIPPS diagnostic criteria for MSA (Table 1) show excellent convergent validity with the investigators' assessment of diagnostic probability (point-biserial correlation: MSA rpb = 0.93, P<0.0001), and excellent predictive validity against histopathology [sensitivity and specificity (95% CI); 0.96 (0.88–0.99) and 0.91 (0.86–0.93)] , so the sample is likely to represent a more highly homogeneous diagnostic group than is usually possible. For replication of results, we analyzed a population of 78 pathologically verified cases from the Institute of Neurology Brain Bank and 83 clinically defined samples from a Parisian study (Table 2). We found that genetic variants of SNCA were associated with MSA and more specifically, with the subset of people who had cerebellar signs.
The protocol for this trial and supporting CONSORT checklist are published elsewhere .
Patients gave informed written consent prior to inclusion in the trial. Additional consent was obtained both for DNA sampling and post-mortem brain tissue donation. The protocol was approved by the Ethics Committees/Institutional Review Boards of each coordinating centre in the three participating countries. The trial was conducted according to International standards of Good Clinical Practice-(ICH guidelines and the Helsinki Declaration).
Subjects were recruited as part of the Neuroprotection and Natural History in Parkinson's Plus Syndromes (NNIPPS) study using the NNIPPS diagnostic criteria which have been described elsewhere together with the trial design, population description and treatment results  (Table 1). The 239 cases and 617 controls in this study were of European ancestry and matched for age (MSA mean age at sampling 62.84, control mean age 61.03) (Table 2). The clinical diagnosis at the study end was used to define MSA unless a pathological diagnosis was available. For exploratory sub-group analysis, patients were stratified as MSA-P or MSA-C based on the absence or presence of cerebellar signs at entry. 11 cases and 14 controls had a low genotyping rate (<90%) and were excluded from further analysis. 101 of the remaining cases were in the MSA-C subgroup. 251 patients with progressive supranuclear palsy (PSP) recruited within the same study were also tested for MSA-associated SNPs to exclude a recruitment bias as the explanation for any findings, as PSP is not a synucleinopathy and we would not therefore expect an MSA-associated SNCA SNP to be associated with PSP.
The NNIPPS study was an academic-led, multi-centre (UK, France, Germany), phase III trial of riluzole in MSA and progressive supranuclear palsy. Controls were recruited in the UK from the neurologically normal spouses of participating patients. In France and Germany, the controls were taken from existing DNA banks of neurologically normal controls.
Replication study samples
The 78 MSA samples from the Institute of Neurology Brain Bank (Table 2) fulfilled the consensus criteria for pathologically proven MSA . All were of UK ancestry. Of these, 68% had cerebellar signs. Samples were derived from blood.
The MSA samples from Paris (Table 2) were collected consecutively as part of a study on atypical Parkinsonism and cerebellar ataxia. There were 44 cases with Probable MSA and 44 with Possible MSA as defined by the consensus criteria . Of 88 samples, five were not of European ancestry and were therefore excluded from further analysis. Of these, 85% had cerebellar signs as the clinic specializes in cerebellar disease. Samples were derived from blood.
32 SNPs in and around SNCA were selected for association testing with MSA (Figure 1, Table 3). In addition, we genotyped the multi-allelic microsatellite repeat known as NACP-Rep1 which is situated within the promoter region ∼10 kbp upstream of the translational start point of SNCA at chromosome 4q21, using an ABI3130XL Genotyper (Applied Biosystems) and Genotyper v4.0 software. This complex microsatellite with sequence (TC)10–11TT(TC)8–11(TA)7–9(CA)10–11 has been variably associated with PD ,  but not MSA , although the numbers studied were small. There are five common alleles, each differing in size by two nucleotides, the greatest variability being in the CA portion with subsidiary variability in the (TC)8–11(TA)7–9 portion. However, ex vivo functional analysis suggests that the overall length of the microsatellite rather than its sequence, determines transcriptional regulation and hence SNCA gene expression . We numbered the alleles from 1 to 5 in order of increasing size.
The base pair position along chromosome 4 is shown by the top ruler. The position of the α-synuclein gene is shown in the next row down, with exons represented by vertical lines and introns by lines connecting them. The relative positions of the genotyped markers are shown below, with vertical lines connecting position to the linkage disequilibrium map. Asterisks show the two markers demonstrating association in MSA-C. Only the left-most marker showed association with MSA as a whole. (For a list of markers genotyped and P-values, see Table 3). The coloured triangle is the linkage disequilibrium heat map showing the strength of association between pairs of markers as measured by D′. Red is high and blue low with the other colours intermediate. The two associated SNPs are in different linkage disequilibrium blocks and are not in linkage disequilibrium with each other.
For the NNIPPS samples, DNA was extracted from venous blood samples collected into Li-heparin tubes by standard methods. SNPs were genotyped independently of the study group and blinded to case-control status by KBiosciences (Hoddesdon Herts, EN11 0EX, UK; www.kbioscience.co.uk) using a patent-protected competitive allele specific PCR system (KASPar) and Taqman™.
The Institute of Neurology pathological samples were genotyped for rs3822086 using Taqman™ assay (Applied Biosystems, Forster City, CA, USA).
The 83 Paris samples were genotyped for the single nucleotide polymorphism rs3822086 by sequencing in a single direction using the BigDye Terminator Cycle Sequencing kit v3.1 (Applied Biosystems, Forster City, CA, USA). Sequences were analysed using Seqscape v2.5 software.
Tests for Hardy-Weinberg equilibrium were performed for each SNP in controls using Fisher's exact test. A P-value<0.05 led to exclusion from further analysis. Tests for systematically missing genotypes in either cases or controls were performed to identify sample selection or genotyping problems preferentially affecting either group. Tests for missingness by genotypic status were also performed to identify errors relating to difficulty calling certain genotypes. Associated SNPs were further tested by looking for association in a tagging haplotype that excluded the associated SNP to reduce the likelihood of an artefactual association resulting from genotyping.
Assuming a lifetime MSA risk of 1 in 1000, and for a P-value close to the permutation corrected threshold of 0.05 (alpha = 0.005), there is 80% power to detect an odds ratio of 1.8 for a minor allele frequency (MAF) of 0.1, 1.6 for MAF 0.2 and 1.5 for MAF>0.2.
Genotypes for SNPs genotyped in the CEU HapMap sample but not in this study were imputed using IMPUTE  with a threshold of 0.9 and default values for other parameters. Subsequent analysis was performed in PLINK.
SNP analyses were performed in PLINK (http://pngu.mgh.harvard.edu/purcell/plink/) . Samples were tested for allelic association using the Mantel-Haenszel chi-squared test, stratifying by country of origin. Odds ratios were tested for homogeneity between countries using the Breslow-Day test. Association testing by Pearson chi-squared test was performed for the replication study to maximise numbers and therefore statistical power. Controls were those used in the primary analysis.
Multiple testing correction was performed using the Max(T) permutation procedure implemented in PLINK permuted within the strata of country of origin.
A multilocus genotype test examining whole gene association was performed using step-wise permutation implemented in PLINK.
Microsatellite alleles were tested for association by test using the permutation procedure instituted in CLUMP to account for the multiple ways that microsatellite alleles can be combined to form two groups.
SNP rs356220 showed missing genotypes in nearly 18% of controls compared with <1% of cases (P = 4.73×10−15) suggesting a systematic problem in genotyping of this SNP in control samples, and it was therefore excluded from further analyses. The remaining 31 SNPs were analysed for association with MSA.
Two SNPs showed association with MSA in the NNIPPS samples: rs3822086 (P = 0.0044), and rs3775444 (P = 0.012) (Table 3). Only rs3822086 survived multiple testing correction for association with MSA (P = 0.047). A step-wise whole gene permutation test gave P = 0.029 with the same two SNPs retained. We repeated the analysis in the MSA-C subgroup for these two SNPs and found the association strengthened despite more than halving the number of cases: rs3822086 P = 0.0024, OR 2.153, (95% CI 1.3–3.6, Breslow-Day test for homogeneity, P = 0.81); rs3775444 P = 0.0017, OR 4.386 (95% CI 1.6–11.7, Breslow-Day test P = 0.36); step-wise whole gene permutation test P = 0.0084.
A haplotype of six surrounding SNPs was identified correlating with rs3822086 at r2>0.5. Without rs3822086 included, this still showed association at P = 0.048, increasing confidence that the association observed was not due to a genotyping artefact. Including rs3822086 strengthened the association with MSA-C. The most strongly associated haplotype, GGATGGT gave P = 8.7×10−4, omnibus test P = 0.027.
As expected, testing of rs3822086 and rs3775444 in PSP showed no association, with unadjusted P-values of 0.112 and 0.242 respectively.
NACP-Rep1 Microsatellite analyses
Permutation-based CLUMP analysis showed no association (P = 0.094).
The samples from the Institute of Neurology Brain Bank and Paris confirmed association of rs3822086 with MSA (P = 0.035) with odds ratio 1.75 (95% C.I. 1.05–2.89).
After imputation of genotypes at ungenotyped SNPs there were a total of 318 SNPs tested, with genotypes predicted at 97.2% accuracy. SNP rs3822086 remained the most strongly associated with MSA. An MSA-associated SNP identified in another study , rs11931074, was also associated with MSA in this study (P = 0.025). For the MSA-C subgroup, rs3775444 and rs3822086 again remained the most strongly associated SNPs. As for the SNPs in this study, rs11931074 was more strongly associated with MSA-C than with MSA alone (P = 0.0125).
We have found two positive associations in the SNCA gene with MSA, one with rs3822086 and the other with rs3775444, although only one survives correction for multiple testing. The association is significant because of the role of α-synuclein in the underlying pathology of MSA. Because the phenotypic spectrum of MSA is broad and the relative frequency of cerebellar and parkinsonian presentations appears to be influenced by ethnicity  we stratified our cases as MSA-C and MSA-P to explore possible differences in association between these phenotypes in our sample. We observed a stronger association of SNCA variants with MSA-C than with MSA as a whole. This is intriguing and requires exploration in other studies, but may indicate that interactions between SNCA gene variants and other risk factors influence phenotype in MSA.
Until recently, studies of polymorphisms of SNCA had failed to demonstrate any association with MSA either by sequencing the entire coding region in a small number of Japanese cases  or by genotyping two microsatellite markers, one in the promoter and the other an intron of SNCA in 47 cases from the UK , . A study examining SNPs prioritized in a genome-wide association study of Parkinson's disease for follow-up testing in MSA has now identified a strong association of homozygosity for the T allele of SNP rs11931074 and MSA . This SNP has a similar minor allele frequency (0.056) to rs3822086 (0.058) and the two SNPs are in strong linkage disequilibrium (D′ 0.977, r2 0.922). It is therefore not surprising that rs11931074 shows association with both MSA and MSA-C in our study, although the association is not as strong as for rs3822086. It would be of interest to impute rs3822086 in the genome-wide association study samples to see if the stronger association of this SNP persists in that sample set. Nevertheless, this suggests that both rs3822086 and rs11931074 are tagging the same functional genetic variation. Given that both have a relatively low minor allele frequency, this may be a rare haplotype or variant.
The associated variants we have identified are both intronic, and neither is close to a splice site, nor are they predicted to disrupt or alter splicing. They are not in intronic splice enhancer sites, nor alternative cassette exons. They are not especially conserved and are not obviously regulatory. It is therefore likely that a different SNP tagged by these variants is the functional variant, and this is further supported by the haplotypic association we identified for SNPs surrounding rs3822086, which persists even when this SNP is excluded.
There are several factors that could confound this study. For example, population stratification can lead to false positive results. We used three strategies to minimize this. Firstly, the samples were all of European ancestry; secondly we stratified the primary analysis by country of origin; and thirdly we replicated the findings in an independent set of cases. The associated SNP survived multiple testing correction, increasing confidence in the association. Furthermore, the global gene-wise evidence for association was significant and requires no further multiple testing correction making a false positive result less likely. Phenotypic heterogeneity was minimized by using validated clinical criteria with excellent inter-observer agreements, and pathological verification where possible. The possibility of bias inherent in the selection process for enrolment to the NNIPPS study was excluded by testing the MSA-associated SNP for association with the different disease PSP, also using the NNIPPS study samples. PSP is not expected to have an abnormality in the SNCA gene since it is not a synucleinopathy: no association was detected. Systematic genotyping errors can lead to false positive results, but we observed strict, comprehensive quality control measures. Furthermore, a haplotype using a set of SNPs surrounding the associated SNP and which correlated with the genotype, also detected the association suggesting that this is not an artefact at the tested SNP.
Our findings show that genetic variation in the α-synuclein gene is associated with sporadic MSA, and suggest that susceptibility to MSA-C may be the greater risk of SNCA variation. These results suggest that α-synuclein can play a primary role in the pathogenesis of MSA.
The NNIPPS study Group
(0.04 MB DOC)
We thank the patients and their families for their commitment and altruism, the DNA and cell bank of IFR 70 for sample preparation, and Dr. Wilhelm Fischer.
The NNIPPS Genetic Study Group is listed in Appendix S1
Conceived and designed the experiments: AAC AD NWW JSH KM YA AB PNL GB. Performed the experiments: AAC MP AC AEMR. Analyzed the data: AAC MP PNL GB. Contributed reagents/materials/analysis tools: AD NWW BL AL AB. Wrote the paper: AAC AD NWW MP JSH KM AB PNL GB. Logistic management: JSH. Quality assurance: JSH. Responsible for repository management: KM. Logistic management of German samples: SS. Coordinator for NNIPPS Germany: AL. Coordinator for NNIPPS UK: PNL. Coordinator for NNIPPS France: GB.
- 1. Bensimon G, Ludolph A, Agid Y, Vidailhet M, Payan C, et al. (2009) Riluzole treatment, survival and diagnostic criteria in Parkinson plus disorders: The NNIPPS Study. Brain 132: 156–171.
- 2. Gilman S, Wenning GK, Low PA, Brooks DJ, Mathias CJ, et al. (2008) Second consensus statement on the diagnosis of multiple system atrophy. Neurology 71: 670–676.
- 3. Lewis P (1964) Familial Orthostatic Hypotension. Brain 87: 719–728.
- 4. Nakazato Y, Yamazaki H, Hirato J, Ishida Y, Yamaguchi H (1990) Oligodendroglial microtubular tangles in olivopontocerebellar atrophy. J Neuropathol Exp Neurol 49: 521–530.
- 5. Costa C, Duyckaerts C, Cervera P, Hauw JJ (1992) [Oligodendroglial inclusions, a marker of multisystemic atrophies]. Rev Neurol (Paris) 148: 274–280.
- 6. Wullner U, Abele M, Schmitz-Huebsch T, Wilhelm K, Benecke R, et al. (2004) Probable multiple system atrophy in a German family. J Neurol Neurosurg Psychiatry 75: 924–925.
- 7. Soma H, Yabe I, Takei A, Fujiki N, Yanagihara T, et al. (2006) Heredity in multiple system atrophy. J Neurol Sci 240: 107–110.
- 8. Hara K, Momose Y, Tokiguchi S, Shimohata M, Terajima K, et al. (2007) Multiplex families with multiple system atrophy. Arch Neurol 64: 545–551.
- 9. Plante-Bordeneuve V, Bandmann O, Wenning G, Quinn NP, Daniel SE, et al. (1995) CYP2D6-debrisoquine hydroxylase gene polymorphism in multiple system atrophy. Mov Disord 10: 277–278.
- 10. Cairns NJ, Atkinson PF, Kovacs T, Lees AJ, Daniel SE, et al. (1997) Apolipoprotein E e4 allele frequency in patients with multiple system atrophy. Neurosci Lett 221: 161–164.
- 11. Ozawa T, Takano H, Onodera O, Kobayashi H, Ikeuchi T, et al. (1999) No mutation in the entire coding region of the alpha-synuclein gene in pathologically confirmed cases of multiple system atrophy. Neurosci Lett 270: 110–112.
- 12. Morris HR, Vaughan JR, Datta SR, Bandopadhyay R, Rohan De Silva HA, et al. (2000) Multiple system atrophy/progressive supranuclear palsy: alpha-Synuclein, synphilin, tau, and APOE. Neurology 55: 1918–1920.
- 13. Nishimura M, Kawakami H, Komure O, Maruyama H, Morino H, et al. (2002) Contribution of the interleukin-1beta gene polymorphism in multiple system atrophy. Mov Disord 17: 808–811.
- 14. Cho S, Kim CH, Cubells JF, Zabetian CP, Hwang DY, et al. (2003) Variations in the dopamine beta-hydroxylase gene are not associated with the autonomic disorders, pure autonomic failure, or multiple system atrophy. Am J Med Genet A 120A: 234–236.
- 15. Combarros O, Infante J, Llorca J, Berciano J (2003) Interleukin-1A (-889) genetic polymorphism increases the risk of multiple system atrophy. Mov Disord 18: 1385–1386.
- 16. Furiya Y, Hirano M, Kurumatani N, Nakamuro T, Matsumura R, et al. (2005) Alpha-1-antichymotrypsin gene polymorphism and susceptibility to multiple system atrophy (MSA). Brain Res Mol Brain Res 138: 178–181.
- 17. Infante J, Llorca J, Berciano J, Combarros O (2005) Interleukin-8, intercellular adhesion molecule-1 and tumour necrosis factor-alpha gene polymorphisms and the risk for multiple system atrophy. J Neurol Sci 228: 11–13.
- 18. Nishimura M, Kuno S, Kaji R, Kawakami H (2005) Brain-derived neurotrophic factor gene polymorphisms in Japanese patients with sporadic Alzheimer's disease, Parkinson's disease, and multiple system atrophy. Mov Disord 20: 1031–1033.
- 19. Ozawa T, Healy DG, Abou-Sleiman PM, Ahmadi KR, Quinn N, et al. (2006) The alpha-synuclein gene in multiple system atrophy. J Neurol Neurosurg Psychiatry 77: 464–467.
- 20. Soma H, Yabe I, Takei A, Fujiki N, Yanagihara T, et al. (2008) Associations between multiple system atrophy and polymorphisms of SLC1A4, SQSTM1, and EIF4EBP1 genes. Mov Disord 23: 1161–1167.
- 21. Scholz SW, Houlden H, Schulte C, Sharma M, Li A, et al. (2009) SNCA variants are associated with increased risk for multiple system atrophy. Ann Neurol 65: 610–614.
- 22. Pals P, Lincoln S, Manning J, Heckman M, Skipper L, et al. (2004) alpha-Synuclein promoter confers susceptibility to Parkinson's disease. Ann Neurol 56: 591–595.
- 23. Mellick GD, Maraganore DM, Silburn PA (2005) Australian data and meta-analysis lend support for alpha-synuclein (NACP-Rep1) as a risk factor for Parkinson's disease. Neurosci Lett 375: 112–116.
- 24. Chiba-Falek O, Touchman JW, Nussbaum RL (2003) Functional analysis of intra-allelic variation at NACP-Rep1 in the alpha-synuclein gene. Hum Genet 113: 426–431.
- 25. Marchini J, Howie B, Myers S, McVean G, Donnelly P (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39: 906–913.
- 26. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81: 559–575.
- 27. Yabe I, Soma H, Takei A, Fujiki N, Yanagihara T, et al. (2006) MSA-C is the predominant clinical phenotype of MSA in Japan: analysis of 142 patients with probable MSA. J Neurol Sci 249: 115–121.