Candidate Biomarkers in Multiple System Atrophy
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1 Workshop on Biomarkers in the Early Diagnosis of Neurodegenerative Disorders Assisi, May 21-23, 2015 Candidate Biomarkers in Multiple System Atrophy Kurt A. Jellinger Institute of Clinical Neurobiology, Vienna, Austria
2 Diagnostic categories of MSA Gilman et al Possible MSA One criterion plus 2 clinical features from other domains. When the criterion is parkinsonism, a poor levodopa response qualifies as one feature. 2. Probable MSA Criterion for autonomic failure/urinary dysfunction plus poorly levodopa responsive parkinsonism or cerebellar dysfunction. 3. Definite MSA Pathologically confirmed by presence of high density of glial cytoplasmic inclusions + combined degenerative changes in the nigrostriatal and olivopontocerebellar pathways. MSA-P: predominant parkinsonian features MSA-C: predominant cerebellar features
3 Clinical and neuropathological characteristics of MSA K Ubhi et al, Trends Neurosci 2011;34:581-90
4 Neuropathology underlying MSA-P, MSA-C and autonomic failure in MSA D. Kuzdas et al (2014) Prog Neurobiol 118; 19-35
5 Distribution of Syn lesions (GCIs) in MSA SE Arnold et al, J Comp Neurol 2013; 521
6 Semi-quantitative rt-pcr analysis of neuronal and glial cell markers in the prefrontal cortex of controls (n=8) and MSA (n=10) NEURONS OLIGODENDROCYTES ASTROCYTES L Salvesen et al, Cer Cortex 2015 submitted ACTIVATED MICROGLIA
7 K. Ubhi et al, TINS (2011) Key mechanisms in MSA
8 A putative pathogenic pathway of MSA JH Wong et al, Exp Neurobiol 2014; 23: Sporadic, Environment, Genetic? Myelin protein redistribution Lipid dyshomesostasis ABCA8 upregulation Myelin dysregulation α-synuclein deposition Demyelination Neurodegeneration Loss of neurons Multiple system atrophy
9 Etiopathogenesis of MSA: current concepts Modified from Fanciulli & Wenning, N Engl J Med 2015; 372:
10 Putaminal changes in patients withmsa A. Sugiyama et al (2015) J Neurol Sci 349; 174-8
11 Diagnosis of MSA Revised consensus criteria allow the diagnosis of MSA with 3 levels of certainty. Possible and probable MSA are based on the presence of clinical core features, while a diagnosis of definite MSA requires post-mortem confirmation. Because of overlapping clinical presentations, it can be difficult to distinguish MSA from PD in early disease, and from other atypical parkinsonian disorders, e.g., progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). No reliable biomarker is currently available to guide the clinical diagnosis and prognosis.
12 N. Aoki et al, ANP 2015 Atypical multiple system atrophy is a new subtype of frontotemporal lobar degeneration: frontotemporal lobar degeneration associated with α-synuclein Based on 4 patients with atypical MSA with clinical features consistent with frontotemporal dementia (FTD), 2 with corticobasal syndrome, one each with progressive non-fluent aphasia and with behavioral variant FTD, it is suggested that MSA may present clinically and pathologically as a frontotemporal lobar degeneration (FTLD). This may represent a novel subtype of FTLD associated with α-synuclein (FTLD-synuclein).
13 Comparison of atypical MSA to typical MSA N. Aoki et al, ANP 2015 Atypical MSA (n=4) Typical MSA (n=34) P value Female 4/4 (100 %) 15/34 (44 %) Brain weight (g) 1130 (693, 1208) 1180 (1100, 1325) Age at death (yrs) 81 (71, 90) 66 (62, 71) Age at onset (yrs) 69 (66, 84) 58 (53, 62) Duration 5 (3, 15) 8 (6, 10) Braak NFT stage III (I, V) I (I, II) Thal Aß phase 1.5 (0, 4.5) 2 (0, 2) α-syn-positive NCI Hippocampal dentate fascia Frequency 4/4 (100 %) 18/33 (55 %) Scores 3 (1.5, 3) 1 (0, 1) Hippocampal CA1/subiculum Frequency 4/4 (100 %) 22/33 (67 %) Scores 3 (3, 3) 1 (0, 1) <0.001 Hypothalamus Frequency 4/4 (100 %) 21/32 (66 %) Scores 3 (3, 3) 1 (0, 2) Inferior olivary nucleus Frequency 3/4 (75 %) 32/32 (100 %) Scores 2 (0.25, 3) 2 (1, 3) 0.873
14 Biomarker definition The Biomarker Definitions Working Group describes a biomarker as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacologic response to a therapeutic intervention. An ideal biomarker should be closely linked to pathophysiology, reliable, accurate, sensitive, specific, reproducible, non-invasive and acceptable for the patient, non expensive, and carefully designed in different studies.
15 Classification of biomarkers S. Sharma et al, Neurochem Internat 63 (2013)
16 Fluid biomarkers in multiple system atrophy: a review of the MODIMSA and Global MSA Taskforce Biomarker Initiative (Neurobiol Dis, submitted) Brice Laurens, Radu Constantinescu, Roy Freeman, Alexander Gerhard, Kurt Jellinger, Alexander Jeromin, Florian Krismer, Brit Mollenhauer, Michael Schlossmacher, Les Shaw, Marcel Verbeek, Gregor K Wenning, Kristian Winge, Jing Zhang, Wassilios G Meissner
17 Biomarkers to be discussed α-synuclein Amyloid precursor protein & Aß-42 Ubiquitin-proteasome system DJ-1 Neuroinflammation Oxidative stress Axonal degeneration (p)tau, NF, NSE Myelin basic protein (MBP) Neurotransmitters: DA, NE, hypocratin Insulin / insulin like growth factor Proteomics Micro-RNA (mrna) expression Combination of biomarkers
18 Total Syn levels in CSF Study Mollenhauer et al 2011 Wang et al 2012 Shi et al 2011 Tateno et al 2012 Hall et al 2012 Aerts et al 2012 Herbert et al 2014 Mondello et al 2014 Foulds et al 2012 Magdalinou et al 2015 MSA cases (n) Concentration [ng/ml] 1.24 ( ) 1.11 ( ) 0.33 ± ± 0.12 MSA vs. controls ± ± ( ) ( ) ± ( ) 8 (pm) 3800 ± ( ) MSA vs. PD MSA vs. APD PSP PSP LBD vs. PSP vs. PSP + CBD vs. CBS, PSP
19 Syn concentrations in CSF F. Tateno et al, Alzheimer Dis Assoc Disord 2012;26:213
20 Phosphorylated and oligomeric Syn in CSF Study Analyte MSA cases (n) Concentr. [ng/ml] MSA vs. contr. MSA vs. PD MSA vs. APD Wang et al 2012 PS ± ± PSP PSP Foulds et al 2012 PS ± 9190 Wang PS-129/ ± 0.12 vs. PSP et al 2012 t-αsyn ± 0.08 Foulds et al 2012 Foulds et al 2012 OligoαSyn Oligo- PS pm ± pm ± 1660
21 CSF Syn immunoassay - box-whisker plots P.G. Foulds et al, Neurobiol Dis 45 (2012) µg/ ml Syn µg/ ml Oligomeric Syn µg/ ml Phospho-Syn µg/ ml Oligomeric phospho-syn
22 Decreased cerebrospinal fluid Syn in the PD group Heegaard et al (2014) Future Neurol 9,
23 CSF amyloid precursor protein and derivatives Study Holmberg et al 2003 Analyte MSA vs. controls MSA vs. PD MSA vs. APD vs. PSP Verbeek et al 2004 PSP Mollenhauer et al 2007 Süssmuth et al 2010 PSP MSA vs. AD Shi et al 2011 A-β42 Mollenhauer et al 2011 Jesse et al 2011 Hall et al 2012 PD, PDD vs. DLB Bech et al 2012 Magdalinou et al 2015 vs. PSP, CBS Süssmuth et al 2010 vs. PSP A-β40 Mollenhauer et al 2007 Bech et al 2012 sappα Magdalinou et al 2015 vs. PSP, CBS Bech et al 2012 sappβ Magdalinou et al 2015 vs. PSP, CBS
24 B. Holmberg et al (2003) Mov Disord 18; 186 CSF Aß-42 levels
25 CSF UCH-L1 concentrations in PD, MSA, PSP, CBD S. Mondello et al (2014) Parkinson Related Disord 20; 382
26 Cerebrospinal fluid DJ-1 levels do not correlate with cerebrospinal fluid Syn levels in PD patients and controls Heegaard et al (2014) Future Neurol 9,
27 Neuroinflammation markers in CSF Study Shi et al 2011 Silajdzic et al 2014 Analyte Flt3-ligand MSA vs. controls MSA vs. PD Shi et al 2011 Fractalkine Magdalinou et al 2015 Olsson et al 2013 Holmberg et al 1998 MCP-1 YKL-40 YKL-40 scd14 MSA-P vs. MSA-C Sussmuth et al 2010 Binomial test:? GFAP Abdo et al 2004 Constantinescu et al 2010b Wang et al 2011 C3 FH C3/FH Brodacki et al 2008 Interferon ɣ Brodacki et al 2008 Interleukin 2 Interleukin 4 Interleukin 10
28 Neuroinflammation markers in plasma Study Kaufman et al 2013 Brodacki et al 2008 Kaufman et al 2013 Brodacki et al 2008 Kaufman et al 2013 Analyte Plasmatic TNF-α Plasmatic IL-6 MSA vs. controls MSA vs. PD MSA-P vs. MSA-C Plasmatic CRP Plasmatic IL-2R
29 CSF total tau Study MSA cases (n) Assay MSA vs. controls MSA vs. PD MSA-P vs. MSA-C MSA vs. APD MSA vs. AD Abdo et al (probable: 26) ELISA Mollenhauer et al 07 MSA-P: 12; MSA-C: 6 ELISA Sussmuth et al 10 MSA-P: 11; MSA-C: 14 ELISA PSP Abdo et al 07a 19 ELISA Shi et al BBMA Abdo et al 07b MSA-P: 19; MSA-C: 26 ELISA Mollenhauer et al 11 MSA-P 21; MSA-C 8 ELISA MSA + PD < DLB 15 Jesse et al 11 MSA-P 12; MSA-C 13 ELISA Hall et al BBMA vs. PD, PDD Bech et al ELISA Herbert et al ELISA? Magdalinou et al ELISA
30 CSF phosphorylated tau Study Shi et al 2011 MSA cases (n) MSA vs. Controls MSA vs. PD MSA-P vs. MSA-C MSA vs. APD 32 MSA vs. AD Süssmuth et al 2010 MSA-P: 11 MSA-C: 14 PSP Hall et al 2012 Bech et al 2012 Herbert et al 2014 Magdalinou et al vs. PD and PDD vs. DLB PSP 10 PSP PSP
31 R. Yamasaki et al. Ann Neurol 2014; 76 (Suppl 18): 50 Distinct value of CSF cytokines in patients with MSA and spinocerebellar degenerations 27 cytokine/chemokine profiles in 20 MSA-C patients and 24 SCD were measured by multiplexed fluorescent bead-based immunoassay. Among 27 cytokines, MIP-1β, IFN-γ and IL-1Ra were increased in MSA-C compared to SCD. IL-1β and IL-1Ra levels were significantly increased in sporadic SCD CSF than in hereditary SCD. Negative correlation between CSF MCP-1 levels and disease durations in MSA-C. Brain MRI also revealed positive correlation between the size of pontine bases and CSF MCP-1 levels in MSA-C. These data suggested the involvement of inflammatory mechanisms at the early stage of MSA-C. Antiinflamatory therapy may be useful.
32 Expression of cytokines Mahlknecht et al, Proteome Science 2012, 10:71
33 Neurofilament in CSF Study Analyte MSA cases (n) MSA vs contr. MSA vs PD MSA vs APD Holmberg et al 1998 Holmberg et al 2001 MSA-P: 5 MSA-C: 5 MSA-P: 29 MSA-C: 7 Abdo et al 2007a 19 Abdo et al 2007b MSA-P: 19 MSA-C: 26 Petzold et al 2009 NFL Baseline: 42 Constantinescu et al 2010b MSA-P: 14 MSA-C: 7 Bech et al PSP, DLB Hall et al vs. DLB Magdalinou et al Hebert et al Brettschneider et al 2006 MSA-P: 11 MSA-C: 10 Abdo et al 2007a 19 NFH MSA-P: 19 Abdo et al 2007b MSA-C: 26 vs. PSP vs. CBS PSP Petzold et al 2009 Baseline: 42 No comparison No comparison No comparison
34 CSF NFL levels in controls and in parkinsonian disorders Constantinescu et al, Parkinson Related Disord 16 (2010)
35 Specific mir-96 dysregulation in MSA cases and MBP1-hasyn tg mice K. Ubhi et al, Eur J Neurosci 39 (2014) 1026
36 DOPAC (A) and DHPG (B) in CSF D.S. Goldstein et al, Brain 2012: 135; 1900
37 Study Neurotransmitters and metabolites Goldstein et al 2012 Analyte in CSF MSA vs. Controls MSA vs. PD Dopamine L-DOPA DOPA DOPAC Goldstein et al 2008 Dopamine/DOPAC Goldstein et al 2012 Abdo et al 2004 Norepinephrine DHPG MSA-P vs. MSA-C HVA MHPG Abdo et al 2007 MHPG
38 Comparison of individual values for CSF DHPG and DOPAC in PD, MSA, PAF, and controls PD MSA PAF Controls D.S. Goldstein et al, Brain 2012: 135; 1900
39 Serum IGF-1 levels in PD, MSA, PSP and controls * p < 0.05 A. Numao et al, Parkinson Relat Disord 20 (2014) 212
40 Serum IGF-I levels Serum IGF-II levels M.T. Pellecchia et al, Mov Disord 15 (2010) 2621
41 Box-whisker plot of DE cmirnas in PD patients vs. MSA patients A. Vallelunga et al, Front Cell Neurosci 8 (2014) 156
42 Syn and tau in CSF Mollenhauer et al, Lancet Neurol 2011; 10:
43 CSF DJ-1 (A) and t-tau (B) levels in PD, MSA, and controls M.K. Herbert et al (2014) Parkinson Related Disord 20; 112
44 Scatterplots of the concentrations of HVA, 5-HIAA, MHPG, MBP, and tau in CSF in MSA-C, MSA-P, and PD W.F. Abdo et al (2003) Mov Disord 19; 571
45 Study Analyte MSA vs. Contr. MSA vs. PD MSA vs. PSP Se Sp AUC Se Sp AUC Se Sp AUC Shi et al 2011 t-syn 94% 70% % 25% 0.72 Wang et al 2012 (discovery cohort) Wang et al 2012 (validation cohort) Hall et al 2012 Herbert et al 2014 Magdalinou et al 2015 t-syn + p-tau/t-tau 90% 65% 0.85 t-syn 75% 86% % 88% % 87% PS % 88% % 86% % 80% t-syn + PS % 82% % 88% % 83% t-syn + PS % 62% % 94% % 82% t-syn + NFL + t-tau + p-tau + Ab-42 DJ-1 + t-tau + p-tau t-syn + DJ-1 + t-tau + p-tau t-syn + t-tau + p-tau + Ab-42 + NFL + YKL-40 + MCP-1 + sapp + sappβ + age 85% 92% % 81% BIOMARKER PANELS Se: sensitivity; Sp: specificity; AUC: area under curve
46 Biomarkers for differentiation of MSA (with sensitivity/specificity) Biomarkers MSA from PD MSA from PSP MSA from AD MSA from contr. MSA-P vs MSA-C CSF tau protein (95%/77%) Syn and p-tau % (90%/71%) DJ-1 and p-tau % (90%/70%) CSF NfH [SMI35] CSF NF-L CSF NfH [p35] CSF Syn Oligo ps Syn CSF Aß-42 / / CSF Flt3 ligand (99%/95%) (95%/90%) CSF C3/FH (80%/87%) (90%/95%) (85%/81%) CSF cystatin C CSF HVA / CSF MHPG (>80% / >80%) CSF MBP CSF 5-HIAA / / CSF DOPAC Serum IGF-I CSF-AI AGHT (92%/96%)* (78%/96%) CGHT (80%/75%)*
47 Diagnostic accuracy of CSF biomarkers in Parkinson S. Hall et al, Arch Neurol 2012;69:1445
48 Candidate biomarkers of MSA vs. PD and controls F. Zhang et al, Rev Neurosci. 2014;25(5):653
49 Biomarkers in plasma Study Analyte MSA (n) Lee et al 2006 Mollenhauer et al 2011 Sun et al 2013 Vallelunga et al 2014 Numao et al 2014 Pellecchia et al 2010 Concentr. [ng/ml] MSA vs. controls MSA vs. PD αsyn ± αsyn 15 αsyn MSA-P: 32 MSA-C: (4.4 ± 19.0) 11.1 (7.1 ± 21.2) mrna 25 IGF-I GH IGF-I IGF-II ± ± ± ± 353.3
50 Summary To differentiate MSA from PD and atypical parkinsonian disorders can be challenging. The clinical diagnosis of MSA relies on current consensus criteria, while no validated biomarker are available. A Pubmed search by the Global MSA Task Force Biomarker Initiative included 60 studies assessing fluid biomarkers in MSA patients. Previous work focused on αsyn, markers of axonal degeneration and catecholamines gave inconsistent results. More recent studies suggest that combining biomarkers may be more successful in the differential diagnosis between MSA and other parkinsonian disorders. Despite growing research efforts, no reliable biomarker currently exists for the diagnosis and prognosis of MSA. Levels of NFP and GFAP did not change over time. Such biomarkers are urgently needed to improve diagnostic accuracy and also to serve as surrogates for future clinical trials. Beyond efforts in biomarker discovery, the harmonization of standard operating procedures will be crucial for future success.
51 B. Laurens W.G. Meissner R. Constantinescu R. Freeman Thanks to co-workers Service de Neurologie, CHU de Bordeaux, France Dept. of Neurology, Sahlgrenska Univ. Hospital, Göteborg, Sweden Dept. of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston A. Gerhard Inst. of Brain Behaviour & Mental Heath, Univ. of Manchester, UK A. Jeromin Quanterix, Inc., Lexington, MA, USA F. Krismer G.K. Wenning Dept. of Neurology, Medical Univ. of Innsbruck, Austria B. Mollenhauer Paracelsus-Elena-Klinik, Kassel, Germany M.G. Schlossmacher L.M. Shaw M.M. Verbeek K. Winge Univ. of Ottawa Brain and Mind Research Inst., Ottawa, Ontario, Canada Perelman School of Medicine, Univ. of Pennsylvania, USA Dept. of Neurology RUMC Nijmegen, the Netherlands Dept. of Neurology, Bispebjerg Univ. Hospital, Copenhagen, Denmark J. Zhang Dept. of Pathology, Univ. of Washington, Seattle, USA
52 Workshop on Biomarkers in the Early Diagnosis of Neurodegenerative Disorders Assisi, May 21-23, 2015 Thank you very much for your attention! Kurt A. Jellinger Institute of Clinical Neurobiology, Vienna, Austria
53 N. Magdalinou et al. Cerebrospinal fluid biomarkers in parkinsonian conditions: an update and future directions JNNP 2014; 85: 1065 Parkinsonian diseases comprise a heterogeneous group of neurodegenerative disorders, which show significant clinical and pathological overlap. Accurate diagnosis still largely relies on clinical acumen; pathological diagnosis remains the gold standard. There is an urgent need for biomarkers to diagnose parkinsonian disorders, particularly in the early stages when diagnosis is most difficult. Several of the most promising CSF candidate markers will be discussed. Their strengths, limitations, and future developments in the field will be considered.
54 Diagnostic approach to a patient presenting with MSA Stamelou et al (2013) Mov Disord 28: 1184
55 Amyloidrelated biomarkers in CSF S. Bech et al, Parkinsonism Relat Disord 18 (2012) 69-72
56 Evaluation of C3/FH as a biomarker of MSA MSA vs. control MSA vs. AD MSA vs. PD Y. Wang et al, Am J Pathol 2011, 178:1509
57 Comparison of individual values for CSF DOPAC (A) and DHPG (B) as a function of CSF L-DOPA in PD, MSA, PAF, and controls PD MSA PAF Controls D.S. Goldstein et al, Brain 2012: 135; 1900
58 Mean spectral features at m/z 6250 from CSF Ishigami et al, Mov Disord 2012, 27:851
59 ROC analysis of CSF tau, NFL and NFHp35 levels in IPD vs. MSA-P W.F. Abdo et al, Neurobiol Aging 28 (2007)
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