European charcot foundation laboratory measures - Giovannoni
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  • 1. MS variability and prognostic implications Laboratory Gavin Giovannoni Barts and The London School of Medicine and Dentistry
  • 2. Disclosures Professor Giovannoni has received personal compensation for participating on Advisory Boards in relation to clinical trial design, trial steering committees and data and safety monitoring committees from: Abbvie, Bayer-Schering Healthcare, Biogen-Idec, Canbex, Eisai, Elan, Fiveprime, Genzyme, Genentech, GSK, GW Pharma, Ironwood, Merck-Serono, Novartis, Pfizer, Roche, Sanofi-Aventis, Synthon BV, Teva, UCB Pharma and Vertex Pharmaceuticals.
  • 3. Why the laboratory? • Diagnostic testing – Positive & negative predictive testing • Pathogenesis – Immunology – Aetiology – Disease progression & recovery – Disease heterogeneity • Pharmacovigilance • Monitor disease processes – Prognosis (high vs. low risk patients) – Monitoring effect of therapeutic interventions
  • 4. Diagnostic & pathogenic markers
  • 5. The evolving clinical definition of MS 1. Schumacher, et al. Problems of Experimental Trials of Therapy in Multiple Sclerosis: Report by the Panel on the Evaluation of Experimental Trials of Therapy in Multiple Sclerosis. Ann N Y Acad Sci 1965;122:552-68. 2. Poser, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13:227-31. 3. McDonald, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 2001;50:121-7. 4. Polman, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald Criteria". Ann Neurol 2005;58:840-6. 5. Polman, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69:292-302.
  • 6. Will Rogers Phenomenon in Multiple Sclerosis 1879 - 1935 “When the Okies left Oklahoma and moved to California, they raised the average intelligence level in both states.”
  • 7. Will Rogers Phenomenon in Multiple Sclerosis Poser McDonald Sormani et al. Ann Neurol 2008;64:428–433.
  • 8. MS diagnosed according the old Poser Criteria Inactive CIS Inactive CIS Active CIS RRMS Less active RRMS More Active RRMS MS diagnosed according the New McDonald Criteria
  • 9. Intrathecal synthesis of IgG Carl Lange – Colloidal Gold Curve Isoelectric focusing with immunfixation Kabat et al. J Clin Invest. 1942 Sep;21(5):571-7. Images courtesy of Alastair Compston and Ed Thompson.
  • 10. Diagnostic criteria for Primary Progressive MS Polman et al. Ann Neurol 2005;58:840-6.
  • 11. Accumulation of disability in PPMS: stratified by intrathecal IgG abnormalities Proportion Progressing 1.0 Proportion Progressing as Percent P =0.03 Epoch 0.2 0.0 0 1 9.8 15.0 20.4 22.8 28.1 24 mo CSF Negative Positive 7.3 18 mo 0.4 CSF+ 6 mo 0.6 CSF- 12 mo 0.8 25.4 34.3 Years to Progression 2.43 2 2.26 3 Years Based on data from a second meeting of the DSMB and assume no therapeutic effect Slide courtesy of Jerry Wolinsky
  • 12. PPMS diagnosed according the original McDonald/Thompson criteria Not MS Not MS OCB+ PPMS Not MS OCB-ve OCB-ve PPMS OCB+ PPMS PPMS diagnosed according the New Polman-McDonald Criteria
  • 13. Dobson R, et al. J Neurol Neurosurg Psychiatry 2013;0:1–6.
  • 14. What constitutes a useful diagnostic test or set of criteria? TARGET DISORDER PRESENT + a b a+b - c d c+d a+c DIAGNOSTIC TEST RESULT ABSENT b+d a+b+c+d From these we determine the sensitivity and specificity as follows: SENSITIVITY = a/(a+c) > 80% SPECIFICITY = d/(b+d) > 80% Neurobiol Aging 1998; 19:109-116.
  • 15. Multiple sclerosis definition Pathological Definition: Inflammatory disease of the CNS characterised by demyelination and variable degrees of axonal loss and gliosis. Clinical Definition: Objective CNS dysfunction, i.e. involvement of two or more white matter structures (space) separated by time, with no other aetiology.
  • 16. A clinico-pathoanatomical study of multiple sclerosis diagnosis SENSITIVITY = True+ve /(True+ve + False-ve) • • Eye Department, Hvidovre Hospital, Denmark Neuropathological examination of 518 consecutive patients with CDMS Clinical or ante-mortem CDMS n=518 Pathological or post-mortem MS n=485 (94%) Not MS n=33(6%) MS, n=33 (66%) Clinically probable MS, n=33 Not MS, n=11(33%) Engell T. Acta Neurol Scand. 1988 Jul;78(1):39-44.
  • 17. A clinico-pathoanatomical study of multiple sclerosis diagnosis. SPECIFICITY = True-ve /(True-ve + False+ve)? Danish post-mortem series of silent MS: • Hvidovre, 5 cases out of 2,600 PMs • Aarhus, 4 cases out of 6,500 • Bispebjerg 3 cases out of 7,000 Frequency of MS diagnosed at PM = 0.08% Estimated 40 cases per year die with silent MS 25% of cases of MS were undiagnosed in life (asymptomatic or benign cases) Routine post-mortems n =16,100 Silent MS n=12 (0.08%) ~ 25% MS undiagnosed in life Engell T. Acta Neurol Scand. 1989 May;79(5):428-30..
  • 18. Key pathological processes in MS “Inflammation” Gliosis “Inflammation” Axonal Toxicity (conduction block) Axonal & Neuronal Loss “Oligodendrocyte Toxicity & Demyelination” Remyelination & Axonal Recovery Central Adaptation & Plasticity
  • 19. Prognostic markers
  • 20. Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology Magliozzi et al. Brain 2007; 130:1089-1104.
  • 21. Intrathecal synthesis of IgG Carl Lange – Colloidal Gold Curve Isoelectric focusing with immunfixation Kabat et al. J Clin Invest. 1942 Sep;21(5):571-7. Images courtesy of Alastair Compston and Ed Thompson.
  • 22. CSF oligoclonal band patterns reveal disease heterogeneity in MS Villar et al. Journal of Neuroimmunology 211 (2009) 101–104
  • 23. Petzold, J Neurol Sci. 2005 Jun 15;233(1-2):183-98.
  • 24. Spinal fluid neurofilament levels Petzold et al. J Neurol Neurosurg Psychiatry. 2005 Feb;76(2):206-11.
  • 25. Natalizumab treatment of progressive MS reduces inflammation and tissue damage: CSF markers of axonal damage Romme Christensen et al. ECTRIMS 2012.
  • 26. Natalizumab and brain atrophy Mean (SE) percentage change in BPF 0.0% Years 0-2 Year 0-1* Year 1-2 -0.2% -0.24% -0.4% -0.40% -0.43% P=0.004 -0.6% -0.56% P=0.002 -0.8% -0.80% -0.82% -1.0% P=0.822 Placebo (N=315) Natalizumab (N=627) Miller DH et al. Neurology 2007;68:1390-1401.
  • 27. Cerebrospinal fluid NfL Fingolimod 0.5mg/1.25 mg versus placebo treated patients Fingolimod, n=23 10000 Placebo, n=12 2500 p<0.001 p=0.470 NfL (pg/ml) NfL (pg/ml) 2000 2000 1000 1500 1000 500 Median (pg/ml) 644 321 (-50%) p w -u in el llo as Fo B Fo llo w -u p in e se l Ba Fingolimod 0.5 mg Baseline Follow-up e 0 0 Fingolimod 1.25 mg Baseline Follow-up 886 *Non-parametric Wilcoxon matched pairs test; p value is calculated with inclusion of outliers 738 (-17%) Dr Jens Khule, ECTRIMS 2013
  • 28. Fingolimod has an early and sustained effect on the rate of brain atrophy compared with placebo and IFNb-1a IM TRANSFORMS, 1 year FREEDOMS, 2 years Time (months) -0.2 -0.4 12 *** −40% vs IFNb-1a IM p<0.001 -0.6 -0.8 -1.0 Change in mean BV from baseline (%) Change in mean BV from baseline (%) 0 0.0 Time (months) 0 6 12 0 24 ** -0.4 -0.8 -1.2 * *** −38% vs placebo p<0.001 -1.6 -2.0 Fingolimod 0.5 mg (n = 368) IFNb-1a IM (n = 359) Fingolimod 0.5 mg (n = 356) Placebo (n = 329) ITT population with evaluable MRI images. Note: n numbers for FREEDOMS data reflect the number of patients with available data at 24 months. *p<0.05; **p<0.01; ***p<0.001 vs comparator; p-values are for comparisons over Months 0-6, Months 0-12, Months 0-24 BV, brain volume; ITT, intent-to-treat. Gilenya™ Prescribing Information 19 April 2012. Reproduced with permission. Kappos L et al. N Engl J Med 2010; 362: 387-401, and Cohen JA et al. N Engl J Med 2010; 362: 402-415. Copyright © 2011 Massachusetts Medical Society. All rights reserved
  • 29. Cerebrospinal fluid chitinase 3-like 1 levels are associated with conversion to multiple sclerosis Comabella et al. Brain 2010: 133; 1082–1093.
  • 30. The MS ‘Endophenotype’ static protective factors dynamic protective factors Favourable disease-modifying factors protective HLA haplotypes Low risk Very low risk At risk High Risk static risk factors RIS dynamic risk factors CIS Unfavourable disease-modifying factors age place of residence outdoor activity / sun exposure / sun screen diet / vitamin D supplements age of exposure to EBV smoking family history genetics sex month of birth place of birth Peripheral immunological changes T-regs (), NK cells, CD8 () 1 2 1. 2. 3. 4. Declining Physiology – “peripheral immunological endophenotype” Biological disease threshold – “CNS endophenotype” Asymptomatic disease – RIS (abnormal MRI and/or evoked potentials) Clinical disease a. Clinically isolated syndrome (CIS) b. Relapsing MS c. Relapsing secondary progressive MS d. Non-relapsing secondary progressive MS In utero MS childhood Adolescence / early adulthood CNS changes (OCBs and microscopic pathology) 3 MRI / evoked potentials changes 4a 2 4b 2 4c 2 Clinical disease adulthood 4d 2
  • 31. ECTRIMS 2012
  • 32. d25-OH Cox univariate HR Q1 Q2 P value 0.74 0.60-0.92 0.008 Q3 0.69 0.55-0.90 Median Survival (days) 1.00 Q4 95% CI D3 0.001 0.74 0.60-0.92 0.007 > Median 1267 < Median 973 Log-rank p 0.021 Dr Jens Khule, ECTRIMS 2013
  • 33. EBNA-1 IgG* Cox univariate HR 95% CI EBNA-1 nOD 1.01 0.996-1.029 0.137 Median Survival (days) P value * similar results in OCB pos and MRI T2 pos patients only < Median 1247 > Median 1032 Log-rank p 0.216 Dr Jens Khule, ECTRIMS 2013
  • 34. Conclusion • Diagnostic/prognostic biomarkers • Intrathecal OCBs (IgG, ? IgM & ? anti-lipid OCBs) • IgG Index • vD levels • ? Chitinase • ? EBV serology • Potential surrogate treatment markers • ? CSF neurofilament levels • ? GFAP • ? MBP
  • 35. Acknowledgements • • • • • Giovannoni – Sharmilee Gnanapavan David Baker – Gareth Pryce – Sarah Al-Izki Sam Jackson – Katie Lidster Yuti Chernajovsky – Alex Annenkov – Anne Rigby – Michelle Sclanders Larry Steinman – Peggy Ho • • • • Charles ffrench-Constant – Robin Franklin Siddharthan Chandran – David Hampton Ian Duncan – Sam Jackson Peter Calabresi – Avi Nath • • • • • Raj Kapoor John Zajicek Doug Brown UK MS Clinical Trial Network BioMS • Co-investigators – NABINMS – Affirm study – Care MS 1 & 2 studies – Select trial