MS Biomarkers in Clinical Practice

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MS Biomarkers in Clinical Practice

  1. 1. Biomarkers in clinical practice & novel biomarkers Gavin Giovannoni Barts and The London
  2. 2. Why MS biomarkers? • 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
  3. 3. Diagnostic & pathogenic markers
  4. 4. Q: Who still does diagnostic lumbar punctures?
  5. 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. 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. 7. Will Rogers Phenomenon in Multiple Sclerosis Poser McDonald Sormani et al. Ann Neurol 2008;64:428–433.
  8. 8. Intrathecal synthesis of IgG Carl Lange – Colloidal Gold Curve Kabat et al. J Clin Invest. 1942 Sep;21(5):571-7. Isoelectric focusing with immunfixation Images courtesy of Alastair Compston and Ed Thompson.
  9. 9. Diagnostic criteria for Primary Progressive MS Polman et al. Ann Neurol 2005;58:840-6.
  10. 10. Accumulation of disability in PPMS: stratified by intrathecal IgG abnormalities 1.0 Proportion Progressing P =0.03 Proportion Progressing as Percent 0.8 Epoch 0.0 0 1 15.0 20.4 22.8 28.1 24 mo 25.4 34.3 Years to Progression Negative Positive 0.2 9.8 18 mo CSF 7.3 12 mo 0.4 CSF+ 6 mo 0.6 CSF- 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
  11. 11. Dobson R, et al. J Neurol Neurosurg Psychiatry 2013;0:1–6.
  12. 12. 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.
  13. 13. 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 clinically definite MS revealed a correct diagnosis in 485 cases (94%). • Clinical diagnosis had been established by a neurologist in all cases. • Erroneous diagnosis included a variety of other neurological disorders. • Also investigated was a randomly selected series of 33 patients with a clinical diagnosis of probable MS: – post mortem confirmation of MS was obtained in circa 66%. – The remainder the error pattern was similar to the above. Engell T. Acta Neurol Scand. 1988 Jul;78(1):39-44.
  14. 14. NMO Lennon et al. Lancet 2004;364:2106-12.
  15. 15. PML complicating treatment with natalizumab and IFNb-1a for MS Kleinschmidt-DeMasters,et al. N Engl J Med. 2005 Jul 28;353(4):369-74.
  16. 16. Pathogenic markers
  17. 17. Key pathological processes in MS “Inflammation” Gliosis “Inflammation” Axonal & Neuronal Loss Axonal Toxicity (conduction block) “Oligodendrocyte Toxicity & Demyelination” Remyelination & Axonal Recovery Central Adaptation & Plasticity
  18. 18. 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.
  19. 19. Brain atrophy Slider courtesy of Dr Nic Losseff, Institute of Numerology, Queen Square.
  20. 20. Brain atrophy Control Multiple sclerosis
  21. 21. Spinal fluid neurofilament levels Petzold et al. J Neurol Neurosurg Psychiatry. 2005 Feb;76(2):206-11.
  22. 22. CSF NFL Gunnarsson et al. Ann Neurol 2010; Epub.
  23. 23. Natalizumab treatment of progressive multiple sclerosis reduces inflammation and tissue damage - results of a phase 2A proof-of-concept study J. Romme Christensen1, R. Ratzer1, L. Börnsen1, E. Garde2, M. Lyksborg2, H.R. Siebner2, T.B. Dyrby2, P. Soelberg Sørensen1 and F. Sellebjerg1 ClinicalTrials.gov Identifier: NCT01077466
  24. 24. Natalizumab treatment of progressive MS reduces inflammation and tissue damage: CSF markers of axonal damage Romme Christensen et al. ECTRIMS 2012.
  25. 25. Natalizumab and brain atrophy Mean (SE) percentage change in BPF Years 0-2 Year 0-1* Year 1-2 0.0% -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.
  26. 26. 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 500 321 (-50%) p w -u in el llo as Fo llo Fo 644 B w -u p in e el Ba s Fingolimod 0.5 mg Baseline Follow-up Median (pg/ml) 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
  27. 27. 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
  28. 28. Q: Who routinely measures vD levels?
  29. 29. 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 Unfavourable disease-modifying factors Peripheral immunological changes T-regs (), NK cells, CD8 () 1 2 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 childhood MS 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 1. 2. 3. 4. CIS Adolescence / early adulthood CNS changes (OCBs and microscopic pathology) 3 MRI / evoked potentials changes 2 4a 2 4b 2 4c Clinical disease adulthood 2 4d
  30. 30. d25-OH D3 Median Survival (days) > Median 1267 < Median 973 Cox univariate HR 95% CI Q1 P value 0.74 0.60-0.92 0.008 Q3 0.69 0.55-0.90 0.001 Q4 0.74 0.60-0.92 0.007 0.021 1.00 Q2 Log-rank p Dr Jens Khule, ECTRIMS 2013
  31. 31. Vitamin D as an Early Predictor of Multiple Sclerosis Activity and Progression Ascherio et al. JAMA Neurol. 2014 Jan 20.
  32. 32. EBNA-1 IgG* Median Survival (days) < Median 1247 > Median 1032 Cox univariate HR 95% CI 1.01 0.996-1.029 0.216 P value EBNA-1 nOD Log-rank p 0.137 * similar results in OCB pos and MRI T2 pos patients only Dr Jens Khule, ECTRIMS 2013
  33. 33. Pharmacovigilance markers
  34. 34. Q: Who routinely does a serum protein electrophoresis before starting IFN-beta?
  35. 35. What is the diagnosis?
  36. 36. Take special care with Interferon-beta-1b: If you might have a disorder of the immune system in which abnormal proteins are found in the blood (monoclonal gammopathy), you must check this with your doctor before you use interferon beta-1b. Patients who have the rare condition known as monoclonal gammopathy may develop problems with their small blood vessels (capillaries) leading to shock (collapse) which can be fatal, when they use medicines like interferon-beta-1b. See also 4. Possible side effects.
  37. 37. ?
  38. 38. Natalizumab Progressive multifocal leukoencephalopathy (PML) 439 cases – 4th February 2014 20% mortality 80% alive Mild disability – 10% Moderate disability – 50% Severe disability – 40% 5% NAbs – infusion reactions Kleinschmidt-DeMasters,et al. N Engl J Med. 2005 Jul 28;353(4):369-74.
  39. 39. Natalizumab PML risk stratification tool Anti-JC virus antibody status Negative Positive Prior immunosuppressant use No Yes Natalizumab treatment >2 Years No Yes Mitoxantrone Azathioprine Methotrexate Cyclophosphamide Mycophenolate Cladribine Rituximab Etc. Natalizumab treatment >2 Years No Lowest Yes Highest Relative PML Risk < 1 in 10,000 1 in 1887 1 in 256 1 in 668 1 in 94
  40. 40. Q: When requesting JCV serology who looks at the antibody index or titre?
  41. 41. Anti-JCV antibody index values may differentiate PML risk for those with no prior immunosuppression PML risk estimates (95% CI) per 1000 patients with no prior IS use Index 1−24 months 25−48 months 49−72 months ≤0.9 0.1 0.3 0.4 (0, 0.41) (0.04, 1.13) (0.01, 2.15) 0.1 0.7 0.7 (0, 0.34) (0.21, 1.53) (0.08, 2.34) 0.1 1.0 1.2 (0.01, 0.39) (0.48, 1.98) (0.31, 2.94) 0.1 1.2 1.3 (0.03, 0.42) (0.64, 2.15) (0.41, 2.96) 1.0 8.1 8.5 (0.64, 1.41) (6.64, 9.80) (6.22, 11.38) ≤1.1 ≤1.3 ≤1.5 >1.5 PML risk estimates for anti-JCV antibody index thresholds were calculated based on the current PML risk stratification algorithm (September 2012) and predicted probabilities (using data from patients with no prior IS use: 2242 non-PML patients and 51 patients who developed PML using all available anti-JCV antibody index data at least 6 months prior to PML diagnosis) for the population at or below that particular index (0.9−1.5) and for the population above an index of 1.5. For index thresholds below 0.9, patient numbers were insufficient to allow for calculation of risk estimates. Plavina T et al. Poster DX51, CMSC May 29–June 1 2013, Orlando, USA; Ticho B. et al, Presented at ENS, June 8–11 2013, Barcelona, Spain O228. 50 50
  42. 42. Predicting autoimmunity following treatment of MS with alemtuzumab Sensitivity NPV Specificity 81 84 70 76 76 54 63 65 49 47 IL-21 or IL-7 98 97 41 55 IL-21 OR IL-7 OR CCL21 98 91 12 45 Sensitivity 500 0.8 0.6 0.4 0.2 0.0 0.0 0 54 CCL21 alone 1.0 1000 66 IL-7 alone 1500 0.2 0.4 0.6 0.8 1.0 0.2 0.4 0.6 0.8 1.0 PPV IL-21 alone Receiver operating characteristic (ROC) curves Given that pts may elect to receive treatment based on results of this test – most weight given to minimizing false negative results. Combining IL-21 and IL-7 into a single test offers improved test accuracy over IL-21 alone. CCL21 did not improve test accuracy 40 1.0 30 0.8 Sensitivity • IL-21 and IL-7 levels in sera of pts who did or did not develop autoimmunity IL-21 • 30% of alemtuzumab-treated pts develop autoimmune side-effects (primarily thyroid disease and idiopathic thrombocytopenia) Aim: To define predictive factors for autoimmune side-effects Sera of 141 pts screened at baseline for 8 different cytokines/chemokines IL-7 • 20 10 0 Autoimmunity No autoimmunity 0.6 0.4 0.2 0.0 0.0 1-Specificity A combined IL-21/IL-7 test on pre-treatment serum may be useful to identify patients at low risk of developing autoimmunity following treatment with alemtuzumab Jones JL, et al. ECTRIMS 2011, Amsterdam. P1009
  43. 43. Neurology 2012;78(Suppl.): [S41.006]
  44. 44. Case study: ITP in alemtuzumab treated patient
  45. 45. Anti-natalizumab Antibodies Impact of anti-natalizumab antibodies on . . . . . Progressive disability 0.5 0.9 0.8 0.73 0.7 0.6 0.48* 0.5 0.4 0.3 0.22 0.16 0.2 0.1 Cumulative Proportion of Patients with Sustained Disability Progression (EDSS) Adjusted Annualized Relapse Rate (95% CI) Annualized relapse rate Placebo Antibody Negative Transiently Antibody Positive 0.4 ,† 34%* Persistently Antibody Positive 0.3 29% 0.2 17% 17% 0.1 0.0 Placebo (n=315) Antibody Negative (n=568) Transiently Antibody Positive ( n=20) 0.0 Persistently Antibody Positive (n=37) 0 12 24 36 48 *p=0.009 vs. antibody-negative patients 60 72 84 96 108 208 460 14 16 120 200 449 14 15 Weeks Number of Patients at Risk Placebo Antibody Negative Transiently Positive Persistently Positive 315 568 20 37 296 550 19 32 283 538 18 26 264 526 16 25 248 506 16 24 240 487 16 22 229 480 15 22 216 470 14 19 *p ≤0.05 vs. antibody-negative patients †p=0.66 vs. placebo Calabresi et al, Neurol 2007
  46. 46. Natalizumab infusion reactions • Acute hypersensitivity reactions are well-recognized • Generalized urticaria, dizziness, fever, rash, rigors, pruritus, nausea, flushing, dyspnea, chest pain • Onset generally during or within 1 hour of second infusion • Incidence ~4% • severe anaphylactic/anaphylactoid reactions <1% • Most reactions are associated with anti-natalizumab antibodies • Treatment: • immediate and permanent cessation of natalizumab • antihistamines Rudick et al, NEJM 2006
  47. 47. Monitoring effect of therapeutic interventions
  48. 48. Reduced efficacy due to NAbs – systematic review Farrell & Giovannoni, Multiple Sclerosis 2007; 13: 567-577.
  49. 49. Clinical importance of neutralising antibodies against interferon beta in patients with relapsing-remitting multiple sclerosis Sorensen et al. Lancet 2003; 362: 1184–91.
  50. 50. Jacob Elkins, James Sheridan, Lakshmi Amaravadi, Katherine Riester, Gilmore O’Neill Neurology 2012;78(Suppl.): S31.004
  51. 51. Prognostic markers
  52. 52. Intrathecal synthesis of IgG Carl Lange – Colloidal Gold Curve Kabat et al. J Clin Invest. 1942 Sep;21(5):571-7. Isoelectric focusing with immunfixation Images courtesy of Alastair Compston and Ed Thompson.
  53. 53. Dobson R, et al. J Neurol Neurosurg Psychiatry 2013;0:1–6.
  54. 54. Petzold, J Neurol Sci. 2005 Jun 15;233(1-2):183-98.
  55. 55. Spinal fluid neurofilament levels Petzold et al. J Neurol Neurosurg Psychiatry. 2005 Feb;76(2):206-11.
  56. 56. Conclusion • • Diagnostic/prognostic biomarkers • Intrathecal OCBs • IgG Index Pharmacovigilance • Baseline screening • Monoclonal gammaopathy (IFNbeta) • Serology – VZV, JCV (immunosuppression) • Monitoring • FBC, LFTs, U&E, TFTs • Monthly platelets and possibly urine (alemtuzmab) • Serology – JCV (natalizumab) • CD56-bright cells (daclizumab) • NABs (IFNbeta and natalizumab) • Potential surrogate treatment markers • CSF neurofilament levels • Potential future baseline response markers • Type 1 interferon signature • PBMC transcriptomic profiles
  57. 57. 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 • • • • NABINMS Affirm study Care MS 1 & 2 studies Select trial

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