Advertisement

Journal of Neurology

, Volume 259, Issue 7, pp 1375–1382 | Cite as

Evolution of MS lesions to black holes under DNA vaccine treatment

  • Athina Papadopoulou
  • Stefanie von Felten
  • Stefan Traud
  • Amena Rahman
  • Joanne Quan
  • Robert King
  • Hideki Garren
  • Lawrence Steinman
  • Gary Cutter
  • Ludwig Kappos
  • Ernst Wilhelm Radue
Original Communication

Abstract

Persistent black holes (PBH) are associated with axonal loss and disability progression in multiple sclerosis (MS). The objective of this work was to determine if BHT-3009, a DNA plasmid-encoding myelin basic protein (MBP), reduces the risk of new lesions becoming PBH, compared to placebo, and to test if pre-treatment serum anti-MBP antibody levels impact on the effect of BHT-3009 treatment. In this retrospective, blinded MRI study, we reviewed MRI scans of 155 MS patients from a double-blind, randomized, phase II trial with three treatment arms (placebo, 0.5 and 1.5 mg BHT-3009). New lesions at weeks 8 and 16 were tracked at week 48 and those appearing as T1-hypointense were classified as PBH. A subset of 46 patients with available pre-treatment serum anti-MBP IgM levels were analyzed separately. Overall, there was no impact of treatment on the risk for PBH. However, there was a significant interaction between anti-MBP antibodies and treatment effect: patients receiving 0.5 mg BHT-3009 showed a reduced risk of PBH with higher antibody levels compared to placebo (p < 0.01). Although we found no overall reduction of the risk for PBH in treated patients, there may be an effect of low-dose BHT-3009, depending on the patients’ pre-treatment immune responses.

Keywords

Multiple sclerosis BHT-3009 DNA vaccine Persistent black holes 

Abbreviations

ABH

Acute black holes

CL

Candidate lesions

CSF

Cerebrospinal fluid

EDSS

Expanded Disability Status Scale

Gd

Gadolinium

MBP

Myelin basic protein

MS

Multiple sclerosis

MSSS

MS Severity Score

MTR

Magnetization transfer ratio

NAA

N-Acetyl aspartate

NAGM

Normal appearing grey matter

NAWM

Normal appearing white matter

NUM

Number of human MBP peptide epitopes recognized by serum antibodies

PBH

Persistent black holes

PD-w SE

Proton density-weighted sequence

RRMS

Relapsing remitting multiple Sclerosis

T1-w SE

T1-weighted sequence

Notes

Acknowledgments

The original study was supported by Bayhill Therapeutics. A. Papadopoulou takes full responsibility for the data, the analyses and interpretation, and the conduct of the research, has full access to all of the data, and has the right to publish any and all data separate and apart from any sponsor. We acknowledge the support of Pascal Kuster (MIAC, Basel, Switzerland) and Marcus Weber (Neurology Clinic, Basel, Switzerland) in technical issues as well as the advice and guidance through this study of Danilo Marzetti, Dr. Nicole Müller-Lenke, Dr. Kerstin Bendfeldt (MIAC, Basel, Switzerland) and Thomas Fabbro, PhD (Clinical Trial Unit, University Hospital Basel, Switzerland).

Conflicts of interest

The original study was supported by Bayhill Therapeutics. Athina Papadopoulou, Stefanie von Felten and Stefan Traud have no conflict of interest. Amena Rahman is paid as a consultant from Bayhill Therapeutics. Joanne Quan and Hideki Garren are employees of Bayhill Therapeutics and hold Bayhill stock options. Robert King is employed full-time by Bayhill Therapeutics and receives stock and financial compensation. Lawrence Steinman consults for Bayhill Therapeutics and serves on their Board of Directors. Gary Cutter has received Consulting, Speaking, & Advisory Boards fees from Bayhill Therapeutics. Ludwig Kappos’ institution has received payments for his participation as principal investigator, member or chair of planning and steering committees or advisory boards in corporate-sponsored clinical trials in multiple sclerosis and other neurological diseases. Sponsoring pharmaceutical companies for these trials include Bayhill Therapeutics. Ernst Wilhelm Radue has received research support (mainly for MS projects) from Bayhill Therapeutics.

Supplementary material

415_2011_6361_MOESM1_ESM.jpg (39 kb)
Supplementary Fig. 1. Two examples of patients with ABH at week 8 and outcome at week 48 (isointense or PBH). Left panel: Patient with two enhancing CL at baseline (week 8: first row), one with ring enhancement and one with nodular enhancement, both mildly hypointense on the T1-w pre-contrast sequence (ABH). At end-point MRI (week 48: second row), both ABH have become T1-isointense. Right panel: Patient with a CL at baseline (week 8: first row), with ring Gd-enhancement, appearing as mildly hypointense on the T1-w pre-contrast SE (ABH). At week 48 (second row), the CL remained T1-hypointense (PBH). The MRI sequences in both examples are (from left to right): T1-weighted Sequence pre-contrast, T1-weighted Sequence post-contrast and Proton Density-weighted Sequence. (JPEG 38 kb)

References

  1. 1.
    Barkhof F, Brueck W, De Groot C et al (2003) Remyelinated lesions in multiple sclerosis magnetic resonance image appearance. Arch Neurol 60:1073–1081PubMedCrossRefGoogle Scholar
  2. 2.
    Bitsch A, Kuhlmann T, Stadelmann C, Lassmann H, Lucchinetti C, Bruck W (2001) A longitudinal MRI study of histopathologically defined hypointense multiple sclerosis lesions. Ann Neurol 49:793–796PubMedCrossRefGoogle Scholar
  3. 3.
    Brueck W, Bitsch A, Kolenda H, Brück Y, Stiefel M, Lassmann H (1997) Inflammatory central nervous system demyelination: correlation of magnetic resonance imaging findings with lesion pathology. Ann Neurol 42:783–793CrossRefGoogle Scholar
  4. 4.
    van Walderveen MA, Kamphorst W, Scheltens P et al (1998) Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis. Neurology 50:1282–1288PubMedCrossRefGoogle Scholar
  5. 5.
    Bitsch A, Bruhn H, Vougioukas V et al (1999) Inflammatory CNS demyelination: histopathologic correlation with in vivo quantitative proton MR spectroscopy. Am J Neuroradiol 20:1619–1627PubMedGoogle Scholar
  6. 6.
    Karampekios S, Papanikolaou N, Papadaki E et al (2005) Quantification of magnetization transfer rate and native T1 relaxation time of the brain: correlation with magnetization transfer ratio measurements in patients with multiple sclerosis. Neuroradiology 47:189–196PubMedCrossRefGoogle Scholar
  7. 7.
    Levesque I, Sled JG, Narayanan S et al (2005) The role of edema and demyelination in chronic T1 black holes: a quantitative magnetization transfer study. J Magn Reson Imaging 21:103–110PubMedCrossRefGoogle Scholar
  8. 8.
    Otaduy MC, Callegaro D, Bacheschi LA, Leite CC (2006) Correlation of magnetization transfer and diffusion magnetic resonance imaging in multiple sclerosis. Mult Scler 12:754–759PubMedCrossRefGoogle Scholar
  9. 9.
    Rovira A, Alonso J, Cucurella G et al (1999) Evolution of multiple sclerosis lesions on serial contrast-enhanced T1-weighted and magnetization-transfer MR images. Am J Neuroradiol 20:1939–1945PubMedGoogle Scholar
  10. 10.
    van Waesberghe JH, van Buchem MA, Filippi M et al (1998) MR outcome parameters in multiple sclerosis: comparison of surface-based thresholding segmentation and magnetization transfer ratio histographic analysis in relation to disability (a preliminary note). Am J Neuroradiol 19:1857–1862PubMedGoogle Scholar
  11. 11.
    van Walderveen MA, Barkhof F, Pouwels PJ, van Schijndel RA, Polman CH, Castelijns JA (1999) Neuronal damage in T1-hypointense multiple sclerosis lesions demonstrated in vivo using proton magnetic resonance spectroscopy. Ann Neurol 46:79–87PubMedCrossRefGoogle Scholar
  12. 12.
    Iannucci G, Minicucci L, Rodegher M, Sormani MP, Comi G, Filippi M (1999) Correlations between clinical and MRI involvement in multiple sclerosis: assessment using T(1), T(2) and MT histograms. J Neurol Sci 171:121–129PubMedCrossRefGoogle Scholar
  13. 13.
    Minneboo A, Uitdehaag BM, Jongen P et al (2009) Association between MRI parameters and the MS severity scale: a 12 year follow-up study. Mult Scler 15:632–637PubMedCrossRefGoogle Scholar
  14. 14.
    Nijeholt GJ, van Walderveen MA, Castelijns JA et al (1998) Brain and spinal cord abnormalities in multiple sclerosis. Correlation between MRI parameters, clinical subtypes and symptoms. Brain 121(Pt 4):687–697PubMedCrossRefGoogle Scholar
  15. 15.
    Rovaris M, Comi G, Rocca MA et al (1999) Relevance of hypointense lesions on fast fluid-attenuated inversion recovery MR images as a marker of disease severity in cases of multiple sclerosis. Am J Neuroradiol 20:813–820PubMedGoogle Scholar
  16. 16.
    Sailer M, Losseff NA, Wang L, Gawne-Cain ML, Thompson AJ, Miller DH (2001) T1 lesion load and cerebral atrophy as a marker for clinical progression in patients with multiple sclerosis. A prospective 18 months follow-up study. Eur J Neurol 8:37–42PubMedCrossRefGoogle Scholar
  17. 17.
    Truyen L, van Waesberghe JH, van Walderveen MA et al (1996) Accumulation of hypointense lesions (“black holes”) on T1 spin-echo MRI correlates with disease progression in multiple sclerosis. Neurology 47:1469–1476PubMedCrossRefGoogle Scholar
  18. 18.
    van Walderveen MA, Barkhof F, Hommes OR et al (1995) Correlating MRI and clinical disease activity in multiple sclerosis: relevance of hypointense lesions on short-TR/short-TE (T1-weighted) spin-echo images. Neurology 45:1684–1690PubMedCrossRefGoogle Scholar
  19. 19.
    van Walderveen MA, Truyen L, van Oosten BW et al (1999) Development of hypointense lesions on T1-weighted spin-echo magnetic resonance images in multiple sclerosis: relation to inflammatory activity. Arch Neurol 56:345–351PubMedCrossRefGoogle Scholar
  20. 20.
    van Walderveen MA, Lycklama ANG, Ader HJ et al (2001) Hypointense lesions on T1-weighted spin-echo magnetic resonance imaging: relation to clinical characteristics in subgroups of patients with multiple sclerosis. Arch Neurol 58:76–81PubMedCrossRefGoogle Scholar
  21. 21.
    Zivadinov R, Leist TP (2005) Clinical-magnetic resonance imaging correlations in multiple sclerosis. J Neuroimaging 15:10S–21SPubMedCrossRefGoogle Scholar
  22. 22.
    van Waesberghe JH, van Walderveen MA, Castelijns JA et al (1998) Patterns of lesion development in multiple sclerosis: longitudinal observations with T1-weighted spin-echo and magnetization transfer MR. Am J Neuroradiol 19:675–683PubMedGoogle Scholar
  23. 23.
    Rovira A, Leon A (2008) MR in the diagnosis and monitoring of multiple sclerosis: an overview. Eur J Radiol 67:409–414PubMedCrossRefGoogle Scholar
  24. 24.
    Dalton CM, Miszkiel KA, Barker GJ et al (2004) Effect of natalizumab on conversion of gadolinium enhancing lesions to T1 hypointense lesions in relapsing multiple sclerosis. J Neurol 251:407–413PubMedCrossRefGoogle Scholar
  25. 25.
    Filippi M, Rovaris M, Rocca MA, Sormani MP, Wolinsky JS, Comi G (2001) Glatiramer acetate reduces the proportion of new MS lesions evolving into “black holes”. Neurology 57:731–733PubMedCrossRefGoogle Scholar
  26. 26.
    Barkhof F, Hulst HE, Drulovic J, Uitdehaag BM, Matsuda K, Landin R (2010) MN166-001 Investigators. Ibudilast in relapsing-remitting multiple sclerosis: a neuroprotectant? Neurology 74(13):1033–1040Google Scholar
  27. 27.
    MacManus DG, Miller D, Kappos L, et al (2008) The effect of BG00012 on conversion of gadolinium-enhancing lesions to T1-hypointense lesions. Mult Scler 14:163Google Scholar
  28. 28.
    Garren H, Robinson WH, Krasulova E et al (2008) Phase 2 trial of a DNA vaccine encoding myelin basic protein for multiple sclerosis. Ann Neurol 63:611–620PubMedCrossRefGoogle Scholar
  29. 29.
    Garren H, Robinson WH, Rahman A, King R, Utz PJ, Steinman L (2010) Baseline plasma anti-MBP antibody levels correlate with subject response to BHT-3009, a novel, antigen-specific tolerizing DNA vaccine therapy for MS patients. Mult Scler p417Google Scholar
  30. 30.
    Frohman EM, Racke MK, Raine CS (2006) Multiple sclerosis—the plaque and its pathogenesis. N Engl J Med 354:942–955PubMedCrossRefGoogle Scholar
  31. 31.
    Sospedra M, Martin R (2005) Immunology of multiple sclerosis. Annu Rev Immunol 23:683–747PubMedCrossRefGoogle Scholar
  32. 32.
    Genain CP, Cannella B, Hauser SL, Raine CS (1999) Identification of autoantibodies associated with myelin damage in multiple sclerosis. Nat Med 5:170–175PubMedCrossRefGoogle Scholar
  33. 33.
    Bielekova B, Goodwin B, Richert N et al (2000) Encephalitogenic potential of the myelin basic protein peptide (amino acids 83–99) in multiple sclerosis: results of a phase II clinical trial with an altered peptide ligand. Nat Med 6:1167–1175PubMedCrossRefGoogle Scholar
  34. 34.
    Cadavid D, Cheriyan J, Skurnick J, Lincoln JA, Wolansky LJ, Cook SD (2009) New acute and chronic black holes in patients with multiple sclerosis randomised to interferon beta-1b or glatiramer acetate. J Neurol Neurosurg Psychiatry 80:1337–1343PubMedCrossRefGoogle Scholar
  35. 35.
    Dalton CM, Miszkiel KA, Barker GJ et al (2004) Effect of natalizumab on conversion of gadolinium enhancing lesions to T1 hypointense lesions in relapsing multiple sclerosis. J Neurol 251:407–413PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Athina Papadopoulou
    • 1
  • Stefanie von Felten
    • 2
  • Stefan Traud
    • 3
  • Amena Rahman
    • 4
  • Joanne Quan
    • 4
  • Robert King
    • 4
  • Hideki Garren
    • 4
  • Lawrence Steinman
    • 5
  • Gary Cutter
    • 6
  • Ludwig Kappos
    • 1
  • Ernst Wilhelm Radue
    • 3
  1. 1.Neurology Clinic, Department of NeurologyUniversity Hospital BaselBaselSwitzerland
  2. 2.Clinical Trial UnitUniversity Hospital BaselBaselSwitzerland
  3. 3.Medical Image Analysis Center (MIAC)University Hospital BaselBaselSwitzerland
  4. 4.Bayhill TherapeuticsPalo AltoUSA
  5. 5.Stanford UniversityStanfordUSA
  6. 6.Department of BiostatisticsUniversity of AlabamaBirminghamUSA

Personalised recommendations