Innate immune cells and myelin profile in multiple sclerosis: a multi-tracer PET/MR study

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art_PITOMBEIRA_Innate_immune_cells_and_myelin_profile_in_multiple_2022.PDF (1.37 MB)
Citações na Scopus
4
Tipo de produção
article
Data de publicação
2022
DOI
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
SPRINGER
Autores
KOOLE, Michel
Citação
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, v.49, n.13, p.4551-4566, 2022
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Purpose Neuropathological studies have demonstrated distinct profiles of microglia activation and myelin injury among different multiple sclerosis (MS) phenotypes and disability stages. PET imaging using specific tracers may uncover the in vivo molecular pathology and broaden the understanding of the disease heterogeneity. Methods We used the 18-kDa translocator protein (TSPO) tracer (R)[C-11]PK11195 and [C-11]PIB PET images acquired in a hybrid PET/MR 3 T system to characterize, respectively, the profile of innate immune cells and myelin content in 47 patients with MS compared to 18 healthy controls (HC). For the volume of interest (VOI)-based analysis of the dynamic data, (R)[C-11]PK11195 distribution volume (VT) was determined for each subject using a metabolite-corrected arterial plasma input function while [C-11]PIB distribution volume ratio (DVR) was estimated using a reference region extracted by a supervised clustering algorithm. A voxel-based analysis was also performed using Statistical Parametric Mapping. Functional disability was evaluated by the Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Symbol Digit Modality Test (SDMT). Results In the VOI-based analysis, [C-11]PIB DVR differed between patients and HC in the corpus callosum (P = 0.019) while no differences in (R)-[C-11]PK11195 V-T were observed in patients relative to HC. Furthermore, no correlations or associations were observed between both tracers within the VOI analyzed. In the voxel-based analysis, high (R)-[C-11]PK11195 uptake was observed diffusively in the white matter (WM) when comparing the progressive phenotype and HC, and lower [C-11]PIB uptake was observed in certain WM regions when comparing the relapsing-remitting phenotype and HC. None of the tracers were able to differentiate phenotypes at voxel or VOI level in our cohort. Linear regression models adjusted for age, sex, and phenotype demonstrated that higher EDSS was associated with an increased (R)-[C-11]PK11195 V-T and lower [C-11]PIB DVR in corpus callosum (P = 0.001; P = 0.023), caudate (P = 0.015; P = 0.008), and total T-2 lesion (P = 0.007; P = 0.012), while better cognitive scores in SDMT were associated with higher [C-11]PIB DVR in the corpus callosum (P = 0.001), and lower (R)-[C-11]PK11195 V-T (P = 0.013). Conclusions Widespread innate immune cells profile and marked loss of myelin in T-2 lesions and regions close to the ventricles may occur independently and are associated with disability, in both WM and GM structures.
Palavras-chave
PET imaging, TSPO, Myelin, Multiple sclerosis, Disability
URI
https://observatorio.fm.usp.br/handle/OPI/50483
Referências
  1. Abel S, 2020, JAMA NETW OPEN, V3, DOI 10.1001/jamanetworkopen.2020.14220
  2. Ashburner J, 2007, NEUROIMAGE, V38, P95, DOI 10.1016/j.neuroimage.2007.07.007
  3. Berg K, 2014, AM J MED QUAL, V29, P242, DOI 10.1177/1062860613492189
  4. Bodini B, 2020, J NUCL MED, V61, P1043, DOI 10.2967/jnumed.119.231340
  5. Bodini B, 2016, ANN NEUROL, V79, P726, DOI 10.1002/ana.24620
  6. Bogie JFJ, 2014, ACTA NEUROPATHOL, V128, P191, DOI 10.1007/s00401-014-1310-2
  7. Brousse B, 2015, BIOL OPEN, V4, P980, DOI 10.1242/bio.012773
  8. Brown JWL, 2017, BRAIN, V140, P387, DOI 10.1093/brain/aww296
  9. Campanholo KR, 2022, MULT SCLER RELAT DIS, V57, DOI 10.1016/j.msard.2021.103331
  10. Carvalho RHF, 2019, MULT SCLER RELAT DIS, V35, P108, DOI 10.1016/j.msard.2019.07.020
  11. Cree BAC, 2019, ANN NEUROL, V85, P653, DOI 10.1002/ana.25463
  12. Cutter GR, 1999, BRAIN, V122, P871, DOI 10.1093/brain/122.5.871
  13. De Biase LM, 2017, NEURON, V95, P341, DOI 10.1016/j.neuron.2017.06.020
  14. de Souza AM, 2021, NEURAL REGEN RES, V16, P2494, DOI 10.4103/1673-5374.313062
  15. Elkjaer ML, 2019, ACTA NEUROPATHOL COM, V7, DOI 10.1186/s40478-019-0855-7
  16. Faria DD, 2019, BRAZ J PSYCHIAT, V41, P101, DOI 10.1590/1516-4446-2017-0002
  17. Faria DD, 2014, MULT SCLER J, V20, P1443, DOI 10.1177/1352458514526941
  18. Faria DD, 2014, J NUCL MED, V55, P1330, DOI 10.2967/jnumed.114.137216
  19. Fischer JS, 1999, MULT SCLER J, V5, P244, DOI 10.1177/135245859900500409
  20. Frischer JM, 2015, ANN NEUROL, V78, P710, DOI 10.1002/ana.24497
  21. Frischer JM, 2009, BRAIN, V132, P1175, DOI 10.1093/brain/awp070
  22. Giannetti P, 2015, BRAIN, V138, P110, DOI 10.1093/brain/awu331
  23. Gruchot J, 2019, CELLS-BASEL, V8, DOI 10.3390/cells8080825
  24. Guerrero BL, 2020, FRONT IMMUNOL, V11, DOI 10.3389/fimmu.2020.00374
  25. Hagemeyer N, 2017, ACTA NEUROPATHOL, V134, P441, DOI 10.1007/s00401-017-1747-1
  26. Haider L, 2014, J NEUROL NEUROSUR PS, V85, P1386, DOI 10.1136/jnnp-2014-307712
  27. Herranz E, 2016, ANN NEUROL, V80, P776, DOI 10.1002/ana.24791
  28. Hess K, 2020, ACTA NEUROPATHOL, V140, P359, DOI 10.1007/s00401-020-02189-9
  29. Ikoma Y, 2013, J CEREBR BLOOD F MET, V33, P1725, DOI 10.1038/jcbfm.2013.133
  30. Jackle K, 2020, BRAIN, V143, P2073, DOI 10.1093/brain/awaa158
  31. Kaunzner UW, 2019, BRAIN, V142, P133, DOI 10.1093/brain/awy296
  32. Kuhlmann T, 2017, ACTA NEUROPATHOL, V133, P13, DOI 10.1007/s00401-016-1653-y
  33. KURTZKE JF, 1983, NEUROLOGY, V33, P1444, DOI 10.1212/WNL.33.11.1444
  34. Kutzelnigg A, 2005, BRAIN, V128, P2705, DOI 10.1093/brain/awh641
  35. Lassmann H, 2007, BRAIN PATHOL, V17, P210, DOI 10.1111/j.1750-3639.2007.00064.x
  36. Li Y, 2008, EUR J NUCL MED MOL I, V35, P2169, DOI 10.1007/s00259-008-0833-y
  37. Lloyd AF, 2019, NAT REV NEUROL, V15, P447, DOI 10.1038/s41582-019-0184-2
  38. Lloyd AF, 2019, NAT NEUROSCI, V22, P1046, DOI [10.1038/s41593-019-0418-Z, 10.1038/s41593-019-0418-z]
  39. LOGAN J, 1990, J CEREBR BLOOD F MET, V10, P740, DOI 10.1038/jcbfm.1990.127
  40. Lubetzki C, 2020, LANCET NEUROL, V19, P678, DOI 10.1016/S1474-4422(20)30140-X
  41. Lublin FD, 2014, EUR NEUROL, V72, P1, DOI 10.1159/000367614
  42. Matthews PM, 2019, NAT REV NEUROL, V15, P582, DOI 10.1038/s41582-019-0240-y
  43. Nutma E, 2021, GLIA, V69, P2447, DOI 10.1002/glia.24052
  44. Nutma E, 2019, BRAIN, V142, P3440, DOI 10.1093/brain/awz287
  45. O'Muircheartaigh J, 2019, HUM BRAIN MAPP, V40, P2104, DOI 10.1002/hbm.24510
  46. Ontaneda D, 2021, BRAIN, V144, P1974, DOI 10.1093/brain/awab132
  47. Pareto D, 2016, NEURORADIOLOGY, V58, P467, DOI 10.1007/s00234-016-1654-5
  48. Plastini MJ, 2020, FRONT CELL NEUROSCI, V14, DOI 10.3389/fncel.2020.00269
  49. Poirion E, 2021, NEUROLOGY, V96, pE1865, DOI 10.1212/WNL.0000000000011700
  50. Politis M, 2012, NEUROLOGY, V79, P523, DOI 10.1212/WNL.0b013e3182635645
  51. Polman Chris H, 2011, Ann Neurol, V69, P292, DOI 10.1002/ana.22366
  52. Reich DS, 2018, NEW ENGL J MED, V378, P169, DOI 10.1056/NEJMra1401483
  53. Rissanen E, 2018, NEUROL-NEUROIMMUNOL, V5, DOI 10.1212/NXI.0000000000000443
  54. Rissanen E, 2014, J NUCL MED, V55, P939, DOI 10.2967/jnumed.113.131698
  55. Rizzo G, 2019, J CEREBR BLOOD F MET, V39, DOI 10.1177/0271678X17742004
  56. Schmidt P, 2012, NEUROIMAGE, V59, P3774, DOI 10.1016/j.neuroimage.2011.11.032
  57. Schocke MFH, 2003, NEUROIMAGE, V20, P1253, DOI 10.1016/S1053-8119(03)00409-9
  58. Sekine T, 2016, J NUCL MED, V57, P1258, DOI 10.2967/jnumed.115.169045
  59. Sepulcre J, 2006, MULT SCLER J, V12, P187, DOI 10.1191/1352458506ms1258oa
  60. Smith A., 1982, SYMBOL DIGIT MODALIT
  61. Stankoff B, 2018, BRAIN PATHOL, V28, P723, DOI 10.1111/bpa.12641
  62. Stankoff B, 2011, ANN NEUROL, V69, P673, DOI 10.1002/ana.22320
  63. Sucksdorff M, 2020, BRAIN, V143, P3318, DOI 10.1093/brain/awaa275
  64. Thomas BA, 2011, EUR J NUCL MED MOL I, V38, P1104, DOI 10.1007/s00259-011-1745-9
  65. Thompson AJ, 2018, LANCET NEUROL, V17, P162, DOI 10.1016/S1474-4422(17)30470-2
  66. Tilbery CP, 2005, ARQ NEURO-PSIQUIAT, V63, P127, DOI 10.1590/S0004-282X2005000100023
  67. Tommasin S, 2019, NEUROSCIENCE, V403, P4, DOI 10.1016/j.neuroscience.2017.07.055
  68. Turkheimer FE, 2015, BIOCHEM SOC T, V43, P586, DOI 10.1042/BST20150058
  69. Veronese M, 2015, J CEREBR BLOOD F MET, V35, P1771, DOI 10.1038/jcbfm.2015.120
  70. Xing YL, 2014, J NEUROSCI, V34, P14128, DOI 10.1523/JNEUROSCI.3491-13.2014
  71. Yamasaki R, 2014, J EXP MED, V211, P1533, DOI 10.1084/jem.20132477
  72. Zeydan B, 2019, ANN CLIN TRANSL NEUR, V6, P678, DOI 10.1002/acn3.741
  73. Zrzavy T, 2017, BRAIN, V140, P1900, DOI 10.1093/brain/awx113

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Artigos e Materiais de Revistas Científicas - FM/MDR
Artigos e Materiais de Revistas Científicas - HC/ICESP
Artigos e Materiais de Revistas Científicas - HC/ICHC
Artigos e Materiais de Revistas Científicas - HC/InRad
Artigos e Materiais de Revistas Científicas - LIM/21
Artigos e Materiais de Revistas Científicas - LIM/43
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