Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-26T15:36:32.361Z Has data issue: false hasContentIssue false

Neurodegeneration of brain networks in the amyotrophic lateral sclerosis–frontotemporal lobar degeneration (ALS–FTLD) continuum: evidence from MRI and MEG studies

Published online by Cambridge University Press:  27 October 2017

Francesca Trojsi*
Affiliation:
Department of Medical, Surgical, Neurological, Metabolic, and Aging Sciences, MRI Research Center SUN–FISM, University of Campania “Luigi Vanvitelli,” Naples, Italy
Pierpaolo Sorrentino
Affiliation:
Department of Engineering, University of Naples Parthenope, Naples, Italy
Giuseppe Sorrentino
Affiliation:
Department of Motor Sciences and Wellness, University of Naples Parthenope, Institute Hermitage–Capodimonte, Naples, Italy
Gioacchino Tedeschi
Affiliation:
Department of Medical, Surgical, Neurological, Metabolic, and Aging Sciences, MRI Research Center SUN–FISM, University of Campania “Luigi Vanvitelli,” Naples, Italy
*
*Address for correspondence: Francesca Trojsi, Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, MRI Research Center SUN–FISM, University of Campania “Luigi Vanvitelli,” Piazza Miraglia 2, 80138 Naples, Italy. (Email: [email protected])

Abstract

Brain imaging techniques, especially those based on magnetic resonance imaging (MRI) and magnetoencephalography (MEG), have been increasingly applied to study multiple large-scale distributed brain networks in healthy people and neurological patients. With regard to neurodegenerative disorders, amyotrophic lateral sclerosis (ALS), clinically characterized by the predominant loss of motor neurons and progressive weakness of voluntary muscles, and frontotemporal lobar degeneration (FTLD), the second most common early-onset dementia, have been proven to share several clinical, neuropathological, genetic, and neuroimaging features. Specifically, overlapping or mildly diverging brain structural and functional connectivity patterns, mostly evaluated by advanced MRI techniques—such as diffusion tensor and resting-state functional MRI (DT–MRI, RS–fMRI)—have been described comparing several ALS and FTLD populations. Moreover, though only pioneering, promising clues on connectivity patterns in the ALS–FTLD continuum may derive from MEG investigations. We will herein overview the current state of knowledge concerning the most advanced neuroimaging findings associated with clinical and genetic patterns of neurodegeneration across the ALS–FTLD continuum, underlying the possibility that network-based approaches may be useful to develop novel biomarkers of disease for adequately designing and monitoring more appropriate treatment strategies.

Type
Review
Copyright
© Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

These authors have contributed equally.

References

1. Burrell, JR, Halliday, GM, Kril, JJ, et al. The frontotemporal dementia–motor neuron disease continuum. Lancet. 2016; 388(10047): 919931.Google Scholar
2. Bennion Callister, J, Pickering-Brown, SM. Pathogenesis/genetics of frontotemporal dementia and how it relates to ALS. Exp Neurol. 2014; 262(Pt B): 8490.Google Scholar
3. Ling, SC, Polymenidou, M, Cleveland, DV. Converging mechanisms in ALS and FTD: disrupted RNA and protein homeostasis. Neuron. 2013; 79(3): 416438.Google Scholar
4. De Jesus-Hernandez, M, Mackenzie, IR, Boeve, BF, et al. Expanded GGGGCC hexanucleotide repeat in noncoding region of C9ORF72 causes chromosome 9p-linked FTD and ALS. Neuron. 2011; 72(2): 245256.Google Scholar
5. Renton, AE, Majounie, E, Waite, A, et al. A hexanucleotide repeat expansion in C9ORF72 is the cause of chromosome 9p21-linked ALS–FTD. Neuron. 2011; 72(2): 257268.Google Scholar
6. Deng, HX, Chen, W, Hong, ST, et al. Mutations in UBQLN2 cause dominant X-linked juvenile and adult-onset ALS and ALS/dementia. Nature. 2011; 477(7363): 211215.Google Scholar
7. Cirulli, ET, Lasseigne, BN, Petrovski, S, et al. Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways. Science. 2015; 347(6229): 14361441.Google Scholar
8. Smith, BN, Ticozzi, N, Fallini, C, et al. Exome-wide rare variant analysis identifies TUBA4A mutations associated with familial ALS. Neuron. 2014; 84(2): 324331.Google Scholar
9. Benajiba, L, Le Ber, I, Camuzat, A, et al. TARDBP mutations in motoneuron disease with frontotemporal lobar degeneration. Ann Neurol. 2009; 65(4): 470473.Google Scholar
10. Blair, IP, Williams, KL, Warraich, ST, et al. FUS mutations in amyotrophic lateral sclerosis: clinical, pathological, neurophysiological and genetic analysis. J Neurol Neurosurg Psychiatry. 2010; 81(6): 639645.Google Scholar
11. Johnson, JO, Pioro, EP, Boehringer, A, et al. Mutations in the Matrin 3 gene cause familial amyotrophic lateral sclerosis. Nat Neurosci. 2014; 17(5): 664666.Google Scholar
12. Brenner, D, Müller, K, Wieland, T, et al. NEK1 mutations in familial amyotrophic lateral sclerosis. Brain. 2016; 139(Pt 5): e28.Google Scholar
13. Arai, T, Hasegawa, M, Akiyama, H, et al. TDP-43 is a component of ubiquitin-positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Biochem Biophys Res Commun. 2006; 351(3): 602611.Google Scholar
14. Neumann, M, Sampathu, DM, Kwong, LK, et al. Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science. 2006; 314(5796): 130133.Google Scholar
15. Van Hoecke, A, Schoonaert, L, Lemmens, R, et al. EPHA4 is a disease modifier of amyotrophic lateral sclerosis in animal models and in humans. Nat Med. 2012; 18(9): 14181422.Google Scholar
16. Xie, T, Deng, L, Mei, P, et al. Genome-wide association study combining pathway analysis for typical sporadic amyotrophic lateral sclerosis in Chinese Han populations. Neurobiol Aging. 2014; 35(7): 1778.e9--1778.e23.Google Scholar
17. Van Battum, EY, Brignani, S, Pasterkamp, RJ. Axon guidance proteins in neurological disorders. Lancet Neurol. 2015; 14(5): 532546.Google Scholar
18. Phukan, J, Pender, NP, Hardiman, O. Cognitive impairment in amyotrophic lateral sclerosis. Lancet Neurol. 2007; 6(11): 9941003.Google Scholar
19. Ringholz, GM, Appel, SH, Bradshaw, M, Cooke, NA, Mosnik, DM, Schulz, PE. Prevalence and patterns of cognitive impairment in sporadic ALS. Neurology. 2005; 65(4): 586590.Google Scholar
20. Abrahams, S, Goldstein, LH, Suckling, J, et al. Frontotemporal white matter changes in amyotrophic lateral sclerosis. J Neurol. 2005; 252(3): 321331.Google Scholar
21. Agosta, F, Pagani, E, Rocca, MA, et al. Voxel-based morphometry study of brain volumetry and diffusivity in amyotrophic lateral sclerosis patients with mild disability. Hum Brain Mapp. 2007; 28(12): 14301438.Google Scholar
22. Agosta, F, Pagani, E, Petrolini, M, et al. Assessment of white matter tract damage in patients with amyotrophic lateral sclerosis: a diffusion tensor MR imaging tractography study. AJNR Am J Neuroradiol. 2010; 31(8): 14571461.Google Scholar
23. Agosta, F, Canu, E, Valsasina, P, et al. Divergent brain network connectivity in amyotrophic lateral sclerosis. Neurobiol Aging. 2013; 34(2): 419427.Google Scholar
24. Mohammadi, B, Kollewe, K, Samii, A, Krampfl, K, Dengler, R, Münte, TF. Changes of resting state brain networks in amyotrophic lateral sclerosis. Exp Neurol. 2009; 217(1): 147153.Google Scholar
25. Filippini, N, Douaud, G, Mackay, CE, Knight, S, Talbot, K, Turner, MR. Corpus callosum involvement is a consistent feature of amyotrophic lateral sclerosis. Neurology. 2010; 75(18): 16451652.Google Scholar
26. Teismann, IK, Warnecke, T, Suntrup, S, et al. Cortical processing of swallowing in ALS patients with progressive dysphagia: a magnetoencephalographic study. PLoS One. 2011; 6(5): E19987.Google Scholar
27. Douaud, G, Filippini, N, Knight, S, Talbot, K, Turner, MR. Integration of structural and functional magnetic resonance imaging in amyotrophic lateral sclerosis. Brain. 2011; 134(Pt 12): 34703479.Google Scholar
28. Tedeschi, G, Trojsi, F, Tessitore, A, et al. Interaction between aging and neurodegeneration in amyotrophic lateral sclerosis. Neurobiol Aging. 2012; 33(5): 886898.Google Scholar
29. Lillo, P, Mioshi, E, Burrell, JR, Kiernan, MC, Hodges, JR, Hornberger, M. Grey and white matter changes across the amyotrophic lateral sclerosis–frontotemporal dementia continuum. PLoS One. 2012; 7(8): e43993.Google Scholar
30. Trojsi, F, Esposito, F, de Stefano, M, et al. Functional overlap and divergence between ALS and bvFTD. Neurobiol Aging. 2015; 36(1): 413423.Google Scholar
31. Proudfoot, M, Rohenkohl, G, Quinn, A, et al. Altered cortical beta-band oscillations reflect motor system degeneration in amyotrophic lateral sclerosis. Hum Brain Mapp. 2017; 38(1): 237254.Google Scholar
32. Whitwell, JL, Josephs, KA, Avula, R, et al. Altered functional connectivity in asymptomatic MAPT subjects: a comparison to bvFTD. Neurology. 2011; 77(9): 866874.Google Scholar
33. Zhou, J, Greicius, MD, Gennatas, ED, et al. Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease. Brain. 2010; 133(Pt 5): 13521367.Google Scholar
34. Whitwell, JL, Avula, R, Senjem, ML, et al. Gray and white matter water diffusion in the syndromic variants of frontotemporal dementia. Neurology. 2010; 74(16): 12791287.Google Scholar
35. Farb, NAS, Grady, CL, Strother, S, et al. Abnormal network connectivity in frontotemporal dementia: evidence for prefrontal isolation. Cortex. 2013; 49(7): 18561873.Google Scholar
36. Filippi, M, Agosta, F, Scola, E, et al. Functional network connectivity in the behavioral variant of frontotemporal dementia. Cortex. 2013; 49(9): 23892401.Google Scholar
37. Lee, SE, Khazenzon, AM, Trujillo, AJ, et al. Altered network connectivity in frontotemporal dementia with C9orf72 hexanucleotide repeat expansion. Brain. 2014; 137(11): 30473060.Google Scholar
38. Kasper, E, Schuster, C, Machts, J, et al. Microstructural white matter changes underlying cognitive and behavioural impairment in ALS: an in vivo study using DTI. PLoS One. 2014; 9(12): e114543.Google Scholar
39. Agosta, F, Ferraro, PM, Riva, N, et al. Structural brain correlates of cognitive and behavioral impairment in MND. Hum Brain Mapp. 2016; 37(4): 16141626.Google Scholar
40. Christidi, F, Karavasilis, E, Riederer, F, et al. Gray matter and white matter changes in non-demented amyotrophic lateral sclerosis patients with or without cognitive impairment: a combined voxel-based morphometry and tract-based spatial statistics whole-brain analysis. Brain Imaging Behav. 2017. doi: 10.1007/s11682-017-9722-y.Google Scholar
41. Van den Heuvel, MP, Stam, CJ, Kahn, RS, Hulshoff Pol, HE. Efficiency of functional brain networks and intellectual performance. J Neurosci. 2009; 29(23): 76197624.Google Scholar
42. Strong, MJ, Abrahams, S, Goldstein, LH, et al. Amyotrophic lateral sclerosis–frontotemporal spectrum disorder (ALS–FTSD): revised diagnostic criteria. Amyotroph Lateral Scler Frontotemporal Degener. 2017; 18(3–4): 153174.Google Scholar
43. Feiler, MS, Strobel, B, Freischmidt, A, et al. TDP-43 is intercellularly transmitted across axon terminals. J Cell Biol. 2015; 211(4): 897911.Google Scholar
44. Friston, KJ, Worsley, KJ, Frackowiak, RS, Mazziotta, JC, Evans, AC. Assessing the significance of focal activations using their spatial extent. Hum Brain Mapp. 1994; 1(3): 210220.Google Scholar
45. Bullmore, E, Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci. 2009; 10(3): 186198.Google Scholar
46. Thivard, L, Pradat, PF, Lehéricy, S, et al. Diffusion tensor imaging and voxel based morphometry study in amyotrophic lateral sclerosis: relationships with motor disability. J Neurol Neurosurg Psychiatry. 2007; 78(8): 889892.Google Scholar
47. Sach, M, Winkler, G, Glauche, V, et al. Diffusion tensor MRI of early upper motor neuron involvement in amyotrophic lateral sclerosis. Brain. 2004; 127(Pt 2): 340350.Google Scholar
48. Sage, CA, Van Hecke, W, Peeters, R, et al. Quantitative diffusion tensor imaging in amyotrophic lateral sclerosis: revisited. Hum Brain Mapp. 2009; 30(11): 36573675.Google Scholar
49. Cirillo, M, Esposito, F, Tedeschi, G, et al. Widespread microstructural white matter involvement in amyotrophic lateral sclerosis: a whole brain DTI study. AJNR Am J Neuroradiol. 2012; 33(6): 11021108.Google Scholar
50. Müller, HP, Turner, MR, Grosskreutz, J, et al. A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2016; 87(6): 570579.Google Scholar
51. Ayers, JI, Fromholt, SE, O’Neal, VM, et al. Prion-like propagation of mutant SOD1 misfolding and motor neuron disease spread along neuroanatomical pathways. Acta Neuropathol. 2016; 131(1): 103114.Google Scholar
52. Brettschneider, J, Del Tredici, K, Toledo, JB, et al. Stages of pTDP-43 pathology in amyotrophic lateral sclerosis. Ann Neurol. 2014; 74(1): 2038.Google Scholar
53. Schmidt, R, de Reus, MA, Scholtens, LH, van den Berg, LH, van den Heuvel, MP. Simulating disease propagation across white matter connectome reveals anatomical substrate for neuropathology staging in amyotrophic lateral sclerosis. NeuroImage. 2016; 124(Pt A): 762769.Google Scholar
54. Verstraete, E, Veldink, JH, Mandl, RCW, van den Berg, LH, van den Heuvel, MP. Impaired structural motor connectome in amyotrophic lateral sclerosis. PLoS One. 2011; 6: e24239.Google Scholar
55. Buchanan, CR, Pettit, LD, Storkey, AJ, Abrahams, S, Bastin, ME. Reduced structural connectivity within a prefrontal–motor–subcortical network in amyotrophic lateral sclerosis. J Magn Reson Imaging. 2015; 41(5): 13421352.Google Scholar
56. Verstraete, E, Veldink, JH, van den Berg, LH, van den Heuvel, MP. Structural brain network imaging shows expanding disconnection of the motor system in amyotrophic lateral sclerosis. Hum Brain Mapp. 2014; 35(4): 13511361.Google Scholar
57. Seeley, WW, Menon, V, Schatzberg, AF, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007; 27(9): 23492356.Google Scholar
58. Mahoney, CJ, Simpson, IJ, Nicholas, JM, et al. Longitudinal diffusion tensor imaging in frontotemporal dementia. Ann Neurol. 2015; 77(1): 3346.Google Scholar
59. Mahoney, CJ, Beck, J, Rohrer, JD, et al. Frontotemporal dementia with the C9ORF72 hexanucleotide repeat expansion: clinical, neuroanatomical and neuropathological features. Brain. 2012; 135(Pt 3): 736750.Google Scholar
60. Galantucci, S, Tartaglia, MC, Wilson, SM, et al. White matter damage in primary progressive aphasias: a diffusion tensor tractography study. Brain. 2011; 134(Pt 10): 30113029.Google Scholar
61. Grossman, M, Powers, J, Ash, S, et al. Disruption of large-scale neural networks in non-fluent/agrammatic variant primary progressive aphasia associated with frontotemporal degeneration pathology. Brain Lang. 2013; 127(2): 106120.Google Scholar
62. McMillan, CT, Irwin, DJ, Avants, BB, et al. White matter imaging helps dissociate tau from TDP-43 in frontotemporal lobar degeneration. J Neurol Neurosurg Psychiatry. 2013; 84(9): 949955.Google Scholar
63. Mantini, D, Perrucci, MG, Del Gratta, C, Romani, GL, Corbetta, M. Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci U S A. 2007; 104(32): 1317013175.Google Scholar
64. Hall, EL, Robson, SE, Morris, PG, Brookes, MJ. The relationship between MEG and fMRI. NeuroImage. 2014; 102(1): 8091.Google Scholar
65. Hämäläinen, MS. Magnetoencephalography: a tool for functional brain imaging. Brain Topogr. 1992; 5(2): 95102.Google Scholar
66. Kew, JJ, Goldstein, LG, Leigh, PN, et al. The relationship between abnormalities of cognitive function and cerebral activation in amyotrophic lateral sclerosis: a neuropsychological and positron emission study. Brain. 1993; 116(Pt 6): 13991423.Google Scholar
67. Abrahams, S, Leigh, PN, Kew, JJ, Goldstein, LH, Lloyd, CM, Brooks, DJ. A positron emission tomography study of frontal lobe function (verbal fluency) in amyotrophic lateral sclerosis. J Neurol Sci. 1995; 129(Suppl): 4446.Google Scholar
68. Vercelletto, M, Belliard, S, Wiertlewski, S, et al. Neuropsychological and scintigraphic aspects of frontotemporal dementia preceding amyotrophic lateral sclerosis. Rev Neurol (Paris). 2003; 159(5 Pt 1): 529542.Google Scholar
69. Jacova, C, Hsiung, GYR, Tawankanjanachot, I, et al. Anterior brain glucose hypometabolism predates dementia in progranulin mutation carriers. Neurology. 2013; 81(15): 13221331.Google Scholar
70. Lant, SB, Robinson, AC, Thompson, JC, et al. Patterns of microglial cell activation in frontotemporal lobar degeneration. Neuropathol Appl Neurobiol. 2013; 40(6): 686696.Google Scholar
71. Cistaro, A, Pagani, M, Montuschi, A, et al. The metabolic signature of C9ORF72-related ALS: FDG PET comparison with nonmutated patients. Eur J Nucl Med Mol Imaging. 2014; 41(5): 844852.Google Scholar
72. Agosta, F, Canu, E, Inuggi, A, et al. Resting state functional connectivity alterations in primary lateral sclerosis. Neurobiol Aging. 2014; 35(4): 916925.Google Scholar
73. Rytty, R, Nikkinen, J, Paavola, L, et al. Group ICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia. Front Hum Neurosci. 2013; 7: 461.Google Scholar
74. Do-Ha, D, Buskila, Y, Ooi, L. Impairments in motor neurons, interneurons and astrocytes contribute to hyperexcitability in ALS: underlying mechanisms and paths to therapy. Mol Neurobiol. 2017. doi: 10.1007/s12035-017-0392-y.Google Scholar
75. Teismann, IK, Warnecke, T, Suntrup, S, et al. Cortical processing of swallowing in ALS patients with progressive dysphagia: a magnetoencephalographic study. PLoS One. 2011; 6(5): e19987.Google Scholar
76. Fraschini, M, Demuru, M, Hillebrand, A, et al. EEG functional network topology is associated with disability in patients with amyotrophic lateral sclerosis. Sci Rep. 2016; 6: 38653.Google Scholar
77. Agosta, F, Sala, S, Valsasina, P, et al. Brain network connectivity assessed using graph theory in frontotemporal dementia. Neurology. 2013; 81(2): 134143.Google Scholar
78. Agosta, F, Galantucci, S, Valsasina, P, et al. Disrupted brain connectome in semantic variant of primary progressive aphasia. Neurobiol Aging. 2014; 35(11): 26462655.Google Scholar
79. Schmidt, R, Verstraete, E, de Reus, MA, Veldink, JH, van den Berg, LH, van den Heuvel, MP. Correlation between structural and functional connectivity impairment in amyotrophic lateral sclerosis. Hum Brain Mapp. 2014; 35(9): 43864395.Google Scholar