Functional connectivity changes resemble patterns of pTDP-43 pathology in amyotrophic lateral sclerosis

Scientific Reports

Volumn 6, Issue , 2016, Pages

  Schulthess, Ines ^a   Gorges, Martin ^a   Müller, Hans Peter ^a   Lulé, Dorotheé ^a   Del Tredici, Kelly ^a   Ludolph, Albert C ^a   Kassubek, Jan ^a  

^a UNIVERSITY OF ULM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DNA BINDING PROTEIN; TDP-43 PROTEIN, HUMAN;

ADULT; AGED; AMYOTROPHIC LATERAL SCLEROSIS; ATTENTION; BRAIN; BRAIN STEM; CONNECTOME; DIAGNOSTIC IMAGING; FEMALE; HUMAN; MALE; METABOLISM; MIDDLE AGED; MOTONEURON; NERVE TRACT; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PATHOPHYSIOLOGY; PHYSIOLOGY;

ADULT; AGED; AMYOTROPHIC LATERAL SCLEROSIS; ATTENTION; BRAIN; BRAIN STEM; CONNECTOME; DNA-BINDING PROTEINS; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MOTOR NEURONS; NEURAL PATHWAYS;

EID: 85003703925     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep38391     Document Type: Article

References (40)

1. Zhang, D., Raichle, M. E. Disease and the brain's dark energy. Nat. Rev. Neurol. 6, 15-28 (2010).
2. Kiernan, M. C., et al. Amyotrophic lateral sclerosis. Lancet 377, 942-55 (2011).
3. Kassubek, J., et al. Diffusion tensor imaging analysis of sequential spreading of disease in amyotrophic lateral sclerosis confirmspatterns of TDP-43 pathology. Brain 137, 1733-40 (2014).
4. Brettschneider, J., et al. Stages of pTDP-43 pathology in amyotrophic lateral sclerosis. Ann. Neurol. 74, 20-38 (2013).
5. Braak, H., et al. Amyotrophic lateral sclerosis-a model of corticofugal axonal spread. Nat. Rev. Neurol. 9, 708-14 (2013).
6. Bede, P., et al. Multiparametric MRI study of ALS stratified for the C9orf72 genotype. Neurology 81, 361-9 (2013).
7. Foerster, B. R., et al. Diagnostic accuracy of diffusion tensor imaging in amyotrophic lateral sclerosis: a systematic review andindividual patient data meta-analysis. Acad. Radiol. 20, 1099-106 (2013).
8. Müller, H.-P., Unrath, A., Huppertz, H.-J., Ludolph, A. C., Kassubek, J. Neuroanatomical patterns of cerebral white matterinvolvement in different motor neuron diseases as studied by diffusion tensor imaging analysis. Amyotroph. Lateral Scler. 13, 254-64(2012).
9. Filippi, M., et al. Progress towards a neuroimaging biomarker for amyotrophic lateral sclerosis. Lancet Neurol. 14, 786-788 (2015).
10. Heimrath, J., et al. Additional resources and the default mode network: Evidence of increased connectivity and decreased whitematter integrity in amyotrophic lateral sclerosis. Amyotroph. Lateral Scler. Frontotemporal Degener. 15, 537-45 (2014).
11. Douaud, G., Filippini, N., Knight, S., Talbot, K., Turner, M. R. Integration of structural and functional magnetic resonance imagingin amyotrophic lateral sclerosis. Brain 134, 3470-9 (2011).
12. Mohammadi, B., et al. Changes of resting state brain networks in amyotrophic lateral sclerosis. Exp. Neurol. 217, 147-53 (2009).
13. Brettschneider, J., et al. TDP-43 pathology and neuronal loss in amyotrophic lateral sclerosis spinal cord. Acta Neuropathol. 128,423-37 (2014).
14. Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., Buckner, R. L. Functional-anatomic fractionation of the brain's defaultnetwork. Neuron 65, 550-62 (2010).
15. Smith, S. M., et al. Correspondence of the brain's functional architecture during activation and rest. Proc. Natl. Acad. Sci. USA 106,13040-5 (2009).
16. Laird, A. R., et al. Behavioral interpretations of intrinsic connectivity networks. J. Cogn. Neurosci. 23, 4022-37 (2011).
17. Müller, H.-P., et al. A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis. J. Neurol. Neurosurg. Psychiatry 87, 570-9 (2016).
18. Müller, H.-P., et al. Diffusion tensor imaging and tractwise fractional anisotropy statistics: quantitative analysis in white matterpathology. Biomed. Eng. Online 6, 42 (2007).
19. Gorges, M., et al. To rise and to fall: functional connectivity in cognitively normal and cognitively impaired patients with Parkinson'sdisease. Neurobiol. Aging 36, 1727-1735 (2015).
20. Agosta, F., et al. Assessment of white matter tract damage in patients with amyotrophic lateral sclerosis: a diffusion tensor MRimaging tractography study. AJNR. Am. J. Neuroradiol. 31, 1457-61 (2010).
21. Schmidt, R., de Reus, M. A., Scholtens, L. H., van den Berg, L. H., van den Heuvel, M. P. Simulating disease propagation acrosswhite matter connectome reveals anatomical substrate for neuropathology staging in amyotrophic lateral sclerosis. Neuroimage 24,762-9 (2016).
22. Hillary, F. G., et al. Hyperconnectivity is a Fundamental Response to Neurological Disruption. Neuropsychology 29, 59-75 (2014).
23. Turner, M. R., et al. Distinct cerebral lesions in sporadic and 'D90A' SOD1 ALS: studies with [11C]flumazenil PET. Brain 128, 1323-9(2005).
24. Prodoehl, J., Burciu, R. G., Vaillancourt, D. E. Resting state functional magnetic resonance imaging in Parkinson's disease. Curr. Neurol. Neurosci. Rep. 14, 448 (2014).
25. Filippi, M., et al. Assessment of system dysfunction in the brain through MRI-based connectomics. Lancet Neurol. 12, 1189-99(2013).
26. Mevel, K., Chételat, G., Eustache, F., Desgranges, B. The default mode network in healthy aging and Alzheimer's disease. Int. J. Alzheimers. Dis. 2011, 535816 (2011).
27. Leech, R., Sharp, D. J. The role of the posterior cingulate cortex in cognition and disease. Brain 137, 12-32 (2014).
28. van der Hulst, E.-J., Bak, T. H., Abrahams, S. Impaired affective and cognitive theory of mind and behavioural change inamyotrophic lateral sclerosis. J. Neurol. Neurosurg. Psychiatry 86, 1208-15 (2014).
29. Gorges, M., et al. Eye Movement Deficits Are Consistent with a Staging Model of pTDP-43 Pathology in Amyotrophic LateralSclerosis. PLoS One 10, e0142546 (2015).
30. Park, H.-J., Friston, K. Structural and functional brain networks: from connections to cognition. Science 342, 1238411 (2013).
31. Bullmore, E., Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186-98 (2009).
32. Van Essen, D. C. Cartography and connectomes. Neuron 80, 775-90 (2013).
33. Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., Petersen, S. E. Spurious but systematic correlations in functionalconnectivity MRI networks arise from subject motion. Neuroimage 59, 2142-54 (2012).
34. Gorges, M., Müller, H.-P., Ludolph, A. C., Rasche, V., Kassubek, J. Intrinsic functional connectivity networks in healthy elderlysubjects: a multiparametric approach with structural connectivity analysis. Biomed Res. Int. 2014, Article ID 947252 (2014).
35. Menke, R. A. L., et al. Widespread grey matter pathology dominates the longitudinal cerebral MRI and clinical landscape ofamyotrophic lateral sclerosis. Brain 137, 2546-55 (2014).
36. Müller, H.-P., Unrath, A., Ludolph, A. C., Kassubek, J. Preservation of diffusion tensor properties during spatial normalization byuse of tensor imaging and fibre tracking on a normal brain database. Phys. Med. Biol. 52, N99-109 (2007).
37. Bright, M. G., Murphy, K. Is fMRI 'noise' really noise? Resting state nuisance regressors remove variance with network structure. Neuroimage 114, 158-69 (2015).
38. Müller, H.-P., Kassubek, J. Diffusion tensor magnetic resonance imaging in the analysis of neurodegenerative diseases. J. Vis. Exp. 77, (2013).
39. Song, X.-W., et al. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS One 6, e25031(2011).
40. Power, J. D., Schlaggar, B. L., Petersen, S. E. Studying Brain Organization via Spontaneous fMRI Signal. Neuron 84, 681-696 (2014).