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Neuroradiology

, Volume 60, Issue 12, pp 1335–1341 | Cite as

White matter involvement in young non-demented Down’s syndrome subjects: a tract-based spatial statistic analysis

  • Andrea Romano
  • Marta Moraschi
  • Riccardo Cornia
  • Alessandro Bozzao
  • Maria Camilla Rossi-Espagnet
  • Federico Giove
  • Giorgio Albertini
  • Alberto Pierallini
Functional Neuroradiology

Abstract

Purpose

Cognitive decline in Down syndrome generally shows neurodegenerative aspects similar to what is observed in Alzheimer’s disease. Few studies reported information on white matter integrity. The aim of this study was to evaluate white matter alterations in a cohort of young Down subjects, without dementia, by means of DTI technique, compared to a normal control group.

Methods

The study group consisted of 17 right-handed subjects with DS and many control subjects. All individuals participating in this study were examined by MR exam including DTI acquisition (32 non-coplanar directions); image processing and analysis were performed using FMRIB Software Library (FSL version 4.1.9, http://www.fmrib.ox.ac.uk/fsl)) software package. Finally, the diffusion tensor was estimated voxel by voxel and the FA map derived from the tensor. A two-sample t test was performed to assess differences between DS and control subjects.

Results

The FA is decreased in DS subjects, compared to control subjects, in the region of the anterior thalamic radiation, the inferior fronto-occipital fasciculum, the inferior longitudinal fasciculum, and the cortico-spinal tract, bilaterally.

Conclusions

The early white matter damage visible in our DS subjects could have great impact in the therapeutic management, in particular in better adapting the timing of therapies to counteract the toxic effect of the deposition of amyloid that leads to oxidative stress.

Keywords

Down syndrome Young White matter TBSS Dementia 

Notes

Compliance with ethical standards

Funding

No funding was received for this study.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    Teipel SJ, Alexander GE, Shapiro MB, Moller HS, Rapoport SI, Hampel H (2004) Age-related cortical grey matter reductions in non-demented Down’s syndrome adults determined by MRI voxel-based morphometry. Brain 127:811–824CrossRefGoogle Scholar
  2. 2.
    Koran MEI, Hohman TJ, Edwards CM, Vega JN, Pryweller JR, Slosky LE et al (2014) Differences in age-related effects on brain volume in Down syndrome as compared to Williams syndrome and typical development. J Neurodev Disord 6:8CrossRefGoogle Scholar
  3. 3.
    Head E, Silverman W, Patterson D, Lott IT (2012) Aging and Down syndrome. Curr Gerontol Geriatr Res 2010:1–6CrossRefGoogle Scholar
  4. 4.
    Cole JH, Annus T, Wilson LR, Remtulla R, Hong YT, Fryer TD et al (2017) Brain-predicted age in Down syndrome is associated with beta amyloid deposition and cognitive decline. Neurobiol Aging 56:41–49CrossRefGoogle Scholar
  5. 5.
    Folin M, Baiquera S, Conconi MT, Pati T, Grandi C, Parnigotto PP et al (2003) The impact of risk factors of Alzheimer’s disease in the Down syndrome. Int J Mol Med 11:267–270PubMedGoogle Scholar
  6. 6.
    Neale NPC, Fonseca LM, Holland T, Zaman S (2017) Neuroimaging and other modalities to assess Alzheimer’s disease in Down syndrome. Neuroimage Clin 17:263–271CrossRefGoogle Scholar
  7. 7.
    Krasuski JS, Alexander GE, Horwitz B, Rapoport SI, Schapiro MB (2002) Relation of medial temporal lobe volumes to age and memory function in nondemented adults with Down’ syndrome: implications for the prodromal phase of Alzheimer’s disease. Am J Psychiatry 159:74–81CrossRefGoogle Scholar
  8. 8.
    White NS, Alkire MT, Haier RJ (2003) A voxel-based morphometric study of non demented adults with Down syndrome. Neuroimage 20:393–303CrossRefGoogle Scholar
  9. 9.
    Beacher F, Daly E, Simmons A, Prasher V, Morris R, Robinson C et al (2010) Brain anatomy and ageing in non-demented adults with Down’s syndrome: an in vivo MRI study. Psychol Med 40:611–619CrossRefGoogle Scholar
  10. 10.
    Cenini G, Dowling ALS, Beckett TL, Barone E, Mancuso C, Murphy MP et al (2012) Association between frontal cortex oxidative damage and beta-amyloid as a function of age in Down syndrome. Biochim Biophys Acta 1822:130–138CrossRefGoogle Scholar
  11. 11.
    Romano A, Moraschi M, Cornia R, Bozzao A, Gagliardo O, Chiacchiararelli L et al (2015) Age effects on cortical thickness in young Down’s syndrome subjects: a cross-sectional gender study. Neuroradiology 57:401–411CrossRefGoogle Scholar
  12. 12.
    Romano A, Cornia R, Moraschi M, Bozzao A, Chiacchiararelli L, Coppola V et al (2016) Age-related cortical thickness reduction in non-demented Down’s syndrome subjects. J Neuroimaging 26:95–102CrossRefGoogle Scholar
  13. 13.
    Teipel SJ, Hampel H (2006) Neuroanatomy of Down syndrome in vivo: a model of preclinical Alzheimer’s disease. Behav Genet 36:405–415CrossRefGoogle Scholar
  14. 14.
    Fenoll R, Pujol J, Esteba-Castillo S, De Sola S, Ribas-Vidal N, Garcia-Alba J, et al (2017) Anomalous white matter structure and the effect of age in down syndrome patients. Alzheimer Dis 57, 61–70CrossRefGoogle Scholar
  15. 15.
    Sundgren PC, Dong Q, Gomez-Hassan D, Mukherji SK, Maly P, Welsh R (2004) Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology 46:339–350CrossRefGoogle Scholar
  16. 16.
    Madden DJ, Bennett IJ, Burzynska A, Potter GG, Chen NK, Song AW (2012) Diffusion tensor imaging of cerebral white matter integrity in cognitive aging. Biochim Biophys Acta 1822:386–400CrossRefGoogle Scholar
  17. 17.
    Madden DJ, Bennett IJ, Song AW (2009) Cerebral white matter integrity and cognitive aging: contributions from diffusion tensor imaging. Neuropsychol Rev 19:415–435CrossRefGoogle Scholar
  18. 18.
    Bilello M, Doshi J, Nabavizadeh SA, Toledo JB, Erus G, Xie SX et al (2015) Correlating cognitive decline with white matter lesion and brain atrophy magnetic resonance imaging measurements in Alzheimer’s disease. J Alzheimers Dis 48:987–994CrossRefGoogle Scholar
  19. 19.
    Gordon BA, Najmi S, Hsu P, Roe CM, Morris JC, Benzinger TLS (2015) The effects of white matter hyperintensities and amyloid deposition on Alzheimer dementia. Neuroimage Clin 8:246–252CrossRefGoogle Scholar
  20. 20.
    Lee SH, Coutu JP, Wilkens P, Yendiki A, Rosas HD, Salat DH et al (2015) Tract-based analysis of white matter degeneration in Alzheimer’s disease. Neuroscience 301:79–89CrossRefGoogle Scholar
  21. 21.
    De Lange AMG, Brathen ACS, Grydeland H, Sexton C, Johansen-Berg H, Andersson JLR, et al (2016) White matter integrity as a marker for cognitive plasticity in aging. Neurobiol Aging 47:74–82Google Scholar
  22. 22.
    Powell D, Caban-Holt A, Jicha G, Robertson W, Davis RGold BT et al (2014) Frontal white matter integrity in adults with Down syndrome with and without dementia. Neurobiol Aging 35:1562–1569CrossRefGoogle Scholar
  23. 23.
    Gedye A (1995) Dementia scale for Down syndrome manual. Gedye Research and Consulting, VancouverGoogle Scholar
  24. 24.
    Evenhuis HM (1996) Further evaluation of the dementia questionnaire for persons with mental retardation (DMR). J Intellect Disabil Res 40:369–373CrossRefGoogle Scholar
  25. 25.
    Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE et al (2006) Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage 31:1487–1505CrossRefGoogle Scholar
  26. 26.
    Smith SM, Johansen-Berg H, Jenkinson M, Rueckert D, Nichols TE, Miller KL et al (2007) Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics. Nat Protoc 2:499–503CrossRefGoogle Scholar
  27. 27.
    Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15:1–25CrossRefGoogle Scholar
  28. 28.
    Carducci F, Condoluci C, Di Gennaro G, Quarato P, Pierallini A, Sarà M, et al (2013) Whole-brain voxel-based morphometry study of children and adolescents with Down syndrome. Funct Neurol 28:19–28Google Scholar
  29. 29.
    Aung WY, Mar S, Benzinger TLS (2013) Diffusion tensor MRI as biomarker in axonal and myelin damage. Imaging Med 5:427–440CrossRefGoogle Scholar
  30. 30.
    Budde MD, Xie M, Cross AH, Song SK (2009) Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. J Neurosci 29:2805–2813CrossRefGoogle Scholar
  31. 31.
    Acosta-Cabronero J, Alley S, Williams GB, Pengas G, Nestor GP (2012) Diffusion tensor metrics as biomarkers in Alzheimer’s disease. PlosONE 11:e49072CrossRefGoogle Scholar
  32. 32.
    Acosta-Cabronero J, Nestor PJ (2014) Diffusion tensor imaging in Alzheimer’s disease: insights into the limbic-diencephalic network and methodological considerations. Front Aging Neurosci 6:266CrossRefGoogle Scholar
  33. 33.
    Nir TM, Jahanshad N, Villalon-reina JE, Toga AW, Jack CR, Weiner MW, Thompson PM (2013) Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging. Neuroimage: Clin 3:180–195CrossRefGoogle Scholar
  34. 34.
    Petry S, Cummings JL, Hill MA, Shapira J (1988) Personality alterations in dementia of the Alzheimer type. Arch Neurol 45:1187–1190CrossRefGoogle Scholar
  35. 35.
    Ismail Z, Smith EE, Geda Y, Sultzer D, Brodaty H, Smith G et al (2016) Neuropsychiatric symptoms as early manifestations of emergent dementia: provisional diagnostic criteria for mild behavioral impairment. Alzheimers Dement 12:95–202CrossRefGoogle Scholar
  36. 36.
    Rigoldi C, Galli M, Condoluci C, Carducci F, Onorati P, Albertini G (2009) Gait analysis and cerebral volumes in Down’s syndrome. Funct Neurol 24:147–152PubMedGoogle Scholar
  37. 37.
    Ball SL, Holland AJ, Treppner P, Watson PC, Huppert FA (2008) Executive dysfunction and its association with personality and behaviour changes in the development of Alzheimer’s disease in adults with Down syndrome and mild to moderate learning disabilities. Br J Clin Psychol 47:1–29CrossRefGoogle Scholar
  38. 38.
    Cacciari C, Moraschi M, Di Paola M, Cherubini A, Orfei MD, Giove F, et al (2010) White matter microstructure and apathy level in amnestic mild cognitive impairment. Journal of Alzheimers Disease 20:501–507CrossRefGoogle Scholar
  39. 39.
    Peters A (2002) The effects of normal aging on myelin and nerve fibers: a review. J Neurocytol 31:581–593CrossRefGoogle Scholar
  40. 40.
    Marner L, Nyengaard JR, Tang Y, Pakkenberg B (2003) Marked loss of myelinated nerve fibers in the human brain with age. J Comp Neurol 462:144–152CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Andrea Romano
    • 1
    • 2
  • Marta Moraschi
    • 3
  • Riccardo Cornia
    • 4
  • Alessandro Bozzao
    • 2
  • Maria Camilla Rossi-Espagnet
    • 2
    • 5
  • Federico Giove
    • 3
    • 6
  • Giorgio Albertini
    • 7
  • Alberto Pierallini
    • 8
  1. 1.Department of Odontostomatological and Maxillo-Facial Sciences, Umberto I HospitalUniversity SapienzaRomeItaly
  2. 2.NESMOS, Department of Neuroradiology, S. Andrea HospitalUniversity SapienzaRomeItaly
  3. 3.Centro Fermi-Museo Storico Della Fisica e Centro Studi e Ricerche Enrico FermiRomeItaly
  4. 4.Department of Biotechnological and Applied Clinical Sciences, Neurological InstituteUniversity of L’AquilaL’AquilaItaly
  5. 5.Neuroradiology Unit, Imaging DepartmentBambino Gesù Children’s HospitalRomeItaly
  6. 6.Fondazione Santa Lucia IRCSSRomeItaly
  7. 7.Department of PaediatricsIRCSS San Raffaele PisanaRomeItaly
  8. 8.Department of RadiologyIRCSS San Raffaele PisanaRomeItaly

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