Robust Identification of Alzheimer's Disease subtypes based on cortical atrophy patterns

Scientific Reports

Volumn 7, Issue , 2017, Pages

  Park, Jong Yun ^a   Na, Han Kyu ^b   Kim, Sungsoo ^b   Kim, Hyunwook ^b   Kim, Hee Jin ^c,d   Seo, Sang Won ^c,d   Na, Duk L ^c,d   Han, Cheol E ^a   Seong, Joon Kyung ^a  

^a Korea University   (South Korea)

^b Yonsei University College of Medicine   (South Korea)

^c Sungkyunkwan University School of Medicine   (South Korea)

^d Samsung Medical Center   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

AGED; ALZHEIMER DISEASE; ATROPHY; BRAIN CORTEX; CLASSIFICATION; DIAGNOSTIC IMAGING; FEMALE; HUMAN; MALE; MIDDLE AGED; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY;

AGED; ALZHEIMER DISEASE; ATROPHY; CEREBRAL CORTEX; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED;

EID: 85014924701     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep43270     Document Type: Article

References (60)

1. Blennow, K., de Leon, M. J. & Zetterberg, H. Alzheimer's disease. Lancet 368, 387-403, doi: 10.1016/S0140-6736(06)69113-7 (2006).
2. Schmidt, C. et al. Clinical features of rapidly progressive Alzheimer's disease. Dementia and geriatric cognitive disorders 29, 371-378, doi: 10.1159/000278692 (2010).
3. Schmidt, C. et al. Rapidly progressive Alzheimer disease. Arch Neurol 68, 1124-1130, doi: 10.1001/archneurol.2011.189 (2011).
4. Wattmo, C., Wallin, A. K. & Minthon, L. Progression of mild Alzheimer's disease: knowledge and prediction models required for future treatment strategies. Alzheimer's research & therapy 5, 44, doi: 10.1186/alzrt210 (2013).
5. Murray, M. E. et al. Neuropathologically defined subtypes of Alzheimer's disease with distinct clinical characteristics: a retrospective study. The Lancet. Neurology 10, 785-796, doi: 10.1016/S1474-4422(11)70156-9 (2011).
6. Noh, Y. et al. Anatomical heterogeneity of Alzheimer disease: based on cortical thickness on MRIs. Neurology 83, 1936-1944, doi: 10.1212/WNL.0000000000001003 (2014).
7. Na, H. K. et al. Malignant progression in parietal-dominant atrophy subtype of Alzheimer's disease occurs independent of onset age. Neurobiology of aging 47, 149-156, doi: 10.1016/j.neurobiolaging.2016.08.001 (2016).
8. Nettiksimmons, J., DeCarli, C., Landau, S. & Beckett, L. & Alzheimer's Disease Neuroimaging, I. Biological heterogeneity in ADNI amnestic mild cognitive impairment. Alzheimers Dement 10, 511-521 e511, doi: 10.1016/j.jalz.2013.09.003 (2014).
9. Blondel, V. D., Guillaume, J.-L., Lambiotte, R. & Lefebvre, E. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment. 1000 (2008).
10. O?Bryant, S. E. et al. Validation of the new interpretive guidelines for the clinical dementia rating scale sum of boxes score in the national Alzheimer's coordinating center database. Arch Neurol 67, 746-749, doi: 10.1001/archneurol.2010.115 (2010).
11. O?Bryant, S. E. et al. Staging dementia using Clinical Dementia Rating Scale Sum of Boxes scores: a Texas Alzheimer's research consortium study. Arch Neurol 65, 1091-1095, doi: 10.1001/archneur.65.8.1091 (2008).
12. Behrmann, M., Geng, J. J. & Shomstein, S. Parietal cortex and attention. Curr Opin Neurobiol 14, 212-217, doi: 10.1016/j. conb.2004.03.012 (2004).
13. Cavanna, A. E. & Trimble, M. R. The precuneus: a review of its functional anatomy and behavioural correlates. Brain: a journal of neurology 129, 564-583, doi: 10.1093/brain/awl004 (2006).
14. Jacobs, H. I., Van Boxtel, M. P., Jolles, J., Verhey, F. R. & Uylings, H. B. Parietal cortex matters in Alzheimer's disease: an overview of structural, functional and metabolic findings. Neurosci Biobehav Rev 36, 297-309, doi: 10.1016/j.neubiorev.2011.06.009 (2012).
15. Wagner, A. D., Shannon, B. J., Kahn, I. & Buckner, R. L. Parietal lobe contributions to episodic memory retrieval. Trends Cogn Sci 9, 445-453, doi: 10.1016/j.tics.2005.07.001 (2005).
16. Gross, R. G. & Grossman, M. Update on apraxia. Current neurology and neuroscience reports 8, 490-496 (2008).
17. Itakura, H. et al. Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities. Science translational medicine 7, 303ra138, doi: 10.1126/scitranslmed.aaa7582 (2015).
18. Makuuchi, M., Kaminaga, T. & Sugishita, M. Brain activation during ideomotor praxis: imitation and movements executed by verbal command. Journal of neurology, neurosurgery, and psychiatry 76, 25-33, doi: 10.1136/jnnp.2003.029165 (2005).
19. Whitwell, J. L. et al. Neuroimaging correlates of pathologically defined subtypes of Alzheimer's disease: a case-control study. The Lancet. Neurology 11, 868-877, doi: 10.1016/S1474-4422(12)70200-4 (2012).
20. Shiino, A. et al. Four subgroups of Alzheimer's disease based on patterns of atrophy using VBM and a unique pattern for early onset disease. NeuroImage 33, 17-26, doi: 10.1016/j.neuroimage.2006.06.010 (2006).
21. Dong, A., Honnorat, N., Gaonkar, B. & Davatzikos, C. CHIMERA: Clustering of Heterogeneous Disease Effects via Distribution Matching of Imaging Patterns. IEEE transactions on medical imaging 35, 612-621, doi: 10.1109/TMI.2015.2487423 (2016).
22. Duyckaerts, C. Disentangling Alzheimer's disease. The Lancet. Neurology 10, 774-775, doi: 10.1016/S1474-4422(11)70171-5 (2011).
23. Mattsson, N., Schott, J. M., Hardy, J., Turner, M. R. & Zetterberg, H. Selective vulnerability in neurodegeneration: insights from clinical variants of Alzheimer's disease. Journal of neurology, neurosurgery, and psychiatry, doi: 10.1136/jnnp-2015-311321 (2016).
24. Didic, M. et al. Which memory system is impaired first in Alzheimer's disease? Journal of Alzheimer's disease: JAD 27, 11-22, doi: 10.3233/JAD-2011-110557 (2011).
25. Domoto-Reilly, K., Sapolsky, D., Brickhouse, M. & Dickerson, B. C. & Alzheimer's Disease Neuroimaging, I. Naming impairment in Alzheimer's disease is associated with left anterior temporal lobe atrophy. NeuroImage 63, 348-355, doi: 10.1016/j. neuroimage.2012.06.018 (2012).
26. Bruner, E. & Jacobs, H. I. Alzheimer's disease: the downside of a highly evolved parietal lobe? Journal of Alzheimer's disease: JAD 35, 227-240, doi: 10.3233/JAD-122299 (2013).
27. Chiang, M. C. et al. Genetics of brain fiber architecture and intellectual performance. J Neurosci 29, 2212-2224, doi: 10.1523/ JNEUROSCI.4184-08.2009 (2009).
28. Gour, N. et al. Basal functional connectivity within the anterior temporal network is associated with performance on declarative memory tasks. NeuroImage 58, 687-697, doi: 10.1016/j.neuroimage.2011.05.090 (2011).
29. King, K. S. et al. Evaluation of a practical visual MRI rating scale of brain white matter hyperintensities for clinicians based on largest lesion size regardless of location. AJNR Am J Neuroradiol 34, 797-801, doi: 10.3174/ajnr.A3283 (2013).
30. Noh, Y. et al. A new classification system for ischemia using a combination of deep and periventricular white matter hyperintensities. J Stroke Cerebrovasc Dis 23, 636-642, doi: 10.1016/j.jstrokecerebrovasdis.2013.06.002 (2014).
31. Shim, Y. S. et al. Effects of medial temporal atrophy and white matter hyperintensities on the cognitive functions in patients with Alzheimer's disease. Eur Neurol 66, 75-82, doi: 10.1159/000329277 (2011).
32. Laakso, M. P. et al. Volumes of hippocampus, amygdala and frontal lobes in the MRI-based diagnosis of early Alzheimer's disease: Correlation with memory functions. Journal of Neural Transmission- Parkinson's Disease and Dementia Section 9, 73-86, doi: 10.1007/bf02252964 (1995).
33. Jack, C. R. Jr. et al. The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. Journal of magnetic resonance imaging: JMRI 27, 685-691, doi: 10.1002/jmri.21049 (2008).
34. Kukull, W. A. et al. The Mini-Mental State Examination score and the clinical diagnosis of dementia. J Clin Epidemiol 47, 1061-1067 (1994).
35. Petersen, R. C. et al. Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology 74, 201-209, doi: 10.1212/WNL.0b013e3181cb3e25 (2010).
36. Kang, Y. W. & Na, D. L. Seoul Neurophsychological Screening Battery: Professional Manual. (Human Brain Research & Consulting Co., 2003).
37. Kang, Y. W., Chang, S. M. & Na, D. L. Seoul Neurophsychological Screening Battery: Professional Manual. 2 edn, (Human Brain Research & Consulting Co., 2012).
38. Kim, H. & Na, D. L. Normative data on the Korean version of the Boston Naming Test. Journal of clinical and experimental neuropsychology 21, 127-133, doi: 10.1076/jcen.21.1.127.942 (1999).
39. Mueller, S. G. et al. Ways toward an early diagnosis in Alzheimer's disease: the Alzheimer's Disease Neuroimaging Initiative (ADNI). Alzheimers Dement 1, 55-66, doi: 10.1016/j.jalz.2005.06.003 (2005).
40. Park, L. Q. et al. Confirmatory factor analysis of the ADNI Neuropsychological Battery. Brain Imaging Behav 6, 528-539, doi: 10.1007/s11682-012-9190-3 (2012).
41. Mohs, R. C. et al. Development of cognitive instruments for use in clinical trials of antidementia drugs: additions to the Alzheimer's Disease Assessment Scale that broaden its scope. The Alzheimer's Disease Cooperative Study. Alzheimer Dis Assoc Disord 11 Suppl 2, S13-21 (1997).
42. Rosen, W. G., Mohs, R. C. & Davis, K. L. A new rating scale for Alzheimer's disease. Am J Psychiatry 141, 1356-1364 (1984).
43. Mack, W. J., Freed, D. M., Williams, B. W. & Henderson, V. W. Boston Naming Test: shortened versions for use in Alzheimer's disease. J Gerontol 47, P154-158 (1992).
44. Barzotti, T. et al. Correlation between cognitive impairment and the Rey auditory-verbal learning test in a population with Alzheimer disease. Arch Gerontol Geriatr Suppl. 57-62, doi: 10.1016/j.archger.2004.04.010 (2004).
45. van Hout, H. & Berkhout, S. Inter-rater reliability of the clock-drawing test. Age Ageing 28, 327-328 (1999).
46. Bowie, C. R. & Harvey, P. D. Administration and interpretation of the Trail Making Test. Nat Protoc 1, 2277-2281, doi: 10.1038/ nprot.2006.390 (2006).
47. Tombaugh, T. N.Trail Making Test A and B: normative data stratified by age and education. Arch Clin Neuropsychol 19, 203-214, doi: 10.1016/S0887-6177(03)00039-8 (2004).
48. Lezak, M. D. Neuropsychological Assessment. 3 edn, (Oxford University Press, 1995).
49. Gibbons, L. E. et al. A composite score for executive functioning, validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment. Brain Imaging Behav 6, 517-527, doi: 10.1007/s11682-012-9176-1 (2012).
50. Crane, P. K. et al. Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Brain Imaging Behav 6, 502-516, doi: 10.1007/s11682-012-9186-z (2012).
51. Dale, A. M., Fischl, B. & Sereno, M. I. Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage 9, 179-194 (1999).
52. Dale, A. M. & Sereno, M. I. Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. J Cogn Neurosci 5, 162-176 (1993).
53. Cho, Y., Seong, J. K., Jeong, Y., Shin, S. Y. & Alzheimer's Disease Neuroimaging, I. Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data. NeuroImage 59, 2217-2230, doi: 10.1016/j.neuroimage.2011.09.085 (2012).
54. Levy, B. In SMI'06: Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006. 13 (IEEE Computer Society).
55. Qiu, A., Bitouk, D. & Miller, M. Smooth functional and structural maps on the neocortex via orthonormal bases of the Laplace- Beltrami operator. IEEE Trans. Med. Imaging 25, 1296-1306 (2006).
56. Rubinov, M. & Sporns, O. Complex network measures of brain connectivity: Uses and interpretations. NeuroImage 52, 1059-1069, doi: S1053-8119(09)01074-X [pii] 10.1016/j.neuroimage.2009.10.003 (2010).
57. Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31, 968-980 (2006).
58. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol, 289-300 (1995).
59. Genovese, C. R., Lazar, N. A. & Nichols, T. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage 15, 870-878 (2002).
60. Poline, J. B., Worsley, K. J., Evans, A. C. & Friston, K. J. Combining spatial extent and peak intensity to test for activations in functional imaging. NeuroImage 5, 83-96, doi: 10.1006/nimg.1996.0248 (1997).