131 Distinct brain MRI phenotypes and their association with long-term dementia risk 6 18. Galili T. dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics. 2015;31(22):3718-3720. doi:10.1093/bioinformatics/ btv428 19. Pantoni L. Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurol. 2010;9(7):689-701. doi:10.1016/S14744422(10)70104-6 20. Apostolova LG, Mosconi L, Thompson PM, et al. Subregional hippocampal atrophy predicts Alzheimer’s dementia in the cognitively normal. Neurobiol Aging. 2010;31(7):1077-1088. doi:10.1016/J.NEUROBIOLAGING.2008.08.008 21. Debette S, Beiser A, Decarli C, et al. Association of MRI markers of vascular brain injury with incident stroke, mild cognitive impairment, dementia, and mortality: the Framingham Offspring Study. Stroke. 2010;41(4):600-606. doi:10.1161/STROKEAHA.109.570044 22. Godin O, Tzourio C, Rouaud O, et al. Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study. J Alzheimers Dis. 2010;20(2):453-463. doi:10.3233/JAD-2010-1389 23. van Rooden S, Goos JDC, van Opstal AM, et al. Increased number of microinfarcts in Alzheimer disease at 7-T MR imaging. Radiology. 2014;270(1):205-211. doi:10.1148/ radiol.13130743 24. Habes M, Grothe MJ, Tunc B, McMillan C, Wolk DA, Davatzikos C. Disentangling heterogeneity in Alzheimer’s disease and related dementias using data-driven methods. Biol Psychiatry. 2020;88(1):70-82. doi:10.1016/J.BIOPSYCH.2020.01.016 25. Haldar P, Pavord ID, Shaw DE, et al. Cluster analysis and clinical asthma phenotypes. Am J Respir Crit Care Med. 2008;178(3):218-224. doi:10.1164/RCCM.200711-1754OC 26. Moore WC, Meyers DA, Wenzel SE, et al; National Heart, Lung, and Blood Institute’s Severe Asthma Research Program. Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program. Am J Respir Crit Care Med. 2010;181(4):315-323. doi:10.1164/RCCM.200906-0896OC 27. Burgel PR, Paillasseur JL, Caillaud D, et al; Initiatives BPCO Scientific Committee. Clinical COPD phenotypes: a novel approach using principal component and cluster analyses. Eur Respir J. 2010;36(3):531-539. doi:10.1183/09031936.00175109 28. Fens N, Van Rossum AGJ, Zanen P, et al. Subphenotypes of mild-to-moderate COPD by factor and cluster analysis of pulmonary function, CT imaging and breathomics in a populationbased survey. COPD. 2013;10(3):277-285. doi:10.3109/15412555.2012.744388 29. Lin IH, Chen DT, Chang YF, et al. Hierarchical clustering of breast cancer methylomes revealed differentially methylated and expressed breast cancer genes. PLoS One. 2015;10(2):e0118453. doi:10.1371/JOURNAL.PONE.0118453 30. Bashyam VM, Erus G, Doshi J, et al. MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide. Brain. 2020;143(7):23122324. doi:10.1093/BRAIN/AWAA160 31. Yang Z, Nasrallah IM, Shou H, et al; iSTAGING Consortium; Baltimore Longitudinal Study of Aging BLSA; Alzheimer’s Disease Neuroimaging Initiative ADNI. A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure. Nat Commun. 2021;12:7065. doi: 10.1038/s41467-021-26703-z 32. Habes M, Pomponio R, Shou H, et al; iSTAGING consortium, the Preclinical AD consortium, the ADNI, and the CARDIA studies. The Brain Chart of Aging: machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonizedMRscans. Alzheimers Dement. 2021;17(1):89102. doi:10.1002/ALZ.12178 33. Nettiksimmons J, DeCarli C, Landau S, Beckett L; Alzheimer’s Disease Neuroimaging Initiative. Biological heterogeneity in ADNI amnestic mild cognitive impairment. Alzheimers Dement. 2014;10(5):511-521.e1. doi:10.1016/J.JALZ.2013.09.003
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