A graph theoretic approach to neurodegeneration: five data-driven neuropsychological subtypes in mild cognitive impairment

References

• Bermejo-Pareja, F., Contador, I., Trincado, R., Lora, D., Sanchez-Ferro, Á., Mitchell, A. J., Boycheva, E., Herrero, A., Hernandez-Gallego, J., Llamas, S., Villarejo Galende, A., & Benito Leon, J. (2016). Prognostic significance of mild cognitive impairment subtypes for dementia and mortality: Data from the NEDICES Cohort. Journal of Alzheimer’s Disease, 50(3), 719–731. https://doi.org/10.3233/JAD-150625
   PubMed Web of Science ®Google Scholar
• Blanken, A. E., Jang, J. Y., Ho, J. K., Edmonds, E. C., Han, S. D., Bangen, K. J., & Nation, D. A. (2020). Distilling heterogeneity of mild cognitive impairment in the National Alzheimer coordinating center database using latent profile analysis. JAMA Network Open, 3(3), e200413. https://doi.org/10.1001/jamanetworkopen.2020.0413
   PubMed Web of Science ®Google Scholar
• Bondi, M. W., Edmonds, E. C., Jak, A. J., Clark, L. R., Delano-Wood, L., McDonald, C. R., Nation, D. A., Libon, D. J., Au, R., Galasko, D., & Salmon, D. P. (2014). Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. Journal of Alzheimer’s Disease, 42(1), 275–289. https://doi.org/10.3233/JAD-140276
   PubMed Web of Science ®Google Scholar
• Casaletto, K. B., Elahi, F. M., Staffaroni, A. M., Walters, S., Contreras, W. R., Wolf, A., Dubal, D., Miller, B., Yaffe, K., & Kramer, J. H. (2019). Cognitive aging is not created equally: Differentiating unique cognitive phenotypes in “normal” adults. Neurobiology of aging, 77, 13–19. https://doi.org/10.1016/j.neurobiolaging.2019.01.007
   PubMed Web of Science ®Google Scholar
• Christa Maree Stephan, B., Minett, T., Pagett, E., Siervo, M., Brayne, C., & McKeith, I. G. (2013). Diagnosing Mild Cognitive Impairment (MCI) in clinical trials: A systematic review. BMJ Open, 3(2), e001909. https://doi.org/10.1136/bmjopen-2012-001909
   PubMed Web of Science ®Google Scholar
• Clark, L. R., Delano-Wood, L., Libon, D. J., McDonald, C. R., Nation, D. A., Bangen, K. J., Jak, A. J., Au, R., Salmon, D. P., & Bondi, M. W. (2013). Are empirically-derived subtypes of mild cognitive impairment consistent with conventional subtypes? Journal of the International Neuropsychological Society, 19(6), 635–645. https://doi.org/10.1017/S1355617713000313
   PubMed Web of Science ®Google Scholar
• Costa, A. S., Dogan, I., Schulz, J. B., & Reetz, K. (2019). Going beyond the mean: Intraindividual variability of cognitive performance in prodromal and early neurodegenerative disorders. The Clinical Neuropsychologist, 33(2), 369–389. https://doi.org/10.1080/13854046.2018.1533587
   PubMed Web of Science ®Google Scholar
• Delano-Wood, L., Bondi, M. W., Sacco, J., Abeles, N., Jak, A. J., Libon, D. J., & Bozoki, A. (2009). Heterogeneity in mild cognitive impairment: Differences in neuropsychological profile and associated white matter lesion pathology. Journal of the International Neuropsychological Society, 15(6), 906–914. https://doi.org/10.1017/S1355617709990257
   PubMed Web of Science ®Google Scholar
• Diaz-Mardomingo, M. D. C., Garcia-Herranz, S., Rodriguez-Fernandez, R., Venero, C., & Peraita, H. (2017). Problems in classifying Mild Cognitive Impairment (MCI): One or multiple syndromes? Brain sciences, 7(9). https://doi.org/10.3390/brainsci7090111
   PubMed Web of Science ®Google Scholar
• Edler, D., Eriksson, A., & Rosvall, M. (2014). The MapEquation software package. mapequation.org
   Google Scholar
• Edmonds, E. C., McDonald, C. R., Marshall, A., Thomas, K. R., Eppig, J., Weigand, A. J., Delano-Wood, L., Galasko, D. R., Salmon, D. P., Bondi, M. W., & Alzheimer’s Disease Neuroimaging, I. (2019). Early versus late MCI: Improved MCI staging using a neuropsychological approach. Alzheimer’s & Dementia, 15(5), 699–708. https://doi.org/10.1016/j.jalz.2018.12.009
   PubMed Web of Science ®Google Scholar
• Edmonds, E. C., Smirnov, D. S., Thomas, K. R., Graves, L. V., Bangen, K. J., Delano-Wood, L., Galasko, D. R., Salmon, D. P., & Bondi, M. W. (2021). Data-driven vs consensus diagnosis of MCI: Enhanced sensitivity for detection of clinical, biomarker, and neuropathologic outcomes. Neurology, 97(13), e1288–1299. https://doi.org/10.1212/WNL.0000000000012600
   PubMed Web of Science ®Google Scholar
• Eliassen, C. F., Reinvang, I., Selnes, P., Grambaite, R., Fladby, T., & Hessen, E. (2017). Biomarkers in subtypes of mild cognitive impairment and subjective cognitive decline. Brain and Behavior, 7(9), e00776. https://doi.org/10.1002/brb3.776
   PubMed Web of Science ®Google Scholar
• Ellendt, S., Vobeta, B., Kohn, N., Wagels, L., Goerlich, K. S., Drexler, E., Schneider, F., & Habel, U. (2017). Predicting stability of Mild Cognitive Impairment (MCI): Findings of a community based sample. Current Alzheimer Research, 14(6), 608–619. https://doi.org/10.2174/1567205014666161213120807
   PubMed Web of Science ®Google Scholar
• Eppig, J. S., Edmonds, E. C., Campbell, L., Sanderson-Cimino, M., Delano-Wood, L., Bondi, M. W., & Alzheimer’s Disease Neuroimaging, I. (2017). Statistically derived subtypes and associations with cerebrospinal fluid and genetic biomarkers in mild cognitive impairment: A latent profile analysis. Journal of the International Neuropsychological Society, 23(7), 564–576. https://doi.org/10.1017/S135561771700039X
   PubMed Web of Science ®Google Scholar
• Ezzati, A., Zammit, A. R., Habeck, C., Hall, C. B., Lipton, R. B., & Alzheimer’s Disease Neuroimaging, I. (2020). Detecting biological heterogeneity patterns in ADNI amnestic mild cognitive impairment based on volumetric MRI. Brain Imaging and Behavior, 14(5), 1792–1804. https://doi.org/10.1007/s11682-019-00115-6
   PubMed Web of Science ®Google Scholar
• Fair, D. A., Bathula, D., Nikolas, M. A., & Nigg, J. T. (2012). Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD. Proceedings of the National Academy of Sciences, 109(17), 6769–6774. https://doi.org/10.1073/pnas.1115365109
   PubMed Web of Science ®Google Scholar
• Feczko, E., Balba, N. M., Miranda-Dominguez, O., Cordova, M., Karalunas, S. L., Irwin, L., Demeter, D. V., Hill, A. P., Langhorst, B. H., Grieser Painter, J., Van Santen, J., Fombonne, E. J., Nigg, J. T., & Fair, D. A. (2018). Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm. Neuroimage, 172, 674–688. https://doi.org/10.1016/j.neuroimage.2017.12.044
   PubMed Web of Science ®Google Scholar
• Feczko, E., & Fair, D. A. (2020). Methods and challenges for Assessing Heterogeneity. Biological psychiatry, 88(1), 9–17. https://doi.org/10.1016/j.biopsych.2020.02.015
   PubMed Web of Science ®Google Scholar
• Feczko, E., Miranda-Dominguez, O., Marr, M., Graham, A. M., Nigg, J. T., & Fair, D. A. (2019). The heterogeneity problem: Approaches to identify psychiatric subtypes. Trends in Cognitive Sciences, 23(7), 584–601. https://doi.org/10.1016/j.tics.2019.03.009
   PubMed Web of Science ®Google Scholar
• Ganguli, M., Snitz, B. E., Saxton, J. A., Chang, C. C., Lee, C. W., Vander Bilt, J., Hughes, T. F., Loewenstein, D. A., Unverzagt, F. W., & Petersen, R. C. (2011). Outcomes of mild cognitive impairment by definition: A population study. Archives of Neurology, 68(6), 761–767. https://doi.org/10.1001/archneurol.2011.101
   PubMedGoogle Scholar
• Giraldo, D. L., Sijbers, J., Romero, E., & Alzheimer’s Disease Neuroimaging, I. (2021). Quantification of cognitive impairment to characterize heterogeneity of patients at risk of developing Alzheimer’s disease dementia. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 13(1), e12237. https://doi.org/10.1002/dad2.12237
   PubMedGoogle Scholar
• Glynn, K., O’Callaghan, M., Hannigan, O., Bruce, I., Gibb, M., Coen, R., Green, E., B, A. L., & Robinson, D. (2021). Clinical utility of mild cognitive impairment subtypes and number of impaired cognitive domains at predicting progression to dementia: A 20-year retrospective study. International Journal of Geriatric Psychiatry, 36(1), 31–37. https://doi.org/10.1002/gps.5385
   PubMed Web of Science ®Google Scholar
• Gorno-Tempini, M. L., Hillis, A. E., Weintraub, S., Kertesz, A., Mendez, M., Cappa, S. F., Ogar, J. M., Rohrer, J. D., Black, S., Boeve, B. F., Manes, F., Dronkers, N. F., Vandenberghe, R., Rascovsky, K., Patterson, K., Miller, B. L., Knopman, D. S., Hodges, J. R., Mesulam, M. M., & Grossman, M. (2011). Classification of primary progressive aphasia and its variants. Neurology, 76(11), 1006–1014. https://doi.org/10.1212/WNL.0b013e31821103e6
   PubMed Web of Science ®Google Scholar
• Gothlin, M., Eckerstrom, M., Rolstad, S., Wallin, A., & Nordlund, A. (2017). Prognostic accuracy of mild cognitive impairment subtypes at different cut-off levels. Dementia and geriatric cognitive disorders, 43(5–6), 330–341. https://doi.org/10.1159/000477341
   PubMed Web of Science ®Google Scholar
• Guo, S., Xiao, B., Wu, C., & Alzheimer’s Disease Neuroimaging, I. (2020). Identifying subtypes of mild cognitive impairment from healthy aging based on multiple cortical features combined with volumetric measurements of the hippocampal subfields. Quantitative Imaging in Medicine and Surgery, 10(7), 1477–1489. https://doi.org/10.21037/qims-19-872
   PubMed Web of Science ®Google Scholar
• Hu, C., Yu, D., Sun, X., Zhang, M., Wang, L., & Qin, H. (2017). The prevalence and progression of mild cognitive impairment among clinic and community populations: A systematic review and meta-analysis. International Psychogeriatrics, 29(10), 1595–1608. https://doi.org/10.1017/S1041610217000473
   PubMed Web of Science ®Google Scholar
• Jak, A. J., Bangen, K. J., Wierenga, C. E., Delano-Wood, L., Corey-Bloom, J., & Bondi, M. W. (2009). Contributions of neuropsychology and neuroimaging to understanding clinical subtypes of mild cognitive impairment. International Review of Neurobiology, 84, 81–103. https://doi.org/10.1016/S0074-7742(09)00405-X
   PubMed Web of Science ®Google Scholar
• Jak, A. J., Bondi, M. W., Delano-Wood, L., Wierenga, C., Corey-Bloom, J., Salmon, D. P., & Delis, D. C. (2009). Quantification of five neuropsychological approaches to defining mild cognitive impairment. The American Journal of Geriatric Psychiatry, 17(5), 368–375. https://doi.org/10.1097/JGP.0b013e31819431d5
   PubMed Web of Science ®Google Scholar
• Jak, A. J., Preis, S. R., Beiser, A. S., Seshadri, S., Wolf, P. A., Bondi, M. W., & Au, R. (2016). Neuropsychological criteria for mild cognitive impairment and Dementia risk in the Framingham heart study. Journal of the International Neuropsychological Society, 22(9), 937–943. https://doi.org/10.1017/S1355617716000199
   PubMed Web of Science ®Google Scholar
• Jessen, F., Amariglio, R. E., Buckley, R. F., van der Flier, W. M., Han, Y., Molinuevo, J. L., Rabin, L., Rentz, D. M., Rodriguez-Gomez, O., Saykin, A. J., Sikkes, S. A. M., Smart, C. M., Wolfsgruber, S., & Wagner, M. (2020). The characterisation of subjective cognitive decline. Lancet neurology, 19(3), 271–278. https://doi.org/10.1016/S1474-4422(19)30368-0
   PubMed Web of Science ®Google Scholar
• Kim, J. Y., Lim, J. H., Jeong, Y. J., Kang, D. -Y., & Park, K. W. (2019). The effect of clinical characteristics and subtypes on amyloid positivity in patients with amnestic mild cognitive impairment. Dementia and Neurocognitive Disorders, 18(4), 130–137. https://doi.org/10.12779/dnd.2019.18.4.130
   PubMedGoogle Scholar
• Lee, H. J., Lee, E. C., Seo, S., Ko, K. P., Kang, J. M., Kim, W. R., Seo, H. E., Lee, S. Y., Lee, Y. B., Park, K. H., Yeon, B. K., Okamura, N., Na, D. L., Seong, J. K., & Noh, Y. (2020). Identification of heterogeneous subtypes of mild cognitive impairment using cluster analyses based on PET imaging of Tau and Astrogliosis. Frontiers in aging neuroscience, 12, 615467. https://doi.org/10.3389/fnagi.2020.615467
   PubMed Web of Science ®Google Scholar
• Lin, C. Y., Chen, T. B., Lin, K. N., Yeh, Y. C., Chen, W. T., Wang, K. S., & Wang, P. N. (2014). Confrontation naming errors in Alzheimer’s disease. Dementia and geriatric cognitive disorders, 37(1–2), 86–94. https://doi.org/10.1159/000354359
   PubMed Web of Science ®Google Scholar
• Machulda, M. M., Lundt, E. S., Albertson, S. M., Kremers, W. K., Mielke, M. M., Knopman, D. S., Bondi, M. W., & Petersen, R. C. (2019). Neuropsychological subtypes of incident mild cognitive impairment in the Mayo clinic study of aging. Alzheimer’s & Dementia : The Journal of the Alzheimer’s Association, 15(7), 878–887. https://doi.org/10.1016/j.jalz.2019.03.014
   PubMed Web of Science ®Google Scholar
• Machulda, M. M., Lundt, E. S., Albertson, S. M., Spychalla, A. J., Schwarz, C. G., Mielke, M. M., Jack, C. R., Jr., Kremers, W. K., Vemuri, P., Knopman, D. S., Jones, D. T., Bondi, M. W., & Petersen, R. C. (2020). Cortical atrophy patterns of incident MCI subtypes in the Mayo clinic study of aging. Alzheimer’s & Dementia, 16(7), 1013–1022. https://doi.org/10.1002/alz.12108
   PubMed Web of Science ®Google Scholar
• Mesulam, M. M., Wieneke, C., Thompson, C., Rogalski, E., & Weintraub, S. (2012). Quantitative classification of primary progressive aphasia at early and mild impairment stages. Brain, 135(Pt 5), 1537–1553. https://doi.org/10.1093/brain/aws080
   PubMedGoogle Scholar
• Michaud, T. L., Su, D., Siahpush, M., & Murman, D. L. (2017). The risk of incident mild cognitive impairment and progression to dementia considering mild cognitive impairment subtypes. Dementia and Geriatric Cognitive Disorders Extra, 7(1), 15–29. https://doi.org/10.1159/000452486
   PubMed Web of Science ®Google Scholar
• Nation, D. A., Ho, J. K., Dutt, S., Han, S. D., Lai, M. H. C., Alzheimer’s Disease Neuroimaging, I., & Bondi, M. (2019). Neuropsychological decline improves prediction of dementia beyond Alzheimer’s disease biomarker and mild cognitive impairment diagnoses. Journal of Alzheimer’s Disease, 69(4), 1171–1182. https://doi.org/10.3233/JAD-180525
   PubMed Web of Science ®Google Scholar
• Nelson, H. E., & O’Connell, A. (1978). Dementia: The estimation of premorbid intelligence levels using the new adult reading test. Cortex, 14(2), 234–244. https://doi.org/10.1016/S0010-9452(78)80049-5
   PubMed Web of Science ®Google Scholar
• Nettiksimmons, J., DeCarli, C., Landau, S., Beckett, L., & Alzheimer’s Disease Neuroimaging, I. (2014). Biological heterogeneity in ADNI amnestic mild cognitive impairment. Alzheimer’s & Dementia, 10(5), 511–521 e511. https://doi.org/10.1016/j.jalz.2013.09.003
   PubMed Web of Science ®Google Scholar
• Nezhadmoghadam, F., Martinez-Torteya, A., Trevino, V., Martinez, E., Santos, A., & Tamez-Pena, J. (2021). Robust discovery of mild cognitive impairment subtypes and their risk of Alzheimer’s disease conversion using unsupervised machine learning and Gaussian mixture modeling. Current Alzheimer Research, 18(7), 595–606. https://doi.org/10.2174/1567205018666210831145825
   PubMed Web of Science ®Google Scholar
• Nordlund, A., Rolstad, S., Hellstrom, P., Sjogren, M., Hansen, S., & Wallin, A. (2005). The Goteborg MCI study: Mild cognitive impairment is a heterogeneous condition. Journal of Neurology, Neurosurgery & Psychiatry, 76(11), 1485–1490. https://doi.org/10.1136/jnnp.2004.050385
   PubMed Web of Science ®Google Scholar
• Oltra-Cucarella, J., Ferrer-Cascales, R., Alegret, M., Gasparini, R., Diaz-Ortiz, L. M., Rios, R., Martinez-Nogueras, A. L., Onandia, I., Perez-Vicente, J. A., Cabello-Rodriguez, L., & Sanchez-SanSegundo, M. (2018). Risk of progression to Alzheimer’s disease for different neuropsychological mild cognitive impairment subtypes: A hierarchical meta-analysis of longitudinal studies. Psychology and Aging, 33(7), 1007–1021. https://doi.org/10.1037/pag0000294
   PubMed Web of Science ®Google Scholar
• Overton, M., Pihlsgard, M., & Elmstahl, S. (2019). Prevalence and incidence of mild cognitive impairment across subtypes, age, and sex. Dementia and Geriatric Cognitive Disorders, 47(4–6), 219–232. https://doi.org/10.1159/000499763
   PubMed Web of Science ®Google Scholar
• Panza, F., Capurso, C., D’Introno, A., Colacicco, A. M., Capurso, A., & Solfrizzi, V. Heterogeneity of mild cognitive impairment and other predementia syndromes in progression to dementia. (2007). Neurobiology of aging, 28(10), 1631–1632; discussion 1633-1634. https://doi.org/10.1016/j.neurobiolaging.2006.07.019
   PubMed Web of Science ®Google Scholar
• Park, L. Q., Gross, A. L., McLaren, D. G., Pa, J., Johnson, J. K., Mitchell, M., Manly, J. J., & Alzheimer’s Disease Neuroimaging, I. (2012). Confirmatory factor analysis of the ADNI neuropsychological battery. Brain Imaging and Behavior, 6(4), 528–539. https://doi.org/10.1007/s11682-012-9190-3
   PubMed Web of Science ®Google Scholar
• Petersen, R. C. (2004). Mild cognitive impairment. CONTINUUM: Lifelong Learning in Neurology, 10(1), 9–28. https://doi.org/10.1212/01.CON.0000293545.39683.cc
   Google Scholar
• Petersen, R. C. (2016). Mild Cognitive Impairment. Continuum (Minneap Minn), 22(2 Dementia), 404–418. https://doi.org/10.1212/CON.0000000000000313
   PubMedGoogle Scholar
• Petersen, R. C., Caracciolo, B., Brayne, C., Gauthier, S., Jelic, V., & Fratiglioni, L. (2014). Mild cognitive impairment: A concept in evolution. Journal of Internal Medicine, 275(3), 214–228. https://doi.org/10.1111/joim.12190
   PubMed Web of Science ®Google Scholar
• Petersen, R. C., & Morris, J. C. Mild cognitive impairment as a clinical entity and treatment target. (2005). Archives of Neurology, 62(7), 1160–1163; discussion 1167. https://doi.org/10.1001/archneur.62.7.1160
   PubMed Web of Science ®Google Scholar
• Petersen, R. C., Wiste, H. J., Weigand, S. D., Fields, J. A., Geda, Y. E., Graff-Radford, J., Knopman, D. S., Kremers, W. K., Lowe, V., Machulda, M. M., Mielke, M. M., Stricker, N. H., Therneau, T. M., Vemuri, P., & Jack, C. R., Jr. (2021). NIA-AA Alzheimer’s disease framework: Clinical characterization of stages. Annals of Neurology, 89(6), 1145–1156. https://doi.org/10.1002/ana.26071
   PubMed Web of Science ®Google Scholar
• Rosvall, M., Axelsson, D., & Bergstrom, C. T. (2009). The map equation. The European Physical Journal Special Topics, 178(1), 13–23. https://doi.org/10.1140/epjst/e2010-01179-1
   Web of Science ®Google Scholar
• Salimi, S., Irish, M., Foxe, D., Hodges, J. R., Piguet, O., & Burrell, J. R. (2018). Can visuospatial measures improve the diagnosis of Alzheimer’s disease? Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 10(1), 66–74. https://doi.org/10.1016/j.dadm.2017.10.004
   PubMedGoogle Scholar
• Tatsuoka, C., Tseng, H., Jaeger, J., Varadi, F., Smith, M. A., Yamada, T., Smyth, K. A., Lerner, A. J., & Alzheimer’s Disease Neuroimaging, I. (2013). Modeling the heterogeneity in risk of progression to Alzheimer’s disease across cognitive profiles in mild cognitive impairment. Alzheimer’s Research & Therapy, 5(2), 14. https://doi.org/10.1186/alzrt168
   PubMed Web of Science ®Google Scholar
• Thomas, K. R., Edmonds, E. C., Eppig, J. S., Wong, C. G., Weigand, A. J., Bangen, K. J., Jak, A. J., Delano-Wood, L., Galasko, D. R., Salmon, D. P., Edland, S. D., Bondi, M. W., & Alzheimer’s Disease Neuroimaging, I. (2019). MCI-to-normal reversion using neuropsychological criteria in the Alzheimer’s disease neuroimaging initiative. Alzheimer’s & Dementia, 15(10), 1322–1332. https://doi.org/10.1016/j.jalz.2019.06.4948
   PubMed Web of Science ®Google Scholar
• Visser, P. J., Scheltens, P., & Verhey, F. R. (2005). Do MCI criteria in drug trials accurately identify subjects with predementia Alzheimer’s disease? Journal of Neurology, Neurosurgery & Psychiatry, 76(10), 1348–1354. https://doi.org/10.1136/jnnp.2004.047720
   PubMed Web of Science ®Google Scholar