Atrophy patterns in early clinical stages across distinct phenotypes of A lzheimer's disease
Open accessAbstract
Alzheimer's disease (AD) can present with distinct clinical variants. Identifying the earliest neurodegenerative changes associated with each variant has implications for early diagnosis, and for understanding the mechanisms that underlie regional vulnerability and disease progression in AD. We performed voxel‐based morphometry to detect atrophy patterns in early clinical stages of four AD phenotypes: Posterior cortical atrophy (PCA, “visual variant,” n = 93), logopenic variant primary progressive aphasia (lvPPA, “language variant,” n = 74), and memory‐predominant AD categorized as early age‐of‐onset (EOAD, <65 years, n = 114) and late age‐of‐onset (LOAD, >65 years, n = 114). Patients with each syndrome were stratified based on: (1) degree of functional impairment, as measured by the clinical dementia rating (CDR) scale, and (2) overall extent of brain atrophy, as measured by a neuroimaging approach that sums the number of brain voxels showing significantly lower gray matter volume than cognitively normal controls ( n = 80). Even at the earliest clinical stage (CDR = 0.5 or bottom quartile of overall atrophy), patients with each syndrome showed both common and variant‐specific atrophy. Common atrophy across variants was found in temporoparietal regions that comprise the posterior default mode network (DMN). Early syndrome‐specific atrophy mirrored functional brain networks underlying functions that are uniquely affected in each variant: Language network in lvPPA, posterior cingulate cortex‐hippocampal circuit in amnestic EOAD and LOAD, and visual networks in PCA. At more advanced stages, atrophy patterns largely converged across AD variants. These findings support a model in which neurodegeneration selectively targets both the DMN and syndrome‐specific vulnerable networks at the earliest clinical stages of AD. Hum Brain Mapp 36:4421–4437, 2015 . © 2015 Wiley Periodicals, Inc .
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Studies have demonstrated that executive or behavioral dysfunction typically develop after memory deficits in fvAD.
“While not apparent in our cases, studies have demonstrated that executive or behavioral dysfunction typically develop after memory deficits in fvAD [1, 22, 23].”
From Diagnosing the frontal variant of Alzheimer’s disease: a clinician’s yellow brick road (2017) · cites this paper as [23]
The Results (Participants and Neuropsychological Scores; page unavailable) describe memory-predominant profiles in early- and late-onset AD. The Discussion (Neuropsychological Features and Atrophy Patterns; page unavailable) reports later decline in non-memory functions, particularly in early-onset AD. The paper does not study fvAD or establish that executive or behavioral dysfunction typically follows memory deficits in that phenotype. (LLM, conf=0.82)
Experimental — accuracy not yet measuredIn fvAD, memory impairment is the first abnormality in up to 85% of patients, with the remainder developing memory impairment within 3 years from symptom onset.
“Conversely, in fvAD memory impairment is the first abnormality in up to 85% of patients (Fig. 4), with the remainder developing memory impairment within 3 years from symptom onset [1, 22, 23].”
From Diagnosing the frontal variant of Alzheimer’s disease: a clinician’s yellow brick road (2017) · cites this paper as [23]
The Introduction says amnesia is the most common presenting symptom of Alzheimer’s disease generally, but the paper studies PCA, lvPPA, EOAD and LOAD—not fvAD. Searches for fvAD, the 85% figure and memory impairment within three years found no passage addressing those claims in our copy; section pages were not provided. (LLM, conf=0.75)
Experimental — accuracy not yet measuredIn fvAD there is greater temporal than frontal atrophy, particularly in the perisylvian area compared to bvFTD.
“In fvAD there is greater temporal than frontal atrophy, particularly in the perisylvian area compared to bvFTD [21, 33].”
From Diagnosing the frontal variant of Alzheimer’s disease: a clinician’s yellow brick road (2017) · cites this paper as [33]
The Results (Voxel Based Morphometry: AD Variants Versus Controls; page unavailable) describe temporal and temporoparietal atrophy in the AD phenotypes studied, but do not examine frontal-variant AD (fvAD) or compare it with bvFTD. Searches for fvAD, bvFTD, perisylvian atrophy, and the frontal-versus-temporal comparison found no passage addressing the cited claim. (LLM, conf=0.76)
Experimental — accuracy not yet measuredIn bvFTD, frontal regions are more affected, particularly the anterior cingulate, orbitofrontal cortex, middle and superior frontal gyrus.
“In bvFTD, frontal regions are more affected, particularly the anterior cingulate, orbitofrontal cortex, middle and superior frontal gyrus [21, 33].”
From Diagnosing the frontal variant of Alzheimer’s disease: a clinician’s yellow brick road (2017) · cites this paper as [33]
The Results (Voxel Based Morphometry: AD Variants Versus Controls; page unavailable) describe atrophy in Alzheimer’s disease variants, not bvFTD. Searches for bvFTD and the named frontal regions found no passage reporting the claimed pattern; a bvFTD study appears only in the References. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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“…pattern of 18F-AV1451 uptake with relative sparing of the frontal cortex, in line with the atrophy pattern shown in patients with this phenotype (Ossenkoppele et al., 2015c), and the patient with corticobasal syndrome uniquely showed involvement of the peri-rolandic cortex and had greater…”
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Pini, L., Pievani, M., Bocchetta, M., Altomare, D., Bosco, P., Cavedo, E., Galluzzi, S., Marizzoni, M., & Frisoni, G. B. (2016) · Ageing Research Reviews · doi:10.1016/j.arr.2016.01.002 · Cited by 874 · see citing works
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BackgroundMethodInfluentialSelf-citationImaging tau and amyloid-β proteinopathies in Alzheimer disease and other conditions
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“Nevertheless, the cortical factor was associated with younger age at AD onset, consistent with previous studies describing subtypes with predominant cortical atrophy (3, 8, 15).”
BackgroundResultDisentangling Heterogeneity in Alzheimer’s Disease and Related Dementias Using Data-Driven Methods
Habes, M., Grothe, M. J., Tunc, B., McMillan, C., Wolk, D. A., & Davatzikos, C. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.01.016 · Cited by 167 · see citing works
18F-flortaucipir (AV-1451) tau PET in frontotemporal dementia syndromes
Tsai, R. M., Bejanin, A., Lesman-Segev, O., LaJoie, R., Visani, A., Bourakova, V., O’Neil, J. P., Janabi, M., Baker, S., Lee, S. E., et al. (2019) · Alzheimer's Research & Therapy · doi:10.1186/s13195-019-0470-7 · Cited by 164 · see citing works
Self-citationLocal and distant relationships between amyloid, tau and neurodegeneration in Alzheimer's Disease
Iaccarino, L., Tammewar, G., Ayakta, N., Baker, S. L., Bejanin, A., Boxer, A. L., Gorno-Tempini, M. L., Janabi, M., Kramer, J. H., Lazaris, A., et al. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.09.016 · Cited by 165 · see citing works
Self-citationAlzheimer disease brain atrophy subtypes are associated with cognition and rate of decline
Risacher, S. L., Anderson, W. H., Charil, A., Castelluccio, P. F., Shcherbinin, S., Saykin, A. J., Schwarz, A. J., Initiative, F. T. A. D. N., Initiative, A. D. N., Weiner, M. W., et al. (2017) · Neurology · doi:10.1212/wnl.0000000000004670 · Cited by 163 · see citing works
Self-citationPathophysiological subtypes of Alzheimer’s disease based on cerebrospinal fluid proteomics
Tijms, B. M., Gobom, J., Reus, L. M., Jansen, I. E., Hong, S., Dobričić, V., Kilpert, F., ten Kate, M., Barkhof, F., Tsolaki, M., et al. (2020) · Brain · doi:10.1093/brain/awaa325 · Cited by 192 · see citing works
“However, individuals with Alzheimer’s disease show considerable variability in terms of clinical symptoms, age of onset, disease progression, cortical atrophy patterns, CSF levels of tau, and other pathological markers (Blennow and Wallin, 1992; Iqbal et al., 2005; van der Vlies et al., 2009; Wallin et al., 2010; Whit…”
BackgroundSelf-citationYounes, K., Borghesani, V., Montembeault, M., Spina, S., Mandelli, M. L., Welch, A. E., Weis, E., Callahan, P., Elahi, F. M., Hua, A. Y., et al. (2022) · Brain · doi:10.1093/brain/awac217 · Cited by 152 · see citing works
Self-citationLongitudinal patterns of leukoaraiosis and brain atrophy in symptomatic small vessel disease
Lambert, C., Benjamin, P., Zeestraten, E., Lawrence, A. J., Barrick, T. R., & Markus, H. S. (2016) · Brain · doi:10.1093/brain/aww009 · Cited by 150 · see citing works
“, 2013), dementia (Whitwell et al., 2007; Ossenkoppele et al., 2015) and parkinsonian syndromes (Price et al.”
BackgroundResultA multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap.
Badhwar, A., McFall, G., Sapkota, S., Black, S., Chertkow, H., Duchesne, S., Masellis, M., Li, L., Dixon, R., & Bellec, L. P. (2019) · Brain : a journal of neurology · doi:10.1101/19008615 · Cited by 146 · see citing works
“For example, the posterior atrophy subtype is evocative of the PCA Alzheimer's disease variant, and the language atrophy subtype of the lvPPA variant (Ossenkoppele et al., 2015).”
BackgroundDissecting the clinical heterogeneity of early-onset Alzheimer’s disease
Sirkis, D. W., Bonham, L. W., Johnson, T. P., La Joie, R., & Yokoyama, J. S. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01531-9 · Cited by 151 · see citing works
“These findings build on prior multimodal imaging analyses which illustrated unique changes in gray matter atrophy [150], white matter integrity [155], and functional connectivity [150, 156] corresponding to each syndrome’s unique neuroanatomic distribution superimposed upon a shared background of neurodegeneration in…”
La Joie, R., Bejanin, A., Fagan, A. M., Ayakta, N., Baker, S. L., Bourakova, V., Boxer, A. L., Cha, J., Karydas, A., Jerome, G., et al. (2018) · Neurology · doi:10.1212/wnl.0000000000004860 · Cited by 141 · see citing works
“This was done by comparing each patient’s warped SUVR image to an independent group of 53 PiB-negative cognitively normal individuals using a W-score procedure adjusting for age.(22,23) Abnormal voxels were defined as those with W > 2 (corresponding to the 97.”
MethodSelf-citationRabinovici, G. D., Knopman, D. S., Arbizu, J., Benzinger, T. L. S., Donohoe, K. J., Hansson, O., Herscovitch, P., Kuo, P. H., Lingler, J. H., Minoshima, S., et al. (2025) · Journal of Nuclear Medicine · doi:10.2967/jnumed.124.268756 · Cited by 82 · see citing works
“Furthermore, variability in tau PET retention patterns closely mirrors the variability seen in neurodegeneration patterns (via MRI or 18 F-FDG PET) in young-onset AD ( 158,163,164 ).”
Self-citationParker, T. D., Slattery, C. F., Zhang, J., Nicholas, J. M., Paterson, R. W., Foulkes, A. J. M., Malone, I. B., Thomas, D. L., Modat, M., Cash, D. M., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24056 · Cited by 122 · see citing works
Rabinovici, G. D., Knopman, D. S., Arbizu, J., Benzinger, T. L. S., Donohoe, K. J., Hansson, O., Herscovitch, P., Kuo, P. H., Lingler, J. H., Minoshima, S., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14338 · Cited by 151 · see citing works
Self-citationThe morphology of the human cerebrovascular system
Bernier, M., Cunnane, S. C., & Whittingstall, K. (2018) · Human Brain Mapping · doi:10.1002/hbm.24337 · Cited by 123 · see citing works
“It is well documented that acute impairment of the cerebral arteries can cause collateral damage (Ossenkoppele et al., 2015) and that venous atrophy may play an important role in the early stages of a number of neurological disorders (Gorelick, Counts, & Nyenhuis, 2016; Kaufman, Milstein, Kaufman,…”
BackgroundDistinct tau PET patterns in atrophy‐defined subtypes of Alzheimer's disease
Ossenkoppele, R., Lyoo, C. H., Sudre, C. H., van Westen, D., Cho, H., Ryu, Y. H., Choi, J. Y., Smith, R. A., Strandberg, O. T., Palmqvist, S., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.08.201 · Cited by 119 · see citing works
“R), which is in line with the distribution of neurofibrillary tangle pathology found in postmortem studies [5], their often atypical “nonamnestic” disease presentation [23], and the lower frequency of APOE ε4positivity [18].”
Self-citationPetersen, C., Nolan, A., Resende, E. D. P. F., Miller, Z., Ehrenberg, A. J., Gorno‐Tempini, M. L., Rosen, H. J., Kramer, J. H., Spina, S., Rabinovici, G. D., et al. (2019) · Acta Neuropathologica · doi:10.1007/s00401-019-02036-6 · Cited by 125 · see citing works
Self-citationAβ-amyloid and Tau Imaging in Dementia
Villemagne, V. L., Doré, V., Bourgeat, P., Burnham, S. C., Laws, S., Salvado, O., Masters, C. L., & Rowe, C. C. (2017) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2016.09.006 · Cited by 110 · see citing works
Joie, R. L., Visani, A. V., Lesman‐Segev, O. H., Baker, S. L., Edwards, L., Iaccarino, L., Soleimani‐Meigooni, D. N., Mellinger, T. J., Janabi, M., Miller, Z., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000011270 · Cited by 130 · see citing works
Self-citationNetwork localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer’s disease
Tetreault, A. M., Phan, T. X., Orlando, D., Lyu, I., Kang, H., Landman, B. A., Darby, R. R., & Initiative, O. B. O. A. D. N. (2020) · Brain · doi:10.1093/brain/awaa058 · Cited by 115 · see citing works
Gordon, B. A., Blazey, T., Su, Y., Fagan, A. M., Holtzman, D. M., Morris, J. C., & Benzinger, T. L. S. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2016.2642 · Cited by 105 · see citing works
ApoE influences regional white-matter axonal density loss in Alzheimer's disease
Slattery, C. F., Zhang, J., Paterson, R. W., Foulkes, A. J. M., Carton, A., Macpherson, K., Mancini, L., Thomas, D. L., Modat, M., Toussaint, N., et al. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.04.021 · Cited by 102 · see citing works
“Introduction (Ossenkoppele et al., 2015b).”
Mormino, E. C., & Papp, K. V. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-179928 · Cited by 117 · see citing works
Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer’s disease
Strom, A., Iaccarino, L., Edwards, L., Lesman-Segev, O. H., Soleimani-Meigooni, D. N., Pham, J., Baker, S. L., Landau, S. M., Jagust, W. J., Miller, B. L., et al. (2022) · Brain · doi:10.1093/brain/awab294 · Cited by 91 · see citing works
Self-citationWeise, C. M., Chen, K., Chen, Y., Kuang, X., Savage, C. R., & Reiman, E. M. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.07.016 · Cited by 96 · see citing works
“Of note though, other focal variants such as the posterior cortical atrophy exist, that do not present with obvious lateralized pathological hallmarks (Ossenkoppele et al. 2015).”
BackgroundStaffaroni, A., Elahi, F., McDermott, D., Marton, K., Karageorgiou, E., Sacco, S., Paoletti, M., Caverzasi, E., Hess, C., Rosen, H., et al. (2017) · Seminars in Neurology · doi:10.1055/s-0037-1608808 · Cited by 91 · see citing works
“5 Furthermore,thepresenceofADpathologydoesnot meanthatcognitivede fi citsaredetected,asaboutone-thirdof cognitively nonimpaired people at around age 75, and half of those around age 85, have in vivo markers [amyloid positron emission tomography (PET) scan] of underlying AD pathology.”
Self-citationGenetic data and cognitively defined late-onset Alzheimer’s disease subgroups
EPAD Study Group, Mukherjee, S., Investigators from ACT, Investigators from ROS, Investigators from MAP, Investigators from ADNI, Mez, J. B., Trittschuh, E. H., Saykin, A. J., Gibbons, L. E., et al. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0298-8 · Cited by 89 · see citing works
Longitudinal neuroimaging biomarkers differ across Alzheimer’s disease phenotypes
Sintini, I., Graff‐Radford, J., Senjem, M. L., Schwarz, C. G., Machulda, M. M., Martin, P. R., Jones, D. T., Boeve, B. F., Knopman, D. S., Kantarci, K., et al. (2020) · Brain · doi:10.1093/brain/awaa155 · Cited by 94 · see citing works
“The effect of age in the cognitively unimpaired group was regressed out of the Alzheimer’s disease participant’s images using SPM12, similar to a previous study (Ossenkoppele et al., 2015).”
BackgroundMethodInfluentialLatif-Hernandez, A., Shah, D., Craessaerts, K., Saido, T., Saito, T., De Strooper, B., Van der Linden, A., & D’Hooge, R. (2019) · Behavioural Brain Research · doi:10.1016/j.bbr.2017.11.017 · Cited by 92 · see citing works
Longitudinal neuroanatomical and cognitive progression of posterior cortical atrophy
Firth, N. C., Primativo, S., Marinescu, R. V., Shakespeare, T. J., Gonzalez, A. S., Lehmann, M., Carton, A. M., Ocal, D., Pavisic, I. M., Paterson, R. W., et al. (2019) · Brain · doi:10.1093/brain/awz136 · Cited by 83 · see citing works
Self-citationCognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts
Scheltens, N. M. E., Tijms, B. M., Koene, T., Barkhof, F., Teunissen, C. E., Wolfsgruber, S., Wagner, M., Kornhuber, J., Peters, O., Cohn‐Sheehy, B. I., et al. (2017) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2017.03.002 · Cited by 82 · see citing works
“deposition, cerebrospinal fluid biomarker concentrations, and pathological findings).[6-10] However,”
BackgroundSelf-citationLi, Y., Wang, X., Li, Y., Sun, Y., Sheng, C., Li, H., Li, X., Yu, Y., Chen, G., Hu, X., et al. (2016) · Neural Plasticity · doi:10.1155/2016/4680972 · Cited by 95 · see citing works
“Interestingly, a recent study on atrophy patterns of various phenotypes of AD showed the atrophy in the visual network to be dominant in the AD phenotype with posterior cortical atrophy [64].”
BackgroundIndividual differences in socioemotional sensitivity are an index of salience network function
Toller, G., Brown, J. A., Sollberger, M. A., Shdo, S. M., Bouvet, L., Sukhanov, P., Seeley, W. W., Miller, B. L., & Rankin, K. P. (2018) · Cortex · doi:10.1016/j.cortex.2018.02.012 · Cited by 86 · see citing works
Self-citationNeocortical origin and progression of gray matter atrophy in nonamnestic Alzheimer's disease
Phillips, J. S., Da Re, F., Dratch, L., Xie, S. X., Irwin, D. J., McMillan, C. T., Vaishnavi, S. N., Ferrarese, C., Lee, E. B., Shaw, L. M., et al. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.11.008 · Cited by 74 · see citing works
“In contrast, one recent study of AD patients with behavioral and dysexecutive presentations (Ossenkoppele et al., 2015b) found that each of these groups exhibited atrophy primarily in posterior temporal and parietal cortices (although the combined behavioral/dysexecutive group had prefrontal…”
InfluentialMattsson, N., Ossenkoppele, R., Smith, R. A., Strandberg, O. T., Ohlsson, T. G., Jögi, J., Palmqvist, S., Stomrud, E., & Hansson, O. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0403-x · Cited by 87 · see citing works
Self-citationTaipa, R. J. F., Ferreira, V., Brochado, P., Robinson, A., Reis, I., Marques, F., Mann, D. M. A., Pires, M. M., & Sousa, N. (2017) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12445 · Cited by 79 · see citing works
A neuroimaging approach to capture cognitive reserve: Application to Alzheimer's disease
van Loenhoud, A. C., Wink, A. M., Groot, C., Verfaillie, S. C. J., Twisk, J. W. R., Barkhof, F., van Berckel, B. N. M., Scheltens, P., van der Flier, W. M., & Ossenkoppele, R. (2017) · Human Brain Mapping · doi:10.1002/hbm.23695 · Cited by 75 · see citing works
“that this effect would be most prominent in AD specific temporoparietal brain regions (Frisoni et al., 2007; Karas et al., 2004; Ossenkoppele et al., 2015; Ridgway et al., 2012).”
BackgroundMethodSelf-citationDetecting frontotemporal dementia syndromes using MRI biomarkers
Bruun, M., Koikkalainen, J., Rhodius-Meester, H., Baroni, M., Gjerum, L., van Gils, M., Soininen, H., Remes, A., Hartikainen, P., Waldemar, G., et al. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.101711 · Cited by 66 · see citing works
Self-citationImaging and Molecular Mechanisms of Alzheimer’s Disease: A Review
Femminella, G. D., Thayanandan, T., Calsolaro, V., Komici, K., Rengo, G., Corbi, G., & Ferrara, N. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19123702 · Cited by 68 · see citing works
Medial Temporal Lobe Disconnection and Hyperexcitability Across Alzheimer’s Disease Stages
Pasquini, L., Rahmani, F., Balajoo, S. M., Joie, R. L., Zarei, M., Sorg, C., Drzezga, A. E., & Tahmasian, M. (2019) · Journal of Alzheimer s Disease Reports · doi:10.3233/adr-190121 · Cited by 79 · see citing works
“Most importantly, our model needs to be adapted to other clinical phenotypes, such as non-amnestic manifestations of AD, including posterior cortical atrophy and logopenic primary progressive aphasias [66].”
BackgroundMethodVisuospatial Functioning in the Primary Progressive Aphasias
Watson, C., Possin, K., Allen, I., Hubbard, H., Meyer, M., Welch, A. E., Rabinovici, G., Rosen, H., Rankin, K. P., Miller, Z., et al. (2017) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617717000984 · Cited by 59 · see citing works
“(2016) but extends the finding to include the domain of visual delayed recall; a finding that may relate to Alzheimer’s disease targeting medial temporal lobe structures (Ossenkoppele et al., 2015).”
Self-citationFirth, N. C., Primativo, S., Brotherhood, E., Young, A. L., Yong, K. X. X., Crutch, S. J., Alexander, D. C., & Oxtoby, N. P. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12083 · Cited by 64 · see citing works
den Haan, J., Csinscik, L., Parker, T., Paterson, R., Slattery, C., Foulkes, A. J. M., Bouwman, F., Verbraak, F., Scheltens, P., Peto, T., et al. (2019) · Alzheimer's Research & Therapy · doi:10.1186/s13195-019-0516-x · Cited by 56
Self-citationLongitudinal brain atrophy and CSF biomarkers in early-onset Alzheimer’s disease
Contador, J., Pérez‐Millan, A., Tort‐Merino, A., Balasa, M., Falgàs, N., Olives, J., Castellví, M., Borrego‐Écija, S., Bosch, B., Fernández‐Villullas, G., et al. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102804 · Cited by 62 · see citing works
“…studies using magnetic resonance imaging (MRI) reveal a pattern of widespread atrophy in EOAD particularly marked in parietal areas, whereas in LOAD, atrophy is restricted to temporal regions (Aziz et al., 2017; Harper et al., 2017; M ¨ oller et al., 2013; Ossenkoppele et al., 2015a).”
InfluentialTopographic staging of tau positron emission tomography images
Schwarz, A. J., Shcherbinin, S., Slieker, L. J., Risacher, S. L., Charil, A., Irizarry, M. C., Fleisher, A., Southekal, S. S., Joshi, A. D., Devous, M. D., et al. (2018) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2018.01.006 · Cited by 62 · see citing works
Self-citationMolecular properties underlying regional vulnerability to Alzheimer’s disease pathology
Grothe, M. J., Sepulcre, J., Gonzalez-Escamilla, G., Jelistratova, I., Schöll, M., Hansson, O., Teipel, S. J., & Initiative, A. D. N. (2018) · Brain · doi:10.1093/brain/awy189 · Cited by 142 · see citing works
Tort‐Merino, A., Falgàs, N., Allen, I. E., Balasa, M., Olives, J., Contador, J., Castellví, M., Juncà‐Parella, J., Guillén, N., Borrego‐Écija, S., et al. (2022) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51689 · Cited by 55 · see citing works
Timmers, T., Ossenkoppele, R., Wolters, E. E., Verfaillie, S. C. J., Visser, D., Golla, S. S. V., Barkhof, F., Scheltens, P., Boellaard, R., van der Flier, W. M., et al. (2019) · Alzheimer s Research & Therapy · doi:10.1186/s13195-019-0510-3 · Cited by 50 · see citing works
Self-citationDiagnosis and Management of Posterior Cortical Atrophy
Yong, K. X. X., Graff-Radford, J., Ahmed, S., Chapleau, M., Ossenkoppele, R., Putcha, D., Rabinovici, G. D., Suarez-Gonzalez, A., Schott, J. M., Crutch, S., et al. (2023) · Current Treatment Options in Neurology · doi:10.1007/s11940-022-00745-0 · Cited by 51 · see citing works
Self-citationOstrand, R., & Gunstad, J. (2021) · Journal of Geriatric Psychiatry and Neurology · doi:10.1177/0891988720933358 · Cited by 49 · see citing works
Ramanan, S., Irish, M., Patterson, K. E., Rowe, J. B., Gorno‐Tempini, M. L., & Ralph, M. A. L. (2022) · Brain · doi:10.1093/brain/awac208 · Cited by 52 · see citing works
“cortical neurodegenerative syndromes, many of which share Alzheimer’s disease pathology.(23,92,153,154) Shifting the focus to re-”
BackgroundSelf-citationLongitudinal progression of grey matter atrophy in non-amnestic Alzheimer’s disease
Phillips, J. S., Re, F. D., Irwin, D. J., McMillan, C. T., Vaishnavi, S., Xie, S. X., Lee, E. B., Cook, P. A., Gee, J. C., Shaw, L. M. J., et al. (2019) · Brain · doi:10.1093/brain/awz091 · Cited by 48 · see citing works
Olney, N. T., Ong, E., Goh, S. M., Bajorek, L., Dever, R., Staffaroni, A. M., Cobigo, Y., Bock, M., Chiang, K., Ljubenkov, P., et al. (2020) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.08.196 · Cited by 46 · see citing works
“Volume loss at each voxel was quantified as a w-score, which represents the gray matter content at that voxel as the number of standard deviations away from the expected mean for a cognitively normal reference group after accounting for age, total intracranial volume, and scanner platform [16].”
Self-citationEvaluation of a visual interpretation method for tau‐PET with 18 F‐flortaucipir
Sonni, I., Lesman‐Segev, O. H., Baker, S. L., Iaccarino, L., Korman, D., Rabinovici, G. D., Jagust, W. J., Landau, S. M., Joie, R. L., & Initiative, A. D. N. (2020) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12133 · Cited by 42 · see citing works
Self-citationCausal structural covariance network revealing atrophy progression in Alzheimer's disease continuum
Zhao, Q., Chen, F., Lu, J., Lv, P., Li, W., Liang, X., Wang, M., Wang, Z., Zhang, X., Zhang, B., et al. (2021) · Human Brain Mapping · doi:10.1002/hbm.25531 · Cited by 52 · see citing works
“Similarly, the PCC/precuneus, as a hub region of the default mode network, has also been identified as an AD-related region (Franzmeier et al., 2017; Grothe et al., 2016; Ossenkoppele et al., 2015).”
Structural, Microstructural, and Metabolic Alterations in Primary Progressive Aphasia Variants
Routier, A., Habert, M., Bertrand, A., Kas, A., Sundqvist, M., Mertz, J., David, P.-M., Bertin, H., Belliard, S., Pasquier, F., et al. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00766 · Cited by 47 · see citing works
“Various neuroimaging studies have demonstrated distinct atrophy (T1 MRI), hypometabolic (FDG PET) and white matter (WM) (di↵usion MRI) alterations in PPA variants [Galantucci et al., 2011; Acosta-Cabronero et al., 2011; Ossenkoppele et al., 2015; Matias-Guiu et al., 2015; Mesulam et al., 2015; Krishnan et al., 2017].”
BackgroundDementia ConnEEGtome: towards multicentric harmonization of EEG connectivity in neurodegeneration
Prado, P., Birba, A., Cruzat, J., Santamaría-García, H., Parra, M., Moguilner, S., Tagliazucchi, E., & Ibáñez, A. (2022) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2021.12.008 · Cited by 43 · see citing works
“This method has been applied to assess neurodegenerative diseases, where correlation of parameters with clinical features has been established (La Joie et al., 2012; Jack et al., 1997; O'Brien and Dyck, 1995; Ossenkoppele et al., 2015).”
MethodBreakdown of specific functional brain networks in clinical variants of Alzheimer’s disease
Pini, L., Wennberg, A. M. V., Salvalaggio, A., Vallesi, A., Pievani, M., & Corbetta, M. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101482 · Cited by 48 · see citing works
Iaccarino, L., Joie, R. L., Edwards, L., Strom, A., Schonhaut, D. R., Ossenkoppele, R., Pham, J. Q., Mellinger, T. J., Janabi, M., Baker, S. L., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa184 · Cited by 55 · see citing works
“W-scores distribution is analogous to Z-scores distribution and can thus be evaluated considering properties of the Gaussian curve (La Joie et al. 2012; Ossenkoppele et al. 2015; van Loenhoud et al. 2017).”
BackgroundMethodSelf-citationCoelho, D. S., Schwartz, S., Merino, M. M., Hauert, B., Topfel, B., Tièche, C., Rhiner, C., & Moreno, E. (2018) · bioRxiv · doi:10.1101/468868 · Cited by 44
Clinical phenotype, atrophy, and small vessel disease in APOE ε2 carriers with Alzheimer disease
Groot, C., Sudre, C. H., Barkhof, F., Teunissen, C. E., van Berckel, B. N. M., Seo, S. W., Sebastien Ourselin, A., Scheltens, P., Cardoso, M. J., van der Flier, W. M., et al. (2018) · Neurology · doi:10.1212/wnl.0000000000006503 · Cited by 53 · see citing works
Self-citationNeuroinflammation is increased in the parietal cortex of atypical Alzheimer’s disease
Boon, B. D. C., Hoozemans, J. J. M., Lopuhaä, B. V., Eigenhuis, K. N., Scheltens, P., Kamphorst, W., Rozemüller, A. J. M., & Bouwman, F. H. (2018) · Journal of Neuroinflammation · doi:10.1186/s12974-018-1180-y · Cited by 47 · see citing works
“In addition to clinical differences, these different AD variants show syndrome-specific atrophy patterns on MRI [6].”
BackgroundSelf-citationFunctional Connectivity of Ventral and Dorsal Visual Streams in Posterior Cortical Atrophy.
Migliaccio, R., Galléa, C., Kas, A., Perlbarg, V., Samri, D., Trotta, L., Michon, A., Lacomblez, L., Dubois, B., Lehéricy, S., et al. (2016) · Journal of Alzheimer's Disease · doi:10.3233/jad-150934 · Cited by 44 · see citing works
Tau‐Atrophy Variability Reveals Phenotypic Heterogeneity in Alzheimer's Disease
Das, S. R., Lyu, X., Duong, M. T., Xie, L., McCollum, L., de Florès, R., DiCalogero, M., Irwin, D. J., Dickerson, B. C., Nasrallah, I. M., et al. (2021) · Annals of Neurology · doi:10.1002/ana.26233 · Cited by 41 · see citing works
“9 For example, greater anterior temporal atrophy than expected for the amount of local NFT pathology may suggest concomitant limbic-predominant age-associated TDP-43 encephalopathy (LATE) 10,11 which often co-occurs with AD and primarily affects this region.”
Going round in circles—The Papez circuit in Alzheimer's disease
Forno, G., Lladó, A., & Hornberger, M. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15494 · Cited by 43 · see citing works
Individualized atrophy scores predict dementia onset in familial frontotemporal lobar degeneration
Staffaroni, A. M., Cobigo, Y., Goh, S. M., Kornak, J., Bajorek, L., Chiang, K., Appleby, B., Bove, J., Bordelon, Y., Brannelly, P., et al. (2020) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.04.007 · Cited by 40 · see citing works
Self-citationIaccarino, L., Sala, A., Caminiti, S. P., Presotto, L., Perani, D., & Initiative, F. T. A. D. N. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-190954 · Cited by 40 · see citing works
“To create maps of statistical deviation of brain volume from the reference control group, we estimated voxel-level atrophy W-score maps [48, 49].”
MethodDiagnosing the frontal variant of Alzheimer’s disease: a clinician’s yellow brick road
Sawyer, R. P., Rodriguez-Porcel, F., Hagen, M., Shatz, R., & Espay, A. J. (2017) · Journal of Clinical Movement Disorders · doi:10.1186/s40734-017-0052-4 · Cited by 40 · see citing works
“gulate, orbitofrontal cortex, middle and superior frontal gyrus [21, 33].”
BackgroundResultWirth, M., Bejanin, A., Joie, R. L., Arenaza‐Urquijo, E. M., Gonneaud, J., Landeau, B., Perrotin, A., Mézenge, F., Sayette, V. D. L., Desgranges, B., et al. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.10.023 · Cited by 37 · see citing works
Pasquini, L., Initiative, A. D. N., Benson, G. S., Grothe, M. J., Utz, L., Myers, N. E., Yakushev, I. Y., Grimmer, T., Scherr, M., & Sorg, C. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170096 · Cited by 37 · see citing works
“The spatial correspondence, together with consistent DMN alterations in AD for iFC [7–9], metabolism [1, 2], and structure [10], have led to the proposal of accumulating A (cid:2) pathology along DMN nodes, i.e., along functionally connected rather than spatially neighboring areas [6, 11–17].”
Neuroimaging in aging and neurologic diseases
Risacher, S. L., & Saykin, A. J. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-12-804766-8.00012-1 · Cited by 54 · see citing works
Musaeus, C. S., Frederiksen, K., Andersen, B. B., Høgh, P., Kidmose, P., Fabricius, M., Hribljan, M., Hemmsen, M. C., Rank, M. L., Waldemar, G., et al. (2023) · Neurobiology of Disease · doi:10.1002/alz.077308 · Cited by 34
“Combined with studies showing atrophy of the temporal lobes in the early stages of the disease (Ossenkoppele et al., 2015; Harper et al., 2017), this suggest that the epileptiform discharges are associated with neuropathological mechanisms in AD.”
Agosta, F., Mandić‐Stojmenović, G., Canu, E., Stojković, T., Imperiale, F., Caso, F., Stefanova, E. D., Copetti, M., Kostić, V., & Filippi, M. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.06.013 · Cited by 33 · see citing works
Can post-mortem MRI be used as a proxy for in vivo? A case study
Boon, B. D. C., Pouwels, P. J. W., Jonkman, L. E., Keijzer, M. J., Preziosa, P., van de Berg, W. D. J., Geurts, J. J. G., Scheltens, P., Barkhof, F., Rozemüller, A. J. M., et al. (2019) · Brain Communications · doi:10.1093/braincomms/fcz030 · Cited by 35 · see citing works
“MRI measures such as atrophy and white matter lesions often correlate with clinical outcome measurements of physical or cognitive disability (Ossenkoppele et al., 2015; Schippling, 2017).”
BackgroundSelf-citationAnterior dorsal attention network tau drives visual attention deficits in posterior cortical atrophy
Katsumi, Y., Putcha, D., Eckbo, R., Wong, B., Quimby, M., McGinnis, S. M., Touroutoglou, A., & Dickerson, B. C. (2022) · Brain · doi:10.1093/brain/awac245 · Cited by 35 · see citing works
Tau Subtypes of Alzheimer’s Disease Determined in vivo Using Flortaucipir PET Imaging
Charil, A., Shcherbinin, S., Southekal, S. S., Devous, M. D., Mintun, M. A., Murray, M. E., Miller, B. B., & Schwarz, A. J. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-190264 · Cited by 37 · see citing works
“…tau PET and brain atrophy patterns that preferentially affect brain regions corresponding to the clinical phenotype—the posterior, especially visual, cortices in the case of PPA and the left temporoparietal junction in the case of logopenic variant primary progressive aphasia [9, 26, 29].”
Self-citationFumagalli, G., Basilico, P., Arighi, A., Mercurio, M., Scarioni, M., Carandini, T., Colombi, A., Pietroboni, A. M., Sacchi, L., Conte, G., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102453 · Cited by 32 · see citing works
“These results are consistent with previous data (Agosta et al., 2018; Lehmann et al., 2012; Migliaccio et al., 2009; Ossenkoppele et al., 2015; Whitwell et al., 2007).”
ResultPutcha, D., Brickhouse, M. J., Touroutoglou, A., Collins, J. A., Quimby, M., Wong, B., Eldaief, M. C., Schultz, A. P., Fakhri, G. E., Johnson, K. A., et al. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101889 · Cited by 35 · see citing works
Tau and the fractionated default mode network in atypical Alzheimer’s disease
Putcha, D., Eckbo, R., Katsumi, Y., Dickerson, B. C., Touroutoglou, A., & Collins, J. A. (2022) · Brain Communications · doi:10.1093/braincomms/fcac055 · Cited by 39 · see citing works
Task-Free Functional Language Networks: Reproducibility and Clinical Application
Battistella, G., Borghesani, V., Henry, M. L., Shwe, W., Lauricella, M., Miller, Z., Deleon, J., Miller, B. L., Dronkers, N. F., Brambati, S. M., et al. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.1485-19.2019 · Cited by 34 · see citing works
“Obtained w-scores (e.g., applied in neurodegeneration by La Joie et al., 2012; Ossenkoppele et al., 2015) are interpreted like z-scores, with mean 0/SD 1.”
BackgroundSelf-citationSimilar pattern of atrophy in early‐ and late‐onset Alzheimer's disease
Eckerström, C., Klasson, N., Olsson, E., Selnes, P., Rolstad, S., & Wallin, A. (2018) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2018.02.001 · Cited by 26 · see citing works
“[29] have evaluated the early stages of three subtypes of AD, finding that while amnestic EOAD had atrophy of the hippocampal-posterior cingulate circuit, the language- and visual-variants had atrophy of these underlying circuits.”
Looking for measures of disease severity in the frontotemporal dementia continuum
Premi, E., Gualeni, V., Costa, P., Cosseddu, M., Gasparotti, R., Padovani, A., & Borroni, B. (2016) · Journal of Alzheimer’s Disease · doi:10.3233/jad-160178 · Cited by 26 · see citing works
“From this point of view, this correlation itself could be considered as a surrogate marker in testing other potentially useful clinical scales, as well as a tool to explore damage modulation in the different stages of the disease, even using a cross-sectional framework [10–12].”
Linking Personalized Brain Atrophy to Schizophrenia Network and Treatment Response
Ji, G., Zalesky, A., Wang, Y., He, K., Wang, L., Du, R., Sun, J., Bai, T., Chen, X., Tian, Y., et al. (2022) · Schizophrenia Bulletin · doi:10.1093/schbul/sbac162 · Cited by 27 · see citing works
Chen, Y., Wang, J., Cui, C., Su, Y., Jing, D., Wu, L., Liang, P., & Liang, Z. (2021) · Aging · doi:10.18632/aging.202580 · Cited by 46 · see citing works
“In general, during early clinical stages of AD, patterns of brain atrophy and glucose hypometabolism converge across wide regions of the DMN, supporting the central role of the DMN in AD [27].”
Effects of bilingualism on age at onset in two clinical Alzheimer's disease variants
de Leon, J., Grasso, S. M., Welch, A. E., Miller, Z., Shwe, W., Rabinovici, G. D., Miller, B. L., Henry, M. L., & Gorno‐Tempini, M. L. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12170 · Cited by 31 · see citing works
Self-citationWord retrieval across the biomarker-confirmed Alzheimer's disease syndromic spectrum
Putcha, D., Dickerson, B. C., Brickhouse, M. J., Johnson, K. A., Sperling, R. A., & Papp, K. V. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2020.107391 · Cited by 25 · see citing works
Distinct Brain Regions in Physiological and Pathological Brain Aging
Lee, J. S., Park, Y. H., Park, S., Yoon, U., Choe, Y. S., Cheon, B. K., Hahn, A., Cho, S. H., Kim, S. J., Kim, J. P., et al. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00147 · Cited by 27 · see citing works
Current Role for Biomarkers in Clinical Diagnosis of Alzheimer Disease and Frontotemporal Dementia
Sheikh‐Bahaei, N., Sajjadi, S. A., & Pierce, A. L. (2017) · Current Treatment Options in Neurology · doi:10.1007/s11940-017-0484-z · Cited by 25 · see citing works
“In atypical AD presentations such as posterior cortical atrophy (PCA), the volume loss is more prominent in posterior–superior parietal lobes involving posterior cingulate cortex (PCC), while atrophy in logopenic variant of PPA (lvPPA) mainly involves the posterolateral and inferior temporal and parietal lobes which c…”
Background
- Authors
- Ossenkoppele, R., Cohn‐Sheehy, B. I., La Joie, R., Vogel, J. W., Möller, C., Lehmann, M., van Berckel, B. N. M., Seeley, W. W., Pijnenburg, Y. A., Gorno‐Tempini, M. L., Kramer, J. H., Barkhof, F., Rosen, H. J., van der Flier, W. M., Jagust, W. J., Miller, B. L., Scheltens, P., & Rabinovici, G. D.
- Affiliations
- University of California, San Francisco (US)
- Helen Wills Neuroscience Institute, University of California Berkeley Berkeley California
- University of California, Berkeley (US)
- Amsterdam Neuroscience (NL)
- Gemeente Amsterdam (NL)
- Department of Neurology & Alzheimer Center Neuroscience Campus Amsterdam, VU University Medical Center Amsterdam The Netherlands
- ORCID
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2015-08-11
- Volume
- 36
- Issue
- 11
- Pages
- 4421-4437
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- PMC
- PMC4692964
- OpenAlex
- W1935126539
- Cited by
- 243
- References
- 70
- Citations by year
- 2026: 14 · 2025: 18 · 2024: 19 · 2023: 18 · 2022: 21 · 2021: 21 · 2020: 34 · 2019: 32 · 2018: 27 · 2017: 24 · 2016: 12 · 2015: 2 · 2014: 1
- FWCI
- 17.60
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Human Brain Mapping (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Marie Curie FP7 International Outgoing Fellowship (628812)
- The donors of [Alzheimer's Disease Research], a program of BrightFocus Foundation
- National Institute on Aging grants (R01-AG045611, P01-AG1792403, P50-AG023501, R01-AG034570)
- Tau Consortium
- Consortium for Frontotemporal Dementia Research
- John Douglas French Alzheimer's Foundation
- State of California Department of Health Services Alzheimer's Disease Research Centre of California (04-33516)
- Netherlands Initiative Brain and Cognition (NIHC), a part of the Netherlands Organization for Scientific Research (NWO) (056-13-001)
- Alzheimer Nederland and Stichting VUMC funds and Stichting Dioraphte
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- Alzheimer's disease, brain atrophy patterns, posterior cortical atrophy, logopenic variant primary progressive aphasia, posterior default mode network, language network, visual network, gray matter volume, Clinical Dementia Rating, early diagnosis, regional vulnerability
- MeSH terms
- Aged, Alzheimer Disease, Animals, Atrophy, Cerebral Cortex, Female, Humans, Male, Middle Aged, Nerve Net, Phenotype, Syndrome, Age of Onset, Aphasia, Primary Progressive
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