Browsing by Author "Ossenkoppele, Rik"
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Item Amyloid-associated increases in soluble tau relate to tau aggregation rates and cognitive decline in early Alzheimer’s disease(Springer Nature, 2022-11-04) Pichet Binette, Alexa; Franzmeier, Nicolai; Spotorno, Nicola; Ewers, Michael; Brendel, Matthias; Biel, Davina; Alzheimer’s Disease Neuroimaging Initiative; Strandberg, Olof; Janelidze, Shorena; Palmqvist, Sebastian; Mattsson-Carlgren, Niklas; Smith, Ruben; Stomrud, Erik; Ossenkoppele, Rik; Hansson, Oskar; Radiology and Imaging Sciences, School of MedicineFor optimal design of anti-amyloid-β (Aβ) and anti-tau clinical trials, we need to better understand the pathophysiological cascade of Aβ- and tau-related processes. Therefore, we set out to investigate how Aβ and soluble phosphorylated tau (p-tau) relate to the accumulation of tau aggregates assessed with PET and subsequent cognitive decline across the Alzheimer's disease (AD) continuum. Using human cross-sectional and longitudinal neuroimaging and cognitive assessment data, we show that in early stages of AD, increased concentration of soluble CSF p-tau is strongly associated with accumulation of insoluble tau aggregates across the brain, and CSF p-tau levels mediate the effect of Aβ on tau aggregation. Further, higher soluble p-tau concentrations are mainly related to faster accumulation of tau aggregates in the regions with strong functional connectivity to individual tau epicenters. In this early stage, higher soluble p-tau concentrations is associated with cognitive decline, which is mediated by faster increase of tau aggregates. In contrast, in AD dementia, when Aβ fibrils and soluble p-tau levels have plateaued, cognitive decline is related to the accumulation rate of insoluble tau aggregates. Our data suggest that therapeutic approaches reducing soluble p-tau levels might be most favorable in early AD, before widespread insoluble tau aggregates.Item Clinicopathological correlations in behavioural variant frontotemporal dementia(Oxford University Press, 2017-12-01) Perry, David C.; Brown, Jesse A.; Possin, Katherine L.; Datta, Samir; Trujillo, Andrew; Radke, Anneliese; Karydas, Anna; Kornak, John; Sias, Ana C.; Rabinovici, Gil D.; Gorno-Tempini, Maria Luisa; Boxer, Adam L.; May, Mary De; Rankin, Katherine P.; Sturm, Virginia E.; Lee, Suzee E.; Matthews, Brandy R.; Kao, Aimee W.; Vossel, Keith A.; Tartaglia, Maria Carmela; Miller, Zachary A.; Seo, Sang Won; Sidhu, Manu; Gaus, Stephanie E.; Nana, Alissa L.; Vargas, Jose Norberto S.; Hwang, Ji-Hye L.; Ossenkoppele, Rik; Brown, Alainna B.; Huang, Eric J.; Coppola, Giovanni; Rosen, Howard J.; Geschwind, Daniel; Trojanowski, John Q.; Grinberg, Lea T.; Kramer, Joel H.; Miller, Bruce L.; Seely, William W.; Neurology, School of MedicineAccurately predicting the underlying neuropathological diagnosis in patients with behavioural variant frontotemporal dementia (bvFTD) poses a daunting challenge for clinicians but will be critical for the success of disease-modifying therapies. We sought to improve pathological prediction by exploring clinicopathological correlations in a large bvFTD cohort. Among 438 patients in whom bvFTD was either the top or an alternative possible clinical diagnosis, 117 had available autopsy data, including 98 with a primary pathological diagnosis of frontotemporal lobar degeneration (FTLD), 15 with Alzheimer's disease, and four with amyotrophic lateral sclerosis who lacked neurodegenerative disease-related pathology outside of the motor system. Patients with FTLD were distributed between FTLD-tau (34 patients: 10 corticobasal degeneration, nine progressive supranuclear palsy, eight Pick's disease, three frontotemporal dementia with parkinsonism associated with chromosome 17, three unclassifiable tauopathy, and one argyrophilic grain disease); FTLD-TDP (55 patients: nine type A including one with motor neuron disease, 27 type B including 21 with motor neuron disease, eight type C with right temporal lobe presentations, and 11 unclassifiable including eight with motor neuron disease), FTLD-FUS (eight patients), and one patient with FTLD-ubiquitin proteasome system positive inclusions (FTLD-UPS) that stained negatively for tau, TDP-43, and FUS. Alzheimer's disease was uncommon (6%) among patients whose only top diagnosis during follow-up was bvFTD. Seventy-nine per cent of FTLD-tau, 86% of FTLD-TDP, and 88% of FTLD-FUS met at least 'possible' bvFTD diagnostic criteria at first presentation. The frequency of the six core bvFTD diagnostic features was similar in FTLD-tau and FTLD-TDP, suggesting that these features alone cannot be used to separate patients by major molecular class. Voxel-based morphometry revealed that nearly all pathological subgroups and even individual patients share atrophy in anterior cingulate, frontoinsula, striatum, and amygdala, indicating that degeneration of these regions is intimately linked to the behavioural syndrome produced by these diverse aetiologies. In addition to these unifying features, symptom profiles also differed among pathological subtypes, suggesting distinct anatomical vulnerabilities and informing a clinician's prediction of pathological diagnosis. Data-driven classification into one of the 10 most common pathological diagnoses was most accurate (up to 60.2%) when using a combination of known predictive factors (genetic mutations, motor features, or striking atrophy patterns) and the results of a discriminant function analysis that incorporated clinical, neuroimaging, and neuropsychological data.Item Cognitively defined Alzheimer's dementia subgroups have distinct atrophy patterns(Wiley, 2024) Crane, Paul K.; Groot, Colin; Ossenkoppele, Rik; Mukherjee, Shubhabrata; Choi, Seo-Eun; Lee, Michael; Scollard, Phoebe; Gibbons, Laura E.; Sanders, R. Elizabeth; Trittschuh, Emily; Saykin, Andrew J.; Mez, Jesse; Nakano, Connie; Mac Donald, Christine; Sohi, Harkirat; Alzheimer’s Disease Neuroimaging Initiative; Risacher, Shannon; Medicine, School of MedicineIntroduction: We sought to determine structural magnetic resonance imaging (MRI) characteristics across subgroups defined based on relative cognitive domain impairments using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and to compare cognitively defined to imaging-defined subgroups. Methods: We used data from 584 people with Alzheimer's disease (AD) (461 amyloid positive, 123 unknown amyloid status) and 118 amyloid-negative controls. We used voxel-based morphometry to compare gray matter volume (GMV) for each group compared to controls and to AD-Memory. Results: There was pronounced bilateral lower medial temporal lobe atrophy with relative cortical sparing for AD-Memory, lower left hemisphere GMV for AD-Language, anterior lower GMV for AD-Executive, and posterior lower GMV for AD-Visuospatial. Formal asymmetry comparisons showed substantially more asymmetry in the AD-Language group than any other group (p = 1.15 × 10-10 ). For overlap between imaging-defined and cognitively defined subgroups, AD-Memory matched up with an imaging-defined limbic predominant group. Discussion: MRI findings differ across cognitively defined AD subgroups.Item Correction: Diagnostic and prognostic performance to detect Alzheimer's disease and clinical progression of a novel assay for plasma p-tau217(BMC, 2022-06-13) Groot, Colin; Cicognola, Claudia; Bali, Divya; Triana‑Baltzer, Gallen; Dage, Jeffrey L.; Pontecorvo, Michael J.; Kolb, Hartmuth C.; Ossenkoppele, Rik; Janelidze, Shorena; Hansson, Oskar; Neurology, School of MedicineErratum for: Diagnostic and prognostic performance to detect Alzheimer's disease and clinical progression of a novel assay for plasma p-tau217. Groot C, Cicognola C, Bali D, Triana-Baltzer G, Dage JL, Pontecorvo MJ, Kolb HC, Ossenkoppele R, Janelidze S, Hansson O. Alzheimers Res Ther. 2022 May 14;14(1):67. doi: 10.1186/s13195-022-01005-8. PMID: 35568889Item Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis(Elsevier, 2024) Chapleau, Marianne; La Joie, Renaud; Yong, Keir; Agosta, Federica; Allen, Isabel Elaine; Apostolova, Liana; Best, John; Boon, Baayla D. C.; Crutch, Sebastian; Filippi, Massimo; Fumagalli, Giorgio Giulio; Galimberti, Daniela; Graff-Radford, Jonathan; Grinberg, Lea T.; Irwin, David J.; Josephs, Keith A.; Mendez, Mario F.; Mendez, Patricio Chrem; Migliaccio, Raffaella; Miller, Zachary A.; Montembeault, Maxime; Murray, Melissa E.; Nemes, Sára; Pelak, Victoria; Perani, Daniela; Phillips, Jeffrey; Pijnenburg, Yolande; Rogalski, Emily; Schott, Jonathan M.; Seeley, William; Sullivan, A. Campbell; Spina, Salvatore; Tanner, Jeremy; Walker, Jamie; Whitwell, Jennifer L.; Wolk, David A.; Ossenkoppele, Rik; Rabinovici, Gil D.; PCA International Work Group; Neurology, School of MedicineBackground: Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. Methods: We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. Findings: We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). Interpretation: These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity.Item Differential patterns of gray matter volumes and associated gene expression profiles in cognitively-defined Alzheimer's disease subgroups(Elsevier, 2021) Groot, Colin; Grothe, Michel J.; Mukherjee, Shubhabrata; Jelistratova, Irina; Jansen, Iris; van Loenhoud, Anna Catharina; Risacher, Shannon L.; Saykin, Andrew J.; Mac Donald, Christine L.; Mez, Jesse; Trittschuh, Emily H.; Gryglewski, Gregor; Lanzenberger, Rupert; Pijnenburg, Yolande A.L.; Barkhof, Frederik; Scheltens, Philip; van der Flier, Wiesje M.; Crane, Paul K.; Ossenkoppele, Rik; Radiology and Imaging Sciences, School of MedicineThe clinical presentation of Alzheimer's disease (AD) varies widely across individuals but the neurobiological mechanisms underlying this heterogeneity are largely unknown. Here, we compared regional gray matter (GM) volumes and associated gene expression profiles between cognitively-defined subgroups of amyloid-β positive individuals clinically diagnosed with AD dementia (age: 66 ± 7, 47% male, MMSE: 21 ± 5). All participants underwent neuropsychological assessment with tests covering memory, executive-functioning, language and visuospatial-functioning domains. Subgroup classification was achieved using a psychometric framework that assesses which cognitive domain shows substantial relative impairment compared to the intra-individual average across domains, which yielded the following subgroups in our sample; AD-Memory (n = 41), AD-Executive (n = 117), AD-Language (n = 33), AD-Visuospatial (n = 171). We performed voxel-wise contrasts of GM volumes derived from 3Tesla structural MRI between subgroups and controls (n = 127, age 58 ± 9, 42% male, MMSE 29 ± 1), and observed that differences in regional GM volumes compared to controls closely matched the respective cognitive profiles. Specifically, we detected lower medial temporal lobe GM volumes in AD-Memory, lower fronto-parietal GM volumes in AD-Executive, asymmetric GM volumes in the temporal lobe (left < right) in AD-Language, and lower GM volumes in posterior areas in AD-Visuospatial. In order to examine possible biological drivers of these differences in regional GM volumes, we correlated subgroup-specific regional GM volumes to brain-wide gene expression profiles based on a stereotactic characterization of the transcriptional architecture of the human brain as provided by the Allen human brain atlas. Gene-set enrichment analyses revealed that variations in regional expression of genes involved in processes like mitochondrial respiration and metabolism of proteins were associated with patterns of regional GM volume across multiple subgroups. Other gene expression vs GM volume-associations were only detected in particular subgroups, e.g., genes involved in the cell cycle for AD-Memory, specific sets of genes related to protein metabolism in AD-Language, and genes associated with modification of gene expression in AD-Visuospatial. We conclude that cognitively-defined AD subgroups show neurobiological differences, and distinct biological pathways may be involved in the emergence of these differences.Item Differential trajectories of hypometabolism across cognitively-defined Alzheimer’s disease subgroups(Elsevier, 2021) Groot, Colin; Risacher, Shannon L.; Chen, J.Q. Alida; Dicks, Ellen; Saykin, Andrew J.; MacDonald, Christine L.; Mez, Jesse; Trittschuh, Emily H.; Mukherjee, Shubhabrata; Barkhof, Frederik; Scheltens, Philip; van der Flier, Wiesje M.; Ossenkoppele, Rik; Crane, Paul K.; Radiology and Imaging Sciences, School of MedicineDisentangling biologically distinct subgroups of Alzheimer's disease (AD) may facilitate a deeper understanding of the neurobiology underlying clinical heterogeneity. We employed longitudinal [18F]FDG-PET standardized uptake value ratios (SUVRs) to map hypometabolism across cognitively-defined AD subgroups. Participants were 384 amyloid-positive individuals with an AD dementia diagnosis from ADNI who had a total of 1028 FDG-scans (mean time between first and last scan: 1.6 ± 1.8 years). These participants were categorized into subgroups on the basis of substantial impairment at time of dementia diagnosis in a specific cognitive domain relative to the average across domains. This approach resulted in groups of AD-Memory (n = 135), AD-Executive (n = 8), AD-Language (n = 22), AD-Visuospatial (n = 44), AD-Multiple Domains (n = 15) and AD-No Domains (for whom no domain showed substantial relative impairment; n = 160). Voxelwise contrasts against controls revealed that all AD-subgroups showed progressive hypometabolism compared to controls across temporoparietal regions at time of AD diagnosis. Voxelwise and regions-of-interest (ROI)-based linear mixed model analyses revealed there were also subgroup-specific hypometabolism patterns and trajectories. The AD-Memory group had more pronounced hypometabolism compared to all other groups in the medial temporal lobe and posterior cingulate, and faster decline in metabolism in the medial temporal lobe compared to AD-Visuospatial. The AD-Language group had pronounced lateral temporal hypometabolism compared to all other groups, and the pattern of metabolism was also more asymmetrical (left < right) than all other groups. The AD-Visuospatial group had faster decline in metabolism in parietal regions compared to all other groups, as well as faster decline in the precuneus compared to AD-Memory and AD-No Domains. Taken together, in addition to a common pattern, cognitively-defined subgroups of people with AD dementia show subgroup-specific hypometabolism patterns, as well as differences in trajectories of metabolism over time. These findings provide support to the notion that cognitively-defined subgroups are biologically distinct.Item Tau PET correlates with different Alzheimer’s disease‐related features compared to CSF and plasma p‐tau biomarkers(EMBO Press, 2021) Ossenkoppele, Rik; Reimand, Juhan; Smith, Ruben; Leuzy, Antoine; Strandberg, Olof; Palmqvist, Sebastian; Stomrud, Erik; Zetterberg, Henrik; Alzheimer’s Disease Neuroimaging Initiative; Scheltens, Philip; Dage, Jeffrey L.; Bouwman, Femke; Blennow, Kaj; Mattsson-Carlgren, Niklas; Janelidze, Shorena; Hansson, Oskar; Neurology, School of MedicinePET, CSF and plasma biomarkers of tau pathology may be differentially associated with Alzheimer's disease (AD)-related demographic, cognitive, genetic and neuroimaging markers. We examined 771 participants with normal cognition, mild cognitive impairment or dementia from BioFINDER-2 (n = 400) and ADNI (n = 371). All had tau-PET ([18 F]RO948 in BioFINDER-2, [18 F]flortaucipir in ADNI) and CSF p-tau181 biomarkers available. Plasma p-tau181 and plasma/CSF p-tau217 were available in BioFINDER-2 only. Concordance between PET, CSF and plasma tau biomarkers ranged between 66 and 95%. Across the whole group, ridge regression models showed that increased CSF and plasma p-tau181 and p-tau217 levels were independently of tau PET associated with higher age, and APOEɛ4-carriership and Aβ-positivity, while increased tau-PET signal in the temporal cortex was associated with worse cognitive performance and reduced cortical thickness. We conclude that biofluid and neuroimaging markers of tau pathology convey partly independent information, with CSF and plasma p-tau181 and p-tau217 levels being more tightly linked with early markers of AD (especially Aβ-pathology), while tau-PET shows the strongest associations with cognitive and neurodegenerative markers of disease progression.Item The prevalence of tau‐PET positivity in aging and dementia(Wiley, 2025-01-09) Coomans, Emma M.; Groot, Colin; Rowe, Christopher C.; Dore, Vincent; Villemagne, Victor L.; van de Giessen, Elsmarieke; van der Flier, Wiesje M.; Pijnenburg, Yolande A. L.; Visser, Pieter Jelle; den Braber, Anouk; Pontecorvo, Michael; Shcherbinin, Sergey; Kennedy, Ian A.; Jagust, William J.; Baker, Suzanne L.; Harrison, Theresa M.; Gispert, Juan Domingo; Shekari, Mahnaz; Minguillon, Carolina; Smith, Ruben; Mattsson-Carlgren, Niklas; Palmqvist, Sebastian; Strandberg, Olof; Stomrud, Erik; Malpetti, Maura; O'Brien, John T.; Rowe, James B.; Jäger, Elena; Bischof, Gérard N.; Drzezga, Alexander; Garibotto, Valentina; Frisoni, Giovanni; Peretti, Débora Elisa; Schöll, Michael; Skoog, Ingmar; Kern, Silke; Sperling, Reisa A.; Johnson, Keith A.; Risacher, Shannon L.; Saykin, Andrew J.; Carrillo, Maria C.; Dickerson, Brad C.; Apostolova, Liana G.; Barthel, Henryk; Rullmann, Michael; Messerschmidt, Konstantin; Vandenberghe, Rik; Van Laere, Koen; Spruyt, Laure; Franzmeier, Nicolai; Brendel, Matthias; Gnörich, Johannes; Benzinger, Tammie L. S.; Lagarde, Julien; Sarazin, Marie; Bottlaender, Michel; Villeneuve, Sylvia; Poirier, Judes; Seo, Sang Won; Gu, Yuna; Kim, Jun Pyo; Mormino, Elizabeth; Young, Christina B.; Vossler, Hillary; Rosa-Neto, Pedro; Therriault, Joseph; Rahmouni, Nesrine; Coath, William; Cash, David M.; Schott, Jonathan M.; Rabinovici, Gil D.; La Joie, Renaud; Rosen, Howard J.; Johnson, Sterling C.; Christian, Bradley T.; Betthauser, Tobey J.; Hansson, Oskar; Ossenkoppele, Rik; Radiology and Imaging Sciences, School of MedicineBackground Tau‐PET imaging allows in‐vivo detection of neurofibrillary tangles. One tau‐PET tracer (i.e., [18F]flortaucipir) has received FDA‐approval for clinical use, and multiple other tau‐PET tracers have been implemented into clinical trials for participant selection and/or as a primary or secondary outcome measure. To optimize future use of tau‐PET, it is essential to understand how demographic, clinical and genetic factors affect tau‐PET‐positivity rates. Method This large‐scale multi‐center study includes 9713 participants from 35 cohorts worldwide who underwent tau‐PET with [18F]flortaucipir (n = 6420), [18F]RO948 (n = 1999), [18F]MK6240 (n = 878) or [18F]PI2620 (n = 416) (Table‐1). We analyzed individual‐level tau‐PET SUVR data using a cerebellar reference region that were processed either centrally (n = 3855) or by each cohort (n = 5858). We computed cohort‐specific SUVR thresholds based on the mean + 2 standard deviations in a temporal meta‐region of amyloid‐negative cognitively normal (CN) individuals aged >50. Logistic generalized estimating equations were used to estimate tau‐PET‐positivity probabilities, using an exchangeable correlation structure to account for within‐cohort correlations. Analyses were performed with (interactions between) age, amyloid‐status, and APOE‐e4 carriership as independent variables, stratified for syndrome diagnosis. Result The study included 5962 CN participants (7.5% tau‐PET‐positive), 1683 participants with mild cognitive impairment (MCI, 33.8% tau‐PET‐positive) and 2068 participants with a clinical diagnosis of dementia (62.1% tau‐PET‐positive) (Figure‐1). From age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 1.2% [95% CI: 0.9%‐1.5%] to 3.7% [2.3%‐5.1%] among CN amyloid‐negative participants; and from 16.4% [10.8%‐22.1%] to 20.5% [18.8%‐22.2%] among CN amyloid‐positive participants. Among amyloid‐negative participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 3.5% [1.6%‐5.3%] to 11.8% [7.1%‐16.5%] and from 12.6% [4.5%‐20.7%] to 15.9% [6.7%‐25.1%] respectively. In contrast, among amyloid‐positive participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity decreased from 66.5% [57.0%‐76.0%] to 48.3% [42.9%‐53.8%] and from 92.3% [88.7%‐95.9%] to 73.4% [67.5%‐79.3%] respectively. APOE‐e4 status primarily modulated the association of age with tau‐PET‐positivity estimates among CN and MCI amyloid‐positive participants (Figure‐2). Conclusion This large‐scale multi‐cohort study provides robust prevalence estimates of tau‐PET‐positivity, which can aid the interpretation of tau‐PET in the clinic and inform clinical trial designs.