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Radford, Jonathan Graff

Mayo Clinic

Mayo Clinic

Citations 46

Caregiver Reports of Lucid Episodes in Alzheimer’s Dementia and Lewy Body Dementias
Bangerter, Lauren R. , Kim, Kyungmin , Liu, Yin, Radford, Jonathan Graff, Liu, Yin, Lapid, Maria I. , Griffin, Joan M.

Journal of Geriatric Psychiatry and Neurology | July 2, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1177/08919887261464594 Get It

Purpose of Research Lucidity is the transient recovery of abilities and communication that were seemingly lost among people living with dementia (PLWD). This study describes lucid episodes reported by Alzheimer’s dementia (AD) and Lewy Body Dementias (LBD) caregivers. We analyzed survey data from 212 current AD ( n = 191) and LBD caregivers who reported the frequency, duration, and characteristics of 653 lucid episodes witnessed in the past month. Major Findings Most AD caregivers (67%) and LBD caregivers (81%) witnessed a lucid episode within the past month. LBD caregivers reported lucid episodes with greater changes in awareness and communication, compared to AD caregivers. LBD caregivers reported longer lucid episodes and that the PLWD knew about their change in lucidity, compared to AD caregivers. Conclusions Findings suggest that differences in lucid episode intensity, timing, and meta-awareness between AD and LBD are possible and may inform care strategies for PLWD.
The Binding Patterns of Neurofibrillary Tangles Observed With High‐Resolution Autoradiography of 18 F MK 6240 and 18 F AV1451 Are Comparable and Predomina
Ghatamaneni, Sujala, Hruska, Courtney, Shin, Ian, Lee, Jeyeon, Fang, Ping , Wood, Ashley C., Constantopoulos, Eleni , Reichard, R. Ross, Jones, David T., Schwarz, Christopher G, Radford, Jonathan Graff, Knopman, David S., Jack, Clifford R., Petersen, Ronald, Dickson, Dennis W., Murray, Melissa E., Lowe, VJ, Bruinsma, Tyler J. , Min, Hoon-Ki Paul , Moloney, Christina M. , Wood, Ashley C., Reichard, R. Ross , Jones, David T. , Schwarz, Christopher G. , Knopman, David S. , Jack, Clifford R. , Petersen, Ronald, Dickson, Dennis W. , Murray, Melissa E.

Alzheimer's & Dementia | January 10, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_106581 Get It

Abstract Background An intense search is underway for tau PET tracers with enhanced capability to visualize tau aggregates. Research indicates that [18F] AV1451 and [18F]MK 6240 exhibit comparable binding properties in terms of spatial distribution and severity of tau aggregates, as observed both in‐vivo and in‐vitro. This study focused on head‐to‐head pathological comparison of both the tracers binding specificity to tangle maturity levels (pretangles, mature tangles and ghost tangles) of tau aggregates as seen on autoradiography as compared to CP‐13 (early tangle maturity marker) and PHF‐1(middling tangle maturity marker) immunohistochemical (IHC) stains in Alzheimer's disease (AD) and non‐AD tauopathies. Method Study participants included included those with AD and non‐AD tauopathies. Analyses were performed on serial 5um formalin fixed paraffin embedded postmortem human brain sections acquired from Mayo clinic brain bank. Visual assessment of colocalization with IHC as well as quantitative analyses were used. IHC sections were incubated with antibodies CP‐13 (recognizing early tangle maturity) and PHF‐1 (recognizing middling tangle maturity). Result A total of 38 participants were examined. The participants included a spectrum from normal to AD, including mild cognitive impairment (MCI) and atypical AD. Participants with N279K (4R), P301L (4R), and R406W MAPT mutations (3R+4R) were included as well. Both the tracers showed strong binding to AD tau aggregates and no or minimal binding to non‐AD tauopathies. Generally, early tangle maturity tau accumulation participants had more tau demonstrated with CP‐13 than PHF‐1 and both the tracers [18F]MK 6240 and [18F]AV 1451 binding are well correlated with the PHF‐1 staining suggesting the preference for middling tangle level and minimal to early tangles. Conclusion The emergence and validation of these new tau PET tracers have opened new opportunities for the development of more accurate diagnostic and management tools for AD. In our study on post‐mortem sections, [ 18 F]MK‐6240 and [ 18 F]Flortaucipir showed similar binding profiles with preference to middling tangle maturity levels.
Association between temporal lobe cortical NODDI measures and plasma biomarkers
Reid, Robert I., Weigand, Stephen D. , Cogswell, Petrice M, Vemuri, Prashanthi, Knopman, David S., Radford, Jonathan Graff, Petersen, Ronald, Jack, Clifford R., Pillai, Jay J. , Reid, Robert I. , Cogswell, Petrice M. , Vemuri, Prashanthi , Algeciras‐Schimnich, Alicia , Knopman, David S. , Petersen, Ronald C. , Jack, Clifford R.

Alzheimer's & Dementia | January 9, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_105668 Get It

Abstract Background Plasma neurofilament light chains (NfL) and glial fibrillary acidic protein (GFAP) are blood‐based biomarkers of axonal injury and astrocytic activation, respectively, that are elevated in those with Alzheimer's disease (AD) and mild cognitive impairment (MCI) relative to cognitively unimpaired (CU) individuals. Neurite orientation dispersion and density imaging (NODDI) is a multishell diffusion MRI method capable of evaluating tissue microstructure at the axonal and dendritic level. We evaluated associations between temporal cortex orientation dispersion index (ODI), neurite density index (NDI) and isotropic volume fraction (ISOVF) and plasma NfL and GFAP concentrations. Method We included Mayo Clinic Study of Aging (MCSA) participants (ages 60‐95 years) with diagnoses or CU ( n = 356) or MCI ( n = 60), and Alzheimer's Dementia Research Center (ADRC) participants with dementia ( n = 51). NODDI imaging was obtained on a 3T Siemens Prisma scanner with 2 mm isotropic resolution. NfL and GFAP were measured using the Simoa® Neurology 4‐Plex E Advantage kit. We fit separate linear regression models within each MCALT_ADIR122 cortical ROI with regional NODDI as the primary predictor and log‐transformed plasma concentration as the outcome. Models were adjusted for age, sex, BMI, cortical thickness (or hippocampal & amygdalar volume) and total intracranial volume. Result The Table displays demographic data. Figures 1 and 2 show the relationship of NDI and ISOVF measures to plasma NfL concentrations across participants in individual ROIs (similar findings were noted with GFAP). A significant inverse relationship between NfL concentrations and NDI was observed in hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus as well as all temporal neocortical regions except the superior temporal gyrus ( p <0.001) (Figure 1), whereas higher NfL concentrations were associated with higher ISOVF in all regions ( p <0.001) (Figure 2). Fewer significant associations were also seen with ODI. After adjusting for age, cortical thickness/volume and other confounds, significant associations with NDI remain, particularly in hippocampal and amygdalar regions. Conclusion NODDI‐derived measures (NDI and ISOVF) within the temporal lobe cortical regions demonstrate significant associations with plasma biomarkers of axonal and astrocytic dysfunction that are elevated during cognitive decline. This association provides preliminary validation of the utility of NODDI in assessing cortical microstructural changes associated with cognitive decline.
Heterogeneous tau patterns in atypical AD are explained by connectivity‐associated tau progression
Bruin, Hannah de , Groot, Colin , (ADNI), Alzheimer's Disease Neuroimaging Initiative, Barthel, Henryk, Bischof, Gérard N. , Boon, Baayla D.C., Brendel, Matthias, Cash, David M, Day, Gregory S, Dickerson, Brad C., Dyck, Christopher H van, Flier, Wiesje M. van der, Fredericks, Carolyn , Fryer, Tim D. , Giessen, Elsmarieke van de, Gordon, Brian A., Radford, Jonathan Graff, Hansson, Oskar H., Höglinger, Günter U, Hönig, Merle C., Irwin, David J., Jones, P Simon, Josephs, Keith A., Katsumi, Yuta , Lee, Eddie B., Xiong, Chengjie , McGinnis, Scott M., Mecca, Adam P. , O'Brien, John T, O'Dell, Ryan S, Rabinovici, Gil D., Rahmouni, Nesrine, Rosa‐Neto, Pedro, Sabri, Osama, Schott, Jonathan M, Schroeter, Matthias L, Seeley, William W., Servaes, Stijn, Sintini, Irene , Smith, Ruben, Stevenson, Jenna , Strandberg, Olof, Therriault, Joseph, Tideman, Pontus , Touroutoglou, Alexandra , Trainer, Anne, Wekselman, Fattin, Weston, Philip SJ., Whitwell, Jennifer L., Yong, Keir X X, O’Brien, John T. , Rabinovici, Gil D. , Day, Gregory S. , O'Brien, John Tiernan , Day, Gregory S , Xiong, Chengjie , Rabinovici, Gil D , Groot, Colin , Initiative, Alzheimer's Disease Neuroimaging, Blazhenets, Ganna , Boellaard, Ronald , Boon, Baayla D.C. , Brendel, Matthias , Cash, David M. , Coath, William , Dickerson, Brad C., Doering, Elena , Drzezga, Alexander E. , Dyck, Christopher H. van , Eimeren, Thilo van , Flier, Wiesje M. van der , Giessen, Elsmarieke van de , Gordon, Brian A. , Grinberg, Lea T. , Hansson, Oskar , Hobbs, Diana A. , Höglinger, Günter U. , Irwin, David J. , Jones, Peter Simon , Josephs, Keith A. , Joie, Renaud La , Lee, Eddie B, Malpetti, Maura , Mohanty, Rosaleena , Nasrallah, Ilya M. , O’Dell, Ryan S. , Palleis, Carla , Perneczky, Robert , Phillips, Jeffrey S , Putcha, Deepti , Rahmouni, Nesrine , Rosa-Neto, Pedro , Rowe, James B. , Rullmann, Michael , Saur, Dorothee , Schildan, Andreas , Schott, Jonathan M. , Schroeter, Matthias L , Seeley, William W. , Servaes, Stijn , Spina, Salvatore , Stomrud, Erik , Therriault, Joseph , Visser, Denise , Weston, Philip S.J. , Whitwell, Jennifer L. , Wolk, David A. , Yong, Keir , Pijnenburg, Yolande A.L. , Franzmeier, Nicolai , Ossenkoppele, Rik

Alzheimer's & Dementia | January 7, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_104871 Get It

Abstract Background The link between regional tau load and clinical manifestation of Alzheimer's disease (AD) highlights the importance of characterizing spatial tau distribution. In typical (memory‐predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicenters. However, atypical (non‐amnestic‐predominant) AD variants with heterogeneous tau patterns provide a key opportunity to assess the universality of connectivity as a scaffold for tau progression. Method We included tau‐PET data from 320 subjects with atypical AD, characterized by highly heterogeneous tau patterns ( n = 139 posterior cortical atrophy/PCA‐AD; n = 103 logopenic variant primary progressive aphasia/lvPPA‐AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS‐AD) from 14 sites, with a subset of patients ( n = 78) having longitudinal tau‐PET data. As an independent sample, we further included regional post‐mortem tau stainings from 93 atypical AD patients from two sites ( n = 19 PCA‐AD, n = 32 lvPPA‐AD, n = 23 bvAD, n = 19 CBS‐AD). Gaussian mixture modeling was used to harmonize different tau‐PET tracers by transforming tau‐PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether 1) brain regions with stronger functional connectivity showed greater covariance in cross‐sectional and longitudinal tau‐PET and post‐mortem tau pathology, and 2) functional connectivity of tau‐PET epicenters and tau‐PET accumulation epicenters was associated with cross‐sectional and longitudinal tau patterns. Result Tau‐PET epicenters—defined as the 5% brain regions with the highest tau load—aligned with clinical variants, e.g. a posterior pattern in PCA‐AD (“visual AD”) and left‐hemispheric temporal predominance in lvPPA‐AD (“language AD”) (Figure 1). More strongly functionally connected regions showed correlated concurrent tau‐PET levels, which was confirmed with post‐mortem data (Figure 2). Moreover, the connectivity profile of tau‐PET epicenters and accumulation epicenters corresponded to tau‐PET progression patterns (Figure 3). Conclusion Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicenters, across all AD clinical variants. Since tau proteinopathy is a key driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant‐specific endpoints in clinical trials.
Changes in Alzheimer's disease blood biomarkers in patients undergoing lecanemab therapy
Ashrafzadeh‐Kian, Susan , Radford, Jonathan Graff, Petersen, Ronald, Ramanan, Vijay K., Bornhorst, Joshua , Figdore, Daniel J. , Petersen, Ronald, Ramanan, Vijay K. , Algeciras‐Schimnich, Alicia

Alzheimer's & Dementia | December 24, 2025 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_099404 Get It

Abstract Background Anti‐amyloid therapy trials have reported changes in some Alzheimer's disease (AD) blood biomarkers (BBMs) suggesting that these BBMs may be useful minimally invasive measures of amyloid clearance and treatment outcomes. However, a better understanding of how AD BBMs changes at the individual level reflect treatment response in relation to other relevant clinical endpoints is necessary before they can be adopted for treatment monitoring. Here, several AD BBMs were assessed longitudinally in patients undergoing lecanemab therapy. Method Patients undergoing lecanemab therapy at Mayo Clinic, Rochester, MN were recruited to participate in this study. Patients were asked to provide an EDTA‐plasma sample before treatment initiation during the first infusion visit and thereafter at 3‐, 6‐, 12‐, and 18 months post‐treatment. p ‐tau217, p ‐tau181, GFAP, NfL, Aβ42, Aβ40, Aβ42/40, and p ‐tau217/Aβ42 measurements were obtained using Fujirebio Lumipulse assays. Biomarker median differences were assessed between all time points. Patients were grouped into three categories: a decreased biomarker (median decrease of at least 10%), an increased biomarker (median increase of at least 10%), and a stable biomarker (median change < +/−10%.) Biomarker data up to 6 months after treatment is presented. Result Of forty‐one patients enrolled since November 2023, twenty had time points up to 6 months. None of the biomarkers showed a statistically significant median change from baseline at 3 months ( p >0.05). At 6 months, only Aβ42/40 showed a statistically significant median change (decrease) between 0 and 6 months ( n = 20, p = 0.0058). Table 1 shows patients grouped by median biomarker changes from baseline to 6 months. GFAP, p ‐tau217, and Aβ42/40 exhibited the greatest number of patients with decreased biomarker concentrations (80%, 60%, and 60% of patients with median decreases of ‐25%, ‐26%, and ‐18% respectively), followed by p ‐tau181 (50% of patients; median decrease ‐22%), p ‐tau217/Aβ42 (45% of patients; median decrease ‐40%) and Aβ42 (45% of patients; median decrease ‐18%). None of the patients showed a decreased NfL or Aβ40 concentration. Conclusion Preliminarily analysis revealed that GFAP, p ‐tau217, and Aβ42/40 had the most frequent post‐lecanemab biomarker decreases. Additional sample collection is ongoing to assess the association of AD BBM changes with Amyloid PET over time.
Association between temporal lobe cortical NODDI measures and plasma biomarkers
Weigand, Stephen D. , Cogswell, Petrice M, Vemuri, Prashanthi, Knopman, D. S., Radford, Jonathan Graff, Petersen, Ronald, Jack, C. R., Pillai, Jay J. , Reid, Robert I. , Cogswell, Petrice M. , Vemuri, Prashanthi , Algeciras‐Schimnich, Alicia , Knopman, David S. , Petersen, Ronald, Jack, Clifford R.

Alzheimer's & Dementia | December 23, 2025 | Volume: 21 | Issue: S8 | Pages: No page available

10.1002/alz70862_109858 Get It

Abstract Background Plasma neurofilament light chains (NfL) and glial fibrillary acidic protein (GFAP) are blood‐based biomarkers of axonal injury and astrocytic activation, respectively, that are elevated in those with Alzheimer’s disease (AD) and mild cognitive impairment (MCI) relative to cognitively unimpaired (CU) individuals. Neurite orientation dispersion and density imaging (NODDI) is a multishell diffusion MRI method capable of evaluating tissue microstructure at the axonal and dendritic level. We evaluated associations between temporal cortex orientation dispersion index (ODI), neurite density index (NDI) and isotropic volume fraction (ISOVF) and plasma NfL and GFAP concentrations. Method We included Mayo Clinic Study of Aging (MCSA) participants (ages 60‐95 years) with diagnoses or CU ( n = 356) or MCI ( n = 60), and Alzheimer’s Dementia Research Center (ADRC) participants with dementia ( n = 51). NODDI imaging was obtained on a 3T Siemens Prisma scanner with 2 mm isotropic resolution. NfL and GFAP were measured using the Simoa® Neurology 4‐Plex E Advantage kit. We fit separate linear regression models within each MCALT_ADIR122 cortical ROI with regional NODDI as the primary predictor and log‐transformed plasma concentration as the outcome. Models were adjusted for age, sex, BMI, cortical thickness (or hippocampal & amygdalar volume) and total intracranial volume. Result The Table displays demographic data. Figures 1 & 2 show the relationship of NDI and ISOVF measures to plasma NfL concentrations across participants in individual ROIs (similar findings were noted with GFAP). A significant inverse relationship between NfL concentrations and NDI was observed in hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus as well as all temporal neocortical regions except the superior temporal gyrus ( p <0.001) (Figure 1), whereas higher NfL concentrations were associated with higher ISOVF in all regions ( p <0.001) (Figure 2). Fewer significant associations were also seen with ODI. After adjusting for age, cortical thickness/volume and other confounds, significant associations with NDI remain, particularly in hippocampal and amygdalar regions. Conclusion NODDI‐derived measures (NDI and ISOVF) within the temporal lobe cortical regions demonstrate significant associations with plasma biomarkers of axonal and astrocytic dysfunction that are elevated during cognitive decline. This association provides preliminary validation of the utility of NODDI in assessing cortical microstructural changes associated with cognitive decline.
Evaluating DTI‐ALPS, an imaging surrogate for glymphatic clearance, in a large population‐based sample
Satpathi, Siddhartha , Przybelski, Scott A. , Raghavan, Sheelakumari, Gunter, Jeffrey L. , Petersen, Ronald C. , Radford, Jonathan Graff, Reid, Robert I. , Raghavan, Sheelakumari , Knopman, David S. , Cogswell, Petrice M. , Jack, Clifford R. , Vemuri, Prashanthi

Alzheimer's & Dementia | January 9, 2025 | Volume: 20 | Issue: S2 | Pages: No page available

10.1002/alz.087185 Get It

Abstract Background Diffusion tensor imaging along perivascular spaces index (DTI‐ALPS), which measures diffusivity increases in the perivascular spaces along the medullary veins, is being increasingly utilized as a surrogate marker of glymphatic clearance (Taoka et. al. Jpn J Radio 2017). Lower DTI‐ALPS index means higher measured diffusivity from the perivascular space, and so it is expected to decrease with age. However, correlation with aging and dementia markers have not been systematically evaluated. The goal of this work was to automatically estimate DTI‐ALPS in a large sample and evaluate the variance explained by various demographic and imaging markers. Methods We identified 2739 participants aged 30+ years (mean 69.6, 48% female, 88% CU) in the population‐based Mayo Clinic Study of Aging with diffusion MRI. We estimated DTI‐ALPS through automated placement of regions as published previously (Liu et al. AAIC 2023) and shown in Figure 1. We examined the associations of DTI‐ALPS with demographics (age, sex), vascular risk (cardiovascular and metabolic condition score), clinical data (diagnosis, global cognition) and imaging markers (white matter hyperintensity (WMH), global amyloid load from PIB‐PET, and the temporal meta‐ROI Tau‐PET SUVR) using partial Pearson correlations and ANCOVA with adjustments for age and sex. Results DTI‐ALPS was negatively correlated with age, higher in females, declined with vascular risk, and lower in MCI/dementia groups (Figure 2). Higher WMH and higher amyloid were associated with lower DTI‐ALPS whereas Tau‐PET SUVR was not associated with DTI‐ALPS. Conclusions DTI‐ALPS can be automatically computed in large samples. Vascular risk and WMH had stronger associations with the computed DTI‐ALPS compared to AD biomarkers (amyloid and tau) suggesting that the surrogate was more likely linked to vascular injury.
Significance of a positive tau pet scan with a negative amyloid pet scan
Robinson, Carling G. , Lee, Jeyeon , Przybelski, Scott A. , Josephs, Keith A. , Radford, Jonathan Graff, Petersen, Ronald C. , Fields, Julie A. , Lowe, Val J. , Min, Hoon-Ki Paul , Jones, David T. , Boeve, Bradley F. , Knopman, David S. , Jack, Clifford R. , Machulda, Mary M.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S24 | Pages: No page available

10.1002/alz.082370 Get It

AbstractBackgroundThe implications of a positive tau (T) Positron Emission Tomography (PET) with a negative beta amyloid (A) PET are not well understood. We investigated cognitive performance in participants who were positive on tau PET but negative on beta amyloid PET.MethodWe evaluated 98 participants from the Mayo Clinic Study of Aging (MCSA) and the Mayo Clinic Alzheimer’s Disease Research Center (ADRC) who were positive for Flortaucipir (FTP) and negative for PiB PET. Participants were classified as A‐ and T+ based on Standardized Uptake Value Ratios (SUVr) of FTP and PiB PET scans, and were matched 2:1 to amyloid negative and tau negative cognitively unimpaired controls from the MCSA. Cognitive test scores were compared between the combined ADRC/MCSA group and MCSA only group. We also examined clinical diagnoses in our cohort. The most common were Alzheimer’s Disease, mild cognitive impairment (MCI), Dementia with Lewy Bodies (DLB) and Frontotemporal dementia (FTD) amongst others.ResultThere were no significant differences in demographic features or PiB SUVr between groups. There were significant differences in APOE genotype between groups. In the combined ADRC/MCSA group, 25% of A‐T‐ and 13% of A‐T+ were APOE e4 carriers (p = 0.016), and in the MCSA only group, 27% of A‐T‐and 10% of A‐T+ were APOE e4 carriers (p = 0.010). In the combined ADRC/MCSA group, the A‐T+ group demonstrated lower performance than the A‐T‐ group on the Mini Mental Status Exam (MMSE) (p<0.001), Wechsler Memory Scale‐Revised Logical Memory I (p<0.001) and Logical Memory II (p<0.001), Auditory verbal Learning Test Delayed Recall (AVLT) (p = 0.004), Category fluency animals (p = 0.005), Category fluency vegetables (p = 0.021), Trailmaking test A (p<0.001), Trail making test B (p<0.001), Wechsler Adult Intelligence Scale‐IV (WAIS‐IV) (p = 0.002), and Unified Parkinson’s Disease Rating Scale part III (UPDRS III) (p = 0.003). In the MCSA only group, the A‐T+ group had lower scores on Logical Memory II (p = 0.022), AVLT delated recall (p = 0.04), and WAIS‐R block design (p = 0.035) compared to the A‐T‐group.ConclusionPositive tau PET in the absence of beta‐amyloid positivity is associated with lower cognitive performance.
Default mode network sub‐systems connectivity in atypical Alzheimer’s disease
Sintini, Irene , Radford, Jonathan Graff, Martin, Peter R. , Gunter, Jeffrey L. , Petersen, Ronald C. , Lowe, Val J. , Josephs, Keith A. , Whitwell, Jennifer L. , Corriveau‐Lecavalier, Nick , Jones, David T. , Singh, Neha Atulkumar , Botha, Hugo , Machulda, Mary M. , Schwarz, Christopher G. , Jack, Clifford R.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S17 | Pages: No page available

10.1002/alz.073446 Get It

AbstractBackgroundDisruption of default mode network (DMN) connectivity is common in Alzheimer’s disease. We investigated cross‐sectional and one‐year longitudinal changes in DMN sub‐systems in atypical clinical presentations of AD, in relation to age and tau.MethodSixty‐four amyloid‐positive atypical AD (Aty‐AD) patients diagnosed with posterior cortical atrophy (n = 35) or logopenic progressive aphasia (n = 29) were recruited by the Neurodegenerative Research Group. Patients underwent structural and resting‐state functional MRI, and [18F]flortaucipir PET at baseline and one‐year follow‐up. 140 amyloid‐negative cognitively unimpaired (CU) individuals from the Mayo Clinic Study of Aging were included as controls. Global tau SUVR was calculated in a meta‐ROI including parietal, temporal, and occipital regions. DMN connectivity was calculated in native space for posterior (pDMN), ventral (vDMN), anterior ventral (avDMN) and anterior dorsal (adDMN) DMN sub‐systems using the dual regression method. A global measure of DMN connectivity, the Network Failure Quotient (NFQ), was calculated as (vDMN_to_pDMN+ adDMN_to_pDMN)/(pDMN+vDMN). Linear mixed‐effects models were computed for each DMN connectivity measure, including diagnosis (Aty‐AD, CU), age, time and their interaction, and a per‐person random effect. SPM paired t‐tests were run to compare baseline and follow‐up images in Aty‐AD and CU separately. Linear mixed‐effect models were run in the Aty‐AD cohort only to investigate the effect of global baseline tau SUVR on each DMN connectivity measure.ResultMixed‐effects models showed evidence of lower cross‐sectional pDMN and higher adDMN connectivity in Aty‐AD relative to CU, with no significant time effects (Fig. 1). While connectivity in all DMN sub‐systems declined with age in CU, connectivity was higher in older Aty‐AD patients relative to younger, particularly in vDMN and pDMN. A similar trend was observed for NFQ, which was significantly higher in Aty‐AD, with a negative age effect (Fig. 1). In Aty‐AD, voxel‐based analyses showed moderate evidence of decline in vDMN connectivity and increase in avDMN connectivity over time (Fig. 2). Greater baseline global tau SUVR was associated with lower vDMN connectivity, cross‐sectionally and longitudinally (Fig. 3).ConclusionDMN connectivity was altered in Aty‐AD, with strongest alterations in younger patients. The vDMN declined over time, suggesting a shift in DMN connectivity with disease progression that was likely related to tau pathology.
Comparison of longitudinal rates of atrophy and tau accumulation between posterior cortical atrophy and logopenic progressive aphasia
Sintini, Irene , Radford, Jonathan Graff, Lowe, Val J. , Josephs, Keith A. , Whitwell, Jennifer L. , Machulda, Mary M. , Singh, Neha Atulkumar , Carlos, Arenn F. , Schwarz, Christopher G. , Senjem, Matthew L. , Jack, Clifford R.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S17 | Pages: No page available

10.1002/alz.073399 Get It

AbstractBackgroundPosterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are atypical variants of Alzheimer’s disease which typically show different cross‐sectional patterns of atrophy and tau deposition. Patterns of atrophy remain distinct longitudinally. A direct comparison of rates of atrophy and tau accumulation between these syndromes has not yet been reported.MethodWe evaluated 20 PCA and 20 LPA patients; all were amyloid‐positive on [11C]PiB‐PET. Structural MRI and tau‐PET were performed at baseline and one‐year follow‐up. Annualized rates of change in grey matter volume (log Jacobians from tensor‐based morphometry) and flortaucipir‐PET SUVRs were calculated at the lobar level. A global tau SUVR was calculated using parietal, temporal, and occipital regions. Lobar rates were compared between PCA and LPA with linear models, accounting for education, sex, age, baseline global tau SUVR (for tau‐PET), with significance set at p = 0.05. SPM voxel‐level comparisons were performed, with the same covariates, with significance set at p = 0.001.ResultGroups did not differ in age, Apoe status, baseline global tau SUVR or whole brain volume, or their annualized rates of change. LPA had shorter disease duration. In the lobar models, PCA had faster rates of atrophy in the occipital lobe and there were no significant differences on rates of tau accumulation, but a trend for LPA having faster rates of tau accumulation in all lobes. Baseline global tau SUVR was negatively associated with rate of tau accumulation in parietal and temporal lobes. Age was negatively associated with rates of tau accumulation in frontal, temporal and occipital lobes and with rates of atrophy in frontal and parietal lobes. Voxel‐level analysis confirmed these results, with PCA showing faster rates of occipital atrophy, and LPA showing subtle evidence for diffuse faster rates of tau accumulation (Figure 1).ConclusionLongitudinal patterns of neuroimaging abnormalities differ between PCA and LPA, although with divergent results for tau accumulation and atrophy that may reflect differences in disease stage. Rates of change are strongly influenced by age and severity of baseline tau, with faster rates of tau accumulation in patients with younger age and lower baseline tau deposition.