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Drubach, Daniel A.

Mayo Clinic

Mayo Clinic

Citations 50

Autoimmune GFAP Astrocytopathy: Prospective Evaluation of 90 Patients in 1 year (S13.005)
Hinson, Shannon R., Ζεκερίδου, Αναστασία , Basal, Eati, Drubach, Daniel A., Lennon, Vanda A. , Dubey, Divyanshu , Flanagan, Eoin P. , Pittock, Sean J. , Lachance, Daniel Honore , McKeon, Andrew

Neurology | December 7, 2023 | Volume: 90 | Issue: 15_supplement | Pages: No page available

10.1212/wnl.90.15_supplement.s13.005 Get It

Clinical-Imaging-Pathologic Analysis in Seven Patients with Dementia: Correlations with Ioflupane SPECT Findings (P6.236)
Lowe, Val J. , Parisi, Joseph, Graff‐Radford, Jonathan , Savica, Rodolfo , Fields, Julie A. , Dheel, Christina, Allen, Laura A., Drubach, Daniel A., Silber, Michael H. , Petersen, Ronald, Boeve, Bradley F. , Kantarci, Kejal , Dickson, Dennis W. , Ferman, Tanis J. , Jones, David T. , Machulda, Mary M. , Louis, Erik K. St. , Jack, Clifford R. , Knopman, David S. , Petersen, Ronald

Neurology | December 7, 2023 | Volume: 86 | Issue: 16_supplement | Pages: No page available

10.1212/wnl.86.16_supplement.p6.236 Get It

Biomarker Confirmed Alzheimer’s Disease Presenting as Amnestic, Aphasic, and Visual Variants: Hippocampal Volume Comparison (P5.181)
Butts, Alissa M. , Drubach, Daniel A., Przybelski, Scott A. , Petersen, Ronald C. , Lowe, Val J. , Josephs, Keith A. , Whitwell, Jennifer , Machulda, Mary M. , Duffy, Joseph R. , Jack, Clifford R.

Neurology | December 7, 2023 | Volume: 86 | Issue: 16_supplement | Pages: No page available

10.1212/wnl.86.16_supplement.p5.181 Get It

Biomarker Confirmed Alzheimer’s Disease Presenting as Amnestic, Aphasic, and Visual Variants: Hippocampal Volume Comparison (I12.009)
Butts, Alissa M. , Strand, Edythe, Drubach, Daniel A., Przybelski, Scott A. , Petersen, Ronald C. , Lowe, Val J. , Josephs, Keith A. , Whitwell, Jennifer , Machulda, Mary M. , Duffy, Joseph R. , Jack, Clifford R.

Neurology | December 7, 2023 | Volume: 86 | Issue: 16_supplement | Pages: No page available

10.1212/wnl.86.16_supplement.i12.009 Get It

Posterior cortical atrophy phenotypic heterogeneity revealed by decoding 18F-FDG-PET
Townley, Ryan , Botha, Hugo , Graff‐Radford, Jonathan , Whitwell, Jennifer , Boeve, Bradley F. , Fields, Julie A. , Drubach, Daniel A., Savica, Rodolfo , Petersen, Ronald C. , Lowe, Val J. , Jack, Clifford R. , Josephs, Keith A. , Townley, Ryan A , Jack, Clifford R , Josephs, Keith A , Boeve, Brad , Botha, Hugo , Machulda, Mary M. , Senjem, Matthew L. , Knopman, David S. , Jones, David T.

Brain Communications | August 17, 2021 | Volume: 3 | Issue: 4 | Pages: No page available

10.1093/braincomms/fcab182 Get It

Abstract Posterior cortical atrophy is a neurodegenerative syndrome with a heterogeneous clinical presentation due to variable involvement of the left, right, dorsal and ventral parts of the visual system, as well as inconsistent involvement of other cognitive domains and systems. 18F-fluorodeoxyglucose (FDG)-PET is a sensitive marker for regional brain damage or dysfunction, capable of capturing the pattern of neurodegeneration at the single-participant level. We aimed to leverage these inter-individual differences on FDG-PET imaging to better understand the associations of heterogeneity of posterior cortical atrophy. We identified 91 posterior cortical atrophy participants with FDG-PET data and abstracted demographic, neurologic, neuropsychological and Alzheimer’s disease biomarker data. The mean age at reported symptom onset was 59.3 (range: 45–72 years old), with an average disease duration of 4.2 years prior to FDG-PET scan, and a mean education of 15.0 years. Females were more common than males at 1.6:1. After standard preprocessing steps, the FDG-PET scans for the cohort were entered into an unsupervised machine learning algorithm which first creates a high-dimensional space of inter-individual covariance before performing an eigen-decomposition to arrive at a low-dimensional representation. Participant values (‘eigenbrains’ or latent vectors which represent principle axes of inter-individual variation) were then compared to the clinical and biomarker data. Eight eigenbrains explained over 50% of the inter-individual differences in FDG-PET uptake with left (eigenbrain 1) and right (eigenbrain 2) hemispheric lateralization representing 24% of the variance. Furthermore, eigenbrain-loads mapped onto clinical and neuropsychological data (i.e. aphasia, apraxia and global cognition were associated with the left hemispheric eigenbrain 1 and environmental agnosia and apperceptive prosopagnosia were associated with the right hemispheric eigenbrain 2), suggesting that they captured important axes of normal and abnormal brain function. We used NeuroSynth to characterize the eigenbrains through topic-based decoding, which supported the idea that the eigenbrains map onto a diverse set of cognitive functions. These eigenbrains captured important biological and pathophysiologic data (i.e. limbic predominant eigenbrain 4 patterns being associated with older age of onset compared to frontoparietal eigenbrain 7 patterns being associated with younger age of onset), suggesting that approaches that focus on inter-individual differences may be important to better understand the variability observed within a neurodegenerative syndrome like posterior cortical atrophy.
Evolution of the core clinical features of dementia with Lewy bodies
Radford, Jonathan Graff, Wurtz, Lincoln , Aakre, Jeremiah A. , Brushaber, Danielle , Knopman, David S. , Savica, Rodolfo , Graff‐Radford, Neill R. , Drubach, Daniel A., Fields, Julie A. , Pedraza, Otto , Forsberg, Leah K. , Allen, Laura A., Miyagawa, Toji , Silber, Michael H. , Petersen, Ronald C. , Choudhury, Parichita , Jones, David T. , Knopman, David S. , Kantarci, Kejal , Machulda, Mary M. , Louis, Erik K. St. , Kremers, Walter K. , Boeve, Bradley F. , Ferman, Tanis J.

Alzheimer's & Dementia | December 7, 2020 | Volume: 16 | Issue: S6 | Pages: No page available

10.1002/alz.044307 Get It

AbstractBackgroundDementia with Lewy Bodies (DLB) is the second most common cause of degenerative dementia but the evolution of the core clinical features of DLB has not been clearly defined. The objective of this study was to identify the temporal relationship between each core feature from the estimated onset of cognitive symptoms.MethodParticipants include 485 patients with probable DLB who were evaluated at the Mayo Clinic Alzheimer Disease Research Center with neurologic and neurocognitive assessment. Each core clinical feature was compared using Kaplan‐Meier (KM) curves with the sentinel event representing age at which each core feature developed, or time from estimated cognitive onset.ResultThe sample was disproportionately male (76%). Patients were followed longitudinally, with 84% followed until death. Mean MMSE at the last evaluation was 18.3 ± 7.8. KM curves for age of onset and cumulative incidence for DLB core features as time from cognitive onset are provided. REM‐sleep behavior disorder (RBD) developed earliest and in 77% of our sample with a median KM survival estimate of 69 years (95% CI: 67.6–70.8). RBD was present in greater than 50% of patients at cognitive symptom onset. The median KM survival estimate for cognitive symptom onset was 70.2 years (95% CI: 69.3‐71.0). Parkinsonism developed in 89% with a median KM survival estimate of 73.7 years (95% CI: 72.7‐74.7). 76% had fluctuations with a similar median KM survival estimate of 74.6 years (95% CI: 73.7‐75.8). Visual hallucinations (VH) were present in 70% emerging at a median KM survival estimate of 80.2 years (95% CI: 79.5‐ 81.3). Cumulative incidence estimates for median time from cognitive onset to parkinsonism, fluctuations and VH were 2 years (95% CI: 2.0‐2.5), 2.3 years (95% CI: 2.0‐3.2) and 4.3 years (95% CI: 4.0‐4.8 years), respectively.ConclusionIn this DLB cohort, RBD was most likely to precede cognitive onset. The evolution of the other core features after cognitive onset was parkinsonism and fluctuations and then VH. While VH occur about 4 years after cognitive symptom onset, parkinsonism and fluctuations occur within the first 2 years.
Progressive dysexecutive syndrome due to Alzheimer’s disease: A description of 55 cases and comparisons to other clinical AD phenotypes
Townley, Ryan , Graff‐Radford, Jonathan, Przybelski, Scott A. , Reichard, Ross R., Savica, Rodolfo , Drubach, Daniel A., Josephs, Keith A. , Lowe, Val J. , Petersen, Ronald C. , Graff‐Radford, Jonathan , Mantyh, William G. , Botha, Hugo , Polsinelli, Angelina J. , Machulda, Mary M. , Senjem, Matthew L. , Murray, Melissa E. , Boeve, Bradley F. , Knopman, David S. , Jack, Clifford R. , Jones, David T.

Alzheimer's & Dementia | December 7, 2020 | Volume: 16 | Issue: S6 | Pages: No page available

10.1002/alz.040622 Get It

AbstractBackgroundWe report a group of individuals presenting with a progressive dementia syndrome characterized by predominant dysfunction in core executive functions and positive biomarkers for Alzheimer’s pathophysiology.MethodIn this retrospective review, we report on 55 participants with a clinically defined progressive dysexecutive syndrome with 18F‐fluorodeoxyglucose‐positron emission tomography (FDG) and AD biomarker positivity. A subset of these individuals enrolled in our ADRC were compared to other phenotypic variants of AD.ResultSixty‐two percent were female with a mean of 15.2 years of education. Mean age of symptom onset was 53.8 while mean age at diagnosis was 57.2 years. Multi‐domain cognitive impairment was evident in neuropsychological testing with executive dysfunction most consistently and severely affected. The frontal and/or parietal regions demonstrate clear hypometabolism on positron emission tomography in all cases. Genetic testing for autosomal dominant genes was negative in all 8 participants tested and at least one APOE ε4 allele was present in 14/26. EEG was abnormal in 14/17 cases. CSF and neuroimaging biomarkers (PIB‐PET and Tau‐PET) were consistent with Alzheimer’s disease pathophysiology, although CSF p‐tau was normal in 24% of cases. In two participants that came to autopsy, the hippocampus was relatively spared compared to frontal and parietal cortex. Participants presenting with a progressive dysexecutive syndrome and evidence of AD pathology are labeled dAD. Comparing FDG in dAD relative to other AD phenotypes revealed unique areas of relatively greater hypometabolism in parieto‐frontal cortex and relative sparing of medial temporal (vs typical AD), visual (vs PCA), and left temporal (vs lvPPA) (Figure 1). Controlling for age did not alter patterns of regional differences. This demonstrates regional variability related to clinical phenotype not accountable by variation in age, duration, stage, or severity (Figure 2).ConclusionA progressive dysexecutive syndrome should be recognized as a distinct clinical phenotype. This clinical presentation can be due to Alzheimer’s disease but is not specific for any single etiology (non‐AD cases of progressive dysexecutive syndrome will be discussed). Prominent impairment of executive task performance, young‐age of onset, normal CSF p‐tau, and relative preservation of the hippocampus were commonly encountered in this case series of dAD.
Progressive dysexecutive syndrome due to Alzheimer’s disease: a description of 55 cases and comparison to other phenotypes
Townley, Ryan , Graff‐Radford, Jonathan , Mantyh, William G. , Botha, Hugo , Polsinelli, Angelina J. , Przybelski, Scott A. , Makhlouf, Ahmed T. , Murray, Melissa E. , Reichard, Ross R., Savica, Rodolfo , Drubach, Daniel A., Josephs, Keith A. , Lowe, Val J. , Petersen, Ronald C. , Townley, Ryan A , Makhlouf, Ahmed T , Botha, Hugo , Murray, Melissa E , Machulda, Mary M. , Senjem, Matthew L. , Boeve, Bradley F. , Knopman, David S. , Jack, Clifford R. , Jones, David T.

Brain Communications | May 27, 2020 | Volume: 2 | Issue: 1 | Pages: No page available

10.1093/braincomms/fcaa068 Get It

Abstract We report a group of patients presenting with a progressive dementia syndrome characterized by predominant dysfunction in core executive functions, relatively young age of onset and positive biomarkers for Alzheimer’s pathophysiology. Atypical frontal, dysexecutive/behavioural variants and early-onset variants of Alzheimer’s disease have been previously reported, but no diagnostic criteria exist for a progressive dysexecutive syndrome. In this retrospective review, we report on 55 participants diagnosed with a clinically defined progressive dysexecutive syndrome with 18F-fluorodeoxyglucose-positron emission tomography and Alzheimer’s disease biomarkers available. Sixty-two per cent of participants were female with a mean of 15.2 years of education. The mean age of reported symptom onset was 53.8 years while the mean age at diagnosis was 57.2 years. Participants and informants commonly referred to initial cognitive symptoms as ‘memory problems’ but upon further inquiry described problems with core executive functions of working memory, cognitive flexibility and cognitive inhibitory control. Multi-domain cognitive impairment was evident in neuropsychological testing with executive dysfunction most consistently affected. The frontal and parietal regions which overlap with working memory networks consistently demonstrated hypometabolism on positron emission tomography. Genetic testing for autosomal dominant genes was negative in all eight participants tested and at least one APOE ε4 allele was present in 14/26 participants tested. EEG was abnormal in 14/17 cases with 13 described as diffuse slowing. Furthermore, CSF or neuroimaging biomarkers were consistent with Alzheimer’s disease pathophysiology, although CSF p-tau was normal in 24% of cases. Fifteen of the executive predominate participants enrolled in research neuroimaging protocols and were compared to amnestic (n = 110), visual (n = 18) and language (n = 7) predominate clinical phenotypes of Alzheimer’s disease. This revealed a consistent pattern of hypometabolism in parieto-frontal brain regions supporting executive functions with relative sparing of the medial temporal lobe (versus amnestic phenotype), occipital (versus visual phenotype) and left temporal (versus language phenotype). We propose that this progressive dysexecutive syndrome should be recognized as a distinct clinical phenotype disambiguated from behavioural presentations and not linked specifically to the frontal lobe or a particular anatomic substrate without further study. This clinical presentation can be due to Alzheimer’s disease but is likely not specific for any single aetiology. Diagnostic criteria are proposed to facilitate additional research into this understudied clinical presentation.