Frontal variant of Alzheimer's disease masquerading as behavioural-variant frontotemporal dementia: a case study comparison

Frontal variant Alzheimer's disease: A systematic narrative synthesis

BACKGROUND

Frontal variant Alzheimer's disease (fvAD) is considered a rare form of Alzheimer's disease (AD) which may be misdiagnosed as behavioural variant frontotemporal dementia (bvFTD). The literature has tended to conflate behavioural and executive dysfunction in fvAD cohorts and uses both AD diagnostic criteria and bvFTD diagnostic criteria to classify fvAD cohorts. The primary aim of this narrative synthesis was to summarise neuropsychological findings in fvAD cohorts in the context of established AD pathology.

METHODS

EMBASE, PsycINFO, PROQUEST and MEDLINE databases were searched for studies eligible for inclusion. Studies with both neuropsychological and biomarker evidence were included in the final narrative synthesis.

RESULTS

Ten studies were reviewed, including samples totalling 342 fvAD participants, 178 typical AD participants and 250 bvFTD participants. The review revealed areas worthy of further investigation that may aid differential diagnosis, including the degree of executive dysfunction in fvAD cohorts relative to bvFTD cohorts, the onset of behavioural and cognitive symptomatology, and similarities between fvAD and typical AD cognitive profiles.

CONCLUSION

There was insufficient neuropsychological evidence to clearly differentiate fvAD and bvFTD cognitive phenotypes, however, the review has highlighted distinctive features of the two disorders that may guide differential diagnosis in future research. Moreover, the review has highlighted issues involving disparate diagnostic criteria used to classify fvAD cohorts, contributing to variation in findings.

The behavioral variant of Alzheimer's disease does not show a selective loss of Von Economo and phylogenetically related neurons in the anterior cingulate cortex

BACKGROUND

The neurobiological origins of the early and predominant behavioral changes seen in the behavioral variant of Alzheimer's disease (bvAD) remain unclear. A selective loss of Von Economo neurons (VENs) and phylogenetically related neurons have been observed in behavioral variant frontotemporal dementia (bvFTD) and several psychiatric diseases. Here, we assessed whether these specific neuronal populations show a selective loss in bvAD.

METHODS

VENs and GABA receptor subunit theta (GABRQ)-immunoreactive pyramidal neurons of the anterior cingulate cortex (ACC) were quantified in post-mortem tissue of patients with bvAD (n = 9) and compared to typical AD (tAD, n = 6), bvFTD due to frontotemporal lobar degeneration based on TDP-43 pathology (FTLD, n = 18) and controls (n = 13) using ANCOVAs adjusted for age and Bonferroni corrected. In addition, ratios of VENs and GABRQ-immunoreactive (GABRQ-ir) pyramidal neurons over all Layer 5 neurons were compared between groups to correct for overall Layer 5 neuronal loss.

RESULTS

The number of VENs or GABRQ-ir neurons did not differ significantly between bvAD (VENs: 26.0 ± 15.3, GABRQ-ir pyramidal: 260.4 ± 87.1) and tAD (VENs: 32.0 ± 18.1, p = 1.00, GABRQ-ir pyramidal: 349.8 ± 109.6, p = 0.38) and controls (VENs: 33.5 ± 20.3, p = 1.00, GABRQ-ir pyramidal: 339.4 ± 95.9, p = 0.37). Compared to bvFTD, patients with bvAD showed significantly more GABRQ-ir pyramidal neurons (bvFTD: 140.5 ± 82.658, p = 0.01) and no significant differences in number of VENs (bvFTD: 10.9 ± 13.8, p = 0.13). Results were similar when assessing the number of VENs and GABRQ-ir relative to all neurons of Layer 5.

DISCUSSION

VENs and phylogenetically related neurons did not show a selective loss in the ACC in patients with bvAD. Our results suggest that, unlike in bvFTD, the clinical presentation in bvAD may not be related to the loss of VENs and related neurons in the ACC.

Research Criteria for the Behavioral Variant of Alzheimer Disease: A Systematic Review and Meta-analysis

Importance

The behavioral variant of Alzheimer disease (bvAD) is characterized by early and predominant behavioral deficits caused by AD pathology. This AD phenotype is insufficiently understood and lacks standardized clinical criteria, limiting reliability and reproducibility of diagnosis and scientific reporting.

Objective

To perform a systematic review and meta-analysis of the bvAD literature and use the outcomes to propose research criteria for this syndrome.

Data Sources

A systematic literature search in PubMed/MEDLINE and Web of Science databases (from inception through April 7, 2021) was performed in duplicate.

Study Selection

Studies reporting on behavioral, neuropsychological, or neuroimaging features in bvAD and, when available, providing comparisons with typical amnestic-predominant AD (tAD) or behavioral variant frontotemporal dementia (bvFTD).

Data Extraction and Synthesis

This analysis involved random-effects meta-analyses on group-level study results of clinical data and systematic review of the neuroimaging literature. The study was performed following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines.

Main Outcomes and Measures

Behavioral symptoms (neuropsychiatric symptoms and bvFTD core clinical criteria), cognitive function (global cognition, episodic memory, and executive functioning), and neuroimaging features (structural magnetic resonance imaging, [18F]fluorodeoxyglucose-positron emission tomography, perfusion single-photon emission computed tomography, amyloid positron emission tomography, and tau positron emission tomography).

Results

The search led to the assessment of 83 studies, including 13 suitable for meta-analysis. Data were collected for 591 patients with bvAD. There was moderate to substantial heterogeneity and moderate risk of bias across studies. Cases with bvAD showed more severe behavioral symptoms than tAD (standardized mean difference [SMD], 1.16 [95% CI, 0.74-1.59]; P < .001) and a trend toward less severe behavioral symptoms compared with bvFTD (SMD, -0.22 [95% CI, -0.47 to 0.04]; P = .10). Meta-analyses of cognitive data indicated worse executive performance in bvAD vs tAD (SMD, -1.03 [95% CI, -1.74 to -0.32]; P = .008) but not compared with bvFTD (SMD, -0.61 [95% CI, -1.75 to 0.53]; P = .29). Cases with bvAD showed a nonsignificant difference of worse memory performance compared with bvFTD (SMD, -1.31 [95% CI, -2.75 to 0.14]; P = .08) but did not differ from tAD (SMD, 0.43 [95% CI, -0.46 to 1.33]; P = .34). The neuroimaging literature revealed 2 distinct bvAD neuroimaging phenotypes: an AD-like pattern with relative frontal sparing and a relatively more bvFTD-like pattern characterized by additional anterior involvement, with the AD-like pattern being more prevalent.

Conclusions and Relevance

These data indicate that bvAD is clinically most similar to bvFTD, while it shares most pathophysiological features with tAD. Based on these insights, we propose research criteria for bvAD aimed at improving the consistency and reliability of future research and aiding the clinical assessment of this AD phenotype.

A systematic review of atypical Alzheimer's disease including behavioural and psychological symptoms

Alzheimer's disease (AD) is the commonest cause of dementia, characterized by the clinical presentation of progressive anterograde episodic memory impairment. However, atypical presentation of patients is increasingly recognized. These atypical AD include logopenic aphasia, behavioural variant AD, posterior cortical atrophy, and corticobasal syndrome. These atypical AD are more common in patients with young onset AD before the age of 65 years old. Since medical needs (including the behavioural and psychological symptoms of dementia) of atypical AD patients could be different from typical AD patients, it is important for clinicians to be aware of these atypical forms of AD. In addition, disease modifying treatment may be available in the future. This review aims at providing an update on various important subtypes of atypical AD including behavioural and psychological symptoms.

Frontal Variant of Alzheimer Disease Differentiated From Frontotemporal Dementia Using in Vivo Amyloid and Tau Imaging

The frontal variant of Alzheimer disease (fvAD) is characterized by behavioral and/or dysexecutive impairments that can resemble those of behavioral-variant frontotemporal dementia (bvFTD). This overlap, in addition to the lack of consensus clinical criteria for fvAD, complicates its identification. We provide the first case report of fvAD differentiated in vivo from bvFTD using amyloid-beta and tau PET imaging. The patient, a right-handed woman, presented with forgetfulness at age 60. Cognitive testing at that time revealed mild impairments in memory, attention, and executive functions. Three years later, her family reported that she was displaying socially inappropriate behaviors, inertia, diminished social interest, and altered food preferences-the sum of which met the criteria for possible bvFTD. PET using an amyloid-beta tracer (F-AZD4694) identified diffuse amyloid plaques across the cerebral cortex. PET using a tau tracer specific for neurofibrillary tangles (F-MK6240) identified substantial tau pathology in the brain's frontal lobes. Together with the clinical findings, these images supported the diagnosis of fvAD rather than bvFTD. Considering past and emerging evidence that tau topography in Alzheimer disease (AD) matches the clinical features of AD, we discuss the potential utility of in vivo tau imaging using F-MK6240 for identifying fvAD.

Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer disease

BACKGROUND

We previously found temporoparietal-predominant atrophy patterns in the behavioral variant of Alzheimer's disease (bvAD), with relative sparing of frontal regions. Here, we aimed to understand the clinico-anatomical dissociation in bvAD based on alternative neuroimaging markers.

METHODS

We retrospectively included 150 participants, including 29 bvAD, 28 "typical" amnestic-predominant AD (tAD), 28 behavioral variant of frontotemporal dementia (bvFTD), and 65 cognitively normal participants. Patients with bvAD were compared with other diagnostic groups on glucose metabolism and metabolic connectivity measured by [18F]FDG-PET, and on subcortical gray matter and white matter hyperintensity (WMH) volumes measured by MRI. A receiver-operating-characteristic-analysis was performed to determine the neuroimaging measures with highest diagnostic accuracy.

RESULTS

bvAD and tAD showed predominant temporoparietal hypometabolism compared to controls, and did not differ in direct contrasts. However, overlaying statistical maps from contrasts between patients and controls revealed broader frontoinsular hypometabolism in bvAD than tAD, partially overlapping with bvFTD. bvAD showed greater anterior default mode network (DMN) involvement than tAD, mimicking bvFTD, and reduced connectivity of the posterior cingulate cortex with prefrontal regions. Analyses of WMH and subcortical volume showed closer resemblance of bvAD to tAD than to bvFTD, and larger amygdalar volumes in bvAD than tAD respectively. The top-3 discriminators for bvAD vs. bvFTD were FDG posterior-DMN-ratios (bvADbvFTD, area under the curve [AUC] range 0.85-0.91, all p < 0.001). The top-3 for bvAD vs. tAD were amygdalar volume (bvAD>tAD), MRI anterior-DMN-ratios (bvAD

CONCLUSIONS

Subtle frontoinsular hypometabolism and anterior DMN involvement may underlie the prominent behavioral phenotype in bvAD.

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Key Words

• Alzheimer’s disease
• Behavior
• Frontotemporal dementia
• MRI
• PET

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MESH Headings

• Alzheimer Disease/diagnostic imaging
• Frontotemporal Dementia/diagnostic imaging
• Gray Matter
• Humans
• Magnetic Resonance Imaging
• Retrospective Studies

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Grants

• R01-AG045611 NIA NIH HHS
• K24 AG045333 NIA NIH HHS
• P01 AG003991 NIA NIH HHS
• P30 AG062422 NIA NIH HHS
• P01 AG019724 NIA NIH HHS
• R01 AG045611 NIA NIH HHS
• National Institute on Aging
• ZonMw

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Affiliation(s)

Ellen H. Singleton Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Yolande A. L. Pijnenburg Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Carole H. Sudre School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
Colin Groot Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Elena Kochova Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Frederik Barkhof Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands Center for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
Renaud La Joie Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
Howard J. Rosen Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
William W. Seeley Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
Bruce Miller Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
M. Jorge Cardoso School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK Translational Imaging Group, CMIC, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
Janne Papma Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands
Philip Scheltens Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
Gil D. Rabinovici Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, USA
Rik Ossenkoppele Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands Clinical Memory Research Unit, Lund University, Lund, Sweden

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