Challenges and new opportunities in the investigation of new drug therapies to treat frontotemporal dementia

Single-subject classification of presymptomatic frontotemporal dementia mutation carriers using multimodal MRI

Background

Classification models based on magnetic resonance imaging (MRI) may aid early diagnosis of frontotemporal dementia (FTD) but have only been applied in established FTD cases. Detection of FTD patients in earlier disease stages, such as presymptomatic mutation carriers, may further advance early diagnosis and treatment. In this study, we aim to distinguish presymptomatic FTD mutation carriers from controls on an individual level using multimodal MRI-based classification.

Methods

Anatomical MRI, diffusion tensor imaging (DTI) and resting-state functional MRI data were collected in 55 presymptomatic FTD mutation carriers (8 microtubule-associated protein Tau, 35 progranulin, and 12 chromosome 9 open reading frame 72) and 48 familial controls. We calculated grey and white matter density features from anatomical MRI scans, diffusivity features from DTI, and functional connectivity features from resting-state functional MRI. These features were applied in a recently introduced multimodal behavioural variant FTD (bvFTD) classification model, and were subsequently used to train and test unimodal and multimodal carrier-control models. Classification performance was quantified using area under the receiver operator characteristic curves (AUC).

Results

The bvFTD model was not able to separate presymptomatic carriers from controls beyond chance level (AUC = 0.582, p = 0.078). In contrast, one unimodal and several multimodal carrier-control models performed significantly better than chance level. The unimodal model included the radial diffusivity feature and had an AUC of 0.642 (p = 0.032). The best multimodal model combined radial diffusivity and white matter density features (AUC = 0.684, p = 0.004).

Conclusions

FTD mutation carriers can be separated from controls with a modest AUC even before symptom-onset, using a newly created carrier-control classification model, while this was not possible using a recent bvFTD classification model. A multimodal MRI-based classification score may therefore be a useful biomarker to aid earlier FTD diagnosis. The exclusive selection of white matter features in the best performing model suggests that the earliest FTD-related pathological processes occur in white matter.

Single-subject classification of presymptomatic frontotemporal dementia mutation carriers using multimodal MRI

Background

Classification models based on magnetic resonance imaging (MRI) may aid early diagnosis of frontotemporal dementia (FTD) but have only been applied in established FTD cases. Detection of FTD patients in earlier disease stages, such as presymptomatic mutation carriers, may further advance early diagnosis and treatment. In this study, we aim to distinguish presymptomatic FTD mutation carriers from controls on an individual level using multimodal MRI-based classification.

Methods

Anatomical MRI, diffusion tensor imaging (DTI) and resting-state functional MRI data were collected in 55 presymptomatic FTD mutation carriers (8 microtubule-associated protein Tau, 35 progranulin, and 12 chromosome 9 open reading frame 72) and 48 familial controls. We calculated grey and white matter density features from anatomical MRI scans, diffusivity features from DTI, and functional connectivity features from resting-state functional MRI. These features were applied in a recently introduced multimodal behavioural variant FTD (bvFTD) classification model, and were subsequently used to train and test unimodal and multimodal carrier-control models. Classification performance was quantified using area under the receiver operator characteristic curves (AUC).

Results

The bvFTD model was not able to separate presymptomatic carriers from controls beyond chance level (AUC = 0.570, p = 0.11). In contrast, one unimodal and several multimodal carrier-control models performed significantly better than chance level. The unimodal model included the radial diffusivity feature and had an AUC of 0.646 (p = 0.021). The best multimodal model combined radial diffusivity and white matter density features (AUC = 0.680, p = 0.005).

Conclusions

FTD mutation carriers can be separated from controls with a modest AUC even before symptom-onset, using a newly created carrier-control classification model, while this was not possible using a recent bvFTD classification model. A multimodal MRI-based classification score may therefore be a useful biomarker to aid earlier FTD diagnosis. The exclusive selection of white matter features in the best performing model suggests that the earliest FTD-related pathological processes occur in white matter.

Frontotemporal lobar degeneration: current perspectives

The term frontotemporal lobar degeneration (FTLD) refers to a group of progressive brain diseases, which preferentially involve the frontal and temporal lobes. Depending on the primary site of atrophy, the clinical manifestation is dominated by behavior alterations or impairment of language. The onset of symptoms usually occurs before the age of 60 years, and the mean survival from diagnosis varies between 3 and 10 years. The prevalence is estimated at 15 per 100,000 in the population aged between 45 and 65 years, which is similar to the prevalence of Alzheimer's disease in this age group. There are two major clinical subtypes, behavioral-variant frontotemporal dementia and primary progressive aphasia. The neuropathology underlying the clinical syndromes is also heterogeneous. A common feature is the accumulation of certain neuronal proteins. Of these, the microtubule-associated protein tau (MAPT), the transactive response DNA-binding protein, and the fused in sarcoma protein are most important. Approximately 10% to 30% of FTLD shows an autosomal dominant pattern of inheritance, with mutations in the genes for MAPT, progranulin (GRN), and in the chromosome 9 open reading frame 72 (C9orf72) accounting for more than 80% of familial cases. Although significant advances have been made in recent years regarding diagnostic criteria, clinical assessment instruments, neuropsychological tests, cerebrospinal fluid biomarkers, and brain imaging techniques, the clinical diagnosis remains a challenge. To date, there is no specific pharmacological treatment for FTLD. Some evidence has been provided for serotonin reuptake inhibitors to reduce behavioral disturbances. No large-scale or high-quality studies have been conducted to determine the efficacy of non-pharmacological treatment approaches in FTLD. In view of the limited treatment options, caregiver education and support is currently the most important component of the clinical management.

Diagnosis and management of behavioral issues in frontotemporal dementia

Frontotemporal lobar degeneration is an umbrella term for several different disorders. In behavioral variant frontotemporal dementia (bvFTD), patients show deterioration in cognition and social behavior. New diagnostic criteria proposed by the International Behavioral Variant FTD Consortium provide greater sensitivity in diagnosing bvFTD. Current pharmacological management of symptoms relies on medications borrowed from treating Alzheimer's disease (AD) and psychiatric disorders. The evidence for using AD medications such as acetylcholinesterase inhibitors is questionable. Psychiatric medications can be helpful. Trazodone or SSRIs can have some efficacy in reducing disinhibition, repetitive behaviors, sexually inappropriate behaviors, and hyperorality. Small doses of atypical antipsychotics may be helpful in decreasing agitation and verbal outbursts. Nonpharmacological management includes caregiver education and support and behavioral interventions. While symptomatic treatments are likely to remain important behavior management tools, targeting the underlying pathology of bvFTD with disease-modifying agents will hopefully be the future of treatment.