Head injury is associated with tau deposition on PET in MCI and AD patients

Clinical implications of head trauma in frontotemporal dementia and primary progressive aphasia

BACKGROUND

Traumatic brain injury (TBI) and repetitive head impacts (RHI) have been linked to increased risk for multiple types of neurodegenerative disease, higher dementia risk, and earlier age of dementia symptom onset, suggesting transdiagnostic implications for later-life brain health. Frontotemporal dementia (FTD) and primary progressive aphasia (PPA) represent a spectrum of clinical phenotypes that are neuropathologically diverse. FTD/PPA diagnoses bring unique challenges due to complex cognitive and behavioral symptoms that disproportionately present as an early-onset dementia (before age 65). We performed a detailed characterization of lifetime head trauma exposure in individuals with FTD and PPA compared to healthy controls to examine frequency of lifetime TBI and RHI and associated clinical implications.

METHODS

We studied 132 FTD/PPA (age 68.9 ± 8.1, 65% male) and 132 sex-matched healthy controls (HC; age 73.4 ± 7.6). We compared rates of prior TBI and RHI (contact/collision sports) between FTD/PPA and HC (chi-square, logistic regression, analysis of variance). Within FTD/PPA, we evaluated associations with age of symptom onset (analysis of variance). Within behavioral variant FTD, we evaluated associations with cognitive function and neuropsychiatric symptoms (linear regression controlling for age, sex, and years of education).

RESULTS

Years of participation were greater in FTD/PPA than HC for any contact/collision sport (8.5 ± 6.7yrs vs. 5.3 ± 4.5yrs, p = .008) and for American football (6.2yrs ± 4.3yrs vs. 3.1 ± 2.4yrs; p = .003). Within FTD/PPA, there were dose-dependent associations with earlier age of symptom onset for TBI (0 TBI: 62.1 ± 8.1, 1 TBI: 59.9 ± 6.9, 2 + TBI: 57.3 ± 8.4; p = .03) and years of American football (0yrs: 62.2 ± 8.7, 1-4yrs: 59.7 ± 7.0, 5 + yrs: 55.9 ± 6.3; p = .009). Within bvFTD, those who played American football had worse memory (z-score: -2.4 ± 1.2 vs. -1.4 ± 1.6, p = .02, d = 1.1).

CONCLUSIONS

Lifetime head trauma may represent a preventable environmental risk factor for FTD/PPA. Dose-dependent exposure to TBI or RHI influences FTD/PPA symptom onset and memory function in bvFTD. Clinico-pathological studies are needed to better understand the neuropathological correlates linking RHI or TBI to FTD/PPA onset and symptoms.

Traumatic Brain Injury and Post-Traumatic Stress Disorder and Their Influence on Development and Pattern of Alzheimer's Disease Pathology in Later Life

Background

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are potential risk factors for the development of dementia including Alzheimer's disease (AD) in later life. The findings of studies investigating this question are inconsistent though.

Objective

To investigate if these inconsistencies are caused by the existence of subgroups with different vulnerability for AD pathology and if these subgroups are characterized by atypical tau load/atrophy pattern.

Methods

The MRI and PET data of 89 subjects with or without previous TBI and/or PTSD from the DoD ADNI database were used to calculate an age-corrected gray matter tau mismatch metric (ageN-T mismatch-score and matrix) for each subject. This metric provides a measure to what degree regional tau accumulation drives regional gray matter atrophy (matrix) and can be used to calculate a summary score (score) reflecting the severity of AD pathology in an individual.

Results

The ageN-T mismatch summary score was positively correlated with whole brain beta-amyloid load and general cognitive function but not with PTSD or TBI severity. Hierarchical cluster analysis identified five different spatial patterns of tau-gray matter interactions. These clusters reflected the different stages of the typical AD tau progression pattern. None was exclusively associated with PTSD and/or TBI.

Conclusions

These findings suggest that a) although subsets of patients with PTSD and/or TBI develop AD-pathology, a history of TBI or PTSD alone or both is not associated with a significantly higher risk to develop AD pathology in later life. b) remote TBI or PTSD do not modify the typical AD pathology distribution pattern.

Traumatic brain injury and Alzheimer's Disease biomarkers: A systematic review of findings from amyloid and tau positron emission tomography (PET)

Traumatic brain injury (TBI) has been discussed as a risk factor for Alzheimer's disease (AD) due to its association with dementia risk and earlier cognitive symptom onset. However, the mechanisms behind this relationship are unclear. Some studies have suggested TBI may increase pathological protein deposition in an AD-like pattern; others have failed to find such associations. This review covers literature that uses positron emission tomography (PET) of amyloid-β and/or tau to examine subjects with history of TBI who are at risk for AD due to advanced age. A comprehensive literature search was conducted on January 9, 2023, and 24 resulting citations met inclusion criteria. Common methodological concerns included small samples, limited clinical detail about subjects' TBI, recall bias due to reliance on self-reported TBI, and an inability to establish causation. For both amyloid and tau, results were widespread but inconsistent. The regions which showed the most compelling evidence for increased amyloid deposition were the cingulate gyrus, cuneus/precuneus, and parietal lobe. Evidence for increased tau was strongest in the medial temporal lobe, entorhinal cortex, precuneus, and frontal, temporal, parietal, and occipital lobes. However, conflicting findings across most regions of interest in both amyloid- and tau-PET studies indicate the critical need for future work in expanded samples and with greater clinical detail to offer a clearer picture of the relationship between TBI and protein deposition in older subjects at risk for AD.

A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles

Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.

Diagnosis of Alzheimer's disease via resting-state EEG: integration of spectrum, complexity, and synchronization signal features

Background

Alzheimer's disease (AD) is the most common neurogenerative disorder, making up 70% of total dementia cases with a prevalence of more than 55 million people. Electroencephalogram (EEG) has become a suitable, accurate, and highly sensitive biomarker for the identification and diagnosis of AD.

Methods

In this study, a public database of EEG resting state-closed eye recordings containing 36 AD subjects and 29 normal subjects was used. And then, three types of signal features of resting-state EEG, i.e., spectrum, complexity, and synchronization, were performed by applying various signal processing and statistical methods, to obtain a total of 18 features for each signal epoch. Next, the supervised machine learning classification algorithms of decision trees, random forests, and support vector machine (SVM) were compared in categorizing processed EEG signal features of AD and normal cases with leave-one-person-out cross-validation.

Results

The results showed that compared to normal cases, the major change in EEG characteristics in AD cases was an EEG slowing, a reduced complexity, and a decrease in synchrony. The proposed methodology achieved a relatively high classification accuracy of 95.65, 95.86, and 88.54% between AD and normal cases for decision trees, random forests, and SVM, respectively, showing that the integration of spectrum, complexity, and synchronization features for EEG signals can enhance the performance of identifying AD and normal subjects.

Conclusion

This study recommended the integration of EEG features of spectrum, complexity, and synchronization for aiding the diagnosis of AD.