Imaging and fluid biomarkers in frontotemporal dementia

Radiomics feature similarity: A novel approach for characterizing brain network changes in patients with behavioral variant frontotemporal dementia

INTRODUCTION

Network modeling is increasingly used to study brain alterations in neurological disorders. In this study, we apply a novel modeling approach based on the similarity of regional radiomics feature to characterize gray matter network changes in patients with behavioral variant frontotemporal dementia (bvFTD) using MRI data.

METHODS

In this cross-sectional study, we assessed structural 3 T MRI data from twenty patients with bvFTD and 20 cognitively normal controls. Radiomics features were extracted from T1-weighted MRI based on cortical and subcortical brain segmentation. Similarity in radiomics features between brain regions was used to construct intra-individual structural gray matter networks. Regional mean connectivity strength (RMCS) and region-to-region radiomics similarity were compared between bvFTD patients and controls. Finally, associations between network measures, clinical data, and biological features were explored in bvFTD patients.

RESULTS

Relative to controls, patients with bvFTD showed higher RMCS values in the superior frontal gyrus, right inferior temporal gyrus and right inferior parietal gyrus (FDR-corrected p < 0.05). Patients with bvFTD also showed several edges of increased radiomics similarity in key components of the frontal, temporal, parietal and thalamic pathways compared to controls (FDR-corrected p < 0.05). Network measures in frontotemporal circuits were associated with Mini-Mental State Examination scores and cerebrospinal fluid total-tau protein levels (Spearman r > |0.7|, p < 0.005).

CONCLUSIONS

Our study provides new insights into frontotemporal network changes associated with bvFTD, highlighting specific associations between network measures and clinical/biological features. Radiomics feature similarity analysis could represent a useful approach for characterizing brain changes in patients with frontotemporal dementia.

Vagus nerve stimulation (VNS) preventing postoperative cognitive dysfunction (POCD): two potential mechanisms in cognitive function

Postoperative cognitive dysfunction (POCD) impacts a significant number of patients annually, frequently impairing their cognitive abilities and resulting in unfavorable clinical outcomes. Aimed at addressing cognitive impairment, vagus nerve stimulation (VNS) is a therapeutic approach, which was used in many mental disordered diseases, through the modulation of vagus nerve activity. In POCD model, the enhancement of cognition function provided by VNS was shown, demonstrating VNS effect on cognition in POCD. In the present study, we primarily concentrates on elucidating the role of the VNS improving the cognitive function in POCD, via two potential mechanisms: the inflammatory microenvironment and epigenetics. This study provided a theoretical support for the feasibility that VNS can be a potential method to enhance cognition function in POCD.

Frontotemporal dementia subtyping using machine learning, multivariate statistics and neuroimaging

Frontotemporal dementia (FTD) is a prevalent form of early-onset dementia characterized by progressive neurodegeneration and encompasses a group of heterogeneous disorders. Due to overlapping symptoms, diagnosis of FTD and its subtypes still poses a challenge. Magnetic resonance imaging (MRI) is commonly used to support the diagnosis of FTD. Using machine learning and multivariate statistics, we tested whether brain atrophy patterns are associated with severity of cognitive impairment, whether this relationship differs between the phenotypic subtypes and whether we could use these brain patterns to classify patients according to their FTD variant. A total of 136 patients (70 behavioural variant FTD, 36 semantic variant primary progressive aphasia and 30 non-fluent variant primary progressive aphasia) from the frontotemporal lobar degeneration neuroimaging initiative (FTLDNI) database underwent brain MRI and clinical and neuropsychological examination. Deformation-based morphometry, which offers increased sensitivity to subtle local differences in structural image contrasts, was used to estimate regional cortical and subcortical atrophy. Atlas-based associations between atrophy values and performance across different cognitive tests were assessed using partial least squares. We then applied linear regression models to discern the group differences regarding the relationship between atrophy and cognitive decline in the three FTD phenotypes. Lastly, we assessed whether the combination of atrophy and cognition patterns in the latent variables identified in the partial least squares analysis could be used as features in a machine learning model to predict FTD subtypes in patients. Results revealed four significant latent variables that combined accounted for 86% of the shared covariance between cognitive and brain atrophy measures. Partial least squares-based atrophy and cognitive patterns predicted the FTD phenotypes with a cross-validated accuracy of 89.12%, with high specificity (91.46-97.15%) and sensitivity (84.19-93.56%). When using only MRI measures and two behavioural tests in the partial least squares and classification algorithms, ensuring clinical feasibility, our model was equally precise in the same participant sample (87.18%, specificity 76.14-92.00%, sensitivity 86.93-98.26%). Here, including only atrophy or behaviour patterns in the analysis led to prediction accuracies of 69.76% and 76.54%, respectively, highlighting the increased value of combining MRI and clinical measures in subtype classification. We demonstrate that the combination of brain atrophy and clinical characteristics and multivariate statistical methods can serve as a biomarker for disease phenotyping in FTD, whereby the inclusion of deformation-based morphometry measures adds to the classification accuracy in the absence of extensive clinical testing.

The Cortical Asymmetry Index for subtyping dementia patients

OBJECTIVES

Frontotemporal dementia (FTD) usually shows more asymmetric atrophy patterns than Alzheimer's disease (AD). We aim to quantify this asymmetry to differentiate FTD, AD, and FTD subtypes.

METHODS

We studied T1-MRI scans, including FTD (different phenotypes), AD, and healthy controls (CTR). We defined the Cortical Asymmetry Index (CAI) using measures based on a metric derived from information theory with the cortical thickness measures. Some participants had additional follow-up MRIs, cerebrospinal fluid (CSF), or plasma measures. We analysed differences at cross-sectional and longitudinal levels. We then clustered FTD and AD participants based on the CAI values and studied the patients' fluid biomarker characteristics within each cluster.

RESULTS

A total of 101 FTD patients (64  ±  8 years, 53 men), 230 AD patients (65  ±  10 years, 84 men), and 173 CTR (59  ±  15 years, 67 men) were studied. CAI differentiated FTD, AD, and CTR. It also distinguished the semantic variant primary progressive aphasia (svPPA) from the other FTD phenotypes. In FTD, the CAI increased over time. The cluster analysis identified two subgroups within FTD, characterised by different neurofilament-light (NfL) levels, and two subgroups within AD, with different plasma glial fibrillary acidic protein (GFAP) levels. In AD, CAI correlated with GFAP and Mini-Mental State Examination (MMSE); in FTD, the CAI was associated with NfL levels.

CONCLUSIONS

The proposed method quantifies asymmetries previously described visually. The CAI could define clinically and biologically meaningful disease subgroups in the differential diagnosis of AD and FTD and its subtypes. CAI could also be of interest in tracking disease progression in FTD.

KEY POINTS

Question There is a need to find quantitative metrics from MRI that can identify disease subgroups, and that could be useful for diagnosis and tracking. Findings We propose a Cortical Asymmetry Index that differentiates Alzheimer's disease (AD) from Frontotemporal dementia (FTD), distinguishes FTD subtypes, correlates with NFL and GFAP levels, and monitors FTD progression. Clinical relevance Our proposed index holds the potential to support clinical applications for diagnosis and disease tracking in AD and FTD, using a quantitative summary metric from MRI data. It also contributes to the understanding of these diseases.

Caregiver perspectives enable accurate diagnosis of neurodegenerative disease

BACKGROUND

The history from a relative or caregiver is an important tool for differentiating neurodegenerative disease. We characterized patterns of caregiver questionnaire responses, at diagnosis and follow-up, on the Cambridge Behavioural Inventory (CBI).

METHODS

Data-driven multivariate analysis (n = 4952 questionnaires) was undertaken for participants (n = 2481) with Alzheimer's disease (typical/amnestic n = 543, language n = 50, and posterior cortical n = 50 presentations), Parkinson's disease (n = 740), dementia with Lewy bodies (n = 55), multiple system atrophy (n = 55), progressive supranuclear palsy (n = 422), corticobasal syndrome (n = 176), behavioral variant frontotemporal dementia (n = 218), semantic (n = 125) and non-fluent variant progressive aphasia (n = 88), and motor neuron disease (n = 12).

RESULTS

Item-level support vector machine learning gave high diagnostic accuracy between diseases (area under the curve mean 0.83), despite transdiagnostic changes in memory, behavior, and everyday function. There was progression in CBI subscores over time, which varied by diagnosis.

DISCUSSION

Our results highlight the differential diagnostic information for a wide range of neurodegenerative diseases contained in a simple, structured collateral history.

HIGHLIGHTS

We analyzed 4952 questionnaires from caregivers of 2481 participants with neurodegenerative disease. Behavioral and neuropsychiatric manifestations of neurodegenerative disease had overlapping diagnostic boundaries. Simple questionnaire response patterns were sufficient for accurate diagnosis of each disease. We reinforce the value of a collateral history to support a diagnosis of dementia. The Cambridge Behavioural Inventory is sensitive to change over time and suitable as an outcome measure in clinical trials.

Recent Advances in Human Cerebrospinal Fluid Proteomics

Cerebrospinal fluid (CSF) proteomics has become an alternative that allows zooming-in where pathophysiological alterations are taking place, detecting protein mediators that might eventually be considered as potential biomarkers in neurological or psychiatric diseases. From a technological point of view, mass-spectrometry-based-proteomics as well as antibody/aptamer-based platforms allow the simultaneous monitoring of secreted and circulating proteins in a broad concentration range in a robust manner, generating innovative facets in biomarker validation. This chapter highlights recent discoveries in the field of CSF protein analysis, covering sample preparation methods for proteomic workflows, shotgun proteomics, subproteomics, and other omics applied to CSF.

Association of Initial Side of Brain Atrophy With Clinical Features and Disease Progression in Patients With GRN Frontotemporal Dementia

BACKGROUND AND OBJECTIVES

Pathogenic variants in the GRN gene cause frontotemporal dementia (FTD-GRN) with marked brain asymmetry. This study aims to assess whether the disease progression of FTD-GRN depends on the initial side of the atrophy. We also investigated the potential use of brain asymmetry as a biomarker of the disease.

METHODS

Retrospective examination of data from the prospective Genetic Frontotemporal Initiative (GENFI) cohort study that recruits individuals who carry or were at risk of carrying a pathogenic variant causing FTD. GENFI participants underwent a standardized clinical and neuropsychological assessment, MRI, and a blood sample test yearly. We generated an asymmetry index for brain MRI to characterize brain asymmetry in participants with or at risk of FTD-GRN. Depending on the side of the asymmetry, we classified symptomatic GRN patients as right-GRN or left-GRN and compared their clinical features and disease progression. We generated generalized additive models to study how the asymmetry index evolves in carriers and noncarriers and compare its models with others created with volumetric values and plasma neurofilament light chain.

RESULTS

A total of 399 participants (mean age 49.7 years, 59% female) were included (63 symptomatic carriers, 177 presymptomatic carriers, and 159 noncarriers). Symptomatic carriers showed higher brain asymmetry (11.6) than noncarriers (1.0, p < 0.001) and presymptomatic carriers (1.0, p < 0.001), making it possible to classify most of them as right-GRN (n = 21) or left-GRN (n = 36). Patients with right-GRN showed more disease severity at baseline (β = 6.9, 95% CI 2.4-11.0, p = 0.003) but a lower deterioration by year (β = -1.5, 95% CI -2.7 to -0.31, p = 0.015) than patients with left-GRN. Brain asymmetry could be found in GRN carriers 10.4 years before the onset of the symptoms (standard difference 0.85, CI 0.01-1.68).

DISCUSSION

FTD-GRN affects the brain hemispheres asymmetrically and causes 2 anatomical asymmetry patterns depending on the side of the disease onset. We demonstrated that these 2 anatomical asymmetry patterns present different symptoms, severity at the time of the first visit, and different disease courses. Our results also suggest brain asymmetry as a possible biomarker of conversion in GRN carriers.

A progranulin gene deletion in frontotemporal lobar degeneration with corticobasal syndrome in a TREDEM case report

Background

Behavioral variant frontotemporal dementia usually presents with behavioral and personality changes, social disinhibition, apathy, and lack of empathy, and is characterized by atrophy of the frontal and temporal lobes. Corticobasal syndrome is characterized by asymmetrical involuntary movements, rigidity, apraxia, tremor, dystonia, and cortical sensory deficits.

Objective

We present the case of a 59-year-old patient with a frontotemporal presentation and parkinsonism linked to progranulin gene deletion. We also report the clinical workup needed to reach the diagnosis.

Methods

Clinical, neuropsychological, computed tomography, magnetic resonance imaging, 18F-fluorodeoxyglucose and 18F-Flutemetamol positron emission tomography (PET), dopamine-transporter-single-photon emission computed tomography imaging, electroencephalography, and genetic evaluations were conducted.

Results

Our patient presented initially with executive and mnesic deficits along with the presence of apathy and loss of autonomy. Subsequently the cognitive deficits became associated with parkinsonian-like movement disorders and apraxia. Structural images showed right onset temporal and insular atrophy, and the PET images demonstrated right frontotemporal hypometabolism and the absence of amyloid in the cortex. The molecular analysis revealed a heterozygous deletion c.813_816delCACT on the GRN gene. This variant has been reported in the literature as pathogenic and associated with autosomal dominant frontotemporal dementia and corticobasal degeneration. Our patient presented different clinical features than those of the members of the families already described. In these families, some patients either presented immediately with motor syndrome with extrapyramidal features, or never developed extrapyramidal signs. Some subjects presented prevalent language dysfunction while others never presented memory disorders.

Conclusions

The clinical case highlights the phenotypic variability of this entity.

Gaps in biomedical research in frontotemporal dementia: A call for diversity and disparities focused research

Frontotemporal dementia (FTD) is one of the leading causes of young-onset dementia before age 65, typically manifesting as abnormal behavior (in behavioral variant FTD) or language impairment (in primary progressive aphasia). Although FTD affects all populations across the globe, knowledge regarding the pathophysiology and genetics derives primarily from studies conducted in North America and Western Europe. Globally, biomedical research for FTD is hindered by variable access to diagnosis, discussed in this group's earlier article, and by reduced access to expertise, funding, and infrastructure. This perspective paper was produced by two professional interest areas of the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART) and discusses the field's current status on the cross-cultural aspects of basic and translational research in FTD (including that focused on epidemiology, genetics, biomarkers, and treatment). It subsequently provides a summary of gaps and needs to address the disparities and advance global FTD biomedical research.

Blood-Based Biomarkers in Frontotemporal Dementia: A Narrative Review

This narrative review explores the current landscape of blood biomarkers in Frontotemporal dementia (FTD). Neurofilament light chain (NfL) may be useful in the differentiation of behavioral variant FTD from primary psychiatric disorders (PPDs) or dementia with Lewy bodies (DLB). In prodromal FTD and presymptomatic mutation carriers (GRN, MAPT, C9orf72), elevated NfL may herald pheno-conversion to full-blown dementia. Baseline NfL correlates with steeper neuroanatomical changes and cognitive, behavioral and functional decline, making NfL promising in monitoring disease progression. Phosphorylated neurofilament heavy chain (pNfH) levels have a potential limited role in the demarcation of the conversion stage to full-blown FTD. Combined NfL and pNfH measurements may allow a wider stage stratification. Total tau levels lack applicability in the framework of FTD. p-tau, on the other hand, is of potential value in the discrimination of FTD from Alzheimer's dementia. Progranulin concentrations could serve the identification of GRN mutation carriers. Glial fibrillary acidic protein (GFAP) may assist in the differentiation of PPDs from behavioral variant FTD and the detection of GRN mutation carriers (additional research is warranted). Finally, TAR DNA-binding protein-43 (TDP-43) appears to be a promising diagnostic biomarker for FTD. Its potential in distinguishing TDP-43 pathology from other FTD-related pathologies requires further research.

Educational disparities in brain health and dementia across Latin America and the United States

BACKGROUND

Education influences brain health and dementia. However, its impact across regions, specifically Latin America (LA) and the United States (US), is unknown.

METHODS

A total of 1412 participants comprising controls, patients with Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD) from LA and the US were included. We studied the association of education with brain volume and functional connectivity while controlling for imaging quality and variability, age, sex, total intracranial volume (TIV), and recording type.

RESULTS

Education influenced brain measures, explaining 24%-98% of the geographical differences. The educational disparities between LA and the US were associated with gray matter volume and connectivity variations, especially in LA and AD patients. Education emerged as a critical factor in classifying aging and dementia across regions.

DISCUSSION

The results underscore the impact of education on brain structure and function in LA, highlighting the importance of incorporating educational factors into diagnosing, care, and prevention, and emphasizing the need for global diversity in research.

HIGHLIGHTS

Lower education was linked to reduced brain volume and connectivity in healthy controls (HCs), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). Latin American cohorts have lower educational levels compared to the those in the United States. Educational disparities majorly drive brain health differences between regions. Educational differences were significant in both conditions, but more in AD than FTLD. Education stands as a critical factor in classifying aging and dementia across regions.

Neurofilaments and progranulin are related to atrophy in frontotemporal lobar degeneration - A transdiagnostic study cross-validating atrophy and fluid biomarkers

INTRODUCTION

Frontotemporal lobar degeneration (FTLD) encompasses behavioral variant frontotemporal dementia (bvFTD), progressive supranuclear palsy, corticobasal syndrome/degeneration, and primary progressive aphasias (PPAs). We cross-validated fluid biomarkers and neuroimaging.

METHODS

Seven fluid biomarkers from cerebrospinal fluid and serum were related to atrophy in 428 participants including these FTLD subtypes, logopenic variant PPA (lvPPA), Alzheimer's disease (AD), and healthy subjects. Atrophy was assessed by structural magnetic resonance imaging and atlas-based volumetry.

RESULTS

FTLD subtypes, lvPPA, and AD showed specific profiles for neurofilament light chain, phosphorylated heavy chain, tau, phospho-tau, amyloid beta1-42 from serum/cerebrospinal fluid, and brain atrophy. Neurofilaments related to regional atrophy in bvFTD, whereas progranulin was associated with atrophy in semantic variant PPA. Ubiquitin showed no effects.

DISCUSSION

Results specify biomarker and atrophy patterns in FTLD and AD supporting differential diagnosis. They identify neurofilaments and progranulin in interaction with structural imaging as promising candidates for monitoring disease progression and therapy.

HIGHLIGHTS

Study cross-validated neuroimaging and fluid biomarkers in dementia. Five kinds of frontotemporal lobar degeneration and two variants of Alzheimer's disease. Study identifies disease-specific fluid biomarker and atrophy profiles. Fluid biomarkers and atrophy interact in a disease-specific way. Neurofilaments and progranulin are proposed as biomarkers for diagnosis and therapy.

Arterial spin labelling magnetic resonance imaging and perfusion patterns in neurocognitive and other mental disorders: a systematic review

We reviewed 33 original research studies assessing brain perfusion, using consensus guidelines from a "white paper" issued by the International Society for Magnetic Resonance in Medicine Perfusion Study Group and the European Cooperation in Science and Technology Action BM1103 ("Arterial Spin Labelling Initiative in Dementia"; https://www.cost.eu/actions/BM1103/ ). The studies were published between 2011 and 2023 and included participants with subjective cognitive decline plus; neurocognitive disorders, including mild cognitive impairment (MCI), Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), dementia with Lewy bodies (DLB) and vascular cognitive impairment (VCI); as well as schizophrenia spectrum disorders, bipolar and major depressive disorders, autism spectrum disorder, attention-deficit/hyperactivity disorder, panic disorder and alcohol use disorder. Hypoperfusion associated with cognitive impairment was the major finding across the spectrum of cognitive decline. Regional hyperperfusion also was reported in MCI, AD, frontotemporal dementia phenocopy syndrome and VCI. Hypoperfused structures found to aid in diagnosing AD included the precunei and adjacent posterior cingulate cortices. Hypoperfused structures found to better diagnose patients with FTLD were the anterior cingulate cortices and frontal regions. Hypoperfusion in patients with DLB was found to relatively spare the temporal lobes, even after correction for partial volume effects. Hyperperfusion in the temporal cortices and hypoperfusion in the prefrontal and anterior cingulate cortices were found in patients with schizophrenia, most of whom were on medication and at the chronic stage of illness. Infratentorial structures were found to be abnormally perfused in patients with bipolar or major depressive disorders. Brain perfusion abnormalities were helpful in diagnosing most neurocognitive disorders. Abnormalities reported in VCI and the remaining mental disorders were heterogeneous and not generalisable.

Induced pluripotent stem cell models as a tool to investigate and test fluid biomarkers in Alzheimer's disease and frontotemporal dementia

Neurodegenerative diseases are increasing in prevalence and comprise a large socioeconomic burden on patients and their caretakers. The need for effective therapies and avenues for disease prevention and monitoring is of paramount importance. Fluid biomarkers for neurodegenerative diseases have gained a variety of uses, including informing participant selection for clinical trials, lending confidence to clinical diagnosis and disease staging, determining prognosis, and monitoring therapeutic response. Their role is expected to grow as disease-modifying therapies start to be available to a broader range of patients and as prevention strategies become established. Many of the underlying molecular mechanisms of currently used biomarkers are incompletely understood. Animal models and in vitro systems using cell lines have been extensively employed but face important translatability limitations. Induced pluripotent stem cell (iPSC) technology, where a theoretically unlimited range of cell types can be reprogrammed from peripheral cells sampled from patients or healthy individuals, has gained prominence over the last decade. It is a promising avenue to study physiological and pathological biomarker function and response to experimental therapeutics. Such systems are amenable to high-throughput drug screening or multiomics readouts such as transcriptomics, lipidomics, and proteomics for biomarker discovery, investigation, and validation. The present review describes the current state of biomarkers in the clinical context of neurodegenerative diseases, with a focus on Alzheimer's disease and frontotemporal dementia. We include a discussion of how iPSC models have been used to investigate and test biomarkers such as amyloid-β, phosphorylated tau, neurofilament light chain or complement proteins, and even nominate novel biomarkers. We discuss the limitations of current iPSC methods, mentioning alternatives such as coculture systems and three-dimensional organoids which address some of these concerns. Finally, we propose exciting prospects for stem cell transplantation paradigms using animal models as a preclinical tool to study biomarkers in the in vivo context.

The pursuit for markers of disease progression in behavioral variant frontotemporal dementia: a scoping review to optimize outcome measures for clinical trials

Behavioral variant frontotemporal dementia (bvFTD) is a neurodegenerative disorder characterized by diverse and prominent changes in behavior and personality. One of the greatest challenges in bvFTD is to capture, measure and predict its disease progression, due to clinical, pathological and genetic heterogeneity. Availability of reliable outcome measures is pivotal for future clinical trials and disease monitoring. Detection of change should be objective, clinically meaningful and easily assessed, preferably associated with a biological process. The purpose of this scoping review is to examine the status of longitudinal studies in bvFTD, evaluate current assessment tools and propose potential progression markers. A systematic literature search (in PubMed and Embase.com) was performed. Literature on disease trajectories and longitudinal validity of frequently-used measures was organized in five domains: global functioning, behavior, (social) cognition, neuroimaging and fluid biomarkers. Evaluating current longitudinal data, we propose an adaptive battery, combining a set of sensitive clinical, neuroimaging and fluid markers, adjusted for genetic and sporadic variants, for adequate detection of disease progression in bvFTD.

Gesture profiles distinguish primary progressive aphasia variants: A preliminary study

Background

Primary progressive aphasia (PPA) is a neurodegenerative syndrome characterized by progressive language deficits. The main variants of PPA -semantic (svPPA), logopenic (lvPPA), and nonfluent (nfvPPA)- can be challenging to distinguish. Limb apraxia often co-occurs with PPA, but it is unclear whether PPA variants are associated with different gesture deficits. Prior evidence from stroke indicates that temporal lobe lesions are associated with reduced benefit from meaning in gesture performance. Temporal lesions are also associated with greater deficits in hand postures compared to arm kinematics in gesture imitation.

Aims

We tested the hypothesis that svPPA, who primarily exhibit temporal lobe atrophy, would differentially show this pattern. In addition, we predicted that as a group, individuals with PPA would more accurately produce meaningful than meaningless gestures and kinematic components than hand postures, as found in neurotypical adults and individuals with stroke.

Methods & Procedures

Participants with PPA completed meaningful and meaningless gesture imitation tasks. Performance was scored for hand posture and arm kinematic components. Bayesian mixed-effect models examined trial-level gesture imitation accuracy, while controlling for dementia severity and random effects of subjects and items. Fixed effects included an interaction between PPA variant, task condition/meaning, and gesture component.

Outcomes & Results

We found a critical interaction between PPA variant, meaning, and gesture component. In particular, unlike lvPPA and nfvPPA, svPPA subjects' hand postures failed to benefit from gesture meaning. This preliminary research extends prior findings on the role of the temporal lobe in action representations associated with manipulable objects, and is among the first to demonstrate distinct gesture imitation patterns between PPA variants.

Conclusions

Characterizing gesture deficits in PPA may help inform diagnostics, compensatory communication strategies, and models of praxis.

Communicative impairment and its neural correlates in Alzheimer's disease and frontotemporal dementia

OBJECTIVE

Communication skills can deteriorate in neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal dementia (FTD); however, their clinical assessment and treatment in patient care can be challenging. In the present study, we aimed to quantify the distinctive communication resources and barriers reported by patients and their relatives in AD and FTD and associated these communicative characteristics with clinical parameters, such as the degree of cognitive impairment and atrophy in language-associated brain areas.

METHODS

We assessed self-reported communication barriers and resources in 33 individuals with AD and FTD through an interview on daily-life communication, using the Aachener KOMPASS questionnaire. We correlated reported communication barriers and resources with atrophy from high-resolution 3T brain magnetic resonance imaging, neuropsychological assessment, and neurodegenerative markers from cerebrospinal fluid.

RESULTS

Communicative impairment was higher in FTD compared to AD. Increased reported communication barriers in our whole sample were associated with the atrophy rate in the left middle temporal lobe, a critical site within the neuronal language network, and with depressive symptoms as well as the semantic word fluency from neuropsychological assessment. The best model for prediction of communicative impairment included the diagnosis (AD or FTD), semantic word fluency, and depressive symptoms.

CONCLUSIONS

Our study demonstrates that communication barriers and resources can be successfully assessed via a structured interview based on self-report and report of patients' relatives in practice and are reflected in neuroimaging specific for AD and FTD as well as in further clinical parameters specific for these neurodegenerative diseases. This can potentially open new treatment options for clinical practice and patient care.

Distinctive cell-free DNA methylation characterizes presymptomatic genetic frontotemporal dementia

OBJECTIVE

Methylation of plasma cell-free DNA (cfDNA) has potential as a marker of brain damage in neurodegenerative diseases such as frontotemporal dementia (FTD). Here, we study methylation of cfDNA in presymptomatic and symptomatic carriers of genetic FTD pathogenic variants, next to healthy controls.

METHODS

cfDNA was isolated from cross-sectional plasma of 10 presymptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), 10 symptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), and 9 healthy controls. Genome-wide methylation of cfDNA was determined using a high-resolution sequencing technique (MeD-seq). Cumulative scores based on the identified differentially methylated regions (DMRs) were estimated for presymptomatic carriers (vs. controls and symptomatic carriers), and reevaluated in a validation cohort (8 presymptomatic: 3 C9orf72, 3 GRN, and 2 MAPT; 26 symptomatic: 7 C9orf72, 6 GRN, 12 MAPT, and 1 TARDBP; 13 noncarriers from genetic FTD families).

RESULTS

Presymptomatic carriers showed a distinctive methylation profile compared to healthy controls and symptomatic carriers. Cumulative DMR scores in presymptomatic carriers enabled to significantly differentiate presymptomatic carriers from healthy controls (p < 0.001) and symptomatic carriers (p < 0.001). In the validation cohort, these scores differentiated presymptomatic carriers from symptomatic carriers (p ≤ 0.007) only. Transcription-start-site methylation in presymptomatic carriers, generally associated with gene downregulation, was enriched for genes involved in ubiquitin-dependent processes, while gene body methylation, generally associated with gene upregulation, was enriched for genes involved in neuronal cell processes.

INTERPRETATION

A distinctive methylation profile of cfDNA characterizes the presymptomatic stage of genetic FTD, and could reflect neuronal death in this stage.

Validation of a newly developed immunoassay for TDP-43 in human plasma

The level of TAR DNA-binding protein 43 (TDP-43) in human blood was reported to have potential for use as a specific fluid biomarker, which represents disease-specific pathologies, for TDP-43 proteinopathies, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), which involves the aggregation and deposition of TDP-43 in the nervous system. However, at present, no reliable immunoassay can precisely quantify TDP-43 in human plasma and detect the difference in plasma TDP-43 levels between patients with ALS and controls. We recently developed a novel ultrasensitive immunoassay to quantify TDP-43 in human plasma, and in this study, we analytically validated this assay for application as a diagnostic biomarker for TDP-43 proteinopathies. The novel TDP-43 assay was assessed for the limit of detection, lower limit of quantification, intra- and interassay variation, linearity, parallelism, and analytical spike recoveries. Additionally, 17 pilot plasma samples obtained from patients with ALS and age-matched controls were analyzed using the assay. Our novel TDP-43 assay showed sufficient analytical performance to quantify TDP-43 in human plasma, with high sensitivity (LOD and LLOQ of 0.109 and 0.759 pg/mL, respectively) and high intra- and interassay precision (%CV) below 15 %. The experimental results for spike recovery, parallelism, and dilution linearity were also acceptable. In addition, despite a small sample size, significant differences in the plasma levels of TDP-43 were found between patients with ALS and controls (ALS, 66.63 ± 20.52 pg/mL; control, 42.70 ± 23.06 pg/mL, p = 0.0330). These results support that our novel TDP-43 assay is a reliable and innovative method for the quantification of TDP-43 in human plasma and can be a potential blood-based biomarker for the diagnosis of TDP-43 proteinopathies. Further large-scale studies are warranted to validate its usefulness.

Tau Protein Alterations Induced by Hypobaric Hypoxia Exposure

Tauopathies are a group of neurodegenerative diseases whose central feature is dysfunction of the microtubule-associated protein tau (MAPT). Although the exact etiology of tauopathies is still unknown, it has been hypothesized that their onset may occur up to twenty years before the clear emergence of symptoms, which has led to questions about whether the prognosis of these diseases can be improved by, for instance, targeting the factors that influence tauopathy development. One such factor is hypoxia, which is strongly linked to Alzheimer's disease because of its association with obstructive sleep apnea and has been reported to affect molecular pathways related to the dysfunction and aggregation of tau proteins and other biomarkers of neurological damage. In particular, hypobaric hypoxia exposure increases the activation of several kinases related to the hyperphosphorylation of tau in neuronal cells, such as ERK, GSK3β, and CDK5. In addition, hypoxia also increases the levels of inflammatory molecules (IL-β1, IL-6, and TNF-α), which are also associated with neurodegeneration. This review discusses the many remaining questions regarding the influence of hypoxia on tauopathies and the contribution of high-altitude exposure to the development of these diseases.

Identifying and Diagnosing TDP-43 Neurodegenerative Diseases in Psychiatry

Neuropsychiatric symptoms (NPS) are common manifestations of neurodegenerative disorders and are often early signs of those diseases. Among those neurodegenerative diseases, TDP-43 proteinopathies are an increasingly recognized cause of early neuropsychiatric manifestations. TDP-43-related diseases include frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), and Limbic-Predominant Age-Related TDP-43 Encephalopathy (LATE). The majority of TDP-43-related diseases are sporadic, but a significant proportion is hereditary, with progranulin (GRN) mutations and C9orf72 repeat expansions as the most common genetic etiologies. Studies reveal that NPS can be the initial manifestation of those diseases or can complicate disease course, but there is a lack of awareness among clinicians about TDP-43-related diseases, which leads to common diagnostic mistakes or delays. There is also emerging evidence that TDP-43 accumulations could play a role in late-onset primary psychiatric disorders. In the absence of robust biomarkers for TDP-43, the diagnosis remains primarily based on clinical assessment and neuroimaging. Given the association with psychiatric symptoms, clinical psychiatrists have a key role in the early identification of patients with TDP-43-related diseases. This narrative review provides a comprehensive overview of the pathobiology of TDP-43, resulting clinical presentations, and associated neuropsychiatric manifestations to help guide clinical practice.

Neuroimaging determinants of cognitive impairment in the memory clinic: how important is the vascular burden?

While neurodegenerative and vascular neurocognitive disorder (NCD) often co-occur, the contribution of vascular lesions, especially stroke lesions identified on MRI, to global cognition in a real-life memory clinic population remains unclear. The main objective of this retrospective study was to determine NCD neuroimaging correlates: the GM atrophy pattern and vascular lesions (especially stroke lesion localization by voxel-based lesion-symptom mapping, VLSM) in a memory clinic. We included 336 patients with mild or major NCD who underwent cerebral MRI and a neuropsychological assessment. The GM atrophy pattern (obtained by voxel-based morphometry, VBM) and the stroke lesion localization (obtained by VLSM) associated with G5 z-score (a global cognitive score), were included as independent variables with other neuroimaging and clinical indices in a stepwise linear regression model. The mean age was 70.3 years and the mean MMSE score 21.3. On MRI, 75 patients had at least one stroke lesion. The G 5 z-score was associated with GM density in the pattern selected by the VBM analysis (R2 variation = 0.166, p < 0.001) and the presence of a stroke lesion in the region selected by the VSLM analysis (mainly in the right frontal region; R2 variation = 0.018, p = 0.008). The interaction between the two factors was insignificant (p = 0.374). In conclusion, in this first study combining VBM and VLSM analysis in a memory clinic, global cognition was associated with a specific GM atrophy pattern and the presence of a stroke lesion mainly in the right frontal region.

Retina Oculomics in Neurodegenerative Disease

Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocular imaging biomarkers to provide insights into systemic diseases. Advances in diagnostic and imaging technologies including electroretinography, optical coherence tomography (OCT), confocal scanning laser ophthalmoscopy, fluorescence lifetime imaging ophthalmoscopy, and OCT angiography have revolutionized the ability to understand systemic diseases and even detect them earlier than clinical manifestations for earlier intervention. With the advent of increasingly large ophthalmic imaging datasets, machine learning models can be integrated into these ocular imaging biomarkers to provide further insights and prognostic predictions of neurodegenerative disease. In this manuscript, we review the use of ophthalmic imaging to provide insights into neurodegenerative diseases including Alzheimer Disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, and Huntington Disease. We discuss recent advances in ophthalmic technology including eye-tracking technology and integration of artificial intelligence techniques to further provide insights into these neurodegenerative diseases. Ultimately, oculomics opens the opportunity to detect and monitor systemic diseases at a higher acuity. Thus, earlier detection of systemic diseases may allow for timely intervention for improving the quality of life in patients with neurodegenerative disease.

Neuroinflammation: The central enabler of postoperative cognitive dysfunction

The proportion of advanced age patients undergoing surgical procedures is on the rise owing to advancements in surgical and anesthesia technologies as well as an overall aging population. As a complication of anesthesia and surgery, older patients frequently suffer from postoperative cognitive dysfunction (POCD), which may persist for weeks, months or even longer. POCD is a complex pathological process involving multiple pathogenic factors, and its mechanism is yet unclear. Potential theories include inflammation, deposition of pathogenic proteins, imbalance of neurotransmitters, and chronic stress. The identification, prevention, and treatment of POCD are still in the exploratory stages owing to the absence of standardized diagnostic criteria. Undoubtedly, comprehending the development of POCD remains crucial in overcoming the illness. Neuroinflammation is the leading hypothesis and a crucial component of the pathological network of POCD and may have complex interactions with other mechanisms. In this review, we discuss the possible ways in which surgery and anesthesia cause neuroinflammation and investigate the connection between neuroinflammation and the development of POCD. Understanding these mechanisms may likely ensure that future treatment options of POCD are more effective.

The association between lifelong personality and clinical phenotype in the FTD-ALS spectrum

Introduction

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are two phenotypes of the same neurodegenerative disease, the FTD-ALS spectrum. What determines the development of one rather than the other phenotype is still unknown. Based on the clinical observation that patients' personality seems to differ between the two phenotypes, i.e., ALS patients tend to display kind, prosocial behaviors whereas FTD patients tend to present anti-social behaviors, and that these traits are often reported as pre-existing the disease onset by caregivers, we set up to study experimentally patients' personality in their premorbid life.

Methods

We first tested for differences between groups, then tested the association between premorbid personality and current functional organization of the brain. Premorbid personality of a cohort of forty patients, 27 FTD and 13 ALS, was explored through the NEO Personality Inventory 3 (NEO-PI-3), which analyses the five main personality factors, completed by the caregiver with reference to patient's personality 20 years before symptoms onset (premorbid). A subgroup of patients underwent a brain MRI including structural and resting-state functional MRI (rsfMRI).

Results

A significant difference between FTD and ALS in premorbid personality emerged in the Openness (133.92 FTD vs. 149.84 ALS, p = 0.01) and Extraversion (136.55 FTD vs. 150.53 ALS, p = 0.04) factors. This suggests that ALS patients had been, in their premorbid life, more open to new experiences, more sociable and optimistic than FTD patients. They also showed greater functional connectivity than both FTD and a control group in the Salience resting state network, over and above differences in gray matter atrophy. Finally, there was a positive correlation between premorbid Openness and functional connectivity in the Salience network across all patients, suggesting a possible association between premorbid personality and current functional organization of the brain, irrespective of the degree of atrophy.

Discussion

Our proof-of-concept results suggest that premorbid personality may eventually predispose to the development of one, rather than the other, phenotype in the FTD-ALS spectrum.

Cortical signature of depressive symptoms in frontotemporal dementia: A surface-based analysis

BACKGROUND AND OBJECTIVES

Depressive symptoms are frequently reported in patients affected by frontotemporal dementia (FTD). At structural MRI, cortical features of depressed FTD patients have been poorly described. Our objective was to investigate correlations between cortical measures and depression severity in FTD patients.

METHODS

Data were obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) database. We included 98 controls and 92 FTD patients, n = 38 behavioral variant FTD (bvFTD), n = 26 non-fluent variant Primary Progressive Aphasia (nfvPPA), and n = 28 semantic variant Primary Progressive Aphasia (svPPA). Patients underwent clinical and cognitive evaluations, as well as a 3D T1-weighted MRI on a 3 Tesla scanner (Siemens, Trio Tim system). Depression was evaluated by means of Geriatric Depression Scale (GDS). Surface-based analysis was performed on T1-weighted images to evaluate cortical thickness, a measure of gray matter integrity, and local gyrification index (lGI), a quantitative metric of cortical folding.

RESULTS

Patients affected by svPPA were more depressed than controls at NPI and depression severity at GDS was higher in svPPA and bvFTD. Severity of depression correlated with a decrease in lGI in left precentral and superior frontal gyrus, supramarginal and postcentral gyrus and right precentral, supramarginal, superior parietal and superior frontal gyri. Furthermore, depression severity correlated positively with cortical thickness in the left medial orbitofrontal cortex.

DISCUSSION

We found that lGI was associated with depressive symptoms over brain regions involved in the pathophysiology of major depressive disorder. This finding provides novel insights into the mechanisms underlying psychiatric symptoms in FTD.

Association of Choroid Plexus Volume With Serum Biomarkers, Clinical Features, and Disease Severity in Patients With Frontotemporal Lobar Degeneration Spectrum

BACKGROUND AND OBJECTIVES

Choroid plexus (ChP) is emerging as a key brain structure in the pathophysiology of neurodegenerative disorders. In this observational study, we investigated ChP volume in a large cohort of patients with frontotemporal lobar degeneration (FTLD) spectrum to explore a possible link between ChP volume and other disease-specific biomarkers.

METHODS

Participants included patients meeting clinical criteria for a probable syndrome in the FTLD spectrum. Structural brain MRI imaging, serum neurofilament light (NfL), serum phosphorylated-Tau181 (p-Tau181), and cognitive and behavioral data were collected. MRI ChP volumes were obtained from an ad-hoc segmentation model based on a Gaussian Mixture Models algorithm.

RESULTS

Three-hundred and sixteen patients within FTLD spectrum were included in this study, specifically 135 patients diagnosed with behavioral variant frontotemporal dementia (bvFTD), 75 primary progressive aphasia, 46 progressive supranuclear palsy, and 60 corticobasal syndrome. In addition, 82 age-matched healthy participants were recruited as controls (HCs). ChP volume was significantly larger in patients with FTLD compared with HC, across the clinical subtype. Moreover, we found a significant difference in ChP volume between HC and patients stratified for disease-severity based on CDR plus NACC FTLD, including patients at very early stage of the disease. Interestingly, ChP volume correlated with serum NfL, cognitive/behavioral deficits, and with patterns of cortical atrophy. Finally, ChP volume seemed to discriminate HC from patients with FTLD better than other previously identified brain structure volumes.

DISCUSSION

Considering the clinical, pathologic, and genetic heterogeneity of the disease, ChP could represent a potential biomarker across the FTLD spectrum, especially at the early stage of disease. Further longitudinal studies are needed to establish its role in disease onset and progression.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that choroid plexus volume, as measured on MRI scan, can assist in differentiating patients with FTLD from healthy controls and in characterizing disease severity.

Clinical Value of Longitudinal Serum Neurofilament Light Chain in Prodromal Genetic Frontotemporal Dementia

BACKGROUND AND OBJECTIVES

Elevated serum neurofilament light chain (NfL) is used to identify carriers of genetic frontotemporal dementia (FTD) pathogenic variants approaching prodromal conversion. Yet, the magnitude and timeline of NfL increase are still unclear. Here, we investigated the predictive and early diagnostic value of longitudinal serum NfL for the prodromal conversion in genetic FTD.

METHODS

In a longitudinal observational cohort study of genetic FTD pathogenic variant carriers, we examined the diagnostic accuracy and conversion risk associated with cross-sectional and longitudinal NfL. Time periods relative to prodromal conversion (>3, 3-1.5, 1.5-0 years before; 0-1.5 years after) were compared with values of participants who did not convert. Next, we modeled longitudinal NfL and MRI volume trajectories to determine their timeline.

RESULTS

We included 21 participants who converted (5 chromosome 9 open-reading frame 72 [C9orf72], 10 progranulin [GRN], 5 microtubule-associated protein tau [MAPT], and 1 TAR DNA-binding protein [TARDBP]) and 61 who did not (20 C9orf72, 30 GRN, and 11 MAPT). Participants who converted had higher NfL levels at all examined periods before prodromal conversion (median values 14.0-18.2 pg/mL; betas = 0.4-0.7, standard error [SE] = 0.1, p < 0.046) than those who did not (6.5 pg/mL) and showed further increase 0-1.5 years after conversion (28.4 pg/mL; beta = 1.0, SE = 0.1, p < 0.001). Annualized longitudinal NfL change was only significantly higher in participants who converted (vs. participants who did not) 0-1.5 years after conversion (beta = 1.2, SE = 0.3, p = 0.001). Diagnostic accuracy of cross-sectional NfL for prodromal conversion (vs. nonconversion) was good-to-excellent at time periods before conversion (area under the curve range: 0.72-0.92), improved 0-1.5 years after conversion (0.94-0.97), and outperformed annualized longitudinal change (0.76-0.84). NfL increase in participants who converted occurred earlier than frontotemporal MRI volume change and differed by genetic group and clinical phenotypes. Higher NfL corresponded to increased conversion risk (hazard ratio: cross-sectional = 6.7 [95% CI 3.3-13.7]; longitudinal = 13.0 [95% CI 4.0-42.8]; p < 0.001), but conversion-free follow-up time varied greatly across participants.

DISCUSSION

NfL increase discriminates individuals who convert to prodromal FTD from those who do not, preceding significant frontotemporal MRI volume loss. However, NfL alone is limited in predicting the exact timing of prodromal conversion. NfL levels also vary depending on underlying variant-carrying genes and clinical phenotypes. These findings help to guide participant recruitment for clinical trials targeting prodromal genetic FTD.

Frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD) is one of the most common causes of early-onset dementia and presents with early social-emotional-behavioural and/or language changes that can be accompanied by a pyramidal or extrapyramidal motor disorder. About 20-25% of individuals with FTLD are estimated to carry a mutation associated with a specific FTLD pathology. The discovery of these mutations has led to important advances in potentially disease-modifying treatments that aim to slow progression or delay disease onset and has improved understanding of brain functioning. In both mutation carriers and those with sporadic disease, the most common underlying diagnoses are linked to neuronal and glial inclusions containing tau (FTLD-tau) or TDP-43 (FTLD-TDP), although 5-10% of patients may have inclusions containing proteins from the FUS-Ewing sarcoma-TAF15 family (FTLD-FET). Biomarkers definitively identifying specific pathological entities in sporadic disease have been elusive, which has impeded development of disease-modifying treatments. Nevertheless, disease-monitoring biofluid and imaging biomarkers are becoming increasingly sophisticated and are likely to serve as useful measures of treatment response during trials of disease-modifying treatments. Symptomatic trials using novel approaches such as transcranial direct current stimulation are also beginning to show promise.

microRNA-based predictor for diagnosis of frontotemporal dementia

AIMS

This study aimed to explore the non-linear relationships between cell-free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis.

METHODS

We initially studied a training cohort of 219 subjects (135 FTD and 84 non-neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls).

RESULTS

On the basis of cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non-linear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ~90% of cases.

CONCLUSIONS

The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development.

Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization

Magnetic resonance imaging and computed tomography from multiple batches (e.g. sites, scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to obtain new insights into the human brain. However, significant confounding due to batch-related technical variation, called batch effects, is present in this data; direct application of downstream analyses to the data may lead to biased results. Image harmonization methods seek to remove these batch effects and enable increased generalizability and reproducibility of downstream results. In this review, we describe and categorize current approaches in statistical and deep learning harmonization methods. We also describe current evaluation metrics used to assess harmonization methods and provide a standardized framework to evaluate newly-proposed methods for effective harmonization and preservation of biological information. Finally, we provide recommendations to end-users to advocate for more effective use of current methods and to methodologists to direct future efforts and accelerate development of the field.

Brain-wide associations between white matter and age highlight the role of fornix microstructure in brain ageing

Unveiling the details of white matter (WM) maturation throughout ageing is a fundamental question for understanding the ageing brain. In an extensive comparison of brain age predictions and age-associations of WM features from different diffusion approaches, we analyzed UK Biobank diffusion magnetic resonance imaging (dMRI) data across midlife and older age (N = 35,749, 44.6-82.8 years of age). Conventional and advanced dMRI approaches were consistent in predicting brain age. WM-age associations indicate a steady microstructure degeneration with increasing age from midlife to older ages. Brain age was estimated best when combining diffusion approaches, showing different aspects of WM contributing to brain age. Fornix was found as the central region for brain age predictions across diffusion approaches in complement to forceps minor as another important region. These regions exhibited a general pattern of positive associations with age for intra axonal water fractions, axial, radial diffusivities, and negative relationships with age for mean diffusivities, fractional anisotropy, kurtosis. We encourage the application of multiple dMRI approaches for detailed insights into WM, and the further investigation of fornix and forceps as potential biomarkers of brain age and ageing.

Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia

INTRODUCTION

We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD).

METHODS

For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression.

RESULTS

We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants.

DISCUSSION

Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion.

HIGHLIGHTS

We investigated brain network predictors of dementia symptom onset Frontotemporal dementia results in characteristic dynamic network patterns Alterations in network dynamics are associated with neuropsychological impairment Network dynamic changes predict symptomatic conversion in presymptomatic carriers Network dynamic changes are associated with longitudinal cognitive decline.

Clusters of co-abundant proteins in the brain cortex associated with fronto-temporal lobar degeneration

BACKGROUND

Frontotemporal lobar degeneration (FTLD) is characterized pathologically by neuronal and glial inclusions of hyperphosphorylated tau or by neuronal cytoplasmic inclusions of TDP43. This study aimed at deciphering the molecular mechanisms leading to these distinct pathological subtypes.

METHODS

To this end, we performed an unbiased mass spectrometry-based proteomic and systems-level analysis of the middle frontal gyrus cortices of FTLD-tau (n = 6), FTLD-TDP (n = 15), and control patients (n = 5). We validated these results in an independent patient cohort (total n = 24).

RESULTS

The middle frontal gyrus cortex proteome was most significantly altered in FTLD-tau compared to controls (294 differentially expressed proteins at FDR = 0.05). The proteomic modifications in FTLD-TDP were more heterogeneous (49 differentially expressed proteins at FDR = 0.1). Weighted co-expression network analysis revealed 17 modules of co-regulated proteins, 13 of which were dysregulated in FTLD-tau. These modules included proteins associated with oxidative phosphorylation, scavenger mechanisms, chromatin regulation, and clathrin-mediated transport in both the frontal and temporal cortex of FTLD-tau. The most strongly dysregulated subnetworks identified cyclin-dependent kinase 5 (CDK5) and polypyrimidine tract-binding protein 1 (PTBP1) as key players in the disease process. Dysregulation of 9 of these modules was confirmed in independent validation data sets of FLTD-tau and control temporal and frontal cortex (total n = 24). Dysregulated modules were primarily associated with changes in astrocyte and endothelial cell protein abundance levels, indicating pathological changes in FTD are not limited to neurons.

CONCLUSIONS

Using this innovative workflow and zooming in on the most strongly dysregulated proteins of the identified modules, we were able to identify disease-associated mechanisms in FTLD-tau with high potential as biomarkers and/or therapeutic targets.

Frontotemporal dementia: Addressing the scattered harbingers of genetics and its relationship with glucose metabolism, bipolar disorder, and amyotrophic lateral sclerosis

Frontotemporal Dementia, also known by the name Pick's disease, is a rare form of dementia that can run for several generations. The two key characteristics are argyrophilic, spherical intraneuronal inclusions, which most frequently impact the frontal and temporal poles, and localized cortical atrophy (Pick bodies). Although personality decline and memory loss are frequently more severe than the visuospatial and apraxia disorders that are common in Alzheimer's disease, clinical overlap with other non-Alzheimer degenerative disorders is being increasingly recognized. The limbic system, which includes the hippocampus, entorhinal cortex, and amygdala, typically experiences the greatest levels of neuronal loss and degeneration. In the hippocampus's dentate fascia, several Pick bodies are frequently seen. Leukoencephalopathy and inflated cortical neurons are less specific symptoms (Pick cells). In this paper, we review the factors leading to Picks disease along with its pathophysiology, clinical manifestations, diagnosis, imaging, treatment, prognosis, and a comprehensive discussion on the same. We have also discussed the relationship of frontotemporal dementia with glucose metabolism, bipolar disorder, and amyotrophic lateral sclerosis, all of which are emerging fields of interest and need more studies.

Retinal Alterations as Potential Biomarkers of Structural Brain Changes in Alzheimer’s Disease Spectrum Patients

Retinal imaging being a potential biomarker for Alzheimer’s disease is gradually attracting the attention of researchers. However, the association between retinal parameters and AD neuroimaging biomarkers, particularly structural changes, is still unclear. In this cross-sectional study, we recruited 25 cognitively impaired (CI) and 21 cognitively normal (CN) individuals. All subjects underwent retinal layer thickness and microvascular measurements with optical coherence tomography angiography (OCTA). Gray matter and white matter (WM) data such as T1-weighted magnetic resonance imaging and diffusion tensor imaging, respectively, were also collected. In addition, hippocampal subfield volumes and WM tract microstructural alterations were investigated as classical AD neuroimaging biomarkers. The microvascular and retinal features and their correlation with brain structural imaging markers were further analyzed. We observed a reduction in vessel density (VD) at the inferior outer (IO) sector (p = 0.049), atrophy in hippocampal subfield volumes, such as the subiculum (p = 0.012), presubiculum (p = 0.015), molecular_layer_HP (p = 0.033), GC-ML-DG (p = 0.043) and whole hippocampus (p = 0.033) in CI patients. Altered microstructural integrity of WM tracts in CI patients was also discovered in the cingulum hippocampal part (CgH). Importantly, we detected significant associations between retinal VD and gray matter volumes of the hippocampal subfield in CI patients. These findings suggested that the retinal microvascular measures acquired by OCTA may be markers for the early prediction of AD-related structural brain changes.

Parkinsonism Is Associated with Altered SMA-Basal Ganglia Structural and Functional Connectivity in Frontotemporal Degeneration

BACKGROUND

Patients with frontotemporal degeneration (FTD) often manifest parkinsonism, which likely results from cortical and subcortical degeneration of brain structures involved in motor control. We used a multimodal magnetic resonance imaging (MRI) approach to investigate possible structural and/or functional alterations in FTD patients with and without parkinsonism (Park+ and Park-).

METHODS

Thirty FTD patients (12 Park+, 18 Park-) and 30 healthy controls were enrolled and underwent 3T MRI scanning. MRI analyses included: (1) surface-based morphometry; (2) basal ganglia and thalamic volumetry; (3) diffusion-based probabilistic tractography of fiber tracts connecting the supplementary motor area (SMA) and primary motor cortex (M1) to the putamen, globus pallidus, and thalamus; and (4) resting-state functional connectivity (RSFC) between the aforementioned regions.

RESULTS

Patients in Park+ and Park- groups showed comparable patterns of cortical thinning in frontotemporal regions and reduced thalamic volume with respect to controls. Only Park+ patients showed reduced putaminal volume and reduced fractional anisotropy of the fibers connecting the SMA to the globus pallidus, putamen, and thalamus, with respect to controls. Park+ patients also showed decreased RSFC between the SMA and putamen with respect to both Park- patients and controls.

CONCLUSIONS

The present findings support the hypothesis that FTD patients with parkinsonism are characterized by neurodegenerative processes in specific corticobasal ganglia-thalamocortical motor loops.

Gesture profiles distinguish primary progressive aphasia variants

Primary progressive aphasia (PPA) is a neurodegenerative syndrome characterized by progressive language deficits. There are three main variants of PPA - semantic (svPPA), logopenic (lvPPA), and nonfluent (nfvPPA) - that can be challenging to distinguish. Limb praxis may also be affected in PPA, but it is unclear whether different variants of PPA are associated with differences in gesture production. Prior research with neurotypical individuals indicates that the left temporal lobe is a critical locus of manipulable object and hand posture representations. Moreover, when imitating gestures, individuals whose strokes include the left temporal lobe show reduced benefit of gesture meaning and disproportionate impairment in hand posture as compared to arm kinematics. We tested the hypothesis that svPPA - who typically exhibit primarily temporal lobe atrophy - would differentially show these expected patterns of gesture imitation performance. Nineteen participants with PPA completed meaningful and meaningless gesture imitation tasks, and performance was scored for hand posture and arm kinematics accuracy. Generalized logistic mixed-effect regression models controlling for dementia severity showed overall benefits from gesture meaning, and greater impairments in hand posture than arm kinematics. We also found that svPPA participants were the most impaired in gesture imitation overall. Critically, there was also a significant three-way interaction of group, meaning, and gesture component: only svPPA participants showed relative impairments of hand posture for meaningful gestures as well as meaningless gestures. Thus, unlike lvPPA and nfvPPA, the hand postures of svPPA failed to benefit from gesture meaning. This research extends prior findings on the role of the temporal lobe in hand posture representations associated with manipulable objects, and is the first to indicate that there may be distinct gesture imitation patterns as a function of PPA variant. Characterizing componential gesture deficits in PPA may help to inform differential diagnosis, compensatory communication strategies, and cognitive praxis models of PPA.

Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging

INTRODUCTION

Dementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI).

METHODS

Atlas-based volumetry was performed on T1-weighted MRI data of 426 patients and 51 controls from the multi-centric German Research Consortium of Frontotemporal Lobar Degeneration including patients with behavioral variant frontotemporal dementia, Alzheimer's disease, the three subtypes of primary progressive aphasia, i.e., semantic, logopenic and nonfluent-agrammatic variant, and the atypical parkinsonian syndromes progressive supranuclear palsy and corticobasal syndrome. Support vector machine classification was used to classify each patient group against controls (binary classification) and all seven diagnostic groups against each other in a multi-syndrome classifier (multiclass classification).

RESULTS

The binary classification models reached high prediction accuracies between 71 and 95% with a chance level of 50%. Feature importance reflected disease-specific atrophy patterns. The multi-syndrome model reached accuracies of more than three times higher than chance level but was far from 100%. Multi-syndrome model performance was not homogenous across dementia syndromes, with better performance in syndromes characterized by regionally specific atrophy patterns. Whereas diseases generally could be classified vs controls more correctly with increasing severity and duration, differentiation between diseases was optimal in disease-specific windows of severity and duration.

DISCUSSION

Results suggest that automated methods applied to MR imaging data can support physicians in diagnosis of dementia syndromes. It is particularly relevant for orphan diseases beside frequent syndromes such as Alzheimer's disease.

Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference

Characterizing a particular neurodegenerative condition against others possible diseases remains a challenge along clinical, biomarker, and neuroscientific levels. This is the particular case of frontotemporal dementia (FTD) variants, where their specific characterization requires high levels of expertise and multidisciplinary teams to subtly distinguish among similar physiopathological processes. Here, we used a computational approach of multimodal brain networks to address simultaneous multiclass classification of 298 subjects (one group against all others), including five FTD variants: behavioral variant FTD, corticobasal syndrome, nonfluent variant primary progressive aphasia, progressive supranuclear palsy, and semantic variant primary progressive aphasia, with healthy controls. Fourteen machine learning classifiers were trained with functional and structural connectivity metrics calculated through different methods. Due to the large number of variables, dimensionality was reduced, employing statistical comparisons and progressive elimination to assess feature stability under nested cross-validation. The machine learning performance was measured through the area under the receiver operating characteristic curves, reaching 0.81 on average, with a standard deviation of 0.09. Furthermore, the contributions of demographic and cognitive data were also assessed via multifeatured classifiers. An accurate simultaneous multiclass classification of each FTD variant against other variants and controls was obtained based on the selection of an optimum set of features. The classifiers incorporating the brain's network and cognitive assessment increased performance metrics. Multimodal classifiers evidenced specific variants' compromise, across modalities and methods through feature importance analysis. If replicated and validated, this approach may help to support clinical decision tools aimed to detect specific affectations in the context of overlapping diseases.

Asymmetric Cerebral Peduncle Atrophy: A Simple Diagnostic Clue for Distinguishing Frontotemporal Lobar Degeneration from Alzheimer's Disease

BACKGROUND

Due to confusing clinicoradiological features such as amnestic symptoms and hippocampal atrophy in frontotemporal lobar degeneration (FTLD), antemortem differentiation between FTLD and Alzheimer's disease (AD) can be challenging. Although asymmetric atrophy of the cerebral peduncle is regarded as a representative imaging finding in some disorders of the FTLD spectrum, the utility of this finding has not been sufficiently evaluated for differentiating between FTLD and AD.

OBJECTIVE

This study aimed to explore the diagnostic performance of asymmetric cerebral peduncle atrophy on axial magnetic resonance imaging as a simple radiological discriminator between FTLD and AD.

METHODS

Seventeen patients with pathologically confirmed FTLD, including six with progressive supranuclear palsy, three with corticobasal degeneration, eight with TAR DNA-binding protein 43 (FTLD-TDP), and 11 with pathologically confirmed AD, were investigated. Quantitative indices representing the difference between the volumes of the bilateral cerebral peduncles (i.e., cerebral peduncular asymmetry index [CPAI]), the voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) Z-score representing the degree of hippocampal atrophy, and semiquantitative visual analysis to evaluate the asymmetry of the cerebral peduncle (visual assessment of cerebral peduncular asymmetry: VACPA) were compared between the two groups.

RESULTS

Contrary to the VSRAD Z-score, the CPAI and VACPA scores demonstrated higher diagnostic performance in differentiating patients with FTLD from those with AD (areas under the receiver operating characteristic curve of 0.88, 082, and 0.60, respectively).

CONCLUSIONS

Quantitative and visual analytical techniques can differentiate between FTLD and AD. These simple methods may be useful in daily clinical practice.

Plasma proteome profiling identifies changes associated to AD but not to FTD

BACKGROUND

Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process.

METHODS

Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis.

RESULTS

Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified.

CONCLUSIONS

We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.

Molecular imaging biomarkers in familial frontotemporal lobar degeneration: Progress and prospects

Familial frontotemporal lobar degeneration (FTLD) is a pathologically heterogeneous group of neurodegenerative diseases with diverse genotypes and clinical phenotypes. Three major mutations were reported in patients with familial FTLD, namely, progranulin (GRN), microtubule-associated protein tau (MAPT), and the chromosome 9 open reading frame 72 (C9orf72) repeat expansion, which could cause neurodegenerative pathological changes years before symptom onset. Noninvasive quantitative molecular imaging with PET or single-photon emission CT (SPECT) allows for selective visualization of the molecular targets in vivo to investigate brain metabolism, perfusion, neuroinflammation, and pathophysiological changes. There was increasing evidence that several molecular imaging biomarkers tend to serve as biomarkers to reveal the early brain abnormalities in familial FTLD. Tau-PET with ¹⁸F-flortaucipir and ¹¹C-PBB3 demonstrated the elevated tau position in patients with FTLD and also showed the ability to differentiate patterns among the different subtypes of the mutations in familial FTLD. Furthermore, dopamine transporter imaging with the ¹¹C-DOPA and ¹¹C-CFT in PET and the ¹²³I-FP-CIT in SPECT revealed the loss of dopaminergic neurons in the asymptomatic and symptomatic patients of familial FTLD. In addition, PET imaging with the ¹¹C-MP4A has demonstrated reduced acetylcholinesterase (AChE) activity in patients with FTLD, while PET with the ¹¹C-DAA1106 and ¹¹C-PK11195 revealed an increased level of microglial activation associated with neuroinflammation even before the onset of symptoms in familial FTLD. ¹⁸F-fluorodeoxyglucose (FDG)-PET indicated hypometabolism in FTLD with different mutations preceded the atrophy on MRI. Identifying molecular imaging biomarkers for familial FTLD is important for the in-vivo assessment of underlying pathophysiological changes with disease progression and future disease-modifying therapy. We review the recent progress of molecular imaging in familial FTLD with focused on the possible implication of these techniques and their prospects in specific mutation types.

Neurovascular dysfunction in GRN-associated frontotemporal dementia identified by single-nucleus RNA sequencing of human cerebral cortex

Frontotemporal dementia (FTD) is the second most prevalent form of early-onset dementia, affecting predominantly frontal and temporal cerebral lobes. Heterozygous mutations in the progranulin gene (GRN) cause autosomal-dominant FTD (FTD-GRN), associated with TDP-43 inclusions, neuronal loss, axonal degeneration and gliosis, but FTD-GRN pathogenesis is largely unresolved. Here we report single-nucleus RNA sequencing of microglia, astrocytes and the neurovasculature from frontal, temporal and occipital cortical tissue from control and FTD-GRN brains. We show that fibroblast and mesenchymal cell numbers were enriched in FTD-GRN, and we identified disease-associated subtypes of astrocytes and endothelial cells. Expression of gene modules associated with blood-brain barrier (BBB) dysfunction was significantly enriched in FTD-GRN endothelial cells. The vasculature supportive function and capillary coverage by pericytes was reduced in FTD-GRN tissue, with increased and hypertrophic vascularization and an enrichment of perivascular T cells. Our results indicate a perturbed BBB and suggest that the neurovascular unit is severely affected in FTD-GRN.

The New Zealand Genetic Frontotemporal Dementia Study (FTDGeNZ): a longitudinal study of pre-symptomatic biomarkers

The New Zealand Genetic Frontotemporal Dementia Study (FTDGeNZ) is an emerging longitudinal study of a large New Zealand pedigree with genetic frontotemporal dementia (FTD). Natural history studies of genetic FTD cohorts provide a unique opportunity to identify biomarkers of pre-symptomatic dementia, as carriers can be identified and studied decades before expected symptom onset. FTDGeNZ was established in 2016 with the aim of identifying the earliest pre-symptomatic biomarkers of FTD, in collaboration with international multi-centre cohorts. We enrolled 25 participants from a single family between April 2016 and August 2018. Participants were genotyped to determine whether they were pre-symptomatic carriers of the mutation (MAPT IVS 10 + 16 C > T), or non-carrier controls. Participants have undergone clinical assessments including neuropsychological and mood assessment; olfactory testing; assessment of social cognition; and blood collection for analyses of microRNA and protein fluid biomarkers annually. We have also performed structural and functional MRI of the brain and assessment of autobiographical memory biennially, and retinal imaging at baseline. Here, we describe the full study protocol and the baseline demographic and clinical characteristics of the FTDGeNZ cohort, and we highlight the latest findings in the field.

The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia

Frontotemporal dementia (FTD) is a spectrum of clinical syndromes that affects personality, behavior, language, and cognition. The current diagnostic criteria recognize three main clinical subtypes: the behavioral variant of FTD (bvFTD), the semantic variant of primary progressive aphasia (svPPA), and the non-fluent/agrammatic variant of PPA (nfvPPA). Patients with FTD display heterogeneous clinical and neuropsychological features that highly overlap with those presented by psychiatric syndromes and other types of dementia. Moreover, up to now there are no reliable disease biomarkers, which makes the diagnosis of FTD particularly challenging. To overcome this issue, different studies have adopted metrics derived from magnetic resonance imaging (MRI) to characterize structural and functional brain abnormalities. Within this field, a growing body of scientific literature has shown that graph theory analysis applied to MRI data displays unique potentialities in unveiling brain network abnormalities of FTD subtypes. Here, we provide a critical overview of studies that adopted graph theory to examine the topological changes of large-scale brain networks in FTD. Moreover, we also discuss the possible role of information arising from brain network organization in the diagnostic algorithm of FTD-spectrum disorders and in investigating the neural correlates of clinical symptoms and cognitive deficits experienced by patients.

Convergent regional brain abnormalities in behavioral variant frontotemporal dementia: A neuroimaging meta-analysis of 73 studies

Introduction

Numerous studies have reported brain alterations in behavioral variant frontotemporal dementia (bvFTD). However, they pointed to inconsistent findings.

Methods

We used a meta‐analytic approach to identify the convergent structural and functional brain abnormalities in bvFTD. Following current best‐practice neuroimaging meta‐analysis guidelines, we searched PubMed and Embase databases and performed reference tracking. Then, the coordinates of group comparisons between bvFTD and controls from 73 studies were extracted and tested for convergence using activation likelihood estimation.

Results

We identified convergent abnormalities in the anterior cingulate cortices, anterior insula, amygdala, paracingulate, striatum, and hippocampus. Task‐based and resting‐state functional connectivity pointed to the networks that are connected to the obtained consistent regions. Functional decoding analyses suggested associated dysfunction of emotional processing, interoception, reward processing, higher‐order cognitive functions, and olfactory and gustatory perceptions in bvFTD.

Discussion

Our findings highlighted the key role of the salience network and subcortical regions in the pathophysiology of bvFTD.

From clinical phenotype to proteinopathy: molecular neuroimaging in neurodegenerative dementias

Neurodegenerative dementias are characterized by the abnormal accumulation of misfolded proteins. However, its diagnostic criteria are still based on the clinical phenotype. The development of biomarkers allowed in vivo detection of pathophysiological processes. This article aims to make a non-systematic review of the use of molecular neuroimaging as a biomarker. Molecular neuroimaging is based on the use of radiotracers for image acquisition. The radiotracer most used in PET is 18F-fluorodeoxyglucose (FDG), with which it is possible to study the regional brain glucose metabolism. The pattern of regional hypometabolism provides neuroanatomical information on the neurodegenerative process, which, in turn, has a good specificity for each type of proteinopathy. FDG is very useful in the differential diagnosis of neurodegenerative dementias through the regional pattern of involvement, including dementia with Lewy bodies and the spectrum of frontotemporal dementia. More recently, radiotracers with specific ligands to some of the pathological proteins have been developed. Pittsburgh compound B (PIB) labeled with 11C and the ligands that use 18F (florbetapir, florbetaben and flutemetamol) are the most used radiotracers for the detection of insoluble β-amyloid peptide in Alzheimer's disease (AD). A first generation of ligands for tau protein has been developed, but it has some affinity for other non-tau protein aggregates. A second generation has the advantage of having a higher affinity for hyperphosphorylated tau protein, including in primary tauopathies.

Potential Protein Blood-Based Biomarkers in Different Types of Dementia: A Therapeutic Overview

Abstract:

Biomarkers capable of identifying and distinguishing types of dementia such as Alzheimer's disease (AD), Parkinson's disease dementia (PDD), Lewy body dementia (LBD), and frontotemporal dementia (FTD) have been become increasingly relentless. Studies of possible biomarker proteins in the blood that can help formulate new diagnostic proposals and therapeutic visions of different types of dementia are needed. However, due to several limitations of these biomarkers, especially in discerning dementia, their clinical applications are still undetermined. Thus, the updating of biomarker blood proteins that can help in the diagnosis and discrimination of these main dementia conditions is essential to enable new pharmacological and clinical management strategies, with specificities for each type of dementia. To review the literature concerning protein blood-based AD and non-AD biomarkers as new pharmacological targets and/or therapeutic strategies. Recent findings for protein-based AD, PDD, LBD, and FTD biomarkers are focused on in this review. Protein biomarkers were classified according to the pathophysiology of the dementia types. The diagnosis and distinction of dementia through protein biomarkers is still a challenge. The lack of exclusive biomarkers for each type of dementia highlights the need for further studies in this field. Only after this, blood biomarkers may have a valid use in clinical practice as they are promising to help in diagnosis and in the differentiation of diseases.