Publications by authors named "Tiraboschi P"

Background And Objectives: Sleep dysfunction is common in patients with neurodegenerative disorders; however, its neural underpinnings remain poorly characterized in genetic frontotemporal dementia (FTD). Hypothalamic nuclei important for sleep regulation may be related to this dysfunction. Thus, we examined changes in hypothalamic structure across the lifespan in patients with genetic FTD and whether these changes related to sleep dysfunction.

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

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Introduction: Genetic mutation carriers of frontotemporal dementia can remain cognitively well despite neurodegeneration. A better understanding of brain structural, perfusion, and functional patterns in the pre-symptomatic stage could inform accurate staging and potential mechanisms.

Methods: We included 207 pre-symptomatic genetic mutation carriers and 188 relatives without mutations.

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Background And Objectives: Behavioral and neuropsychiatric symptoms are frequent in patients with genetic frontotemporal dementia (FTD). We aimed to describe behavioral and neuropsychiatric phenotypes in genetic FTD, quantify their temporal association, and investigate their regional association with brain atrophy.

Methods: We analyzed data of pathogenic variant carriers in the chromosome 9 open reading frame 72 (), progranulin (), or microtubule-associated protein tau () gene from the Genetic Frontotemporal dementia Initiative cohort study that enrolls both symptomatic pathogenic variant carriers and first-degree relatives of known carriers.

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The advent of computerized medical recording systems in healthcare facilities has made data retrieval tasks easier, compared to manual recording. Nevertheless, the potential of the information contained within medical records remains largely untapped, mostly due to the time and effort required to extract data from unstructured documents. Natural Language Processing (NLP) represents a promising solution to this challenge, as it enables the use of automated text-mining tools for clinical practitioners.

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Background: Inflammation has been proposed as a crucial player in neurodegeneration, including Frontotemporal Dementia (FTD). A few studies on sporadic FTD lead to inconclusive results, whereas large studies on genetic FTD are lacking. The aim of this study is to determine cytokine and chemokine plasma circulating levels in a large cohort of genetic FTD, collected within the GENetic Frontotemporal dementia Initiative (GENFI).

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Background: Long non-coding RNAs (lncRNAs) play crucial roles in gene regulation and are implicated in neurodegenerative diseases, including frontotemporal dementia (FTD). However, their expression patterns and potential as biomarkers in genetic FTD involving Chromosome 9 Open Reading Frame (C9ORF72), Microtubule Associated Protein Tau (MAPT), and Progranulin (GRN) genes are not well understood.

Objective: This study aimed to profile the expression levels of lncRNAs in peripheral blood mononuclear cells collected within the GENetic Frontotemporal dementia Initiative (GENFI).

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The glymphatic system is an emerging target in neurodegenerative disorders. Here, we investigated the activity of the glymphatic system in genetic frontotemporal dementia with a diffusion-based technique called diffusion tensor image analysis along the perivascular space. We investigated 291 subjects with symptomatic or presymptomatic frontotemporal dementia (112 with [] expansion, 119 with [] mutations and 60 with [] mutations) and 83 non-carriers (including 50 young and 33 old non-carriers).

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Article Synopsis
  • The study investigates the effectiveness of the Italian Uniform Data Set Neuropsychological Test Battery (I-UDSNB) in differentiating between Mild Cognitive Impairment (MCI), Alzheimer's Disease (AD), and healthy controls (HC).
  • The research involved 137 patients randomly assigned to MCI, AD, and HC groups and employed statistical analyses to identify tests that effectively distinguished between these groups.
  • Results indicated that specific episodic memory tests from the I-UDSNB, particularly the Craft Story and Five Words tests, showed significant differentiation between MCI, AD, and HC, confirming the battery's reliability for assessing cognitive decline.
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Article Synopsis
  • Effective longitudinal biomarkers, like cerebral perfusion, are crucial for tracking disease progression in presymptomatic genetic frontotemporal dementia (FTD) carriers.
  • The study examined cerebral perfusion in various genetic FTD groups using advanced MRI techniques and found declines in gray matter perfusion across all groups, with specific regional patterns.
  • Results suggest that monitoring cerebral perfusion could serve as an early biomarker for detecting FTD before symptoms appear, especially highlighting differences among genetic subgroups.
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Introduction: We aimed to expand the range of the frontotemporal dementia (FTD) phenotypes assessed by the Clinical Dementia Rating Dementia Staging Instrument plus National Alzheimer's Coordinating Center Behavior and Language Domains (CDR plus NACC FTLD).

Methods: Neuropsychiatric and motor domains were added to the standard CDR plus NACC FTLD generating a new CDR plus NACC FTLD-NM scale. This was assessed in 522 mutation carriers and 310 mutation-negative controls from the Genetic Frontotemporal dementia Initiative (GENFI).

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Background: Blood neurofilament light chain (NfL) is increasingly considered as a key trial biomarker in genetic frontotemporal dementia (gFTD). We aimed to facilitate the use of NfL in gFTD multicentre trials by testing its (1) reliability across labs; (2) reliability to stratify gFTD disease stages; (3) comparability between blood matrices and (4) stability across recruiting sites.

Methods: Comparative analysis of blood NfL levels in a large gFTD cohort (GENFI) for (1)-(4), with n=344 samples (n=148 presymptomatic, n=11 converter, n=46 symptomatic subjects, with mutations in , or ; and n=139 within-family controls), each measured in three different international labs by Simoa HD-1 analyzer.

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Article Synopsis
  • The study aimed to validate clinical criteria for diagnosing mild cognitive and/or behavioral and/or motor impairment (MCBMI) in cases suspected of frontotemporal dementia (FTD).
  • A total of 398 participants were studied, including 117 FTD variant carriers with mild symptoms and 281 healthy controls, with some undergoing additional neurobiological assessments.
  • The MCBMI criteria effectively distinguished between affected individuals and healthy controls, with classification accuracy improving significantly when incorporating blood neurofilament light levels and anterior cingulate atrophy measurements.
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Introduction: F-Fluoro-deoxyglucose-positron emission tomography (FDG-PET) is a supportive biomarker in dementia with Lewy bodies (DLB) diagnosis and its advanced analysis methods, including radiomics and machine learning (ML), were developed recently. The aim of this study was to evaluate the FDG-PET diagnostic performance in predicting a DLB versus Alzheimer's disease (AD) diagnosis.

Methods: FDG-PET scans were visually and semi-quantitatively analyzed in 61 patients.

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Introduction: Dementia with Lewy bodies (DLB) is typically characterized by parietal, temporal, and occipital atrophy, but less is known about the newly defined prodromal phases. The objective of this study was to evaluate structural brain alterations in prodromal DLB (p-DLB) as compared to healthy controls (HC) and full-blown dementia (DLB-DEM).

Methods: The study included 42 DLB patients ( = 20 p-DLB;  = 22 DLB-DEM) and 27 HC with a standardized neurological assessment and 3-tesla magnetic resonance imaging.

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Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables.

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Article Synopsis
  • The current Alzheimer's disease diagnosis relies on various clinical and laboratory tests, but there's a risk of misdiagnosis due to symptom overlap with other dementias.
  • A new diagnostic method combines seed amplification assay (SAA) for enhanced sensitivity and surface-enhanced Raman spectroscopy (SERS) for unique specificity to detect brain biomarkers.
  • This SAA-SERS technique, aided by machine learning, effectively identifies problematic Aβ oligomers in the cerebrospinal fluid, enabling earlier patient stratification for treatments and clinical trials.
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Objective: To identify whether language impairment exists presymptomatically in genetic frontotemporal dementia (FTD), and if so, the key differences between the main genetic mutation groups.

Methods: 682 participants from the international multicentre Genetic FTD Initiative (GENFI) study were recruited: 290 asymptomatic and 82 prodromal mutation carriers (with C9orf72, GRN, and MAPT mutations) as well as 310 mutation-negative controls. Language was assessed using items from the Progressive Aphasia Severity Scale, as well as the Boston Naming Test (BNT), modified Camel and Cactus Test (mCCT) and a category fluency task.

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Background: Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches.

Methods: In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission.

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Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations.

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Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception.

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