Camillo Imbimbo

Alterations in the gut microbiota (GM) are increasingly implicated in Alzheimer's disease (AD) pathogenesis through the microbiota-gut-brain axis (MGBA), influencing neuroinflammation, amyloid-β deposition, and tau aggregation. The inherent complexity of microbiota data necessitates artificial intelligence (AI) and machine learning (ML) to identify novel biomarkers and therapeutic targets. In this narrative review, we examined AI applications in AD-related GM research, including metataxonomic and metagenomic approaches. AI methods facilitate microbial signature identification and enterotype characterization associated with AD progression, enable multi-omics integration clarifying molecular pathways linking GM dysbiosis to neurodegeneration, support predictive modeling for early AD detection, and inform personalized MGBA-targeted interventions. Employed techniques include classical ML (e.g., random forests) for taxonomic classification, deep learning (e.g., neural networks) for complex pattern recognition, and explainable AI for identifying key bacterial taxa and metabolic functions. Significant challenges persist regarding methodological standardization, larger longitudinal cohorts, and ethical considerations in clinical applications. Future priorities include developing interpretable models, integrating longitudinal multi-omics data to establish causality, and validating AI-derived insights for precision AD prevention and treatment. AI uniquely enables high-dimensional, non-linear analyses that advance understanding of microbiome-brain interactions, though clinical translation requires rigorous validation and interdisciplinary collaboration.

Background: Plasma phosphorylated tau 217 (pTau217) has emerged as one of the most accurate biomarkers for Alzheimer's disease (AD). However, direct comparisons of pTau217 levels between different automated immunoassays remain limited. Objective: In this context, our work aimed to compare Lumipulse and Ella platforms for the measurement of plasma pTau217 across the AD continuum. Methods: Blood samples were collected from 32 subjective cognitive decline (SCD), 25 mild cognitive impairment (MCI), and 10 Alzheimer's disease (AD) patients. Plasma pTau217 levels were assessed using Lumipulse G600II automated system and Ella immunoassay SR-X platform. Associations with clinical variables and agreement between platforms were assessed. Results: Plasma pTau217 levels increased from SCD to AD with both assays. Lumipulse showed a significant difference between SCD and AD (p = 0.0011), while Ella detected differences between SCD and MCI (p = 0.0198) and SCD and AD (p = 0.0001). Both assays showed a significant inverse correlation with Mini-Mental State Examination (Lumipulse: r = −0.4913; p = 0.0001. Ella: Pearson r = −0.5139; p = 0.0001). A moderate correlation between platforms was observed. Bland–Altman analysis revealed a negative bias, with Lumipulse yielding lower values than Ella and increasing variability at higher concentrations. Conclusions: Lumipulse and Ella provided consistent qualitative information on plasma pTau217 across the AD continuum and show similar associations with cognitive performance, meaning that they are both comparable techniques. However, systematic bias and proportional variability limit their quantitative interchangeability, highlighting the need for cross-platform standardization.

Tau positron emission tomography (PET) has become a central imaging modality for in vivo detection and quantification of tau pathology across the Alzheimer's disease (AD) clinical and biological continuum. [18F]-Florzolotau is a second-generation tau PET tracer developed to improve target-to-background contrast and mitigate off-target binding relative to first-generation ligands, thereby improving interpretability for translational research and clinical use. In this narrative review, we provide a critical appraisal of the available literature on [18F]-Florzolotau PET imaging in AD, with emphasis on diagnostic and differential-diagnostic performance, the spatiotemporal topography of tau deposition in relation to Braak staging and disease progression, and the clinical significance of tracer uptake with respect to cognitive measures, disease severity, and prognosis. Eligible studies were clinical investigations published between 2020 and 2025 that applied [18F]-Florzolotau PET in cohorts spanning cognitively unimpaired individuals through symptomatic AD stages. Across reports, [18F]-Florzolotau PET differentiated AD dementia from cognitively unimpaired comparators with high accuracy, with sensitivities ≥ 90% and specificities of 87–96%. Regional uptake patterns were broadly consistent with Braak-like propagation, progressing from medial temporal regions toward associative neocortex in parallel with increasing clinical severity. Quantitative tracer uptake also correlated with global cognition and key domains, including episodic memory and executive function. We conclude that [18F]-Florzolotau PET provides a robust in vivo measure of AD tau burden, motivating further evaluation for diagnostic and prognostic applications. Larger multicenter studies with harmonized acquisition/quantification and head-to-head comparisons versus other second-generation tracers remain priorities.

Background and Objectives: The concept of the gut–muscle–brain axis encompasses the intricate, multidirectional interactions between the gut microbiota (GM), physical exercise (PE), and the central nervous system. Within this framework, gut dysbiosis has been implicated in the pathogenesis of Alzheimer’s disease (AD). Given that cognitive functions in AD appear to benefit from PE, it is plausible to hypothesize that these improvements may be partially mediated by PE-induced alterations in GM taxonomy. Therefore, the objective of this study is to evaluate the potential effects of PE in the GM and their implications for AD. Methods: A systematic review was conducted in PubMed, Web of Science and Scopus following the PRISMA guidelines up to July 2025 for preclinical controlled trials that assessed the effects of PE on the GM of AD animal models. A random-effects model meta-analysis was performed to estimate the pooled effect of PE on GM frequency or composition. This study received no external funding. Results: Eight studies were included in the systematic review (sample size, n = 126), of which two could be meta-analyzed. We found that PE significantly reduced Actinobacteria abundance (MD = −0.005%; 95% CI, −0.008 to −0.002; p = 0.001) with no statistically significant evidence of heterogeneity (I² = 89.60%, Q = 0.102, p = 0.950) or publication bias observed (Begg’s test, p = 0.296), but no significant effects were found for other phylums or genera. Conclusions: PE appears capable of modulating the GM of animal models with AD in a selective and heterogeneous manner. Further studies are needed to clarify the mechanisms by which this is possible and to determinate its impact on the pathogenesis of the disease.

Background: Behavioral and psychological symptoms of dementia (BPSD) have poorly understood pathological/morphological correlates. Objective: We aimed to (1) investigate the perception of the utility of different biomarkers in the assessment of BPSD among Italian Memory Clinics and (2) review current literature in this regard. Methods: A multicenter, national survey was launched by the BPSD Study Group of the Italian Neurological Society for Dementia (SINdem). Participants completed a semi-structured questionnaire on their perception of possible associations between the occurrence/severity of different BPSD and different biomarkers, based on their individual knowledge and clinical experience, regarding any type and severity of cognitive impairment. Then, we performed a systematic review according to PRISMA guidelines. Only papers reporting biomarkers correlates of BPSD in neurocognitive disorders were included. Results: Among the 53 responders, 94%, 68%, 68%, and 45% perceived neuropsychological testing, MRI, FDG-PET, and EEG, respectively, associated with the total amount of BPSD. EEG alterations were perceived selectively associated with nighttime behavior disturbances and psychosis cluster (p < 0.01). Hallucinations, apathy and delusions were perceived as more correlated with biomarkers. Years of experience using biomarkers for diagnosis were associated with a more selective use of topographical biomarkers (p < 0.01). 91% of participants consider useful increasing the use of biomarkers to predict the occurrence/severity of BPSD. The literature review identified 99 eligible studies. Brain MRI (60 articles) and FDG-PET (12 studies) alterations are the most associated with BPSD. Conclusions: In clinical practice, topographical biomarkers related to regional consequences of the pathology are perceived as potentially informative in the BPSD's assessment.

Psychosis and agitation are among the most distressing neuropsychiatric symptoms (NPSs) of Alzheimer’s disease (AD), linked to faster disease progression and earlier admission to nursing homes. While nonpharmacological treatments may alleviate mild behavioral symptoms, more severe syndromes often require pharmacological intervention. Brexpiprazole is the only medication approved for agitation in AD, although its limited clinical efficacy has raised criticism. No drugs have been approved for treating psychosis in AD, highlighting the critical need for new, effective, and safe treatments. Recent studies have elucidated part of the neurobiological basis of NPSs in the AD brain, offering insights for testing repurposed and novel drugs. We conducted a comprehensive nonsystematic literature review, aiming to provide a critical overview of both current treatments and emerging pharmacological interventions under clinical development for treating psychosis and agitation in AD. Additionally, we present strategies to optimize the clinical development of new drug candidates. We identify three promising compounds that are currently in phase 3 trials: xanomeline-trospium for AD psychosis, and dextromethorphan-bupropion and dexmedetomidine for agitation in AD. We propose that biomarkers linked to the neuropsychiatric traits of AD patients should be identified in dedicated studies and then included in phase 2 dose-range-finding studies with novel compounds to establish biological engagement. Furthermore, phase 3 placebo-controlled studies should be carried out in AD biomarker-confirmed subjects with narrower cognitive impairment ranges and precise NPS severity at screening. Alternative study designs, such as sequential phase approaches, may also be adopted.