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Abstract The present study was aimed to cluster sub-groups of patients with varying degrees of cognitive impairment (Subjective Cognitive Decline, mild or Major Neurocognitive Disorder) based on their modifiable risk factors and cognitive reserve with k-means analysis. As a secondary analysis, we described the identified clusters from different perspectives, i.e., socio-demographic characteristics, cognitive functioning, and mental health. The analysis revealed two clusters, which were composed by 27 and 43 patients characterized by protective (Cluster 1) and unprotective (Cluster 2) everyday life habits, respectively. The two groups showed significant differences across all examined dimensions, with Cluster 1 demonstrating a more favourable profile compared to Cluster 2. Specifically, Cluster 1 exhibited advantages in: (1) sociodemographic (education, technological skills, and occupation), (2) cognitive (global cognitive functioning, executive functioning, and working memory), and (3) mental health (mood state and quality of life) characteristics. Such a finding is representative of a more positive individual wellbeing for people who adopt protective behaviours. In the field of dementia prevention, these results support the importance to intervene proactively and simultaneously in the management of multiple risk factors during the entire lifespan.

Abstract Background The identification and staging of Alzheimer’s Disease (AD) represent a challenge, especially in the prodromal stage of Mild Cognitive Impairment (MCI), when cognitive changes can be subtle. Worldwide efforts were dedicated to select and harmonize available neuropsychological instruments. In Italy, the Italian Network of Neuroscience and Neuro-Rehabilitation has promoted the adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB), collecting normative data from 433 healthy controls (HC). Here, we aimed to explore the ability of I-UDSNB to differentiate between a) MCI and HC, b) AD and HC, c) MCI and AD. Methods One hundred thirty-seven patients (65 MCI, 72 AD) diagnosed after clinical-neuropsychological assessment, and 137 HC were included. We compared the I-UDSNB scores between a) MCI and HC, b) AD and HC, c) MCI and AD, with t-tests. To identify the test(s) most capable of differentiating between groups, significant scores were entered in binary logistic and in stepwise regressions, and then in Receiver Operating Characteristic curve analyses. Results Two episodic memory tests (Craft Story and Five Words test) differentiated MCI from HC subjects; Five Words test, Semantic Fluency (vegetables), and TMT-part B differentiated AD from, respectively, HC and MCI. Conclusions Our findings indicate that the I-UDSNB is a suitable tool for the harmonized and concise assessment of patients with cognitive decline, showing high sensitivity and specificity for the diagnosis of MCI and AD.

Abstract Background Several risk factors are associated with the chronic evolution of migraine. Clinical and preclinical studies have provided data about the role of hypertension (HT) as one of the potential modifiable risk factors of chronic migraine (CM). This review is focused on the biological and clinical evidence supporting common mechanisms underlying HT and migraine and the potential role of HT in the transition from episodic to chronic migraine. Methods We conducted a narrative review from a literature search covering the available evidence from studies investigating: i) the role of HT in the transition to CM in clinical practice; ii) the biological mechanisms potentially underpinning the association between HT and evolution to CM; iii) the role of antihypertensive medications in migraine prophylaxis. Results HT proved to be at the base of multiple mechanisms underlying migraine and migraine chronicization. Endothelial dysfunction, blood–brain barrier alterations, calcitonin gene-related peptide signaling, and renin–angiotensin–aldosterone system dysregulation are involved in the worsening effect of HT on migraine frequency, and the role of HT in the transition to CM is supported by clinical observations. Conclusions The observed evidence supports HT contribution to CM evolution due to shared pathophysiologic mechanisms. While a bidirectional influence appears to be ascertained, data are still lacking about the one-way role of HT as direct risk factor for CM transition. Further research is needed to confirm a causal role of HT in this process.

BackgroundNeuropsychiatric symptoms (NPSs) are a distressful aspect of dementia and the knowledge of structural correlates of NPSs is limited. We aimed to identify associations of fronto-limbic circuit with specific NPSs in patients with various types of cognitive impairment.MethodsOf 84 participants, 27 were diagnosed with mild cognitive impairment (MCI), 41 with Alzheimer’s disease (AD) dementia and 16 with non-AD dementia. In all patients we assessed regional brain morphometry using a region of interest (ROI)-based analysis. The mean cortical thickness (CT) of 20 cortical regions and the volume (V) of 4 subcortical areas of the fronto-limbic system were extracted. NPSs were rated with the Neuropsychiatric Inventory (NPI). We used multiple linear regression models adjusted for age and disease duration to identify significant associations between scores of NPI sub-domains and MRI measures of brain morphometry.ResultsAll significant associations found were negative, except those between irritability and the fronto-opercular regions in MCI patients (corresponding to a 40-50% increase in CT) and between delusions and hippocampus and anterior cingulate gyrus (with a 40-60% increase). Apathy showed predominant involvement of the inferior frontal regions in AD group (a 30% decrease in CT) and of the cingulate cortex in non-AD group (a 50-60% decrease in CT). Anxiety correlated in MCI patients with the cingulate gyrus and caudate, with a CT and V decrease of about 40%, while hallucinations were associated with left enthorinal gyrus and right amygdala and temporal pole. Agitation showed associations in the AD group with the frontal regions and the temporal pole, corresponding to a 30-40% decrease in CT. Euphoria, disinhibition and eating abnormalities were associated in the MCI group with the entorhinal, para-hippocampal and fusiform gyri, the temporal pole and the amygdala (with a 40-70% decrease in CT and V). Finally, aberrant motor behavior reported a significant association with frontal and cingulate regions with a 50% decrease in CT.ConclusionOur findings indicate that specific NPSs are associated with the structural involvement of the fronto-limbic circuit across different types of neurocognitive disorders. Factors, such as age and disease duration, can partly account for the variability of the associations observed.

Objectives: Despite extensive research, a clear understanding of the role of the interaction between lifestyle and socioeconomic status (SES) on cognitive health is still lacking. We investigated the joint association of socioeconomic factors in early to midlife and lifestyle in later life and Mild Cognitive Impairment (MCI). Design: Observational cross-sectional study. Setting: NutBrain study in northern Italy. Participants: 773 community-dwelling adults aged 65 years and older (73.2 ± 6.0 SD, 58.6% females) participating in the NutBrain study (2019–2023). Measurements: Three SES indicators (home ownership, educational level, occupation) and five lifestyle factors (adherence to Mediterranean diet, physical activity, smoking habits, social network, leisure activities) were selected. Each factor was scored and summed to calculate SES and healthy lifestyle scores; their joint effect was also examined. The association with MCI was assessed by logistic regression controlling for potential confounders. Sex-stratified analysis was performed. Results: In total, 24% of the subjects had MCI. The multivariable logistic model showed that a high SES and a high lifestyle score were associated with 81.8% (OR0.182; 95%CI 0.095−0.351), and 44.1% (OR0.559; 95%CI 0.323−0.968) lower odds of having MCI, respectively. When examining the joint effect of SES and lifestyle factors, the cognitive benefits of a healthy lifestyle were most pronounced in participants with low SES. A healthier lifestyle score was found to be significantly associated with lower odds of MCI, only in females. Conclusions: According to our findings, SES was positively associated with preserved cognitive function, highlighting the importance of active lifestyles in reducing socioeconomic health inequalities, particularly among those with a relatively low SES. Trial registration: Trial registration number NCT04461951, date of registration July 7, 2020 (retrospectively registered, ClinicalTrials.gov).

Behavioral and Psychological Symptoms of Dementia (BPSD) are a heterogeneous set of psychological and behavioral abnormalities seen in persons with dementia (PwD), significantly impacting their quality of life and that of their caregivers. Current assessment tools, such as the Neuropsychiatric Inventory (NPI), are limited by recall bias and lack of direct observation. This study aims to overcome this limitation by making caregiver reports more objective through the use of a novel instrument, referred to as the BPSDiary. This randomized controlled trial will involve 300 caregiver-PwD dyads. The objective is to evaluate whether the use of the BPSDiary could significantly reduce caregiver burden, assessed using the Zarit Burden Interview (ZBI), compared to usual care. The study will include adult PwD, caregivers living with or close to the patient, and BPSD related to the HIDA (hyperactivity, impulsivity, irritability, disinhibition, aggression, agitation) domain. Caregivers randomized to the intervention arm will use the BPSDiary to record specific BPSD, including insomnia, agitation/anxiety, aggression, purposeless motor behavior, and delusions/hallucinations, registering time of onset, severity, and potential triggers. The primary outcome will be the change in ZBI scores at 3 months, with secondary outcomes including changes in NPI scores, olanzapine equivalents, NPI-distress scores related to specific BPSD domains, and caregiver and physician satisfaction. The study will be conducted in 9 Italian centers, representing diverse geographic and sociocultural contexts. While potential limitations include the relatively short observation period and the focus on specific BPSD disturbances, the BPSDiary could provide physicians with objective data to tailor appropriate non-pharmacological and pharmacological interventions. Additionally, it may empower caregivers by encouraging reflection on BPSD triggers, with the potential to improve the quality of life for both PwD and their caregivers.Trial registryNCT05977855.

Abstract Neurofilament light chains (NfL) are neuron-specific cytoskeletal proteins whose plasmatic concentrations have been explored as a clinically useful marker in several types of dementia. Plasma concentrations of NfL are extremely low, and just two assays are commercially available for their study: one based on the SiMoA technology and one based on Ella. We thus studied plasma levels of NfL with both platforms to check the correlation between them and to assess their potential in the diagnosis of neurodegeneration. Plasma NfL levels were measured on 50 subjects: 18 healthy controls, 20 Alzheimer’s disease, and 12 frontotemporal dementia patients. Ella returned plasmatic NfL levels significantly higher than SiMoA, however the results were strongly correlated (r = 0.94), and a proportional coefficient of 0.58 between the two assays was calculated. Both assays detected higher plasma NfL levels in patients with dementia than in the control group (p 0.95). No difference was found between Alzheimer’s and Frontotemporal dementia either using SiMoA or Ella. In conclusion, both the analytical platforms resulted effective in analysing plasma levels of NfL. However, the correct interpretation of results requires the precise knowledge of the assay used.

Abstract The present study aimed to identify clusters of cognitive profiles as well as to explore the effects of these clusters on demographic/individual characteristics and on improvements after a computer-based cognitive training (CCT) in early cognitive impairment. Fifty-seven subjects underwent to an adaptive CCT for 3 weeks (4 individual face-to-face sessions/week of 45 min) and were evaluated at baseline (T0), post-intervention (T1), and after 6 (T2) and 12 (T3) months. Clusters of cognitive profiles were explored with k-means analysis. The analysis revealed two clusters, which were composed by 27 and 30 patients characterized by lower (Cluster 1) and higher (Cluster 2) cognitive functioning. At T1, cognitive performance improved in both groups, but Cluster 1 gained more benefits in global cognitive functioning than Cluster 2. However, at T3, Cluster 2 remained stable in its clinical condition, whereas Cluster 1 showed a pronounced worsening. In conclusion, Cluster 1 profile was associated with a more marked but also short-lasting responsiveness to CCT, whereas patients fitting with Cluster 2 characteristics seemed to obtain more CCT benefits in terms of stability or even delay of cognitive/functional decline. These findings may have relevant implications in informing the timing and modality of delivery of CCT.

ObjectiveDementias and mild cognitive impairment (MCI) are associated with variously combined changes in the neurotransmitter system and signaling, from neurotransmitter synthesis to synaptic binding. The study tested the hypothesis that different dementia subtypes and MCI may share similar reductions of brain availability in amino acid precursors (AAPs) of neurotransmitter synthesis and concomitant similar impairment in energy production and increase of oxidative stress, i.e., two important metabolic alterations that impact neurotransmission.Materials and methodsSixty-five demented patients (Alzheimer’s disease, AD, n = 44; frontotemporal disease, FTD, n = 13; vascular disease, VaD, n = 8), 10 subjects with MCI and 15 control subjects (CTRL) were recruited for this study. Cerebrospinal fluid (CSF) and plasma levels of AAPs, energy substrates (lactate, pyruvate), and an oxidative stress marker (malondialdehyde, MDA) were measured in all participants.ResultsDemented patients and subjects with MCI were similar for age, anthropometric parameters, biohumoral variables, insulin resistance (HOMA index model), and CSF neuropathology markers. Compared to age-matched CTRL, both demented patients and MCI subjects showed low CSF AAP tyrosine (precursor of dopamine and catecholamines), tryptophan (precursor of serotonin), methionine (precursor of acetylcholine) limited to AD and FTD, and phenylalanine (an essential amino acid largely used for protein synthesis) (p = 0.03 to

IntroductionNeural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission.MethodsWe used TVB to simulate brain networks, which are key for human brain function, in Alzheimer’s disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks.ResultsThe pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles.DiscussionThese TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.

BackgroundCOVID-19 has caused a parallel epidemic of fear, anxiety, depression, stress, and frustration, particularly among the most fragile and vulnerable individuals, such as older people and those with previous mental health disorders. The present study aims to investigate the association between pre-existing mental health disorders, particularly depressive symptoms and Mild Cognitive Impairment (MCI), and the fear of COVID-19 and to explore which cognitive domains were involved in coping with fear in older people.Materials and methodsIn April 2020, we conducted a phone-interview questionnaire on community-dwelling older adults living in Lombardy Region (Italy) who participated in the NutBrain study. At baseline, socio-demographic characteristics along with lifestyles, and medical history were recorded. Participants underwent a neuropsychological battery exploring the global cognitive function and specific cognitive domains, to detect cases of MCI. The Center for Epidemiologic Studies Depression scale (CES-D) was used for screening depressive symptoms. During the phone survey, respondents were assessed using a structured questionnaire querying about fear of the COVID-19 pandemic. We performed multivariate logistic regression models to study the association between MCI and depressive symptomatology and fear. We also explored which cognitive domains were associated with fear. Odds Ratios (OR) with Confidence Intervals (95%CI) were estimated adjusting for potential confounders.ResultsOut of the 351 respondents (mean age 73.5 ± 6.1 years, 59.8% women, 49.1% high education), at baseline, 22.9% had MCI and 18.8% had depressive symptoms. In the multivariate analyses gender, age, and body mass index were significantly associated with the fear score. Considering different domains of fear, MCI was associated with fear of being infected themselves (OR 2.55, 95%CI 1.39–4.70) while depressive symptoms were associated with fear of contagion for family members (OR 2.38, 95%CI 1.25–4.52). Impaired executive cognitive function was positively associated with the highest tertile of the fear score (OR 3.28, 95%CI 1.37–7.74) and with fear of contagion for themselves (OR 3.39, 95%CI 1.61-7.17).ConclusionOlder adults experienced different fear reactions, particularly when suffering from neurocognitive disorders and depressive symptoms; executive dysfunction was associated with increased fear. These results highlighted the need to pay attention to the psychological effects of the outbreak of COVID-19 to target intervention, especially among vulnerable subgroups of individuals.Clinical trial registration[ClinicalTrials.gov], identifier [NCT04461951].

Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients’ excitation/inhibition profiles on neurodegenerative diseases including Alzheimer’s Disease, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. In this work, we used The Virtual Brain (TVB) simulation platform to simulate brain dynamics in healthy and neurodegenerative conditions and to extract information about the excitatory/inhibitory balance in single subjects. The brain structural and functional connectomes were extracted from 3T-MRI (Magnetic Resonance Imaging) scans and TVB nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. Simulations were performed including both cerebral and cerebellar nodes and their structural connections to explore cerebellar impact on brain dynamics generation. The potential for clinical translation of TVB derived biophysical parameters was assessed by exploring their association with patients’ cognitive performance and testing their discriminative power between clinical conditions. Our results showed that TVB biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer’s Disease and stronger N-methyl-D-aspartate (NMDA) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed us to perform an advanced analysis of patients’ conditions. In backward regressions, TVB-derived parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of TVB parameters and neuropsychological scores significantly improved the discriminative power between clinical conditions. Moreover, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. Importantly, the integration of cerebro-cerebellar loops in simulations improved TVB predictive power, i.e., the correlation between experimental and simulated functional connectivity in all pathological conditions supporting the cerebellar role in brain function disrupted by neurodegeneration. Overall, TVB simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.

BackgroundBehavioral and psychological symptoms of dementia (BPSD) have a high prevalence, and their presence is associated with a severe impact in terms of social costs. However, dedicated clinical tools or biomarkers to detect these symptoms are lacking. Thus, BPSD management in clinical settings is challenging. The aim of this study was to investigate the perception and the treatment strategies for BPSD in Italian centers working in the dementia field.MethodsA multicenter, national survey was developed by BPSD Study Group of the Italian Neurological Society for Dementia (SINDEM). The survey consisted of a semi-structured questionnaire that was e-mailed to SINDEM members, dementia centers part of the national network of memory clinics (Centers for Cognitive Deterioration and Dementia [CDCD]), and clinicians working in dementia care settings. The questions were focused on (1) perceived global frequency and relevance of BPSD; (2) tools used to assess BPSD; (3) pharmacological treatment for psychosis, apathy, agitation, aggression, depression, anxiety, sleep, and nutrition disturbances; (4) non-pharmacological treatments; (5) drugs side effects.ResultsOne-hundred and thirty-six clinicians participated in this study. Seventy-nine participants worked in a CDCD and 57 in other settings. The perceived frequency of BPSD was 74%. BPSD are detected by means of a clinical assessment for 96.3% or a caregiver interview for 97%. For psychosis treatment the first choice was atypical antipsychotics (83.3%), followed by typical antipsychotic (8.9%) and antidepressants (4.8%). For agitation, atypical antipsychotics were the first-choice treatment in 64% of cases and antidepressants in 16.1%. For aggression, the most used drugs were atypical antipsychotics (82.9%). For anxiety, 55.2% use antidepressants, 17.9% use atypical antipsychotics, and 16.9% use benzodiazepines. Interestingly, most of the centers apply non-pharmacological treatments for BPSD. Some differences emerged comparing the responses from CDCD and other care settings.ConclusionThe survey results revealed many differences in BPSD perception, treatment options, and observed side effect according to the clinical setting. This variability can be explained by the absence of clear guidelines, by differences in patients' characteristics, and by clinical practice based on subjective experience. These results suggest that producing guidelines for the pharmacological treatment of BPSD is a major need.

ObjectivesThere is a lack of effective biomarkers for neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia. Extracellular vesicle (EV) RNA cargo can have an interesting potential as a non-invasive biomarker for NDs. However, the knowledge about the abundance of EV-mRNAs and their contribution to neurodegeneration is not clear.MethodsLarge and small EVs (LEVs and SEVs) were isolated from plasma of patients and healthy volunteers (control, CTR) by differential centrifugation and filtration, and RNA was extracted. Whole transcriptome was carried out using next generation sequencing (NGS).ResultsCoding RNA (i.e., mRNA) but not long non-coding RNAs (lncRNAs) in SEVs and LEVs of patients with ALS could be distinguished from healthy CTRs and from other NDs using the principal component analysis (PCA). Some mRNAs were found in commonly deregulated between SEVs of patients with ALS and frontotemporal dementia (FTD), and they were classified in mRNA processing and splicing pathways. In LEVs, instead, one mRNA and one antisense RNA (i.e., MAP3K7CL and AP003068.3) were found to be in common among ALS, FTD, and PD. No deregulated mRNAs were found in EVs of patients with AD.ConclusionDifferent RNA regulation occurs in LEVs and SEVs of NDs. mRNAs and lncRNAs are present in plasma-derived EVs of NDs, and there are common and specific transcripts that characterize LEVs and SEVs from the NDs considered in this study.

Background: Behavioral and psychological symptoms of dementia (BPSD) are a distressful condition. We aimed to investigate the BPSD distribution in subjects with cognitive impairment, and the potential correlations between BPSD and neurodegeneration in terms of cerebrospinal fluid (CSF) tau and brain atrophy.Methods: One-hundred patients with mild cognitive impairment (MCI) or dementia (Alzheimer’s disease, AD; Lewy-body disease, LBD; frontotemporal dementia, FTD; vascular dementia, VD) underwent a complete diagnostic workup, including 3T-MRI and/or CT and CSF. Cortical atrophy was assessed with medial temporal atrophy (MTA), posterior atrophy (PA), and global cortical atrophy-frontal lobe (GCA-F) scales. BPSD were rated using the Neuropsychiatric Inventory (NPI), and BPSD clusters were defined according to the European Alzheimer Disease Consortium.Results: Delusions, hallucinations, and psychosis cluster were differently distributed among the diagnostic groups (p < 0.05, p < 0.001, and p < 0.05), with LBD patients showing higher scores for hallucinations (vs. MCI, p < 0.001, and AD, p < 0.05) and psychosis cluster (vs. MCI, p < 0.05). In primary dementias, we found a negative correlation between NPI total score and tau levels (p = 0.08), confirmed by beta regression (p < 0.01), while a positive non-significant relationship was observed in MCI. Higher GCA-F scores were associated with delusions and apathy (p < 0.05, on both hemispheres) and hallucinations (left: p < 0.01, right: p < 0.05). GCA-F scores were positively correlated with psychosis cluster (right: p < 0.05), and agitation/aggression (left: p < 0.05). Conversely, nighttime disturbances were positively correlated with both GCA-F and MTA scores (left: p < 0.01; right: p < 0.05).Conclusion: Our results suggest that psychotic symptoms are significantly more represented in LBD patients and that CSF tau and frontal atrophy are associated with the occurrence and severity of BPSD in clinical practice. Longitudinal studies are however required to ascertain their actual predictive value.

BackgroundFrontotemporal Spectrum Disorder (FTSD) and Amyotrophic Lateral Sclerosis (ALS) are neurodegenerative diseases often considered as a continuum from clinical, epidemiologic, and genetic perspectives. We used localized brain volume alterations to evaluate common and specific features of FTSD, FTSD-ALS, and ALS patients to further understand this clinical continuum.MethodsWe used voxel-based morphometry on structural magnetic resonance images to localize volume alterations in group comparisons: patients (20 FTSD, seven FTSD-ALS, and 18 ALS) versus healthy controls (39 CTR), and patient groups between themselves. We used mean whole-brain cortical thickness (CT¯) to assess whether its correlations with local brain volume could propose mechanistic explanations of the heterogeneous clinical presentations. We also assessed whether volume reduction can explain cognitive impairment, measured with frontal assessment battery, verbal fluency, and semantic fluency.ResultsCommon (mainly frontal) and specific areas with reduced volume were detected between FTSD, FTSD-ALS, and ALS patients, confirming suggestions of a clinical continuum, while at the same time defining morphological specificities for each clinical group (e.g., a difference of cerebral and cerebellar involvement between FTSD and ALS). CT¯ values suggested extensive network disruption in the pathological process, with indications of a correlation between cerebral and cerebellar volumes and CT¯ in ALS. The analysis of the neuropsychological scores indeed pointed toward an important role for the cerebellum, along with fronto-temporal areas, in explaining impairment of executive, and linguistic functions.ConclusionWe identified common elements that explain the FTSD-ALS clinical continuum, while also identifying specificities of each group, partially explained by different cerebral and cerebellar involvement.

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify—CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup.Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD (n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools.Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from “slight” to “significant” in 80% of the cases.Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology.

BackgroundIn March 2020, the World Health Organization declared a global pandemic due to the novel coronavirus SARS-CoV-2 and several governments planned a national quarantine in order to control the virus spread. Acute psychological effects of quarantine in frail elderly subjects with special needs, such as patients with dementia, have been poorly investigated. The aim of this study was to assess modifications of neuropsychiatric symptoms during quarantine in patients with dementia and their caregivers.MethodsThis is a sub-study of a multicenter nation-wide survey. A structured telephone interview was delivered to family caregivers of patients with diagnosis of Alzheimer disease (AD), dementia with Lewy bodies (DLB), frontotemporal dementia (FTD), and vascular dementia (VD), followed regularly at 87 Italian memory clinics. Variations in behavioral and psychological symptoms (BPSD) were collected after 1 month since quarantine declaration and associations with disease type, severity, gender, and caregiver’s stress burden were analyzed.ResultsA total of 4,913 caregivers participated in the survey. Increased BPSD was reported in 59.6% of patients as worsening of preexisting symptoms (51.9%) or as new onset (26%), and requested drug modifications in 27.6% of these cases. Irritability, apathy, agitation, and anxiety were the most frequently reported worsening symptoms and sleep disorder and irritability the most frequent new symptoms. Profile of BPSD varied according to dementia type, disease severity, and patients’ gender. Anxiety and depression were associated with a diagnosis of AD (OR 1.35, CI: 1.12–1.62), mild to moderate disease severity and female gender. DLB was significantly associated with a higher risk of worsening hallucinations (OR 5.29, CI 3.66–7.64) and sleep disorder (OR 1.69, CI 1.25–2.29), FTD with wandering (OR 1.62, CI 1.12–2.35), and change of appetite (OR 1.52, CI 1.03–2.25). Stress-related symptoms were experienced by two-thirds of caregivers and were associated with increased patients’ neuropsychiatric burden (p

During the recent coronavirus disease 2019 (COVID-19) outbreak in Northern Italy, we observed a 57-year-old man developing acute motor-sensory axonal neuropathy, a variant of Guillain–Barré syndrome (GBS), 12 days after severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection. Similarly to other bacterial and viral infections, dysregulation of the immune system due to post-infectious mechanisms, such as the molecular mimicry, could lead to an indirect damage of the peripheral nervous system related to SARS-CoV-2. GBS causes motor dysfunctions that are not easily recognizable in non-neurological settings or in patients requiring ventilatory assistance. Several reports also suggested that GBS and Miller Fisher syndrome (MFS) could be neurological complications of COVID-19. Therefore, we performed a review of the 29 articles so far published, describing 33 GBS cases and five MFS cases associated with SARS-CoV-2 infection. We recommend awareness of this rare, but treatable, neurological syndrome, which may also determine a sudden and otherwise unexplained respiratory deterioration in COVID-19 patients.

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD–AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a “mixed VD–AD dementia” (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations.

Objective: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer’s disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia.Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients’ classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors.Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance.Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.

Background: Chronic headache is one of the most common pain conditions, often leading to symptomatic drug overuse. The aim of this study was to provide data on symptomatic drug consumption in an Italian outpatient population and to describe how the clinical picture of headache may change after headache experts take charge of the care of affected individuals.Methods: A total of 199 adults complaining of chronic headache were recruited through 32 pharmacies in the Pavia health district. Participants underwent four evaluations: a baseline assessment (T0) and three follow-up evaluations performed by a neurologist at 3, 6, and 12 months (T3, T6, and T12, respectively). On each occasion, they underwent a complete neurological assessment and received therapeutic adjustments to achieve better management of their headache.Results: On the basis of a preliminary telephone interview, the prevalence rates of chronic headache and medication overuse headache (MOH) were 16 and 12%, respectively. At 12 months of follow-up, we observed a significant decrease in the frequency of attacks (T0: 9 ± 9/month vs. T12: 2 ± 2/month; p < 0.001), in the number of days/month with headache (T0: 11 ± 9 vs. T12: 4 ± 4; p < 0.001) and in single attack duration (T0: 34 ± 30 h vs. T12: 10 ± 19 h; p < 0.001). Careful headache management resulted in a significant decrease in analgesic consumption (T0: 12 ± 16 vs. T12: 4 ± 6 doses/month; p = 0.014) and a significant increase in quality of life, measured using the Migraine Disability Assessment Scale (MIDAS) and Headache Under-Response to Treatment (HURT) scales (p < 0.001).Conclusions: Headache management by a specialist is more effective than self-treatment, resulting in an overall benefit for headache patients.

Introduction: The aim of this study was to compare the effect of ramipril/canrenone versus ramipril/hydrochlorothiazide (HCTZ) combination on atrial fibrillation (AF) recurrence in type 2 diabetic hypertensives with and without cardiac autonomic neuropathy (CAN). Material and methods : A total of 289 hypertensive type 2 diabetic patients, 95 with CAN, in sinus rhythm but with at least two episodes of AF in the previous 6 months were randomized to ramipril 5 mg plus canrenone 50 mg (titrated to 10/100 mg) or to ramipril 5 mg plus HCTZ 12.5 mg (titrated to 10/25 mg) or to amlodipine 5 mg (titrated to 10 mg) for 1 year. Clinic blood pressure (BP) and a 24-h ECG were evaluated monthly. Patients were asked to report any episode of symptomatic AF and to perform an ECG as early as possible. Serum procollagen type I carboxy-terminal peptide (PIP) and carboxy-terminal telopeptide of collagen type I (CITP) were evaluated before and after each treatment period. Results : Blood pressure was similarly and significantly reduced by all treatments. A total of 51% of patients with amlodipine had a recurrence of AF, as did 31% of patients with ramipril/HCTZ (p < 0.05 vs amlodipine) and 13% of patients with ramipril/canrenone (p < 0.01 vs amlodipine and p < 0.05 vs ramipril/HCTZ). A similar trend was found in diabetic patients with CAN. Both combinations reduced PIP and increased CITP, but the effects of ramipril/canrenone were significantly more marked. Conclusions : These findings suggest that in type 2 diabetic hypertensives, ramipril/canrenone treatment was more effective than ramipril/HCTZ in reducing AF recurrence. This could be related to the greater improvement in cardiac fibrosis.

Objectives: The medial temporal lobe atrophy (MTA) and the posterior atrophy (PA) scales allow to assess the degree hippocampal and parietal atrophy from magnetic resonance imaging (MRI) scans. Despite reliable, easy and widespread employment, appropriate normative values are still missing. We aim to provide norms for the Italian population. Methods: Two independent raters assigned the highest MTA and PA score between hemispheres, based on 3D T1-weighted MRI of 936 Italian Brain Normative Archive subjects (age: mean ± SD: 50.2 ± 14.7, range: 20–84; MMSE>26 or CDR = 0). The inter-rater agreement was assessed with the absolute intraclass correlation coefficient (aICC). We assessed the association between MTA and PA scores and sociodemographic features and APOE status, and normative data were established by age decade based on percentile distributions. Results: Raters agreed in 90% of cases for MTA (aICC = 0.86; 95% CI = 0.69–0.98) and in 86% for PA (aICC = 0.82; 95% CI = 0.58–0.98). For both rating scales, score distribution was skewed, with MTA = 0 in 38% of the population and PA = 0 in 52%, while a score ≥ 2 was only observed in 12% for MTA and in 10% for PA. Median denoted overall hippocampal (MTA: median = 1, IQR = 0–1) and parietal (PA: median = 0, IQR = 0–1) integrity. The 90th percentile of the age-specific distributions increased from 1 (at age 20–59) for both scales, to 2 for PA over age 60, and up to 4 for MTA over age 80. Gender, education and APOE status did not significantly affect the percentile distributions in the whole sample, nor in the subset over age 60. Conclusions: Our normative data for the MTA and PA scales are consistent with previous studies and overcome their main limitations (in particular uneven representation of ages and missing percentile distributions), defining the age-specific norms to be considered for proper brain atrophy assessment. Keywords: Medial temporal atrophy, Posterior atrophy, Normative values, Magnetic resonance imaging, Visual assessment

Alzheimer disease (AD) and vascular dementia (VaD) together represent the majority of dementia cases. Since their neuropsychological profiles often overlap and white matter lesions are observed in elderly subjects including AD, differentiating between VaD and AD can be difficult. Characterization of these different forms of dementia would benefit by identification of quantitative imaging biomarkers specifically sensitive to AD or VaD. Parameters of microstructural abnormalities derived from diffusion tensor imaging (DTI) have been reported to be helpful in differentiating between dementias, but only few studies have used them to compare AD and VaD with a voxelwise approach. Therefore, in this study a whole brain statistical analysis was performed on DTI data of 93 subjects (31 AD, 27 VaD, and 35 healthy controls—HC) to identify specific white matter patterns of alteration in patients affected by VaD and AD with respect to HC. Parahippocampal tracts were found to be mainly affected in AD, while VaD showed more spread white matter damages associated with thalamic radiations involvement. The genu of the corpus callosum was predominantly affected in VaD, while the splenium was predominantly affected in AD revealing the existence of specific patterns of alteration useful in distinguishing between VaD and AD. Therefore, DTI parameters of these regions could be informative to understand the pathogenesis and support the etiological diagnosis of dementia. Further studies on larger cohorts of subjects, characterized for brain amyloidosis, will allow to confirm and to integrate the present findings and, furthermore, to elucidate the mechanisms of mixed dementia. These steps will be essential to translate these advances to clinical practice.

Introduction: Behavioral and Psychological Symptoms of Dementia (BPSD) are a heterogeneous set of psychological reactions and abnormal behaviors in people with dementia (PwD). Current assessment tools, like the Neuropsychiatric Inventory (NPI), only rely on caregiver assessment of BPSD and are therefore prone to bias. Materials and methods: A multidisciplinary team developed the BPSD-SINDEM scale as a three-part instrument, with two questionnaires administered to the caregiver (evaluating BPSD extent and caregiver distress) and a clinician-rated observational scale. This first instrument was tested on a sample of 33 dyads of PwD and their caregivers, and the results were qualitatively appraised in order to revise the tool through a modified Delphi method. During this phase, the wording of the questions was slightly changed, and the distress scale was changed into a coping scale based on the high correlation between extent and distress (r = 0.94). The final version consisted of three 17-item subscales, evaluating BPSD extent and caregiver coping, and the unchanged clinician-rated observational scale. Results: This tool was quantitatively validated in a sample of 208 dyads. It demonstrated good concurrent validity, with the extent subscale correlating positively with NPI scores (r = 0.64, p < 0.001) and the coping subscale inversely correlating with NPI distress (r = −0.20, p = 0.004). Diagnosis (Lewy body dementia and frontotemporal dementia), medication (antidepressants and antipsychotics), caregiver, and PwD age predicted BPSD burden on the BPSD-SINDEM scale. Caregiver coping was influenced by diagnosis (Alzheimer's and Lewy body dementia) and benzodiazepine. Discussion: The BPSD-SINDEM scale offers a more comprehensive approach compared to NPI, by combining caregiver ratings with clinician observations. The design of the scale allows for rapid administration in diverse clinical contexts, with the potential to enhance the understanding and management of BPSD. [ABSTRACT FROM AUTHOR]