Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD) are the two major neurodegenerative diseases with distinct clinical and neuropathological profiles. The aim of this report is to conduct a ...population-based investigation in well-characterized APP, PSEN1, PSEN2, MAPT, GRN, and C9orf72 mutation carriers/pedigrees from the north, the center, and the south of Italy. We retrospectively analyzed the data of 467 Italian individuals. We identified 21 different GRN mutations, 20 PSEN1, 11 MAPT, 9 PSEN2, and 4 APP. Moreover, we observed geographical variability in mutation frequencies by looking at each cohort of participants, and we observed a significant difference in age at onset among the genetic groups. Our study provides evidence that age at onset is influenced by the genetic group. Further work in identifying both genetic and environmental factors that modify the phenotypes in all groups is needed. Our study reveals Italian regional differences among the most relevant AD/FTD causative genes and emphasizes how the collaborative studies in rare diseases can provide new insights to expand knowledge on genetic/epigenetic modulators of age at onset.
We aimed to assess diagnostic accuracy of plasma p-tau181 and NfL separately and in combination in discriminating Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) patients ...carrying Alzheimer's Disease (AD) pathology from non-carriers; to propose a flowchart for the interpretation of the results of plasma p-tau181 and NfL. We included 43 SCD, 41 MCI and 21 AD-demented (AD-d) patients, who underwent plasma p-tau181 and NfL analysis. Twenty-eight SCD, 41 MCI and 21 AD-d patients underwent CSF biomarkers analysis (Aβ1-42, Aβ1-42/1-40, p-tau, t-tau) and were classified as carriers of AD pathology (AP+) it they were A+/T+ , or non-carriers (AP-) when they were A-, A+/T-/N-, or A+/T-/N+ according to the A/T(N) system. Plasma p-tau181 and NfL separately showed a good accuracy (AUC = 0.88), while the combined model (NfL + p-tau181) showed an excellent accuracy (AUC = 0.92) in discriminating AP+ from AP- patients. Plasma p-tau181 and NfL results were moderately concordant (Coehn's k = 0.50, p < 0.001). Based on a logistic regression model, we estimated the risk of AD pathology considering the two biomarkers: 10.91% if both p-tau181 and NfL were negative; 41.10 and 76.49% if only one biomarker was positive (respectively p-tau18 and NfL); 94.88% if both p-tau181 and NfL were positive. Considering the moderate concordance and the risk of presenting an underlying AD pathology according to the positivity of plasma p-tau181 and NfL, we proposed a flow chart to guide the combined use of plasma p-tau181 and NfL and the interpretation of biomarker results to detect AD pathology.
Plasma biomarkers are preferable to invasive and expensive diagnostic tools, such as neuroimaging and lumbar puncture that are gold standard in the clinical management of Alzheimer's Disease (AD). ...Here, we investigated plasma Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light Chain (NfL) and Phosphorylated-tau-181 (pTau 181) in AD and in its early stages: Subjective cognitive decline (SCD) and Mild cognitive impairment (MCI).
This study included 152 patients (42 SCD, 74 MCI and 36 AD). All patients underwent comprehensive clinical and neurological assessment. Blood samples were collected for Apolipoprotein E (APOE) genotyping and plasma biomarker (GFAP, NfL, and pTau 181) measurements. Forty-three patients (7 SCD, 27 MCI, and 9 AD) underwent a follow-up (FU) visit after 2 years, and a second plasma sample was collected. Plasma biomarker levels were detected using the Simoa SR-X technology (Quanterix Corp.). Statistical analysis was performed using SPSS software version 28 (IBM SPSS Statistics). Statistical significance was set at p < 0.05.
GFAP, NfL and pTau 181 levels in plasma were lower in SCD and MCI than in AD patients. In particular, plasma GFAP levels were statistically significant different between SCD and AD (
=0.003), and between MCI and AD (
=0.032). Plasma NfL was different in SCD vs MCI (
=0.026), SCD vs AD (
<0.001), SCD vs AD FU (
<0.001), SCD FU vs AD (
), SCD FU vs AD FU (
), MCI vs AD (
=0.002), MCI FU vs AD (
=0.003), MCI FU vs AD FU (
=0.003) and MCI vs AD FU (
=0.003). Plasma pTau 181 concentration was significantly different between SCD and AD (
=0.001), MCI and AD (
=0.026), MCI FU and AD (
=0.020). In APOE ϵ4 carriers, a statistically significant increase in plasma NfL (
) and pTau 181 levels was found (
Moreover, an association emerged between age at disease onset and plasma GFAP (p = 0.021) and pTau181 (p < 0.001) levels.
Plasma GFAP, NfL and pTau 181 are promising biomarkers in the diagnosis of the prodromic stages and prognosis of dementia.
Background and objectives: Huntington’s disease (HD) is characterized by motor, cognitive and psychiatric manifestations and caused by an expansion of CAG repeats over 35 triplets on the huntingtin ...(HTT) gene. However, expansions in the range 27–35 repeats (intermediate allele) can be associated with pathological phenotypes. The onset of HD is conventionally defined by the onset of motor symptoms, but psychiatric disturbances can precede the motor phase by up to twenty years. The aims of the present study are to identify HD patients in the pre-motor phase of the disease among patients diagnosed with bipolar disorders and evaluate any differences between bipolar patients carrying the normal HTT allele and patients with the expanded HTT gene. Methods: We assessed the HTT genotype in an Italian cohort of 69 patients who were affected by either type 1 or type 2 bipolar disorder. Results: No patient was found to be a carrier of the pathological HTT allele, but 10% of bipolar subjects carried an intermediate allele. Carriers of the intermediate allele were older at the onset of psychiatric symptoms than non-carriers. Conclusion: The pathological HTT gene was not associated with bipolar disorder, while we found a higher frequency of the intermediate allele among the bipolar population with respect to healthy controls. The identification of this subset of bipolar subjects has implications for the clinical management of patients and their family members and promotes further investigation into possible pathological mechanisms common to both HD and bipolar disorder.
•EEG reveals differences between prodromal stages of Alzheimer’s Disease.•Microstates analysis yield more inter-condition differences than spectral and network metrics.•Microstate C topography ...differs significantly in patients positive to cerebrospinal fluid Alzheimer’s biomarkers.
Alzheimer’s disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.
As disease-modifying therapies (DMTs) for Alzheimer's disease (AD) are becoming a reality, there is an urgent need to select cost-effective tools that can accurately identify patients in the earliest ...stages of the disease. Subjective Cognitive Decline (SCD) is a condition in which individuals complain of cognitive decline with normal performances on neuropsychological evaluation. Many studies demonstrated a higher prevalence of Alzheimer's pathology in patients diagnosed with SCD as compared to the general population. Consequently, SCD was suggested as an early symptomatic phase of AD. We will describe the study protocol of a prospective cohort study (PREVIEW) that aim to identify features derived from easily accessible, cost-effective and non-invasive assessment to accurately detect SCD patients who will progress to AD dementia.
We will include patients who self-referred to our memory clinic and are diagnosed with SCD. Participants will undergo: clinical, neurologic and neuropsychological examination, estimation of cognitive reserve and depression, evaluation of personality traits, APOE and BDNF genotyping, electroencephalography and event-related potential recording, lumbar puncture for measurement of Aβ
, t-tau, and p-tau concentration and Aβ
/Aβ
ratio. Recruited patients will have follow-up neuropsychological examinations every two years. Collected data will be used to train a machine learning algorithm to define the risk of being carriers of AD and progress to dementia in patients with SCD.
This is the first study to investigate the application of machine learning to predict AD in patients with SCD. Since all the features we will consider can be derived from non-invasive and easily accessible assessments, our expected results may provide evidence for defining cost-effective and globally scalable tools to estimate the risk of AD and address the needs of patients with memory complaints. In the era of DMTs, this will have crucial implications for the early identification of patients suitable for treatment in the initial stages of AD.
NCT05569083.
In this spectrum, seven biomarkers have attained widely recognized diagnostic relevance, including low levels of the 42-residue amyloid beta (Aβ42) and high concentrations of total tau (T-tau) and ...phosphorylated tau (P-tau) in the cerebrospinal fluid (CSF), high cortical amyloid deposition and tau deposition measured with positron emission tomography (PET), poor brain glucose metabolism measured with fluoro-deoxyglucose PET, and significant brain atrophy imaged with magnetic resonance imaging. The mean and individual demographic characteristics of both groups, values of the classical CSF biomarkers (levels of P-tau, T-tau, Aβ42 and Aβ42/Aβ40 ratio), percentages of patients with the ε4 allele of the Apolipoprotein E (APOE) gene and scores of mini-mental state examination (MMSE) tests are shown in Additional file 1: ...the AD CSFs were characterized by higher values of LSI from large protein species in the DLS distributions and higher ability to induce high cytosolic Ca2+ levels when added to the medium of cultured cells. ...these results extend our attention from individual specific proteins to the status of the entire proteome in the CSF for the assessment of an AD-associated biological profile.
is a gene containing a key region of CAG repeats. When expanded beyond 39 repeats, Huntington disease (HD) develops.
genes with <35 repeats are not associated with HD. The biological function of CAG ...repeat expansion below the non-pathological threshold is not well understood. In fact higher number of repeats in HTT confer advantageous changes in brain structure and general intelligence, but several studies focused on establishing the association between CAG expansions and susceptibility to psychiatric disturbances and to other neurodegenerative disease than HD. We hypothesized that
CAG repeat length below the pathological threshold might influence mood and personality traits in a longitudinal sample of individuals with Subjective Cognitive Decline.
We included 54 patients with SCD. All patients underwent an extensive neuropsychological battery at baseline,
genotyping and analysis of
alleles. We used the Big Five Factors Questionnaire (BFFQ) and Hamilton Depression Rating Scale (HDRS), respectively, to assess personality traits of patients and depression at baseline. Patients who did not progress to Mild Cognitive Impairment (MCI) had at least 5-year follow-up time.
In the whole sample, CAG repeat number in the shorter
allele was inversely correlated with conscientiousness (Pearson = -0.364,
= 0.007). There was no correlation between HDRS and CAG repeats. During the follow-up, 14 patients 25.93% (95% C.I. = 14.24-37.61) progressed to MCI (MCI
) and 40 74.07% (95% C.I. = 62.39-85.76) did not (MCI
). When we performed the same analysis in the MCI
group we found that: CAG repeat length on the shorter allele was inversely correlated with energy (Pearson = 0.639,
= 0.014) and conscientiousness (Pearson = -0.695,
= 0.006). CAG repeat length on the longer allele was inversely correlated with conscientiousness (Pearson = -0.901,
< 0.001) and directly correlated with emotional stability (Pearson = 0.639,
= 0.014). These associations were confirmed also by multivariate analysis. We found no correlations between BFFQ parameters and CAG repeats in the MCI
group.
Personality traits and CAG repeat length in the intermediate range have been associated with progression of cognitive decline and neuropathological findings consistent with AD. We showed that CAG repeat lengths in the
gene within the non-pathological range influence personality traits.
Due to continuous advances in intensive care technology and neurosurgical procedures, the number of survivors from severe acquired brain injuries (sABIs) has increased considerably, raising several ...delicate ethical issues. The heterogeneity and complex nature of the neurological damage of sABIs make the detection of predictive factors of a better outcome very challenging. Identifying the profile of those patients with better prospects of recovery will facilitate clinical and family choices and allow to personalize rehabilitation. This paper describes a multicenter prospective study protocol, to investigate outcomes and baseline predictors or biomarkers of functional recovery, on a large Italian cohort of sABI survivors undergoing postacute rehabilitation.
All patients with a diagnosis of sABI admitted to four intensive rehabilitation units (IRUs) within 4 months from the acute event, aged above 18, and providing informed consent, will be enrolled. No additional exclusion criteria will be considered. Measures will be taken at admission (T0), at three (T1) and 6 months (T2) from T0, and follow-up at 12 and 24 months from onset, including clinical and functional data, neurophysiological results, and analysis of neurogenetic biomarkers.
Advanced machine learning algorithms will be cross validated to achieve data-driven prediction models. To assess the clinical applicability of the solutions obtained, the prediction of recovery milestones will be compared to the evaluation of a multiprofessional, interdisciplinary rehabilitation team, performed within 2 weeks from admission.
Identifying the profiles of patients with a favorable prognosis would allow customization of rehabilitation strategies, to provide accurate information to the caregivers and, possibly, to optimize rehabilitation outcomes.
The application and validation of machine learning algorithms on a comprehensive pool of clinical, genetic, and neurophysiological data can pave the way toward the implementation of tools in support of the clinical prognosis for the rehabilitation pathways of patients after sABI.
The complex nature of stroke sequelae, the heterogeneity in rehabilitation pathways, and the lack of validated prediction models of rehabilitation outcomes challenge stroke rehabilitation quality ...assessment and clinical research. An integrated care pathway (ICP), defining a reproducible rehabilitation assessment and process, may provide a structured frame within investigated outcomes and individual predictors of response to treatment, including neurophysiological and neurogenetic biomarkers. Predictors may differ for different interventions, suggesting clues to personalize and optimize rehabilitation. To date, a large representative Italian cohort study focusing on individual variability of response to an evidence-based ICP is lacking, and predictors of individual response to rehabilitation are largely unexplored. This paper describes a multicenter study protocol to prospectively investigate outcomes and predictors of response to an evidence-based ICP in a large Italian cohort of stroke survivors undergoing post-acute inpatient rehabilitation.
All patients with diagnosis of ischemic or hemorrhagic stroke confirmed both by clinical and brain imaging evaluation, admitted to four intensive rehabilitation units (adopting the same stroke rehabilitation ICP) within 30 days from the acute event, aged 18+, and providing informed consent will be enrolled (expected sample: 270 patients). Measures will be taken at admission (T0), at discharge (T1), and at follow-up 6 months after a stroke (T2), including clinical data, nutritional, functional, neurological, and neuropsychological measures, electroencephalography and motor evoked potentials, and analysis of neurogenetic biomarkers.
In addition to classical multivariate logistic regression analysis, advanced machine learning algorithms will be cross-validated to achieve data-driven prognosis prediction models.
By identifying data-driven prognosis prediction models in stroke rehabilitation, this study might contribute to the development of patient-oriented therapy and to optimize rehabilitation outcomes.
ClinicalTrials.gov, NCT03968627. https://www.clinicaltrials.gov/ct2/show/NCT03968627?term=Cecchi&cond=Stroke&draw=2&rank=2.
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