saliva and extracellular vesicles for neurodegenerative diseases

Conditions: Neurodegenerative Diseases; Parkinson Disease; Alzheimer Disease; Parkinsonism; Mild Cognitive Impairment (MCI); Prodromal Parkinson&#39;s Disease

Summary: early diagnosis of neurodegenerative diseases (ndds) and accurate patient profiling are key goals needed to tailor prompt personalized therapeutic strategies that can significantly impact disease progression and patients' quality of life. the project will validate a novel, cost-effective and quick biophotonic-based method for early and differential diagnosis of ndds (parkinson's disease, atypical parkinsonisms, alzheimer's disease) and for routine clinical monitoring of ndd progression (longitudinal study). raman spectroscopy (rs) will be applied to biochemically profile saliva and salivaderived extracellular vesicles (sevs) and to identify a spectroscopic biomarker for ndds. optimized protocols for rs will be used to concomitantly evaluate saliva and sevs from people with ndds and to detect salivary changes in the biochemical profile, with special focus on ev-associated components. the accuracy of the method in discriminating ndds at different disease stages and during disease progression will be verified. a nanotechnology-based biomolecular characterization of saliva and sev will clarify the involvement of specific pathological molecules in ndds progression.

background: neurodegenerative diseases (ndds) are a miscellaneous group of disorders that variably affect individuals, with many subtle distinctions and different speeds across individuals and syndromes. the evolution of ndds involves cognition, behavior and motor domains of clinical assessment that result in lifelong functional and social impairments with high economic and social costs. the biochemical pathophysiological drivers occur far earlier than symptoms appearance making the identification of subjects with preclinical disease the basis for early diagnosis, needed for an effective therapy. the clinical definition of ndds is basically insufficient, but the molecular signals from the brain can lead to the identification of a biomarker that can be measured periodically in a non-invasive way. therefore, a disease-specific biomarker is needed. the possibility of identifying specific markers for ndds within saliva has recently emerged. saliva and salivary extracelluler vesicles (sevs) are vehicles for molecules associated with neuronal damage and neuroinflammation. their isolation allows an enrichment of the molecules involved in the pathogenetic mechanisms of ndds, improving their quantification. raman spectroscopy (rs) is a method useful for the exhaustive biochemical characterization of saliva and its vesicular component, without staining and labeling procedures, highly informative, rapid and sustainable. in a rapid, sensitive and non-destructive way, rs provides with a spectrum that can be used as a highly specific "fingerprint" for the selected sample (e.g. saliva, blood, ev) representing the diagnostic biomarker itself. the rs study of saliva has already demonstrated the possibility of profiling patients with progressive pathologies with good accuracy and, specifically, of distinguishing subjects suffering from ndds, with no further investigation of the ability to distinguish the ndds at an early stage, the verification of the possibility to monitor its progression, nor the investigation of the biomolecular moieties involved in the observed differences. raman spectroscopy is proposed as a reliable method for the rapid and exhaustive biochemical characterization of salivary and vesicular component present in the sample, without the need for staining or labeling procedures. objectives: the objective of this project is the validation of a raman molecular fingerprint for the considered exerimental groups, leading to the identification of a complex biomarker useful for 1) the early identification, 2) phenotyping and 3) molecular profiling of subjects with ndds, leading to the prompt identification of tailored therapeutic strategies, including optimal pharmacological and rehabilitation therapies for each subject, with a significant impact on patients' quality of life and, in the future, on the increased probability of slowing down the progression of ndds with optimal effective therapies. at a national level, early personalized intervention can reduce patient management times and costs. sample size: sample size was calculated with g-power (medium effect size f=0.25, statistical power 85%, a=0.05, for anova omnibus statistical test with 5 experimental groups ad, pd, atp, ppd, mci, drop-out rate of about 10%). the minimum number of subjects to be involved is 242. considering the different incidence of the considered ndds, distribution is not equal among groups. data collection: demographic, clinical and research data will be pseudonymized and stored in a custom made redcap database. ndds diagnosis (ad, pd, atpd, ppd or mci), demographic (age, sex), clinical history, and comorbidities (cumulative illness rating scale) data will be stored. saliva will be collected using an optimized protocol. sample collection: at recruitment (t0), at least 60min after the intake of food and/or drinks, saliva will be collected using salivette tubes(starstedt®). after 12 months(t12), subjects will be asked for a second saliva sample. pre-analytical parameters, dietary and smoking habit will be recorded. samples will be frozen until used. sample biomolecular evaluation: simoa technology will be used to quantify ndds related markers: asyn for pd, atp and ppd, aβ1-42 for ad and mci, nfl as general biomarkers of neurological damage in all groups. ev isolation and characterization: saliva will be used for the isolation of evs by size exclusion chromatography (sec) and by ultracentrifugation. effective isolation will be verified with dot blot for protein markers, nanoparticle tracking analysis (nta) for size distribution and transmission electron microscopy for morphology. raman analysis: salivary and saliva derived ev spectra will be acquired using an aramis raman microscope (horiba jobin-yvon, france) equipped with a laser light source operating at 785 nm and 532 nm (carlomagno et al., frontiers, 2021; mangolini et al., biology, 2023). data processing: acquired spectra will be baseline corrected and normalized by unit vector, to homogenize the dataset using the labspec6(i.e. baseline, normalization). multivariate analysis will be used to create a classification model for ad, pd, atpd, ppd and mci at t0, obtaining the dispersion of the canonical variables. the accuracy, specificity and sensitivity of saliva and sev rs will be calculated after the leave-one out cross-validation (loocv). roc curve will be calculated. data obtained from the molecular profiling of ndds patients and the raman databases will be used to interpret the spectral variation in the different experimental groups. the correlation between raman biomolecular and clinical data will be performed to evaluate the ability of the raman platform to stratify patients at different disease stages. the changes in the rs fingerprint between t0 and t12 will be investigated (longitudinal study) and correlated with the changes in the clinical scale scores.

Eligibility criteria:
inclusion criteria: * ad: standard criteria for dementia due to ad with ad neurochemical demonstration. * pd: mds criteria; modified hoehn\&yahr stages; stable pharmacological treatment (last 4 weeks). * atp: current consensus diagnostic criteria for progressive supranuclear palsy; corticobasal degeneration and multiple system atrophy. * prodromic pd: according to diagnostic criteria by berg; * mci: according to diagnostic criteria by dubois and albert. exclusion criteria: * for all the experimental groups considered, subjects with concomitant chronic and / or inflammatory diseases of the oral cavity, other systemic diseases, oncological or infectious diseases will be excluded. * patients not able to provide written informed consent autonomously will be excluded. * for pd patients: vascular, familiar and drug- induced parkinsonism, other known or suspected causes (metabolic, brain tumor etc) or any suggestive features of atp; dementia with moca test correct score\<15

Keywords: saliva raman spectroscopy extracellular vesicles diagnosis