About this trial
In recent decades, advances in medicine have significantly improved both quality of life and life expectancy. However, these positive effects are also associated with a considerable increase in the prevalence of age-related diseases. Among these, Alzheimer's disease (AD), Parkinson's disease (PD), and type 2 diabetes (T2D) currently represent a major threat to human health. PD and AD are the most common neurodegenerative diseases in industrialized populations. In particular, AD accounts for 54% of all cases of dementia, with a prevalence of 4.4% among individuals over 65 years of age. PD has a prevalence of about 1% in people older than 60 years, reaching up to 4% in those over 80 years of age. AD and PD are highly disabling disorders with a slow but progressive course, caused by the degeneration and/or death of nerve cells. This results in impairments in the control of movement and balance, as in the case of PD, or in cognitive functioning, as in AD.
To date, neither effective treatments nor early diagnostic tools are available to address these conditions in the initial phase of neurodegeneration. Likewise, there are no tools capable of monitoring disease progression and improving patients' adaptation to therapy.
Moreover, although the association between T2D and the risk of PD and/or AD has long been recognized, these conditions were historically considered unrelated. Recent evidence from clinical and epidemiological studies suggests the existence of shared pathophysiological mechanisms associated with insulin resistance and persistent inflammation in several metabolically relevant tissues, such as adipose tissue and the brain. However, the mechanisms that increase the risk of PD and/or AD in individuals with T2D remain poorly understood.
These data highlight how relevant these diseases are for the National Health System and demonstrate that they represent one of the most important priorities to be addressed, requiring substantial investments in both scientific research and early diagnostic strategies.
Therefore, the present project proposal, which aims to develop new minimally invasive tools for the early prediction and monitoring of neurodegenerative diseases such as AD and PD, will help fill an important gap in the clinical and therapeutic management of these patients.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Inclusion criteria for PD patients. For the IRCCS INM Neuromed, patients will be recruited from those affiliated with the Center for the Study and Treatment of Parkinson's Disease of the Neuromed Institute of Pozzilli.
Disqualifiers
Pre-existing psychiatric disorders;
Neurodegenerative neurological diseases such as multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer's disease, neuromuscular disorders, epilepsy;
Diagnosis of dementia.
Trial population
In this multicenter, observational, prospective study, a total of 500 subjects will be consecutively enrolled at the two clinical recruiting centers involved in the study (IRCCS Neuromed (UO1) and the University of Campania Luigi Vanvitelli (UO2)), including: 100 subjects with Parkinson's disease (PD) (UO1); 50 subjects with PD and diabetes (UO1); 100 subjects with Alzheimer's disease (AD) (UO2); 50 subjects with AD and diabetes (UO2); 50 subjects with diabetes (UO2); 50 first-degree relatives (FDR) of patients with AD or type 2 diabetes (UO2); 100 healthy control subjects for the validation of specific genotypes/epigenotypes and/or biomarkers associated with PD, AD, and/or T2D (UO1 and UO2). The control subjects will be recruited according to standard clinical practice among patients attending the outpatient clinics of IRCCS Neuromed and the Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli - Naples.
Trial design
Case-control
Prospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
motor symptoms of PD patients will be evaluated with Hoehn and Yahr (HY) score
The Hoehn and Yahr Scale will be used to measure how Parkinson's symptoms progress and the level of disability. Itincludes stages 1 through 5: Stage 1. Unilateral involvement only, usually with minimal or no functional impairment; Stage 2 = Bilateral disease, without impairment of balance; Stage 3 = Mild to moderate bilateral disease; some postural instability; physically independent. Stage 4 = Severe disability; still able to walk or stand unassisted. Stage 5 = Wheelchair bound or bedridden unless aided.
motor and non motor symptoms of PD patients will be evaluated with MDS-UPDRS
The MDS-UPDRS has four parts, namely, I: Non-motor Experiences of Daily Living; II: Motor Experiences of DailyLiving; III: Motor Examination; IV: Motor Complications. Twenty questions are completed by the patient/caregiver
clinical evaluation of cognitive impairment of PD and AD patients
PD patients will be evaluated with the Montreal Cognitive Assessment (MoCA) test. This is a test used by healthcare providers to evaluate people with memory loss or other symptoms of cognitive decline. The MoCA contains 30 questions and checks different types of cognitive or thinking abilities. These include:orientation, short-term memory/delayed recall, executive function/visuospatial ability, clock-drawing test.- assessment of language disorders. AD patients: - assessment of cognitive disorders (MMSE, MOCA test, clock test); - assessment of language disorders.
identification of variants/mutations
PD patients: the number of multiple rare (Minor allele frequency, MAF\<0.01) deleterious (missense, non sense, frameshift and splicing) variants in PD genes will be counted in PD patients and unrelated healthy subjects. Case-control assoiciation study will evaluate the PD risk. AD, T2D: deleterious variants (missense, non sense, frameshift and splicing) in responsible genes will be considered.
Sponsors and contacts
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Neuromed IRCCS
Lead sponsor
University of Campania Luigi Vanvitelli
Collaborator
Istituto di Genetica e Biofisica "A. Buzzati Traverso", CNR
Collaborator
Istituto degli Endotipi in Oncologia, Metabolismo e Immunologia "G. Salvatore" (IEOMI), CNR
Collaborator
Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), CNR
Collaborator