Clinical trial NCT06433427: Metabolic Dysregulation as Biomarker of Frailty: Role of the Mitochondrial Dysfunction
Official title: Metabolic Dysregulation as Biomarker of Frailty: Role of the Mitochondrial Dysfunction
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Aging
Frailty
Mitochondrial Dysfunction
Chronic Disease
Keywords: Metabolic dysregulation
Lead sponsor: University Hospital of Ferrara
Sponsor class: OTHER
Collaborators: name: University of Milano Bicocca
First posted: 2024-05-29
Enrollment: 75
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: OTHER
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study will enroll individuals aged 65 years or older. The enrollment will take place among patients accessing geriatric outpatient clinics or being discharged from geriatric wards in clinically stable conditions.

Brief summary: The goal of this observational study is to evaluate the presence of mitochondrial dysfunction related to oxidative stress and its possible role in frailty, with and without multimorbidity, and to identify possible frailty biomarkers correlated with mitochondrial dysfunction. The main questions it aims to answer are:

* What is the role of oxidative stress-related mitochondrial dysfunction in frailty, taking into account the interaction with multimorbidity.
* What could be the specific biomarkers associated with mitochondrial dysfunction in the assessment of frailty.

In order to reach the study goals, we will enroll three categories of older adults:

* Non-Frail without Multimorbidity (NFWoM);
* Frail with Multimorbidity (FWM);
* Frail without Multimorbidity (FWoM).

Each individual will undergo an assessment of frailty phenotype and multimorbidity, and the collection of blood samples to isolate Peripheral Blood Mononuclear Cells (PBMCs). The identification of frailty biomarkers in each group of participants will be performed by combining untargeted metabolomics-based approaches and functional studies on specific mitochondrial dysfunctions performed on PBMCs and their subpopulations. Multivariate statistical and machine learning techniques will characterize the three clinical phenotype groups based on molecular data.

Detailed description: Study type: observational prospective study. Primary aim: is to evaluate the presence of mitochondrial dysfunction related to oxidative stress and its possible role in frailty, with and without multimorbidity.

Primary endpoint: mitochondrial dysfunction in frailty. Secondary aims: to combine untargeted metabolomics-based approaches and functional studies on specific mitochondrial dysfunctions performed on PBMCs and PBMC subpopulations (B lymphocytes, T lymphocytes and monocytes).

The research activities are organized in the following tasks:

* Task 1, Patient Enrollment: We will enroll individuals aged 65 years or older from geriatric outpatient clinics or geriatric wards. For each individual, we will perform an assessment of frailty and multimorbidity, and collect blood samples to isolate Peripheral Blood Mononuclear Cells (PBMCs). Three categories of individuals will be enrolled: 25 non-frail individuals without multimorbidity (NFWoM), 25 frail individuals with multimorbidity (FWM), and 25 frail individuals without multimorbidity (FWoM).
* Task 2, Separation of PBMC Subpopulations: T lymphocytes, B lymphocytes, and monocytes will be separated from frozen PBMCs using the Cell Sorting Facility for Fluorescence-Activated Cell Sorting (FACS) separation and the MoFlo Astrios cell sorter. The analyses on CD45+/CD3+/CD19-/CD14- T lymphocytes, CD45+/CD3-/CD19+/CD14- B lymphocytes, CD45+/CD3-/CD19-/CD14+ monocytes.
* Task 3, Mitochondrial Dysfunction Analysis on PBMCs and PBMC Subpopulations: For each individual, mitochondrial dysfunction will be evaluated by analyzing mtDNA damage (by Real-Time PCR), mitochondrial mass alteration (by Mitotracker staining), and intracellular and mitochondrial Reactive Oxygen Species (by DCF and MitoSOX staining). Moreover, we will evaluate alteration of glycolytic and mitochondrial metabolism using Agilent Seahorse Extracellular Flux Analyzer XFe96.
* Task 4, Untargeted Metabolomics on PBMCs and PBMC Subpopulations: To assess metabolic signature of PBMCs and subpopulations and highlight metabolic dysregulations linked to frailty, we will perform untargeted LC-MS-based metabolomics on PBMCs, T lymphocytes, B lymphocytes, and monocytes. The analysis on the polar metabolome will allow us to understand better the metabolic alterations associated with mitochondrial dysregulation.
* Task 5, Characterization of Biomarkers and Molecular Mechanism of Frailty: The potential biomarkers of frailty and the molecular mechanisms involved in mitochondrial dysfunction will be studied using statistical and machine learning techniques on molecular, metabolic and clinical data. This step will help characterize clinical phenotypes based on molecular measurements.

Eligibility criteria: Inclusion Criteria:

* Age ≥ 65 years
* Stable clinical conditions
* Willingness to participate in the study (provision of informed consent)
* Proficiency in the Italian language

Exclusion Criteria:

- Acute or unstable clinical conditions

Primary outcomes:
measure: Difference in the mtDNA copy number between frail individuals with vs without multimorbidity
timeFrame: Baseline
measure: Difference in the mtDNA copy number between non-frail vs frail individuals without multimorbidity
timeFrame: Baseline
Secondary outcomes:
measure: Variation in the mean intensity of mitochondrial fluorescence between non-frail vs frail individuals without multimorbidity
timeFrame: Baseline
measure: Variation in the mean intensity of mitochondrial fluorescence between frail individuals with vs without multimorbidity
timeFrame: Baseline
measure: Difference of intracellular Reactive Oxygen Species (ROS) between non-frail vs frail individuals without multimorbidity
timeFrame: Baseline
measure: Difference of intracellular Reactive Oxygen Species (ROS) between frail individuals with vs without multimorbidity
timeFrame: Baseline
measure: Qualitative difference in metabolomics profiles of PBMCs and PBMC subpopulations between non-frail vs frail individuals without multimorbidity
timeFrame: Baseline
measure: Qualitative difference in metabolomics profiles of PBMCs and PBMC subpopulations between frail individuals with vs without multimorbidity
timeFrame: Baseline
Other outcomes:
Locations:
Study officials:
affiliation: Università degli Studi di Ferrara
name: Caterina Trevisan, PhD
role: PRINCIPAL_INVESTIGATOR
References: