Metabolomics: A Novel Tool for Investigating the Pathogenesis of Age-related Macular Degeneration
NCT ID: NCT04241536
Last Updated: 2023-01-09
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
NA
295 participants
INTERVENTIONAL
2021-06-01
2022-11-29
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Ocular, Vascular, and Genetic Findings in AMD Patients
NCT06015633
Project AMD: Comprehensive Characterisation of Age-Related Macular Degeneration and Its Progression
NCT04739319
10-year Progression of Diabetic Retinopathy: Identification of Signs and Surrogate Outcomes
NCT04650165
Epidemiologic, Laboratory, and Clinical Characterization of Individuals With Ocular Diseases
NCT00249392
Five-year Incidence of Age-related Macular Degeneration in the Central Region of Portugal
NCT02748824
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Predicting progression is therefore of utmost importance. It is established that AMD progression has a multifactorial nature, combining phenotypic and several environmental and genetic risk factors. Attempts have been made to include the different risk-factors in theoretical predicting models, however they are not practical on the clinical setting and fail to explain biological interactions. Thus, in the current clinical practice, risk prediction is still being assessed on a phenotypic basis, not considering AMD multifactorial nature.
A new approach that may allow the integration of all AMD interacting factors is metabolomics, the simultaneous multiparametric measurement of metabolic changes in living organisms as a response to perturbation (disease, diet, environment, others). The value of metabolomics in medical research has become clear through several studies on cancer, cardiovascular disease, and Alzheimer disease (AD), the latter sharing common pathways with AMD, as well as by increasing investments in this area. The metabolome reflects the occurring biochemical processes, therefore forming a fingerprint of the organism's health status, at a given time, which can be measured through nuclear magnetic resonance (NMR) spectroscopy and/or mass spectrometry (MS). The research team's previous work showed that metabolomics can be a powerful tool to study AMD as well, enabling the identification of specific plasma metabolomic profiles in AMD, which vary with the severity stages, and are primarily lipid metabolites linked to glycerophospholipid and sphingolipid pathways, as well as purines The current study will further elucidate the role of metabolomics in the understanding of AMD, and will also identify potential biologically robust biomarkers that can address the problem of predicting progression. The investigators hypothesize that the plasma and urinary metabolomic profile of subjects who progress over a five-year period (progressors) is distinct from those who remain at the same AMD severity stage (non-progressors). Based on our preliminary data, The investigators hypothesize that a panel of metabolites will distinguish these two groups (progressors vs non-progressors), and that this will mostly consist of lipids and amino acids.
To achieve these purposes, subjects who participated in our group's previous prospective study on AMD metabolomics will be recruited. Eligible subjects will be all that participated in the the IN654 study (between January 2015 and July 2016). These will be recalled and progression will be phenotypically assessed, thus defining the AMD-progressors and non-progressors groups.
Metabolomic signatures of AMD progression and disease will lay the path for the future definition of progression metabolic biomarkers, which can represent a rapid, reliable and potentially affordable methodology for progression prediction. Overall, this approach should offer an opportunity to identify new valuable supplemental tools for routine clinical evaluation. This will allow medical interventions based on preventive strategies to reduce progression to blindness stages, which will, ultimately, also reduce societal costs of AMD.
Preliminary data The researh team pioneered the application of metabolomics to the study of AMD across all stages, and, in 2015, the AIBILI team recruited and collected baseline data on a total of 295 subjects (242 AMD patients and 53 controls). This study cohort will be derived from that study population.
The investigators have published extensively on the hypothesis that metabolomic profiles differ across AMD stages. The latest paper, which includes the entire study population, meta-analyses to combine data from different cohorts was used. This paper provides additional evidence that patients with AMD present an altered plasma metabolomic profile as compared to controls, and that these profiles vary with disease severity. Results revealed that 28 metabolites differed significantly between AMD patients versus controls (false discovery rate (FDR) q-value: 4.1 x 10-2 - 1.8 x 10-5), and 67 across disease stages (FDR q-value: 4.5 x 10-2 - 1.7 x 10-4). Pathway analysis showed significant enrichment of glycerophospholipid, purine, taurine and hypotaurine, and nitrogen metabolism (p-value \< 0.04).
To assess the performance of models considering metabolite information, receiving operating curve (ROC) assessments were made. Both a model considering metabolite changes across disease stages (AUC = 0.815; 95% CI:0.771-0.860) and a model comparing patients with AMD versus controls (AUC = 0.789; 95% CI: 0.738-0.840) outperformed (p-value = 3.74 x 10-6 and p-value = 2.07 x 10-4, respectively) a more classical model considering demographic covariates alone (AUC = 0.725; 95% CI: 0.671-0.779) This is evidence that metabolomics can be a useful tool for longitudinal study of AMD progression.
General research design Five-years after the first AMD metabolomic study, all participants will be invited to participate in this study.
All participants will be invited to come to AIBILI to perform the study procedures, which include color fundus photographs (CFP), SD-OCT and swept source OCT (SS-OCT). Additionally, they will also be invited to answer a validated food frequency questionnaire (FFQ)19 and a questionnaire about their regular physical activity. Systemic comorbidities and current medication will be registered. Blood and urine samples will be collected for metabolomic profiling. Functional testing with microperimetry and dark adaptation will be offered as an additional optional study procedure.
Afterwards, the obtained CFP will be graded. According to the procedures for IN654 study classification, all CFP will be standardized using software developed by our group. Two independent graders, masked to any other data, will assess AMD staging of all eyes, according to the AREDS classification.21 Each eye of patients will be assessed separately, and if different, the most advanced eye will be considered as the classification for that subject. Previously performed IN654 study classification will be compared. Progressors will be defined as patients who: (i) had originally been classified as early AMD, and at five years have intermediate or late AMD; (ii) had originally been classified as intermediate AMD and have at five years late AMD. Non-progressors will be defined as those who remain within the same AMD stage at the five-year visit.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
NA
SINGLE_GROUP
OTHER
NONE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
No arm
This is an epidemiologic study. No arms are considered.
Blood draw and urine collection
Patients will collect blood and urine for metabolome analysis
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Blood draw and urine collection
Patients will collect blood and urine for metabolome analysis
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
55 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Association for Innovation and Biomedical Research on Light and Image
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
AIBILI
Coimbra, , Portugal
Countries
Review the countries where the study has at least one active or historical site.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
CEC/010/20
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.