COVID-19, Aging, and Cardiometabolic Risk Factors Study

Study Overview
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Brief Summary
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COVID-19 pandemic has made a tremendous impact on Indonesian economic and health care system especially with the double burden of diseases facing by Indonesia as a developing country. The prevalence of non-communicable diseases such as obesity, type diabetes, and cardiovascular diseases is increasing. These diseases along with older age have been known as an established risk factors for higher mortality and severe clinical disease entity in COVID-19 infection. Although, there is still some part of patients with these co-morbidities that only present with mild symptoms when infected with SARS-CoV-2, even for some without any symptoms. Thus, it would be very interesting to evaluate how are these role of aging and cardiometabolic parameters in the clinical disease course of COVID-19 infection, and how are the relationship with the immune system.

Detailed Description
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Indonesia is a country in transition where the burden of non-communicable diseases is taking over the infectious diseases problem, mostly due to the changes in lifestyle and increase in life expectancy. However, the unprecedented rising numbers of COVID-19 patients in Indonesia has impacted the Indonesian healthcare system heavily. It has been reported that older age and the presence of cardiometabolic risk factors pose a poor prognostic factor of COVID-19. It is also important to note that in Indonesia, the presence of cardiometabolic risk factors is often observed at a younger age. Thus, this might also contribute to the higher mortality of COVID19 infected patients despite their relatively younger age in comparison to other countries. Nevertheless, specific data on the impact of aging and cardiometabolic risk factors on COVID-19 are fragmentary, justifying the achievement of a dedicated prospective observational study. The CARAMEL study aims to specifically describe the phenotypic aging and cardiometabolic characteristics of patients with COVID-19 infection, in relation with the changes in the mucosal and systemic immune system. Particular attention will be devoted to obesity, central obesity, prediabetes, diabetes, hypertension, dyslipidemia, as well as anti-diabetic, antihypertensive, and anti-dyslipidemia therapies. This study will provide answers to researchers, medical professionals, and especially patients, regarding the impact of aging and cardiometabolic risk factors for COVID-19 prognosis. This pilot study will be used for the development of new studies and for the establishment of recommendations for the care of patients with cardiometabolic risk factors and COVID-19.

Official Title
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COVID-19, Aging, and Cardiometabolic Risk Factors (CARAMEL) Study: Integrating Aging, Cardiovascular, Metabolic, and Immunological Studies to Unravel COVID-19 Pathophysiology

Conditions
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Covid19, Obesity, Diabetes Mellitus, Aging, Cardiometabolic Syndrome, Immune System Disorder

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients newly diagnosed with COVID-19 at hospital setting or community screening, confirmed with biological proof (RT-PCR) Exclusion Criteria: Subjects opposed to the use of their data Minors, adults under guardianship, protected persons History of malignancy History of autoimmune disease Pregnancy

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Correlation of Body Mass Index with Clinical Disease Severity | To compare the body mass index, which calculated from body height (in meters) and body weight (in kilograms), in groups of COVID-19 patients with various disease severity based on WHO criteria | Baseline | 
| Correlation of Visceral Fat with Clinical Disease Severity | To compare the visceral fat that measures using a bio-impedance analyzer, in groups of COVID-19 patients with various disease severity based on WHO criteria | Baseline | 
| Correlation of Blood Glucose Levels with Clinical Disease Severity | To compare the random blood glucose levels during admission in groups of COVID-19 patients with various disease severity based on WHO criteria | Baseline | 
| Correlation of HbA1c with Clinical Disease Severity | To compare the HbA1c levels during admission in groups of COVID-19 patients with various disease severity based on WHO criteria | Baseline | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Changes of Insulin Resistance Levels in COVID-19 Patients Overtime | To compare the changes of HOMA-IR, a surrogate marker for whole-body insulin resistance which calculated from fasting blood glucose (IU/mL) and fasting insulin (mg/dL), between COVID-19 patients and healthy control subjects | Baseline, 6, and 12 month | 
| Changes of Leptin/Adiponectin Ratio in COVID-19 Patients Overtime | To compare the changes of leptin/adiponectin ratio, which calculated from leptin levels (ng/mL) divided by adiponectin levels (mikrogram/dL), between COVID-19 patients and healthy control subjects | Baseline, 6, and 12 month | 
| Systemic Immune Profiles in Diabetic COVID-19 Patients | To compare the systemic immune profiles using mass cytometry between diabetic/COVID-19, non-diabetic/COVID-19, and healthy control subjects | Baseline | 
| Nasal Mucosal Immune Profiles in Diabetic COVID-19 Patients | To compare the nasal-mucosal immune profiles using mass cytometry between diabetic/COVID-19, non-diabetic/COVID-19, and healthy control subjects | Baseline | 
| Aging Parameter (ACE-2 gene expression) in COVID-19 Patients | To compare the nasal epithelial ACE-2 gene expression in groups of COVID-19 patients with various disease severity based on WHO criteria | Baseline | 
| Aging Parameter (Telomere Length) in COVID-19 Patients | To compare the aging parameter using telomere length in groups of COVID-19 patients with various disease severity based on WHO criteria | Baseline | 
| Immune Cells Exhaustion in COVID-19 Patients | To compare the immune cells exhaustion marker (T-cell immunoglobulin mucin-3/TIM-3 expressions) in groups of COVID-19 patients with various disease severity based on WHO criteria | Baseline | 
| Changes of Pro-Inflammatory Cytokine (IL-6) in COVID-19 Patients | To compare the changes of pro-inflammatory cytokine (IL-6) levels overtime, measured from the supernatant of stimulated PBMC isolation in groups of patients with various clinical disease severity based on WHO criteria | Baseline, 1, 3, and 6 months | 
| Changes of Anti-Inflammatory Cytokine (IL-10) in COVID-19 Patients | To compare the changes of anti-inflammatory cytokine (IL-10) levels overtime, measured from the supernatant of stimulated PBMC isolation in groups of patients with various clinical disease severity based on WHO criteria | Baseline, 1, 3, and 6 months | 
| Antibody Kinetics in COVID-19 Patients | To compare the changes of antibody titers in groups of patients with various clinical disease severity based on WHO criteria | Baseline, 1, 3, and 6 months | 
| Proportion of Long COVID Syndrome | Percentage of COVID-19 patients still present with symptoms compared to whole study subjects | 3, 6, and 12 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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COVID-19, adiposity, diabetes, insulin resistance, aging, inflammation, immune system