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| Name | Class |
|---|---|
| Leiden University Medical Center | OTHER |
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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.
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.
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| 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 |
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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COVID-19 patients in hospital and community setting
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| Name | Affiliation | Role |
|---|---|---|
| Dicky L Tahapary | Indonesia University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Dr. Cipto Mangunkusumo National General Hospital | Jakarta Pusat | DKI Jakarta | 10430 | Indonesia | ||
| Metabolic Disorder, Cardiovascular, and Aging Research Cluster IMERI-FKUI, Research Tower, 5th Floor |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32171866 | Background | Liu K, Chen Y, Lin R, Han K. Clinical features of COVID-19 in elderly patients: A comparison with young and middle-aged patients. J Infect. 2020 Jun;80(6):e14-e18. doi: 10.1016/j.jinf.2020.03.005. Epub 2020 Mar 27. | |
| 32451913 | Background | Iannelli A, Favre G, Frey S, Esnault V, Gugenheim J, Bouam S, Schiavo L, Tran A, Alifano M. Obesity and COVID-19: ACE 2, the Missing Tile. Obes Surg. 2020 Nov;30(11):4615-4617. doi: 10.1007/s11695-020-04734-7. No abstract available. |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| D009765 | Obesity |
| D003920 | Diabetes Mellitus |
| D024821 | Metabolic Syndrome |
| D007154 | Immune System Diseases |
| D007333 | Insulin Resistance |
| D007249 | Inflammation |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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Serum Urine PBMC Nasal scrape Nasal swab
| 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 |
| Jakarta Pusat |
| DKI Jakarta |
| 10430 |
| Indonesia |
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| 32437299 | Background | Wu H, Ballantyne CM. Metabolic Inflammation and Insulin Resistance in Obesity. Circ Res. 2020 May 22;126(11):1549-1564. doi: 10.1161/CIRCRESAHA.119.315896. Epub 2020 May 21. |
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| 28848738 | Background | Li M, Qian M, Xu J. Vascular Endothelial Regulation of Obesity-Associated Insulin Resistance. Front Cardiovasc Med. 2017 Aug 9;4:51. doi: 10.3389/fcvm.2017.00051. eCollection 2017. |
| 28585207 | Background | Engin A. Endothelial Dysfunction in Obesity. Adv Exp Med Biol. 2017;960:345-379. doi: 10.1007/978-3-319-48382-5_15. |
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| 24848057 | Background | van Deursen JM. The role of senescent cells in ageing. Nature. 2014 May 22;509(7501):439-46. doi: 10.1038/nature13193. |
| 32660650 | Background | Ni W, Yang X, Yang D, Bao J, Li R, Xiao Y, Hou C, Wang H, Liu J, Yang D, Xu Y, Cao Z, Gao Z. Role of angiotensin-converting enzyme 2 (ACE2) in COVID-19. Crit Care. 2020 Jul 13;24(1):422. doi: 10.1186/s13054-020-03120-0. |
| 32327758 | Background | Sungnak W, Huang N, Becavin C, Berg M, Queen R, Litvinukova M, Talavera-Lopez C, Maatz H, Reichart D, Sampaziotis F, Worlock KB, Yoshida M, Barnes JL; HCA Lung Biological Network. SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes. Nat Med. 2020 May;26(5):681-687. doi: 10.1038/s41591-020-0868-6. Epub 2020 Apr 23. |
| 26672612 | Background | Khemais-Benkhiat S, Idris-Khodja N, Ribeiro TP, Silva GC, Abbas M, Kheloufi M, Lee JO, Toti F, Auger C, Schini-Kerth VB. The Redox-sensitive Induction of the Local Angiotensin System Promotes Both Premature and Replicative Endothelial Senescence: Preventive Effect of a Standardized Crataegus Extract. J Gerontol A Biol Sci Med Sci. 2016 Dec;71(12):1581-1590. doi: 10.1093/gerona/glv213. Epub 2015 Dec 15. |
| 32169277 | Background | Song J, Hu B, Qu H, Wang L, Huang X, Li M, Zhang M. Upregulation of angiotensin converting enzyme 2 by shear stress reduced inflammation and proliferation in vascular endothelial cells. Biochem Biophys Res Commun. 2020 May 7;525(3):812-818. doi: 10.1016/j.bbrc.2020.02.151. Epub 2020 Mar 10. |
| 32432657 | Background | Bunyavanich S, Do A, Vicencio A. Nasal Gene Expression of Angiotensin-Converting Enzyme 2 in Children and Adults. JAMA. 2020 Jun 16;323(23):2427-2429. doi: 10.1001/jama.2020.8707. |
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| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D004700 | Endocrine System Diseases |
| D006946 | Hyperinsulinism |
| D010335 | Pathologic Processes |