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Clinical Trial Details — Status: Active, not recruiting

Administrative data

NCT number NCT05515653
Other study ID # HAlemaoOswaldoCruz
Secondary ID CAAE: 56482922.2
Status Active, not recruiting
Phase
First received
Last updated
Start date July 18, 2022
Est. completion date July 15, 2024

Study information

Verified date May 2024
Source Hospital Alemão Oswaldo Cruz
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The main objective of this project is to evaluate the genomic information previously associated with cardiovascular diseases (CVD) and its importance as an independent risk predictor (expressed in Odds Ratio) when adjusted for traditional risk factors (smoking, diabetes, arterial hypertension, obesity , anxiety and depression, inadequate diet, physical inactivity, alcohol consumption and apolipoprotein B/A1 ratio (ApoB/ApoA1). An unpaired case-control study of individuals over 18 years of age will be carried out. Cases (N = 1867) will be enrolled right after the occurrence of the first atherosclerotic cardiovascular event (Acute Myocardial Infarction, Stroke and Peripheral Artery Thrombotic-Ischemic Events). The ratio between cases and controls will be 1:1. The controls (N = 1867) will be adult individuals over 18 years of age who sought medical care at the same locations for other clinical reasons (no CVD) or individuals without any overt disease. The genetic evaluation will be performed through the association of Low-covering Whole Genome Sequencing (coverage 0.5-5x) and Whole Exome Sequencing (average coverage 30x).


Description:

The study will be carried out in about 50 centers, comprising the five Brazilian regions. The study will be conducted from July 2022 to December 2023. Data collection will be performed at each center consecutively, for cases and controls, through electronic Case Report Form (CRF). Cases (N = 1867) will be selected by the occurrence of the first atherosclerotic cardiovascular event (Acute Myocardial Infarction, Stroke and Peripheral Arterial Thrombotic-Ischemic Events) during the hospitalization phase for the management of the acute atherothrombotic event. The ratio between cases and controls will be 1:1. Controls (N = 1867) will be adult individuals over 18 years of age who sought medical care at the same locations for other clinical reasons (no CVD) or individuals without any overt disease. The definitions of acute atherothrombotic events follow classic clinical and complementary exam criteria and are based on national and international guidelines. The complete project was submitted to the local Institutional Review Board (IRB)/National Research Ethics Commission (CONEP) system and has ethical approval (CAAE: 56482922.2.1001.0070). All cases and controls will be invited to participate and, if they agree, an Informed Consent Form will be obtained. Investigators will assess exposures to traditional risk factors in combination with genomic data (polygenic risk score) in both cases and controls, and these exposures will be expressed as odds ratios. Multiple logistic regression models will be built to adjust and determine the strengths of association between demographic variables, traditional risk factors and genetic data: gender, age, ethnicity, weight, body mass index, smoking, diabetes, hypertension, obesity, anxiety and depression, inadequate diet, physical inactivity, alcohol consumption and apolipoprotein B/A1 ratio (ApoB/ApoA1). For each association variable with a greater chance of cardiovascular disease (significant OR), an attributable risk will be calculated to estimate the fraction of risk attributable to the genetic component (Polygenic Risk Score) and to other clinical and demographic variables. The polygenic risk score will be calculated through a hybrid approach by taking into account the following features: effect size of each Single Nucleotide Polymorphism (SNP), number of effect alleles observed, sample ploidy, total number of SNPs included in the Polygenic Risk Score, and the number of nonmissing SNPs in the sample. Each risk allele will be given points in the risk score, and the total score will range between 0 (absence of risk alleles) and the maximum value (yet to be defined), based on the distribution of risk alleles that will be identified in the population included in the study. The scale will be interpreted in a direct (positive) association, i.e., the higher the score, the higher the number of alleles and respective weighted effect sizes. Finally, the polygenic risk score will be adjusted to previously reported traditional risk factors for atherosclerotic cardiovascular disease to determine the attributable risk fraction associated with the genomic profile.


Recruitment information / eligibility

Status Active, not recruiting
Enrollment 3974
Est. completion date July 15, 2024
Est. primary completion date February 20, 2023
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - Cases: adults over 18 years with first atherosclerotic cardiovascular event (Acute Myocardial Infarction, Stroke and Peripheral Artery Thrombotic-Ischemic Events) - Controls: adult individuals over 18 years of age who sought medical care at the same locations for other clinical reasons (no CVD) or individuals without any overt disease Exclusion Criteria: - Previous occurrence of Cardiovascular Event (Myocardial Infarction, Stroke or Peripheral Artery Thrombotic Events - Patients already recruited in another study linked to the GENOMA Brazil Program.

Study Design


Related Conditions & MeSH terms


Intervention

Genetic:
Exposure to genetics (polygenic)
The polygenic risk score (PRS) aggregates the effects of genetic variants into a single number that predicts the genetic predisposition to a phenotype. PRS are typically composed of hundreds to millions of genetic variants, usually Single Nucleotide Polymorphisms (SNPs). For each individual, the number of risk alleles computed in each variant is summed and weighted by the estimated value of the obtained effects (log odds ratio for traits with binary values or Beta coefficients for traits with continuous value) obtained from large-scale genomic studies ( GWAS)

Locations

Country Name City State
Brazil Centro de Pesquisa Clínica do Coração Aracaju CE
Brazil Hospital Cirurgia Aracaju SE
Brazil Hospital Maternidade São Vicente de Paulo Barbalha Ceará
Brazil Hospital Municipal de Barueri Barueri SP
Brazil Santa Casa de Misericordia de Belo Horizonte Belo Horizonte MG
Brazil Santa Casa de Misericórdia de Belo Horizonte Belo Horizonte MG
Brazil Associação Dr. Bartholomeu Tacchini Bento Gonçalves Rio Grande Do Sul
Brazil Maestri e Kormann Consultoria Medico Cientifica Blumenau Santa Catarina
Brazil Hospital e Maternidade Angelina Caron Campina Grande Do Sul PR
Brazil Instituto de Pesquisa Clínica de Campinas Campinas SP
Brazil Scentryfar Pesquisa Clínica Campinas SP
Brazil Hospital Universitário Maria Aparecida Pedrossian Campo Grande MS
Brazil Hospital Geral Filantrópico Universitário - Assoc. de Proteção à Maternidade e Infância de Cuiabá Cuiabá Mount
Brazil Núcleo de Pesquisa Clínica S/S Curitiba PR
Brazil Universidade Federal de Goiás - UFG Goiânia GO
Brazil Hospital e Clínica São Roque Ipiaú Bahia
Brazil H&W Cardiologia LTDA Joinville Santa Catarina
Brazil Centro de Pesquisas Clínicas Dr. Marco Mota HCOR Maceió Alagoas
Brazil Hospital Carlos Fenando Malzoni Matão São Paulo
Brazil Instituto Atena de Pesquisa Clínica Natal RN
Brazil Associacao Hospitalar Beneficente Sao Vicente de Paulo Passo Fundo RS
Brazil Santa Casa de Misericórdia de Pelotas Pelotas RS
Brazil Hospital de Clínicas de Porto Alegre Porto Alegre RS
Brazil Hospital Nossa Senhora Da Conceicao Sa Porto Alegre RS
Brazil Instituto de Cardiologia do Rio Grande do Sul Porto Alegre RS
Brazil Real Hospital Português de Beneficência em Pernambuco Recife PE
Brazil Acurácia Serviços Médicos Rio Branco AC
Brazil Instituto Cárdio Pulmonar da Bahia Salvador Bahia
Brazil Hospital Universitário de Santa Maria Santa Maria RS
Brazil Braile Hospital Dia Ltda São José Do Rio Preto São Paulo
Brazil Fundação Faculdade de Medicina de São José do Rio Preto São José Do Rio Preto SP
Brazil Hospital Universitário da Universidade Federal do Maranhão/HU/UFMA São Luís MA
Brazil Hospital Alemão Oswaldo Cruz São Paulo Sao Paulo
Brazil Hospital Santa Paula São Paulo
Brazil Instituto Dante Pazzanese de Cardiologia São Paulo SP
Brazil Instituto de Cardiologia HCFMUSP São Paulo SP
Brazil Instituto de Pesquisa GNDI São Paulo SP
Brazil Hospital Universitário da Universidade Federal do Piauí Teresina PI
Brazil Hospital de Clínicas da Universidade Federal do Triângulo Mineiro Uberaba MG
Brazil Hospital Evangélico de Vila Velha Vila Velha ES
Brazil Hospital Universitário Cassiano Antônio de Moraes Vitória ES

Sponsors (3)

Lead Sponsor Collaborator
Hospital Alemão Oswaldo Cruz Grupo Fleury, Ministry of Health, Brazil

Country where clinical trial is conducted

Brazil, 

References & Publications (30)

Anand SS, Xie C, Pare G, Montpetit A, Rangarajan S, McQueen MJ, Cordell HJ, Keavney B, Yusuf S, Hudson TJ, Engert JC; INTERHEART Investigators. Genetic variants associated with myocardial infarction risk factors in over 8000 individuals from five ethnic groups: The INTERHEART Genetics Study. Circ Cardiovasc Genet. 2009 Feb;2(1):16-25. doi: 10.1161/CIRCGENETICS.108.813709. Epub 2009 Jan 23. — View Citation

Carneiro-Proietti ABF, Kelly S, Miranda Teixeira C, Sabino EC, Alencar CS, Capuani L, Salomon Silva TP, Araujo A, Loureiro P, Maximo C, Lobo C, Flor-Park MV, Rodrigues DOW, Mota RA, Goncalez TT, Hoppe C, Ferreira JE, Ozahata M, Page GP, Guo Y, Preiss LR, Brambilla D, Busch MP, Custer B; International Component of the NHLBI Recipient Epidemiology and Donor Evaluation Study (REDS-III). Clinical and genetic ancestry profile of a large multi-centre sickle cell disease cohort in Brazil. Br J Haematol. 2018 Sep;182(6):895-908. doi: 10.1111/bjh.15462. Epub 2018 Jul 19. — View Citation

Colares VS, Titan SM, Pereira Ada C, Malafronte P, Cardena MM, Santos S, Santos PC, Fridman C, Barros RT, Woronik V. MYH9 and APOL1 gene polymorphisms and the risk of CKD in patients with lupus nephritis from an admixture population. PLoS One. 2014 Mar 21;9(3):e87716. doi: 10.1371/journal.pone.0087716. eCollection 2014. — View Citation

Cubillos-Angulo JM, Arriaga MB, Melo MGM, Silva EC, Alvarado-Arnez LE, de Almeida AS, Moraes MO, Moreira ASR, Lapa E Silva JR, Fukutani KF, Sterling TR, Hawn TR, Kritski AL, Oliveira MM, Andrade BB. Polymorphisms in interferon pathway genes and risk of Mycobacterium tuberculosis infection in contacts of tuberculosis cases in Brazil. Int J Infect Dis. 2020 Mar;92:21-28. doi: 10.1016/j.ijid.2019.12.013. Epub 2019 Dec 13. — View Citation

Gauderman WJ MJ. Quanto 1.1: A computer program for power and sample size calculations for genetic-epidemiology studies. 2006.

Gerstein HC, Islam S, Anand S, Almahmeed W, Damasceno A, Dans A, Lang CC, Luna MA, McQueen M, Rangarajan S, Rosengren A, Wang X, Yusuf S. Dysglycaemia and the risk of acute myocardial infarction in multiple ethnic groups: an analysis of 15,780 patients from the INTERHEART study. Diabetologia. 2010 Dec;53(12):2509-17. doi: 10.1007/s00125-010-1871-0. Epub 2010 Aug 14. — View Citation

Gladding PA, Legget M, Fatkin D, Larsen P, Doughty R. Polygenic Risk Scores in Coronary Artery Disease and Atrial Fibrillation. Heart Lung Circ. 2020 Apr;29(4):634-640. doi: 10.1016/j.hlc.2019.12.004. Epub 2019 Dec 27. — View Citation

Iqbal R, Anand S, Ounpuu S, Islam S, Zhang X, Rangarajan S, Chifamba J, Al-Hinai A, Keltai M, Yusuf S; INTERHEART Study Investigators. Dietary patterns and the risk of acute myocardial infarction in 52 countries: results of the INTERHEART study. Circulation. 2008 Nov 4;118(19):1929-37. doi: 10.1161/CIRCULATIONAHA.107.738716. Epub 2008 Oct 20. — View Citation

Kehdy FS, Gouveia MH, Machado M, Magalhaes WC, Horimoto AR, Horta BL, Moreira RG, Leal TP, Scliar MO, Soares-Souza GB, Rodrigues-Soares F, Araujo GS, Zamudio R, Sant Anna HP, Santos HC, Duarte NE, Fiaccone RL, Figueiredo CA, Silva TM, Costa GN, Beleza S, Berg DE, Cabrera L, Debortoli G, Duarte D, Ghirotto S, Gilman RH, Goncalves VF, Marrero AR, Muniz YC, Weissensteiner H, Yeager M, Rodrigues LC, Barreto ML, Lima-Costa MF, Pereira AC, Rodrigues MR, Tarazona-Santos E; Brazilian EPIGEN Project Consortium. Origin and dynamics of admixture in Brazilians and its effect on the pattern of deleterious mutations. Proc Natl Acad Sci U S A. 2015 Jul 14;112(28):8696-701. doi: 10.1073/pnas.1504447112. Epub 2015 Jun 29. — View Citation

Kim V, Wal TV, Nishi MY, Montenegro LR, Carrilho FJ, Hoshida Y, Ono SK. Brazilian cohort and genes encoding for drug-metabolizing enzymes and drug transporters. Pharmacogenomics. 2020 Jun;21(9):575-586. doi: 10.2217/pgs-2020-0013. Epub 2020 Jun 3. — View Citation

Lanas F, Seron P, Lanas A. Coronary heart disease and risk factors in latin america. Glob Heart. 2013 Dec;8(4):341-8. doi: 10.1016/j.gheart.2013.11.005. — View Citation

Leon DA, Saburova L, Tomkins S, Andreev E, Kiryanov N, McKee M, Shkolnikov VM. Hazardous alcohol drinking and premature mortality in Russia: a population based case-control study. Lancet. 2007 Jun 16;369(9578):2001-2009. doi: 10.1016/S0140-6736(07)60941-6. — View Citation

Leong DP, Smyth A, Teo KK, McKee M, Rangarajan S, Pais P, Liu L, Anand SS, Yusuf S; INTERHEART Investigators. Patterns of alcohol consumption and myocardial infarction risk: observations from 52 countries in the INTERHEART case-control study. Circulation. 2014 Jul 29;130(5):390-8. doi: 10.1161/CIRCULATIONAHA.113.007627. Epub 2014 Jun 13. — View Citation

Li R, Chen Y, Ritchie MD, Moore JH. Electronic health records and polygenic risk scores for predicting disease risk. Nat Rev Genet. 2020 Aug;21(8):493-502. doi: 10.1038/s41576-020-0224-1. Epub 2020 Mar 31. — View Citation

Lu H, Zhang J, Chen YE, Garcia-Barrio MT. Integration of Transformative Platforms for the Discovery of Causative Genes in Cardiovascular Diseases. Cardiovasc Drugs Ther. 2021 Jun;35(3):637-654. doi: 10.1007/s10557-021-07175-1. Epub 2021 Apr 15. — View Citation

Moura RR, Coelho AV, Balbino Vde Q, Crovella S, Brandao LA. Meta-analysis of Brazilian genetic admixture and comparison with other Latin America countries. Am J Hum Biol. 2015 Sep-Oct;27(5):674-80. doi: 10.1002/ajhb.22714. Epub 2015 Mar 26. — View Citation

O'Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H, Rao-Melacini P, Zhang X, Pais P, Agapay S, Lopez-Jaramillo P, Damasceno A, Langhorne P, McQueen MJ, Rosengren A, Dehghan M, Hankey GJ, Dans AL, Elsayed A, Avezum A, Mondo C, Diener HC, Ryglewicz D, Czlonkowska A, Pogosova N, Weimar C, Iqbal R, Diaz R, Yusoff K, Yusufali A, Oguz A, Wang X, Penaherrera E, Lanas F, Ogah OS, Ogunniyi A, Iversen HK, Malaga G, Rumboldt Z, Oveisgharan S, Al Hussain F, Magazi D, Nilanont Y, Ferguson J, Pare G, Yusuf S; INTERSTROKE investigators. Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study. Lancet. 2016 Aug 20;388(10046):761-75. doi: 10.1016/S0140-6736(16)30506-2. Epub 2016 Jul 16. — View Citation

Pena SDJ, Santos FR, Tarazona-Santos E. Genetic admixture in Brazil. Am J Med Genet C Semin Med Genet. 2020 Dec;184(4):928-938. doi: 10.1002/ajmg.c.31853. Epub 2020 Nov 18. — View Citation

Piegas LS, Avezum A, Pereira JC, Neto JM, Hoepfner C, Farran JA, Ramos RF, Timerman A, Esteves JP; AFIRMAR Study Investigators. Risk factors for myocardial infarction in Brazil. Am Heart J. 2003 Aug;146(2):331-8. doi: 10.1016/S0002-8703(03)00181-9. — View Citation

Pinho Nde A, Pierin AM. Hypertension control in brazilian publications. Arq Bras Cardiol. 2013 Sep;101(3):e65-73. doi: 10.5935/abc.20130173. — View Citation

Roberts R, Chang CC, Hadley T. Genetic Risk Stratification: A Paradigm Shift in Prevention of Coronary Artery Disease. JACC Basic Transl Sci. 2021 Mar 22;6(3):287-304. doi: 10.1016/j.jacbts.2020.09.004. eCollection 2021 Mar. — View Citation

Rosengren A, Hawken S, Ounpuu S, Sliwa K, Zubaid M, Almahmeed WA, Blackett KN, Sitthi-amorn C, Sato H, Yusuf S; INTERHEART investigators. Association of psychosocial risk factors with risk of acute myocardial infarction in 11119 cases and 13648 controls from 52 countries (the INTERHEART study): case-control study. Lancet. 2004 Sep 11-17;364(9438):953-62. doi: 10.1016/S0140-6736(04)17019-0. — View Citation

Schmidt MI, Duncan BB, Azevedo e Silva G, Menezes AM, Monteiro CA, Barreto SM, Chor D, Menezes PR. Chronic non-communicable diseases in Brazil: burden and current challenges. Lancet. 2011 Jun 4;377(9781):1949-61. doi: 10.1016/S0140-6736(11)60135-9. Epub 2011 May 9. — View Citation

Stram DO. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer; 2014.

Teo KK, Ounpuu S, Hawken S, Pandey MR, Valentin V, Hunt D, Diaz R, Rashed W, Freeman R, Jiang L, Zhang X, Yusuf S; INTERHEART Study Investigators. Tobacco use and risk of myocardial infarction in 52 countries in the INTERHEART study: a case-control study. Lancet. 2006 Aug 19;368(9536):647-58. doi: 10.1016/S0140-6736(06)69249-0. — View Citation

van Rheenen W, Peyrot WJ, Schork AJ, Lee SH, Wray NR. Genetic correlations of polygenic disease traits: from theory to practice. Nat Rev Genet. 2019 Oct;20(10):567-581. doi: 10.1038/s41576-019-0137-z. — View Citation

Vrablik M, Dlouha D, Todorovova V, Stefler D, Hubacek JA. Genetics of Cardiovascular Disease: How Far Are We from Personalized CVD Risk Prediction and Management? Int J Mol Sci. 2021 Apr 17;22(8):4182. doi: 10.3390/ijms22084182. — View Citation

Walldius G, Jungner I, Holme I, Aastveit AH, Kolar W, Steiner E. High apolipoprotein B, low apolipoprotein A-I, and improvement in the prediction of fatal myocardial infarction (AMORIS study): a prospective study. Lancet. 2001 Dec 15;358(9298):2026-33. doi: 10.1016/S0140-6736(01)07098-2. — View Citation

Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004 Sep 11-17;364(9438):937-52. doi: 10.1016/S0140-6736(04)17018-9. — View Citation

Yusuf S, Joseph P, Rangarajan S, Islam S, Mente A, Hystad P, Brauer M, Kutty VR, Gupta R, Wielgosz A, AlHabib KF, Dans A, Lopez-Jaramillo P, Avezum A, Lanas F, Oguz A, Kruger IM, Diaz R, Yusoff K, Mony P, Chifamba J, Yeates K, Kelishadi R, Yusufali A, Khatib R, Rahman O, Zatonska K, Iqbal R, Wei L, Bo H, Rosengren A, Kaur M, Mohan V, Lear SA, Teo KK, Leong D, O'Donnell M, McKee M, Dagenais G. Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet. 2020 Mar 7;395(10226):795-808. doi: 10.1016/S0140-6736(19)32008-2. Epub 2019 Sep 3. Erratum In: Lancet. 2020 Mar 7;395(10226):784. — View Citation

* Note: There are 30 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Population attributable risk fraction measured for the Polygenic Risk Score. Scale will range from 0 to maximum number of risk alleles. The higher the score, the higher the number of risk alleles (worse). Population attributable risk fraction of atherosclerotic cardiovascular diseases adjusted for other risk factors related to: diet, physical exercise, smoking, alcoholism, chronic disease history (diabetes, hypertension, dyslipidemia, etc) and biochemical parameters. through study completion, an average of 1 year
Primary Polymorphisms genes as an independent risk factor for the occurrence of Acute Myocardial infarction (AMI), stroke and peripherical arterial thrombotic-ischemic events As it is a case-control study, there will be no follow-up for the occurrence of clinical events. Therefore, we will assess exposures to traditional risk factors to cardiovascular events (MI, Stroke and acute peripheral atherothrombotic event) in combination with genomic data (polygenic risk score) in both cases and controls, and these exposures will be expressed as odds ratios. Multiple logistic regression models will be built to adjust and determine the strengths of association between demographic variables, traditional risk factors and genetic data through study completion, an average of 1 year
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