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Biobanks for cardiovascular epidemiology and prevention Licia Iacoviello*,1, Amalia De Curtis1, Maria Benedetta Donati2 & Giovanni de Gaetano3

ABSTRACT: Biobanks for medical research are organized collections of biological samples associated with personal data and information on their donors, to be stored for an indefinite period of time. The storage of biological samples has varied considerably over time, ranging from the informal storage of tissue specimens in a researcher’s freezer in the past, to the present well-structured formal repositories. Large-scale population-related biobanks are being set up in several countries and will allow not only research into individual diseases, but also approaches to a wide range of health-related issues, such as physical activity, eating, drinking, education and pollution, among others. The purpose of this article is to discuss how biobanks have improved research in cardiovascular disease epidemiology and prevention, by describing the most relevant population-based epidemiological studies that used set-up biobanks and stored samples for research. The selection of epidemiological studies and biobanks was based on their dimensions and their contribution to the field. Biobanks for medical research are defined as organized collections of biological samples, such as blood, plasma, serum, urine, DNA, cells and tissues, that are or can be associated with personal data and information on their donors, to be stored for an indefinite period of time [1,2] . Biobanks for research, therefore, can be organized as collections of both samples and data, and can be population- or disease-based [3] . Moreover, for epidemiological studies, it would be necessary, or at least desirable, for the subjects who have provided samples and data remain identifiable, although names may be coded (pseudoanonymized) to protect confidentiality. This is particularly striking for cohort studies where it would be possible to follow-up included subjects for diseases that develop during the course of life. However, it would also be important for cross-sectional studies to have the possibility to re-evaluate the study results in light of new discoveries. Indeed, biobanking enriches epidemiological studies with the possibility to investigate risk factors of diseases, such as external factors (e.g., environmental factors or lifestyles) and molecular factors (e.g., genes or proteins). The storage of biological samples has varied considerably over time, ranging from the informal storage of tissue specimens in a researcher’s freezer in the past, to well-organized formal repositories in the present. While in the past, tissue collection was performed by local pathology or clinical departments dealing with local operating procedures, at present, constitution of biobanks requires more sophisticated approaches, with stringent standard operating procedures for sample collection, processing and storage [4] . In the last decade, the number of organized biobanks has increased significantly. An estimated US$1 billion has been invested in the biobanking industry in the USA

KEYWORDS 

• biobanks • cardiovascular disease • cerebrovascular disease • cohort studies • genetics

Unit of Molecular & Nutritional Epidemiology, Department of Epidemiology & Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy 2 Unit of Translational Medicine, Department of Epidemiology & Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy 3 Department of Epidemiology & Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy *Author for correspondence: Tel.: +39 0865 929 664; [email protected] 1

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Review  Iacoviello, De Curtis, Donati & de Gaetano within the last 10 years, with the aim to accelerate the development of personalized diagnostics and therapeutics over the next decade. At least 179 biobanks with hundreds of thousands of donors exist in the USA, most of which have been established in the last 10 years [5] . Centers that cannot comply with such stringent requirements should abandon the idea to create their own biobank and use centralized biorepositories that can guarantee the maximal protection and integrity of the samples. The purpose of this article is to discuss why biobanks for cardiovascular epidemiology and prevention have been set up and how they have improved this field, by describing large-scale population-related biobanks and the most relevant population-based epidemiological studies that organized their sample collection in formal biobanks and used stored samples for research in the field. The selection of the biobanks and epidemiological studies described was based on their dimensions and on the importance of their contribution to the epidemiology and prevention of cardiovascular disease. Large-scale national population-related biobanks Large-scale population-related biobanks are being set up in several countries and will allow not only research into individual diseases, but also approaches to a wide range of health-related issues, such as physical activity, eating, drinking or education. Some of the genomics research projects involving whole populations, join together to create international consortia, such as the Public Population Project in Genomics (P3G) [6,7] . The UK Biobank is a major national health resource, with the aim of improving the prevention, diagnosis and treatment of a wide range of serious and life-threatening illnesses, including cancer, heart diseases, stroke, diabetes, arthritis, osteoporosis, eye disorders, depression and forms of dementia [8–10] . The UK Biobank has recruited 500,000 people aged between 40 and 69 years in 2006–2010 all over the country. These individuals provided blood, urine and saliva samples for future analysis, detailed information about themselves and agreed to have their health followed. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It is also

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financed by the Welsh Assembly Government and the British Heart Foundation. The Estonian Biobank is the population-based biobank of the Estonian Genome Center at the University of Tartu (Estonia) [11] . The cohort size is currently 51,535 people from 18 years of age and up. Information is collected on personal data (e.g., age and sex), genealogical data (family structure), educational and occupational history, lifestyle data (e.g., smoking, diet and physical activity), medical history, current health status (e.g., hypertension, diabetes, hypercholerolemia and cardiovascular disease) and medication. Anthropometric measurements, blood pressure and resting heart rate are measured during the visit. DNA, plasma and white blood cells are stored in liquid nitrogen for further use [12] . deCODE genetics is a private company headquartered in Iceland that, between 1998 and 2000, received a license to build and run the Icelandic Health Sector Database [13,14] . They have gathered genotypic and medical data from more than 140,000 volunteer participants, comprising well over half of the adult Iceland population. Using Iceland’s uniquely comprehensive genealogical records, deCODE has also put together a genealogy database covering the entire present day population and stretching back to the founding of the country more than 1000 years ago. At present deCODE has created a biobank of genetic samples from 100 000 Icelandic volunteers. Already, it has mapped genes involved in more than 50 common diseases and identified several specific disease-causing genes, including genes related to myocardial infarction, stroke and vascular aneurysms [15–17] . The CARTaGENE Project is a scientific project at the Centre Hospitalier Universitaire Sainte-Justine (Quebec, Canada) that created an infrastructure including a health database and a bank of biological samples, with the aim to lead, in the long term, to better prevention, diagnosis and treatments of chronic diseases, such as heart diseases, diabetes, stroke and cancer, and thus to the improvement of Quebec’s healthcare system [18,19] . Over 20,000 women and men aged 40–69 years old residing in Quebec participated in the initial phase of CARTaGENE (Phase A) from June 2009 to October 2010. These participants belong to the baseline cohort, which can potentially be traced long term. Each participant provided information about their health and lifestyles, and provided blood and urine samples. Some participants also chose to

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Biobanks for cardiovascular epidemiology & prevention  participate in a genealogical option conducted in collaboration with the BALSAC Project [20] . CARTaGENE is now beginning a new phase of recruitment, aiming to recruit an additional 17,000 participants. The Swedish National Biobanking Program is a joint national program of the two Swedish initiatives on functional genomics, Swegene and Wallenberg Consortium North, supported by the Wallenberg Foundation and by the major universities of Sweden [21,22] . The National Biobank Program has been running from 2002 to 2005, with an overall budget of more than 51 million Swedish kronor. The biobank stores samples collected for research or during routine medical care. The total number of samples in the biobanks of the Swedish Health Care system is estimated to be approximately 50–100 million human samples, with an increase rate of approximately 3–4 million samples per year. In particular, the population-based research biobank has a comprehensive collection of phenotypic and environmental information, as well as biobanking of buffy coats, plasma and erythrocytes stored at -80°C or lower. The four participating research cohort biobanks (Umeå Medical Biobank, Malmö Diet & Cancer, Malmö Preventive Medicine and Twin Gene Biobank), all located in Sweden, together contain blood samples from >185,000 sampling occasions. Why biobanks for cardiovascular epidemiology & prevention? Box 1 summarizes the possible advantages of biobanking for medical and, in particular, cardiovascular research. First, biobanks enable scientists to identify new biomarkers for the prediction of disease progression or outcomes. Second, they allow the investigation of the influence of genetics on the risk of multifactorial diseases and the combined effects of genetics, lifestyle (e.g., smoking habits, dietary habits and physical activity) and other environmental factors (e.g., education, pollution, seasonality and stress) in the development of common diseases, such as unstable angina, myocardial infarction, peripheral arterial diseases and stroke. In addition, biobanks create the possibility to translate discoveries in Mendelian disorders to common disease. Finally, the identification of pathways involved in disease initiation or progression may lead to the discovery of new therapeutic targets, but also to the development of drugs tailored to the peculiarities of individual patients.

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We shall now discuss the possible advantages of biobanks for cardiovascular research and mention the larger epidemiological studies that used DNA, plasma and serum stored in the biobanks to make advances in the field of cardiovascular disease. ●●Detection of biomarkers for the prediction

of disease progression or outcome

Following the Framingham heart study in 1951 in the USA [23] , several population-based studies have set up large biobanks to identify novel biomarkers that could improve the prediction of disease risk; others include the CARDIA [24] and ARIC [25] studies in 1985, and more recently the Women’s Health Initiative in 1993 [26,27] and the MESA study [28] in 2000. In Europe, the MONICA project was established in the early 1980s in many centers around Europe to monitor trends in cardiovascular diseases, and to relate them to risk factor changes in the population over a 10-year period [29] . ●●The MORGAM experience

Some years after the start of the MONICA project, the multinational MORGAM project [30] put together cohort studies across Europe, each with their own serum, plasma and DNA biobanks (Table 1) [31] ; the specific aim was to develop cardiovascular risk scores based on classic and new risk factors and to determine whether genetic biomarker assessment could confer an improvement to these scores [32,33] . The MORGAM project did not centralize samples in a common biobank, but made a catalog of participating cohorts, describing samples available in each cohort, the main outcomes and exposure variables. Samples necessary for the analysis were sent time by time to centralized laboratories for assays and resulting data were collected in a common harmonized database, also containing information on all the variables related to the biological samples. In the framework of this project, the MORGAM Biomarker Study had as the main end point, Box 1. Advantages of biobanks for cardiovascular and cerebrovascular research. ●● Detection of biomarkers for prediction of disease progression or outcome ●● Investigation of the influence of genetics in the risk of multifactorial diseases ●● Translation of discoveries in Mendelian disorders to common disease ●● Discovery of new therapeutic targets ●● Development of drugs tailored to the peculiarities of individual patients

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Review  Iacoviello, De Curtis, Donati & de Gaetano Table 1. MORGAM/BioMarCare participating centers. City, Country

Name

Site(s)

Newcastle, Australia Prague, Czech Republic Denmark

Newcastle Czech Republic Glostrup

Helsinki, Finland

FINRISK ATBC PRIME/Strasbourg

Faculty of Health, University of Newcastle National Institute of Public Health Københavns AMT, Centre of Preventive Medicine, Glostrup National Institute for Health and Welfare National Institute for Health and Welfare Department of Epidemiology and Public Health, Faculty of Medicine, Strasbourg Department of Epidemiology, Faculty of Medicine, Toulouse-Purpan, Toulouse Department of Epidemiology and Public Health, Pasteur Institute, Lille Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Epidemiology, Neuherberg Institute for Community Medicine, University of Greifswald, Greifswald University of Milan - Bicocca, Monza Centre for Cardiovascular Prevention, ASS4 ‘Medio Friuli’, Udine National Institute of Health, Rome IRCCS Neurological Mediterranean Institute NEUROMED, Pozzilli Kaunas University of Medicine, Institute of Cardiology, Kaunas Institute of Community Medicine, University of Tromsø Department of Epidemiology and Population Studies, Institute of Public Health, Jagiellonian University Medical College, Krakow Department of Epidemiology CVD Prevention and Health Promotion, National Institute of Cardiology, Warsaw Institute of Internal and Preventive Medicine, Siberian Branch of Russian Academy of Medical Sciences Institute of Internal and Preventive Medicine, Siberian Branch of Russian Academy of Medical Sciences Institute of Health Studies, Department of Health, Barcelona Umeå University Hospital, Department of Medicine, Umeå The Queen’s University of Belfast, Belfast, Northern Ireland University of Dundee, Dundee, Scotland The Queen’s University of Belfast, Belfast, Northern Ireland

France

PRIME/Toulouse PRIME/Lille Germany

Augsburg

Greifswald Italy

Brianza Friuli Rome Moli-sani

Lithuania

Kaunas

Norway

Tromsø

Poland

Krakow

Warsaw

Russian Federation

Novosibirsk HAPIEE/Novosibirsk

Spain

Catalonia

Sweden

Northern Sweden

UK

PRIME/Belfast Scotland Caerphilly

the first occurrence during follow-up of major cardiovascular events, which included first fatal or nonfatal definite or suspected myocardial infarction or coronary death, unstable angina, cardiac revascularization, ischemic stroke and unclassifiable death. Box 2 provides a list of the

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biomarkers tested in the MORGAM Biomarker Study; they are related to: lipid metabolism, inflammation, hemodynamic physiology, vascular function, oxidative stress, coagulation, renal function, angiogenesis and myocardial necrosis. A biomarker score was obtained with the three

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Biobanks for cardiovascular epidemiology & prevention  biomarkers with the strongest associations with incident cardiovascular events (N-terminal probrain natriuretic peptide, C-reactive protein and sensitive troponin I). The addition of this score to a conventional risk factor model improved the 10-year risk estimation for cardiovascular events in two middle-aged European populations [34] . Recently, a new extension of the interests and objectives of the MONICA study has been funded by the EU, including not only the MONICA/MORGAM cohort, but also several new cohorts with their biobanks around the world. ●●The BioMarCare project

The BioMarCare project, coordinated by Stefan Blanckenberg at the University Medical Centre of Hamburg-Eppendorf (Hamburg, Germany), includes biobanks from 17 primary prevention population-based cohorts (mainly derived from the MORGAM cohorts), four secondary prevention disease cohorts and five clinical trials cohorts, which store serum and plasma samples in their biobanks [35] . The primary objective of the BioMarCare consortium is to establish the predictive role of cardiovascular disease of existing and emerging biomarkers (selected on integrated cutting-edge quantitative proteomic, transcriptomic, metabolomic, and miRNomic data sets), individually and as an integrated panel. ●●The EPIC experience

The EPIC study was designed to investigate the relationships between diet, nutritional status, lifestyle and environmental factors and the incidence of cancer [36,37] . EPIC is one of the largest studies on diet and health, having recruited over half a million (520,000) people in 22 centers of ten European countries (Denmark, France, Germany, Greece, Italy, The Netherlands, Norway, Spain, Sweden and the UK). The master EPIC database is hosted by the International Agency for Research on Cancer (IARC, Lyon, France) and is responsible for the maintenance of the individual baseline and follow-up data collected from the different participating centers. The IARC also hosts and maintains the EPIC biorepository containing more than 6 million samples of plasma, serum, red cells and buffy coats, collected in small tubes called straws, and stored in liquid nitrogen containers. Different IARC teams and groups are leading and involved in projects on the interaction between diet,

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biomarkers of diet, other lifestyle and genetic factors, and cancer. Although the EPIC study was born as a project dedicated to cancer, along the years, cardiovascular and cerebrovascular disease also became a relevant outcome [38,39] . Several studies performed in different countries participating to the EPIC study have identified biomarkers as risk factors of coronary artery disease (CAD) and stroke [40–46] . Among others, EPICOR is a prospective investigation into the causes of cardiovascular disease [47–49] , being performed on Italian cohorts [50] recruited from 1993 to 1998 as part of the EPIC study. More recently, four out of five of the EPICOR study centers have Box 2. List of biomarkers tested in the MORGAM Biomarker Study. Lipid metabolism markers ●● ApoA1 ●● ApoB100 ●● Lipoprotein-associated phospholipase A2 ●● Paraoxonase-1 Inflammation markers ●● C-reactive protein ●● IL-1B ●● IL-1B receptor antagonist ●● Neopterin Vascular function markers ●● B-type natriuretic peptide ●● C-terminal pro-vasopressin ●● C-terminal pro-endothelin-1 ●● Mid-regional pro-adrenomedullin ●● Mid-regional pro-atrial natriuretic peptide Oxidative stress markers ●● Homocysteine ●● Myeloperoxidase ●● Vitamin B12 ●● Active vitamin B12 Coagulation markers ●● D-dimers Metabolic markers ●● Adiponectin ●● Leptin ●● Insulin ●● Ferritin Renal function markers ●● Creatinine ●● Cystatin-C Angiogenesis markers ●● Cardiac placental growth factor Myocardial necrosis markers ●● Creatinine kinase MB ●● Troponins

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Review  Iacoviello, De Curtis, Donati & de Gaetano used their biobanks to investigate metabolic and hemostasis biomarkers linked to cardiovascular disease and epigenetic changes, in particular genome-wide methylation, as a risk factor of myocardial infarction. ●●Common soil hypothesis & the Moli-sani

project experience

One of the most interesting possibilities offered by biobanks linked to prospective cohort studies is the possibility to evaluate the ‘common soil’ hypothesis for cardiovascular disease and cancer. It has long been thought that there might be a basic common ground, the so-called ‘common soil’, in the pathogenesis of ischemic cardiovascular disease, such as acute coronary syndrome and ischemic stroke, and certain types of cancer, such as those of the GI tract and hormonedependent tumors (e.g., breast, uterus, ovary and prostate cancers) [51–53] . Common intermediate mechanisms of these different clinical conditions would be insulin resistance, inflammation or hemostasis activation pathways, which could be considered as a general bridge between cellular processes related to atherosclerosis and to malignant cells proliferation [54,55] . Case–cohort studies, nested within longitudinal cohorts, whose biological samples were biobanked at baseline can, indeed, allow the simultaneous investigation of biomarkers for different diseases. The parallel evaluation of both cardio– cerebro­vascular disease and tumors as end points was the main aim of the Moli-sani project, a recent cohort study, conducted in Molise, a small region in Center–Southern Italy, which recruited from April 2005 to April 2010, 24,600 people over 34 years from the general population [56–59] . In the Moli-sani project, a fundamental role is played by the biological data bank (the ‘Moli-bank’). At the end of recruitment, this infrastructure contained 700,000 samples preserved in liquid nitrogen at -196°C and protected by sophisticated technologies allowing automatic refilling of nitrogen, remote control and computerized retrieval of samples. For each participant, two batches of 28 straws are stored in two different tanks as follows: eight straws containing EDTA plasma, six citrated plasma, eight serums and six buffy coats for later DNA extraction. This ‘treasure chest’ will serve as the basis not only for already planned tests and analyses, but will also give researchers, from our laboratories or other institutions, opportunities to develop

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new concepts and ideas. In the frame of these facilities, a study has already been conducted on the association of levels of D-dimers with the risk of total mortality [60] . The Moli-sani biobank together with the EPICOR biobanks (Italian branch), the biobanks of the Centro Nazionale di Epidemiologia Sorveglianza e Promozione della Salute related to the progetto Cuore [61,62] and the Italian Cardiovascular Epidemiological Observatories [63–65] offer an important national resource for studying biomarkers of cardiovascular disease. Besides population-based studies, biobanks of disease cohorts (including subjects of secondary prevention) are also of high interest. Examples for this are the APACE [66] , stenoCardia [67] or the LURIC studies [68] . The APACE study [69] and the stenoCardia study are prospective studies on patients with suspected acute coronary syndrome; they aim to develop novel cardiac markers for faster detection or exclusion of acute myocardial infarction. They set up biobanks of serum and plasma samples and participate in the BioMarCare project. In the LURIC study, patients with angiographically confirmed CAD were followed-up for over 10 years for fatal and nonfatal cardiovascular events. The corresponding biobank of plasma, serum and DNA allowed the identification of biomarkers for cardiovascular risk prediction. ●●Investigation of the influence of genetics

on the risk of cardiovascular diseases

Investigating the influence of genetics on the risk of chronic multifactorial diseases has been a main issue in the development of modern biobanking. Storing of DNA (or blood or buffy coat from which to extract DNA) reinforced biobank structure by requiring the development of new tools involving bioethics, regulation and biotechnology, such as specific informed consent, privacy regulation, liquid nitrogen storage and new technologies for sample tracing and retrieval. The possibility to study polymorphisms in candidate genes for cardiovascular disease as innovative factors for disease prediction and prevention has accelerated the growth of biobanks associated with epidemiological and clinical studies. The first evidence of associations between genetics and myocardial infarction was published in Nature in 1992, by the group of Francois Cambien, using DNA samples collected in the frame of the ECTIM study [70] .

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Biobanks for cardiovascular epidemiology & prevention  The possibility to study polymorphisms spanning the entire genome, through the genomewide approach, has developed throughout the years, requiring larger and larger numbers of cases and controls with greater accuracy in sample management and phenotype definition. Fifteen years after Cambien’s study and thousands of publications in genetic epidemiology using the candidate gene approach, three big consortia published, almost simultaneously, the results of genome-wide association studies showing that a common allele in chromosome 9p21 was associated with the risk of CAD [71–73] . In order to favor meta-analyses of genome-wide association studies and replication opportunities, the CHARGE consortium was created, including several large population-based cohort studies [74] . The consortium originally included five prospective cohort studies from the USA and Europe (the AGES–Reykjavik, ARIC, CHS, Framingham Heart Study and the Rotterdam studies). Thereafter, additional core cohorts were included (the CARDIA, the Family Heart Study, Health ABC, JHS and the MESA studies). More than 100,000 samples were analyzed by each consortium, putting together resources from the main population-based biobanks in the world. Since then, more than 25 loci have been associated with CAD risk in genome-wide association studies [75] , allowing the formulation of a genetic risk score to be used in the prediction of the disease [76] . More recently, the CARDIoGRAMplusC4D Consortium [77] , comprising over 180 researchers from countries across Europe (UK, Germany, Iceland, Sweden, Finland, The Netherlands, France, Italy and Greece), Lebanon, Pakistan, Korea, USA and Canada analyzed DNA from over 60,000 CAD cases and 130,000 apparently unaffected people. They identified 15 genetic regions newly associated with the CAD, bringing the number to 46 of regions associated with the risk of such a disease. Another important approach that could be developed thanks to the availability of DNA biobanks is the translation of discoveries in Mendelian disorders to common diseases. This was the case of three candidate genes (ABCA1, APOA1 and LCAT ) that cause Mendelian forms of low HDL cholesterol (HDL-C) levels that were sequenced in DNA samples, representing the extreme distribution of HDL levels, from a population-based study [78] . Nonsynonymous sequence variants were significantly more

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common (16 vs 2%) in individuals in the low HDL-C extreme compared with those in the high extreme. Some of the sequence variants in the low HDL-C group were functionally important, suggesting that rare alleles with major phenotypic effects contribute significantly to low plasma HDL-C levels in the general population. Another example is the PCSK9 gene, encoding a serine protease in the secretory pathway of LDL cholesterol (LDL-C), where missense gainof-function mutations can cause severe hypercholesterolemia [79] . To test whether loss-of-function mutations in PCSK9 have the opposite effect, the coding region of PCSK9 was sequenced in subjects with low plasma levels of LDL, and two nonsense mutations (Y142X and C679X) were found that were associated with a 40% reduction in plasma levels of LDL-C. By using the biobank of the ARIC study, a longitudinal, biracial cohort study designed to assess subclinical and clinical atherosclerosis, nonsense mutations in PCSK9 associated with a reduction in mean LDL-C were also associated with a reduction in the risk of CAD in both black and white subjects examined [80] . A new drug inhibiting PCSK9 is being developed to lower LDL-C and, consequently, CAD, and results will be available in the near future [81] . ●●Development of drugs tailored to the

peculiarities of individual patients

Finally, biobanks can be useful for the development of therapy tailored to individual patients. Clopidogrel is an antiplatelet agent that specifically and irreversibly inhibits the P2Y12 subtype of the ADP receptor, which is important in the activation of platelets. It is a prodrug activated in the liver by CYP450 enzymes, including CYP2C19. An interindividual variability in the response to clopidogrel [82–84] has been described and has been associated with poorer clinical outcomes after percutaneous coronary intervention [85] . Pharmacogenomic analyses have identified loss-of-function variant alleles of CYP2C19, specifically the 2C19*2 allele, to be the predominant genetic mediators of the antiplatelet effects of clopidogrel [86] . Variant allele carriers with lower active metabolite levels of clopidogrel and higher platelet reactivity were associated with poorer outcomes. such as death or ischemic vascular disease [87–90] . Polymorphisms in the CYP2C19 gene were tested in biobanked samples of the FAST-MI study who were receiving clopidogrel after acute

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Review  Iacoviello, De Curtis, Donati & de Gaetano myocardial infarction [91] . The variant allele of CYP2C19 gene was linked to an increased rate of cardiovascular events. In addition, homozygosity for the variant allele was associated with a more than three-times increase in the rate of cardiovascular events among the patients who underwent percutaneous coronary intervention during hospitalization, as compared with those who did not. The use of clopidogrel with aspirin is recommended for reducing recurrent thrombotic events after acute myocardial infarction and is mandatory after stent placement [92,93] . Among such patients, genotyping could be a suitable strategy to identify patients who would or world not benefit from clopidogrel therapy and then address a more specific and efficient treatment.

discovery of new therapeutic targets, as well as to the development of drugs tailored to individual patients. Studies of large populations uniquely contribute to determine whether genetic and/or biomarker variability would improve the development of personalized medicine. The possibility to study polymorphisms in candidate genes as innovative factors for cardiovascular disease prediction and prevention has accelerated the progress of biobanking associated with epidemiological and clinical studies. As an example, the Italian EPICOR study centers are presently using their biobanks to investigate metabolic and hemostasis biomarkers linked to cardiovascular disease and epigenetic changes, in particular genome-wide methylation, as a risk factor of acute myocardial infarction.

Conclusion In conclusion, biobanks are a novel important resource for identifying new biomarkers for prediction of disease progression or outcomes, to investigate the role of genetics in the risk of multifactorial diseases and the combined effects of genetics, lifestyles (e.g., smoking, diet and physical activity) and other environmental factors (e.g., education pollution, seasonality and stress) in the development of such diseases. In addition, biobanks make the translation of discoveries on Mendelian disorders to common disease possible. Finally, the identification of pathways involved in disease initiation or progression may lead to the

Future perspective It is quite an easy task to predict that the field of biobanks will rapidly grow and evolve in 5–10 years time. The rapid increase in the number of organized biobanks would require the establishment of larger and larger biobank networks, which should cover the need for a harmonized approach on biobanking practices and improved networking of existing and new collections. Technology for biological sample storing will rapidly improve, in parallel with the development of novel bioethical and organizational guidelines. Ethical committees will be asked to elaborate and diffuse internationally accepted

EXECUTIVE SUMMARY Background ●●

iobanks are organized collections of biological samples associated with personal data and information on their B donors, to be stored for an indefinite period of time.

●●

The number of well-organized biobanks has increased significantly in the last few years.

Large-scale national population-related biobanks ●●

L arge-scale population-related biobanks are being set up in several countries and will allow not only research into individual diseases, but also approaches to a wide range of health-related issues, such as physical activity, eating, drinking, education or pollution.

Why biobanks for cardiovascular epidemiology & prevention? ●●

umerous advantages of biobanking for cardiovascular and cerebrovascular epidemiology and prevention are N identified and discussed in this review.

●●

iobanks are useful for the detection of circulating and genetic biomarkers for the prediction of disease progression or B outcomes.

Future perspective ●●

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T echnology for biological sample storing will be rapidly improved, in parallel with the development of novel bioethical and organizational guidelines.

Future Cardiol. (2014) 10(2)

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Biobanks for cardiovascular epidemiology & prevention  rules for establishing and running disease- or population-based biobanks. Hopefully, the latter will not be simple sample repositories, but will become an integral part of translational research departments. Moreover, novel/emerging biomaterials will be stored, such as RNA/miRNA [94] , for studying gene expression and epigenetic phenomena, tissues or cells for generation of induced pluripotent stem cells [95] , which will require the development of new technologies of biomaterials isolation and storage. In this context, the initiative to establish a pan-European Biobanking and Biomolecular Resources Research Infrastructure for biomedical and biological research in Europe and References

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2

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8

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worldwide, has been developed in recent years [96] . The Biobanking and Biomolecular Resources Research Infrastructure specifically builds on existing infrastructures, resources and technologies, embedding European ethical, legal and societal frameworks [97] . Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript. Public Population Project in Genomics and Society (P3G). http://p3g.org

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Biobanks for cardiovascular epidemiology and prevention.

Biobanks for medical research are organized collections of biological samples associated with personal data and information on their donors, to be sto...
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