Cohort Profile: The Leipzig Research Center for Civilization Diseases–Heart Study (LIFE-Heart)

Coronary artery disease (CAD) is the most common cause of death worldwide and its prevalence is rapidly increasing in developing countries. CAD has a complex and heterogeneous aetiology involving numerous lifestyle, environmental and genetic factors whose interplay is only partly understood. Moreover, clinical presentation of the disease is highly heterogeneous, including subclinical asymptomatic forms, symptomatic stable disease of different severity, myocardial infarction and sequelae such as heart failure. Heritability of CAD is considerable, with estimates of ∼50%.1 Large-scale genome-wide association studies have discovered 168 loci associated with CAD as of now.2,3 However, little is known about the underlying biology at these loci. Moreover, studies were typically performed in a case/control setting often relying on anamnestic rather than physiological assessments of disease state. Efforts to analyse more refined phenotypes such as severity of disease, or sub-clinical phenotypes such as carotid plaques, are still in their infancy. The Leipzig Research Center for Civilization Diseases–Heart Study (LIFE-Heart, initially named the LE-Heart study) was set up to contribute to the understanding of the heterogeneity of CAD and the impact of molecular-genetic, lifestyle and environmental risk factors thereon. For this purpose, we aimed to establish a cohort with detailed vascular assessments. Severity of CAD was determined in (almost) all study participants by coronary angiography and atherosclerosis was assessed at different anatomical sites (e.g. carotid arteries). Concomitantly, we focused on comprehensive assessments of different molecular-genetic layers (genetics, transcriptomics, proteomics, metabolomics) in order to understand their inter-relationships and contributions to disease development. Our recruitment strategies enable us to define different disease entities and sub-groups with sufficiently large sample size to study potential molecular-genetic associations and biomarkers in and between these groups. As the genetic factors driving progression of CAD are an under-investigated issue, we continuously complete patient data from medical records and retrieve life status via registry offices. We also performed follow-up campaigns of mail-based questionnaires and reappointments for physical examinations. Based on the rich cross-sectional and longitudinal data and available biospecimens, our study is well suited to perform diagnostic and prognostic biomarker research to improve individual cardiovascular risk assessment and to develop personalized treatment concepts. LIFE-Heart is a monocentric study. All patients were recruited at the Heart Center Leipzig, Germany—one of the largest cardiology centers worldwide and with a catchment area covering several German states. The study was initially funded by the Roland-Ernst Foundation. LIFE-Heart is an integral part of the Leipzig Research Center for Civilization Diseases (LIFE), an organizational unit affiliated to the Medical Faculty of the University of Leipzig. LIFE is funded by means of the European Union, by the European Regional Development Fund (ERDF) and by funds of the Free State of Saxony within the framework of the excellence initiative. Follow-up investigations are again funded by the Roland-Ernst Foundation. In LIFE-Heart, three modes of patient recruitment were implemented. First, patients with suspected CAD as indicated by clinical signs or symptoms such as chest pain or ischaemia in exercise electrocardiogram were collected. Patients with previous coronary revascularization percutaneous coronary intervention (PCI) or coronary artery bypass graft were excluded. Typically, these patients were admitted by their outpatient cardiologists to undergo diagnostic coronary angiography. A significant number of these patients showed no signs of occlusive CAD. Second, we enrolled patients with confirmed stable CAD, preferentially left-main CAD. Third, patients with myocardial infarction requiring PCI were collected either at emergency admission acute myocardial infarction (AMI) or after a myocardial infarction event (post-MI). General exclusion criteria included pregnancy, breast-feeding and severe systemic diseases such as auto-immune diseases treated with immune-modulating therapies, patients requiring dialysis, patients with acute or chronic infectious diseases and patients with cancer or cancer therapy within the last 2 years. Patients were recruited at hospital by randomly selecting consecutive patients fulfilling the respective inclusion criteria, with a maximum of three patients per day due to organizational restrictions. About 7300 patients were invited to participate. A total of 6994 patients (5025 male, 1969 female, age range 23–89 years) were successfully recruited. The characteristics of these patients are provided in Table 1. Baseline characteristics of patients for the different modes of recruitment. Values are given as median (interquartile range) for quantitative variables and as n (%) for binary variables Coronary artery disease. Acute myocardial infarction. Post myocardial infarction. Body mass index. Antihypertensive medication according to ATC-code C02, C03, C07, C08 or C09. Medication according to ATC-code C10. Based on anamnestic information, medication with ATC-code A10 or HbA1c > 6.5%. Glomerular filtration rate estimated according to Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Creatinin.4 Anamnestic information (referral letter) or newly diagnosed. Results of coronary angiography at baseline. Note that previous angiographies or subsequent events could change group assignment. Normal angiogram, only lesions with 6.5%. Glomerular filtration rate estimated according to Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Creatinin.4 Anamnestic information (referral letter) or newly diagnosed. Results of coronary angiography at baseline. Note that previous angiographies or subsequent events could change group assignment. Normal angiogram, only lesions with 6.5%. Glomerular filtration rate estimated according to CKD-EPI creatinin.4 Anamnestic information (referral letter) or newly diagnosed,. Low-density lipoprotein–cholesterol. High-density lipoprotein–cholesterol. Interleukin-6. N-terminal pro-brain natriuretic peptide. Non-responder analysis of first mail-based follow-up campaign; patients with no or no relevant stenosis at baseline were invited. Values are given as median (interquartile range) for quantitative variables and as n (%) for binary variables; comparisons between responders and non-responders were performed with Mann-Whitney U-Test for quantitative variables and Fisher’s exact test for binary variables at baseline Body mass index. Antihypertensive medication according to ATC-code C02, C03, C07, C08 or C09. Medication according to ATC-code C10. Based on anamnestic information, medication with ATC-code A10 or HbA1c > 6.5%. Glomerular filtration rate estimated according to CKD-EPI creatinin.4 Anamnestic information (referral letter) or newly diagnosed,. Low-density lipoprotein–cholesterol. High-density lipoprotein–cholesterol. Interleukin-6. N-terminal pro-brain natriuretic peptide. In 2018, we initiated a second follow-up campaign of patients without heart failure left-ventricular ejection fraction ≥50%, N-terminal pro-brain natriuretic peptide (NT-pro-BNP) < 125 ng/ml. Exclusion criteria include unstable CAD and cardiac valvular disease. Patients are re-invited and receive a physical examination comprising echocardiography, vascular status and laboratory tests with the major aim of detecting newly developed heart failure of different clinical appearance. Finally, in 2019 we started a mail-based follow-up campaign of all study participants to capture cardiovascular events since baseline, present complaints, changes in lifestyle and medication, nutrition, and, for the first time, gender aspects. Assessments are primarily focused on evaluating atherosclerotic cardiovascular disease states, related risk factors and sequelae. Coronary angiography is available for (almost) all patients at baseline including detailed evaluation of the degree of occlusion of coronary vessels allowing, for example, calculation of the Gensini score.6 Carotid vessels were assessed by high-resolution B-mode ultrasound images generated with the Vivid platform (GE-Healthcare, USA). We determined intima media thickness and plaque status of the common carotid artery, the carotid bulb, and the internal and the external carotid artery. Ankle–brachial index was determined by Doppler sonography sphygmomanometer cuffs and a hand-held Doppler probe (Huntleigh Mini-Dopplex, Germany). Patients were in a supine position and blood pressures were taken at both ankles and the right arm. In the follow-up, this method was replaced by automated photo-plethysmography (Vicorder, Skidmore Medical, UK). Additionally, we used Vicorder to perform pulse-wave analyses, deriving variables of vascular stiffness such as pulse-wave velocities between different anatomic sites.7 Electrocardiogram was determined at rest (5 min) and partly during exercise using a treadmill ergometer (LE 200 CE, CareFusion, Germany) or a semi-reclining cycle ergometer (Ergoselect 1000, ergoline GmbH, Germany). Transthoracic echocardiography was performed using again the Vivid platform (GE-Healthcare) with the following views: parasternal short and long axis, apical two, three and four chamber views, left and right ventricular outflow tract, tissue velocity imaging, spectral tissue Doppler, aortic, mitral, pulmonary and tricuspidal valve. Anthropometric assessments included height, weight and hip and waist circumference. In the follow-up, we added bio-impedance analysis using InBody 770 (JP Global Markets GmbH, Germany). Moreover, to assess sleep duration and physical activity, patients were asked to wear a Fit Bit Flex 2 (fitbit, USA) for 5 days combined with an activity protocol. Interview-based questionnaires comprise sociodemography, cardiac symptoms, complaints and events, medical history, medication, smoking behaviour, alcohol consumption and physical activity. In a subset of patients, the German version of the Food-Frequency-Questionnaire (FFQ) is available.8 In the follow-ups, we additionally ask for quality of life (SF-12), adherence to Mediterranean diet (MEDAS-149), anxiety and depression symptoms (HADS-D10) and gender roles (German version of the Personal Attributes Questionnaire11) An overview of available assessments per campaign can be found in Table 3. Overview of major assessments in each follow-up campaign Overview of major assessments in each follow-up campaign Besides follow-up campaigns, patient data are completed by linking medical records and continuously updating life status. Assessment of causes of deaths and linkage to records of insurance companies is in preparation. All assessments were performed following standard operating procedures (SOPs). Technical staff were regularly trained and supervised to comply with the SOPs. Data were captured by electronic data-entry systems and stored in a central database. A data quality and query management system was established. Standardized blood collection systems (Sarstedt, Germany; Becton Dickinson, USA) were used to collect the following biospecimens: serum, Ethylenediaminetetraacetic acid (EDTA) plasma, citrate plasma, dried blood spots and peripheral blood mononuclear cells (PBMC). RNA of whole blood was stabilized using a PAXgene system (BD Bioscience, USA) later replaced by a Tempus system (Life Technologies, USA). Centrifugation of blood and PBMC samples was done between 30 and 60 min after blood collection. Samples were stored at 4 °C and transported within 5 h to the Institute of Laboratory Medicine of the University Hospital Leipzig (ILM) for laboratory analyses and storage. Aliquots of biospecimens were stored at −80°C or in the vapour phase of liquid nitrogen in the Central Biobank of the Medical Faculty of the University of Leipzig (Leipzig Medical Biobank). A comprehensive panel of blood analytes was assessed at the ILM on the day of blood sampling. The laboratory has been accredited according to the norms ISO 15189 and ISO 17025. Analyses were performed using automated Roche Cobas 6000/8000 clinical-chemistry analysers (Roche Diagnostics, Mannheim, Germany). The following variables were assessed: alanine aminotransferase, alkaline phosphatase, apolipoprotein A1 and B, aspartate aminotransferase, bilirubin, blood urea nitrogen, cholesterol, creatine kinase, creatine kinase MB, creatinine, high-sensitive C-reactive protein, gamma glutamyltransferase, glucose, haemoglobin A1c, HDL-cholesterol, LDL-cholesterol, small-dense LDL-cholesterol, lipoprotein(a), NT-pro-brain natriuretic peptide, total protein, triglycerides, thyroid-stimulating hormone and high-sensitive troponin T (see Table 1). Differential blood counts were assessed using Sysmex XE/XN analysers (Sysmex, Germany). A special feature of LIFE-Heart is the comprehensive assessment of several multiomics layers including genetics, gene expression, proteome and metabolome at baseline. DNA was extracted from whole blood samples by Invisorb Spin Blood Maxi Kit (Invitek, Germany), dissolved in distilled water and stored at −80°C until analysis. Genome-wide single-nucleotide polymorphism (SNP) analysis was performed using Affymetrix-Axiom CEU or Affymetrix Axiom-CADLIFE micro-arrays. The CADLIFE array essentially contains the CEU array as a backbone accompanied by a custom content of SNPs near genes relevant for cardiovascular disease risk. RNA of whole blood was isolated using a PAXgene 96 Blood RNA Kit (QIAGEN/Becton Dickinson, USA) or Norgen Preserved Blood RNA Purification Kit I (Norgen Biotek, Canada). RNA from PBMC was extracted using TRIzol reagent (Invitrogen, USA) and hybridized to Illumina HT-12 v4 expression micro-arrays (Illumina, USA). Proteome and metabolome analyses were based on liquid chromatography–tandem mass spectrometry (LC–MS/MS) techniques developed at the ILM allowing high-throughput quantitative target assessment. Corresponding pre-analytical protocols were also developed and applied to the sampling and storage of LIFE-Heart biospecimens. The corresponding methods, an overview of available sample sizes and example publications are shown in Table 4. Overview of molecular data available in LIFE-Heart. If applicable, methods developed for these data and example publications are also presented Enzyme-linked immunosorbent assay. Not applicable. Overview of molecular data available in LIFE-Heart. If applicable, methods developed for these data and example publications are also presented Enzyme-linked immunosorbent assay. Not applicable. A total of 30 peer-reviewed publications are based on data from the LIFE-Heart study. A number of these manuscripts focused on molecular mechanisms of CAD and corresponding sub-phenotypes. For example, three studies unravelled the molecular mechanisms underlying the CAD locus at chromosome 9p21. At this locus, isoforms of the non-coding RNA ANRIL (antisense non-coding RNA in the INK4 locus) serve as modifiers of CAD risk.38–40 Several manuscripts aimed at establishing or validating diagnostic or prognostic biomarkers of cardiovascular disease. For example, we assessed the properties of eight apolipoproteins as diagnostic biomarkers of cardiovascular disease risk and identified apolipoproteins A-IV, B-100, C-III and E to be independently associated with stable CAD.26 Further, expression alterations of distinct gene transcripts were identified as prognostic factors of a short-term outcome of AMI 17 or heart failure as late Finally, were in studies on or genome-wide genetic associations of disease or potential molecular of CAD. studies were often accompanied by Analyses were either performed with LIFE-Heart as a or in with large such as Disease and The Coronary Disease Kidney Disease for Heart and Research in and of Coronary Heart Disease The rich molecular data enable us to perform multiomics analyses and to molecular The major are and in Table Overview of of genetic studies by data of LIFE-Heart Genome-wide association study. Coronary artery disease. analysis. Not applicable. quantitative loci analysis. Glomerular filtration rate estimated according to CKD-EPI creatinin.4 Overview of of genetic studies by data of LIFE-Heart Genome-wide association study. Coronary artery disease. analysis. Not applicable. quantitative loci analysis. Glomerular filtration rate estimated according to CKD-EPI creatinin.4 The major of LIFE-Heart is the of assessments for (almost) all patients. a sample size of assessed is of the largest studies worldwide with this Based on the comprehensive assessments of atherosclerotic cardiovascular disease status of patients, we can define a of CAD phenotypes for analyses and biomarker development. Patients were by a comprehensive set of laboratory variables and biospecimens were collected pre-analytical Finally, the of several data comprehensive analyses and molecular to the molecular of CAD. A of LIFE-Heart is that follow-up has not been completed for all patients. Moreover, status is causes of death are not available We to these in the near LIFE-Heart is an integral part of the LIFE Research Center for Civilization Diseases and is for studies with and Data can be on the of be to the corresponding The LIFE-Heart study was to and environmental risk factors of coronary artery disease (CAD) and their About patients with suspected or confirmed stable CAD or myocardial infarction were recruited at the Heart Center Leipzig between 2006 and 2014. all patients coronary angiography. Data comprise lifestyle and environmental cardiovascular risk factors including and physical activity, as well as physical including coronary carotid echocardiography and Patients were by a large panel of blood biomarkers and several layers including genetics, transcriptomics, and status of patients is continuously were initiated for of the A complete mail-based follow-up is LIFE-Heart is a part of the LIFE Research Center for Civilization to data can be on the of LIFE-Heart was funded by the Roland-Ernst by means of the European Union, by the European Regional Development Fund (ERDF) and by funds of the Free State of Saxony within the framework of the excellence initiative. We all patients of the LIFE-Heart study for their time and as well as for their in our follow-up We and for the study and for development. study and of study quality study recruitment and study recruitment and laboratory analyses and of data analysis and quality molecular and laboratory assessments and of from for a not related to this study.