Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory. Computer models are widespread in neuroscience, where they are used to mimic brain function at different levels. These models offer a variety of new possibilities for the neuroscientist, but also numerous challenges, such as: where to sample the input space for the simulator, how to make sense of the data that is generated, and how to estimate unknown parameters in the model. Statistical emulation can be a valuable complement to simulator-based research. Emulators are able to mimic the simulator, often with a much smaller computational burden and they are especially valuable for parameter estimation, which may require many simulator evaluations. This work compares different statistical models that address these challenges, and applies them to simulations of neocortical L2/3 large basket cells, created and run with the NEURON simulator in the context of the European Human Brain Project. The novelty of our approach is the use of fast empirical emulators, which have the ability to accelerate the optimization process for the simulator and to identify which inputs (in this case, different membrane ion channels) are most influential in affecting simulated features. These contributions are complementary, as knowledge of the important features can further improve the optimization process. Subsequent research, conducted after the process is completed, will gain efficiency by focusing on these inputs.

Hierarchical Data-Driven Analysis of Clinical Symptoms Among Patients With Parkinson's Disease

Mutations in the LRRK2 and GBA genes are the most common inherited causes of Parkinson's disease (PD). Studies exploring phenotypic differences based on genetic status used hypothesis-driven data-gathering and statistical-analyses focusing on specific symptoms, which may influence the validity of the results. We aimed to explore phenotypic expression in idiopathic PD (iPD) patients, G2019S-LRRK2-PD, and GBA-PD using a data-driven approach, allowing screening of large numbers of features while controlling selection bias. Data was collected from 1525 Ashkenazi Jews diagnosed with PD from the Tel-Aviv Medical center; 161 G2019S-LRRK2-PD, 222 GBA-PD, and 1142 iPD (no G2019S-LRRK2 or any of the 7 AJ GBA mutations tested). Data included 771 measures: demographics, cognitive, physical and neurological functions, performance-based measures, and non-motor symptoms. The association of the genotypes with each of the measures was tested while accounting for age at motor symptoms onset, gender, and disease duration; p-values were reported and corrected in a hierarchical approach for an average over the selected measures false discovery rate control, resulting in 32 measures. GBA-PD presented with more severe symptoms expression while LRRK2-PD had more benign symptoms compared to iPD. GBA-PD presented greater cognitive and autonomic involvement, more frequent hyposmia and REM sleep behavior symptoms while these were less frequent among LRRK2-PD compared to iPD. Using a data-driven analytical approach strengthens earlier studies and extends them to portray a possible unique disease phenotype based on genotype among AJ PD. Such findings could help direct a more personalized therapeutic approach.

Current and Potential Approaches for Defining Disease Signatures: a Systematic Review

Identifying disease signatures in order to facilitate accurate diagnosis/treatment has been the focus of research efforts in the last decade. However, the term "disease signature" has not been properly defined, resulting in inconsistencies between studies, as well as limited ability to fully utilize the tools/information available in the evolving field of healthcare big data. Research was conducted according to the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. The search (in PubMed, Cochrane, and Web of Science) was limited to English articles published up to 31/12/2016. The search string was "disease signature" OR "disease signatures" OR "disease fingerprint" OR "disease fingerprints" OR "subtype signature" OR "subtype signatures" OR "subgroup signature" OR "subgroup signatures." The full text of the articles was reviewed to determine the meaning of the phrase "disease signature" as well as the context of its use. Of 285 articles identified in the search, 129 were included in the final analysis. The term disease signature was first found in an article from 2001. In the last 10 years, the use of the term increased by approximately ninefold, which is double the general increase in the number of published articles. Only one article attempted to define the term. The two major medical fields where the term was used were oncology (31%) and neurology (20%); 71% of the identified articles used a single biomarker to define the term, 13% of the articles used a pair of biomarkers, and 16% used signatures with multiple biomarker; in 42% of the identified articles, genomic biomarkers were used for the signature, in 17% measurements of biochemical compounds in body fluids, and in 10%, changes in imaging studies were used for the signature. Our findings identified a lack of consistency in defining the term disease signature. We suggest a novel hierarchical multidimensional concept for this term that would combine both current approaches for identifying diseases (one focusing on undesired effects of the disease and the other on its causes). This model can improve disease signature definition consistency which will enable to generalize and classify diseases, resulting in more precise treatments and better outcomes. Ultimately, this model could lead to developing a statistical confidence in a disease signature that would allow physicians/patients to estimate the precision of the diagnosis, which, in turn, may have important implications on patients' prognosis and treatment.

The Importance of Nonlinear Transformations Use in Medical Data Analysis

Background

The accumulation of data and its accessibility through easier-to-use platforms will allow data scientists and practitioners who are less sophisticated data analysts to get answers by using big data for many purposes in multiple ways. Data scientists working with medical data are aware of the importance of preprocessing, yet in many cases, the potential benefits of using nonlinear transformations is overlooked.

Objective

Our aim is to present a semi-automated approach of symmetry-aiming transformations tailored for medical data analysis and its advantages.

Methods

We describe 10 commonly encountered data types used in the medical field and the relevant transformations for each data type. Data from the Alzheimer’s Disease Neuroimaging Initiative study, Parkinson’s disease hospital cohort, and disease-simulating data were used to demonstrate the approach and its benefits.

Results

Symmetry-targeted monotone transformations were applied, and the advantages gained in variance, stability, linearity, and clustering are demonstrated. An open source application implementing the described methods was developed. Both linearity of relationships and increase of stability of variability improved after applying proper nonlinear transformation. Clustering simulated nonsymmetric data gave low agreement to the generating clusters (Rand value=0.681), while capturing the original structure after applying nonlinear transformation to symmetry (Rand value=0.986).

Conclusions

This work presents the use of nonlinear transformations for medical data and the importance of their semi-automated choice. Using the described approach, the data analyst increases the ability to create simpler, more robust and translational models, thereby facilitating the interpretation and implementation of the analysis by medical practitioners. Applying nonlinear transformations as part of the preprocessing is essential to the quality and interpretability of results.

EPMA-World Congress 2015

A1 Predictive and prognostic biomarker panel for targeted application of radioembolisation improving individual outcomes in hepatocellular carcinoma

Jella-Andrea Abraham, Olga Golubnitschaja

A2 Integrated market access approach amplifying value of “Rx-CDx”

Ildar Akhmetov

A3 Disaster response: an opportunity to improve global healthcare

Russell J. Andrews, Leonidas Quintana

A4 USA PPPM: proscriptive, profligate, profiteering medicine-good for 1 % wealthy, not for 99 % unhealthy

Russell J. Andrews

A5 The role of IDO in a murine model of gingivitis: predictive and therapeutic potentials

Babak Baban, Jun Yao Liu, Xu Qin, Tailing Wang, Mahmood S. Mozaffari

A6 Specific diets for personalised treatment of diabetes type 2

Viktoriia V. Bati, Tamara V. Meleshko, Olga B. Levchuk, Nadiya V. Boyko

A7 Towards personalized physiotherapeutic approach

Joanna Bauer, Ewa Boerner, Halina Podbielska

A8 Cells, animal, SHIME and in silico models for detection and verification of specific biomarkers of non-communicable chronic diseases

Alojz Bomba, Viktor O. Petrov, Volodymyr G. Drobnych, Rostyslav V. Bubnov, Oksana M. Bykova, Nadiya V. Boyko

A9 INTERACT-chronic care model: Self-treatment by patients with decision support e-Health solution

Hans-Peter Brunner-La Rocca, Lutz Fleischhacker, Olga Golubnitschaja, Frank Heemskerk, Thomas Helms, Tiny Jaarsma, Judita Kinkorova, Jan Ramaekers, Peter Ruff, Ivana Schnur, Emilio Vanoli, Jose Verdu

A10 PPPM in cardiovascular medicine in 2015

Hans-Peter Brunner-La Rocca

A11 Magnetic resonance imaging of nanoparticles in mice, potential for theranostic and contrast media development – pilot results

Rostyslav V. Bubnov, Sergiy A. Grabovetskyi, Olena M. Mykhalchenko, Natalia O. Tymoshok, Oleksandr B. Shcherbakov, Igor P. Semeniv, Mykola Y. Spivak

A12 Ultrasound diagnosis for diabetic neuropathy - comparative study

Rostyslav V. Bubnov, Tetyana V. Ostapenko

A13 Ultrasound for stratification patients with diabetic foot ulcers for prevention and personalized treatment - pilot results

Rostyslav V. Bubnov, Nazarii M. Kobyliak, Nadiya M. Zholobak, Mykola Ya. Spivak

A14 Project ImaGenX – designing and executing a questionnaire on environment and lifestyle risk of breast cancer

John Paul Cauchi

A15 Genomics – a new structural brand of predictive, preventive and personalized medicine or the new driver as well?

Dmitrii Cherepakhin, Marina Bakay, Artem Borovikov, Sergey Suchkov

A16 Survey of questionnaires for evaluation of the quality of life in various medical fields

Barbara Cieślik, Agnieszka Migasiewicz, Maria-Luiza Podbielska, Markus Pelleter, Agnieszka Giemza, Halina Podbielska

A17 Personalized molecular treatment for muscular dystrophies

Sebahattin Cirak

A18 Secondary mutations in circulating tumour DNA for acquired drug resistance in patients with advanced ALK + NSCLC

Marzia Del Re, Paola Bordi, Valentina Citi, Marta Palombi, Carmine Pinto, Marcello Tiseo, Romano Danesi

A19 Recombinant species-specific FcεRI alpha proteins for diagnosis of IgE-mediated allergies in dogs, cats and horses

Lukas Einhorn, Judit Fazekas, Martina Muhr, Alexandra Schoos, Lucia Panakova, Ina Herrmann, Krisztina Manzano-Szalai, Kumiko Oida, Edda Fiebiger, Josef Singer, Erika Jensen-Jarolim

A20 Global methodology for developmental neurotoxicity testing in humans and animals early and chronically exposed to chemical contaminants

Arpiné A. Elnar, Nadia Ouamara, Nadiya Boyko, Xavier Coumoul, Jean-Philippe Antignac, Bruno Le Bizec, Gauthier Eppe, Jenny Renaut, Torsten Bonn, Cédric Guignard, Margherita Ferrante, Maria Liusa Chiusano, Salvatore Cuzzocrea, Gerard O'Keeffe, John Cryan, Michelle Bisson, Amina Barakat, Ihsane Hmamouchi, Nasser Zawia, Anumantha Kanthasamy, Glen E. Kisby, Rui Alves, Oscar Villacañas Pérez, Kim Burgard, Peter Spencer, Norbert Bomba, Martin Haranta, Nina Zaitseva, Irina May, Stéphanie Grojean, Mathilde Body-Malapel, Florencia Harari, Raul Harari, Kristina Yeghiazaryan, Olga Golubnitschaja, Vittorio Calabrese, Christophe Nemos, Rachid Soulimani

A21 Mental indicators at young people with attributes hypertension and pre-hypertension

Maria E. Evsevyeva, Elena A. Mishenko, Zurida V. Kumukova, Evgeniy V. Chudnovsky, Tatyana A. Smirnova

A22 On the approaches to the early diagnosis of stress-induced hypertension in young employees of State law enforcement agencies

Maria E. Evsevyeva, Ludmila V. Ivanova, Michail V. Eremin, Maria V. Rostovtseva

A23 Сentral aortic pressure and indexes of augmentation in young persons in view of risk factors

Maria E. Evsevyeva, Michail V. Eremin, Vladimir I. Koshel, Oksana V. Sergeeva, Nadesgda M. Konovalova

A24 Breast cancer prediction and prevention: Are reliable biomarkers in horizon?

Shantanu Girotra, Olga Golubnitschaja

A25 Flammer Syndrome and potential formation of pre-metastatic niches: A multi-centred study on phenotyping, patient stratification, prediction and potential prevention of aggressive breast cancer and metastatic disease

Olga Golubnitschaja, Manuel Debald, Walther Kuhn, Kristina Yeghiazaryan, Rostyslav V. Bubnov, Vadym M. Goncharenko, Ulyana Lushchyk, Godfrey Grech, Katarzyna Konieczka

A26 Innovative tools for prenatal diagnostics and monitoring: improving individual pregnancy outcomes and health-economy in EU

Olga Golubnitschaja, Jan Jaap Erwich, Vincenzo Costigliola, Kristina Yeghiazaryan, Ulrich Gembruch

A27 Immunohistochemical assessment of APUD cells in endometriosis

Vadym M. Goncharenko, Vasyl O. Beniuk, Olga V. Kalenska, Rostyslav V. Bubnov

A28 Updating personalized management algorithm of endometrial hyperplasia in pre-menopause women

Vadym M. Goncharenko, Vasyl O. Beniuk, Rostyslav V. Bubnov, Olga Melnychuk

A29 The personified treatment approach of polimorbid patients with periodontal inflammatory diseases

Irina A. Gorbacheva, Lyudmila Y. Orekhova, Vadim V. Tachalov

A30 Ukrainian experience in hybrid war – the challenge to update algorithms for personalized care and early prevention of different military injuries

Olena I. Grechanyk, Rizvan Ya. Abdullaiev, Rostyslav V. Bubnov

A31 Tear fluid biomarkers: a comparison of tear fluid sampling and storage protocols

Suzanne Hagan, Eilidh Martin, Ian Pearce, Katherine Oliver

A32 The correlation of dietary habits with gingival problems during menstruation

Cenk Haytac, Fariz Salimov, Servin Yoksul, Anatoly A. Kunin, Natalia S. Moiseeva

A33 Genomic medicine in a contemporary Spanish population of prostate cancer: our experience

Bernardo Herrera-Imbroda, Sergio del Río-González, Maria Fernanda Lara, Antonia Angulo, Francisco Javier Machuca Santa-Cruz

A34 Challenges, opportunities and collaborations for personalized medicine applicability in uro-oncological disease

Bernardo Herrera-Imbroda, Sergio del Río-González, Maria Fernanda Lara

A35 Metabolic hallmarks of cancer as targets for a personalized therapy

John Ionescu

A36 Influence of genetic polymorphism as a predictor of the development of periodontal disease in patients with gastric ulcer and 12 duodenal ulcer

Alfiya Z. Isamulaeva, Anatoly A. Kunin, Shamil Sh. Magomedov, Aida I. Isamulaeva

A37 Challenges in diabetic macular edema

Tatjana Josifova

A38 Overview of the EPMA strategies in laboratory medicine relevant for PPPM

Marko Kapalla, Juraj Kubáň, Olga Golubnitschaja, Vincenzo Costigliola

A39 EPMA initiative for effective organization of medical travel: European concepts and criteria

Vincenzo Costigliola, Marko Kapalla, Juraj Kubáň, Olga Golubnitschaja

A40 Design and innovation in e-textiles: implications for PPPM

Anthony Kent, Tom Fisher, Tilak Dias

A41 Biobank in Pilsen as a member of national node BBMRI_CZ

Judita Kinkorová, Ondřej Topolčan

A42 Big data in personalized medicine: hype and hope

Matthias Kohl

A43 The 3P approach as the platform of the European Dentistry Department (DPPPD)

Anatoly A. Kunin, Natalia S. Moiseeva

A44 The endometrium cytokine patterns for predictive diagnosis of proliferation severity and cancer prevention

Andrii I. Kurchenko, Vasyl A. Beniuk, Vadym M. Goncharenko, Rostyslav V. Bubnov, Nadiya V. Boyko, Andriy M. Strokan

A45 A monocyte-based in-vitro system for testing individual responses to the implanted material: future for personalized implant construction

Julia Kzhyshkowska, Alexandru Gudima, Ksenia S. Stankevich, Victor D. Filimonov⁴, Harald Klüter, Evgeniya M. Mamontova, Sergei I. Tverdokhlebov

A46 Prediction and prevention of adverse health effects by meteorological factors: Biomarker patterns and creation of a device for self-monitoring and integrated care

Ulyana B. Lushchyk, Viktor V. Novytskyy, Igor P. Babii, Nadiya G. Lushchyk, Lyudmyla S. Riabets, Ivanna I. Legka

A47 Targeting "disease signatures" towards personalized healthcare

Mira Marcus-Kalish, Alexis Mitelpunkt, Tal Galili, Neta Shachar, Yoav Benjamini

A48 Influence of the skin imperfection on the personal quality of life and possible tools for objective diagnosis

Agnieszka Migasiewicz, Markus Pelleter, Joanna Bauer, Ewelina Dereń, Halina Podbielska

A49 The new direction in caries prevention based on the ultrastructure of dental hard tissues and filling materials

Natalia S. Moiseeva, Anatoly A. Kunin, Dmitry A. Kunin

A50 The use of LED radiation in prevention of dental diseases

Natalia S. Moiseeva, Yury A. Ippolitov, Dmitry A. Kunin, Alexei N. Morozov, Natalia V. Chirkova, Nakhid T. Aliev

A51 Status of endothelial progenitor cells in diabetic nephropathy: predictive and preventive potentials

Mahmood S. Mozaffari, Jun Yao Liu, Babak Baban

A52 The status of glucocorticoid-induced leucine zipper protein in salivary gland in Sjögren’s syndrome: predictive and personalized treatment potentials

Mahmood S. Mozaffari, Jun Yao Liu, Rafik Abdelsayed, Xing-Ming Shi, Babak Baban

A53 Maximal aerobic capacity - important quality marker of health

Jaroslav Novák, Milan Štork, Václav Zeman

A54 The EMPOWER project: laboratory medicine and Horizon 2020

Wytze P. Oosterhuis, Elvar Theodorsson

A55 Personality profile manifestations in patient’s attitude to oral care and adherence to doctor’s prescriptions

Lyudmila Y. Orekhova, Tatyana V. Kudryavtseva, Elena R. Isaeva, Vadim V. Tachalov, Ekaterina S. Loboda

A56 Results of an European survey on personalized medicine addressed to directions of laboratory medicine

Mario Pazzagli, Francesca Malentacchi, Irene Mancini, Ivan Brandslund, Pieter Vermeersch, Matthias Schwab, Janja Marc, Ron H.N. van Schaik, Gerard Siest, Elvar Theodorsson, Chiara Di Resta

A57 MCI or early dementia predictive speech based diagnosis techniques

Matus Pleva, Jozef Juhar

A58 Personalized speech based mobile application for eHealth

Matus Pleva, Jozef Juhar

A59 Circulating tumor cell-free DNA as the biomarker in the management of cancer patients

Jiří Polívka jr., Filip Janků, Martin Pešta, Jan Doležal, Milena Králíčková, Jiří Polívka

A60 Complex stroke care – educational programme in Stroke Centre University Hospital Plzen

Jiří Polívka, Alena Lukešová, Nina Müllerová, Petr Ševčík, Vladimír Rohan

A61 Sleep apnea and sleep fragmentation contribute to brain aging

Kneginja Richter, Lence Miloseva, Günter Niklewski

A62 Personalised approach for sleep disturbances in shift workers

Kneginja Richter, Jens Acker, Guenter Niklewski

A63 Medical travel and innovative PPPM clusters: new concept of integration

Olga Safonicheva, Vincenzo Costigliola

A64 Medical travel and women health

Olga Safonicheva

A65 Continuity of generations in the training of specialists in the field of reconstructive microsurgery

Maxim Sautin, Janna Sinelnikova, Sergey Suchkov

A66 Telemonitoring of stroke patients – empirical evidence of individual risk management results from an observational study in Germany

Songül Secer, Stephan von Bandemer

A67 Women’s increasing breast cancer risk with n-6 fatty acid intake explained by estrogen-fatty acid interactive effect on DNA damage: implications for gender-specific nutrition within personalized medicine

Niva Shapira

A68 Cytobacterioscopy of the gingival crevicular fluid as a method for preventive diagnosis of periodontal diseases

Aleksandr Shcherbakov, Anatoly A. Kunin, Natalia S. Moiseeva

A69 Use of specially treated composites in dentistry to avoid violations of aesthetics

Bogdan R. Shumilovich, Zhanna Lipkind, Yulia Vorobieva, Dmitry A. Kunin, Anastasiia V. Sudareva

A70 National eHealth system – platform for preventive, predictive and personalized diabetes care

Ivica Smokovski, Tatjana Milenkovic

A72 The common energy levels of Prof. Szent-Györgyi, the intrinsic chemistry of melanin, and the muscle physiopathology. Implications in the context of Preventive, Predictive, and Personalized Medicine

Arturo Solís-Herrera, María del Carmen Arias-Esparza, Sergey Suchkov

A73 Plurality and individuality of hepatocellular carcinoma: PPPM perspectives

Krishna Chander Sridhar, Olga Golubnitschaja

A74 Strategic aspects of higher medical education reforms to secure newer educational platforms for getting biopharma professionals matures

Maria Studneva, Sihong Song, James Creeden, Мark Мandrik, Sergey Suchkov

A75 Overview of the strategies and activities of the European Federation of Clinical Chemistry and Laboratory Medicine, (EFLM)

Elvar Theodorsson, EFLM

A76 New spectroscopic techniques for point of care label free diagnostics

Syed A. M. Tofail

A77 Tumor markers for personalized medicine and oncology - the role of Laboratory Medicine

Ondřej Topolčan, Judita Kinkorová, Ondřej Fiala, Marie Karlíková, Šárka Svobodová, Radek Kučera, Radka Fuchsová, Vladislav Třeška, Václav Šimánek, Ladislav Pecen, Jan Šoupal, Štěpán Svačina²

A78 Modern medical terminology (MMT) as a driver of the global educational reforms

Evgeniya Tretyak, Maria Studneva, Sergey Suchkov

A79 Juvenile hypertension; the relevance of novel predictive, preventive and personalized assessment of its determinants

Francesca M. Trovato, G. Fabio Martines, Daniela Brischetto, Daniela Catalano, Giuseppe Musumeci, Guglielmo M. Trovato

A80 Proteomarkers Biotech

George Th. Tsangaris, Athanasios K. Anagnostopoulos

A81 Proteomics and mass spectrometry based non-invasive prenatal testing of fetal health and pregnancy complications

George Th. Tsangaris, Athanasios K. Anagnostopoulos

A82 Integrated Ecosystem for an Integrated Care model for Heart Failure (HF) patients including related comorbidities (ZENITH)

José Verdú, German Gutiérrez, Jordi Rovira, Marta Martinez, Lutz Fleischhacker, Donna Green, Arthur Garson, Elena Tamburini, Stefano Cuomo, Juan Martinez-Leon, Teresa Abrisqueta, Hans-Peter Brunner-La Rocca, Tiny Jaarsma, Teresa Arredondo, Cecilia Vera, Giuseppe Fico, Olga Golubnitschaja, Fernando Arribas, Martina Onderco, Isabel Vara, on behalf of ZENITH consortium

A83 Predictive, preventive and personalized medicine in diabetes onset and complication (MOSAIC project)

José Verdú, Francesco Sambo, Barbara Di Camillo, Claudio Cobelli, Andrea Facchinetti, Giuseppe Fico, Riccardo Bellazzi, Lucia Sacchi, Arianna Dagliati, Daniele Segnani, Valentina Tibollo, Manuel Ottaviano, Rafael Gabriel, Leif Groop, Jacqueline Postma, Antonio Martinez, Liisa Hakaste, Tiinamaija Tuomi, Konstantia Zarkogianni, on behalf of MOSAIC consortium

A84 Possibilities for personalized therapy of diabetes using in vitro screening of insulin and oral hypoglycemic agents

Igor Volchek, Nina Pototskaya, Andrey Petrov

A85 The innovative technology for personalized therapy of human diseases based on in vitro drug screening

Igor Volchek, Nadezhda Pototskaya, Andrey Petrov

A86 Bone destruction and temporomandibular joint: predictive markers, pathogenetic aspects and quality of life

Ülle Voog-Oras, Oksana Jagur, Edvitar Leibur, Priit Niibo, Triin Jagomägi, Minh Son Nguyen, Chris Pruunsild, Dagmar Piikov, Mare Saag

A87 Sub-optimal health management – global vision for concepts in medical travel

Wei Wang

A88 Sub-optimal health management: synergic PPPM-TCAM approach

Wei Wang

A89 Innovative technologies for minimal invasive diagnostics

Andreas Weinhäusel, Walter Pulverer, Matthias Wielscher, Manuela Hofner, Christa Noehammer, Regina Soldo, Peter Hettegger, Istvan Gyurjan, Ronald Kulovics, Silvia Schönthaler, Gabriel Beikircher, Albert Kriegner, Stephan Pabinger, Klemens Vierlinger

A90 Rare disease diobanks for personalized medicine

Ayşe Yüzbaşıoğlu, Meral Özgüç, Member of EuroBioBank - European Network of DNA, Cell and Tissue Banks for Rare Diseases

The influence of Erythropoietin on platelet activation, thrombin generation and FVII/active FVII in patients with AMI

BACKGROUND

Erythropoietin (Epo) has been shown to improve myocardial function in models of experimental myocardial infarction, but has also been associated with a rise in thromboembolic events. Thus, the aim of this study was to investigate the influence of Epo on platelet activation and coagulation in patients with acute myocardial infarction (AMI).

METHODS

The study was designed as a substudy of the randomised, double-blind, placebo controlled REVIVAL-3 (REgeneration of VItal Myocardium in ST-Segment EleVation MyocardiAL Infarction by Erythropoietin) study that investigated the effects of recombinant human Epo in AMI. Serial venous blood samples were collected before and after study medication. Circulating prothrombin fragment F1 + 2, FVII, active FVII, beta thromboglobulin (TG) and P-Selectin were measured before and 60 hours after randomization by immunoassay (n = 94). In a randomly selected subgroup platelet aggregation was measured using whole blood aggregometry (Multiplate Analyzer, n = 45).

RESULTS

After 5 days an increase in FVII was observed after Epo as compared to placebo (P = 0.02), yet active FVII and prothrombin fragment F1 + 2 remained unchanged. Moreover, no statistically significant differences in circulating TG or P-selectin were observed between the groups. As an expected response to peri-interventional therapy with clopidogrel and aspirin, platelet aggregation after stimulation with ADP, TRAP, ASPI or collagen decreased 12 hours and 2 days after PCI. However, no difference between the Epo and the placebo group was observed.

CONCLUSION

After treatment with Epo in patients with AMI a slight increase in circulating FVII after Epo was not associated with an increase in active FVII, prothrombin fragment F1 + 2, TG or P-selectin. Moreover, platelet aggregation was not altered after treatment with Epo as compared to placebo.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01761435.

The simultaneous systematic analysis approach for personalized management of cardiovascular diseases

The simultaneous systematic analysis (SSA) approach, emanating from the novel achievements in science and technology, is targeted to provide a broad insight into the human body physical and mental functioning in various surroundings. Thus it paves the way to personalized, preventive and predictive medicine. The goal is to form an ongoing collaborative research and development platform focusing on the micro and macroenvironmental factors of the complex human functioning. This approach aims to build an open, innovative, systematic joint effort, combining and sharing all acquired knowledge and expertise among the leading professionals in all relevant areas of science and technology, while reducing technical, conceptual and formal barriers. The CHEST methodology (converging humanities, education, science and technology) will be utilized, as an innovative meeting point, enabling open and coherent discussions among all stakeholders from all relevant disciplines. The SSA approach is complementary and fully aligned with the partitioned research, creating a well-structured joint effort, ongoing R&D sharing and borderless discussions among the academic research, government, regulatory agencies, industry, and the public. Bringing on board all stakeholders including young students, could provide innovative outcomes and new regulations adjusted to the new era. This review study focuses on the cardiovascular diseases (CVDs) diagnosis and treatment case study, as CVDs accounts for about one third of human morbidity and mortality and is a main driver in the biomedical and drug industries. The American Heart Association (AHA) in its 2020 published health goals reflect a similar attitude and thus provides strong support to the SSA approach. It is the authors’ contention that applying the SSA approach could provide the essential comprehensive insight into individual complex functioning over time and place. Thus, it would enable responsible personalized, accessible healthcare and yielding major economical and sociological impact on society.