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Session Chair: Justin O'Grady, Quadram Insitute Bioscience, United Kingdom
Location:HS 14 ZHG -- Lecture Hall 14
The End of Medicine as we know it.
Harald H.H.W. Schmidt
Department of Pharmacology and Personalised Medicine, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands
Following the IT revolution, the next socio-economic revolution appears to be a complete redefinition of health and disease, how we define them, how we handle them and how we finance this. Such revolutions follow upon a major crisis, and medicine is in a crisis. Existing drugs fail to provide benefit for most patients. The efficacy of drug discovery is in a constant decline and big pharma about to disappear in its current form by the end of the 2020s. Biomedical research has a poor translational success rate due to false incentives, lack of quality/reproducibility and publication bias. The most important reason and need for change, however, is our current concept of disease, i.e. mostly 19th/20th century-derived and based on organs or symptoms, but hardly every by mechanisms. Without a disease mechanism, however, no curative therapy is possible. Enabled by big-data and interdisciplinary research with applied bioinformaticians, the new Systems Medicine will lead to a mechanism-based redefinition of disease, precision diagnosis and therapy eliminating the need for drug discovery and a complete reorganization of how we teach, train and practice medicine.
Precision Medicine beyond Cancer: Why We Need New Multi-Omics Driven Definitions for Health & Disease
InnVentis Ltd, Germany
Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease” describes the concept to generate a molecularly-informed taxonomy of disease. This presentation addresses key challenges in data collection and labeling to achieve this goal.
Circulating miRNAs as Potential Biomarkers
Technical University of Munich, Germany
Non-cellular blood circulating microRNAs (plasma miRNAs) represent a promising source for the development of prognostic and diagnostic tools owing to their minimally invasive sampling, high stability, and simple quantification by standard techniques such as RT-qPCR. In this talk, I'll briefly present projects investigating the potential of plasma miRNAs both in a population-based cohort study and in patient cohorts for specific diseases.
We profiled circulating miRNAs in the population-based sohort study SHIP and investigated associations with age, sex, BMI. After regressing out technical parameters and adjusting for the respective other two phenotypes, 7, 15, and 35 plasma miRNAs were significantly (q < 0.05) associated with age, BMI, and sex, respectively. Adjustment for blood cell parameters slightly increased the number of age- or BMI-associated miRNAs but drastically reduced the number of sex-associted miRNAs. These findings emphasize that circulating miRNAs are strongly impacted by age, BMI, and sex. These parameters should be considered as covariates in association studies based on plasma miRNA levels. The established experimental and computational workflow can be used in future screening studies to determine associations of plasma miRNAs with defined disease phenotypes.
In a multicentre, prospective ACS cohort, 1002 out of 2168 patients presented with ST-segment elevation myocardial infarction (STEMI). Sixty-three STEMI patients experienced an adjudicated major cardiovascular event (MACE, defined as cardiac death or recurrent myocardial infarction) within 1 year of follow-up. From a miRNA profiling in a matched derivation case–control cohort, 14 miRNAs were selected for validation. Comparing 63 cases vs. 126 controls, miR-26b-5p levels (P=0.038) were decreased, whereas miR-320a (P=0.047) and miR-660-5p (P=0.01) levels were increased in MACE patients. MiR-26b-5p has been suggested to prevent adverse cardiomyocyte hypertrophy, whereas miR-320a promotes cardiomyocyte death and apoptosis, and miR-660-5p has been related to active platelet production. This suggests that miR-26b-5p, miR-320a, and miR660-5p may reflect alterations of different pathophysiological pathways involved in clinical outcome after ACS. These three miRNAs also discriminated cases from controls in age- and sex-adjusted Cox regression (AUC=0.718). Addition of the three miRNAs to both, the Global Registry of Acute Coronary Events (GRACE) score and a clinical model led to a net reclassification improvement of 0.20 in both cases.