OMICS session at the 35 th International symposium on Intensive Care and Emergency Medicine (ISICEM) symposium, 2015.
Omics: the basics.
Today we had the pleasure of attending the 35th ISICEM session on Omics during critical illness,
moderated by Prof. P Schuetz and Prof. B Kavanagh.
Prof. Brian Kavanagh (Toronto, Canada) works at the Hospital for Sick Children and he´s also Chair of the Department of Anesthesia at the University of Toronto.
Prof. Philipp Schuetz (Aarau, Switzerland) is an attending physician at the Kantonsspital Aarau, University of Basel.
1. Overview, by Tom van der Poll (Amsterdam, NL).
"Targeting specific components of the human genome in mixed populations can reduce heterogeneity".
In my opinion this was the best talk of the session. He did a good job on highlighting the importance of increasing the knowledge in medicine and taking that next text on tailored treatments according the individual characteristics.
Proteomic analysis of bodily fluids in critical care patients seems feasible and easy (in the majority of cases) and many have reported results, specially in the field of sepsis. But, does it come with a high price and thus only available to highly specialized centers?
2. Genomics, by Dr. Jean-Paul Mira (Paris, FR).
"The price is not the problem".
The key note of his lecture was when he left the stage: "we need a bank!!", an Omics bank. Definitively a great idea. A large database of samples from healthy control patients could be compared to samples from critical care patients and reduce time consuming efforts. Also, international cooperation of different groups working in clinical and animal research in Omics during critical illness will allow a more rapid development of the fill.
3. Transcriptomics, by Hector R. Wong (Cincinnati, USA).
"Powerful, unbiased approach for discovery and generating new hypothesis".
I really enjoy when he said that the future will be the integration of genomics, transcriptomics, proteinomics and metabolomics to answer a clinical question. It maid be feel that in the future we will need to re-think the way we treat patients. For now, Omits during critical illness remain an hypothesis generating method.
4. Proteomics, by Jochen Hinkelbein (Cologne, Germany)
"We must exclude certain proteins of no interest before doing the statistical analysis".
And it´s true...excessive amount of proteins that are of no interest (e.g albumin, fibrinogen) complicates the statistical analysis of your data set. How to choose witch protein to exclude? He recommended that high abundance proteins like albumin should be excluded. Low abundance proteins are not detected. So, he seem to said that we should focus on proteins that are between those ranges. However, this remains subjective and methods to exclude such proteins in a more objective way such be developed.
He recommended 2D electrophoresis as the method of choice for identifying proteins. However, i must say that this could not be true for patients with acute neurological emergencies. Many now recommend LC/MS as the method of choice for CSF analysis.
5. Metabolomics, by Kenneth Christopher (Boston, USA)
"Lost of homeostasis is a common trait of critical illness".
This talk was all about strategy. He said that untargeted metabolic strategies are time consuming, and tends to be bias towards the detection of abundant molecules. He then used the term false discovery rate (FDR), a source of bias present in the analysis of abundant molecules. He suggested principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA) has means to reduce dimensionality preserving variance of data.
6. Clinical applications, by Jean Daniel Chiche (Paris, FR)
" Evidence based medicine will evolve to precision medicine".
Omics has multiple applications in different fields of medicine. It can help select the correct quimotherapy in specific tumors but it could also help select the appropriate antibiotic in patients with sepsis. Specific treatment tailored to each individual patient will be the future. Also, predicting doses of vitamin k antagonist or platelet inhibitors by Omic-analysis of proteins related to drug metabolism will be possible. Finally, acquisition of big data sets from heterogenous population will allow for predictive models of disease and thus development of new strategies for treatment.
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