Leiden-Brazil Summer School on Data Science in Health and Disease
- Big Data Analytics applications to guide patient care in Brazil: examples from a tertiary-care Hospital and a National Primary Care program.
By Dr. Edson Amaro (Albert Einstein Hospital)
- Molecular epidemiology, big data and the generation and use of predictors
By Prof. Dr. Eline Slagboom (LUMC)
- Whole-genome sequencing of 1,171 elderly admixed individuals from the largest Latin American metropolis
By Prof. Dr. Michel Satya Naslavsky (USP)
- From GWAS to functional genomics
By Dr. Rodrigo C. de Almeida (LUMC)
- “Omics” for Infectious Diseases
By Prof. Dr. Annemieke Geluk (LUMC)
- Genetics of Leprosy – expected and unexpected developments
By Prof. Dr. Marcelo Tavora Mira (PUCPR)
- Applications of Metabolomics in leprosy and tuberculosis research
By Dr. Cristiana Macedo (FIOCRUZ)
- Translating Omics to the Field
By Prof. Dr. Annemieke Geluk (LUMC)
- The study of Tuberculosis from model systems to the clinic
By Prof. Dr. Fons Verbeek and Prof. Dr. Herman Spaink (Leiden University)
- Tools for large scale readout and processing in the life sciences
By Prof. Dr. Fons Verbeek (Leiden University)
- Modelling Tuberculosis, a computational approach
By Dr. Rafael R. Carvalho (Pontifical Catholic University of Goiás)
- Natural Products as new drug candidates for tuberculosis treatment
By Michelle Frazao Muzitano (UFRJ)
Big Data, Genetics and Omics Analytics in Population Health, Hospital Care and the pathophysiology of ageing and disease.
During the course of life, human individuals develop physiological changes that make them vulnerable for loss of function and development of disease. Our Brazil and Dutch Ageing societies testify the diversity of this process. The genetic make-up plays a vital role, especially earlier in life, and so do the environmental hazards one is exposed to throughout life, including lifestyle and hospitalization. Major technical developments and professionalization in biomedical data acquisition, record linkage and data mining makes it possible to place the unique person in the center and study health and well being in an integrated fashion from a diversity of data sources. This to guide patient care, predict vulnerabilities and provide personalized treatment.
Clinical, multi-omics and genetics research at USP and Albert Einstein in Brazil parallels that of the Leiden University Medical Center in The Netherlands. The course will start by Dr. Amaro (Albert Einstein Hospital) at the clinical level demonstrating how big data analytics of Hospital care data can be applied for the quality of care and the well-being of the patient. Next Professor Slagboom will indicate how quantitative multi-omics data (such as epigenome and metabolome information) can help in predicting vulnerabilities of older persons outside and inside the hospital. The host genetics element and especially the challenges and opportunities of studying the admixed Brazilian individuals and their genomes is discussed by Prof. Dr. Michel Satya Naslavsky (USP). And finally, Dr Rodrigo Coutinho de Almeida (LUMC) will explain the etiological element of multi-omics data analysis by illustrating how the specificities of genetic variation can be translated in functionality and vulnerability to disease.
The course will be followed up by a practical session on day 5 of the course.
Omics for Infectious diseases
Tuberculosis (caused by Mycobacterium tuberculosis) is one of the deadliest diseases globally and remains a major health problem.
Leprosy (caused by Mycobacterium leprae) ranks second after TB in the order of severe human mycobacterial diseases. Although leprosy is an ancient infectious disease that has been infamous for its feared disabilities and deformities for ages, it still poses a considerable health threat in LMIC of which Brazil is the second most affected country globally.
Early diagnosis is vital to stop the still ongoing transmission. However, both TB and leprosy lack sensitive, specific diagnostic tools which hampers stopping transmission of the bacteria causing these poverty associated diseases.
The research of the Geluk group at the LUMC is focused on immunodiagnosis of leprosy and TB and includes basic-, translational-, applied- as well as field research aimed to identify mechanisms of disease as well as host biomarkers using “Multi-omics”.
Within this research, Geluk has collaborated for over 20 years with researchers in Brazil, e.g. at the Oswaldo Cruz Foundation (FIOCRUZ) in Rio de Janeiro and the Pontifical Catholic University of Paraná (PUCPR) in Curitiba.
This course will start with an introduction on the aims of TB and leprosy research and will address how in general multi-omics can be used to tackle the current research challenges.
This will include a presentation by Dr. Cristiana Macedo (Fiocruz) on metabolomics and lipidomics in leprosy and TB using mass spectrometry to detect mycobacterial lipids.
Genomics will be addressed by Prof. dr. Mira who is an expert in identifying genetic risk factors contributing to the control of complex diseases, with focus on leprosy involving a unique, highly endemic population of an isolated, former leprosy colony located in the outskirts of the Amazon, north of Brazil. His presentation will address modern technologies, high throughput genotyping and next generation sequencing, combined with various genetic analyses to investigate the molecular basis of leprosy.
The course will be followed up by a practical session on day 6 of the course.
Data Science for Tuberculosis Research - a multidisciplinary approach
The plan for the data science part is as follows.
- Present a case study in Tuberculosis
- Understand the networks that are involved in TB
- What compounds can influence the networks and how
- How do we investigate large amounts of compounds?
The first part of the lectures will be on the presentation of the problem.
A modelling of the networks will show how everything connects in different layers of detail.
This model is used to consider some changes in “what-if” scenarios.
Tools important for network analysis are explained. As are tools for data analysis that support the networks. As we intend to obtain “new knowledge” it is probed how that can be visualized. The information that is considered is of a complex nature and therefore a visualization should support the fast understanding of this information. In this manner new information can be brought on the table for discussion and evaluation.
Natural compounds, as they are “found” in Brazil, can contribute to cure of diseases like TB. We present a case study in which compounds are presented that can have this effect. These compounds should be related to the networks and model of TB that we have discussed. In addition, a readout is presented of the application of compounds to a model system (zebrafish). The readout should be analysed and experiments for new compounds should be designed such that the right data are obtained.
Model system research must be translated to the clinic. The data from the model systems must be analysed in view of a transfer to clinical applications. This is elaborated for 2 case studies in different model systems.
The course will be followed up by a practical session on day 7 of the course.