Group of Clinical Genomic Networks - Research

Department of  Combinatorics and Geometry - CAS-MPG Partner Institute for Computational Biology

 

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Translational research represents a novel approach to life sciences with the specific goal to enhance and accelerate their applications in healthcare. In particular, it focuses on multi-disciplinary collaboration among life sciences, exact sciences. and medicine, with the aim of advancing “molecular-based medicine”. In fact, it aims to enable physicians to leverage systems- and computational-biology approaches to allow early detection of complex diseases, increase efficiency in drug development and therapy testing, improve drug efficacy, and enable personalized medicine. Such an approach is necessary

·         to narrow the gap existing between clinical practice and basic research,

·         to accelerate the bidirectional flow of scientific discoveries into the clinic and of clinical findings into novel research directions, and

·         to realize the (crucial !) return on investment made by private and public institutions on life science basic research (as pursued for example by the NIH Clinical and Translational Science Awards network).

To fully realize this vision, translational research requires researchers and clinicians to have access to three types of information

(1)        clinical information, including data contained in hospital systems and medical records, pathology reports and diagnostic labs, clinical trials systems and study participant questionnaires;

(2)        biomolecular information, including genomics, proteomics, medical imaging and other high-throughput molecular and cellular research data;

(3)        methods and tool to synergistically process the data described above.

Our group contributes to this vision with research on two families of diseases, metabolic and immune syndromes that appear to be ultimately intertwined via the disruption of the immune system.

The two projects are intertwined since, in fact, the study of the GI microbiome is tightly related to the functioning of the immune system, crucial in autoimmune diseases.

 

RA Project. we are interested in enhancing the treatment of Rheumatoid Arthritis (RA), a complex autoimmune disorder. In particular, we intend to perform differential molecular analysis of the effect of different clinical treatments (including TCM procedures) of poorly understood diseases by integrating distinct layers of molecular information (transcriptional and post-transcriptional). The goal is to understand how treatments work at the molecular, and in particular the transcriptional level in order to improve therapies and reduce side effects. This is done in our lab using the following three approaches:

-          Methods and tools: We develop computational approaches to infer the association between clinical traits and genomic data, by designing and adapting ad-hoc statistics.

-          Biomolecular information: We process high-throughput proteomic, transcriptional, and post-transcriptional data from patients in the acute and post-acute phase of RA to infer the differential molecular effect of various treatments.

Clinical Information: We have a consulting contract with the Renji and Longhua Hospitals of Shanghai to collect blood samples and clinical information from patients, to be related to the molecular information.

This multiomic integration will be used as a base and adapted to allow the detection of specific and sensitive target molecules in the identification of mouse stem cell differentiation. This work will be done in collaboration with the Institute of Electrical Engineering and the Integrated Systems Centre at  EPF Lausanne, Switzerland, with funds from the Sino-Swiss Science and Technology Cooperation Program, in the Project “Nano-structured Bio-Chip development for Stem Cells Monitoring.

 

 

 

 

 


Metabolic Syndromes We are interested in the etiology of metabolic syndromes, in particular in the functioning of the GastroIntestinal (GI) microbiome which is the ensemble of microorganisms living in and with us. It contributes to our proper development, to homeostasis, and certainly to a number of other functions. Focusing on this aspect, humans can be seen as super-organisms (Nichols et al., 2004) with a total genome composed of human and microbiotic genes, all synergistically influencing our state of health and disease, in particular in Metabolic Syndromes (MS). Investigation of the relationship between the etiology of MS and the variations of the microbiome is done in our lab using the following three approaches:

-          Methods and tools: We develop systems-biology approaches (network reconstruction) to uncover gene-gene interactions with and in GI bacteria.

-          Biomolecular information: We cultivate in our lab bifidobacterium, a key player in the GI, and we harvest cells to study variations of the gene expression to uncover the genomic interactions networks of this organism. Here, we collaborate with the Ministry of Education Laboratory of Systems Biomedicine at SJTU to obtain and interpret data at the metagenomic level with the aim of understanding the interplay of different bacterial populations and their role in changing a patient’s state.

-          Clinical Information: We collaborate with the Ministry of Education Laboratory of Systems Biomedicine at SJTU also to obtain clinical human data of MbS-affected patients, for analysis and joint interpretation.

Contributions to this work will come from Dr. J.E. Dent from the Veterinary Laboratory Agency (VLA), UK, who will work for 18 months in our lab funded by the Grant for “Science & Technology Fellowship Programme in China”, funded by the European Commission for sponsored collaboration at PICB.

 

Nano-structured Bio-Chip development for Stem Cells Monitoring Project. The project aims at the development of a bio-chip for metabolic detection in stem cell culture medium for on-line monitoring stem cells differentiation. The full set of metabolic molecules to be monitored will be identified by means of Statistical-Computational Techniques for Extraction of Functional Genomic Units from high-throughput molecular Experiments. This work will be done in collaboration with the Institute of Electrical Engineering and the Integrated Systems Centre at  EPF Lausanne, Switzerland, with funds from the Sino-Swiss Science and Technology Cooperation Program.