The new era of Big Data presents immense opportunities for a complex and heterogeneous disease such as cancer with many types and subtypes. The increasing availability of open datasets and advances in big data analytics and technologies gives researchers and healthcare professionals enormous power to study cancer and to provide personalized health solutions.

Big Data for Cancer (BD4Cancer) is an open data initiative for cancer research. The project aims at developing analytic frameworks and a large integrative database for cancer research and Big Data in pharmacovigilance and pharmacogenomics.

Key words : Cancer, Big Data, Open Data, Pharmacovigilance, Pharmacogenomics, BioNLP, Text Mining, Machine learing, Social Media.

Project Website : http://bd4cancer.tbiscientific.com

BD4Cancer on Data.Gouv.fr

Publications resulting from this project : Link

The availability and real-time nature of social media provides tremendous opportunities for digital drug safety surveillance and real-time monitoring of adverse drug reactions (ADRs).

Real-Time pharmacovigilance (RT-PharmacoVigil) was conceived to combine BioNLP algorithms and Big Data analysis of social media data for real-time pharmacovigilance.

Key words : Big Data, Open Data, Pharmacovigilance, Pharmacogenomics, BioNLP, Text Mining, Machine Learning, Social Media.

Project Website : http://bd4cancer.tbiscientific.com/RTpharmacovigil.html

Publications resulting from this project : Link

OMICtools is an open science initiative to develop the first platform centralizing life-sciences data analysis tools.

Key words : Omics, data analysis, bioinformatics, computational biology, software.

Project Website : https://omictools.com

Publications resulting from this project : Link

PostGWAS Knowledge Miner

Key words : GWAS, Omics, data analysis, bioinformatics, computational biology, software.

Publications resulting from this project : Link

ResExomeDB: an online catalog for exome sequencing results.

Key words : Exome sequencing, Omics, data analysis, bioinformatics, computational biology, software.

Publications resulting from this project : Link

The CARDIoGRAMplusC4D (Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) plus The Coronary Artery Disease (C4D) Genetics) is a collaborative initiative that was launched in 2011 to combine GWAS and eQTL data from multiple omics studies in coronary artery disease and myocardial infarction.

Key words : Genome-wide association study, GWAS, Meta-Analysis, Coronary Artery Disease, myocardial infarction, microarray.

Project Website : http://www.cardiogramplusc4d.org

Publications resulting from this project : Link

The Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) is a large scale international consortium in which 14 GWA studies for CAD and MI have been meta-analyzed. CARDIoGRAM included 22,233 cases and 64,762 controls. The design of this large consortium has been previously described in Preuss et al.(2010). The pooled analysis of this large sample sized has led to the identification of 13 new loci at genome-wide significance (Table 1 in Schunkert et al. (2011)). CARDIoGRAM has replicated previously identified common genetic variants. A review discussing the results of this transatlantic consortium have been published by Maouche and Schunkert (2012).

Key words : Genome-wide association study, GWAS, Meta-Analysis, Coronary Artery Disease, myocardial infarction, microarray.

Publications resulting from this project : Link

Cardiogenic is a large-scale EU-funded project within the 6th framework program (LSHM-CT-2006-037593). The project aims at studying the global transcriptional profiling of monocytes and macrophages and association with coronary artery disease risk factors in a large multi-center collaborative study.

Key words: circulating monocytes, monocyte heterogeneity, myocardial infarction, transcriptomics, microarray.

Project Website : https://www.cardiogenics.org

Publications resulting from this project : Link

Cardiogenic eQTL

Key words: Gene expression, eQTL, genetics of gene expression, Genome-wide association study, GWAS, Meta-Analysis, Coronary Artery Disease, myocardial infarction, microarray.

Project Website : https://www.cardiogenics.org

Publications resulting from this project : Link

I developed an R package for cardiogenics gene expression data

In this study, we compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers.

Key words: Genetics of gene expression, eQTL, allele-specific gene expression, ASE, Coronary Artery Disease, myocardial infarction, microarray.

Data availability : The allelic genotyping data and expression in this paper are in the process of being deposited in the EGA with accession number EGAS00000000119.

Publications resulting from this project : Link

In this project, temporal transcriptional profiling of human monocytes following myocardial infarction. The GerMIFS expression study

We performed microarray whole-genome temporal transcriptional profiling of monocytes following acute myocardial infarction (AMI). mRNAs were isolated from venous blood of 28 MI patients at t1: within 6 hours after onset of chest pain (acute phase), t2:3 days after MI (subacute phase), t3:90 days after MI (chronic phase). For comparison, we studied a control group(n=21) with stable CAD. Using flow cytometry and expression patterns specific to CD14+/CD16+ and CD14+/CD16- subsets, we investigated monocyte heterogeneity in MI.

This project was supported by the European Community funded Cardiogenics network (6th framework program; LSHM-CT-2006-037593), by the integrated project ENGAGE (201413), by the BMBF funded projects Atherogenomics (NGFN FKZ:01GS0831), and by CARDomics (FKZ:01KU0908B).

Key words : gene expression, circulating monocytes, monocyte heterogeneity, myocardial infarction, transcriptomics, microarray, gene-set enrichment analysis.

Data availability : Gene expression data generated within this project have been submitted to NCBI GEO database and are accessible using the code GSE28454.

Publications resulting from this project : Link

Communication :

Time-series and gene co-expression analyses of transcriptional changes in human monocyte RNAs after acute myocardial infarction. The GerMIFS study.

Maouche S, Belz S, Brocheton J, Proust C, Erdmann J, Schunkert H, Cambien F, and Linsel-Nitschke P.

The 17th Annual International conference on Intelligent Systems for molecular Biology and 8th European Conference on Computational Biology (ISMB/ECCB 2009), June 27 - July 2, 2009, Stockholm, Sweden.

This section is being updated.

Key words: Coronary artery disease, myocardial infarction, Gene expression, Microarrays.

Data availability : Gene expression data are available at this URL.

This section is being updated.

Key words: Systems genetics, Genome-wide association study, GWAS, Meta-Analysis, Coronary Artery Disease, myocardial infarction, microarray.

The Gutenberg Heart Study (GHS) is a population based prospective study initiated at the University Mainz Johannes Gutenberg (Mainz, Germany). GHS eQTL investigated the genetics of gene expression of circulating monocytes obtained from 1 490 unrelated individuals. Detailed description of this study can be found in Ziller et al. (2010).

Key words: Coronary artery disease, myocardial infarction, Gene expression, Genomics, eQTL, genetic of gene expression, monocyte, Microarrays.

Data availability : eQTL results are available at this URL.

Publications resulting from this project : Link

Key words: Macrophages, monocytes

Data availability : NCBI GEO (accession code: GSE18275)

Publication(s) : 21159337

Phospholipases are a group of enzymes that share the property of hydrolyzing phospholipids. They play pivotal roles in regulating signalling during numerous cellular events. Four families of phospholipases have been described and are named A, B, C and D.

This categorization is based on the stereospecifically numbered sites within phospholipids where they promote cleavage.

Secreted phospholipases A2 (sPLA2s) are a large family of these enzymes which catalyze the hydrolysis of glycophospholipids at the sn-2 position. They are present in atherosclerotic plaques and have emerged as promising therapeutic targets and potential biomarkers.

This project aims at studying the whole-genome transcriptional profiling of macrophages in response to LDL particles modified by human group X secreted phospholipase A2. The aim is the understanding of atherosclerotic mechanisms.

The project also studied the global transcriptional gene expression profiling of the response of endothelial cells exposed to either LDL or LDL-X.

Data availability : EBI ArrayExpress (accession code: E-MEXP-2256)

Publication(s) : 20430794

This section is being updated.

Key words: Genome-wide association study, GWAS, Coronary Artery Disease, myocardial infarction, microarray.

This section is being updated.

Key words: eQTL, Genome-wide association study, GWAS, Meta-Analysis, Coronary Artery Disease, myocardial infarction, microarray.

This section is being updated.

Key words: Microarray, Data quality.

Data availability : Illumina Data (accession code: GSE10213)
Affymetrix Data (accession code: GSE11430)
RNG/MRC Data (accession code: GSE10220)

Publication(s) : 18578872