Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

Introduction: Notably differences in CYP2C9 allele frequencies among worldwide populations have been reported, with an interesting low frequency of the CYP2C9*2 allele in Amerindians compared with ...

Global precision medicine demands characterization of drug metabolism and phenotype variation in diverse populations, including the indigenous societies. A related question is the extent to which CYP450 drug metabolizing enzyme genotype and phenotype data are concordant and whether they can be used interchangeably. These issues are increasingly debated as precision medicine continues to expand as a popular research topic worldwide. We report here the first study in clinically relevant CYP450 drug metabolism phenotypes and genotypes in Mexican Amerindian indigenous subjects. In a large sample of 450 unrelated and medication free Mexican Amerindian indigenous healthy persons from four Mexican states (Chihuahua, Durango, Nayarit, and Sonora), we performed multiplexed phenotyping for the CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 drug metabolizing enzymes using the CEIBA cocktail and genotyped the same pathways for functional polymorphic variation. Remarkable interindividual variability was found for the actual drug metabolizing capacity of all the enzymes analyzed, and, more specifically, the metabolic ratios calculated were significantly different across individuals with different number of active alleles for CYP2C9 , CYP2C19 , and CYP2D6 . The drug metabolizing capacity “predicted” from the genotype determined was not in accordance with the actual capacity “measured” by phenotyping in several individuals for CYP2C9, CYP2C19, and CYP2D6. Consequently, a more extensive genotyping of the main CYP enzymes, including rare variants, together with the analysis of the actual drug metabolizing capacity using an appropriate phenotyping approach will add valuable information for accurate drug metabolism studies, especially useful in understudied populations such as Mexican Amerindians. In sum, this study demonstrates that current personalized medicine strategies based on “predicted” phenotype from genotyping of alleles with high frequency in European populations are not adequate for Mestizos and Native American populations.

Depression is a common, severe, disabling mental disease that affects millions of people of all ages worldwide. Various studies have shown that neurotrophic/growth factors have a key role in depression and, more specifically, vascular endothelial growth factor (VEGF) is implicated in the pathogenesis of depression. The purpose of this study was to investigate the potential links between four VEGF-related single-nucleotide polymorphisms (SNPs), previously identified through a genome-wide association study (GWAS) and depression. The direct effects and epistatic interactions of the four VEGF-related SNPs (rs10738760, rs6921438, rs6993770 and rs4416670) on depression were investigated through a case–control study including 437 individuals diagnosed with depression and 477 healthy volunteers as controls. Gender, age and body mass index influence was additionally analyzed. The SNP rs4416670 was associated with increased risk for depression (OR: 1.60, P: 0.010). This result demonstrates the existence of relationships between VEGF genetic determinants and depression. This novel association reveals new molecular mechanisms suggesting the potential role of VEGF in depression development that could help to promote a personalized prediction for this severe common disease.