Discretization of expression quantitative trait loci in association analysis between genotypes and expression data

Expression quantitative trait loci are used as a tool to identify genetic causes of natural variation in gene expression. Only in a few cases the expression of a gene is controlled by a variant on a single genetic marker. There is a plethora of different complexity levels of interaction effects within markers, within genes and between marker and genes. This complexity challenges biostatisticians and bioinformatitians every day and makes findings difficult to appear. As a way to simplify analysis and better control confounders, we tried a new approach for association analysis between genotypes and expression data. We pursued to understand whether discretization of expression data can be useful in genome-transcriptome association analyses. By discretizing the dependent variable, algorithms for learning classifiers from data as well as performing block selection were used to help understanding the relationship between the expression of a gene and genetic markers. We present the results of using this approach to detect new possible causes of expression variation of DRB5, a gene playing an important role within the immune system. Together with expression of gene DRB5 obtained from the classical microarray technology, we have also measured DRB5 expression by using the more recent next-generation sequencing technology. A supplementary website including a link to the software with the method implemented can be found at http: //bios.ugr.es/DRB5

A comparison of genomic profiles of complex diseases under different models

Background: Various approaches are being used to predict individual risk to polygenic diseases from data provided by genome-wide association studies. As there are substantial differences between the diseases investigated, the data sets used and the way they are tested, it is difficult to assess which models are more suitable for this task. Results: We compared different approaches for seven complex diseases provided by the Wellcome Trust Case Control Consortium (WTCCC) under a within-study validation approach. Risk models were inferred using a variety of learning machines and assumptions about the underlying genetic model, including a haplotype-based approach with different haplotype lengths and different thresholds in association levels to choose loci as part of the predictive model. In accordance with previous work, our results generally showed low accuracy considering disease heritability and population prevalence. However, the boosting algorithm returned a predictive area under the ROC curve (AUC) of 0.8805 for Type 1 diabetes (T1D) and 0.8087 for rheumatoid arthritis, both clearly over the AUC obtained by other approaches and over 0.75, which is the minimum required for a disease to be successfully tested on a sample at risk, which means that boosting is a promising approach. Its good performance seems to be related to its robustness to redundant data, as in the case of genome-wide data sets due to linkage disequilibrium. Conclusions: In view of our results, the boosting approach may be suitable for modeling individual predisposition to Type 1 diabetes and rheumatoid arthritis based on genome-wide data and should be considered for more in-depth research.This work was supported by the Spanish Secretary of Research, Development and Innovation [TIN2010-20900-C04-1]; the Spanish Health Institute Carlos III [PI13/02714]and [PI13/01527] and the Andalusian Research Program under project P08-TIC-03717 with the help of the European Regional Development Fund (ERDF). The authors are very grateful to the reviewers, as they believe that their comments have helped to substantially improve the quality of the paper

The multiple sclerosis-associated regulatory variant rs10877013 affects expression of CYP27B1 and VDR under inflammatory or vitamin D stimuli

BACKGROUND: Vitamin D deficit is considered an important risk factor for many inflammatory and autoimmune diseases. OBJECTIVE: To investigate the influence of the multiple sclerosis (MS)-associated regulatory variant rs10877013 on the expression of genes involved in vitamin D activation (CYP27B1), vitamin D receptor (VDR), and vitamin D degradation (CYP24A1) under inflammatory environment or vitamin D. METHODS: We used lipopolysaccharide and interferon-gamma (LPS+IFNγ) activated monocytes from 119 individuals and vitamin D-stimulated lymphoblastoid cell lines (LCLs, n = 109) of 1000 genomes to quantify the mRNA expression of vitamin D genes by quantitative reverse transcription polymerase chain reaction (RT-qPCR). RESULTS: We found that CYP27B1 mRNA expression level was associated with the rs10877013 genotypes (p = 5.0E-6) in LPS+IFNγ treated monocytes, but not in vitamin D-stimulated LCLs. Inversely, rs10877013 genotypes were associated with VDR expression in LCLs (p = 6.0E-4) but not in monocytes. Finally, CYP24A1 was highly induced by the active form of vitamin D and its expression correlated with the expression of VDR in LCLs but neither the MS-associated variant in the region (rs2248359) nor any other variant located in 1 Mb around CYP24A1 was associated with its expression. CONCLUSIONS: The MS-associated variant rs10877013 is a genetic determinant that affects the functioning of the vitamin D system linking environmental and genetic factors.This work was supported by Fondo de Investigacion Sanitaria (FIS)-Instituto de Salud Carlos III-(ISCIII)-Fondos Europeos de Desarrollo Regional (FEDER), Union Europea (grant numbers P12/00555, PI13/01527, PI13/01466), and Junta de Andalucia (JA)- Fondos Europeos de Desarrollo Regional (FEDER) (grant number CTS2704).Peer reviewe

SP140 regulates the expression of immune-related genes associated with multiple sclerosis and other autoimmune diseases by NF-kappa B inhibition

SP140 locus has been associated with multiple sclerosis (MS) as well as other autoimmune diseases by genome-wide association studies (GWAS). The causal variant of these associations (rs28445040-T) alters the splicing of the SP140 gene transcripts reducing the protein expression. We aimed to understand why the reduction of SP140 expression produced by the risk variant can increase the susceptibility to MS. To this end, we determined by RNA sequencing (RNA-seq) analysis the differentially expressed genes after SP140 silencing in lymphoblastoid cell lines (LCLs). We analyzed these genes by gene ontology (GO), comparative transcriptome profiles, enrichment of transcription factors (TFs) in the promoters of these genes and colocalization with GWAS risk variants. We also monitored the activity of the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kappa B) in SP140-silenced cells by luciferase reporter system. We identified 100 genes that were up-regulated and 22 genes down-regulated in SP140-silenced LCLs. GO analysis revealed that genes affected by SP140 were involved in regulation of cytokine production, inflammatory response and cell-cell adhesion. We observed enrichment of NF-kappa B TF in the promoter of up-regulated genes and NF-kappa B-increased activity in SP140-silenced cell lines. We showed enrichment of genes regulated by SP140 in GWAS-detected risk loci for MS (14.63 folds), Crohn's disease (4.82 folds) and inflammatory bowel disease (4.47 folds), not observed in other unrelated immune diseases. Our findings showed that SP140 is an important repressor of genes implicated in inflammation, suggesting that decreased expression of SP140, promoted by the rs28445040-T risk variant, may lead to up-regulation of these genes by means of NF-kappa B inhibition in B cells.Agencia Estatal de Investigación del Ministerio de Ciencia, Innovación y Universidades of Spain (SAF2016-80595 to A.A. and F.M.); Junta de Andalucía-Fondo Europeo de Desarrollo Regional (FEDER) (CTS2704 to F.M.)Peer reviewe