Predictive modelling using pathway scores: robustness and significance of pathway collections

Background Transcriptomic data is often used to build statistical models which are predictive of a given phenotype, such as disease status. Genes work together in pathways and it is widely thought that pathway representations will be more robust to noise in the gene expression levels. We aimed to test this hypothesis by constructing models based on either genes alone, or based on sample specific scores for each pathway, thus transforming the data to a ‘pathway space’. We progressively degraded the raw data by addition of noise and examined the ability of the models to maintain predictivity. Results Models in the pathway space indeed had higher predictive robustness than models in the gene space. This result was independent of the workflow, parameters, classifier and data set used. Surprisingly, randomised pathway mappings produced models of similar accuracy and robustness to true mappings, suggesting that the success of pathway space models is not conferred by the specific definitions of the pathway. Instead, predictive models built on the true pathway mappings led to prediction rules with fewer influential pathways than those built on randomised pathways. The extent of this effect was used to differentiate pathway collections coming from a variety of widely used pathway databases. Conclusions Prediction models based on pathway scores are more robust to degradation of gene expression information than the equivalent models based on ungrouped genes. While models based on true pathway scores are not more robust or accurate than those based on randomised pathways, true pathways produced simpler prediction rules, emphasizing a smaller number of pathways

diXa: a data infrastructure for chemical safety assessment

Motivation: The field of toxicogenomics (the application of ‘-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available. Results: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal. Availability and implementation: http://www.dixa-fp7.eu Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genomewide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ~60 000 individuals in the discovery stage and ~90 000 samples in the replication stage. Results Our study resu

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from similar to 60 000 individuals in the discovery stage and similar to 90 000 samples in the replication stage. Results Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene. Conclusions This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.Peer reviewe

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels.Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from similar to 60 000 individuals in the discovery stage and similar to 90 000 samples in the replication stage.Results Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene.Conclusions This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels

KLB is associated with alcohol drinking, and its gene product β-Klotho is necessary for FGF21 regulation of alcohol preference.

Excessive alcohol consumption is a major public health problem worldwide. Although drinking habits are known to be inherited, few genes have been identified that are robustly linked to alcohol drinking. We conducted a genome-wide association metaanalysis and replication study among >105,000 individuals of European ancestry and identified β-Klotho (KLB) as a locus associated with alcohol consumption (rs11940694; P = 9.2 × 10(-12)). β-Klotho is an obligate coreceptor for the hormone FGF21, which is secreted from the liver and implicated in macronutrient preference in humans. We show that brain-specific β-Klotho KO mice have an increased alcohol preference and that FGF21 inhibits alcohol drinking by acting on the brain. These data suggest that a liver-brain endocrine axis may play an important role in the regulation of alcohol drinking behavior and provide a unique pharmacologic target for reducing alcohol consumption