Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk.

Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls.

BACKGROUND: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. CONCLUSIONS: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer.

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1ß pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

Genome-wide association study of INDELs identified four novel susceptibility loci associated with lung cancer risk.

Genome-wide association studies (GWAS) have identified 45 susceptibility loci associated with lung cancer. Only less than SNPs, small insertions and deletions (INDELs) are the second most abundant genetic polymorphisms in the human genome. INDELs are highly associated with multiple human diseases, including lung cancer. However, limited studies with large-scale samples have been available to systematically evaluate the effects of INDELs on lung cancer risk. Here, we performed a large-scale meta-analysis to evaluate INDELs and their risk for lung cancer in 23,202 cases and 19,048 controls. Functional annotations were performed to further explore the potential function of lung cancer risk INDELs. Conditional analysis was used to clarify the relationship between INDELs and SNPs. Four new risk loci were identified in genome-wide INDEL analysis (1p13.2: rs5777156, Insertion, OR = 0.92, p = 9.10 × 10-8 ; 4q28.2: rs58404727, Deletion, OR = 1.19, p = 5.25 × 10-7 ; 12p13.31: rs71450133, Deletion, OR = 1.09, p = 8.83 × 10-7 ; and 14q22.3: rs34057993, Deletion, OR = 0.90, p = 7.64 × 10-8 ). The eQTL analysis and functional annotation suggested that INDELs might affect lung cancer susceptibility by regulating the expression of target genes. After conducting conditional analysis on potential causal SNPs, the INDELs in the new loci were still nominally significant. Our findings indicate that INDELs could be potentially functional genetic variants for lung cancer risk. Further functional experiments are needed to better understand INDEL mechanisms in carcinogenesis.

Transcriptome-wide association study reveals candidate causal genes for lung cancer.

We have recently completed the largest GWAS on lung cancer including 29,266 cases and 56,450 controls of European descent. The goal of our study has been to integrate the complete GWAS results with a large-scale expression quantitative trait loci (eQTL) mapping study in human lung tissues (n = 1,038) to identify candidate causal genes for lung cancer. We performed transcriptome-wide association study (TWAS) for lung cancer overall, by histology (adenocarcinoma, squamous cell carcinoma and small cell lung cancer) and smoking subgroups (never- and ever-smokers). We performed replication analysis using lung data from the Genotype-Tissue Expression (GTEx) project. DNA damage assays were performed in human lung fibroblasts for selected TWAS genes. As expected, the main TWAS signal for all histological subtypes and ever-smokers was on chromosome 15q25. The gene most strongly associated with lung cancer at this locus using the TWAS approach was IREB2 (pTWAS = 1.09E-99), where lower predicted expression increased lung cancer risk. A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (pTWAS = 3.72E-6). Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3-adenocarcinoma on 9p13.3 was replicated using GTEx (pTWAS = 6.55E-5). Consistent with the effect of risk alleles on gene expression levels, IREB2 knockdown and AQP3 overproduction promote endogenous DNA damage. These findings indicate genes whose expression in lung tissue directly influences lung cancer risk.

Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population.

Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never- versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13336 non-small cell lung cancer cases. Candidate SNPs with P-value <0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with P-value <3.5 × 10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 non-small cell lung cancer cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis P-value for these two SNPs were 1.24 with 6.96 × 10-7 and 1.37 with 3.49 × 10-7, respectively. In addition, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and P-value of 8.12 × 10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease.

Genome-wide Association Analysis of Psoriatic Arthritis and Cutaneous Psoriasis Reveals Differences in Their Genetic Architecture.

Psoriasis vulgaris (PsV) is a common inflammatory and hyperproliferative skin disease. Up to 30% of people with PsV eventually develop psoriatic arthritis (PsA), an inflammatory musculoskeletal condition. To discern differences in genetic risk factors for PsA and cutaneous-only psoriasis (PsC), we carried out a genome-wide association study (GWAS) of 1,430 PsA case subjects and 1,417 unaffected control subjects. Meta-analysis of this study with three other GWASs and two targeted genotyping studies, encompassing a total of 9,293 PsV case subjects, 3,061 PsA case subjects, 3,110 PsC case subjects, and 13,670 unaffected control subjects of European descent, detected 10 regions associated with PsA and 11 with PsC at genome-wide (GW) significance. Several of these association signals (IFNLR1, IFIH1, NFKBIA for PsA; TNFRSF9, LCE3C/B, TRAF3IP2, IL23A, NFKBIA for PsC) have not previously achieved GW significance. After replication, we also identified a PsV-associated SNP near CDKAL1 (rs4712528, odds ratio [OR] = 1.16, p = 8.4 × 10(-11)). Among identified psoriasis risk variants, three were more strongly associated with PsC than PsA (rs12189871 near HLA-C, p = 5.0 × 10(-19); rs4908742 near TNFRSF9, p = 0.00020; rs10888503 near LCE3A, p = 0.0014), and two were more strongly associated with PsA than PsC (rs12044149 near IL23R, p = 0.00018; rs9321623 near TNFAIP3, p = 0.00022). The PsA-specific variants were independent of previously identified psoriasis variants near IL23R and TNFAIP3. We also found multiple independent susceptibility variants in the IL12B, NOS2, and IFIH1 regions. These results provide insights into the pathogenetic similarities and differences between PsC and PsA.

Genetic modifiers of radon-induced lung cancer risk: a genome-wide interaction study in former uranium miners.

PURPOSE: Radon is a risk factor for lung cancer and uranium miners are more exposed than the general population. A genome-wide interaction analysis was carried out to identify genomic loci, genes or gene sets that modify the susceptibility to lung cancer given occupational exposure to the radioactive gas radon. METHODS: Samples from 28 studies provided by the International Lung Cancer Consortium were pooled with samples of former uranium miners collected by the German Federal Office of Radiation Protection. In total, 15,077 cases and 13,522 controls, all of European ancestries, comprising 463 uranium miners were compared. The DNA of all participants was genotyped with the OncoArray. We fitted single-marker and in multi-marker models and performed an exploratory gene-set analysis to detect cumulative enrichment of significance in sets of genes. RESULTS: We discovered a genome-wide significant interaction of the marker rs12440014 within the gene CHRNB4 (OR = 0.26, 95% CI 0.11-0.60, p = 0.0386 corrected for multiple testing). At least suggestive significant interaction of linkage disequilibrium blocks was observed at the chromosomal regions 18q21.23 (p = 1.2 × 10-6), 5q23.2 (p = 2.5 × 10-6), 1q21.3 (p = 3.2 × 10-6), 10p13 (p = 1.3 × 10-5) and 12p12.1 (p = 7.1 × 10-5). Genes belonging to the Gene Ontology term "DNA dealkylation involved in DNA repair" (GO:0006307; p = 0.0139) or the gene family HGNC:476 "microRNAs" (p = 0.0159) were enriched with LD-blockwise significance. CONCLUSION: The well-established association of the genomic region 15q25 to lung cancer might be influenced by exposure to radon among uranium miners. Furthermore, lung cancer susceptibility is related to the functional capability of DNA damage signaling via ubiquitination processes and repair of radiation-induced double-strand breaks by the single-strand annealing mechanism.

[Low emission zones in Germany : A reliable measure for keeping current air quality standards?] / Umweltzonen in Deutschland : Probates Mittel zur Einhaltung geltender Luftqualitätsstandards?

Low Emission Zones (LEZs) were implemented as a measure for improving the quality of ambient air. As of February 2018, 58 LEZs were in operation in Germany; however they differ significantly, especially regarding their size.The effectiveness of LEZs has been investigated by dispersion modelling as well as by analysis of PM10 (particles which pass through a size-selective inlet with a 50 % efficiency cut-off at 10 µm aerodynamic diameter) and nitrogen dioxide (NO2) measurement values. Recent studies show a clear trend. In sufficiently large and strictly regulated LEZs, a reduction of PM10 concentration between 5 and 10% can be shown, and at some traffic sites above 10%. The current (currently valid) limit values for PM10 were introduced in 2005, mainly due to the adverse health effects of fine particles on respiratory and cardiovascular morbidity and mortality. The most health-relevant PM10 particle fraction consists mainly of traffic-related particles and here especially of diesel soot particles. Therefore, the German regulations for LEZs promote using diesel particulate filters in diesel cars.Unfortunately, the evaluation of the LEZ effects is mostly restricted to PM10, a particle fraction containing only a comparatively small portion of highly toxic exhaust-related particles. The analysis of air pollutants that are more traffic specific (such as elemental carbon, ultrafine particles, PM2.5 [particles which pass through a size-selective inlet with a 50 % efficiency cut-off at 10 µm aerodynamic diameter]) would be more adequate. For "powerful" LEZs, more pronounced reductions of such pollutants have clearly been shown. This also means that the benefit of LEZs on human health is by far greater than is presently visible from routine measurements of PM10.Since the stickers for LEZs are in fact meant to reduce particulate matter, it is not surprising that the introduction of LEZs has not resulted in a demonstrable reduction in NO2 concentrations.

Assessing the Genetic Predisposition of Education on Myopia: A Mendelian Randomization Study.

Myopia is the largest cause of uncorrected visual impairments globally and its recent dramatic increase in the population has made it a major public health problem. In observational studies, educational attainment has been consistently reported to be correlated to myopia. Nonetheless, correlation does not imply causation. Observational studies do not tell us if education causes myopia or if instead there are confounding factors underlying the association. In this work, we use a two-step least squares instrumental-variable (IV) approach to estimate the causal effect of education on refractive error, specifically myopia. We used the results from the educational attainment GWAS from the Social Science Genetic Association Consortium to define a polygenic risk score (PGRS) in three cohorts of late middle age and elderly Caucasian individuals (N = 5,649). In a meta-analysis of the three cohorts, using the PGRS as an IV, we estimated that each z-score increase in education (approximately 2 years of education) results in a reduction of 0.92 ± 0.29 diopters (P = 1.04 × 10(-3) ). Our estimate of the effect of education on myopia was higher (P = 0.01) than the observed estimate (0.25 ± 0.03 diopters reduction per education z-score [∼2 years] increase). This suggests that observational studies may actually underestimate the true effect. Our Mendelian Randomization (MR) analysis provides new evidence for a causal role of educational attainment on refractive error.

Inherited variation in circadian rhythm genes and risks of prostate cancer and three other cancer sites in combined cancer consortia.

Circadian disruption has been linked to carcinogenesis in animal models, but the evidence in humans is inconclusive. Genetic variation in circadian rhythm genes provides a tool to investigate such associations. We examined associations of genetic variation in nine core circadian rhythm genes and six melatonin pathway genes with risk of colorectal, lung, ovarian and prostate cancers using data from the Genetic Associations and Mechanisms in Oncology (GAME-ON) network. The major results for prostate cancer were replicated in the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial, and for colorectal cancer in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). The total number of cancer cases and controls was 15,838/18,159 for colorectal, 14,818/14,227 for prostate, 12,537/17,285 for lung and 4,369/9,123 for ovary. For each cancer site, we conducted gene-based and pathway-based analyses by applying the summary-based Adaptive Rank Truncated Product method (sARTP) on the summary association statistics for each SNP within the candidate gene regions. Aggregate genetic variation in circadian rhythm and melatonin pathways were significantly associated with the risk of prostate cancer in data combining GAME-ON and PLCO, after Bonferroni correction (ppathway < 0.00625). The two most significant genes were NPAS2 (pgene = 0.0062) and AANAT (pgene = 0.00078); the latter being significant after Bonferroni correction. For colorectal cancer, we observed a suggestive association with the circadian rhythm pathway in GAME-ON (ppathway = 0.021); this association was not confirmed in GECCO (ppathway = 0.76) or the combined data (ppathway = 0.17). No significant association was observed for ovarian and lung cancer. These findings support a potential role for circadian rhythm and melatonin pathways in prostate carcinogenesis. Further functional studies are needed to better understand the underlying biologic mechanisms.

Human metabolic individuality in biomedical and pharmaceutical research.

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses.

Availability of standardized metabolite panels and genome-wide single-nucleotide polymorphism data endorse the comprehensive analysis of gene-metabolite association. Currently, many studies use genome-wide association analysis to investigate the genetic effects on single metabolites (mGWAS) separately. Such studies have identified several loci that are associated not only with one but with multiple metabolites, facilitated by the fact that metabolite panels often include metabolites of the same or related pathways. Strategies that analyse several phenotypes in a combined way were shown to be able to detect additional genetic loci. One of those methods is the phenotype set enrichment analysis (PSEA) that tests sets of metabolites for enrichment at genes. Here we applied PSEA on two different panels of serum metabolites together with genome-wide data. All analyses were performed as a two-step identification-validation approach, using data from the population-based KORA cohort and the TwinsUK study. In addition to confirming genes that were already known from mGWAS, we were able to identify and validate 12 new genes. Knowledge about gene function was supported by the enriched metabolite sets. For loci with unknown gene functions, the results suggest a function that is interrelated with the metabolites, and hint at the underlying pathways.

Modeling Lung Carcinogenesis in Radon-Exposed Miner Cohorts: Accounting for Missing Information on Smoking.

Epidemiological miner cohort data used to estimate lung cancer risks related to occupational radon exposure often lack cohort-wide information on exposure to tobacco smoke, a potential confounder and important effect modifier. We have developed a method to project data on smoking habits from a case-control study onto an entire cohort by means of a Monte Carlo resampling technique. As a proof of principle, this method is tested on a subcohort of 35,084 former uranium miners employed at the WISMUT company (Germany), with 461 lung cancer deaths in the follow-up period 1955-1998. After applying the proposed imputation technique, a biologically-based carcinogenesis model is employed to analyze the cohort's lung cancer mortality data. A sensitivity analysis based on a set of 200 independent projections with subsequent model analyses yields narrow distributions of the free model parameters, indicating that parameter values are relatively stable and independent of individual projections. This technique thus offers a possibility to account for unknown smoking habits, enabling us to unravel risks related to radon, to smoking, and to the combination of both.

Genome-wide association study of restless legs syndrome identifies common variants in three genomic regions.

Restless legs syndrome (RLS) is a frequent neurological disorder characterized by an imperative urge to move the legs during night, unpleasant sensation in the lower limbs, disturbed sleep and increased cardiovascular morbidity. In a genome-wide association study we found highly significant associations between RLS and intronic variants in the homeobox gene MEIS1, the BTBD9 gene encoding a BTB(POZ) domain as well as variants in a third locus containing the genes encoding mitogen-activated protein kinase MAP2K5 and the transcription factor LBXCOR1 on chromosomes 2p, 6p and 15q, respectively. Two independent replications confirmed these association signals. Each genetic variant was associated with a more than 50% increase in risk for RLS, with the combined allelic variants conferring more than half of the risk. MEIS1 has been implicated in limb development, raising the possibility that RLS has components of a developmental disorder.

[The biobank of the German National Cohort as a resource for epidemiologic research]. / Die Biobank der Nationalen Kohorte als Ressource der epidemiologischen Forschung.

BACKGROUND: The linkage of high-quality biosamples with detailed data from medical examinations, questionnaires and interviews offers great opportunities for research. This is particularly true for large-scale prospective epidemiological studies with long observation periods, like the German National Cohort (GNC). AIM: The modalities of collecting, processing and storing biosamples of high quality and with a high throughput, as well as ethical aspects are described using the GNC as an example. MATERIAL AND METHODS: For the GNC, 200,000 randomly selected adults will be recruited by 18 study centres and will be followed up for 20-30 years. In addition to the extensive basic examination protocol, followed by reassessment examinations and follow-up questionnaires, the biorepository is a cornerstone of the GNC. RESULTS: The GNC biorepository will comprise more than 20 million aliquots of plasma, serum, erythrocytes, lymphocytes, urine, saliva, nasal swabs and stool. Preanalytics and aliquoting are performed locally in the study centres and are highly standardised and extensively automated. All samples are stored at - 80 and - 180 °C, respectively. A laboratory information system documents all processing steps and storage locations. Access to data and biosamples will be granted to researchers within and outside Germany after completion of the baseline recruitment (i.e. from 2018 onwards). DISCUSSION: Experience with already existing epidemiological biobanks shows impressive results, especially with regard to genetic research, as well as post-genomics (e.g. transcriptomics, metabolomics, epigenomics). Previous success stories explain the strongly increased demand for data and biosamples from the population. Thus the GNC will provide an important resource for biomedical research in the future.

[Connecting biobanks of large European cohorts (EU Project BBMRI-LPC)]. / Vernetzung von Biobanken großer europäischer Kohorten (EU-Projekt BBMRI-LPC).

BACKGROUND: In addition to the Biobanking and BioMolecular resources Research Initiative (BBMRI), which is establishing a European research infrastructure for biobanks, a network for large European prospective cohorts (LPC) is being built to facilitate transnational research into important groups of diseases and health care. One instrument for this is the database "LPC Catalogue," which supports access to the biomaterials of the participating cohorts. OBJECTIVES: To present the LPC Catalogue as a relevant tool for connecting European biobanks. In addition, the LPC Catalogue has been extended to establish compatibility with existing Minimum Information About Biobank data Sharing (MIABIS) and to allow for more detailed search requests. This article describes the LPC Catalogue, its organizational and technical structure, and the aforementioned extensions. MATERIALS AND METHODS: The LPC Catalogue provides a structured overview of the participating LPCs. It offers various retrieval possibilities and a search function. To support more detailed search requests, a new module has been developed, called a "data cube". The provision of data by the cohorts is being supported by a "connector" component. RESULTS: The LPC Catalogue contains data on 22 cohorts and more than 3.8 million biosamples. At present, data on the biosamples of three cohorts have been acquired for the "cube," which is continuously being expanded. In the BBMRI-LPC, tendering for scientific projects using the data and samples of the participating cohorts is currently being carried out. In this context, several proposals have already been approved. CONCLUSIONS: The LPC Catalogue is supporting transnational access to biosamples. A comparison with existing solutions illustrates the relevance of its functionality.

Meta-analysis of genome-wide association studies in five cohorts reveals common variants in RBFOX1, a regulator of tissue-specific splicing, associated with refractive error.

Visual refractive errors (REs) are complex genetic traits with a largely unknown etiology. To date, genome-wide association studies (GWASs) of moderate size have identified several novel risk markers for RE, measured here as mean spherical equivalent (MSE). We performed a GWAS using a total of 7280 samples from five cohorts: the Age-Related Eye Disease Study (AREDS); the KORA study ('Cooperative Health Research in the Region of Augsburg'); the Framingham Eye Study (FES); the Ogliastra Genetic Park-Talana (OGP-Talana) Study and the Multiethnic Study of Atherosclerosis (MESA). Genotyping was performed on Illumina and Affymetrix platforms with additional markers imputed to the HapMap II reference panel. We identified a new genome-wide significant locus on chromosome 16 (rs10500355, P = 3.9 × 10(-9)) in a combined discovery and replication set (26 953 samples). This single nucleotide polymorphism (SNP) is located within the RBFOX1 gene which is a neuron-specific splicing factor regulating a wide range of alternative splicing events implicated in neuronal development and maturation, including transcription factors, other splicing factors and synaptic proteins.

Combined analysis of genome-wide association studies for Crohn disease and psoriasis identifies seven shared susceptibility loci.

Psoriasis (PS) and Crohn disease (CD) have been shown to be epidemiologically, pathologically, and therapeutically connected, but little is known about their shared genetic causes. We performed meta-analyses of five published genome-wide association studies on PS (2,529 cases and 4,955 controls) and CD (2,142 cases and 5,505 controls), followed up 20 loci that showed strongest evidence for shared disease association and, furthermore, tested cross-disease associations for previously reported PS and CD risk alleles in additional 6,115 PS cases, 4,073 CD cases, and 10,100 controls. We identified seven susceptibility loci outside the human leukocyte antigen region (9p24 near JAK2, 10q22 at ZMIZ1, 11q13 near PRDX5, 16p13 near SOCS1, 17q21 at STAT3, 19p13 near FUT2, and 22q11 at YDJC) shared between PS and CD with genome-wide significance (p < 5 × 10(-8)) and confirmed four already established PS and CD risk loci (IL23R, IL12B, REL, and TYK2). Three of the shared loci are also genome-wide significantly associated with PS alone (10q22 at ZMIZ1, p(rs1250544) = 3.53 × 10(-8), 11q13 near PRDX5, p(rs694739) = 3.71 × 10(-09), 22q11 at YDJC, p(rs181359) = 8.02 × 10(-10)). In addition, we identified one susceptibility locus for CD (16p13 near SOCS1, p(rs4780355) = 4.99 × 10(-8)). Refinement of association signals identified shared genome-wide significant associations for exonic SNPs at 10q22 (ZMIZ1) and in silico expression quantitative trait locus analyses revealed that the associations at ZMIZ1 and near SOCS1 have a potential functional effect on gene expression. Our results show the usefulness of joint analyses of clinically distinct immune-mediated diseases and enlarge the map of shared genetic risk loci.