BackgroundGenome-wide association studies (GWAS) are an important method for mapping genetic variation underlying complex traits and diseases. Tools to visualize, annotate and analyse results from these studies can be used to generate hypotheses about the molecular mechanisms underlying the associations.FindingsThe Complex-Traits Genetics Virtual Lab (CTG-VL) integrates over a thousand publicly-available GWAS summary statistics, a suite of analysis tools, visualization functions and diverse data sets for genomic annotations. CTG-VL also makes available results from gene, pathway and tissue-based analyses from over 1,500 complex-traits allowing to assess pleiotropy not only at the genetic variant level but also at the gene, pathway and tissue levels. In this manuscript, we showcase the platform by analysing GWAS summary statistics of mood swings derived from UK Biobank. Using analysis tools in CTG-VL we highlight hippocampus as a potential tissue involved in mood swings, and that pathways including neuron apoptotic process may underlie the genetic associations. Further, we report a negative genetic correlation with educational attainment rG = −0.41 ± 0.018 and a potential causal effect of BMI on mood swings OR = 1.01 (95% CI = 1.00–1.02). Using CTG-VL’s database, we show that pathways and tissues associated with mood swings are also associated with neurological traits including reaction time and neuroticism, as well as traits such age at menopause and age at first live birth.ConclusionsCTG-VL is a platform with the most complete set of tools to carry out post-GWAS analyses. The CTG-VL is freely available at https://genoma.io as an online web application.

Assessment and visualization of phenome-wide causal relationships using genetic data: an application to dental caries and periodontitis.

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.

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two

Endometrial cancer, the most commonly diagnosed cancer of the female reproductive tract in developed countries, has a heritable component. To date, 16 genetic risk regions have been robustly discovered by genome-wide association studies (GWAS) of endometrial cancer. Post-GWAS analyses including expression quantitative trait loci analysis and laboratorybased functional studies have been successful in identifying genes and pathways involved in endometrial carcinogenesis. Mendelian randomization analysis studies have confirmed factors causal for endometrial cancer risk, including increased body mass index and early onset of menarche. In this review, we summarize findings from GWAS and post-GWAS analyses of endometrial cancer. We discuss clinical implications of these findings, current knowledge gaps, and future directions for the study of endometrial cancer genetics.

doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

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Genome-wide association studies (GWAS) have revealed sixteen risk loci for endoemtrial cancer but the identification of candidate susceptibility genes remains challenging. Here, we perform transcriptome-wide association study (TWAS) analyses using the largest endometrial cancer GWAS and gene expression from six relevant tissues, prioritizing eight candidate endometrial cancer susceptibility genes, one of which (EEFSEC) is located at a potentially novel endometrial cancer risk locus. We also show evidence of biologically relevant tissue-specific expression associations for CYP19A1 (adipose), HEY2 (ovary) and SKAP1 (whole blood). A phenome-wide association study demonstrates associations of candidate susceptibility genes with anthropometric, cardiovascular, diabetes, bone health and sex hormone traits that are related to endometrial cancer risk factors. Lastly, analysis of TWAS data highlights candidate compounds for endometrial cancer repurposing. In summary, this study reveals endometrial cancer susceptibility genes, including those with evidence of tissue specificity, providing insights into endometrial cancer aetiology and avenues for therapeutic development.