Wood, A. R. et al. Additionally, a separate study performed SNP enrichment analysis for nine immune diseases using gene expression and chromatin accessibility profiles of 25 immune cell types in resting and activated states (Calderon et al., 2019). As aptly described by Hyppönen and colleagues, specific assumptions about causal mechanisms are needed to estimate effects with mendelian randomisation (no horizontal pleiotropy, independence of pleiotropic effect sizes, and so on). A., and Clayton, D. G. (2009). The significant effects after correcting for multiple testing (PGSMR < 7.6×10−4) are labeled with ORs (P-values). GSMR accounts for LD if the SNP instruments are not fully independent. Genet. Psychiatric traits, which involve dysregulation of the central nervous system, pose a similar challenge due to the complex histological structure of the brain. It requires relatively simple annotations from GWAS summary statistics, genomic positions and DNaseI hypersensitive sites (DHS). However, single-cell genomic approaches introduce new challenges to the current statistical methods, such as data size, sparsity, and high dropout rates (Lähnemann et al., 2020).
(2019). and y and \(r_{p(x_i,y)}\) is the phenotypic correlation between x Gosselin, D., Skola, D., Coufal, N. G., Holtman, I. R., Schlachetzki, J. C. M., Sajti, E., et al. 2019 Nov;27(11):1745-1756. doi: 10.1038/s41431-019-0468-4. Garland, D. E., Adkins, R. H., Kushwaha, V. & Stewart, C. Risk factors for osteoporosis at the knee in the spinal cord injury population. doi: 10.1038/s41586-018-0579-z, Calderon, D., Bhaskar, A., Knowles, D. A., Golan, D., Raj, T., Fu, A. Q., et al. The Lancet Regional Health – Western Pacific, Walking the tightrope of artificial intelligence guidelines in clinical practice, Using patient safety-event report data to assess health-IT safety: benefits and challenges, Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0), https://doi.org/10.1016/S2589-7500(19)30059-7, From GWAS to PheWAS: the search for causality in big data, A data-driven approach for studying the role of body mass in multiple diseases: a phenome-wide registry-based case-control study in the UK Biobank, Recommend Lancet journals to your librarian, Redistribute or republish the final article, Translate the article (private use only, not for distribution), Reuse portions or extracts from the article in other works, Distribute translations or adaptations of the article. Biobanks can also help in functionally interpreting PRSs. 17, 392–406. Nat Commun 9, 224 (2018).
We therefore can estimate the effect size of x0 on y accounting for x by a GSMR analysis using SNP effects on x0 and y conditioning on x.
Võsa et al. Importantly, three of these four genes (TSPAN8, GNB5, and JAZF1) were supported by previous functional studies. Gusev et al. The statistical significance of \(\hat b_{xy}\) can be tested by \(T_{GSMR} = \hat b_{xy}^2/{\mathrm{var}}(\hat b_{xy})\) which follows a χ2 distribution with 1 degree of freedom. CRISPR-editing is further limited by the p53-dependent cellular toxicity which accompanies Cas9-induced double-strand breaks (Ihry et al., 2018). & Thompson, S. G. Mendelian randomization analysis with multiple genetic variants using summarized data. converted Not only do we expect these findings to accelerate drug development, by providing guidance on which Genet. Global Lipids Genetics Consortium et al. Article The effects of TG on diseases were largely consistent with those for LDL-c (Supplementary Fig.
We applied the HEIDI-outlier approach to remove SNPs that showed pleiotropic effects on both risk factor and disease, significantly deviated from a causal model (Methods). (2016). doi: 10.1038/ng.2870. http://prismstandard.org/namespaces/basic/2.0/ & Hinds, D. A. In summary, colocalization and TWAS prioritize the genes causally involved in complex diseases. using the estimates of b pdfToolbox (2015). Int. To address this issue, enrichment of disease variants in DHS regions can compare GWAS SNPs to random sets of SNPs with similar properties (i.e., LD, gene density and distance to TSS) in a permutation-based approach (GREGOR) (Schmidt et al., 2015). Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Lancet 362, 782–788 (2003). (2020).
Although disease status and disease count are two distinct phenotypes and the analysis of disease count is more powerful, for the ease of interpretation, b The first objective of my thesis was to study the expression of type 2 diabetes susceptibility genes in a panel of human tissues comprising pancreatic and insulin-sensitive tissues using an unbiased technique of quantification of genes expression in order to show that these genes associated with type 2 diabetes were enriched in pancreatic β-cells. From R.A. fisher’s 1918 Paper to GWAS a century later. 47, 1091–1098. xy Khera, A. V., Chaffin, M., Aragam, K. G., Haas, M. E., Roselli, C., Choi, S. H., et al. J. Hum. Reduction in incidence of coronary heart disease.
6:e107. Jonathan Y Huang. Article Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested. HHS
(2010). Eye Vis. Biotechnol. (2013). j 42, 1118–1125. This analysis requires individual-level data so that the statistical power could be limited if b However, a limitation is that it only tests for two traits at a time.
Sci. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Pennington, K. L. & DeAngelis, M. M. Epidemiology of age-related macular degeneration (AMD): associations with cardiovascular disease phenotypes and lipid factors. We call this approach mtCOJO (multi-trait-based conditional and joint analysis), and have demonstrated the accuracy of the approximation by simulation (Supplementary Fig. Despite the LD difference between populations, most causal variants are thought to be shared (Marigorta and Navarro, 2013). (2018) integrated GWAS loci for coronary artery disease (CAD) with expression and splicing QTLs mapped in smooth muscle cells from 52 individuals. Text doi: 10.7554/eLife.57492. Author information: contains the name of each author and his/her ORCID (ORCiD: Open Researcher and Contributor ID). We found that HDL-c had protective effects against T2D (OR = 0.83), hypertensive disease (OR = 0.88), CVD (OR = 0.88) and disease count (OR = 0.94) in the community data, and T2D (OR = 0.81) and CAD (OR = 0.84) in the case–control data. A. R., Zhang, J., and Chaput, J. C. (2010). Overview of transcriptome-wide association studies TWAS leverage information from eQTL catalogs and GWAS studies to directly associate traits to genes. apoptosis of pancreatic cells, insulinemia, glycolysis, endoplasmic reticulum stress response...).
(2019).
These methods are called colocalization tests. The aggregation type specifies the unit of aggregation for a content collection. Let y i indicate the phenotypic value of the ith individual and g i k ∈ {0, 1, 2} indicate the minor allele count of the ith individual for the kth variant. The estimated SNP effects and standard errors (SE) for age-related macular degeneration (AMD) were not available in the summary data32, which were estimated from z-statistics using an approximate approach (Supplementary Note 3). Genome-wide association studies variants can be used to identify individuals at high risk of disease. In this context, we conducted a “fishing” study to decipher this large amount of data generated by GWAS and to pinpoint potentially important genes that may be new therapeutic targets.
These cells are able to secrete insulin in response to glucose and other secretagogues. A study by Huang et al. For instance, we have identified from the GSMR analysis that EduYears had effects on many diseases (Fig. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. (2018) demonstrated that individuals at the highest PRS percentiles were at a risk equivalent to that of carrying a monogenic mutation for familial hypercholesterolemia. by GSMR is unbiased under the alternative hypothesis that b Secondly, PRSs are based on European GWASs and their transferability between populations is low (Martin et al., 2017, 2019). doi: 10.2337/db07-1305, Hannon, E., Spiers, H., Viana, J., Pidsley, R., Burrage, J., Murphy, T. M., et al. Li, Y., Oosting, M., Smeekens, S. P., Jaeger, M., Aguirre-Gamboa, R., Le, K. T. T., et al. Pleiotropy is an important potential confounding factor that could bias the estimate and often results in an inflated test-statistic in a MR analysis9,10,13,19. (2019).
Robert Maier Moreover, TWAS allows the direct association of genes with phenotypes via transcriptome imputation. Maciej Trzaskowski 2020 Sep 11;21(1):235. doi: 10.1186/s13059-020-02129-6. The second study focused on cardiomyocyte differentiation and mapped eQTLs at 16 time points across 19 iPS cell lines (Strober et al., 2019). The authors declare no competing financial interests. Predicting expression of a gene based on genotypes is possible because gene expression is highly heritable (Wright et al., 2014) and most of the gene expression heritability is attributable to variants in proximity (in cis) to the genes (Lloyd-Jones et al., 2017). https://doi.org/10.1038/s41467-017-02317-2, DOI: https://doi.org/10.1038/s41467-017-02317-2, European Journal of Neurology UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. Nat. Am. Ideally, gene-editing should be performed in disease-relevant cell types (for example, in cells prioritized by SNP enrichment). Genet. (2020), Arteriosclerosis, Thrombosis, and Vascular Biology Genet. If all the risk factors increase by 1 SD (i.e., ~4 kg m−2 for BMI, ~1 mmol L−1 for LDL-c, ~1 mmol L−1 for TG and ~19 mm Hg for SBP), we would have an increased risk of ~2.3-fold to T2D (e1.01−0.17), and 4.5-fold to CAD (e0.41+0.47+0.14+0.48). The PsychENCODE project. 48, 134–143 (2016). Most disease-associated variants are thought to act by mechanisms analogous to those at the SORT1 locus. Systematic functional dissection of common genetic variation affecting red blood cell traits. 48, 245–252. High trans-ethnic replicability of GWAS results implies common causal variants. Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium.
name The authors also used this approach across immune-mediated traits where pathogenic cell types are less well characterized. doi: 10.1016/j.cell.2017.05.038, Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., and Greenleaf, W. J. Z.Z. The disease status was coded as 0 (unaffected) and 1 (affected). xy eCollection 2020 Apr. is estimated without error.
This will allow us to confidently nominate the specific cell types and states causally involved in disease. “Random mutagenesis by Error-Prone PCR,” in In Vitro Mutagenesis Protocols, 3rd Edn, ed. doi: 10.1093/bioinformatics/btu326, Smith, G. D., Ebrahim, S., Lewis, S., Hansell, A. L., Palmer, L. J., and Burton, P. R. (2005). 13:e1006646. doi: 10.1016/j.ajhg.2017.09.009, Calderon, D., Nguyen, M. L. T., Mezger, A., Kathiria, A., Müller, F., Nguyen, V., et al. Disord. author Determining causality and consequence of expression quantitative trait loci.