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Biol."],"published-print":{"date-parts":[[2021,6]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Genome\u2010wide association studies (GWASs) have identified thousands of genetic variants that are associated with many complex traits. However, their biological mechanisms remain largely unknown. Transcriptome\u2010wide association studies (TWAS) have been recently proposed as an invaluable tool for investigating the potential gene regulatory mechanisms underlying variant\u2010trait associations. Specifically, TWAS integrate GWAS with expression mapping studies based on a common set of variants and aim to identify genes whose GReX is associated with the phenotype. Various methods have been developed for performing TWAS and\/or similar integrative analysis. Each such method has a different modeling assumption and many were initially developed to answer different biological questions. Consequently, it is not straightforward to understand their modeling property from a theoretical perspective.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We present a technical review on thirteen TWAS methods. Importantly, we show that these methods can all be viewed as two\u2010sample Mendelian randomization (MR) analysis, which has been widely applied in GWASs for examining the causal effects of exposure on outcome. Viewing different TWAS methods from an MR perspective provides us a unique angle for understanding their benefits and pitfalls. We systematically introduce the MR analysis framework, explain how features of the GWAS and expression data influence the adaptation of MR for TWAS, and re\u2010interpret the modeling assumptions made in different TWAS methods from an MR angle. We finally describe future directions for TWAS methodology development.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>We hope that this review would serve as a useful reference for both methodologists who develop TWAS methods and practitioners who perform TWAS analysis.<\/jats:p><\/jats:sec>","DOI":"10.1007\/s40484-020-0207-4","type":"journal-article","created":{"date-parts":[[2020,6,17]],"date-time":"2020-06-17T09:02:46Z","timestamp":1592384566000},"page":"107-121","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Transcriptome\u2010wide association studies: a view from Mendelian randomization"],"prefix":"10.1002","volume":"9","author":[{"given":"Huanhuan","family":"Zhu","sequence":"first","affiliation":[{"name":"<!--1--> Department of Biostatistics University of Michigan Ann Arbor MI 48109 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Zhou","sequence":"additional","affiliation":[{"name":"<!--1--> Department of Biostatistics University of Michigan Ann Arbor MI 48109 USA"},{"name":"<!--2--> Center for Statistical Genetics University of Michigan Ann Arbor MI 48109 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,6]]},"reference":[{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/ng.3506"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2653"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature12531"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1101\/gr.155192.113"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1038\/nn.3801"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1000952"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.04729"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature08872"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.2337\/db11\u20101378"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2015.10.025"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4399"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2951"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dym225"},{"key":"e_1_2_10_15_2","doi-asserted-by":"publisher","DOI":"10.1038\/ng.3367"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467\u20109868.2005.00503.x"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1003264"},{"key":"e_1_2_10_18_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467\u2010017\u201000470\u20102"},{"key":"e_1_2_10_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2019.05.018"},{"key":"e_1_2_10_20_2","doi-asserted-by":"publisher","DOI":"10.1038\/ng.3538"},{"key":"e_1_2_10_21_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467\u2010017\u201002317\u20102"},{"key":"e_1_2_10_22_2","doi-asserted-by":"crossref","unstructured":"Yuan Z. 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