{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T05:14:47Z","timestamp":1791436487216,"version":"4.3.3"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1009266","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T00:00:00Z","timestamp":1628726400000}}],"reference-count":46,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2021,8,2]],"date-time":"2021-08-02T00:00:00Z","timestamp":1627862400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS 1711226"],"award-info":[{"award-number":["DMS 1711226"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"minnesota supercomputing institute at the university of minnesota"},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["RF1AG067924, R01 AG065636, R01 HL116720, R01GM113250 and R01GM126002"],"award-info":[{"award-number":["RF1AG067924, R01 AG065636, R01 HL116720, R01GM113250 and R01GM126002"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS 1711226"],"award-info":[{"award-number":["DMS 1711226"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"minnesota supercomputing institute at the university of minnesota"},{"DOI":"10.13039\/100000002","name":"national institutes of health","doi-asserted-by":"publisher","award":["U01 AG024904"],"award-info":[{"award-number":["U01 AG024904"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000005","name":"department of defense","doi-asserted-by":"crossref","award":["W81XWH-12-2-0012"],"award-info":[{"award-number":["W81XWH-12-2-0012"]}],"id":[{"id":"10.13039\/100000005","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>It is of great interest and potential to discover causal relationships between pairs of exposures and outcomes using genetic variants as instrumental variables (IVs) to deal with hidden confounding in observational studies. Two most popular approaches are Mendelian randomization (MR), which usually use independent genetic variants\/SNPs across the genome, and transcriptome-wide association studies (TWAS) (or their generalizations) using cis-SNPs local to a gene (or some genome-wide and likely dependent SNPs), as IVs. In spite of their many promising applications, both approaches face a major challenge: the validity of their causal conclusions depends on three critical assumptions on valid IVs, and more generally on other modeling assumptions, which however may not hold in practice. The most likely as well as challenging situation is due to the wide-spread horizontal pleiotropy, leading to two of the three IV assumptions being violated and thus to biased statistical inference. More generally, we\u2019d like to conduct a goodness-of-fit (GOF) test to check the model being used. Although some methods have been proposed as being robust to various degrees to the violation of some modeling assumptions, they often give different and even conflicting results due to their own modeling assumptions and possibly lower statistical efficiency, imposing difficulties to the practitioner in choosing and interpreting varying results across different methods. Hence, it would help to directly test whether any assumption is violated or not. In particular, there is a lack of such tests for TWAS. We propose a new and general GOF test, called TEDE (TEsting Direct Effects), applicable to both correlated and independent SNPs\/IVs (as commonly used in TWAS and MR respectively). Through simulation studies and real data examples, we demonstrate high statistical power and advantages of our new method, while confirming the frequent violation of modeling (including valid IV) assumptions in practice and thus the importance of model checking by applying such a test in MR\/TWAS analysis.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1009266","type":"journal-article","created":{"date-parts":[[2021,8,2]],"date-time":"2021-08-02T13:46:00Z","timestamp":1627911960000},"page":"e1009266","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":5,"title":["Model checking via testing for direct effects in Mendelian Randomization and transcriptome-wide association studies"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6218-3437","authenticated-orcid":true,"given":"Yangqing","family":"Deng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1159-0582","authenticated-orcid":true,"given":"Wei","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2021,8,2]]},"reference":[{"key":"pcbi.1009266.ref001","doi-asserted-by":"crossref","first-page":"e43657","DOI":"10.7554\/eLife.43657","article-title":"An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome","volume":"8","author":"TG Richardson","year":"2019","journal-title":"eLife"},{"issue":"3","key":"pcbi.1009266.ref002","doi-asserted-by":"crossref","first-page":"e1001779","DOI":"10.1371\/journal.pmed.1001779","article-title":"UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age","volume":"12","author":"C Sudlow","year":"2015","journal-title":"PLoS medicine"},{"key":"pcbi.1009266.ref003","author":"Neale Lab","year":"2017","journal-title":"Rapid GWAS of thousands of phenotypes for 337,000 samples in the UK Biobank"},{"issue":"8","key":"pcbi.1009266.ref004","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pgen.1002254","article-title":"Pervasive sharing of genetic effects in autoimmune disease","volume":"7","author":"C Cotsapas","year":"2011","journal-title":"PLoS Genetics"},{"key":"pcbi.1009266.ref005","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.1007\/s00439-015-1596-8","article-title":"Pervasive pleiotropy between psychiatric disorders and immune disorders revealed by integrative analysis of multiple GWAS","volume":"134","author":"Q Wang","year":"2015","journal-title":"Human Genetics"},{"key":"pcbi.1009266.ref006","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1038\/s41588-018-0099-7","article-title":"Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases","volume":"50","author":"M Verbanck","year":"2018","journal-title":"Nature genetics"},{"issue":"7","key":"pcbi.1009266.ref007","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1038\/s41588-020-0631-4","article-title":"Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics","volume":"52","author":"J Morrison","year":"2020","journal-title":"Nat Genet"},{"issue":"2","key":"pcbi.1009266.ref008","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1093\/ije\/dyv080","article-title":"Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression","volume":"44","author":"J Bowden","year":"2015","journal-title":"International journal of epidemiology"},{"issue":"4","key":"pcbi.1009266.ref009","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1002\/gepi.21965","article-title":"Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator","volume":"40","author":"J Bowden","year":"2016","journal-title":"Genetic epidemiology"},{"issue":"11","key":"pcbi.1009266.ref010","doi-asserted-by":"crossref","first-page":"1880","DOI":"10.1002\/sim.6835","article-title":"Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods","volume":"35","author":"S Burgess","year":"2016","journal-title":"Statistics in medicine"},{"key":"pcbi.1009266.ref011","unstructured":"Burgess S, Bowden J, Dudbridge F, Thompson SG. 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