{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T22:01:39Z","timestamp":1787954499145,"version":"build-2784847793"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T00:00:00Z","timestamp":1735603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,31]]},"abstract":"<jats:title>Summary<\/jats:title>\n                  <jats:p>Genome-wide association studies (GWASs) have highlighted the importance of pleiotropy in human diseases, where one gene can impact 2 or more unrelated traits. Examining shared genetic risk factors across multiple diseases can enhance our understanding of these conditions by pinpointing new genes and biological pathways involved. Furthermore, with an increasing wealth of GWAS summary statistics available to the scientific community, leveraging these findings across multiple phenotypes could unveil novel pleiotropic associations. Existing selection methods examine pleiotropic associations one by one at a scale of either the genetic variant or the gene, and thus cannot consider all the genetic information at the same time. To address this limitation, we propose a new approach called MPSG (Meta-analysis model adapted for Pleiotropy Selection with Group structure). This method performs a penalized multivariate meta-analysis method adapted for pleiotropy and takes into account the group structure information nested in the data to select relevant variants and genes (or pathways) from all the genetic information. To do so, we implemented an alternating direction method of multipliers algorithm. We compared the performance of the method with other benchmark meta-analysis approaches such as GCPBayes, PLACO, and ASSET by considering as inputs different kinds of summary statistics. We provide an application of our method to the identification of potential pleiotropic genes between breast and thyroid cancers.<\/jats:p>","DOI":"10.1093\/biostatistics\/kxaf037","type":"journal-article","created":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T16:07:09Z","timestamp":1763309229000},"source":"Crossref","is-referenced-by-count":1,"title":["Meta-analysis models with group structure for pleiotropy detection at gene and variant level using summary statistics from multiple datasets"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5846-1104","authenticated-orcid":false,"given":"Pierre-Emmanuel","family":"Sugier","sequence":"first","affiliation":[{"name":"Laboratoire de Math\u00e9matiques et de leurs Applications de Pau, Universit\u00e9 de Pau et des Pays de l\u2019Adour , UMR CNRS 5142, E2S-UPPA ,","place":["France"]},{"name":"Team \u201cExposome and Heredity\u201d, Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP , Villejuif,","place":["France"]},{"name":"Universit\u00e9 Paris Cit\u00e9, CNRS, MAP5 , F-75006 Paris,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6993-6956","authenticated-orcid":false,"given":"Yazdan","family":"Asgari","sequence":"additional","affiliation":[{"name":"Team \u201cExposome and Heredity\u201d, Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP , Villejuif,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5489-9611","authenticated-orcid":false,"given":"Mohammed","family":"Sedki","sequence":"additional","affiliation":[{"name":"Team \u201cPsychiatrie du d\u00e9veloppement et trajectoires\u201d, Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP , Villejuif,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2943-6786","authenticated-orcid":false,"given":"Th\u00e9r\u00e8se","family":"Truong","sequence":"additional","affiliation":[{"name":"Team \u201cExposome and Heredity\u201d, Paris-Saclay University, UVSQ, Gustave Roussy, Inserm, CESP , Villejuif,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8136-2294","authenticated-orcid":false,"given":"Benoit","family":"Liquet","sequence":"additional","affiliation":[{"name":"Laboratoire de Math\u00e9matiques et de leurs Applications de Pau, Universit\u00e9 de Pau et des Pays de l\u2019Adour , UMR CNRS 5142, E2S-UPPA ,","place":["France"]},{"name":"School of Mathematical and Physical Sciences, Macquarie University , 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