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This paper investigates an MR scenario in which genetic variants aggregate into clusters that identify heterogeneous causal effects. Such variant clusters are likely to emerge if they affect the exposure and outcome via distinct biological pathways. In the multi\u2010outcome MR framework, where a shared exposure causally impacts several disease outcomes simultaneously, these variant clusters can provide insights into the common disease\u2010causing mechanisms underpinning the co\u2010occurrence of multiple long\u2010term conditions, a phenomenon known as multimorbidity. To identify such variant clusters, we adapt the general method of agglomerative hierarchical clustering to multi\u2010sample summary\u2010data MR setup, enabling cluster detection based on variant\u2010specific ratio estimates. Particularly, we tailor the method for multi\u2010outcome MR to aid in elucidating the causal pathways through which a common risk factor contributes to multiple morbidities. We show in simulations that our \u201cMR\u2010AHC\u201d method detects clusters with high accuracy, outperforming the existing methods. We apply the method to investigate the causal effects of high body fat percentage on type 2 diabetes and osteoarthritis, uncovering interconnected cellular processes underlying this multimorbid disease pair.<\/jats:p>","DOI":"10.1002\/gepi.22582","type":"journal-article","created":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T00:25:35Z","timestamp":1723595135000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Using clustering of genetic variants in Mendelian randomization to interrogate the causal pathways underlying multimorbidity from a common risk factor"],"prefix":"10.1002","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2142-2427","authenticated-orcid":false,"given":"Xiaoran","family":"Liang","sequence":"first","affiliation":[{"name":"Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences University of Exeter Exeter UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ninon","family":"Mounier","sequence":"additional","affiliation":[{"name":"Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences University of Exeter Exeter UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Apfel","sequence":"additional","affiliation":[{"name":"Department of Economics University of Southampton Southampton UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"Khalid","sequence":"additional","affiliation":[{"name":"Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy M.","family":"Frayling","sequence":"additional","affiliation":[{"name":"Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences University of Exeter Exeter UK"},{"name":"Department of Genetic Medicine and Development, Faculty of Medicine CMU Geneva Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jack","family":"Bowden","sequence":"additional","affiliation":[{"name":"Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences University of Exeter Exeter UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,8,13]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2458-13-1161"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00036"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/jae.3078"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2023.06.010"},{"key":"e_1_2_10_6_1","volume-title":"Ion channels and disease","author":"Ashcroft F. 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