{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:43:06Z","timestamp":1753875786282,"version":"3.41.2"},"reference-count":82,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T00:00:00Z","timestamp":1741651200000},"content-version":"vor","delay-in-days":10,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["R01DA048993","R01MH105561","R01GM124061","R01GM087964"],"award-info":[{"award-number":["R01DA048993","R01MH105561","R01GM124061","R01GM087964"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["IIS2123777"],"award-info":[{"award-number":["IIS2123777"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong Talent Program","award":["2021CX02Y145"],"award-info":[{"award-number":["2021CX02Y145"]}]},{"name":"Guangdong Provincial Key Laboratory of Big Data Computing"},{"name":"Shenzhen Key Laboratory of Cross-Modal Cognitive Computing","award":["ZDSYS20230626091302006"],"award-info":[{"award-number":["ZDSYS20230626091302006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Understanding genetic regulation of metabolism is critical for gaining insights into the causes of metabolic diseases. Traditional metabolome-based genome-wide association studies (mGWAS) focus on static associations between single nucleotide polymorphisms (SNPs) and metabolite levels, overlooking the changing relationships caused by genotypes within the metabolic network. Notably, some metabolites exhibit changes in correlation patterns with other metabolites under certain physiological conditions while maintaining their overall abundance level. In this manuscript, we develop Metabolic Differential-coordination GWAS (mdGWAS), an innovative framework that detects SNPs associated with the changing correlation patterns between metabolites and metabolic pathways. This approach transcends and complements conventional mean-based analyses by identifying latent regulatory factors that govern the system-level metabolic coordination. Through comprehensive simulation studies, mdGWAS demonstrated robust performance in detecting SNP-metabolite-metabolite associations. Applying mdGWAS to genotyping and mass spectrometry (MS)-based metabolomics data of the METabolic Syndrome In Men (METSIM) Study revealed novel SNPs and genes potentially involved in the regulation of the coordination between metabolic pathways.<\/jats:p>","DOI":"10.1093\/bib\/bbaf095","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T13:33:04Z","timestamp":1741699984000},"source":"Crossref","is-referenced-by-count":0,"title":["Dissecting genetic regulation of metabolic coordination"],"prefix":"10.1093","volume":"26","author":[{"given":"Emily C","family":"Hector","sequence":"first","affiliation":[{"name":"Department of Statistics, North Carolina State University , Raleigh, NC 27695 ,","place":["United States"]}]},{"given":"Daiwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Michigan , Ann Arbor, MI 48109 ,","place":["United States"]},{"name":"Department of Biostatistics and Department of Genetics, University of North Carolina , Chapel Hill, NC 27599 ,","place":["United States"]}]},{"given":"Leqi","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Data Science, the Chinese University of Hong Kong , Shenzhen, Guangdong 518172 ,","place":["P.R.China"]}]},{"given":"Junning","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Data Science, the Chinese University of Hong Kong , Shenzhen, Guangdong 518172 ,","place":["P.R.China"]}]},{"given":"Xianyong","family":"Yin","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Michigan , Ann Arbor, MI 48109 ,","place":["United States"]}]},{"given":"Tianyi","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Data Science, the Chinese University of Hong Kong , Shenzhen, Guangdong 518172 ,","place":["P.R.China"]}]},{"given":"Markku","family":"Laakso","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Eastern Finland , FI-70211 Kuopio ,","place":["Finland"]}]},{"given":"Yun","family":"Bai","sequence":"additional","affiliation":[{"name":"School of Medicine, the Chinese University of Hong Kong , Shenzhen, Guangdong 518172 ,","place":["P.R.China"]}]},{"given":"Jiashun","family":"Xiao","sequence":"additional","affiliation":[{"name":"Shenzhen Research Institute of Big Data , Shenzhen, Guangdong 518172 ,","place":["P.R.China"]}]},{"given":"Jian","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Michigan , Ann Arbor, MI 48109 ,","place":["United States"]}]},{"given":"Tianwei","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Data Science, the Chinese University of Hong Kong , Shenzhen, Guangdong 518172 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