{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T04:08:47Z","timestamp":1784088527739,"version":"3.55.0"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T00:00:00Z","timestamp":1779408000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"vor","delay-in-days":54,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004829","name":"Science and Technology Department of Sichuan Province","doi-asserted-by":"publisher","award":["2025ZNSFSC0641"],"award-info":[{"award-number":["2025ZNSFSC0641"]}],"id":[{"id":"10.13039\/501100004829","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U25A20154"],"award-info":[{"award-number":["U25A20154"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Genome Med"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The etiology of gestational diabetes mellitus (GDM) is constituted by both type 2 diabetes (T2D)-dependent and T2D-independent mechanisms. However, existing studies have evaluated the impact of T2D-dependent loci only for GDM, which limits the power to assess to what extent genetic variants or biological pathways are specific to GDM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We subtracted the genetic effects of a genome-wide association study (GWAS) data for T2D from a GWAS data for GDM to reveal loci linked with T2D-independent components of GDM using genomic structural equation model (SEM). In the discovery stage of GWAS-by-subtraction, we used GWAS summary statistics of GDM and T2D from the FinnGen study as input latent variables (16,802 GDM cases and 237,816 controls; 71,728 T2D cases and 369,007 controls). In the replication stage, we adopted the summary statistics from a previously reported GWAS for GDM and T2D as input (21,263 GDM cases and 301,918 controls; 50,409 T2D cases and 523,897 controls). We functionally annotated variants with genome-wide significance, and performed comprehensive analyses including transcriptome-wide and proteome-wide associations, summary-data-based mendelian randomization, linkage disequilibrium score regression, and Mendelian randomization, to explore genetic patterns for T2D-dependent and -independent components of GDM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We found 69 independent genome-wide significant loci associated with the T2D-independent components of GDM for discovery stage, of which 49 SNPs are not significant in the GWAS for GDM used as input. T2D-independent components of GDM showed only genetic correlation with birth weight dependent on maternal genetic effect (rg\u2009=\u20090.19;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.01), whilst T2D-dependent components of GDM showed genetic correlation with birth weight dependent on fetal genetic effect (rg = -0.22;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20094.76\u2009\u00d7\u200910\n                      <jats:sup>\u2212\u20097<\/jats:sup>\n                      ). Loci of T2D-independent components of GDM effects map to genes related to islets of Langerhans, neural stem cells, blood levels of mannose, abundance of\n                      <jats:italic>Streptococcus thermophilus<\/jats:italic>\n                      and\n                      <jats:italic>Bacteroides vulgatus<\/jats:italic>\n                      , glucose and carbohydrate homeostasis, and the MAPK cascade and adenylate cyclase-activating G protein-coupled receptor signaling pathway.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We identified independent genetic components, loci and genes of GDM that may have been previously masked by T2D, providing more accurate targets for early detection and management of GDM.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13073-026-01674-2","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T07:06:34Z","timestamp":1779433594000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GWAS-by-subtraction reveals new genetic architecture and health implications of type 2 diabetes-independent gestational diabetes mellitus"],"prefix":"10.1186","volume":"18","author":[{"given":"Siquan","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhichang","family":"Ran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanliu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayuan","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanqi","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruirui","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujie","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ciling","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9354-862X","authenticated-orcid":false,"given":"Jingyuan","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0945-5728","authenticated-orcid":false,"given":"Guo","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,22]]},"reference":[{"issue":"7","key":"1674_CR1","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1001\/jama.2021.7217","volume":"326","author":"NS Shah","year":"2021","unstructured":"Shah NS, Wang MC, Freaney PM, Perak AM, Carnethon MR, Kandula NR, et al. Trends in Gestational Diabetes at First Live Birth by Race and Ethnicity in the US, 2011\u20132019. JAMA. 2021;326(7):660\u20139. https:\/\/doi.org\/10.1001\/jama.2021.7217.","journal-title":"JAMA"},{"issue":"19","key":"1674_CR2","doi-asserted-by":"publisher","first-page":"3377","DOI":"10.1093\/hmg\/ddac050","volume":"31","author":"N Pervjakova","year":"2022","unstructured":"Pervjakova N, Moen GH, Borges MC, Ferreira T, Cook JP, Allard C, et al. Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes. Hum Mol Genet. 2022;31(19):3377\u201391. https:\/\/doi.org\/10.1093\/hmg\/ddac050.","journal-title":"Hum Mol Genet"},{"issue":"3","key":"1674_CR3","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1038\/s41588-023-01607-4","volume":"56","author":"A Elliott","year":"2024","unstructured":"Elliott A, Walters RK, Pirinen M, Kurki M, Junna N, Goldstein JI, et al. Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes. Nat Genet. 2024;56(3):377\u201382. https:\/\/doi.org\/10.1038\/s41588-023-01607-4.","journal-title":"Nat Genet"},{"issue":"1","key":"1674_CR4","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1038\/s41588-020-00754-2","volume":"53","author":"PA Demange","year":"2021","unstructured":"Demange PA, Malanchini M, Mallard TT, Biroli P, Cox SR, Grotzinger AD, et al. Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction. Nat Genet. 2021;53(1):35\u201344. https:\/\/doi.org\/10.1038\/s41588-020-00754-2.","journal-title":"Nat Genet"},{"issue":"1","key":"1674_CR5","doi-asserted-by":"publisher","first-page":"8962","DOI":"10.1038\/s41467-024-53331-0","volume":"15","author":"Y Huang","year":"2024","unstructured":"Huang Y, Plotnikov D, Wang H, Shi D, Li C, Zhang X, et al. GWAS-by-subtraction reveals an IOP-independent component of primary open angle glaucoma. Nat Commun. 2024;15(1):8962. https:\/\/doi.org\/10.1038\/s41467-024-53331-0.","journal-title":"Nat Commun"},{"issue":"5","key":"1674_CR6","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1038\/s41562-019-0566-x","volume":"3","author":"AD Grotzinger","year":"2019","unstructured":"Grotzinger AD, Rhemtulla M, de Vlaming R, Ritchie SJ, Mallard TT, Hill WD, et al. Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits. Nat Hum Behav. 2019;3(5):513\u201325. https:\/\/doi.org\/10.1038\/s41562-019-0566-x.","journal-title":"Nat Hum Behav"},{"issue":"7944","key":"1674_CR7","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1038\/s41586-022-05473-8","volume":"613","author":"MI Kurki","year":"2023","unstructured":"Kurki MI, Karjalainen J, Palta P, Sipil\u00e4 TP, Kristiansson K, Donner KM, et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature. 2023;613(7944):508\u201318. https:\/\/doi.org\/10.1038\/s41586-022-05473-8.","journal-title":"Nature"},{"issue":"11","key":"1674_CR8","doi-asserted-by":"publisher","first-page":"1505","DOI":"10.1038\/s41588-018-0241-6","volume":"50","author":"A Mahajan","year":"2018","unstructured":"Mahajan A, Taliun D, Thurner M, Robertson NR, Torres JM, Rayner NW, et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat Genet. 2018;50(11):1505\u201313. https:\/\/doi.org\/10.1038\/s41588-018-0241-6.","journal-title":"Nat Genet"},{"issue":"1","key":"1674_CR9","doi-asserted-by":"publisher","first-page":"4178","DOI":"10.1038\/s41467-025-59442-6","volume":"16","author":"Y Gu","year":"2025","unstructured":"Gu Y, Zheng H, Wang P, et al. Genetic architecture and risk prediction of gestational diabetes mellitus in Chinese pregnancies. Nat Commun. 2025;16(1):4178. https:\/\/doi.org\/10.1038\/s41467-025-59442-6.","journal-title":"Nat Commun"},{"issue":"7811","key":"1674_CR10","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1038\/s41586-020-2263-3","volume":"582","author":"CN Spracklen","year":"2020","unstructured":"Spracklen CN, Horikoshi M, Kim YJ, et al. Identification of type 2 diabetes loci in 433,540 East Asian individuals. Nature. 2020;582(7811):240\u20135. https:\/\/doi.org\/10.1038\/s41586-020-2263-3.","journal-title":"Nature"},{"issue":"1","key":"1674_CR11","doi-asserted-by":"publisher","first-page":"1826","DOI":"10.1038\/s41467-017-01261-5","volume":"8","author":"K Watanabe","year":"2017","unstructured":"Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8(1):1826. https:\/\/doi.org\/10.1038\/s41467-017-01261-5.","journal-title":"Nat Commun"},{"issue":"11","key":"1674_CR12","doi-asserted-by":"publisher","first-page":"1236","DOI":"10.1038\/ng.3406","volume":"47","author":"B Bulik-Sullivan","year":"2015","unstructured":"Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015;47(11):1236\u201341. https:\/\/doi.org\/10.1038\/ng.3406.","journal-title":"Nat Genet"},{"issue":"3","key":"1674_CR13","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1038\/ng.3211","volume":"47","author":"BK Bulik-Sullivan","year":"2015","unstructured":"Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S, Yang J, Schizophrenia Working Group of the Psychiatric Genomics Consortium. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47(3):291\u20135. https:\/\/doi.org\/10.1038\/ng.3211.","journal-title":"Nat Genet"},{"issue":"6","key":"1674_CR14","doi-asserted-by":"publisher","first-page":"840","DOI":"10.1038\/s41588-021-00852-9","volume":"53","author":"J Chen","year":"2021","unstructured":"Chen J, Spracklen CN, Marenne G, et al. The trans-ancestral genomic architecture of glycemic traits. Nat Genet. 2021;53(6):840\u201360. https:\/\/doi.org\/10.1038\/s41588-021-00852-9.","journal-title":"Nat Genet"},{"issue":"10","key":"1674_CR15","doi-asserted-by":"publisher","first-page":"2624","DOI":"10.2337\/db11-0415","volume":"60","author":"RJ Strawbridge","year":"2011","unstructured":"Strawbridge RJ, Dupuis J, Prokopenko I, et al. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes. Diabetes. 2011;60(10):2624\u201334. https:\/\/doi.org\/10.2337\/db11-0415.","journal-title":"Diabetes"},{"issue":"2","key":"1674_CR16","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1038\/ng.520","volume":"42","author":"J Dupuis","year":"2010","unstructured":"Dupuis J, Langenberg C, Prokopenko I, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42(2):105\u201316. https:\/\/doi.org\/10.1038\/ng.520.","journal-title":"Nat Genet"},{"issue":"6","key":"1674_CR17","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1038\/s41588-023-01408-9","volume":"55","author":"A Williamson","year":"2023","unstructured":"Williamson A, Norris DM, Yin X, et al. Genome-wide association study and functional characterization identifies candidate genes for insulin-stimulated glucose uptake. Nat Genet. 2023;55(6):973\u201383. https:\/\/doi.org\/10.1038\/s41588-023-01408-9.","journal-title":"Nat Genet"},{"issue":"2","key":"1674_CR18","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1016\/j.ajhg.2023.01.002","volume":"110","author":"KA Broadaway","year":"2023","unstructured":"Broadaway KA, Yin X, Williamson A, et al. Loci for insulin processing and secretion provide insight into type 2 diabetes risk. Am J Hum Genet. 2023;110(2):284\u201399. https:\/\/doi.org\/10.1016\/j.ajhg.2023.01.002.","journal-title":"Am J Hum Genet"},{"issue":"9","key":"1674_CR19","doi-asserted-by":"publisher","first-page":"1448","DOI":"10.1038\/s41588-023-01462-3","volume":"55","author":"V Lagou","year":"2023","unstructured":"Lagou V, Jiang L, Ulrich A, et al. GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification. Nat Genet. 2023;55(9):1448\u201361. https:\/\/doi.org\/10.1038\/s41588-023-01462-3.","journal-title":"Nat Genet"},{"issue":"4","key":"1674_CR20","doi-asserted-by":"publisher","first-page":"1155","DOI":"10.1093\/hmg\/ddu510","volume":"24","author":"RJ van der Valk","year":"2015","unstructured":"van der Valk RJ, Kreiner-M\u00f8ller E, Kooijman MN, et al. A novel common variant in DCST2 is associated with length in early life and height in adulthood. Hum Mol Genet. 2015;24(4):1155\u201368. https:\/\/doi.org\/10.1093\/hmg\/ddu510.","journal-title":"Hum Mol Genet"},{"issue":"4","key":"1674_CR21","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1038\/s41588-023-01343-9","volume":"55","author":"P Sol\u00e9-Navais","year":"2023","unstructured":"Sol\u00e9-Navais P, Flatley C, Steinthorsdottir V, et al. Genetic effects on the timing of parturition and links to fetal birth weight. Nat Genet. 2023;55(4):559\u201367. https:\/\/doi.org\/10.1038\/s41588-023-01343-9.","journal-title":"Nat Genet"},{"issue":"1","key":"1674_CR22","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1186\/s12920-022-01281-1","volume":"15","author":"S Vogelezang","year":"2022","unstructured":"Vogelezang S, Bradfield JP, Early Growth Genetics Consortium, Grant SFA, Felix JF, Jaddoe VWV. Genetics of early-life head circumference and genetic correlations with neurological, psychiatric and cognitive outcomes. BMC Med Genomics. 2022;15(1):124. https:\/\/doi.org\/10.1186\/s12920-022-01281-1.","journal-title":"BMC Med Genomics"},{"issue":"5","key":"1674_CR23","doi-asserted-by":"publisher","first-page":"804","DOI":"10.1038\/s41588-019-0403-1","volume":"51","author":"NM Warrington","year":"2019","unstructured":"Warrington NM, Beaumont RN, Horikoshi M, et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat Genet. 2019;51(5):804\u201314. https:\/\/doi.org\/10.1038\/s41588-019-0403-1.","journal-title":"Nat Genet"},{"issue":"4","key":"1674_CR24","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1038\/ijo.2017.248","volume":"42","author":"NM Warrington","year":"2018","unstructured":"Warrington NM, Richmond R, Fenstra B, et al. Maternal and fetal genetic contribution to gestational weight gain. Int J Obes (Lond). 2018;42(4):775\u201384. https:\/\/doi.org\/10.1038\/ijo.2017.248.","journal-title":"Int J Obes (Lond)"},{"issue":"11","key":"1674_CR25","doi-asserted-by":"publisher","first-page":"1807","DOI":"10.1038\/s41588-023-01520-w","volume":"55","author":"RN Beaumont","year":"2023","unstructured":"Beaumont RN, Flatley C, Vaudel M, et al. Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth. Nat Genet. 2023;55(11):1807\u201319. https:\/\/doi.org\/10.1038\/s41588-023-01520-w.","journal-title":"Nat Genet"},{"issue":"2","key":"1674_CR26","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1038\/s41588-020-00757-z","volume":"53","author":"N Sinnott-Armstrong","year":"2021","unstructured":"Sinnott-Armstrong N, Tanigawa Y, Amar D, Mars N, Benner C, Aguirre M, et al. Genetics of 35 blood and urine biomarkers in the UK Biobank. Nat Genet. 2021;53(2):185\u201394. https:\/\/doi.org\/10.1038\/s41588-020-00757-z.","journal-title":"Nat Genet"},{"issue":"3","key":"1674_CR27","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1038\/ng.3506","volume":"48","author":"A Gusev","year":"2016","unstructured":"Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx BW, et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016;48(3):245\u201352. https:\/\/doi.org\/10.1038\/ng.3506.","journal-title":"Nat Genet"},{"issue":"5","key":"1674_CR28","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1038\/s41588-022-01051-w","volume":"54","author":"J Zhang","year":"2022","unstructured":"Zhang J, Dutta D, K\u00f6ttgen A, Tin A, Schlosser P, Grams ME, et al. Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies. Nat Genet. 2022;54(5):593\u2013602. https:\/\/doi.org\/10.1038\/s41588-022-01051-w.","journal-title":"Nat Genet"},{"issue":"5","key":"1674_CR29","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1038\/ng.3538","volume":"48","author":"Z Zhu","year":"2016","unstructured":"Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48(5):481\u20137.","journal-title":"Nat Genet"},{"issue":"4","key":"1674_CR30","doi-asserted-by":"publisher","first-page":"1153","DOI":"10.1038\/s41380-023-02400-9","volume":"29","author":"S Liu","year":"2024","unstructured":"Liu S, Zhong H, Zhu J, Wu L. Identification of blood metabolites associated with risk of Alzheimer\u2019s disease by integrating genomics and metabolomics data. Mol Psychiatry. 2024;29(4):1153\u201362. https:\/\/doi.org\/10.1038\/s41380-023-02400-9.","journal-title":"Mol Psychiatry"},{"issue":"11","key":"1674_CR31","doi-asserted-by":"publisher","first-page":"e1007081","DOI":"10.1371\/journal.pgen.1007081","volume":"13","author":"G Hemani","year":"2017","unstructured":"Hemani G, Tilling K, Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017;13(11):e1007081. https:\/\/doi.org\/10.1371\/journal.pgen.1007081.","journal-title":"PLoS Genet"},{"issue":"4","key":"1674_CR32","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1038\/s41588-018-0081-4","volume":"50","author":"HK Finucane","year":"2018","unstructured":"Finucane HK, Reshef YA, Anttila V, Slowikowski K, Gusev A, Byrnes A, et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat Genet. 2018;50(4):621\u20139. https:\/\/doi.org\/10.1038\/s41588-018-0081-4.","journal-title":"Nat Genet"},{"issue":"1","key":"1674_CR33","doi-asserted-by":"publisher","first-page":"1523","DOI":"10.1038\/s41467-019-09234-6","volume":"10","author":"Y Zhou","year":"2019","unstructured":"Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523. https:\/\/doi.org\/10.1038\/s41467-019-09234-6.","journal-title":"Nat Commun"},{"issue":"2","key":"1674_CR34","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1038\/s41592-024-02561-7","volume":"22","author":"Y Guo","year":"2025","unstructured":"Guo Y, Xu T, Luo J, Jiang Z, Chen W, Chen H, et al. SMR-Portal: an online platform for integrative analysis of GWAS and xQTL data to identify complex trait genes. Nat Methods. 2025;22(2):220\u20132. https:\/\/doi.org\/10.1038\/s41592-024-02561-7.","journal-title":"Nat Methods"},{"issue":"2","key":"1674_CR35","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1038\/s41588-021-00992-y","volume":"54","author":"EA Lopera-Maya","year":"2022","unstructured":"Lopera-Maya EA, Kurilshikov A, van der Graaf A, Hu S, Andreu-S\u00e1nchez S, Chen L, et al. Effect of host genetics on the gut microbiome in 7,738 participants of the Dutch Microbiome Project. Nat Genet. 2022;54(2):143\u201351. https:\/\/doi.org\/10.1038\/s41588-021-00992-y.","journal-title":"Nat Genet"},{"key":"1674_CR36","doi-asserted-by":"publisher","first-page":"e34408","DOI":"10.7554\/eLife.34408","volume":"7","author":"G Hemani","year":"2018","unstructured":"Hemani G, Zheng J, Elsworth B, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018;7:e34408. https:\/\/doi.org\/10.7554\/eLife.34408. Published 2018 May 30.","journal-title":"Elife"},{"issue":"7","key":"1674_CR37","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1002\/gepi.21758","volume":"37","author":"S Burgess","year":"2013","unstructured":"Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37(7):658\u201365. https:\/\/doi.org\/10.1002\/gepi.21758.","journal-title":"Genet Epidemiol"},{"issue":"4","key":"1674_CR38","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1002\/gepi.21965","volume":"40","author":"J Bowden","year":"2016","unstructured":"Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol. 2016;40(4):304\u201314. https:\/\/doi.org\/10.1002\/gepi.21965.","journal-title":"Genet Epidemiol"},{"issue":"6","key":"1674_CR39","doi-asserted-by":"publisher","first-page":"1985","DOI":"10.1093\/ije\/dyx102","volume":"46","author":"FP Hartwig","year":"2017","unstructured":"Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46(6):1985\u201398.","journal-title":"Int J Epidemiol"},{"issue":"2","key":"1674_CR40","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1093\/ije\/dyv080","volume":"44","author":"J Bowden","year":"2015","unstructured":"Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512\u201325. https:\/\/doi.org\/10.1093\/ije\/dyv080.","journal-title":"Int J Epidemiol"},{"key":"1674_CR41","doi-asserted-by":"publisher","unstructured":"Ma RC, Chan JC. Type 2 diabetes in East Asians: similarities and differences with populations in Europe and the United States. Ann N Y Acad Sci. https:\/\/doi.org\/10.1111\/nyas.12098","DOI":"10.1111\/nyas.12098"},{"issue":"12","key":"1674_CR42","doi-asserted-by":"publisher","first-page":"2211","DOI":"10.2337\/dc19-053244","volume":"42","author":"Y Zhu","year":"2019","unstructured":"Zhu Y, Sidell MA, Arterburn D, et al. Racial\/Ethnic Disparities in the Prevalence of Diabetes and Prediabetes by BMI: Patient Outcomes Research To Advance Learning (PORTAL) Multisite Cohort of Adults in the U.S. Diabetes Care. 2019;42(12):2211\u20139. https:\/\/doi.org\/10.2337\/dc19-053244.","journal-title":"Diabetes Care"},{"issue":"5","key":"1674_CR43","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1016\/j.cmet.2018.03.005","volume":"27","author":"HC Roh","year":"2018","unstructured":"Roh HC, Tsai LTY, Shao M, Tenen D, Shen Y, Kumari M, et al. Warming Induces Significant Reprogramming of Beige, but Not Brown, Adipocyte Cellular Identity. Cell Metab. 2018;27(5):1121\u2013e375. https:\/\/doi.org\/10.1016\/j.cmet.2018.03.005.","journal-title":"Cell Metab"},{"issue":"12","key":"1674_CR44","doi-asserted-by":"publisher","first-page":"829","DOI":"10.1038\/nrg3813","volume":"15","author":"S Gerstberger","year":"2014","unstructured":"Gerstberger S, Hafner M, Tuschl T. A census of human RNA-binding proteins. Nat Rev Genet. 2014;15(12):829\u201345. https:\/\/doi.org\/10.1038\/nrg3813.","journal-title":"Nat Rev Genet"},{"key":"1674_CR45","doi-asserted-by":"publisher","unstructured":"Dumesic PA, Wilensky SE, Bose S, Van Vranken JG, Gygi SP, Spiegelman BM. RBM43 links adipose inflammation and energy expenditure through translational regulation of PGC1\u03b1. bioRxiv [Preprint]. 2023:2023.01.06.522985. https:\/\/doi.org\/10.1101\/2023.01.06.522985.","DOI":"10.1101\/2023.01.06.522985"},{"issue":"1","key":"1674_CR46","doi-asserted-by":"publisher","first-page":"2079","DOI":"10.1038\/s41598-021-81457-4","volume":"11","author":"JP Werneck-de-Castro","year":"2021","unstructured":"Werneck-de-Castro JP, Pe\u00e7anha FLM, Silvestre DH, Bernal-Mizrachi E. The RNA-binding protein LARP1 is dispensable for pancreatic \u03b2-cell function and mass. Sci Rep. 2021;11(1):2079. https:\/\/doi.org\/10.1038\/s41598-021-81457-4.","journal-title":"Sci Rep"},{"issue":"4","key":"1674_CR47","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1101\/gad.231407.113","volume":"28","author":"J Tcherkezian","year":"2014","unstructured":"Tcherkezian J, Cargnello M, Romeo Y, Huttlin EL, Lavoie G, Gygi SP, et al. Proteomic analysis of cap-dependent translation identifies LARP1 as a key regulator of 5\u2019TOP mRNA translation. Genes Dev. 2014;28(4):357\u201371. https:\/\/doi.org\/10.1101\/gad.231407.113.","journal-title":"Genes Dev"},{"key":"1674_CR48","doi-asserted-by":"publisher","first-page":"e25237","DOI":"10.7554\/eLife.25237","volume":"6","author":"S Hong","year":"2017","unstructured":"Hong S, Freeberg MA, Han T, Kamath A, Yao Y, Fukuda T, et al. LARP1 functions as a molecular switch for mTORC1-mediated translation of an essential class of mRNAs. Elife. 2017;6:e25237. https:\/\/doi.org\/10.7554\/eLife.25237.","journal-title":"Elife"},{"issue":"9","key":"1674_CR49","doi-asserted-by":"publisher","first-page":"1556","DOI":"10.3390\/genes13091556","volume":"13","author":"P Janusz","year":"2022","unstructured":"Janusz P, Tok\u0142owicz M, Andrusiewicz M, Kotwicka M, Kotwicki T. Association of LBX1 Gene Methylation Level with Disease Severity in Patients with Idiopathic Scoliosis: Study on Deep Paravertebral Muscles. Genes (Basel). 2022;13(9):1556. https:\/\/doi.org\/10.3390\/genes13091556.","journal-title":"Genes (Basel)"},{"issue":"8","key":"1674_CR50","doi-asserted-by":"publisher","first-page":"e0308445","DOI":"10.1371\/journal.pone.0308445","volume":"19","author":"T Nakagawa","year":"2024","unstructured":"Nakagawa T, Horiuchi K, Kagami K, Kondo S, Isaji M, Matsuhashi Y, et al. The alteration of LBX1 expression is associated with changes in parameters related to energy metabolism in mice. PLoS ONE. 2024;19(8):e0308445. https:\/\/doi.org\/10.1371\/journal.pone.0308445.","journal-title":"PLoS ONE"},{"issue":"7","key":"1674_CR51","doi-asserted-by":"publisher","first-page":"706","DOI":"10.1038\/s41594-022-00792-w","volume":"29","author":"F Vallese","year":"2022","unstructured":"Vallese F, Kim K, Yen LY, Johnston JD, Noble AJ, Cal\u00ec T, et al. Architecture of the human erythrocyte ankyrin-1 complex. Nat Struct Mol Biol. 2022;29(7):706\u201318. https:\/\/doi.org\/10.1038\/s41594-022-00792-w.","journal-title":"Nat Struct Mol Biol"},{"issue":"10","key":"1674_CR52","doi-asserted-by":"publisher","first-page":"1600","DOI":"10.3390\/children10101600","volume":"10","author":"W Xu","year":"2023","unstructured":"Xu W, Ma M, Zhao S, Yuan Y, Tian Z. Case of Congenital Hemolytic Anemia with ATP11C and ANK1 Variants. Child (Basel). 2023;10(10):1600. https:\/\/doi.org\/10.3390\/children10101600.","journal-title":"Child (Basel)"},{"issue":"1","key":"1674_CR53","doi-asserted-by":"publisher","first-page":"8195","DOI":"10.1038\/s41598-023-35393-0","volume":"13","author":"E Pierantozzi","year":"2023","unstructured":"Pierantozzi E, Raucci L, Buonocore S, Rubino EM, Ding Q, Laurino A, et al. Skeletal muscle overexpression of sAnk1.5 in transgenic mice does not predispose to type 2 diabetes. Sci Rep. 2023;13(1):8195. https:\/\/doi.org\/10.1038\/s41598-023-35393-0.","journal-title":"Sci Rep"},{"key":"1674_CR54","doi-asserted-by":"publisher","first-page":"25105","DOI":"10.1038\/srep25105","volume":"6","author":"R Yan","year":"2016","unstructured":"Yan R, Lai S, Yang Y, Shi H, Cai Z, Sorrentino V, et al. A novel type 2 diabetes risk allele increases the promoter activity of the muscle-specific small ankyrin 1 gene. Sci Rep. 2016;6:25105. https:\/\/doi.org\/10.1038\/srep25105.","journal-title":"Sci Rep"},{"issue":"13","key":"1674_CR55","doi-asserted-by":"publisher","first-page":"3042","DOI":"10.1093\/hmg\/dds113","volume":"21","author":"M Imamura","year":"2012","unstructured":"Imamura M, Maeda S, Yamauchi T, Hara K, Yasuda K, Morizono T, et al. A single-nucleotide polymorphism in ANK1 is associated with susceptibility to type 2 diabetes in Japanese populations. Hum Mol Genet. 2012;21(13):3042\u20139. https:\/\/doi.org\/10.1093\/hmg\/dds113.","journal-title":"Hum Mol Genet"},{"key":"1674_CR56","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.placenta.2022.11.012","volume":"131","author":"L Ge","year":"2023","unstructured":"Ge L, Huang P, Miao H, Yu H, Wu D, Chen F, et al. The new landscape of differentially expression proteins in placenta tissues of gestational diabetes based on iTRAQ proteomics. Placenta. 2023;131:36\u201348. https:\/\/doi.org\/10.1016\/j.placenta.2022.11.012.","journal-title":"Placenta"},{"issue":"5","key":"1674_CR57","doi-asserted-by":"publisher","first-page":"e70017","DOI":"10.1111\/aji.70017","volume":"92","author":"A Zhao","year":"2024","unstructured":"Zhao A, Yang Y, Yang Y, Chi Z, Sun Y. Circ-ADAM9 Knockdown Reduces Insulin Resistance and Placental Injury in Diabetic Mice via MAPK Pathway Inactivation. Am J Reprod Immunol. 2024;92(5):e70017. https:\/\/doi.org\/10.1111\/aji.70017.","journal-title":"Am J Reprod Immunol"},{"key":"1674_CR58","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.placenta.2024.05.138","volume":"154","author":"E Musa","year":"2024","unstructured":"Musa E, Salazar-Petres E, Vatish M, Levitt N, Sferruzzi-Perri AN, Matjila MJ. Kisspeptin signalling and its correlation with placental ultrastructure and clinical outcomes in pregnant South African women with obesity and gestational diabetes. Placenta. 2024;154:49\u201359. https:\/\/doi.org\/10.1016\/j.placenta.2024.05.138.","journal-title":"Placenta"},{"issue":"1","key":"1674_CR59","doi-asserted-by":"publisher","first-page":"20220920","DOI":"10.1515\/biol-2022-0920","volume":"19","author":"Y Zhu","year":"2024","unstructured":"Zhu Y, Huang S, Chai D, Liang L. G protein-coupled receptor 1 participating in the mechanism of mediating gestational diabetes mellitus by phosphorylating the AKT pathway. Open Life Sci. 2024;19(1):20220920. https:\/\/doi.org\/10.1515\/biol-2022-0920.","journal-title":"Open Life Sci"},{"key":"1674_CR60","doi-asserted-by":"publisher","first-page":"1220472","DOI":"10.3389\/fendo.2023.1220472","volume":"14","author":"Q He","year":"2023","unstructured":"He Q, Lin M, Wu Z, Yu R. Predictive value of first-trimester GPR120 levels in gestational diabetes mellitus. Front Endocrinol (Lausanne). 2023;14:1220472. https:\/\/doi.org\/10.3389\/fendo.2023.1220472.","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"12","key":"1674_CR61","doi-asserted-by":"publisher","first-page":"1709","DOI":"10.1007\/s00592-023-02165-1","volume":"60","author":"M Zhu","year":"2023","unstructured":"Zhu M, Lv Y, Peng Y, Wu Y, Feng Y, Jia T, et al. GCKR and ADIPOQ gene polymorphisms in women with gestational diabetes mellitus. Acta Diabetol. 2023;60(12):1709\u201318. https:\/\/doi.org\/10.1007\/s00592-023-02165-1.","journal-title":"Acta Diabetol"},{"issue":"1","key":"1674_CR62","doi-asserted-by":"publisher","first-page":"116","DOI":"10.3390\/biom14010116","volume":"14","author":"HH Shen","year":"2024","unstructured":"Shen HH, Zhang YY, Wang XY, Wang CJ, Wang Y, Ye JF, et al. Potential Causal Association between Plasma Metabolites, Immunophenotypes, and Female Reproductive Disorders: A Two-Sample Mendelian Randomization Analysis. Biomolecules. 2024;14(1):116. https:\/\/doi.org\/10.3390\/biom14010116.","journal-title":"Biomolecules"},{"key":"1674_CR63","doi-asserted-by":"publisher","first-page":"711","DOI":"10.3389\/fendo.2019.00711","volume":"10","author":"D Feng","year":"2019","unstructured":"Feng D, Shi B, Bi F, Sagnelli M, Sun X, Jiao J, et al. Elevated Serum Mannose Levels as a Marker of Polycystic Ovary Syndrome. Front Endocrinol (Lausanne). 2019;10:711. https:\/\/doi.org\/10.3389\/fendo.2019.00711.","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"2","key":"1674_CR64","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/j.cmet.2017.07.006","volume":"26","author":"A Mardinoglu","year":"2017","unstructured":"Mardinoglu A, Stan\u010d\u00e1kov\u00e1 A, Lotta LA, Kuusisto J, Boren J, Bl\u00fcher M, et al. Plasma Mannose Levels Are Associated with Incident Type 2 Diabetes and Cardiovascular Disease. Cell Metab. 2017;26(2):281\u20133. https:\/\/doi.org\/10.1016\/j.cmet.2017.07.006.","journal-title":"Cell Metab"},{"key":"1674_CR65","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.ijcard.2021.11.038","volume":"346","author":"E Ferrannini","year":"2022","unstructured":"Ferrannini E, Marx N, Andreini D, Campi B, Saba A, Gorini M, et al. Mannose as a biomarker of coronary artery disease: Angiographic evidence and clinical significance. Int J Cardiol. 2022;346:86\u201392. https:\/\/doi.org\/10.1016\/j.ijcard.2021.11.038.","journal-title":"Int J Cardiol"},{"issue":"1","key":"1674_CR66","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.cmet.2016.05.026","volume":"24","author":"S Lee","year":"2016","unstructured":"Lee S, Zhang C, Kilicarslan M, Piening BD, Bjornson E, Hallstr\u00f6m BM, et al. Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance. Cell Metab. 2016;24(1):172\u201384. https:\/\/doi.org\/10.1016\/j.cmet.2016.05.026.","journal-title":"Cell Metab"},{"issue":"12","key":"1674_CR67","doi-asserted-by":"publisher","first-page":"3087","DOI":"10.1016\/j.celrep.2018.08.064","volume":"24","author":"V Sharma","year":"2018","unstructured":"Sharma V, Smolin J, Nayak J, Ayala JE, Scott DA, Peterson SN, et al. Mannose Alters Gut Microbiome, Prevents Diet-Induced Obesity, and Improves Host Metabolism. Cell Rep. 2018;24(12):3087\u201398. https:\/\/doi.org\/10.1016\/j.celrep.2018.08.064.","journal-title":"Cell Rep"},{"issue":"9","key":"1674_CR68","doi-asserted-by":"publisher","first-page":"5423","DOI":"10.1128\/AEM.69.9.5423-5432.2003","volume":"69","author":"A Cochu","year":"2003","unstructured":"Cochu A, Vadeboncoeur C, Moineau S, Frenette M. Genetic and biochemical characterization of the phosphoenolpyruvate:glucose\/mannose phosphotransferase system of Streptococcus thermophilus. Appl Environ Microbiol. 2003;69(9):5423\u201332. https:\/\/doi.org\/10.1128\/AEM.69.9.5423-5432.2003.","journal-title":"Appl Environ Microbiol"}],"container-title":["Genome Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13073-026-01674-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13073-026-01674-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13073-026-01674-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T03:53:17Z","timestamp":1784087597000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13073-026-01674-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,22]]},"references-count":68,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1674"],"URL":"https:\/\/doi.org\/10.1186\/s13073-026-01674-2","relation":{},"ISSN":["1756-994X"],"issn-type":[{"value":"1756-994X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,22]]},"assertion":[{"value":"14 March 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 May 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Ethics approval was granted by the Medical Research Ethics Committee of West China Second Hospital Sichuan University (Protocol 2024\u2013174). Analyses on these de-identified, secondary data were approved by the Resource Access Board of West China Second Hospital.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"105"}}