{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T05:29:31Z","timestamp":1777526971101,"version":"3.51.4"},"posted":{"date-parts":[[2026,4,25]]},"group-title":"Endocrinology (including Diabetes Mellitus and Metabolic Disease)","reference-count":40,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T00:00:00Z","timestamp":1777075200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.medrxiv.org\/about\/FAQ#license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,4,25]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:p>Type 2 diabetes (T2D) is a heterogeneous disease shaped by genetic pathways related to insulin resistance and \u03b2-cell dysfunction, but how this heterogeneity is reflected molecularly remains unclear. We integrated partitioned polygenic scores (pPS) with proteomic and metabolomic profiling to define molecular signatures of T2D and their clinical relevance.<\/jats:p>\n                <jats:p>We analyzed UK Biobank participants with genomic, proteomic, and metabolomic data. In a disease-free training subset, we used LASSO regression to identify multi-omic signatures associated with each pPS by jointly modeling proteins and metabolites. In an independent testing set, we constructed multi-omic scores and examined their associations with clinical traits and diabetes-related outcomes. Mediation analyses were used to investigate putative causal pathways. Key findings were evaluated in the Multi-Ethnic Study of Atherosclerosis (MESA).<\/jats:p>\n                <jats:p>We identified distinct multi-omic signatures that capture the molecular architecture of T2D genetic risk across physiological subtypes. Compared with genetic scores alone, multi-omic pPS showed larger effect sizes and better disease discrimination. These scores recapitulated subtype-specific physiology and were associated with T2D risk. The Beta-Cell 2 multi-omic score showed marked stratification for insulin use, which was replicated in MESA, where it also predicted future insulin use. Mediation analyses implicated lipoprotein remodeling and fatty acid metabolism in the Lipodystrophy 1 cluster, accounting for 30\u201345% of the total effect of pPS on T2D risk.<\/jats:p>\n                <jats:p>Integrating process-specific genetic risk with circulating multi-omic profiles reveals biologically distinct endotypes of T2D and supports a framework for improved patient stratification and risk assessment.<\/jats:p>","DOI":"10.64898\/2026.04.17.26351136","type":"posted-content","created":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T01:55:11Z","timestamp":1777168511000},"source":"Crossref","is-referenced-by-count":0,"title":["Multi-omic signatures of genetic mechanisms inform on type 2 diabetes biology and patient heterogeneity"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6135-9998","authenticated-orcid":false,"given":"Magdalena","family":"Sevilla-Gonz\u00e1lez","sequence":"first","affiliation":[{"name":"Clinical and Translational Epidemiology Unit. Mongan Institute. Massachusetts General Hospital. Boston, MA, 02114, USA"},{"name":"Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA"},{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alan Magno","family":"Mart\u00ednez-Mu\u00f1oz","sequence":"additional","affiliation":[{"name":"Clinical and Translational Epidemiology Unit. Mongan Institute. Massachusetts General Hospital. Boston, MA, 02114, USA"},{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul A.","family":"Hanson","sequence":"additional","affiliation":[{"name":"Clinical and Translational Epidemiology Unit. Mongan Institute. Massachusetts General Hospital. Boston, MA, 02114, USA"},{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah","family":"Hsu","sequence":"additional","affiliation":[{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingyang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Epidemiology. Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA"},{"name":"Department of Preventive Medicine. Brigham & Women\u2019s Hospital, Boston, MA, 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kirk","family":"Smith","sequence":"additional","affiliation":[{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zsu-Zsu","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lukasz","family":"Szczerbinski","sequence":"additional","affiliation":[{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Varinderpal","family":"Kaur","sequence":"additional","affiliation":[{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kent D.","family":"Taylor","sequence":"additional","affiliation":[{"name":"The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexis C.","family":"Wood","sequence":"additional","affiliation":[{"name":"USDA\/ARS Children\u2019s Nutrition Research Center, Baylor College of Medicine-Department of Pediatrics, Houston, Texas, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael Y.","family":"Mi","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Life Sciences, Food and Nutrition Science, SciLifeLab, Chalmers University of Technology, Gothenburg, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7792-877X","authenticated-orcid":false,"given":"Clemens","family":"Wittenbecher","sequence":"additional","affiliation":[{"name":"Department of Life Sciences, Food and Nutrition Science, SciLifeLab, Chalmers University of Technology, Gothenburg, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert E.","family":"Gerszten","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen S.","family":"Rich","sequence":"additional","affiliation":[{"name":"Department of Genome Sciences, University of Virginia School of Medicine, Charlottesville, VA, 22908, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jerome I.","family":"Rotter","sequence":"additional","affiliation":[{"name":"The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Epidemiology. Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA"},{"name":"Department of Preventive Medicine. Brigham & Women\u2019s Hospital, Boston, MA, 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8494-3660","authenticated-orcid":false,"given":"Josep M.","family":"Mercader","sequence":"additional","affiliation":[{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alisa K.","family":"Manning","sequence":"additional","affiliation":[{"name":"Clinical and Translational Epidemiology Unit. Mongan Institute. Massachusetts General Hospital. Boston, MA, 02114, USA"},{"name":"Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA"},{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ravi V.","family":"Shah","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Vanderbilt University Medical Center, Nashville, TN 37232, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miriam S.","family":"Udler","sequence":"additional","affiliation":[{"name":"Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA"},{"name":"Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2026042809301227000_2026.04.17.26351136v1.1","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S0140-6736(23)01301-6","article-title":"Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021","volume":"402","year":"2023","journal-title":"The Lancet"},{"key":"2026042809301227000_2026.04.17.26351136v1.2","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1016\/S2213-8587(25)00256-6","article-title":"Type 2 diabetes subtypes classification: a global reckoning with heterogeneity","volume":"13","year":"2025","journal-title":"Lancet Diabetes Endocrinol"},{"key":"2026042809301227000_2026.04.17.26351136v1.3","doi-asserted-by":"crossref","unstructured":"Udler, M. S. et al. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis. PLoS Med. 15, (2018).","DOI":"10.1371\/journal.pmed.1002654"},{"key":"2026042809301227000_2026.04.17.26351136v1.4","doi-asserted-by":"publisher","DOI":"10.1038\/S41591-024-02865-3"},{"key":"2026042809301227000_2026.04.17.26351136v1.5","doi-asserted-by":"crossref","first-page":"2569","DOI":"10.1038\/s41467-025-57452-y","article-title":"Heterogeneous effects of genetic variants and traits associated with fasting insulin on cardiometabolic outcomes","volume":"16","year":"2025","journal-title":"Nat. Commun"},{"key":"2026042809301227000_2026.04.17.26351136v1.6","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07019-6"},{"key":"2026042809301227000_2026.04.17.26351136v1.7","doi-asserted-by":"publisher","DOI":"10.1161\/circresaha.120.315898"},{"key":"2026042809301227000_2026.04.17.26351136v1.8","doi-asserted-by":"publisher","DOI":"10.2337\/dc21-1705"},{"key":"2026042809301227000_2026.04.17.26351136v1.9","doi-asserted-by":"crossref","unstructured":"Tobias, D. K. et al. Type 2 diabetes metabolomics score and risk of progression to type 2 diabetes among women with a history of gestational diabetes mellitus. Diabetes. Metab. Res. Rev. 40, (2024).","DOI":"10.1002\/dmrr.3763"},{"key":"2026042809301227000_2026.04.17.26351136v1.10","doi-asserted-by":"publisher","DOI":"10.1136\/bmjdrc-2022-003010"},{"key":"2026042809301227000_2026.04.17.26351136v1.11","first-page":"939","article-title":"Blood protein assessment of leading incident diseases and mortality in the UK Biobank. Nat","volume":"4","year":"2024","journal-title":"Aging"},{"key":"2026042809301227000_2026.04.17.26351136v1.12","doi-asserted-by":"crossref","unstructured":"Smith, A. , Elliott, P. , Mayr, M. , Dehghan, A. & Tzoulaki, I . Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank. Scientific Reports 2025 15:1 15, 20520- (2025).","DOI":"10.1038\/s41598-025-06232-1"},{"key":"2026042809301227000_2026.04.17.26351136v1.13","first-page":"1","article-title":"CEACAM1 induces B-cell survival and is essential for protective antiviral antibody production","volume":"6","year":"2015","journal-title":"Nature Communications"},{"key":"2026042809301227000_2026.04.17.26351136v1.14","doi-asserted-by":"publisher","DOI":"10.1016\/S0002-9343(99)00414-3"},{"key":"2026042809301227000_2026.04.17.26351136v1.15","doi-asserted-by":"publisher","DOI":"10.1016\/S0039-6109(02)00207-4"},{"key":"2026042809301227000_2026.04.17.26351136v1.16","doi-asserted-by":"crossref","unstructured":"Miranda, A. M. A. et al. Selective remodelling of the adipose niche in obesity and weight loss. Nature 2025 644:8077 644, 769\u2013779 (2025).","DOI":"10.1038\/s41586-025-09233-2"},{"key":"2026042809301227000_2026.04.17.26351136v1.17","doi-asserted-by":"crossref","first-page":"2568","DOI":"10.7150\/ijbs.97008","article-title":"Cgref1 is a CREB-H-regulated hepatokine that promotes hepatic de novo lipogenesis by mediating epididymal fat insulin resistance","volume":"21","year":"2025","journal-title":"Int. J. Biol. Sci"},{"key":"2026042809301227000_2026.04.17.26351136v1.18","doi-asserted-by":"publisher","DOI":"10.2337\/db18-0620"},{"key":"2026042809301227000_2026.04.17.26351136v1.19","doi-asserted-by":"crossref","first-page":"1133","DOI":"10.3390\/ijms22031133","article-title":"Potential Role of Insulin Growth-Factor-Binding Protein 2 as Therapeutic Target for Obesity-Related Insulin Resistance","volume":"22","year":"2021","journal-title":"Int. J. Mol. Sci"},{"key":"2026042809301227000_2026.04.17.26351136v1.20","doi-asserted-by":"publisher","DOI":"10.1016\/j.tem.2008.09.004"},{"key":"2026042809301227000_2026.04.17.26351136v1.21","doi-asserted-by":"publisher","DOI":"10.1210\/er.2007-0025"},{"key":"2026042809301227000_2026.04.17.26351136v1.22","doi-asserted-by":"crossref","first-page":"666","DOI":"10.2337\/db22-0628","article-title":"Plasma Proteomic Risk Markers of Incident Type 2 Diabetes Reflect Physiologically Distinct Components of Glucose-Insulin Homeostasis","volume":"72","year":"2023","journal-title":"Diabetes"},{"key":"2026042809301227000_2026.04.17.26351136v1.23","unstructured":"Khairnar, V. et al. CEACAM1 induces B-cell survival and is essential for protective antiviral antibody production. Nature Communications 2015 6:1 6, 6217- (2015)."},{"key":"2026042809301227000_2026.04.17.26351136v1.24","doi-asserted-by":"crossref","unstructured":"Loesch, D. P. et al. Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities. Nature Communications 2025 16:1 16, 2124-(2025).","DOI":"10.1038\/s41467-025-56695-z"},{"key":"2026042809301227000_2026.04.17.26351136v1.25","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.1038\/s42255-024-01133-5","article-title":"Mapping biological influences on the human plasma proteome beyond the genome","volume":"6","year":"2024","journal-title":"Nature Metabolism"},{"key":"2026042809301227000_2026.04.17.26351136v1.26","doi-asserted-by":"crossref","unstructured":"You, J. et al. Plasma proteomic profiles predict individual future health risk. Nature Communications 2023 14:1 14, 7817- (2023).","DOI":"10.1038\/s41467-023-43575-7"},{"key":"2026042809301227000_2026.04.17.26351136v1.27","doi-asserted-by":"crossref","unstructured":"Gupte, T. P. et al. Plasma proteomic signatures for type 2 diabetes and related traits in the UK Biobank cohort. Diabetes Res. Clin. Pract. 224, (2025).","DOI":"10.1016\/j.diabres.2025.112194"},{"key":"2026042809301227000_2026.04.17.26351136v1.28","doi-asserted-by":"publisher","DOI":"10.64898\/2026.01.15.26344187"},{"key":"2026042809301227000_2026.04.17.26351136v1.29","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.321.7258.405"},{"key":"2026042809301227000_2026.04.17.26351136v1.30","doi-asserted-by":"crossref","unstructured":"Sudlow, C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, (2015).","DOI":"10.1371\/journal.pmed.1001779"},{"key":"2026042809301227000_2026.04.17.26351136v1.31","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-018-0579-z"},{"key":"2026042809301227000_2026.04.17.26351136v1.32","doi-asserted-by":"crossref","unstructured":"Julkunen, H. et al. Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank. Nat. Commun. 14, (2023).","DOI":"10.1038\/s41467-023-36231-7"},{"key":"2026042809301227000_2026.04.17.26351136v1.33","doi-asserted-by":"publisher","DOI":"10.1038\/s41586023-06592-6"},{"key":"2026042809301227000_2026.04.17.26351136v1.34","doi-asserted-by":"publisher","DOI":"10.2337\/db16-1253"},{"key":"2026042809301227000_2026.04.17.26351136v1.35","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkw377"},{"key":"2026042809301227000_2026.04.17.26351136v1.36","doi-asserted-by":"publisher","DOI":"10.2337\/DC25-S002"},{"key":"2026042809301227000_2026.04.17.26351136v1.37","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMOA2102953\/SUPPL_FILE\/NEJMOA2102953_DISCLOSURES.PDF"},{"key":"2026042809301227000_2026.04.17.26351136v1.38","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjcard.2005.03.085"},{"key":"2026042809301227000_2026.04.17.26351136v1.39","doi-asserted-by":"crossref","first-page":"E20","DOI":"10.1097\/EDE.0000000000001378","article-title":"CMAverse: A Suite of Functions for Reproducible Causal Mediation Analyses","volume":"32","year":"2021","journal-title":"Epidemiology"},{"key":"2026042809301227000_2026.04.17.26351136v1.40","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwf113"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2026.04.17.26351136","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T16:31:31Z","timestamp":1777393891000},"score":1,"resource":{"primary":{"URL":"http:\/\/medrxiv.org\/lookup\/doi\/10.64898\/2026.04.17.26351136"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,25]]},"references-count":40,"URL":"https:\/\/doi.org\/10.64898\/2026.04.17.26351136","relation":{},"subject":[],"published":{"date-parts":[[2026,4,25]]},"subtype":"preprint"}}