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Blood-based obesity biomarkers and their relevance for disease risk

Nature Reviews Endocrinology (2026)Cite this article

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Abstract

Obesity is a risk factor for chronic diseases and early death; however, the underlying mechanisms are not fully understood. Whereas insulin resistance and inflammation are established pathways in several of these relationships, it is less clear how increases in body adipose tissue relate to these pathways and disease risk. Several adipose tissue-derived blood-based biomarkers have been identified as purported mediators, including adipokines, inflammatory cytokines and sex steroid hormones. Traditionally, these markers were discovered in animal models and their relevance in humans has then been investigated in epidemiological studies. Today, proteomics and metabolomics approaches in human observational studies are used to discover obesity biomarkers in blood, supported by Mendelian randomization studies to draw causal inferences. Here we review adipose tissue-derived blood-based obesity biomarkers and their relevance for disease risk, along with their potential role as mediators. Proteomics and metabolomics studies have partly re-identified traditional biomarkers, but more large-scale prospective analyses are needed to obtain evidence of the relevance of omics-based and traditional obesity biomarkers to disease.

Key points

  • Obesity biomarkers are quantitative measures in biological specimens causally affected by excess adipose tissue. Blood-based obesity biomarkers have the highest clinical relevance and include markers directly secreted by the adipose tissue (that is, adipokines, inflammatory cytokines and sex steroid hormones).

  • Traditional obesity biomarkers have been studied in human observational studies following their discovery in experimental settings. There is good evidence for a causal effect of obesity on circulating concentrations of leptin, fatty acid binding protein 4 (FABP4), IL-6 and, particularly in postmenopausal women, oestradiol.

  • Of the traditional obesity biomarkers, the most consistent evidence is available for circulating IL-6, which has a causal role in cardiovascular disease risk, and oestradiol, which is a risk factor for postmenopausal breast and endometrial cancer.

  • Over the past 10 years, targeted and untargeted proteomics and metabolomics studies have been conducted to identify novel obesity biomarkers.

  • In proteomics approaches, traditional obesity biomarkers such as leptin, FABP4 and IL-6 have been re-identified, along with novel proteins such as complement factor I and RAGE (receptor for advanced glycosylation end products), although their relevance for disease risk needs to be established.

  • In metabolomics studies, the most consistent associations have been found between obesity and altered concentrations of branched chain and aromatic amino acids, certain lipoproteins (such as HDL) and glucose. Several of these obesity-related metabolites, such as branched chain and aromatic amino acids, have also been related to diabetes mellitus risk.

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Fig. 1: Concept of Mendelian randomization in the context of obesity biomarkers.
Fig. 2: Evidence on obesity biomarkers originating from adipose tissue and chronic disease risk.

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References

  1. NCD Risk Factor Collaboration (NCD-RisC) Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet 403, 1027–1050 (2024).

    Article  Google Scholar 

  2. Speliotes, E. K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Sandovici, I., Morais, T., Constancia, M. & Monteiro, M. P. Epigenetic changes associated with obesity-related metabolic comorbidities. J. Endocr. Soc. 9, bvaf129 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Cuevas-Sierra, A., Ramos-Lopez, O., Riezu-Boj, J. I., Milagro, F. I. & Martinez, J. A. Diet, gut microbiota, and obesity: links with host genetics and epigenetics and potential applications. Adv. Nutr. 10, S17–S30 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Haslam, D. W. & James, W. P. Obesity. Lancet 366, 1197–1209 (2005).

    Article  PubMed  Google Scholar 

  6. Nimptsch, K. & Pischon, T. Body fatness, related biomarkers and cancer risk: an epidemiological perspective. Horm. Mol. Biol. Clin. Investig. 22, 39–51 (2015).

    Article  CAS  PubMed  Google Scholar 

  7. Larsson, S. C. & Burgess, S. Causal role of high body mass index in multiple chronic diseases: a systematic review and meta-analysis of Mendelian randomization studies. BMC Med. 19, 320 (2021). A comprehensive systematic review of the evidence from Mendelian randomization studies regarding the causal role of obesity for chronic disease risk.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Reaven, G. M. Banting Lecture 1988. Role of insulin resistance in human disease. Diabetes 37, 1595–1607 (1988).

    Article  CAS  PubMed  Google Scholar 

  9. Alberti, K. G. et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120, 1640–1645 (2009).

    Article  CAS  PubMed  Google Scholar 

  10. Eckel, R. H., Grundy, S. M. & Zimmet, P. Z. The metabolic syndrome. Lancet 365, 1415–1428 (2005).

    Article  CAS  PubMed  Google Scholar 

  11. Zhang, Y. et al. Positional cloning of the mouse obese gene and its human homologue. Nature 372, 425–432 (1994).

    Article  CAS  PubMed  Google Scholar 

  12. Friedman, J. M. Leptin and the endocrine control of energy balance. Nat. Metab. 1, 754–764 (2019).

    Article  CAS  PubMed  Google Scholar 

  13. Friedman, J. The long road to leptin. J. Clin. Invest. 126, 4727–4734 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Friedman, J. 20 years of leptin: leptin at 20: an overview. J. Endocrinol. 223, T1–T8 (2014).

    Article  CAS  PubMed  Google Scholar 

  15. Hotamisligil, G. S. Foundations of immunometabolism and implications for metabolic health and disease. Immunity 47, 406–420 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sethi, J. K. & Hotamisligil, G. S. Metabolic messengers: tumour necrosis factor. Nat. Metab. 3, 1302–1312 (2021).

    Article  CAS  PubMed  Google Scholar 

  17. Hotamisligil, G. S., Shargill, N. S. & Spiegelman, B. M. Adipose expression of tumor necrosis factor-α: direct role in obesity-linked insulin resistance. Science 259, 87–91 (1993).

    Article  CAS  PubMed  Google Scholar 

  18. Li, J., Papadopoulos, V. & Vihma, V. Steroid biosynthesis in adipose tissue. Steroids 103, 89–104 (2015).

    Article  CAS  PubMed  Google Scholar 

  19. Pischon, T. Use of obesity biomarkers in cardiovascular epidemiology. Dis. Markers 26, 247–263 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. [No authors listed] Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ. Tech. Rep. Ser. 894, 1–253 (2000).

    Google Scholar 

  21. [No authors listed] Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults — the evidence report. Obes. Res. 6, 51S–209S (1998).

    Google Scholar 

  22. Rubino, F. et al. Definition and diagnostic criteria of clinical obesity. Lancet Diabetes Endocrinol. 13, 221–262 (2025).

    Article  PubMed  Google Scholar 

  23. Pischon, T. BMI and mortality-time to revisit current recommendations for risk assessment. Am. J. Clin. Nutr. 113, 3–4 (2021).

    Article  PubMed  Google Scholar 

  24. Pischon, T. et al. General and abdominal adiposity and risk of death in Europe. N. Engl. J. Med. 359, 2105–2120 (2008).

    Article  CAS  PubMed  Google Scholar 

  25. Friedman, J. Fat in all the wrong places. Nature 415, 268–269 (2002).

    Article  CAS  PubMed  Google Scholar 

  26. Tilg, H., Ianiro, G., Gasbarrini, A. & Adolph, T. E. Adipokines: masterminds of metabolic inflammation. Nat. Rev. Immunol. 25, 250–265 (2025).

    Article  CAS  PubMed  Google Scholar 

  27. Quehenberger, O. & Dennis, E. A. The human plasma lipidome. N. Engl. J. Med. 365, 1812–1823 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Scherer, P. E., Williams, S., Fogliano, M., Baldini, G. & Lodish, H. F. A novel serum protein similar to C1q, produced exclusively in adipocytes. J. Biol. Chem. 270, 26746–26749 (1995).

    Article  CAS  PubMed  Google Scholar 

  29. Pischon, T. et al. Plasma adiponectin levels and risk of myocardial infarction in men. JAMA 291, 1730–1737 (2004).

    Article  CAS  PubMed  Google Scholar 

  30. Pai, J. K. et al. Inflammatory markers and the risk of coronary heart disease in men and women. N. Engl. J. Med. 351, 2599–2610 (2004).

    Article  CAS  PubMed  Google Scholar 

  31. Watanabe, K. et al. Multiomic signatures of body mass index identify heterogeneous health phenotypes and responses to a lifestyle intervention. Nat. Med. 29, 996–1008 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Cirulli, E. T. et al. Profound perturbation of the metabolome in obesity is associated with health risk. Cell Metab. 29, 488–500.e2 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lash, T. L., VanderWeele, T. J., Haneuse, S. & Rothman, K. J. Modern Epidemiology 4th edn (Wolters Kluwer, 2021).

  34. Wang, Z. & Yang, Q. The causal relationship between human blood metabolites and the risk of visceral obesity: a mendelian randomization analysis. Lipids Health Dis. 23, 39 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Davey Smith, G. & Hemani, G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum. Mol. Genet. 23, R89–R98 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pischon, T. & Nimptsch, K. Obesity and risk of cancer: an introductory overview. Recent Results Cancer Res. 208, 1–15 (2016).

    Article  CAS  PubMed  Google Scholar 

  37. Lauby-Secretan, B. et al. Body fatness and cancer — viewpoint of the IARC working group. N. Engl. J. Med. 375, 794–798 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Aleksandrova, K., Mozaffarian, D. & Pischon, T. Addressing the perfect storm: biomarkers in obesity and pathophysiology of cardiometabolic risk. Clin. Chem. 64, 142–153 (2018).

    Article  CAS  PubMed  Google Scholar 

  39. Tilg, H. & Moschen, A. R. Adipocytokines: mediators linking adipose tissue, inflammation and immunity. Nat. Rev. Immunol. 6, 772–783 (2006).

    Article  CAS  PubMed  Google Scholar 

  40. Gonzalez-Gil, E. M. et al. Association of body shape phenotypes and body fat distribution indexes with inflammatory biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank. BMC Med. 22, 334 (2024). An investigation of various anthropometric indices in relation to inflammatory biomarkers in the UK Biobank and EPIC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Nielsen, M. B. et al. Plasma adiponectin levels and risk of heart failure, atrial fibrillation, aortic valve stenosis, and myocardial infarction: large-scale observational and Mendelian randomization evidence. Cardiovasc. Res. 120, 95–107 (2024).

    Article  CAS  PubMed  Google Scholar 

  42. Nielsen, M. B., Colak, Y., Benn, M. & Nordestgaard, B. G. Causal relationship between plasma adiponectin and body mass index: one- and two-sample bidirectional mendelian randomization analyses in 460 397 individuals. Clin. Chem. 66, 1548–1557 (2020). A well-powered Mendelian randomization study clarifying the direction in the association of BMI and adiponectin.

    Article  PubMed  Google Scholar 

  43. Clontz, A. D., Gan, E., Hursting, S. D. & Bae-Jump, V. L. Effects of weight loss on key obesity-related biomarkers linked to the risk of endometrial cancer: a systematic review and meta-analysis. Cancers 16, 2197 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Bluher, M. et al. Two patterns of adipokine and other biomarker dynamics in a long-term weight loss intervention. Diabetes Care 35, 342–349 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Pajvani, U. B. et al. Structure-function studies of the adipocyte-secreted hormone Acrp30/adiponectin. Implications fpr metabolic regulation and bioactivity. J. Biol. Chem. 278, 9073–9085 (2003).

    Article  CAS  PubMed  Google Scholar 

  46. Pajvani, U. B. et al. Complex distribution, not absolute amount of adiponectin, correlates with thiazolidinedione-mediated improvement in insulin sensitivity. J. Biol. Chem. 279, 12152–12162 (2004).

    Article  CAS  PubMed  Google Scholar 

  47. Fisher, F. F. et al. Serum high molecular weight complex of adiponectin correlates better with glucose tolerance than total serum adiponectin in Indo-Asian males. Diabetologia 48, 1084–1087 (2005).

    Article  CAS  PubMed  Google Scholar 

  48. Pischon, T. et al. Plasma total and high molecular weight adiponectin levels and risk of coronary heart disease in women. Atherosclerosis 219, 322–329 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wang, Y. et al. Plasma adiponectin levels and type 2 diabetes risk: a nested case-control study in a Chinese population and an updated meta-analysis. Sci. Rep. 8, 406 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Zhang, M. et al. Causal associations of circulating adiponectin with cardiometabolic diseases and osteoporotic fracture. Sci. Rep. 12, 6689 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Schulze, M. B. et al. Adiponectin and future coronary heart disease events among men with type 2 diabetes. Diabetes 54, 534–539 (2005).

    Article  CAS  PubMed  Google Scholar 

  52. Cesari, M. et al. Low plasma adiponectin is associated with coronary artery disease but not with hypertension in high-risk nondiabetic patients. J. Intern. Med. 260, 474–483 (2006).

    Article  CAS  PubMed  Google Scholar 

  53. Frystyk, J. et al. Serum adiponectin is a predictor of coronary heart disease: a population-based 10-year follow-up study in elderly men. J. Clin. Endocrinol. Metab. 92, 571–576 (2007).

    Article  CAS  PubMed  Google Scholar 

  54. Arregui, M. et al. Adiponectin and risk of stroke: prospective study and meta-analysis. Stroke 45, 10–17 (2014).

    Article  CAS  PubMed  Google Scholar 

  55. Sook Lee, E. et al. Association between adiponectin levels and coronary heart disease and mortality: a systematic review and meta-analysis. Int. J. Epidemiol. 42, 1029–1039 (2013).

    Article  PubMed  Google Scholar 

  56. Wu, Z. J., Cheng, Y. J., Gu, W. J. & Aung, L. H. Adiponectin is associated with increased mortality in patients with already established cardiovascular disease: a systematic review and meta-analysis. Metabolism 63, 1157–1166 (2014).

    Article  CAS  PubMed  Google Scholar 

  57. Menzaghi, C. & Trischitta, V. The adiponectin paradox for all-cause and cardiovascular mortality. Diabetes 67, 12–22 (2018).

    Article  CAS  PubMed  Google Scholar 

  58. Pischon, T. Adiponectin: a biomarker of obesity? Curr. Cardiovasc. Risk Rep. 2, 150–155 (2008).

    Article  Google Scholar 

  59. Mukama, T., Johnson, T., Kaaks, R. & Katzke, V. A case-cohort study of the association between adiponectin and mortality in EPIC-Heidelberg: NT-proBNP may explain the adiponectin paradox. Nutr. Metab. Cardiovasc. Dis. 33, 853–863 (2023).

    Article  CAS  PubMed  Google Scholar 

  60. Vahed, I. E. et al. The role of adiponectin and leptin in colorectal cancer and adenoma: a systematic review and meta-analysis. BMC Cancer 25, 968 (2025).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Aleksandrova, K. et al. Total and high-molecular weight adiponectin and risk of colorectal cancer: the European Prospective Investigation into Cancer and Nutrition Study. Carcinogenesis 33, 1211–1218 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Song, M. et al. Plasma adiponectin and soluble leptin receptor and risk of colorectal cancer: a prospective study. Cancer Prev. Res. 6, 875–885 (2013).

    Article  CAS  Google Scholar 

  63. Xu, X. T. et al. Meta-analysis: circulating adiponectin levels and risk of colorectal cancer and adenoma. J. Dig. Dis. 12, 234–244 (2011).

    Article  CAS  PubMed  Google Scholar 

  64. Nimptsch, K. et al. Genetic variation in the ADIPOQ gene, adiponectin concentrations and risk of colorectal cancer: a Mendelian randomization analysis using data from three large cohort studies. Eur. J. Epidemiol. 32, 419–430 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Dimou, N. L. et al. Circulating adipokine concentrations and risk of five obesity-related cancers: a Mendelian randomization study. Int. J. Cancer 148, 1625–1636 (2021).

    Article  CAS  PubMed  Google Scholar 

  66. Engin, A. Diet-induced obesity and the mechanism of leptin resistance. Adv. Exp. Med. Biol. 960, 381–397 (2017).

    Article  CAS  PubMed  Google Scholar 

  67. Schaab, M. & Kratzsch, J. The soluble leptin receptor. Best. Pract. Res. Clin. Endocrinol. Metab. 29, 661–670 (2015).

    Article  CAS  PubMed  Google Scholar 

  68. Huang, L., Wang, Z. & Li, C. Modulation of circulating leptin levels by its soluble receptor. J. Biol. Chem. 276, 6343–6349 (2001).

    Article  CAS  PubMed  Google Scholar 

  69. Lammert, A., Kiess, W., Bottner, A., Glasow, A. & Kratzsch, J. Soluble leptin receptor represents the main leptin binding activity in human blood. Biochem. Biophys. Res. Commun. 283, 982–988 (2001).

    Article  CAS  PubMed  Google Scholar 

  70. Liu, C. et al. Expression and characterization of a putative high affinity human soluble leptin receptor. Endocrinology 138, 3548–3554 (1997).

    Article  CAS  PubMed  Google Scholar 

  71. Wabitsch, M. et al. Biologically inactive leptin and early-onset extreme obesity. N. Engl. J. Med. 372, 48–54 (2015).

    Article  PubMed  Google Scholar 

  72. Houseknecht, K. L. et al. Evidence for leptin binding to proteins in serum of rodents and humans: modulation with obesity. Diabetes 45, 1638–1643 (1996).

    Article  CAS  PubMed  Google Scholar 

  73. Konigorski, S. et al. Prediction of circulating adipokine levels based on body fat compartments and adipose tissue gene expression. Obesity Facts 12, 590–605 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Askarpour, M. et al. Effect of bariatric surgery on the circulating level of adiponectin, chemerin, plasminogen activator inhibitor-1, leptin, resistin, and visfatin: a systematic review and meta-analysis. Horm. Metab. Res. 52, 207–215 (2020).

    Article  CAS  PubMed  Google Scholar 

  75. Welsh, P. et al. Unraveling the directional link between adiposity and inflammation: a bidirectional Mendelian randomization approach. J. Clin. Endocrinol. Metab. 95, 93–99 (2010).

    Article  CAS  PubMed  Google Scholar 

  76. Folkersen, L. et al. Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals. Nat. Metab. 2, 1135–1148 (2020). A large scale proteomics study identifying protein quantitative trait loci and applying these in Mendelian randomization analyses for various anthropometric and chronic disease outcomes.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Yang, H. et al. Leptin concentration and risk of coronary heart disease and stroke: a systematic review and meta-analysis. PLoS ONE 12, e0166360 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Chen, G. C., Qin, L. Q. & Ye, J. K. Leptin levels and risk of type 2 diabetes: gender-specific meta-analysis. Obes. Rev. 15, 134–142 (2014).

    Article  CAS  PubMed  Google Scholar 

  79. Yoon, Y. S., Kwon, A. R., Lee, Y. K. & Oh, S. W. Circulating adipokines and risk of obesity related cancers: a systematic review and meta-analysis. Obes. Res. Clin. Pract. 13, 329–339 (2019).

    Article  PubMed  Google Scholar 

  80. Paz-Filho, G., Mastronardi, C. A. & Licinio, J. Leptin treatment: facts and expectations. Metabolism 64, 146–156 (2015).

    Article  CAS  PubMed  Google Scholar 

  81. Farooqi, I. S. et al. Effects of recombinant leptin therapy in a child with congenital leptin deficiency. N. Engl. J. Med. 341, 879–884 (1999).

    Article  CAS  PubMed  Google Scholar 

  82. Zhao, S. et al. Hyperleptinemia contributes to antipsychotic drug-associated obesity and metabolic disorders. Sci. Transl. Med. 15, eade8460 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Boord, J. B., Fazio, S. & Linton, M. F. Cytoplasmic fatty acid-binding proteins: emerging roles in metabolism and atherosclerosis. Curr. Opin. Lipidol. 13, 141–147 (2002).

    Article  CAS  PubMed  Google Scholar 

  84. Aleksandrova, K. et al. Fatty acid-binding protein 4 and risk of type 2 diabetes, myocardial infarction, and stroke: a prospective cohort study. J. Clin. Endocrinol. Metab. 104, 5991–6002 (2019).

    PubMed  Google Scholar 

  85. Nimptsch, K. et al. Prospective and Mendelian randomization analyses on the association of circulating fatty acid binding protein 4 (FABP-4) and risk of colorectal cancer. BMC Med. 21, 391 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Goudswaard, L. J. et al. Effects of adiposity on the human plasma proteome: observational and Mendelian randomisation estimates. Int. J. Obes. 45, 2221–2229 (2021).

    Article  CAS  Google Scholar 

  87. Witczak, J. K. et al. Bariatric surgery is accompanied by changes in extracellular vesicle-associated and plasma fatty acid binding protein 4. Obes. Surg. 28, 767–774 (2018).

    Article  PubMed  Google Scholar 

  88. Prentice, K. J., Saksi, J. & Hotamisligil, G. S. Adipokine FABP4 integrates energy stores and counterregulatory metabolic responses. J. Lipid Res. 60, 734–740 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Furuhashi, M. et al. Treatment of diabetes and atherosclerosis by inhibiting fatty-acid-binding protein aP2. Nature 447, 959–965 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Zhao, W. et al. Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease. Nat. Genet. 49, 1450–1457 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Hao, J. et al. Circulating adipose fatty acid binding protein is a new link underlying obesity-associated breast/mammary tumor development. Cell Metab. 28, 689–705.e5 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Yang, R. Z. et al. Identification of omentin as a novel depot-specific adipokine in human adipose tissue: possible role in modulating insulin action. Am. J. Physiol. Endocrinol. Metab. 290, E1253–E1261 (2006).

    Article  CAS  PubMed  Google Scholar 

  93. Zhao, A. et al. Omentin-1: a newly discovered warrior against metabolic related diseases. Expert Opin. Ther. Targets 26, 275–289 (2022).

    Article  CAS  PubMed  Google Scholar 

  94. Komiya, T., Tanigawa, Y. & Hirohashi, S. Cloning of the novel gene intelectin, which is expressed in intestinal Paneth cells in mice. Biochem. Biophys. Res. Commun. 251, 759–762 (1998).

    Article  CAS  PubMed  Google Scholar 

  95. Schaffler, A. et al. Genomic structure of human omentin, a new adipocytokine expressed in omental adipose tissue. Biochim. Biophys. Acta 1732, 96–102 (2005).

    Article  CAS  PubMed  Google Scholar 

  96. de Souza Batista, C. M. et al. Omentin plasma levels and gene expression are decreased in obesity. Diabetes 56, 1655–1661 (2007).

    Article  PubMed  Google Scholar 

  97. Arab, A., Moosavian, S. P., Hadi, A., Karimi, E. & Nasirian, M. The association between serum omentin level and bodyweight: a systematic review and meta-analysis of observational studies. Clin. Nutr. ESPEN 39, 22–29 (2020).

    Article  PubMed  Google Scholar 

  98. Lapointe, M. et al. Omentin changes following bariatric surgery and predictive links with biomarkers for risk of cardiovascular disease. Cardiovasc. Diabetol. 13, 124 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  99. de Luis, D., Izaola, O., Primo, D. & Aller, R. A randomized trial with two hypocaloric diets with different lipid profiles and effects on serum omentin-1 levels in obese subjects. Dis. Markers 2022, 6777283 (2022).

    PubMed  PubMed Central  Google Scholar 

  100. de Luis, D. A., Izaola, O., Primo, D. & Aller, R. Impact of 2 different hypocaloric diets on serum omentin levels in obese subjects. Ann. Nutr. Metab. 73, 138–144 (2018).

    Article  PubMed  Google Scholar 

  101. Nonnecke, E. B. et al. Characterization of an intelectin-1 (Itln1) knockout mouse model. Front. Immunol.l 13, 894649 (2022).

    Article  CAS  Google Scholar 

  102. Sena, C. M. Omentin: a key player in glucose homeostasis, atheroprotection, and anti-inflammatory potential for cardiovascular health in obesity and diabetes. Biomedicines 12, 284 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Pan, X., Kaminga, A. C., Wen, S. W., Acheampong, K. & Liu, A. Omentin-1 in diabetes mellitus: a systematic review and meta-analysis. PLoS ONE 14, e0226292 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. As Habi, A., Sadeghi, M., Arab, A. & Hajianfar, H. The association between omentin and diabetes: a systematic review and meta-analysis of observational studies. Diabetes Metab. Syndr. Obes. 12, 1277–1286 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Wittenbecher, C. et al. Omentin-1, adiponectin, and the risk of developing type 2 diabetes. Diabetes Care 39, e79–e80 (2016).

    Article  CAS  PubMed  Google Scholar 

  106. Menzel, J. et al. Omentin-1 and risk of myocardial infarction and stroke: results from the EPIC-Potsdam cohort study. Atherosclerosis 251, 415–421 (2016).

    Article  CAS  PubMed  Google Scholar 

  107. Menzel, J. et al. Association between chemerin, omentin-1 and risk of heart failure in the population-based EPIC-Potsdam study. Sci. Rep. 7, 14171 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  108. Saely, C. H. et al. High plasma omentin predicts cardiovascular events independently from the presence and extent of angiographically determined atherosclerosis. Atherosclerosis 244, 38–43 (2016).

    Article  CAS  PubMed  Google Scholar 

  109. Arjmand, M. H., Moradi, A., Akbari, A. & Mehrad-Majd, H. Clinical significance of circulating omentin levels in various malignant tumors: evidence from a systematic review and meta-analysis. Cytokine 125, 154869 (2020).

    Article  CAS  PubMed  Google Scholar 

  110. Aleksandrova, K. et al. Circulating omentin as a novel biomarker for colorectal cancer risk: data from the EPIC-Potsdam cohort study. Cancer Res. 76, 3862–3871 (2016).

    Article  CAS  PubMed  Google Scholar 

  111. Nagpal, S. et al. Tazarotene-induced gene 2 (TIG2), a novel retinoid-responsive gene in skin. J. Invest. Dermatol. 109, 91–95 (1997).

    Article  CAS  PubMed  Google Scholar 

  112. Roman, A. A., Parlee, S. D. & Sinal, C. J. Chemerin: a potential endocrine link between obesity and type 2 diabetes. Endocrine 42, 243–251 (2012).

    Article  CAS  PubMed  Google Scholar 

  113. Ernst, M. C. & Sinal, C. J. Chemerin: at the crossroads of inflammation and obesity. Trends Endocrinol. Metab. 21, 660–667 (2010).

    Article  CAS  PubMed  Google Scholar 

  114. Goralski, K. B. et al. Chemerin, a novel adipokine that regulates adipogenesis and adipocyte metabolism. J. Biol. Chem. 282, 28175–28188 (2007).

    Article  CAS  PubMed  Google Scholar 

  115. Bozaoglu, K. et al. Chemerin is a novel adipokine associated with obesity and metabolic syndrome. Endocrinology 148, 4687–4694 (2007).

    Article  CAS  PubMed  Google Scholar 

  116. Rourke, J. L., Dranse, H. J. & Sinal, C. J. Towards an integrative approach to understanding the role of chemerin in human health and disease. Obes. Rev. 14, 245–262 (2013).

    Article  CAS  PubMed  Google Scholar 

  117. Tan, L., Lu, X., Danser, A. H. J. & Verdonk, K. The role of chemerin in metabolic and cardiovascular disease: a literature review of its physiology and pathology from a nutritional perspective. Nutrients 15, 2878 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Li, Y., Shi, B. & Li, S. Association between serum chemerin concentrations and clinical indices in obesity or metabolic syndrome: a meta-analysis. PLoS ONE 9, e113915 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  119. Chakaroun, R. et al. Effects of weight loss and exercise on chemerin serum concentrations and adipose tissue expression in human obesity. Metabolism 61, 706–714 (2012).

    Article  CAS  PubMed  Google Scholar 

  120. Terra, X. et al. Long-term changes in leptin, chemerin and ghrelin levels following different bariatric surgery procedures: Roux-en-Y gastric bypass and sleeve gastrectomy. Obes. Surg. 23, 1790–1798 (2013).

    Article  PubMed  Google Scholar 

  121. Schmid, A., Roderfeld, M., Karrasch, T., Roeb, E. & Schaffler, A. Serum chemerin is decreased by Roux-en-Y gastric bypass and low calorie-formula diet in obese individuals. Biomedicines 12, 33 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  122. Siegrist, M. et al. Changes of omentin-1 and chemerin during 4 weeks of lifestyle intervention and 1 year follow-up in children with obesity. Clin. Nutr. 40, 5648–5654 (2021).

    Article  CAS  PubMed  Google Scholar 

  123. Zylla, S. et al. Serum chemerin is associated with inflammatory and metabolic parameters — results of a population-based study. Obesity 25, 468–475 (2017).

    Article  CAS  PubMed  Google Scholar 

  124. Eichelmann, F. et al. Chemerin as a biomarker linking inflammation and cardiovascular diseases. J. Am. Coll. Cardiol. 73, 378–379 (2019).

    Article  PubMed  Google Scholar 

  125. Eichelmann, F. et al. Association of chemerin plasma concentration with risk of colorectal cancer. JAMA Netw. Open 2, e190896 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  126. Noppes, K. et al. Association of plasma chemerin with all-cause and disease-specific mortality — results from a population-based study. Int. J. Obes. 47, 956–962 (2023).

    Article  CAS  Google Scholar 

  127. Chen, D. et al. Causal associations between circulating adipokines and cardiovascular disease: a mendelian randomization study. J. Clin. Endocrinol. Metab. 107, e2572–e2580 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  128. Romacho, T., Sanchez-Ferrer, C. F. & Peiro, C. Visfatin/Nampt: an adipokine with cardiovascular impact. Mediators Inflamm. 2013, 946427 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  129. Sommer, G. et al. Visfatin/PBEF/Nampt: structure, regulation and potential function of a novel adipokine. Clin. Sci. 115, 13–23 (2008).

    Article  CAS  Google Scholar 

  130. Semerena, E., Nencioni, A. & Masternak, K. Extracellular nicotinamide phosphoribosyltransferase: role in disease pathophysiology and as a biomarker. Front. Immunol. 14, 1268756 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Cybulska, A. M. et al. Predictive biomarkers for cardiometabolic risk in postmenopausal women: insights into visfatin, adropin, and adiponectin. Front. Endocrinol. 16, 1527567 (2025).

    Article  Google Scholar 

  132. Hernando-Redondo, J. et al. Mid- and long-term changes in satiety-related hormones, lipid and glucose metabolism, and inflammation after a Mediterranean diet intervention with the goal of losing weight: a randomized, clinical trial. Front. Nutr. 9, 950900 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Luhn, P. et al. Circulating adipokine levels and endometrial cancer risk in the prostate, lung, colorectal, and ovarian cancer screening trial. Cancer Epidemiol. Biomarkers Prev. 22, 1304–1312 (2013).

    Article  CAS  PubMed  Google Scholar 

  134. Steppan, C. M. et al. The hormone resistin links obesity to diabetes. Nature 409, 307–312 (2001).

    Article  CAS  PubMed  Google Scholar 

  135. Patel, L. et al. Resistin is expressed in human macrophages and directly regulated by PPARγ activators. Biochem. Biophys. Res. Commun. 300, 472–476 (2003).

    Article  CAS  PubMed  Google Scholar 

  136. Filkova, M., Haluzik, M., Gay, S. & Senolt, L. The role of resistin as a regulator of inflammation: implications for various human pathologies. Clin. Immunol. 133, 157–170 (2009).

    Article  CAS  PubMed  Google Scholar 

  137. Pham, T. T. et al. Pre-diagnostic circulating resistin concentrations are not associated with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition Study. Cancers 14, 5499 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Fontana, A. et al. Association between resistin levels and all-cause and cardiovascular mortality: a new study and a systematic review and meta-analysis. PLoS ONE 10, e0120419 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  139. Pham, T. T. et al. Genetically determined circulating resistin concentrations and risk of colorectal cancer: a two-sample Mendelian randomization study. J. Cancer Res. Clin. Oncol. 149, 14889–14900 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Ho, G. Y. et al. Adipokines linking obesity with colorectal cancer risk in postmenopausal women. Cancer Res. 72, 3029–3037 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Fain, J. N., Madan, A. K., Hiler, M. L., Cheema, P. & Bahouth, S. W. Comparison of the release of adipokines by adipose tissue, adipose tissue matrix, and adipocytes from visceral and subcutaneous abdominal adipose tissues of obese humans. Endocrinology 145, 2273–2282 (2004).

    Article  CAS  PubMed  Google Scholar 

  142. Hotamisligil, G. S. Inflammation and metabolic disorders. Nature 444, 860–867 (2006).

    Article  CAS  PubMed  Google Scholar 

  143. Libby, P. Inflammation in atherosclerosis. Nature 420, 868–874 (2002).

    Article  CAS  PubMed  Google Scholar 

  144. Lawler, P. R. et al. Targeting cardiovascular inflammation: next steps in clinical translation. Eur. Heart J. 42, 113–131 (2021).

    Article  CAS  PubMed  Google Scholar 

  145. Bulmer, C. & Avenell, A. The effect of dietary weight-loss interventions on the inflammatory markers interleukin-6 and TNF-alpha in adults with obesity: a systematic review and meta-analysis of randomized controlled clinical trials. Obes. Rev. 26, e13910 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Askarpour, M., Khani, D., Sheikhi, A., Ghaedi, E. & Alizadeh, S. Effect of bariatric surgery on serum inflammatory factors of obese patients: a systematic review and meta-analysis. Obes. Surg. 29, 2631–2647 (2019).

    Article  PubMed  Google Scholar 

  147. Emerging Risk Factors Collaboration C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis. Lancet 375, 132–140 (2010).

    Article  Google Scholar 

  148. Zhu, M. et al. C-reactive protein and cancer risk: a pan-cancer study of prospective cohort and Mendelian randomization analysis. BMC Med. 20, 301 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. C Reactive Protein Coronary Heart Disease Genetics Collaboration (CCGC) Association between C reactive protein and coronary heart disease: mendelian randomisation analysis based on individual participant data. BMJ 342, d548 (2011).

    Article  Google Scholar 

  150. Ridker, P. M. & Rane, M. Interleukin-6 signaling and anti-interleukin-6 therapeutics in cardiovascular disease. Circ. Res. 128, 1728–1746 (2021).

    Article  CAS  PubMed  Google Scholar 

  151. Kaptoge, S. et al. Inflammatory cytokines and risk of coronary heart disease: new prospective study and updated meta-analysis. Eur. Heart J. 35, 578–589 (2014).

    Article  CAS  PubMed  Google Scholar 

  152. Lukanova, A. et al. Body mass index, circulating levels of sex-steroid hormones, IGF-I and IGF-binding protein-3: a cross-sectional study in healthy women. Eur. J. Endocrinol. 150, 161–171 (2004).

    Article  CAS  PubMed  Google Scholar 

  153. Nimptsch, K. & Pischon, T. Obesity biomarkers, metabolism and risk of cancer: an epidemiological perspective. Recent Results Cancer Res. 208, 199–217 (2016).

    Article  CAS  PubMed  Google Scholar 

  154. Key, T. J. et al. Steroid hormone measurements from different types of assays in relation to body mass index and breast cancer risk in postmenopausal women: reanalysis of eighteen prospective studies. Steroids 99, 49–55 (2015).

    Article  CAS  PubMed  Google Scholar 

  155. Marriott, R. J. et al. Factors associated with circulating sex hormones in men: individual participant data meta-analyses. Ann. Intern. Med. 176, 1221–1234 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  156. Wan, B., Ma, N., Zhou, Z. & Lv, C. Putative causal inference for the relationship between obesity and sex hormones in males: a bidirectional mendelian randomization study. PeerJ 11, e15760 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  157. Campbell, K. L. et al. Reduced-calorie dietary weight loss, exercise, and sex hormones in postmenopausal women: randomized controlled trial. J. Clin. Oncol. 30, 2314–2326 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Emami, M. R. et al. Effect of bariatric surgery on endogenous sex hormones and sex hormone-binding globulin levels: a systematic review and meta-analysis. Surg. Obes. Relat. Dis. 17, 1621–1636 (2021).

    Article  PubMed  Google Scholar 

  159. Nounu, A., Kar, S. P., Relton, C. L. & Richmond, R. C. Sex steroid hormones and risk of breast cancer: a two-sample Mendelian randomization study. Breast Cancer Res. 24, 66 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Kaaks, R. et al. Postmenopausal serum androgens, oestrogens and breast cancer risk: the European Prospective Investigation into Cancer and Nutrition. Endocr. Relat. Cancer 12, 1071–1082 (2005).

    Article  CAS  PubMed  Google Scholar 

  161. Key, T., Appleby, P., Barnes, I. & Reeves, G. Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies. J. Natl Cancer Inst. 94, 606–616 (2002).

    Article  CAS  PubMed  Google Scholar 

  162. Allen, N. E. et al. Endogenous sex hormones and endometrial cancer risk in women in the European Prospective Investigation into Cancer and Nutrition (EPIC). Endocr. Relat. Cancer 15, 485–497 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Johansson, A. et al. Investigating the effect of estradiol levels on the risk of breast, endometrial, and ovarian cancer. J. Endocr. Soc. 6, bvac100 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  164. Dashti, S. G. et al. Adiposity and breast, endometrial, and colorectal cancer risk in postmenopausal women: quantification of the mediating effects of leptin, C-reactive protein, fasting insulin, and estradiol. Cancer Med. 11, 1145–1159 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Li, Z. et al. Association between testosterone and cancers risk in women: a two-sample Mendelian randomization study. Discov. Oncol. 14, 198 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  166. Brown, S. B. & Hankinson, S. E. Endogenous estrogens and the risk of breast, endometrial, and ovarian cancers. Steroids 99, 8–10 (2015).

    Article  CAS  PubMed  Google Scholar 

  167. Roddam, A. W., Allen, N. E., Appleby, P. & Key, T. J. Endogenous sex hormones and prostate cancer: a collaborative analysis of 18 prospective studies. J. Natl Cancer Inst. 100, 170–183 (2008).

    Article  CAS  PubMed  Google Scholar 

  168. Rodriguez-Munoz, A. et al. A systematic review of proteomics in obesity: unpacking the molecular puzzle. Curr. Obes. Rep. 13, 403–438 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  169. Cominetti, O. et al. Obesity shows preserved plasma proteome in large independent clinical cohorts. Sci. Rep. 8, 16981 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  170. Oller Moreno, S. et al. The differential plasma proteome of obese and overweight individuals undergoing a nutritional weight loss and maintenance intervention. Proteomics Clin. Appl. 12, 1600150 (2018).

    Article  Google Scholar 

  171. Zaghlool, S. B. et al. Revealing the role of the human blood plasma proteome in obesity using genetic drivers. Nat. Commun. 12, 1279 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Panova-Noeva, M. et al. Obesity-related inflammatory protein signature in cardiovascular clinical outcomes: results from the Gutenberg Health Study. Obesity 32, 1198–1209 (2024). Application of targeted proteomics identifying an obesity-related inflammation signature in a population-based cohort study and relating this signature to cardiovascular disease outcomes in a prospective cohort of individuals with all stages of heart failure.

    Article  CAS  PubMed  Google Scholar 

  173. Yaskolka Meir, A. et al. Individual response to lifestyle interventions: a pooled analysis of three long-term weight loss trials. Eur. J. Prev. Cardiol. 32, 1660–1670 (2025).

    Article  PubMed  Google Scholar 

  174. Li, X. et al. Distinct factors associated with short-term and long-term weight loss induced by low-fat or low-carbohydrate diet intervention. Cell Rep. Med. 3, 100870 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. Hinte, L. C. et al. Adipose tissue retains an epigenetic memory of obesity after weight loss. Nature 636, 457–465 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. Rooney, M. R. et al. Comparison of proteomic measurements across platforms in the Atherosclerosis Risk in Communities (ARIC) Study. Clin. Chem. 69, 68–79 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  177. Dumas, M. E. Metabolome 2.0: quantitative genetics and network biology of metabolic phenotypes. Mol. Biosyst. 8, 2494–2502 (2012).

    Article  CAS  PubMed  Google Scholar 

  178. Fux, E. et al. A global perspective on the status of clinical metabolomics in laboratory medicine — a survey by the IFCC Metabolomics Working Group. Clin. Chem. Lab. Med. 62, 1950–1961 (2024).

    Article  CAS  PubMed  Google Scholar 

  179. Wishart, D. S. et al. HMDB: the Human Metabolome Database. Nucleic Acids Res. 35, D521–D526 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Beger, R. D. et al. Metabolomics enables precision medicine: “A White Paper, Community Perspective”. Metabolomics 12, 149 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  181. Rangel-Huerta, O. D., Pastor-Villaescusa, B. & Gil, A. Are we close to defining a metabolomic signature of human obesity? A systematic review of metabolomics studies. Metabolomics 15, 93 (2019). A systematic review of metabolomics studies in relation to obesity.

    Article  PubMed  PubMed Central  Google Scholar 

  182. Payab, M. et al. Metabolomics prospect of obesity and metabolic syndrome; a systematic review. J. Diabetes Metab. Disord. 21, 889–917 (2022). A systematic review of metabolomics studies in relation to obesity.

    Article  PubMed  Google Scholar 

  183. Vaz, M., Pereira, S. S. & Monteiro, M. P. Metabolomic signatures after bariatric surgery — a systematic review. Rev. Endocr. Metab. Disord. 23, 503–519 (2022).

    Article  PubMed  Google Scholar 

  184. Elshorbagy, A. K., Smith, A. D., Kozich, V. & Refsum, H. Cysteine and obesity. Obesity 20, 473–481 (2012).

    Article  CAS  PubMed  Google Scholar 

  185. Elshorbagy, A. K., Kozich, V., Smith, A. D. & Refsum, H. Cysteine and obesity: consistency of the evidence across epidemiologic, animal and cellular studies. Curr. Opin. Clin. Nutr. Metab. Care 15, 49–57 (2012).

    CAS  PubMed  Google Scholar 

  186. Vanweert, F., Schrauwen, P. & Phielix, E. Role of branched-chain amino acid metabolism in the pathogenesis of obesity and type 2 diabetes-related metabolic disturbances BCAA metabolism in type 2 diabetes. Nutr. Diabetes 12, 35 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  187. Adams, S. H. Emerging perspectives on essential amino acid metabolism in obesity and the insulin-resistant state. Adv. Nutr. 2, 445–456 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Alves, A., Bassot, A., Bulteau, A. L., Pirola, L. & Morio, B. Glycine metabolism and its alterations in obesity and metabolic diseases. Nutrients 11, 1356 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  189. Varghese, A. et al. Unravelling cysteine-deficiency-associated rapid weight loss. Nature 643, 776–784 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  190. Quehenberger, O. et al. Lipidomics reveals a remarkable diversity of lipids in human plasma. J. Lipid Res. 51, 3299–3305 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  191. Visseren, F. L. J. et al. 2021 ESC guidelines on cardiovascular disease prevention in clinical practice. Eur. Heart J. 42, 3227–3337 (2021).

    Article  PubMed  Google Scholar 

  192. Arnett, D. K. et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 140, e596–e646 (2019).

    PubMed  PubMed Central  Google Scholar 

  193. Hasan, B. et al. Weight loss and serum lipids in overweight and obese adults: a systematic review and meta-analysis. J. Clin. Endocrinol. Metab. 105, dgaa673 (2020).

    Article  PubMed  Google Scholar 

  194. Pischon, T. et al. Habitual dietary intake of n-3 and n-6 fatty acids in relation to inflammatory markers among US men and women. Circulation 108, 155–160 (2003).

    Article  CAS  PubMed  Google Scholar 

  195. Pischon, T. et al. Inflammation, the metabolic syndrome, and risk of coronary heart disease in women and men. Atherosclerosis 197, 392–399 (2008).

    Article  CAS  PubMed  Google Scholar 

  196. Bachlechner, U. et al. Associations of anthropometric markers with serum metabolites using a targeted metabolomics approach: results of the EPIC-potsdam study. Nutr. Diabetes 6, e215 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  197. Carayol, M. et al. Blood metabolic signatures of body mass index: a targeted metabolomics study in the EPIC cohort. J. Proteome Res. 16, 3137–3146 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Hsu, Y. H. et al. Integrating untargeted metabolomics, genetically informed causal inference, and pathway enrichment to define the obesity metabolome. Int. J. Obes. 44, 1596–1606 (2020).

    Article  CAS  Google Scholar 

  199. Wurtz, P. et al. Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change. PLoS Med 11, e1001765 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  200. Morze, J. et al. Metabolomics and type 2 diabetes risk: an updated systematic review and eta-analysis of prospective cohort studies. Diabetes Care 45, 1013–1024 (2022). A comprehensive systematic review of metabolomics studies in relationship to type 2 diabetes mellitus.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  201. McGranaghan, P. et al. Predictive value of metabolomic biomarkers for cardiovascular disease risk: a systematic review and meta-analysis. Biomarkers 25, 101–111 (2020). A comprehensive systematic review of metabolomics studies in relation to cardiovascular disease.

    Article  PubMed  Google Scholar 

  202. Gold, A., Choueiry, F., Jin, N., Mo, X. & Zhu, J. The application of metabolomics in recent colorectal cancer studies: a state-of-the-art review. Cancers 14, 725 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  203. Erben, V., Bhardwaj, M., Schrotz-King, P. & Brenner, H. Metabolomics biomarkers for detection of colorectal neoplasms: a systematic review. Cancers 10, 246 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  204. Yang, L. et al. Application of metabolomics in the diagnosis of breast cancer: a systematic review. J. Cancer 11, 2540–2551 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  205. His, M., Gunter, M. J., Keski-Rahkonen, P. & Rinaldi, S. Application of metabolomics to epidemiologic studies of breast cancer: new perspectives for etiology and prevention. J. Clin. Oncol. 42, 103–115 (2024).

    Article  PubMed  Google Scholar 

  206. Breeur, M. et al. Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition. BMC Med. 20, 351 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  207. Harewood, R. et al. Association between pre-diagnostic circulating lipid metabolites and colorectal cancer risk: a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). EBioMedicine 101, 105024 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  208. Rothwell, J. A. et al. Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts. BMC Med. 21, 80 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  209. His, M. et al. Prospective analysis of circulating metabolites and breast cancer in EPIC. BMC Med. 17, 178 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  210. Grenville, Z. S. et al. Perturbations in the blood metabolome up to a decade before prostate cancer diagnosis in 4387 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition. Int. J. Cancer 156, 943–952 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  211. Dong, Q. et al. Metabolic signatures elucidate the effect of body mass index on type 2 diabetes. Metabolites 13, 227 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  212. Ali, M. K. et al. Obesity-associated metabolites in relation to type 2 diabetes risk: a prospective nested case-control study of the CARRS cohort. Diabetes Obes. Metab. 24, 2008–2016 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  213. Liang, X. et al. Abdominal obesity-related lipid metabolites may mediate the association between obesity and glucose dysregulation. Pediatr. Res. 93, 183–188 (2023).

    Article  CAS  PubMed  Google Scholar 

  214. Kliemann, N. et al. Metabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European Prospective Investigation into Cancer and Nutrition. BMC Med. 19, 101 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  215. Ridker, P. M. From RESCUE to ZEUS: will interleukin-6 inhibition with ziltivekimab prove effective for cardiovascular event reduction. Cardiovasc. Res. 117, e138–e140 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  216. Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 25, 44–56 (2019).

    Article  CAS  PubMed  Google Scholar 

  217. van Smeden, M., Reitsma, J. B., Riley, R. D., Collins, G. S. & Moons, K. G. Clinical prediction models: diagnosis versus prognosis. J. Clin. Epidemiol. 132, 142–145 (2021).

    Article  PubMed  Google Scholar 

  218. van Smeden, M. et al. Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease. Eur. Heart J. 43, 2921–2930 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  219. Moons, K. G. et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann. Intern. Med. 162, W1–W73 (2015).

    Article  PubMed  Google Scholar 

  220. Aleksandrova, K. et al. Leptin and soluble leptin receptor in risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition Cohort. Cancer Res. 72, 5328–5337 (2012).

    Article  CAS  PubMed  Google Scholar 

  221. van der Ark-Vonk, E. M., Puijk, M. V., Pasterkamp, G. & van der Laan, S. W. The effects of FABP4 on cardiovascular disease in the aging population. Curr. Atheroscler. Rep. 26, 163–175 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  222. Yuan, S. et al. Effects of tumour necrosis factor on cardiovascular disease and cancer: a two-sample Mendelian randomization study. EBioMedicine 59, 102956 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  223. Wei, T. et al. Circulating levels of cytokines and risk of cardiovascular disease: a Mendelian randomization study. Front. Immunol. 14, 1175421 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  224. Liu, C. et al. Adiponectin, TNF-α and inflammatory cytokines and risk of type 2 diabetes: a systematic review and meta-analysis. Cytokine 86, 100–109 (2016).

    Article  CAS  PubMed  Google Scholar 

  225. Zheng, H. T., Lou, M. W. C., Dugue, P. A. & Lynch, B. M. Circulating inflammatory markers and risk of endometrial cancer: a systematic review and meta-analysis. Cancer Epidemiol. 93, 102662 (2024).

    Article  PubMed  Google Scholar 

  226. Tian, G. et al. Circulating interleukin-6 and cancer: a meta-analysis using Mendelian randomization. Sci. Rep. 5, 11394 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  227. Holmegard, H. N., Nordestgaard, B. G., Jensen, G. B., Tybjaerg-Hansen, A. & Benn, M. Sex hormones and ischemic stroke: a prospective cohort study and meta-analyses. J. Clin. Endocrinol. Metab. 101, 69–78 (2016).

    Article  CAS  PubMed  Google Scholar 

  228. Chang, X., Liu, S. & Han, L. Mendelian randomization analysis to elucidate the causal relationship between small molecule metabolites and ovarian cancer risk. Front. Oncol. 13, 1291033 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  229. Ma, C., Tang, L., Yao, J. & Tan, G. Identifying proteins and amino acids associated with liver cancer risk: a study utilizing mendelian randomization and bulk RNA sequencing analysis. J. Pers. Med. 14, 262 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  230. Li, Z., Hao, J., Wang, T., Guo, C. & Liu, L. Branched-chain amino acids and risk of lung cancer: insights from mendelian randomization and NHANES III. J. Thorac. Dis. 16, 5248–5261 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  231. Yu, L. et al. Association between branched-chain amino acid levels and gastric cancer risk: large-scale prospective cohort study. Front. Nutr. 11, 1479800 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  232. Hisada, I. et al. Association of plasma branched-chain amino acid levels with colorectal cancer risk in a nested case-control study. Jpn J. Clin. Oncol. 55, 334–340 (2024).

    Article  Google Scholar 

  233. Li, Z. Y. et al. Prediagnostic plasma metabolite concentrations and liver cancer risk: a population-based study of Chinese men. EBioMedicine 100, 104990 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  234. Lecuyer, L. et al. NMR metabolomic profiles associated with long-term risk of prostate cancer. Metabolomics 17, 32 (2021).

    Article  CAS  PubMed  Google Scholar 

  235. Stolzenberg-Solomon, R. et al. Associations between metabolites and pancreatic cancer risk in a large prospective epidemiological study. Gut 69, 2008–2015 (2020).

    Article  CAS  PubMed  Google Scholar 

  236. Lecuyer, L. et al. NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer. Int. J. Epidemiol. 47, 484–494 (2018).

    Article  PubMed  Google Scholar 

  237. Yang, S. et al. Genetically predicted circulating concentrations of alanine and alanine aminotransferase were associated with prostate cancer risk. Clin. Epidemiol. 14, 1255–1264 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  238. Dossus, L. et al. Prospective analysis of circulating metabolites and endometrial cancer risk. Gynecol. Oncol. 162, 475–481 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  239. Page, J. H. et al. Plasma total cysteine and total homocysteine and risk of myocardial infarction in women: a prospective study. Am. Heart J. 159, 599–604 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  240. Lin, J. et al. Plasma homocysteine and cysteine and risk of breast cancer in women. Cancer Res. 70, 2397–2405 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  241. Miller, J. W. et al. Homocysteine, cysteine, and risk of incident colorectal cancer in the Women’s Health Initiative observational cohort. Am. J. Clin. Nutr. 97, 827–834 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  242. Yao, X. & Tian, Z. Dyslipidemia and colorectal cancer risk: a meta-analysis of prospective studies. Cancer Causes Control 26, 257–268 (2015).

    PubMed  Google Scholar 

  243. Markozannes, G. et al. Systematic review of mendelian randomization studies on risk of cancer. BMC Med. 20, 41 (2022). A comprehensive systematic review of Mendelian randomization studies relating to risk factors for cancer.

    Article  PubMed  PubMed Central  Google Scholar 

  244. Del Gobbo, L. C. et al. ω-3 Polyunsaturated fatty acid biomarkers and coronary heart disease: pooling project of 19 cohort studies. JAMA Intern. Med. 176, 1155–1166 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  245. Jiang, H. et al. Omega-3 polyunsaturated fatty acid biomarkers and risk of type 2 diabetes, cardiovascular disease, cancer, and mortality. Clin. Nutr. 41, 1798–1807 (2022).

    Article  CAS  PubMed  Google Scholar 

  246. Singh, G. M. et al. The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: a pooled analysis. PLoS ONE 8, e65174 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  247. Zheng, J., Gao, Y., Xie, S. H., Santoni, G. & Lagergren, J. Haemoglobin A1c and serum glucose levels and risk of gastric cancer: a systematic review and meta-analysis. Br. J. Cancer 126, 1100–1107 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  248. Liao, W. C. et al. Blood glucose concentration and risk of pancreatic cancer: systematic review and dose-response meta-analysis. BMJ 350, g7371 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  249. Shi, J. et al. A linear dose-response relationship between fasting plasma glucose and colorectal cancer risk: systematic review and meta-analysis. Sci. Rep. 5, 17591 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  250. Vojinovic, D. et al. Association of circulating metabolites in plasma or serum and risk of stroke: meta-analysis from 7 prospective cohorts. Neurology 96, e1110–e1123 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  251. Yun, Z. et al. Genetically predicted 486 blood metabolites in relation to risk of colorectal cancer: a Mendelian randomization study. Cancer Med. 12, 13784–13799 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  252. Matsushita, K. et al. The association of plasma lactate with incident cardiovascular outcomes: the ARIC study. Am. J. Epidemiol. 178, 401–409 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  253. Riboli, E. et al. European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr. 5, 1113–1124 (2002).

    Article  CAS  PubMed  Google Scholar 

  254. Riboli, E. The role of metabolic carcinogenesis in cancer causation and prevention: evidence from the European Prospective Investigation into Cancer and Nutrition. Cancer Treat. Res. 159, 3–20 (2014).

    Article  CAS  PubMed  Google Scholar 

  255. Lee, D. H., Keum, N. & Giovannucci, E. L. Colorectal cancer epidemiology in the Nurses’ Health Study. Am. J. Public Health 106, 1599–1607 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  256. Peters, A. et al. Framework and baseline examination of the German National Cohort (NAKO). Eur. J. Epidemiol. 37, 1107–1124 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Berlin, Germany

    Tobias Pischon & Katharina Nimptsch

  2. Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany

    Tobias Pischon

  3. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany

    Tobias Pischon

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Nature Reviews Endocrinology thanks Michael Stumvoll, who co-reviewed with Marleen Würfel, Gunnar Mellgren, who co-reviewed with Johan Fernø, Maria Dalamaga and Rexford Ahima for their contribution to the peer review of this work.

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Pischon, T., Nimptsch, K. Blood-based obesity biomarkers and their relevance for disease risk. Nat Rev Endocrinol (2026). https://doi.org/10.1038/s41574-025-01229-2

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