The Immunometabolic Network of Diabetes Mellitus: A Review of its Mechanisms, Complications and Therapeutic Implications
DOI:
https://doi.org/10.54987/jobimb.v14i1.821Keywords:
β-cell dysfunction, Diabetes mellitus, Metabolic memory, NLRP3 inflammasome, Oxidative stressAbstract
Diabetes mellitus is defined clinically by dysglycaemia but the initiation, progression and complications of diabetes are the result of reciprocal interactions between nutrient sensing, cellular stress and immune regulation. This narrative review summarizes the evidence for immunometabolic mechanisms linking insulin resistance, β-cell dysfunction and multi-organ injury. In type 1 diabetes, β-cell loss is largely driven by adaptive autoimmunity . Metabolic stress plays a role in modulating disease tempo, but this should not be confused with the initiating mechanism. In type 2 diabetes, reinforcing loops of adipose dysfunction, ectopic lipid deposition, altered insulin signaling, endoplasmic-reticulum stress, mitochondrial impairment and innate immune activation progressively erode insulin sensitivity and β-cell reserve. Activation of the NLRP3 inflammasome and interleukin-1 signaling are paradigms of molecular convergence of metabolic danger signals and inflammation. Persistent oxidative, epigenetic and inflammatory changes also contribute to metabolic memory. This helps explain why earlier glycemic exposure influences later vascular risk. Common processes—endothelial dysfunction, redox imbalance, mitochondrial injury and fibrotic signalling—are differentially expressed in the heart, kidney, retina, peripheral nerves and periodontal tissues. Since glucose, blood pressure, lipids, weight and cardiorenal risk are still actionable treatment anchors, clinical translation requires some restraint. In addition, most inflammatory and multi-omics biomarkers are still investigational. Thus, immunometabolic therapy is not a replacements but it should be an adjunct to established risk-factor management. Mechanism-informed intervention shows both promise and limitations, as demonstrated by stage-specific teplizumab in type 1 diabetes, incretin-based therapies, sodium-glucose cotransporter 2 inhibitors, and select anti-inflammatory trials.
References
1 Chung WK, Erion K, Florez JC, Hattersley AT, Hivert MF, Lee CG, et al. Precision medicine in diabetes: a consensus report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia. 2020;63:1671–1693. doi:10.1007/s00125-020-05181-w.
2 Davies MJ, Aroda VR, Collins BS, Gabbay RA, Green J, Maruthur NM, et al. Management of hyperglycaemia in type 2 diabetes, 2022: a consensus report by the ADA and the EASD. Diabetologia. 2022;65:1925–1966. doi:10.1007/s00125-022-05787-2.
3 Ahlqvist E, Storm P, Käräjämäki A, Martinell M, Dorkhan M, Carlsson A, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018;6:361–369. doi:10.1016/S2213-8587(17)30374-3.
4 Dennis JM, Shields BM, Henley WE, Jones AG, Hattersley AT. Disease progression and treatment response in data-driven subgroups of type 2 diabetes compared with models based on simple clinical features: an analysis using clinical trial data. Lancet Diabetes Endocrinol. 2019;7:442–451. doi:10.1016/S2213-8587(19)30087-7.
5 Zaharia OP, Strassburger K, Strom A, Bönhof GJ, Karusheva Y, Antoniou S, et al. Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study. Lancet Diabetes Endocrinol. 2019;7:684–694. doi:10.1016/S2213-8587(19)30187-1.
6 Atkinson MA, Eisenbarth GS, Michels AW. Type 1 diabetes. Lancet. 2014;383:69–82. doi:10.1016/S0140-6736(13)60591-7.
7 Insel RA, Dunne JL, Atkinson MA, Chiang JL, Dabelea D, Gottlieb PA, et al. Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care. 2015;38:1964–1974. doi:10.2337/dc15-1419.
8 Hotamisligil GS. Inflammation and metabolic disorders. Nature. 2006;444:860–867. doi:10.1038/nature05485.
9 Hattersley AT, Patel KA. Precision diabetes: learning from monogenic diabetes. Diabetologia. 2017;60:769–777. doi:10.1007/s00125-017-4226-2.
10 Pearson ER, Flechtner I, Njølstad PR, Malecki MT, Flanagan SE, Larkin B, et al. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med. 2006;355:467–477. doi:10.1056/NEJMoa061759.
11 Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, et al. A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab. 2009;9:311–326. doi:10.1016/j.cmet.2009.02.002.
12 Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, et al. Metabolite profiles and the risk of developing diabetes. Nat Med. 2011;17:448–453. doi:10.1038/nm.2307.
13 Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature. 2012;490:55–60. doi:10.1038/nature11450.
14 Marso SP, Daniels GH, Brown-Frandsen K, Kristensen P, Mann JFE, Nauck MA, et al. Liraglutide and cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2016;375:311–322. doi:10.1056/NEJMoa1603827.
15 Marso SP, Bain SC, Consoli A, Eliaschewitz FG, Jódar E, Leiter LA, et al. Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. N Engl J Med. 2016;375:1834–1844. doi:10.1056/NEJMoa1607141.
16 Gerstein HC, Colhoun HM, Dagenais GR, Diaz R, Lakshmanan M, Pais P, et al. Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): a double-blind, randomised placebo-controlled trial. Lancet. 2019;394:121–130. doi:10.1016/S0140-6736(19)31149-3.
17 Frías JP, Davies MJ, Rosenstock J, Pérez Manghi FC, Fernández Landó L, Bergman BK, et al. Tirzepatide versus semaglutide once weekly in patients with type 2 diabetes. N Engl J Med. 2021;385:503–515. doi:10.1056/NEJMoa2107519.
18 Jastreboff AM, Aronne LJ, Ahmad NN, Wharton S, Connery L, Alves B, et al. Tirzepatide once weekly for the treatment of obesity. N Engl J Med. 2022;387:205–216. doi:10.1056/NEJMoa2206038.
19 Herold KC, Bundy BN, Long SA, Bluestone JA, DiMeglio LA, Dufort MJ, et al. An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes. N Engl J Med. 2019;381:603–613. doi:10.1056/NEJMoa1902226.
20 Ridker PM, Everett BM, Thuren T, MacFadyen JG, Chang WH, Ballantyne C, et al. Antiinflammatory therapy with canakinumab for atherosclerotic disease. N Engl J Med. 2017;377:1119–1131. doi:10.1056/NEJMoa1707914.
21 Everett BM, Donath MY, Pradhan AD, Thuren T, Pais P, Nicolau JC, et al. Anti-inflammatory therapy with canakinumab for the prevention and management of diabetes. J Am Coll Cardiol. 2018;71:2392–2401. doi:10.1016/j.jacc.2018.03.002.
22 DeFronzo RA. From the triumvirate to the ominous octet: a new paradigm for the treatment of type 2 diabetes mellitus. Diabetes. 2009;58:773–795. doi:10.2337/db09-9028.
23 Kahn SE, Cooper ME, Del Prato S. Pathophysiology and treatment of type 2 diabetes: perspectives on the past, present, and future. Lancet. 2014;383:1068–1083. doi:10.1016/S0140-6736(13)62154-6.
24 Udler MS, Kim J, von Grotthuss M, Bonàs-Guarch S, Cole JB, Chiou J, et al. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: a soft clustering analysis. PLoS Med. 2018;15:e1002654. doi:10.1371/journal.pmed.1002654.
25 Wagner R, Heni M, Tabák AG, Machann J, Schick F, Randrianarisoa E, et al. Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes. Nat Med. 2021;27:49–57. doi:10.1038/s41591-020-1116-9.
26 Vujkovic M, Keaton JM, Lynch JA, Miller DR, Zhou J, Tcheandjieu C, et al. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat Genet. 2020;52:680–691. doi:10.1038/s41588-020-0637-y.
27 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;50:1505–1513. doi:10.1038/s41588-018-0241-6.
28 McCarthy MI. Painting a new picture of personalised medicine for diabetes. Diabetologia. 2017;60:793–799. doi:10.1007/s00125-017-4210-x.
29 Noble JA, Erlich HA. Genetics of type 1 diabetes. Cold Spring Harb Perspect Med. 2012;2:a007732. doi:10.1101/cshperspect.a007732.
30 Ziegler AG, Rewers M, Simell O, Simell T, Lempainen J, Steck A, et al. Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children. JAMA. 2013;309:2473–2479. doi:10.1001/jama.2013.6285.
31 Palmer JP, Fleming GA, Greenbaum CJ, Herold KC, Jansa LD, Kolb H, et al. C-peptide is the appropriate outcome measure for type 1 diabetes clinical trials to preserve beta-cell function. Diabetes. 2004;53:250–264. doi:10.2337/diabetes.53.1.250.
32 Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–419. doi:10.1007/BF00280883.
33 Samuel VT, Shulman GI. Mechanisms for insulin resistance: common threads and missing links. Cell. 2012;148:852–871. doi:10.1016/j.cell.2012.02.017.
34 Donath MY, Shoelson SE. Type 2 diabetes as an inflammatory disease. Nat Rev Immunol. 2011;11:98–107. doi:10.1038/nri2925.
35 Guasch-Ferré M, Hruby A, Toledo E, Clish CB, Martínez-González MA, Salas-Salvadó J, et al. Metabolomics in prediabetes and diabetes: a systematic review and meta-analysis. Diabetes Care. 2016;39:833–846. doi:10.2337/dc15-2251.
36 Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012;379:2279–2290. doi:10.1016/S0140-6736(12)60283-9.
37 Forslund K, Hildebrand F, Nielsen T, Falony G, Le Chatelier E, Sunagawa S, et al. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature. 2015;528:262–266. doi:10.1038/nature15766.
38 Torkamani A, Wineinger NE, Topol EJ. The personal and clinical utility of polygenic risk scores. Nat Rev Genet. 2018;19:581–590. doi:10.1038/s41576-018-0018-x.
39 Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD). Ann Intern Med. 2015;162:55–63. doi:10.7326/M14-0697.
40 Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170:51–58. doi:10.7326/M18-1376.
41 Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346:393–403. doi:10.1056/NEJMoa012512.
42 Look AHEAD Research Group. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med. 2013;369:145–154. doi:10.1056/NEJMoa1212914.
43 Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015;373:2117–2128. doi:10.1056/NEJMoa1504720.
44 Neal B, Perkovic V, Mahaffey KW, de Zeeuw D, Fulcher G, Erondu N, et al. Canagliflozin and cardiovascular and renal events in type 2 diabetes. N Engl J Med. 2017;377:644–657. doi:10.1056/NEJMoa1611925.
45 Perkovic V, Jardine MJ, Neal B, Bompoint S, Heerspink HJL, Charytan DM, et al. Canagliflozin and renal outcomes in type 2 diabetes and nephropathy. N Engl J Med. 2019;380:2295–2306. doi:10.1056/NEJMoa1811744.
46 Heerspink HJL, Stefánsson BV, Correa-Rotter R, Chertow GM, Greene T, Hou FF, et al. Dapagliflozin in patients with chronic kidney disease. N Engl J Med. 2020;383:1436–1446. doi:10.1056/NEJMoa2024816.
47 Wilding JPH, Batterham RL, Calanna S, Davies M, Van Gaal LF, Lingvay I, et al. Once-weekly semaglutide in adults with overweight or obesity. N Engl J Med. 2021;384:989–1002. doi:10.1056/NEJMoa2032183.
48 Rubino D, Abrahamsson N, Davies M, Hesse D, Greenway FL, Jensen C, et al. Effect of continued weekly subcutaneous semaglutide vs placebo on weight loss maintenance in adults with overweight or obesity. JAMA. 2021;325:1414–1425. doi:10.1001/jama.2021.3224.
49 Wadden TA, Chao AM, Machineni S, Kushner R, Ard J, Srivastava G, et al. Tirzepatide after intensive lifestyle intervention in adults with overweight or obesity: the SURMOUNT-3 phase 3 trial. Nat Med. 2023;29:2909–2918. doi:10.1038/s41591-023-02597-w.
50 Sattar N, Lee MMY, Kristensen SL, Branch KRH, Del Prato S, Khurmi NS, et al. Cardiovascular, mortality, and kidney outcomes with GLP-1 receptor agonists in patients with type 2 diabetes: a systematic review and meta-analysis of randomised trials. Lancet Diabetes Endocrinol. 2021;9:653–662. doi:10.1016/S2213-8587(21)00203-5.
51 Olamoyegun MA, Akinlade AT, Ala OA, Fawale MB, Akintan PE. A systematic review and meta-analysis of the prevalence and risk factors of type 2 diabetes mellitus in Nigeria. Clin Diabetes Endocrinol. 2024;10(1):43. doi:10.1186/s40842-024-00209-1.
52 NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in diabetes prevalence and treatment from 1990 to 2022: a pooled analysis of 1108 population-representative studies with 141 million participants. Lancet. 2024;404(10467):2077–2093. doi:10.1016/S0140-6736(24)02317-1.
53 World Health Organization Regional Office for Africa. World Diabetes Day 2025: message from the Regional Director for Africa. Brazzaville: WHO Regional Office for Africa; 2025. Available from: https://www.afro.who.int/regional-director/speeches-messages/world-diabetes-day-2025 [cited 2026 Sep 5].
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Fakhraddeen Yahya Muhammad, Ibrahim A. Abdulganiyyu, Jamil Dauda Usman, Salihu Ismail
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
