Dietary Advanced Glycation End Products and Insulin Resistance: Comparison
Please note this is a comparison between Version 3 by Dean Liu and Version 2 by Dean Liu.

Insulin resistance (IR) is commonly observed during aging and is at the root of many of the chronic nontransmissible diseases experienced as people grow older. Many factors may play a role in causing IR, but diet is undoubtedly an important one. Whether it is total caloric intake or specific components of the diet, the factors responsible remain to be confirmed. Of the many dietary influences that may play a role in aging-related decreased insulin sensitivity, advanced glycation end products (AGEs) appear particularly important.

  • insulin resistance
  • glycation
  • oxidative stress
  • inflammation
  • HOMA-IR

1. Introduction

Insulin resistance (IR) is a pathophysiological condition in which organs—mostly skeletal muscle, adipose tissue, and liver—do not respond at an adequate rate to insulin, and it is considered to be a consequence of the disruption of different molecular pathways affected by insulin in these tissues [1]. In the general population, sensitivity to insulin-mediated glucose disposal in several tissues varies greatly [2]. The major consequence of IR, type 2 diabetes, arises when people who are insulin-resistant are unable to maintain the level of hyperinsulinemia required to correct the insulin action deficiency. Clinically, it appears as a defect in insulin-mediated glucose control in tissues, prominently in the above named muscle, fat and liver. Primary characteristics of IR are inhibited lipolysis in adipose tissue, impaired glucose uptake by muscle and inhibited gluconeogenesis in liver [3]. Therefore, IR also encompasses defects in lipid metabolism, in line with the multifaceted roles of insulin in metabolism regulation [4]. IR is one of the earliest manifestations of a constellation of human pathologic conditions that include metabolic syndrome, type 2 diabetes, cardiovascular diseases and aging [5]. Lifestyle modifications, including reduced intake of ultraprocessed foods containing advanced glycation (AGEs) and lipo-oxidation end products (ALEs), body weight loss and increased physical activity, have been shown to increase insulin sensitivity, thereby preventing IR [6][7].
Whether total caloric intake with body fat accretion or the presence of specific nutrients or diet-derived insulin-signaling disruptors is mostly responsible for the IR of aging is unclear [8]. Of the many dietary factors that may play a role in the aging-related lack of or decreased insulin sensitivity, AGEs appear potentially important. Recent clinical data suggest that food-derived AGEs may contribute to IR [9].

2. Evidence of an Association between Dietary AGEs and IR

2.1. Animal Data

A role of dietary AGEs as a causative agent in IR has been well documented in several studies in different mouse strains by independent teams. Researchers review some of these studies here and in Table 1. Reduced AGE intake leads to lower levels of circulating AGEs and to improved insulin sensitivity in the db/db mouse IR model [10]. To demonstrate this, db/db mice were randomly placed for 20 weeks (more than 50% of their usual life span) on a diet with either low AGE content (LAGE) or a 3.4-fold higher content of AGEs (HAGE). LAGE mice showed lower fasting plasma insulin levels and body weight compared with HAGE mice, despite equal caloric intake. LAGE mice had improved responses to both glucose (at 40 min, p = 0.003) and insulin (at 60 min, p = 0.007) tolerance tests, which correlated with a doubling of glucose uptake by adipose tissue. LAGE mice had twofold lower serum carboxymethyllysine (CML) and methylglyoxal (MG) concentrations and a better-preserved structure of pancreatic islets compared with HAGE mice [10]. Thus, the effect of dietary AGEs affects multiple tissues (liver, adipose tissue, pancreas), leading overall to impaired metabolism.
Table 1. Selected animal studies showing an association between dietary AGEs and IR.
Author, Reference Animal Model Study Design Intervention Findings
Hofmann [10] Db/Db mice (5 week old) Dietary intervention with random assignment into two parallel groups for 20 weeks (n = 20) High versus low AGE diets Lower body weight, lower serum AGEs, better response to both glucose and insulin tolerance tests and better preservation of pancreatic islets than with the high AGE diet
Sandu [11] C57/BL6 female mice (6 week old) Dietary intervention with random assignment into two parallel groups for 6 months High fat (35% fat) high AGE diet (HAGE-HF) versus High fat low AGE diet (LAGE-HF) None of the LAGE-HF mice became diabetic, while 75% of HAGE-HF did.
Cai [12] C57/BL6 Dietary intervention with random assignment into three parallel groups for 18 months Pair-fed three diets throughout life: (1) low AGE (MG) *, (2) MG supplemented low AGE chow (MG+) and regular chow (Reg) Older MG+ and Reg fed mice developed IR (higher fasting insulin levels and abnormal intraperitoneally glucose tolerance test) and dementia, which did not happen in MG mice.
32]. Since circulating AGE levels appear to be useful surrogates of dietary AGE exposure, their lack of change during the study raises the possibility that the dietary intervention might not have been effective. A second study also failed to show a relationship between dietary AGE restriction and changes in insulin sensitivity [30]. However, several key facts, mainly related to differences in the composition and methods to measure AGEs of the experimental diets, could help clarify the inconclusive outcome of the study in comparison with other studies. For example, mass-spectrometry-based AGE measurement may differ profoundly in the content of several bio-accessible AGE products assessed by immunological measurements such as ELISA. Moreover, in those studies showing a clear effect of dietary AGEs in IR, dietary AGEs were delivered mostly by ingestion of meats and animal products, highly processed and cooked at high temperatures, while in this negative study [30], most dietary AGEs came predominantly from cereals and were based on dietary frequency in a specific Dutch population [33]. Processing of samples before AGE measurement, particularly the inclusion or not of delipidation, may also be relevant, as AGE content in dietary lipids is important [34]. All these points emphasize that standardization is a key factor in designing dietary interventions. Of interest, individual factors, such as ethnicity and age, may also be relevant in interpreting insulin sensitivity tests [35][36]. Genotypic characteristics have been shown to influence interaction with dietary AGEs (for example, FADS2 (definer) polymorphisms) [37]. Lastly, intervention length is key in interpretating data employing methods with a high interindividual variation, such as the hyperglycemic–euglycemic clamp, which in the case of the cited negative study showed a 50% standard deviation over the mean values [30]. In fact, a prior randomized controlled trial employing isotope-based euglycemic clamps showed that insulin sensitivity changed only after a six-month intensive weight-loss and exercise program [6].

2.4. Clinical Trials with Mediterranean and Vegan Dietary Patterns Support the Association between Dietary AGEs and IR in Humans

The above studies (Table 2) show that—generally, although not universally—reducing dietary AGE intake can diminish IR markers. One of the limitations of these studies is that they are of short duration. A longer study, CORDIOPREV, indirectly evaluated the potential impact of dietary AGEs in IR [38]. Reduction in serum AGE levels in subjects following a Mediterranean diet as part of the CORDIOPREV study, lasting for 5 years, was shown to increase significantly the probability of type 2 diabetes remission, a hard measure of IR. All participants had previous cardiovascular events and type 2 diabetes when recruited [38]. In a cohort of overweight subjects (n = 244) randomly assigned to an intervention with a low-fat plant-based diet (n = 122) or a control diet (n = 122) for 16 weeks, dietary AGE consumption decreased on a low-fat plant-based diet, and this was associated with changes in body weight, body composition, and insulin sensitivity, independently of energy intake [39]. Therefore, the epidemiological data and most of the interventional studies in humans support a long-term reduction in dietary AGEs being associated with an improvement in clinically relevant outcomes (insulin sensitivity, weight loss, probability of type 2 diabetes remission) requiring minimal time for revealing its beneficial effects.
Table 2. Summary of selected clinical trials evaluating the effect of an AGE-restricted diet on insulin resistance.
Author, Year, Reference Study Design Intervention Number of Participants Randomized Participant Characteristics Duration and Allocation Specified Outcomes Findings
Birlouez, 2010 [64] Crossover High- and low-AGE diets 62 Yes Healthy individuals 1 month, France Changes in serum AGEs and HOMA Decreased serum AGEs and HOMA
Uribarri, 2011 [70] Parallel High- and low-AGE diets 18 Yes Patients with diabetes 3 months, USA Changes in serum AGEs, markers of OS and inflammation and HOMA Decreased levels of serum AGEs, markers of OS *, inflammation and HOMA
Luevano-Contreras 2013 [71] Parallel High- and low-AGE diets 26 Yes Patients with diabetes 1.5 months, Mexico Changes in serum AGEs, markers of OS and inflammation and HOMA Decreased markers of OS and inflammation, but no changes in serum AGEs or HOMA
Wang [13] C57/BL6 male mice (12 week old) Dietary intervention with random assignment into three parallel groups for 24 weeks Three parallel diets: (1) regular chow (n = 10), (2) regular chow + MG (n = 15) or (3) heat-treated chow (n = 15) IR (high fasting insulin, HOMA and abnormal intraperitoneal glucose tolerance test) developed in groups 2 and 3, but not 1. Microbiota was also altered in groups 2 and 3 (not in group 1) leading to loss of butyrate-producing bacteria
Mastrocola [14] Db/Db and C57/BL6 mice Dietary intervention followed by pharmacological intervention in the C57/BL6 mice C57/BL6 mice were randomly assigned to 4 groups for 12 weeks: (1) standard diet, (2) high fat diet (60%trans-fat), (3) standard diet + pyridoxamine for last 8 weeks, (4) high fat diet + pyridoxamine for last 8 weeks High levels of AGEs and RAGE and abnormal enzymes of sphingolipid metabolism were found in the liver of Db/Db and group 2 C57/BL6, but not in groups 1, 3 and C57/BL6
MG * = methylglyoxal.
To overcome a potential effect of the db/db genotype itself, another group focused on euglycemic mice. Nontransgenic C57/BL6 mice were randomly assigned to high-fat diets (35% g fat) to induce IR, with either high (HAGE-HF group; 995.4 units/mg AGE) or low (by 2.4-fold LAGE-HF group; 329.6 units/mg AGE) dietary AGE content for 6 months (approximately 20% of the usual life span) [11]. At the end of 6 months, 75% of the HAGE-HF mice had become diabetic, while none of the LAGE-HF mice had, despite a similar rise in body weight and plasma lipids. Moreover, the HAGE-HF group showed markedly impaired glucose and insulin responses during glucose tolerance tests and euglycemic and hyperglycemic clamps and abnormal pancreatic islet structure and function compared with those of LAGE-HF mice. These findings demonstrate that the development of IR and type 2 diabetes during prolonged high-fat feeding in mice are linked to the excess AGEs/ALEs in fatty diets [11]. In addition to type 2 diabetes, IR has been associated with cognitive dysfunctions, such as Alzheimer’s disease [15]. To determine whether dietary AGEs promote aging-related cognitive decline, mice were subjected to different levels of AGEs in their diets for 18 months (i.e., 60% of their life span) [12]. Those mice in the high-AGE diet developed metabolic syndrome (with IR), increased brain amyloid-β42, intracerebral deposits of AGEs, gliosis, and cognitive deficits, accompanied by suppressed expressions of SIRT1, nicotinamide phosphoribosyltransferase, AGE receptor 1, and PPARγ. These changes were not due to aging or caloric intake, as none of them were present in age-matched, pair-fed low-AGE mice. The animal data were strengthened by the demonstration of significant temporal correlations between high circulating AGEs, impaired cognition, and insulin sensitivity in elderly subjects [16]. Clinically, it has been postulated that IR could explain part of the age-related decrease in cognitive function [17][18]. Considering the importance of the microbiota in IR [19][20] (see above), yet another study showed that a high-AGE diet induced IR and altered the gut microbiota composition and structure, reducing its diversity in mice [13]. The authors postulated that the loss of butyrate-producing bacteria in the AGE-loaded animals might have impaired the colonic epithelial barrier, thereby triggering chronic low-grade inflammation and possibly IR [13]. An involvement of AGEs in general, not necessarily dietary AGEs, in the development of IR mediated by alteration of sphingolipid metabolism was demonstrated in two different models of IR in mice, one genetically diabetic and the other diet-induced IR (fed a 60% trans-fat diet). Supplementation of a group of mice with pyridoxamine that lowered AGE levels reduced the development of IR [14]. All in all, these independent studies highlight the potential role of dietary AGEs as modifiable agents in the development of IR in mice, acting on several factors (peripheral insulin function, microbiota, cellular stress responses).

2.2. Epidemiological Evidence Linking Dietary AGEs and IR in Humans

In a large cross-sectional study conducted in young healthy Slovakian individuals of both sexes (n = 2769) IR, assessed through the Quantitative Insulin Sensitivity Check Index (QUICKI), was associated with serum and urinary levels of some α-dicarbonyls (AGE precursors, such as methylglyoxal) and AGEs, independently of cardiometabolic risk markers and sex [21]. In an American cohort, an increased association of very high dietary AGE intake (defined as the top quartile) and metabolic syndrome was described in adolescents aged 12–19 years from NHANES (years 2003–2004 and 2005–2006) [22]. The latter study also demonstrated that very high dietary AGE intake was significantly associated with three of five criteria for metabolic syndrome: waist circumference, serum triglyceride, and HDL cholesterol levels [22]. A meta-analysis of 17 randomized controlled trials comprising 560 participants also demonstrated that IR, measured by HOMA-IR, was significantly reduced in a low-AGE compared to a high-AGE diet, although there was no significant difference in fasting insulin, 2 h insulin and insulin area under the curve results between both diets after an oral glucose tolerance test [23]. This apparent contradiction stresses the need for adequate standardization of the methods to define IR, as is discussed in detail later in this chapter [24].

2.3. Randomized Controlled Interventional Studies Testing the Association between Dietary AGEs and IR in Humans

Table 2 describes eight independent clinical trials [25][26][27][28][29][30][31][32] that have looked at the effects of an AGE-restricted diet on IR markers, comprising a total of more than 440 participants. Six of the studies demonstrated an association between decreased dietary AGE intake and improved insulin sensitivity. One study, in healthy subjects, indicated that a low-AGE diet led to decreased serum levels of AGEs in parallel with HOMA-IR [25]. Five other studies looked at the effect of a low-AGE diet on IR in overweight and/or metabolic syndrome subjects. In four of these studies, the low-AGE diet was associated with lower serum or urinary levels of AGEs, as well as parallel decreases in IR as assessed by HOMA-IR in three of them [26][28][29] or improved glucose uptake assessed by euglycemic clamp in the fourth study [27]. One of the studies was a randomized 6-week prospective intervention in type 2 diabetes subjects with a standard diet (n = 13) versus low-AGE diet (n = 13), which showed a significant decrease in TNF-α and malondialdehyde levels in the low-AGE diet group, but without a significant change in HOMA-IR or serum AGEs [
Mark, 2014 [
65
] Parallel High- and low-AGE diets 74 Yes Overweight women 1 month, Denmark Changes in urinary AGEs and HOMA Decreased urinary AGEs and HOMA
De courten 2016 [66] Crossover High- and low-AGE diets 20 Yes Overweight individuals 0.5 months, Denmark Changes in serum AGEs and insulin resistance (hyperinsulinemic–euglycemic clamp and intravenous glucose tolerance test) Decreased serum AGEs and insulin resistance
Vlassara, 2016 [67] Parallel High- and low-AGE diets 138 Yes Patients with metabolic syndrome 12 months, USA Changes in serum AGEs, markers of OS and inflammation and HOMA Decreased levels of serum AGEs, markers of OS, inflammation and HOMA
Goudarzi 2020 [68] Parallel High- and low-AGE diets 40 Yes Patients with metabolic syndrome 2 months, Iran Changes in serum AGEs, markers of OS and inflammation and HOMA Decreased serum AGEs, markers of OS, inflammation, HOMA and weight (were also calorie restricted)
Linkens 2022 [69] Parallel High- and low-AGE diets 82 Yes Patients with obesity 1.5 months, Netherlands Changes in serum AGEs, markers of OS and inflammation and insulin resistance (hyperinsulinemic–euglycemic and hyperglycemic clamp) Decreased circulating AGEs but not markers of OS/inflammation or insulin sensitivity
OS * Oxidative stress.

References

  1. Li, M.; Chi, X.; Wang, Y.; Setrerrahmane, S.; Xie, W.; Xu, H. Trends in insulin resistance: Insights into mechanisms and therapeutic strategy. Signal Transduct. Target. Ther. 2022, 7, 216.
  2. Yeni-Komshian, H.; Carantoni, M.; Abbasi, F.; Reaven, G.M. Relationship between several surrogate estimates of insulin resistance and quantification of insulin-mediated glucose disposal in 490 healthy nondiabetic volunteers. Diabetes Care 2000, 23, 171–175.
  3. Wilcox, G. Insulin and insulin resistance. Clin. Biochem. Rev. 2005, 26, 19–39.
  4. Gastaldelli, A. Measuring and estimating insulin resistance in clinical and research settings. Obesity 2022, 30, 1549–1563.
  5. Costantino, S.; Paneni, F.; Cosentino, F. Ageing, metabolism and cardiovascular disease. J. Physiol. 2016, 594, 2061–2073.
  6. Brennan, A.M.; Standley, R.A.; Anthony, S.J.; Grench, K.E.; Helbling, N.L.; DeLany, J.P.; Cornnell, H.H.; Yi, F.; Stefanovic-Racic, M.; Toledo, F.G.S.; et al. Weight Loss and Exercise Differentially Affect Insulin Sensitivity, Body Composition, Cardiorespiratory Fitness, and Muscle Strength in Older Adults With Obesity: A Randomized Controlled Trial. J. Gerontol. A Biol. Sci. Med. Sci. 2022, 77, 1088–1097.
  7. Castro-Barquero, S.; Ruiz-León, A.M.; Sierra-Pérez, M.; Estruch, R.; Casas, R. Dietary Strategies for Metabolic Syndrome: A Comprehensive Review. Nutrients 2020, 12, 2983.
  8. Lutsey, P.L.; Steffen, L.M.; Stevens, J. Dietary intake and the development of the metabolic syndrome: The Atherosclerosis Risk in Communities study. Circulation 2008, 117, 754–761.
  9. Ottum, M.S.; Mistry, A.M. Advanced glycation end-products: Modifiable environmental factors profoundly mediate insulin resistance. J. Clin. Biochem. Nutr. 2015, 57, 1–12.
  10. Hofmann, S.M.; Dong, H.J.; Li, Z.; Cai, W.; Altomonte, J.; Thung, S.N.; Zeng, F.; Fisher, E.A.; Vlassara, H. Improved insulin sensitivity is associated with restricted intake of dietary glycoxidation products in the db/db mouse. Diabetes 2002, 51, 2082–2089.
  11. Sandu, O.; Song, K.; Cai, W.; Zheng, F.; Uribarri, J.; Vlassara, H. Insulin resistance and type 2 diabetes in high-fat-fed mice are linked to high glycotoxin intake. Diabetes 2005, 54, 2314–2319.
  12. Cai, W.; Uribarri, J.; Zhu, L.; Chen, X.; Swamy, S.; Zhao, Z.; Grosjean, F.; Simonaro, C.; Kuchel, G.A.; Schnaider-Beeri, M.; et al. Oral glycotoxins are a modifiable cause of dementia and the metabolic syndrome in mice and humans. Proc. Natl. Acad. Sci. USA 2014, 111, 4940–4945.
  13. Wang, J.; Cai, W.; Yu, J.; Liu, H.; He, S.; Zhu, L.; Xu, J. Dietary Advanced Glycation End Products Shift the Gut Microbiota Composition and Induce Insulin Resistance in Mice. Diabetes Metab. Syndr. Obes. Targets Ther. 2022, 15, 427–437.
  14. Mastrocola, R.; Dal Bello, F.; Cento, A.S.; Gaens, K.; Collotta, D.; Aragno, M.; Medana, C.; Collino, M.; Wouters, K.; Schalkwijk, C.G. Altered hepatic sphingolipid metabolism in insulin resistant mice: Role of advanced glycation endproducts. Free Radic. Biol. Med. 2021, 169, 425–435.
  15. Pillai, J.A.; Bena, J.; Bekris, L.; Kodur, N.; Kasumov, T.; Leverenz, J.B.; Kashyap, S.R. Metabolic syndrome biomarkers relate to rate of cognitive decline in MCI and dementia stages of Alzheimer’s disease. Alzheimer’s Res. Ther. 2023, 15, 54.
  16. Beeri, M.S.; Moshier, E.; Schmeidler, J.; Godbold, J.; Uribarri, J.; Reddy, S.; Sano, M.; Grossman, H.T.; Cai, W.; Vlassara, H.; et al. Serum concentration of an inflammatory glycotoxin, methylglyoxal, is associated with increased cognitive decline in elderly individuals. Mech. Ageing Dev. 2011, 132, 583–587.
  17. Arnold, S.E.; Arvanitakis, Z.; Macauley-Rambach, S.L.; Koenig, A.M.; Wang, H.Y.; Ahima, R.S.; Craft, S.; Gandy, S.; Buettner, C.; Stoeckel, L.E.; et al. Brain insulin resistance in type 2 diabetes and Alzheimer disease: Concepts and conundrums. Nat. Rev. Neurol. 2018, 14, 168–181.
  18. Chow, H.M.; Shi, M.; Cheng, A.; Gao, Y.; Chen, G.; Song, X.; So, R.W.L.; Zhang, J.; Herrup, K. Age-related hyperinsulinemia leads to insulin resistance in neurons and cell-cycle-induced senescence. Nat. Neurosci. 2019, 22, 1806–1819.
  19. Cani, P.D.; Amar, J.; Iglesias, M.A.; Poggi, M.; Knauf, C.; Bastelica, D.; Neyrinck, A.M.; Fava, F.; Tuohy, K.M.; Chabo, C.; et al. Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes 2007, 56, 1761–1772.
  20. Kootte, R.S.; Levin, E.; Salojärvi, J.; Smits, L.P.; Hartstra, A.V.; Udayappan, S.D.; Hermes, G.; Bouter, K.E.; Koopen, A.M.; Holst, J.J.; et al. Improvement of Insulin Sensitivity after Lean Donor Feces in Metabolic Syndrome Is Driven by Baseline Intestinal Microbiota Composition. Cell Metab. 2017, 26, 611–619.e616.
  21. Csongová, M.; Scheijen, J.; van de Waarenburg, M.P.H.; Gurecká, R.; Koborová, I.; Tábi, T.; Szökö, É.; Schalkwijk, C.G.; Šebeková, K. Association of α-Dicarbonyls and Advanced Glycation End Products with Insulin Resistance in Non-Diabetic Young Subjects: A Case-Control Study. Nutrients 2022, 14, 4929.
  22. Saha, A.; Poojary, P.; Chan, L.; Chauhan, K.; Nadkarni, G.; Coca, S.; Uribarri, J. Increased odds of metabolic syndrome with consumption of high dietary advanced glycation end products in adolescents. Diabetes Metab. 2017, 43, 469–471.
  23. Baye, E.; Kiriakova, V.; Uribarri, J.; Moran, L.J.; de Courten, B. Consumption of diets with low advanced glycation end products improves cardiometabolic parameters: Meta-analysis of randomised controlled trials. Sci. Rep. 2017, 7, 2266.
  24. Sharma, V.R.; Matta, S.T.; Haymond, M.W.; Chung, S.T. Measuring Insulin Resistance in Humans. Horm. Res. Paediatr. 2020, 93, 577–588.
  25. Birlouez-Aragon, I.; Saavedra, G.; Tessier, F.J.; Galinier, A.; Ait-Ameur, L.; Lacoste, F.; Niamba, C.N.; Alt, N.; Somoza, V.; Lecerf, J.M. A diet based on high-heat-treated foods promotes risk factors for diabetes mellitus and cardiovascular diseases. Am. J. Clin. Nutr. 2010, 91, 1220–1226.
  26. Mark, A.B.; Poulsen, M.W.; Andersen, S.; Andersen, J.M.; Bak, M.J.; Ritz, C.; Holst, J.J.; Nielsen, J.; de Courten, B.; Dragsted, L.O.; et al. Consumption of a diet low in advanced glycation end products for 4 weeks improves insulin sensitivity in overweight women. Diabetes Care 2014, 37, 88–95.
  27. de Courten, B.; de Courten, M.P.; Soldatos, G.; Dougherty, S.L.; Straznicky, N.; Schlaich, M.; Sourris, K.C.; Chand, V.; Scheijen, J.L.; Kingwell, B.A.; et al. Diet low in advanced glycation end products increases insulin sensitivity in healthy overweight individuals: A double-blind, randomized, crossover trial. Am. J. Clin. Nutr. 2016, 103, 1426–1433.
  28. Vlassara, H.; Cai, W.; Tripp, E.; Pyzik, R.; Yee, K.; Goldberg, L.; Tansman, L.; Chen, X.; Mani, V.; Fayad, Z.A.; et al. Oral AGE restriction ameliorates insulin resistance in obese individuals with the metabolic syndrome: A randomised controlled trial. Diabetologia 2016, 59, 2181–2192.
  29. Goudarzi, R.; Sedaghat, M.; Hedayati, M.; Hekmatdoost, A.; Sohrab, G. Low advanced Glycation end product diet improves the central obesity, insulin resistance and inflammatory profiles in Iranian patients with metabolic syndrome: A randomized clinical trial. J. Diabetes Metab. Disord. 2020, 19, 1129–1138.
  30. Linkens, A.M.; Houben, A.J.; Niessen, P.M.; Wijckmans, N.E.; de Goei, E.E.; Van den Eynde, M.D.; Scheijen, J.L.; van den Waarenburg, M.P.; Mari, A.; Berendschot, T.T.; et al. A 4-week high-AGE diet does not impair glucose metabolism and vascular function in obese individuals. JCI Insight 2022, 7, e156950.
  31. Uribarri, J.; Cai, W.; Ramdas, M.; Goodman, S.; Pyzik, R.; Chen, X.; Zhu, L.; Striker, G.E.; Vlassara, H. Restriction of advanced glycation end products improves insulin resistance in human type 2 diabetes: Potential role of AGER1 and SIRT1. Diabetes Care 2011, 34, 1610–1616.
  32. Luévano-Contreras, C.; Garay-Sevilla, M.E.; Wrobel, K.; Malacara, J.M.; Wrobel, K. Dietary advanced glycation end products restriction diminishes inflammation markers and oxidative stress in patients with type 2 diabetes mellitus. J. Clin. Biochem. Nutr. 2013, 52, 22–26.
  33. Scheijen, J.; Clevers, E.; Engelen, L.; Dagnelie, P.C.; Brouns, F.; Stehouwer, C.D.A.; Schalkwijk, C.G. Analysis of advanced glycation endproducts in selected food items by ultra-performance liquid chromatography tandem mass spectrometry: Presentation of a dietary AGE database. Food Chem. 2016, 190, 1145–1150.
  34. Kodate, A.; Otoki, Y.; Shimizu, N.; Ito, J.; Kato, S.; Umetsu, N.; Miyazawa, T.; Nakagawa, K. Development of quantitation method for glycated aminophospholipids at the molecular species level in powdered milk and powdered buttermilk. Sci. Rep. 2018, 8, 8729.
  35. Chiu, K.C.; Cohan, P.; Lee, N.P.; Chuang, L.M. Insulin sensitivity differs among ethnic groups with a compensatory response in beta-cell function. Diabetes Care 2000, 23, 1353–1358.
  36. Herpich, C.; Kochlik, B.; Weber, D.; Ott, C.; Grune, T.; Norman, K.; Raupbach, J. Fasting Concentrations and Postprandial Response of 1,2-Dicarbonyl Compounds 3-Deoxyglucosone, Glyoxal, and Methylglyoxal Are Not Increased in Healthy Older Adults. J. Gerontol. A Biol. Sci. Med. Sci. 2022, 77, 934–940.
  37. Mahmoudinezhad, M.; Farhangi, M.A.; Kahroba, H.; Dehghan, P. Personalized diet study of dietary advanced glycation end products (AGEs) and fatty acid desaturase 2 (FADS(2)) genotypes in obesity. Sci. Rep. 2021, 11, 19725.
  38. Gutierrez-Mariscal, F.M.; Cardelo, M.P.; de la Cruz, S.; Alcala-Diaz, J.F.; Roncero-Ramos, I.; Guler, I.; Vals-Delgado, C.; López-Moreno, A.; Luque, R.M.; Delgado-Lista, J.; et al. Reduction in Circulating Advanced Glycation End Products by Mediterranean Diet Is Associated with Increased Likelihood of Type 2 Diabetes Remission in Patients with Coronary Heart Disease: From the Cordioprev Study. Mol. Nutr. Food Res. 2021, 65, e1901290.
  39. Kahleova, H.; Znayenko-Miller, T.; Uribarri, J.; Holubkov, R.; Branard, N.D. Dietary advanced glycation products and their associations with insulin sensitivity and body weight: A 16-week randomized clinical trial. Obes. Sci. Pract. 2022, 9, 235–242.
More
Video Production Service