Circulating short-chain and branched short-chain fatty acids and the risk of incident type 2 diabetes: findings from the 4C study

Abstract

Previous studies suggested that fecal short-chain fatty acids (SCFAs) and branched short-chain fatty acids (BCFAs) are associated with glucose regulation. However, the potential relationship between circulating SCFAs and BCFAs with incident diabetes risk in both men and women remains unidentified in prospective cohort studies. In this study, we examined a panel of nine serum SCFAs and BCFAs in 3414 subjects with incident diabetes, and matched normoglycemic controls from the China Cardiometabolic Disease and Cancer Cohort study. In fully adjusted conditional logistic regression models, total SCFAs, total BCFAs, and isovaleric acid were significantly associated with incident type 2 diabetes mellitus (T2DM) (P < 0.05). Interestingly, gender-specific analysis showed that per standard deviation (SD) increment of SCFAs were positively associated with incident T2DM among women, with the odds ratio (95% confidence interval) of 1.16 (1.05–1.29) for total SCFAs and 1.18 (1.07–1.31) for propionate, respectively (P < 0.05, false discovery rate (FDR) < 0.05). No significant associations were observed in men. A significant interaction was detected between men and women for propionate (P_interaction < 0.001, FDR < 0.01). After further adjustment of insulin measurements, the associations of serum propionate with diabetes remained significant (P < 0.05, FDR < 0.05). Meanwhile, the associations of total BCFAs and isovaleric acid with diabetes were partially mediated by triglycerides, insulin resistance, and β-cell function in mediation analysis. These findings, for the first time in a large prospective cohort, provide evidence for an association between circulating SCFAs and BCFAs with T2DM risk, and support the potential role of circulating propionate with gender disparities in the early pathogenesis of diabetes.

Keywords

short-chain fatty acids / branched short-chain fatty acids / type 2 diabetes / insulin resistance

References

[1] Koh A , De Vadder F , Kovatcheva-Datchary P et al. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell 2016; 165: 1332- 45.

[2] Haghikia A , Zimmermann F , Schumann P et al. Propionate attenuates atherosclerosis by immune-dependent regulation of intestinal cholesterol metabolism. Eur Heart J 2022; 43: 518- 33.

[3] Zhao L , Zhang F , Ding X et al. Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes. Science 2018; 359: 1151- 6.

[4] Larraufie P , Martin-Gallausiaux C , Lapaque N et al. SCFAs strongly stimulate PYY production in human enteroendocrine cells. Sci Rep 2018; 8: 74.

[5] Chambers ES , Viardot A , Psichas A et al. Effects of targeted delivery of propionate to the human colon on appetite regulation, body weight maintenance and adiposity in overweight adults. Gut 2015; 64: 1744- 54.

[6] Rios-Covian D , González S , Nogacka AM et al. An overview on fecal branched short-chain fatty acids along human life and as related with body mass index: associated dietary and anthropometric factors. Front Microbiol 2020; 11: 973.

[7] Canfora EE , Meex RCR , Venema K et al. Gut microbial metabolites in obesity, NAFLD and T2DM. Nat Rev Endocrinol 2019; 15: 261- 73.

[8] Choi BS , Daniel N , Houde VP et al. Feeding diversified protein sources exacerbates hepatic insulin resistance via increased gut microbial branched-chain fatty acids and mTORC1 signaling in obese mice. Nat Commun 2021; 12: 3377.

[9] Ratajczak W , Mizerski A , Rył A et al. Alterations in fecal short chain fatty acids (SCFAs) and branched short-chain fatty acids (BCFAs) in men with benign prostatic hyperplasia (BPH) and metabolic syndrome (MetS). Aging (Albany NY). 2021; 13: 10934- 54.

[10] Heimann E , Nyman M , Pålbrink AK et al. Branched short-chain fatty acids modulate glucose and lipid metabolism in primary adipocytes. Adipocyte. 2016; 5: 359- 68.

[11] Müller M , Hernández MAG , Goossens GH et al. Circulating but not faecal short-chain fatty acids are related to insulin sensitivity, lipolysis and GLP-1 concentrations in humans. Sci Rep 2019; 9: 12515.

[12] Salamone D , Costabile G , Corrado A et al. Circulating shortchain fatty acids in type 2 diabetic patients and overweight/ obese individuals. Acta Diabetol 2022; 59: 1653- 6.

[13] Zhao L , Lou H , Peng Y et al. Elevated levels of circulating shortchain fatty acids and bile acids in type 2 diabetes are linked to gut barrier disruption and disordered gut microbiota. Diabetes Res Clin Pract 2020; 169: 108418.

[14] Lu J , Wang S , Li M et al. Association of serum bile acids profile and pathway dysregulation with the risk of developing diabetes among normoglycemic chinese adults: findings from the 4C study. Diabetes Care 2021; 44: 499- 510.

[15] Wang S , Li M , Lin H et al. Amino acids, microbiota-related metabolites, and the risk of incident diabetes among normoglycemic Chinese adults: findings from the 4C study. Cell Rep Med 2022; 3: 100727.

[16] Zhao L , Lou H , Peng Y et al. Comprehensive relationships between gut microbiome and faecal metabolome in individuals with type 2 diabetes and its complications. Endocrine 2019; 66: 526- 37.

[17] Zhong C , Dai Z , Chai L et al. The change of gut microbiotaderived short-chain fatty acids in diabetic kidney disease. J Clin Lab Anal 2021; 35: e24062.

[18] Yin XQ , An YX , Yu CG et al. The association between fecal shortchain fatty acids, gut microbiota, and visceral fat in monozygotic twin pairs. Diabetes Metab Syndr Obes 2022; 15: 359- 68.

[19] de la Cuesta-Zuluaga J , Mueller NT , Álvarez-Quintero R et al. Higher fecal short-chain fatty acid levels are associated with gut microbiome dysbiosis, obesity, hypertension and cardiometabolic disease risk factors. Nutrients 2018; 11: 51.

[20] Deng K , Xu JJ , Shen L et al. Comparison of fecal and blood metabolome reveals inconsistent associations of the gut microbiota with cardiometabolic diseases. Nat Commun 2023; 14: 571.

[21] Murphy EF , Cotter PD , Healy S et al. Composition and energy harvesting capacity of the gut microbiota: relationship to diet, obesity and time in mouse models. Gut 2010; 59: 1635- 42.

[22] Guo W , Zhang Z , Li L et al. Gut microbiota induces DNA methylation via SCFAs predisposing obesity-prone individuals to diabetes. Pharmacol Res 2022; 182: 106355.

[23] Sanna S , van Zuydam NR , Mahajan A et al. Causal relationships among the gut microbiome, short-chain fatty acids and metabolic diseases. Nat Genet 2019; 51: 600- 5.

[24] Xu D , Feng M , Chu Y et al. The prebiotic effects of oats on blood lipids, gut microbiota, and short-chain fatty acids in mildly hypercholesterolemic subjects compared with rice: a randomized, controlled trial. Front Immunol 2021; 12: 787797.

[25] Du Y , Li X , An Y et al. Association of gut microbiota with sortchain fatty acids and inflammatory cytokines in diabetic patients with cognitive impairment: a cross-sectional, noncontrolled study. Front Nutr 2022; 9: 930626.

[26] Falony G , Joossens M , Vieira-Silva S et al. Population-level analysis of gut microbiome variation. Science 2016; 352: 560- 4.

[27] Zhang L , Chu J , Hao W et al. Gut microbiota and type 2 diabetes mellitus: association, mechanism, and translational applications. Mediators Inflamm 2021; 2021: 5110276.

[28] Cummings JH , Pomare EW , Branch WJ et al. Short chain fatty acids in human large intestine, portal, hepatic and venous blood. Gut 1987; 28: 1221- 7.

[29] Gao A , Su J , Liu R et al. Sexual dimorphism in glucose metabolism is shaped by androgen-driven gut microbiome. Nat Commun 2021; 12: 7080.

[30] Gojda J , Cahova M . Gut microbiota as the link between elevated BCAA serum levels and insulin resistance. Biomolecules 2021; 11: 1414.

[31] Rosli NSA , Abd Gani S , Khayat ME et al. Short-chain fatty acids: possible regulators of insulin secretion. Mol Cell Biochem 2023; 478: 517- 30.

[32] Tirosh A , Calay ES , Tuncman G et al. The short-chain fatty acid propionate increases glucagon and FABP4 production, impairing insulin action in mice and humans. Sci Transl Med 2019; 11: eaav0120.

[33] Lu J , He J , Li M et al. Predictive value of fasting glucose, postload glucose, and hemoglobin A_1c on risk of diabetes and complications in Chinese adults. Diabetes Care 2019; 42: 1539- 48.

[34] Lu J , Li M , Xu Y et al. Early life famine exposure, ideal cardiovascular health metrics, and risk of incident diabetes: findings from the 4C study. Diabetes Care 2020; 43: 1902- 9.

[35] Parsons LS . Performing a 1:N case-control match on propensity score. In: Proceedings of the 29th Annual SAS users group international conference. Cary, NC: SAS Institute Inc., 2004.

[36] Craig CL , Marshall AL , Sjostrom M et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003; 35: 1381- 95.

[37] Lloyd-Jones DM , Hong Y , Labarthe D et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association’s Strategic Impact Goal through 2020 and beyond. Circulation 2010; 121: 586- 613.

[38] Matthews DR , Hosker JP , Rudenski AS et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412- 9.

[39] Lin H , Hu C , Wang S et al. Protocol for analysis of liquid chromatography-mass spectrometry metabolomics data using R to understand how metabolites affect disease. STAR Protoc 2023; 4: 102137.

RIGHTS & PERMISSIONS

The Author(s). Published by Oxford University Press on behalf of Higher Education Press.