Abstract
Background and aims
Zonulin, carnitine, choline, γ-butyrobetaine (γ-BB), and trimethylamine-N-oxide (TMAO) are intricately involved in metabolic anomalies and type 2 diabetes mellitus (T2D). This study aimed to compare and correlate the plasma levels of zonulin, carnitine, choline, γ-butyrobetaine, and TMAO, along with the adiposity, atherogenicity, surrogate insulin resistance (sIR), and proinflammatory hematological indices of newly diagnosed drug-naive prediabetic and diabetic patients vs. apparently healthy normoglycemic controls.
Methods
In a cross-sectional study, 30 normoglycemic subjects (controls) and 16 prediabetic (preDM) and 14 type 2 diabetes (T2D) cases, that were gender and age-matched, were enrolled. Zonulin, carnitine, choline, γ-BB, and TMAO plasma levels were appraised using colorimetric assays. A comparison between the study groups was conducted by ANOVA while Spearman rank correlations between the metabolic risk biomarkers and between the risk markers and adiposity, sIR, atherogenicity, and proinflammatory hematological indices were also examined.
Results
Significant intergroup discrepancies in plasma carnitine, choline, γ-BB, and TMAO (but not zonulin) could be recognized in the cases vs. controls. Fasting blood glucose (FPG), glycated hemoglobin (A1C), triglycerides (TGs), body mass index (BMI), lipid accumulation product (LAP), visceral adiposity index (VAI), atherogenic index of plasma (AIP), and all sIR were outstandingly higher in the cases vs. controls. Blood indices lacked a scoring value to discriminate cases from controls. Inadvertently, no relation was found between plasma carnitine, choline, γ-BB, TMAO, or zonulin in cases. Among the rest of the markers and sIR indices, the triglyceride glucose-body mass index (TyG*BMI) related reciprocally to zonulin. Noticeably, among adiposity indices, TyG*BMI, triglyceride glucose-waist circumference (TyG*WC), and metabolic score for insulin resistance (MetS-IR) positively associated with waist circumference (WC), hip circumference (HC), BMI, body adiposity index (BAI), and waist-to-height ratio (WHtR). Exceptionally, LAP proportionally correlated with all sIR. TyG*WC and MetS-IR correlated directly with the conicity index (CI). WHR directly associated with triglyceride glucose (TyG) index and TyG*WC. Remarkably, the TyG index (but not TyG*BMI, TyG*WC, or MetS-IR) positively associated with all atherogenicity indices and RDW (but none of other blood indices). TMAO correlated inversely (p < 0.05) and moderately with choline. Distinctively, carnitine associated negatively with TC (p < 0.05). Both choline and carnitine related similarly and directly with PLR but inversely with lymphocytes (p<.05). Effectively, γ-butyrobetaine associated with both WC and the TyG-WC index equally negatively (p < 0.05). Substantially, γ-butyrobetaine correlated inversely with both atherogenic LDL-C/HDL-C ratio and MPV (p < 0.05). No pronounced relations were detected between the five microbiome signature determinants and glycemic control parameters (FBG and A1C%), sIR (TyG, TyG-BMI, or MetS-IR), adiposity (WHR, WHtR, CI, BAI, LAP, or VAI), atherogenicity indices (TC/HDL-C ratio, non-HDL-C/HDL-C ratio, or AIP), or blood indices (NLR or MLR).
Conclusion
Given the intergroup discrepancies in sIR, plasma zonulin, carnitine, choline, γ-BB, and TMAO along with their elective correlations with indices and clinical parameters of metabolic dysregulations, our study cannot rule out any possible molecular crosstalk and interplay of the biomarkers studied with the pathophysiology of prediabetes/diabetes. All in all, plasma zonulin, carnitine, choline, γ-BB, and TMAO with sIR can be putative surrogates for molecular cardiometabolic risk biomarkers to use as prognostic/predictive tools for the diagnosis/prevention and potential targets for prediabetes/diabetes management modalities.
Similar content being viewed by others
References
Qin J, Li R, Raes J, Arumugam M, Burgdorf K, Manichanh C, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. 2010;464:59–65.
Kamo T, Akazawa H, Suda W, Saga-Kamo A, Shimizu Y, Yagi H, Liu Q, Nomura S, Naito A, Takeda M, Harada M, Toko H, Kumagai H, Ikeda Y, Takimoto E, Suzuki JI, Honda K. Dysbiosis and compositional alterations with aging in the gut microbiota of patients with heart failure. PLoS ONE. 2017;12(3):e0174099.
Tang H, Kitai T, Hazen S. Gut microbiota in cardiovascular health and disease. Circ. Res. 2018;120(7):1183–96.
Trøseid M, Nestvold T, Rudi K, Thoresen H, Nielsen E, Lappegård K. Plasma lipopolysaccharide is closely associated with glycemic control and abdominal obesity. Diabetes Care. 2013;36:3627–32.
Bergeron N, Williams PT, Lamendella R, Faghihnia N, Grube A, Li X, Wang Z, Knight R, Jansson J, Hazen S, Krauss R. Diets high in resistant starch increase plasma levels of trimethylamine N-oxide, a gut microbiome metabolite associated with CVD risk. Br J Nutr. 2016;116(12):2020–9.
Lynch S. Gut microbiota and allergic disease. New Insights. Ann Am Thorac Soc. 2016;13(1):S51–4.
Skye SM, Zhu W, Romano KA, Guo CJ, Wang Z, Jia X, Kirsop J, Haag B, Lang JM, DiDonato JA, Tang WHW, Lusis AJ, Rey FE, Fischbach MA, Hazen SL. Microbial transplantation with human gut commensals containing CutC is sufficient to transmit enhanced platelet reactivity and thrombosis potential. Circ Res. 2018a;123(10):1164–76.
Rinninella E, Raoul P, Cintoni M, Franceschi F, Miggiano G, Gasbarrini A. What is the healthy gut microbiota composition? A changing ecosystem across age, environment, diet, and diseases. Microorganisms. 2019;10:7(1).
Vojvodic A, Peric-Hajzler Z, Matovic D, Vojvodic P, Vlaskovic-Jovicevic T, Sijan G, Dimitrijevic S, Stepic N, Wollina U, Badr B, Badawi A, Goldust M, Tirant M, Nguyen V, Fioranelli M, Lotti T. Gut microbiota and the alteration of immune balance in skin diseases: from nutraceuticals to fecal transplantation. J Med Sci. 2019;7(18):3034–8.
Tsigalou C, Konstantinidis T, Stavropoulou E, Bezirtzoglou E, Tsakris A. Potential elimination of human gut resistome by exploiting the benefits of functional foods. Front Microbiol. 2020;11(50).
Trøseid M, Hov J, Nestvold T, Thoresen H, Berge R, Svardal A, Lappegård K. Major increase in microbiota dependent proatherogenic metabolite TMAO one year after bariatric surgery. Metab Syndr Relat Disord. 2016;14:197–201.
Koeth A, Levison S, Culley K. Gamma butyrobetaine is a proatherogenic intermediate in gut microbial metabolism of L-L-carnitine to TMAO. Cell Metab. 2014;20:799–812.
Wang Z, Klipfell E, Bennett BJ, Koeth R, Levison BS, Dugar B, Feldstein A, Britt E, Fu X, Chung YM, Wu Y, Schauer PH, Smith J, Allayee H, Tang WH. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature. 2011;472:57–63.
Gruppen E, Garcia E, Connelly M, Jeyarajah E, Otvos J, Bakker S, Dullaart R. TMAO is associated with mortality: impact of modestly impaired renal function. Sci Rep. 2017;7:13781.
Al-Obaide M, Singh P, Rewers-Felkins K, Salguero V, Kottapalli K, Vasylyeva T. Gut microbiota-dependent trimethylamine-N-oxide and serum biomarkers in patients with T2D and advanced CKD. J Clin Med. 2017;6(9):86.
Al Bataineh MT, Dash NR, Lassen PB, Banimfregf BH, Nada AM, Belda E, Clement K. Revealing links between gut microbiome and its fungal community in type 2 diabetes mellitus among Emirati subjects: a pilot study. Sci Rep. 2020;10:9624.
Gurung M, Li Z, You H, Rodrigues R, Jump DB, Morgun A, Shulzhenko N. Role of gut microbiota in type 2 diabetes pathophysiology. Lancet EBioMed. 2020;51:102590.
Li Q, Chang Y, Zhang K, Chen H, Tao S, Zhang Z. Implication of the gut microbiome composition of type 2 diabetic patients from northern China. Sci Rep. 2020;10:5450.
Vujkovic-Cvijin I, Sklar J, Jiang L, Natarajan L, Knight R, Belkaid Y. Host variables confound gut microbiota studies of human disease. Nature. 2020;587:448–54.
Skagen K, Trøseid M, Ueland T, Holm S, Abbas A, Gregersen I, Kummen M, Bjerkeli V, Reier-Nilsen F, Russell D, Svardal A, Karlsen TH, Aukrust P, Berge R, Hov E, Halvorsen B, Skjell M. The carnitine-butyrobetaine-trimethylamine-N-oxide pathway and its association with cardiovascular mortality in patients with carotid atherosclerosis. Atherosclerosis. 2016;247:64–9.
Wu WK, Panyod S, Liu PY, et al. Characterization of TMAO productivity from carnitine challenge facilitates personalized nutrition and microbiome signatures discovery. Microbiome. 2020;8:162.
Ohlsson B, Roth B, Larsson E, Höglund P. Calprotectin in serum and zonulin in serum and feces are elevated after introduction of a diet with lower carbohydrate content and higher fiber, fat and protein contents. Biomed Rep. 2017;6:411–22.
Sturgeon G, Fasano A. Zonulin, a regulator of epithelial and endothelial barrier functions, and its involvement in chronic inflammatory diseases. Tissue Barriers. 2016;4(4):e1251384.
Ajamian M, Steer D, Rosella G, Gibson PR. Serum zonulin as a marker of intestinal mucosal barrier function: may not be what it seems. PLoS ONE. 2019;14(1):e0210728.
Fasano A. All disease begins in the (leaky) gut: role of zonulin-mediated gut permeability in the pathogenesis of some chronic inflammatory diseases. F1000Res. 2020;9:F1000 Faculty Rev–69.
Dorcely B, Katz K, Jagannathan R, Chiang S, Oluwadare B, Goldberg I, Bergman M. Novel biomarkers for prediabetes, diabetes, and associated complications. Diabetes Metab Syndr Obes. 2017;10:345–61.
Lees T, Nassif N, Simpson A, Shad-Kaneez F, Martiniello-Wilks R, Lin Y, Jones A, Qu X, Lal S. Recent advances in molecular biomarkers for diabetes mellitus: a systematic review. Biomarkers. 2017;22(7):604–13.
American Diabetes Association (ADA). Standards of medical care in diabetes. Diabetes Care. 2020;42(Supplement 1):S13–28.
American Diabetes Association. (ADA). Clin Diabetes J. 2020;38(1).
Hameed I, Masoodi S, Mir S, Nabi M, Ghazanfar K, Ganai B. Type 2 diabetes mellitus: from a metabolic disorder to an inflammatory condition. World J Diabetes. 2015;6(4):598–612.
Ducarmon Q, Zwittink R, Hornung B, Schaik W, Young V, Kuijper E. Gut microbiota and colonization resistance against bacterial enteric infection. Microbiol Mol Biol Rev. 2019;83(3).
Dobiasova M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate in apoB-lipoprotein-depleted plasma (FER(HDL)). Clin Biochem. 2001;34(7):583–8.
Khanduker S, Ahmed R, Nazneen M, Alam A, Khondokar F. A comparative study of lipid profile and atherogenic index of plasma among the pre and post-menopausal women. Answer Khan Mod Med Coll J. 2018;9(1):44–9.
Pradhan A. Obesity, metabolic syndrome, and type 2 diabetes: inflammatory basis of glucose metabolic disorders. Nutr Rev. 2007;65:152–6.
Akour A, Kasabri V, Boulatova N, Bustanji Y, Naffa R, Hyasat D, Khawaja N, Bustanji H, Zayed A, Momani M. Levels of metabolic markers in drug-naive prediabetic and type 2 diabetic patients. Acta Diabetol. 2016;54(2):163–70.
Tam Z, Ng S, Tan L, Lin C, Rothenbacher D, Klenk J, Boehm B. Metabolite profiling in identifying metabolic biomarkers in older people with late-onset type 2 diabetes mellitus. Sci Rep. 2017;7:4392.
Gedela S, Rao A, Medicher N. Identification of biomarkers for type 2 diabetes and its complications: a bioinformatic approach. Int J Biomed Sci. 2007;3(4):229–36.
International Diabetes Foundation (IDF). Worldwide definition of the metabolic syndrome. The IDF consensus worldwide definition of the Metabolic Syndrome, 2006; 1-19.
Janeiro M, Ramírez M, Milagro F, Martínez A, Solas M. Implication of trimethylamine N-oxide (TMAO) in disease: potential biomarker or new therapeutic target. Nutrients. 2018;10(10):1398.
Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for developing diabetes. Lancet. 2012;379(9833):2279–90.
Sh Z, Du T, Li M, Jia J, Lu H, Lin X, Yu X. Triglyceride glucose-body mass index is effective in identifying nonalcoholic fatty liver disease in nonobese subjects. Medicine. 2017;96:22.
Simental-Mendía L, Rodríguez-Morán M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Related Disord. 2008;6(4):299–304.
Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, Fernández-Montero A, Martinez J. Triglyceride–glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: the vascular-metabolic CUN cohort. Prev Med. 2016;86:99–105.
Kim M, Ahn C, Kang S, Nam J, Kim K, Park J. Relationship between the triglyceride glucose index and coronary artery calcification in Korean adults. Cardiovasc Diabetol. 2017;16(1):108.
Er LK, Wu S, Chou HH, Hsu LA, Teng MS, Sun YC, Ko YL. Triglyceride glucose-body mass index is a simple and clinically useful surrogate marker for insulin resistance in nondiabetic individuals. PLoS ONE. 2016;11(3):0149731.
Okosun IS, Okosun B, Lyn R, Airhihenbuwa C. Surrogate indexes of insulin resistance and risk of metabolic syndrome in non-Hispanic White, non-Hispanic Black and Mexican American. Diabetes Metab Syndr. 2020;14(1):3–9.
Bello-Chavolla OY, Almeda-Valdes P, Gomez-Velasco D, Viveros-Ruiz T, Cruz-Bautista I, Romo-Romo A, Sánchez-Lázaro D, Meza-Oviedo D, Vargas-Vázquez A, Campos OA, MDR S-G, Martagón AJ, Hernández LM, Mehta R, Caballeros-Barragán CR, Aguilar-Salinas CA. METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity. Eur J Endocrinol. 2018;178:533–44.
Lockie R, Ruvalcaba T, Stierli M, Dulla J, Dawes J, Orr R. Waist circumference and waist-to-hip ratio in law enforcement agency recruits: relationship to performance in physical fitness tests. J Strength Cond Res. 2020;34(6):1666–75.
Filgueiras MS, Vieira SA, Fonseca PCA, Pereira PF, Ribeiro AQ, Priore SE, Franceschini SDC. Waist circumference, waist-to-height ratio and conicity index to evaluate android fat excess in Brazilian children. Public Health Nutr. 2019;22(1):140–6.
Cerqueira MS, Santos CAD, Silva DAS, Amorim P, Marins JCB, Franceschini S. Validity of the body adiposity index in predicting body fat in adults: a systematic review. Adv Nutr. 2018;9(5):617–24.
Mazidi M, Kengne AP, Katsiki N, Mikhailidis D, Banach M. Lipid accumulation product and triglycerides/glucose index are useful predictors of insulin resistance. J Diabetes Complicat. 2018;32(3):266–70.
Gupta G, Sharma P, Kumar P, Sharma R. Is cardiovascular risk associated with subclinical hypothyroidism: role of C reactive protein and interleukin-6. J Cardiovasc Dis Res. 2018;9(1):20–3.
Morikawa SY, Fujihara K, Hatta M, Osawa T, Ishizawa M, Yamamoto M, Furukawa K, Ishiguro H, Matsunaga S, Ogawa Y, Shimano H. Relationships among cardiorespiratory fitness, muscular fitness, and cardiometabolic risk factors in Japanese adolescents: Niigata screening for and preventing the development of non-communicable disease study-Agano(nice evidence study-agano) 2. Pediatr Diabetes. 2018;19(4):593–602.
Chrom P, Stec R, Bodnar L, Szczylik C. Incorporating neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in place of neutrophil count and platelet count improves prognostic accuracy of the international metastatic renal cell carcinoma database consortium model. Cancer Res Treat. 2018;50(1):103–10.
Antwi-Baffour S, Kyeremeh R, Buabeng D, Adjei JK, Aryeh C, Kpentey G, Seidu MA. Correlation of malaria parasitaemia with peripheral blood monocyte to lymphocyte ratio as indicator of susceptibility to severe malaria in Ghanaian children. Malar J. 2018;17(1):419.
Arab GA, Zahedi M, Kazemi V, Sanagoo A, Azimi M. Correlation between hemoglobin A1C and serum lipid profile in type 2 diabetic patients referred to the diabetes clinic in Gorgan. Iran J Clin Basic Res. 2018;2:26–31.
Phapale Y, Badade Z, Kaul S, Rai S. Assessment of atherogenic indices section in type 2 diabetes mellitus. J Clin Diagn Res. 2019;13(12):10–3.
Mirmiran P, Bahadoran Z, Azizi F. Lipid Accumulation product is associated with insulin resistance, lipid peroxidation, and systemic inflammation in type 2 diabetic patients. Endocrinol Metab. 2014;29:443–9.
Van Mens T, Buller H, Nieuwdrop M. Targeted inhibition of gut microbiota proteins involved in TMAO production to reduce platelet aggregation and arterial thrombosis: a blueprint for drugging the microbiota in the treatment of cardiometabolic disease ? J Thromb Haemost. 2019;17(1):3–5.
Demir E, Ozkan H, Seckin KD, Sahtiyancı B, Demir B, Tabak O, Kumbasar A, Uzun H. Plasma zonulin levels as a non-invasive biomarker of intestinal permeability in women with gestational diabetes mellitus. Biomolecules. 2019;9(1):24.
Hasslacher C, Kulozik F, Platten I, Kraft M, Siege EG. Serum zonulin as parameter of intestinal permeability in longstanding type 2 diabetes: correlations with metabolism parameter and renal function. J Diabetes Metab Dis Control (JDMDC). 2018;5(2):58–6.
Moreno-Navarrete J, Sabater M, Ortega F, Ricart W, Fernández-Real J. Circulating zonulin, a marker of intestinal permeability, is increased in association with obesity associated insulin resistance. PLoS ONE. 2012;7(5):e37160.
Lim J, Kim J, Koo S, Kwon G. Comparison of triglyceride glucose index, and related parameters to predict insulin resistance in Korean adults: an analysis of the 2007-2010 Korean National Health and Nutrition Examination Survey. PLoS ONE. 2019;14(3):e0212963.
Hameed E. TyG index a promising biomarker for glycemic control in type 2 diabetes mellitus. Diabetes Metab Syndr. 2018;13:560e563–3.
Wang S, Ma W, Yuan Z, Wang S, Yi X, Jia H, Xue F. Association between obesity indices and type 2 diabetes mellitus among middle-aged and elderly people in Jinan, China: a cross-sectional study. Br Med J. 2016;6(11):e012742.
Bene J, Hadzsiev K, Melegh B. Role of carnitine and its derivatives in the development and management of type 2 diabetes. Nutr Diabetes. 2018;8:8.
Alipour B, Barzegar A, Panahi F, Safaeian A, Eshaghi M. Effect of L-carnitine supplementation on metabolic status in obese diabetic women with hypocaloric diet. Health Scope. 2014;3:e14615.
Fathizadeh H, Milajerdi A, Reiner Z, Kolahdooz F, Asemi Z. The effects of L-carnitine supplementation on glycemic control: a systematic review and meta-analysis of randomized controlled trials. Excli J. 2019;18:631–43.
Xu Y, Jiang W, Chen G, Zhu W, Ding W, Ge Z, Tan Y, Ma T, Cui G. L-carnitine treatment of insulin resistance: a systematic review and meta-analysis. Adv Clin Exp Med. 2017;26(2):333–8.
Kerner J, Hoppel C. Fatty acid import into mitochondria. Biochim Biophys Acta. 2000;1486(1):1–17.
Malaguarnera M, Vacante M, Avitabile T, Malaguarnera M, Cammalleri L, Motta M. L-carnitine supplementation reduces oxidized LDL cholesterol in patients with diabetes. Am J Clin Nutr. 2009;89(1):71–6.
Walford GA, Ma Y, Clish C, Florez JC, Wang TJ, Gerszten RE, Diabetes Prevention Program Research Group. Metabolite profiles of diabetes incidence and intervention response in the diabetes prevention program. Diabetes. 2016;65(5):1424–33.
Li Y, Wang D, Chiuve S, Manson J, Willett W, Hu F, Qi L. Dietary phosphatidylcholine intake and type 2 diabetes in men and women. Diabetes Care. 2015;38(2):e13–4.
Karalis D, Karalis T, Karalis S, Kleisiari A. L-L-carnitine as a diet supplement in patients with type II diabetes. Cureus. 2020;12(5):e7982.
Ejaz A, Martinez-Guino L, Goldfine AB, Ribas-Aulinas F, De-Nigris V, Ribo S, Gonzalez-Franquesa A, Garcia-Roves PM, Li E, Dreyfuss JM, Gall W, Kim JK, Bottiglieri T, Villarroya F, Gerszten RE, Patti ME, Lerin C. Dietary betaine supplementation increases Fgf21 levels to improve glucose homeostasis and reduce hepatic lipid accumulation in mice. Diabetes. 2016;65(4):902–12.
Liepinsh E, Vilskersts R, Loca D, Kirjanova O, Pugovichs O, Kalvinsh I, Dambrova M. Inhibitor of carnitine biosynthesis, induces an increase in gamma-butyrobetaine contents and cardioprotection in isolated rat heart infarction. J Cardiovasc Pharmacol. 2006;6:314–9.
Du J, Shen L, Tan Z, Zhang P, Zhao X, Xu Y, Gan M, Yang Q, Ma J, Jiang A, Tang G, Jiang Y, Jin L, Li M, Bai L, Li X, Wang J, Zhang S, Zhu L. Betaine supplementation enhances lipid metabolism and improves insulin resistance in mice fed a high-fat diet. Nutrients. 2018;10(2):131.
Virtanen J, Tuomainen T, Voutilainen S. Dietary intake of choline and phosphatidylcholine and risk of type 2 diabetes in men: the Kuopio Ischaemic Heart Disease Risk Factor Study. Eur J Nutr. 2020;59:3857–61.
Malinowska A, Szwengiel A, Chmurzynska A. Dietary, anthropometric, and biochemical factors influencing plasma choline, L-carnitine, trimethylamine, and trimethylamine-N-oxide concentrations. Int J Food Sci Nutr. 2017;68(4):488–95.
Barrea L, Annunziata G, Muscogiuri G, Somma C, Laudisio D, Maisto M, Alteriis G, Tenore G. Trimethylamine-N-oxide (TMAO) as novel potential biomarker of early predictors of metabolic syndrome. Nutrients. 2018;10:1971.
Blaak E, Canfora E. Increased circulating choline, L-carnitine and TMAO levels are related to changes in adiposity during weight loss: role of the gut microbiota? Ann Transl Med. 2018;6(Suppl 2):S92.
Mazidi M, Rezaie P, Kengne AP, Mobarhan MG, Ferns GA. Gut microbiome and metabolic syndrome. Diabetes Metab Syndr. 2016;10(2 Suppl 1):150–7.
Brunkwall L, Orho-Melander M. The gut microbiome as a target for prevention and treatment of hyperglycaemia in type 2 diabetes: from current human evidence to future possibilities. Diabetologia. 2017;60(6):943–51.
Trøseid M, Ueland T, Hov JR, Svardal A, Gregersen I, Dahl C, Aakhus S, Gude E, Bjørndal B, Halvorsen B, Karlsen T, Aukrust P, Gullestad L, Berge R, Yndestad A. Microbiota-dependent metabolite trimethylamine-N-oxide is associated with disease severity and survival of patients with chronic heart failure. J Intern Med. 2015;277:717–26.
Acknowledgments
We sincerely thank all patients who participated in the study.
Funding
The research was funded by the Deanship of Scientific Research, University of Jordan (4/2016-2017; grant number 1938).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethics approval
This article does not contain any studies with animals performed by any of the authors.
Conflict of interest
The authors declare no competing interests.
Ethics statement
Written informed consent was obtained from all subjects. The experimental protocol was reviewed and approved by the Ethical Committee of Jordan University. Approval for the study was obtained from the Institutional Review Board affiliated with the Jordan University Hospital (JUH; 7/2019/IRB) and King Hussein Medical City (KHMC; 271/2019/2) and was conducted according to the principles expressed in the Declaration of Helsinki (World Medical Association, 2008).
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Snouper, A., Kasabri, V., Bulatova, N. et al. Plasma carnitine, choline, γ-butyrobetaine, and trimethylamine-N-oxide, but not zonulin, are reduced in overweight/obese patients with pre/diabetes or impaired glycemia. Int J Diabetes Dev Ctries 43, 592–605 (2023). https://doi.org/10.1007/s13410-022-01088-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13410-022-01088-x