Elevated fasting serum xylitol levels are associated with a lower risk of incident type 2 diabetes among individuals with prediabetes in the Chinese population

doi:10.21203/rs.3.rs-4666401/v1

Download PDF

Article

Elevated fasting serum xylitol levels are associated with a lower risk of incident type 2 diabetes among individuals with prediabetes in the Chinese population

https://doi.org/10.21203/rs.3.rs-4666401/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background

Detection of predictors of prediabetes progressing to diabetes are important for exploration the strategy of reversing diabetes. Although polyols have beneficial effects on glycometabolism in clinical intervention studies, little is known about the association between fasting serum polyols of participant with habitual diet and the risk of prediabetes progressing to type 2 diabetes.

Methods

In this nested case-control study, 180 participants with type 2 diabetes developed from prediabetes (progressors), and 180 matched controls (non-progressors) with prediabetes during a 3.5-year follow-up were enrolled. The baseline levels of serum polyols in the fasting state were quantified using time-of-flight mass spectrometry. Multivariate conditional logistic regression was performed to assess the effects of the differentially polyols levels on the risk of incident diabetes.

Results

Baseline fasting xylitol levels, but not sorbitol or erythritol levels, were higer in non-progressors than in progressors (P < 0.001). Non-progressors, compared with progressors, had significantly higer proportions within the third tertile of xylitol levels (71/180 non-progressors [39.4%] vs. 49/180 progressors [27.2%]). After adjusting for potential confounders, the odds ratio of risk for incident diabetes in the highest tertile of xylitol levels was 0.338 (95% confidence interval 0.182–0.628), compared with that in the lowest quartile. In addition, the association between xylitol levels and incident diabetes was persistent in the diabetes subtype with high fasting blood glucose and both high fasting and 2h-postprandial blood glucose, but disappeared in the isolated high 2h-postprandial blood glucose subtype.

Conclusions

Elevated baseline fasting serum xylitol levels are associated with a lower risk of prediabetes progressing to diabetes. This association was particularly evident in the high fasting blood glucose subtype. These findings suggest that fasting serum xylitol levels may serve as an important predictor and protective factor against diabetes development.

Health sciences/Diseases/Endocrine system and metabolic diseases/Diabetes/Type 2 diabetes

Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Type 2 diabetes

polyol

prediabetes

type 2 diabetes

nested case-control study

xylitol

The global prevalence of diabetes has reached pandemic proportions, leading to serious complications and poor life expectancy [1]. Diabetes prevalence, particularly type 2 diabetes mellitus (T2DM), has significantly increased in China over the past few decades. Prediabetes, an intermediate stage of the progression to diabetes, affects approximately 38.1% of Chinese adults [2]. Without intervention, 5–10% of people with prediabetes progressed to T2DM each year [3]. Therefore, detection of early markers and interventions for the progression of prediabetes to diabetes are of major importance.

Studies have shown that lifestyle modification (dietary or physical activity improvements) is the most effective strategy for reversing prediabetes [4]. Artificial and natural sweeteners are widely used as sugar substitutes in the food industry to reduce energy intake [5]. Sugar alcohols (polyols), natural sweeteners with low-calorie content, are preferable alternative sweeteners to sucrose because of their beneficial effects on metabolism [6–7]. The most commonly used polyols are xylitol, sorbitol, and erythritol, which contribute to hyperglycemia management [8–11]. In addition to dietary sources, polyols are synthesized endogenously as a part of carbohydrate metabolism [12]. Xylitol is an intermediate in the glucoronate–xylulose cycle, sorbitol is endogenously produced from glucose and oxidized to fructose, and erythritol is endogenously produced by the pentose phosphate pathway [13–15]. Therefore, detecting serum polyol levels is vital to elucidate their effects on glycometabolism. However, the association between serum polyols and the progression of prediabetes to diabetes has not yet been investigated.

In the current study, we evaluated the concentrations of the most commonly used polyols and found that baseline fasting xylitol levels were higher in non-progressors than progressors. We subsequently found that lower fasting xylitol concentration was associated with the risk of progression of prediabetes to T2DM.

Study population

A total of 9,961 participants from Shanghai Chongming District were included in the baseline survey of the REACTION study from 2011 to 2012, and 7,587 completed the follow-up survey in 2014 [16]. Participants with prediabetes at baseline who developed T2DM during the 3.5-year follow-up period were classified as progressors. After 3.5 years of follow-up, the patients who maintained prediabetes were classified as non-progressors. Progressors were defined as cases and non-progressors as controls. Controls were selected for cases in a 1:1 ratio and matched according to sex, age, fasting blood glucose (FBG), 2h-postprandial blood glucose (PBG), glycated hemoglobin (HbA1c), and body mass index (BMI). Figure 1 shows the patient selection process. This study was approved by the Ethics Committee of Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine. All the participants provided written informed consent.

Characteristics collection and laboratory measurements

Information on lifestyle, disease history, and medication use was obtained using standard questionnaires. A food frequency questionnaire was used to estimate the participants' usual diet at baseline. The frequency ranged from times per day to times per week, month, or year. The sugar-sweetened beverages consumed were recorded in standard bottles (250 mL).

Height, weight, waist circumference, hip circumference, and blood pressure were measured using standardized methods. BMI was derived from weight in kilograms divided by the square of height in meters. The waist-to-hip ratio is the waist circumference divided by the hip circumference. Ultrasonography was used to assess fatty liver disease.

After fasting for 10 h, a 75-g oral glucose tolerance test (OGTT) was performed in the morning. Blood samples were collected during fasting and 2 h post-load. For blood glucose, HbA1c, triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT) and serum creatinine measurements, the samples were sent to the central laboratory of Shanghai Institute of Endocrine and Metabolic Diseases. Serum fasting insulin levels (catalog #8K41-74, RRID:AB_3075437) were measured using a chemiluminescent immunoassay. The homeostasis model assessment for insulin resistance (HOMA-IR) was calculated as follows: FPG (mmol/l) × FINS (mU/L)/22.5. Homeostatic model assessment of β-cell function (HOMA-β) was calculated as FINS × 20/(FPG-3.5).

Definition and classification of diabetes subtypes

Prediabetes was defined as 1) impaired fasting glucose (IFG): FBG 6.1–6.9 mmol/L and 2h-PBG < 7.8 mmol/L, or 2) impaired glucose tolerance (IGT): FBG < 6.1 mmol/L and 2h-PBG 7.8–11.0 mmol/L, or 3) IFG + IGT: FBG 6.1–6.9 mmol/L and 2h-PBG 7.8–11.0 mmol/L.

Diabetes was defined as 1) FBG ≥ 7.0 mmol/L, and/or 2) 2h-PBG ≥ 11.1 mmol/L, and/or 3) HbA1c value ≥ 6.5%.

Participants with T2DM were classified according to increased fasting blood glucose levels (F-DM) or 2 h postload glucose level (2h-DM), or both (F-2h-DM) [17].

Serum polyol level measurement

Peripheral venous blood samples were collected after at least a 10 h overnight fast and stored at − 80°C until assay. Samples were thawed on ice at 4°C before preparation.

Quality control samples were prepared by aspirating and mixing equal amounts of each serum sample. 25 µL serum was pipetted into a 1.5 mL centrifuge tube, and then 170 µL pre-cooled methanol was added. The mixture was shaken at 1,450 rpm for 15 min at 10°C (MSC-100; Allsheng Instruments Co., Ltd., Hangzhou, China). After − 20°C for 20 min, the samples were centrifuged at 18,000×g for 20 min at 4°C (Microfuge 20R, Beckman Coulter, Inc., Indianapolis, IN, USA). With a lyophilizer (Labconco, Kansas City, USA) 160 µL supernatant was lyophilized. Lyophilized powder reacted with 50 µL methoxamine solution at 37°C for 2 h. Next, 50 µL MSTFA (Thermo-Fisher Scientific, Fairlawn, NJ, USA) was added, and the reaction continued for 1 h at 37°C. All the standards (Sigma-Aldrich, St. Louis, MO, USA) were accurately weighed and prepared in water to obtain the individual stock solution at a concentration of 5.0 mg·mL^− 1. The appropriate amount of each stock solution was mixed to create stock calibration solutions.

Serum polyols were quantified using gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF/MS) system (Pegasus HT, Leco Corp., St. Joseph, MO, USA) as previously described [18]. For separation, a Rxi-5Sil MS capillary column (30 m × 0.25 mm × 0.25 µm i.d., 0.25-µm film thickness; Restek Corporation, Bellefonte, PA, USA) was used. Helium was used as the carrier gas at a constant 1.0 mL/min flow rate. Derivatized samples (1 µL) were injected into the GC/MS instrument. The programmed column temperature was optimized for successful separation. The injection and transfer interface temperature were set to 270 ºC. The source temperature was 220ºC. Electron impact ionization (70 eV) was used for measurements in full scan mode (m/z 50–500). The acquisition rate was set to 15 spectra/s. The instrument was optimized every 48 h.

The original GC-TOF/MS data were processed using Chroma TOF software (v5.51, Leco Corp., USA) for peak integration, calibration, and quantification of each metabolite. The self-developed iMAP platform (v1.0, Metabo-Profile, Shanghai, China) was used for statistical analyses.

Statistical analysis

Continuous variables are shown as means ± standard deviation (SD) or medians (IQR) for skewed variables. Categorical variables are presented as numbers (proportions). Student’s t-test and Wilcoxon rank-sum test were used to compare continuous variables. For comparison of categorical data, the chi-square test or Fisher’s exact test was used.

As continuous variables, multivariate conditional logistic regression was used to assess the association between polyol levels and incident diabetes. Odds ratios (OR) with 95% confidence intervals [CI] were calculated. The first model was adjusted for matching variables, including sex, age, FBG, PBG, HbA1c, and BMI. The second model was additionally adjusted for fasting insulin levels, systolic blood pressure, diastolic blood pressure, hypertension history, and serum creatinine and AST levels. The third model included the variables in Model 2 plus adjustments for current smoking status, alcohol consumption, and beverage intake. Baseline fasting xylitol levels were further grouped into tertiles. The unadjusted difference with a 95% CI was calculated between progressors and non-progressors. The odds of incident diabetes were calculated by comparing patients in the lowest tertile of xylitol levels. Subgroup analysis was conducted based on diabetes subtypes.

Spearman’s correlations were used to assess the relationship between fasting serum xylitol levels and changes in FBG, PBG, and HbA1c levels (follow-up levels minus baseline levels).

A two-sided P-value<0.05 was considered statistically significant. Statistical analyses were performed using SAS 9.3 software (SAS Institute, Cary, NC, USA).

Characteristics of study participants at baseline

Table 1 shows the baseline characteristics of the 180 non-progressors and 180 progressors. Baseline age, sex, FBG, PBG, HbA1C, and BMI were well balanced between non-progressors and progressors. Lifestyle factors, including current smoking status, alcohol consumption, and beverage intake, were similar in each group. The progressors tended to have higher systolic blood pressure, diastolic blood pressure, and fasting insulin levels at baseline.

Fasting serum xylitol, sorbitol, and erythritol levels were assessed. Xylitol levels in patients who developed diabetes were significantly lower than those in non-progressors (1.19±0.19 vs. 1.28±0.25 μmol/L, P＜0.001) (Figure 2). However, the sorbitol and erythritol concentrations did not differ between the two groups.

Association of baseline serum xylitol levels with odds of prediabetes to diabetes progression

A multivariate conditional logistic regression analysis was performed to clarify the association between polyols and diabetes progression. Only baseline xylitol levels were associated with incident diabetes. In the matching variables adjusted Model 1, the estimated OR was 0.294 (95% CI 0.125-0.693). The association was consistent after further adjusting for fasting insulin levels, systolic blood pressure, diastolic blood pressure, hypertension history, serum creatinine, and AST in Model 2 (0.279 [95% CI 0.115-0.674]). In addition, after adjusting for current smoking, alcohol consumption, and beverage intake at baseline in Model 3, an association was also observed (0.269 [95% CI 0.11-0.657]) (Supplemental Table 1).

The participants were then categorized into tertiles based on baseline fasting serum xylitol levels. Incident diabetes rates gradually decreased as the fasting serum xylitol tertile increased (Supplemental Figure 1). Compared with non-progressors, progressors had lower proportions within the third tertile of xylitol levels (71/180 non-progressors [39.4%] vs. 49/180 progressors [27.2%]) and higher proportions within the first tertile of xylitol levels (45/180 non-progressors [25%] vs. 76/180 progressors [42.2%]). We further analyzed the association between xylitol tertiles and incident diabetes (Table 2). In Model 1, the estimated OR of diabetes for participants in the highest tertile of serum xylitol levels compared with that of those in the lowest tertile was 0.374 (95% CI 0.212-0.658). The final adjusted model had an OR of 0.338 (95% CI 0.182-0.628) in the highest tertile of serum xylitol levels.

Lower baseline fasting xylitol levels associatied with developed diabetes with isolated high fasting blood glucose

Compared with those in non-progressors, FBG and PBG levels were higher in progressors at 3.5 years follow-up than at baseline (Supplemental Table 2). Spearman correlation analyses further revealed that ΔFBG was negatively correlated with baseline fasting serum xylitol levels (r=-0.197, P＜0.001). No correlation was observed between serum xylitol levels and ΔPBG or ΔHbA1c (Table 3). Progressors were divided into three subtypes according to FBG and PBG levels. The baseline fasting serum xylitol concentrations were lower in the F-DM and F-2h-DM groups than in the 2h-DM group (Figure 3A).

The association between baseline fasting serum xylitol levels and incident diabetes was estimated across the three subtypes. Compared with that in matched non-progressors, the proportion of F-DM was lower in the third tertile of xylitol levels (24/53 non-progressors [45.3%] vs.11/53 progressors [20.8]). In the fully adjusted model, the OR for the incidence of F-DM in the third tertile of xylitol levels was lower than that in the first tertile of xylitol levels (OR 0.08 [95% CI 0.014–0.467]). The association persisted in the F-2h-DM group (OR 0.038 [95% CI 0.001–0.990]) but was not detected in the 2h-DM group (OR 0.904 [95% CI 0.329–2.486]) (Figure 3B and Supplemental Table 3).

In this nested case-control study, we revealed that the xylitol levels were lower in progressors than in non-progressors. We demonstrated, for the first time, that elevated fasting serum xylitol levels were significantly associated with a lower risk of prediabetes progression to diabetes, especially in patients with isolated high fasting blood glucose.

Polyols are used extensively as sugar substitutes in diabetic food formulations. However, little is known about the effectiveness of polyols in ameliorating diabetes progression. It has been reported that the circulating sorbitol and erythritol levels were higher in patients with type 2 diabetes mellitus [19,20]. However, no significant differences were observed between non-progressors and progressors in terms of baseline serum sorbitol and erythritol concentrations in our study. While the baseline serum concentrations of xylitol were lower in progressors than in non-progressors after the 3.5-year follow-up. Xylitol has been reported to improve blood glucose levels in type 2 diabetes rats [21,22]. Patients with diabetes consuming xylitol had 32.6% less insulin requirement [10]. Logistic regression analysis revealed that xylitol was the only polyol associated with incident diabetes. No association was found in serum sorbitol or erythritol concentrations. These results indicate that xylitol has a protective effect against diabetes development.

Xylitol was absorbed in a dose-dependent manner. Xylitol was barely detected in the circulation after the 7 g dose. It was detected in some participants after the 17 g dose and in all participants after the 35 g dose [23]. Andrea et al. reported that xylitol did not accumulate in patients’ blood; 24 hours after xylitol intervention, it returned to baseline level [10]. In our study, we observed fasting xylitol levels in participants with habitual diets who received no extra xylitol intervention. Sugar-sweetened beverage consumption was adjusted for in multivariate Model 3, and the association between fasting serum xylitol levels and incident diabetes remained unchanged. In addition to food intake, endogenous xylitol is produced at approximately 5–15 g/day during the glucoronate–xylulose cycle [24]. This cycle is primarily active in the liver and kidneys of mammals and produces the metabolite xylulose 5-P. Xylulose 5-P then enters the pentose-phosphate pathway and subsequently affects glucose metabolism in other pathways or continues to generate glucuronate [25]. Accordingly, we speculate that fasting serum xylitol concentrations largely reflect endogenous xylitol production.

Interestingly, elevated fasting xylitol concentrations mainly correlated with improved fasting blood glucose rather than with postprandial glucose. After meal ingestion, multiple mechanisms are involved in glucose metabolism, including gastric emptying, intestinal glucose absorption, secretion, action of gastrointestinal hormones, and insulin secretion and action [26]. Xylitol has been reported to improve blood glucose levels through these mechanisms [27]. However, endogenous xylitol avoids gastrointestinal absorption and has lesser effect on gastrointestinal action. Fasting blood glucose levels are mainly determined by glycogenolysis and gluconeogenesis in the liver, which is also the organ involved in endogenous xylitol metabolism. As mentioned above, xylitol participates in glycometabolism through the pentose-phosphate pathway. In a bioclock study, proteins within the pentose-phosphate pathway peaked during the circadian morning [28]. This suggests that endogenous xylitol is more effective in improving fasting blood glucose levels than postprandial glucose.

This study had some limitations. First, it was a nested case-control study with a small sample size, which could not prove causality. Second, the detection method could not distinguish between endogenous and exogenous xylitol. And last, the mechanism underlying the effect of xylitol on fasting blood glucose levels remains unclear.

In conclusion, we found that those with elevated fasting serum xylitol levels had a lower risk of progression to diabetes. Importantly, we found that xylitol levels were negatively associated with changes in fasting blood glucose. These findings suggest that fasting serum xylitol levels may serve as an important predictor and protective factor against diabetes development. However, to validate these findings, further prospective studies with larger sample sizes utilizing molecular probe techniques focused on hepatic carbohydrate metabolism intervened by xylitol are needed.

BMI

body mass index

FPG

fasting plasma glucose

PBG

2h-postprandial blood glucose

HbA1c

glycated hemoglobin

HOMA-IR

homeostasis model assessment for insulin resistance

HOMA-β

homeostatic model assessment of β cell function

LDL

low-density lipoprotein

HDL

high-density lipoprotein

ALT

alanine aminotransferase

AST

aspartate aminotransferase

GGT

gamma-glutamyl transferase.

COMPETING INTERESTS:

The authors declare no competing interests.

AUTHOR CONTRIBUTIONS:

JM and LQ conceived the study. YQ, XL, MW, and YW contributed to the data acquisition. YQ and YL performed data analyses. YQ and XL drafted the manuscript. All the authors contributed to the discussion and critical revision of the manuscript. All the authors have read and approved the final version of the manuscript.

ACKNOWLEDGEMENTS:

The authors thank the study participants and administrators for their generous contributions. This study was supported by Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support(20181807), Shanghai Health and Medical Development Foundation(DMRFP_I_06), Science and Technology Commission of Shanghai Municipality-Science and Technology Program (20DZ2201500), Shanghai Municipal Health Commission (20204Y0294 and 202240107), Shanghai “Rising Stars of Medical Talents” Youth Development Program-Youth Medical Talents-Specialist Program(2022) and the Young Scientists Fund of the National Natural Science Foundation of China (82100864).

DATA AVAILABILITY:

The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable

Sun H, Saeedi P, Karuranga S, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119.
Wang L, Peng W, Zhao Z, et al. Prevalence and treatment of diabetes in China, 2013–2018. JAMA. 2021;326(24):2498–2506.
Bansal N. Prediabetes diagnosis and treatment: A review. World J Diabetes. 2015;6(2):296–303.
Echouffo-Tcheugui JB, Perreault L, Ji L, Dagogo-Jack S. Diagnosis and management of prediabetes: A review. JAMA. 2023;329(14):1206–1216.
Mooradian AD, Smith M, Tokuda M. The role of artificial and natural sweeteners in reducing the consumption of table sugar: A narrative review. Clin Nutr ESPEN. 2017;18:1–8.
de Cock P, Mäkinen K, Honkala E, Saag M, Kennepohl E, Eapen A. Erythritol Is more effective than xylitol and sorbitol in managing oral health endpoints. Int J Dent. 2016;2016:9868421.
Mäkinen KK. Sugar alcohol sweeteners as alternatives to sugar with special consideration of xylitol. Med Princ Pract. 2011;20(4):303–320.
Leutenegger A, Buchmann M, Frutiger A. [Comparative study of a new commercially produced combination solution (fat, carbohydrates, aminoacids) for complete parenteral feeding of surgery patients in intensive care]. Schweiz Med Wochenschr. 1984;114(21):742–753.
Santos J, Freire AP, Mira LB, Azevedo M, Manso C. [Sorbitol metabolism and diabetes]. Acta Med Port. 1984;5(7–8):241–249.
Schneider AS, Schettler A, Markowski A, et al. Assessment of xylitol serum levels during the course of parenteral nutrition including xylitol in intensive care patients: a case control study. Clin Nutr. 2014;33(3):483–488.
Wölnerhanssen BK, Cajacob L, Keller N, et al. Gut hormone secretion, gastric emptying, and glycemic responses to erythritol and xylitol in lean and obese subjects. Am J Physiol Endocrinol Metab. 2016;310(11):E1053-1061.
Msomi NZ, Erukainure OL, Islam MS. Suitability of sugar alcohols as antidiabetic supplements: A review. J Food Drug Anal. 2021;29(1):1–14.
Barnett PA, González RG, Chylack LT, Jr., Cheng HM. The effect of oxidation on sorbitol pathway kinetics. Diabetes. 1986;35(4):426–432.
Hootman KC, Trezzi JP, Kraemer L, et al. Erythritol is a pentose-phosphate pathway metabolite and associated with adiposity gain in young adults. Proc Natl Acad Sci U S A. 2017;114(21):E4233-e4240.
Jakob A, Williamson JR, Asakura T. Xylitol metabolism in perfused rat liver. Interactions with gluconeogenesis and ketogenesis. J Biol Chem. 1971;246(24):7623–7631.
Bi Y, Lu J, Wang W, et al. Cohort profile: risk evaluation of cancers in Chinese diabetic individuals: a longitudinal (REACTION) study. Journal of diabetes. 2014;6(2):147–157.
Færch K, Johansen NB, Witte DR, Lauritzen T, Jørgensen ME, Vistisen D. Relationship between insulin resistance and β-cell dysfunction in subphenotypes of prediabetes and type 2 diabetes. J Clin Endocrinol Metab. 2015;100(2):707–716.
Chen WL, Wang JH, Zhao AH, et al. A distinct glucose metabolism signature of acute myeloid leukemia with prognostic value. Blood. 2014;124(10):1645–1654.
Menni C, Fauman E, Erte I, et al. Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach. Diabetes. 2013;62(12):4270–4276.
Enquobahrie DA, Denis M, Tadesse MG, Gelaye B, Ressom HW, Williams MA. Maternal early pregnancy serum metabolites and risk of gestational diabetes mellitus. J Clin Endocrinol Metab. 2015;100(11):4348–4356.
Msomi NZ, Erukainure OL, Salau VF, Olofinsan KA, Islam MS. Xylitol improves antioxidant, purinergic and cholinergic dysfunction, and lipid metabolic homeostasis in hepatic injury in type 2 diabetic rats. J Food Biochem. 2022;46(4):e14040.
Islam MS, Indrajit M. Effects of xylitol on blood glucose, glucose tolerance, serum insulin and lipid profile in a type 2 diabetes model of rats. Ann Nutr Metab. 2012;61(1):57–64.
Bordier V, Teysseire F, Senner F, et al. Absorption and metabolism of the natural sweeteners erythritol and xylitol in humans: A dose-ranging study. Int J Mol Sci. 2022;23(17):9867.
Zacharis C. Xylitol. In Sweeteners and Sugar Alternatives in Food Technology (eds K. O'Donnell and M.W.Kearsley). WILEY; 2012.
Touster O. Essential pentosuria and the glucuronate-xylulose pathway. Fed Proc. 1960;19:977–983.
Dimitriadis GD, Maratou E, Kountouri A, Board M, Lambadiari V. Regulation of postabsorptive and postprandial glucose metabolism by insulin-dependent and insulin-independent mechanisms: An integrative approach. Nutrients. 2021;13(1):159.
Wölnerhanssen BK, Meyer-Gerspach AC, Beglinger C, Islam MS. Metabolic effects of the natural sweeteners xylitol and erythritol: A comprehensive review. Crit Rev Food Sci Nutr. 2020;60(12):1986–1998.
Hurley JM, Jankowski MS, De Los Santos H, et al. Circadian proteomic analysis uncovers mechanisms of post-transcriptional regulation in metabolic pathways. Cell Syst. 2018;7(6):613–626.e615.

Table 1 to 3 are available in the Supplementary Files section.

There is NO conflict of interest to disclose

Download PDF

Editorial decision: revise
04 Sep, 2024
Review #1 received at journal
16 Jul, 2024
Reviewer #1 agreed at journal
05 Jul, 2024
Reviewers invited by journal
05 Jul, 2024
Submission checks completed at journal
01 Jul, 2024
Editor assigned by journal
01 Jul, 2024
First submitted to journal
01 Jul, 2024

You are reading this latest preprint version

Elevated fasting serum xylitol levels are associated with a lower risk of incident type 2 diabetes among individuals with prediabetes in the Chinese population

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

INTRODUCTION

MATERIALS AND METHODS

Study population

Characteristics collection and laboratory measurements

Definition and classification of diabetes subtypes

Serum polyol level measurement

Statistical analysis

RESULTS

DISSCUSSION

Abbreviations

Declarations

COMPETING INTERESTS:

AUTHOR CONTRIBUTIONS:

ACKNOWLEDGEMENTS:

DATA AVAILABILITY:

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1