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Dysregulated tryptophan metabolism contributes to metabolic syndrome in Chinese community-dwelling older adults

BMC Endocrine Disorders volume 25, Article number: 7 (2025) Cite this article

Abstract

Background

As the prevalence of metabolic syndrome (MetS) rises among older adults, the associated risks of cardiovascular diseases and diabetes significantly increase, and it is closely linked to various metabolic processes in the body. Dysregulation of tryptophan (TRP) metabolism, particularly alterations in the kynurenine (KYN) and serotonin pathways, has been linked to the onset of chronic inflammation, oxidative stress, and insulin resistance, key contributors to the development of MetS. We aim to investigate the relationship between the TRP metabolites and the risk of MetS in older adults.

Methods

Ultra-performance liquid chromatography tandem mass spectrometry was used to detect TRP and its seven metabolites in a study involving 986 participants. Physical examination included the following indicators: blood pressure, body mass index, triglyceride levels, and high-density lipoprotein cholesterol (HDL-C) levels. Multiple linear regression, restricted cubic spline curve, binary logistic analysis, and sex-stratified analysis were used to explore the relationship between the metabolites and the risk of MetS in older adults.

Results

The results indicated that, after adjusting for covariates, higher levels of TRP, KYN, kynurenic acid (KA), and xanthurenic acid (XA) were risk factors for MetS (P for trend < 0.05). By contrast, higher ratios of 5-hydroxytryptamine to TRP and indole-3-propionic acid to TRP were protective factors against MetS (P for trend < 0.05).

Conclusions

TRP and its metabolites may serve as potential indicators for assessing and managing MetS in older adults, complementing existing biomarkers.

Clinical trial number

Not applicable.

Peer Review reports

Introduction

Metabolic syndrome (MetS) refers to a group of cardiometabolic risk factors involving hypertension, hyperglycemia, central obesity, and dyslipidemia, as well as other noncommunicable diseases [1, 2]. The global prevalence of MetS has been summarized as ranging from 12.5 to 31.4%, with significantly higher prevalence in the Eastern Mediterranean region and the Americas, and increasing with the income level of the country [3]. In older adults, the prevalence of MetS increases rapidly every year worldwide, which is associated with reduced physical function and an elevated risk of dependency [4]. In 2017, older adults with MetS aged ≥ 60 and ≥ 65 years accounted for 24.7% and 16.4%, respectively, of the registered population in Beijing, with increasing population aging expected to exacerbate the problem of MetS [5]. Many factors affect the prevalence of MetS. For instance, the circulating levels of several amino acids and metabolites are associated with cardiometabolic risk and MetS [6]. Increasing evidence also suggests that the metabolism of tryptophan (TRP) with aging is linked to the overall risk of MetS. The imbalance in TRP metabolism with age may lead to chronic low-grade inflammation, insulin resistance, and abnormalities in fat metabolism, which are all key features of MetS [7,8,9].

TRP metabolism primarily occurs via the kynurenine (KYN), serotonin (5-hydroxytryptamine, 5-HT), and indole pathways (Figure S1). Emerging evidence suggests a close relationship between TRP metabolism disorders and various diseases [10,11,12].

More than 95% of dietary TRP is metabolized through the kynurenine pathway (KP). KYN is a key metabolite of TRP; other compounds produced through the KP contribute to MetS development [7, 9]. Older adults with MetS tend to have higher levels of KYN, kynurenic acid (KA), and xanthurenic acid (XA) [13]. According to experimental studies, mature adipocytes extracted from individuals with obesity that are characterized by indoleamine 2,3-dioxygenase 1 (IDO1) overexpression mediate the catabolism of TRP, producing excess KYN, which in turn increases obesity and insulin resistance [14]. The ratio of KYN to TRP serves as a surrogate marker of the enzymatic activities of IDO [13]. The ratio of KA to KYN is a surrogate measure of kynurenine aminotransferase (KAT) enzyme activity and KYN catabolism. KAT has 3 isoforms (I, II, and III) that catalyze the degradation of KYN to KA [15]. It also catalyzes the conversion of 3-hydroxykynurenine (3-HKYN) to XA [11]. These key regulatory enzymes can be targeted for the treatment of specific diseases.

In the serotonin pathway, approximately 3% of TRP is metabolized by tryptophan hydroxylase (TPH) to 5-hydroxytryptophan and converted into 5-HT [16]. During the induction and development of MetS, 5-HT is produced in the brain (hypothalamus and striatum) and peripheral system (plasma and urine) [17].

TRP can be degraded into specific gut microbiota to metabolites such as indole-3-acetic acid (IAA) and indole-3-propionic acid (IPA) [16, 18]. These metabolites are involved in intestinal permeability, inflammatory regulation, and host immunity [12]. Therefore, therapeutic targeting of gut microbiota may be a viable treatment option for gut–brain axis disorders caused by indole derivatives. For instance, IPA can be used to improve intestinal barrier function and mitigate inflammatory responses by downregulating the expression of genes involved in inflammation and oxidative stress [19]. Immune response and inflammation strongly contribute to MetS [20].

To the best of our knowledge, no systematic study has yet examined the relationship between the metabolism components of TRP and the risk of MetS in older adults. In this study, we investigated the relationships between TRP and its metabolites and the risk of MetS in older adults. These metabolites can be used as markers of major age-related diseases. Overall, our findings may provide novel insights into potential mechanisms for understanding and addressing MetS in older adults, which could inform future preventive and therapeutic approaches.

Methods

Study Population

A cross-sectional survey was conducted in Lu’an, China. Older adults in the Environment and Health Controllable Factors Cohort for Older Adults in Lu’an City were selected for the study. According to statistical data from Anhui Province in 2014, the prevalence of chronic diseases among older adults aged 60 years and above was 61.3%, and the prevalence of hypertension among older adults in Lu’an City ranked first in the province, with a crude prevalence rate of 48.8%. The burden of chronic diseases in this population is high, which can effectively represent the health problems related to metabolic syndrome and cardiovascular diseases in older adults [21]. Briefly, multistage stratified random sampling was used to first select a township and street and then a community or village. Questionnaires were distributed, and health check-ups were conducted for all older participants. A total of 1080 individuals were initially included in the study. After screening for eligibility, only 986 participants were included (Figure S2). The study protocol was reviewed and approved by the Human Research Committee of Anhui Medical University (ethical clearance number: 20170284). All participants provided informed consent before the study was commenced.

Definition of MetS

According to the International Diabetes Federation, MetS involves central obesity (waist circumference [WC] of ≥ 90 cm in Chinese males and ≥ 80 cm in Chinese females) with any two of the following factors: (1) hypertension (systolic blood pressure [SBP] of ≥ 130 mmHg, diastolic blood pressure [DBP] of ≥ 85 mmHg, or known treatment for hypertension), (2) hypertriglyceridemia (fasting serum triglyceride [TG] level of ≥ 1.7 mmol/L), (3) low high-density lipoprotein cholesterol (HDL-C; fasting HDL-C of < 1.0 mmol/L in males and < 1.3 mmol/L in females), and (4) hyperglycemia (fasting blood glucose [FBG] level of ≥ 5.6 mmol/L [≥ 100 mg/dL] or known treatment for diabetes mellitus) [22].

Collection of serum samples and data

All investigators were consistently trained by professionals, and the questionnaire was administered face to face. Data on the demographics, lifestyles, disease history, height, weight, WC, and blood pressure of the participants were collected. Fasting for 8 h prior to biospecimen collection was requested of participants. Biochemical data were also collected and analyzed by professionals from specialized institutions, and test reports were issued. For more details on these measurements, please refer to our previous study [23]. After fasting, venous blood was collected and centrifuged at 3000 rpm for 5 min at 4 °C. The serum was then divided into several aliquots and stored at − 80 °C.

Measurement of TRP and its metabolites

In this study, a sensitive, reliable, and well-validated technique based on ultra-performance liquid chromatography tandem mass spectrometry was used to quantify TRP and its seven metabolites [24].

For additional methodological validation of our experiment, please refer to our previous study [24]. In summary, the limit of detection (LOD) was calculated as three times the signal-to-noise (S/N) ratio, revealing an LOD of 0.01 to 0.50 ng/mL for all analytes. Similarly, the limit of quantitation (LOQ) was calculated as 10 times the S/N ratio, revealing an LOQ of 0.05 to 1.00 ng/mL for all analytes.

Data analysis

Serum TRP and its metabolites below the LOD were replaced with LODs/\(\:\sqrt{2}\). Shapiro–Wilk and Levene tests were used to examine the normality and heterogeneity of the data. Differences in demographic characteristics between the MetS, dyslipidemia, central obesity, hyperglycemia, hypertension, and control groups were independently analyzed using the chi-square test or Mann–Whitney U test for univariate analysis.

Log10 transformations were performed on the serum concentrations of TRP and its metabolites and on their ratios. Multiple linear regression was used to determine the relationship between each metabolite and the components of MetS. A restricted cubic spline curve (RCS) was used to reflect the dose–response relationship between MetS and changes in TRP and its metabolites.

Binary logistic analysis was conducted to estimate the potential risk factors and identify the likely interactions between each analyte and MetS. We also conducted a sex-stratified analysis to examine the relationships between TRP metabolites and MetS. In different models, we included relevant covariates to account for potential confounding factors. Specifically, the selection of covariates for adjustment was based on variables deemed meaningful for the target outcomes, as outlined in Table S1. These covariates were also explained in the comments section of the relevant results chart or table. These covariates were chosen based on prior knowledge and their potential to influence the relationship between the exposure and the outcomes.

All statistical analyses were conducted using IBM SPSS Statistics version 23.0 (IBM, Armonk, NY, USA). Dose–response curves were visualized using R software version 4.1.0 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided P value less than 0.05 was considered statistically significant.

Results

Characteristics of the Study Population and Concentration distribution of TRP and its metabolites

The ages (mean ± SD) of the participants in the total population, older adults with MetS, and older adults without MetS were 71.13 ± 6.72, 71.05 ± 6.16, and 72.14 ± 6.46 years, respectively. Independent samples t-test analysis showed a significant difference between the groups (P = 0.03). Table S1 provides a summary of the demographic characteristics of the study population. Covariates with P < 0.05 were used as influencing variables for the outcomes. Age, sex, region of residence, per-capita income, smoking habits, drinking habits, dietary structure, and sugar consumption contributed to MetS. Figure 1 shows the concentration distribution of TRP and its metabolites. The average concentrations (nmol/L) of TRP, KYN, KA, XA, 5-HT, IPA, and IAA were 37 905, 2506, 83.40, 138.00, 488.08, 1952, and 2112, respectively. TA exhibited the lowest concentration (0.674 nmol/L).

Fig. 1
figure 1

Distribution of serum tryptophan metabolites. Technique based on ultra-performance liquid chromatography tandem mass spectrometry was used to quantify TRP and its 7 metabolites. The average concentrations of TRP, KYN, KA, XA, 5-HT, IPA, and IAA were 37 905, 2506, 83.40, 138.00, 488.08, 1952, and 2112 nmol/L, respectively, with TA exhibiting the lowest concentration (0.674 nmol/L). TRP: tryptophan; KYN: kynurenine; KA: kynurenic acid; IAA: indoleacetic acid; IPA: indolepropionic acid; XA: xanthurenic acid; 5-HT: 5-hydroxytryptamine; TA: tryptamine

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Relationship between the metabolites of MetS and its components

Distribution of analytes between older adults with MetS and older adults without MetS

According to the results of our Mann–Whitney U test (Tables S2 to S6), older adults with MetS exhibited higher levels of TRP, KYN, KA, and XA, but lower levels of 5-HT and 5-HT/TRP ratios compared with older adults without MetS. Older adults with hypertension exhibited significantly higher KA levels and KA/KYN ratios but lower XA/TRP ratios compared with older adults without hypertension. Older adults with dyslipidemia exhibited higher levels of TRP, KYN, KA, and XA, but lower IPA/TRP ratios compared with older adults without dyslipidemia. Older adults with central obesity exhibited higher levels of TRP, KYN, KA, and XA, but lower levels of TA and IAA, and lower IAA/TRP ratios compared with older adults without central obesity. Older adults with hyperglycemia exhibited significantly higher KA levels, but slightly lower levels of TA and IAA, and lower IAA/TRP ratios compared with older adults without hyperglycemia.

Relationship between analytes and MetS components

After covariates were adjusted for, multiple linear regression (Fig. 2) revealed that higher levels of TRP, KA, and TA were associated with an increase in blood pressure. Higher levels of TRP, KYN, KA, XA, and IAA were also associated with an increase in TG levels. Similarly, higher levels of TRP, KYN, KA, XA, and TA were associated with an increased risk of central obesity. By contrast, higher levels of 5-HT were associated with a decrease in SBP, FBG, WC, and HDL-C. The potential activity of IDO and TDO had a positive effect on the regulation of blood lipids, while the activity of KAT increased the levels of FBG. However, the levels of TGs were negatively correlated with the activity of KAT and tryptophan 2-monooxygenase (TMO). In addition, the potential activity of TPH was negatively correlated with blood pressure, central obesity, and blood lipids.

Fig. 2
figure 2

The association between the change of tryptophan with its metabolites and the components of MetS. Model 1: Covariates included age, sex. Model 2: Covariates included age, sex, region, educational level, occupational history, per capita income, physical activity, drinking in SBP and DBP; Covariates included age, sex, skinfold thickness, hip circumference, body mass index (BMI), consumption of sugar, smoking, drinking, region, occupational history in FBG; Covariates included age, sex, physical activity, per capita income, region, occupational history, consumption of sugar, smoking, drinking, sleep time, depression in WC; Covariates included age, sex, per capita income, region, occupational history, educational level, consumption of salt, smoking, drinking, hip circumference, skinfold thickness, physical activity in HDL-C and TG. MetS: metabolic syndrome; SBP: Systolic blood pressure, DBP: Diastolic blood pressure; FBG: fasting blood glucose; WC: waist circumference; HDL-C: high-density lipoprotein cholesterol; TG: triglyceride; TRP: tryptophan; KYN: kynurenine; KA: kynurenic acid; IAA: indoleacetic acid; IPA: indolepropionic acid; XA: xanthurenic acid; 5-HT: 5-hydroxytryptamine; TA: tryptamine. * Statistically significant association (P-value < 0.05)

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Dose–response relationship between analytes and MetS

After age, sex, region of residence, smoking habits, drinking habits, and dietary structure were adjusted for, 4 nodes were selected for RCS analysis (Figure S3). A significant nonlinear relationship was observed between MetS and TRP, KYN, and KA. When the inflection point of log-TRP increased to 3.9, the risk of MetS was increased. Similarly, when the inflection point of log-KYN reached approximately 2.7, the risk of MetS gradually increased. When the inflection point of log-KA reached 1.2, the risk of MetS exhibited a significant positive correlation with the change of KA. Overall, the levels of TRP, KYN, and KA exhibited a significant dose–response relationship with MetS.

Analysis of target analytes and MetS risk

As shown in Table 1, the first tertile of TRP and its metabolite concentrations was used as the reference group to examine the relationship between concentration changes and the risk of MetS, with tertiles 2–4 being compared to it in the analysis. Adjusted analysis revealed that higher levels of TRP were associated with an increase in the risk of MetS. Similarly, with age and sex adjusted for, higher levels of KYN (tertile 4: OR = 2.047, 95% CI = 1.403, 2.987) were associated with an increase in the risk of MetS. After other covariates were adjusted for, the same trend was observed for KYN (tertile 4: OR = 1.746, 95% CI = 1.132, 2.693). In addition, with age and sex adjusted for, higher levels of KA were associated with an increase in the risk of MetS. By contrast, with other covariates adjusted for, KA was associated with an increase in the risk of MetS (tertile 4: OR = 2.291, 95% CI = 1.463, 3.586). Adjusted analysis revealed that higher levels of XA were associated with an increase in the risk of MetS. Overall, our results indicated that TRP, KYN, KA, and XA may be potential risk factors for MetS.

Table 1 Association of the concentrations of tryptophan metabolites with metabolic syndrome by binary logistic regression in the elderly
Full size table

We conducted adjusted analyses using TRP and its metabolites as continuous variables (Table S7). In these analyses, the associations between TRP, its metabolites, and MetS risk remained significant (e.g., TRP, KYN, KA, XA, 5-HT, and 5-HT/TRP). However, we also observed differences in the results for certain metabolites (e.g., IPA/TRP). Classification methods may more effectively reflect the risk associated with these specific metabolites.

With age and sex adjusted for, higher levels of TA (tertile 3: OR = 1.559, 95% CI = 1.070, 2.271) and KYN/TRP ratios (tertile 4: OR = 1.474, 95% CI = 1.009, 2.154) were associated with an increase in the risk of MetS. By contrast, higher levels of 5-HT (tertile 4: OR = 0.653, 95% CI = 0.449, 0.951) were associated with a decrease in the risk of MetS. With age and sex adjusted for, the 5-HT/TRP ratio and IPA/TRP ratio (tertile 3: OR = 0.732, 95% CI = 0.502, 1.066) were associated with a decrease in the risk of MetS. Similarly, with other covariates adjusted for, the 5-HT/TRP ratio (tertile 4: OR = 0.619, 95% CI = 0.398, 0.962) and IPA/TRP ratio were associated with a decrease in the risk of MetS. Overall, our results indicated that TPH and aromatic amino acid aminotransferase (ArAT) may be protective factors against MetS.

Sensitivity analysis and sex-stratified analysis of target analytes and MetS risk

The results of the sensitivity analyses (Table S8) align with the primary outcome observed in the full cohort study, which excluded participants who had received medication in the preceding month.

Sex-stratified analysis (Table 2) revealed that higher levels of TA (tertile 2: OR = 1.247, 95% CI = 0.562, 2.769) were associated with an increase in the risk of MetS in males. By contrast, higher IPA/TRP ratios (tertile 2: OR = 0.436, 95% CI = 0.204, 0.932) were associated with a decrease in the risk of MetS. In females, higher levels of TRP (tertile 2: OR = 1.651, 95% CI = 0.960, 2.839]; tertile 3: OR = 1.647, 95% CI = 0.955, 2.840]; tertile 4: OR = 2.280, 95% CI = 1.288, 4.035), KYN (tertile 4: OR = 1.759, 95% CI = 1.018, 3.038), KA (tertile 4: OR = 3.098, 95% CI = 1.761, 5.452), and XA (tertile 3: OR = 1.716, 95% CI = 1.007, 2.925) were associated with an increase in the risk of MetS, whereas higher 5-HT/TRP ratios (tertile 2: OR = 0.502, 95% CI = 0.290, 0.869]; tertile 4: OR = 0.520, 95% CI = 0.296, 0.915) were associated with a decrease in the risk of MetS. Overall, our results indicated that the levels of TA influence the risk of MetS in both males and females. However, ArAT may serve as a protective factor against MetS in males only, and TPH may have a protective effect against MetS in females only.

Table 2 Sex-stratified analysis in the association of serum tryptophan metabolites with metabolic syndrome
Full size table

Discussion

In this study, the serum concentrations of TRP and its metabolites were measured among older adults. The relationships between the metabolites of TRP in three major metabolic pathways and MetS were also examined, and the relationship between TRP metabolism and MetS was comprehensively investigated. Overall, our findings may serve as a valuable reference for further studies on the mechanisms underlying the relationship between TRP metabolism and MetS development in older adults. Notably, the KYN/TRP, 5-HT/TRP, and IPA/TRP ratios represent the conversion ratios between metabolites in a metabolic pathway and the potential activity of the participating enzymes. Among these ratios, the 5-HT/TRP ratio is significantly correlated with MetS. Therefore, profiling serum TRP metabolites may serve as an indicator of age-related diseases, including MetS.

As shown in Table S1, the prevalence of MetS among our participants was 40.16%, which is higher than that reported in middle-aged and older individuals in eastern China (34.39%) [25], presumably because our participants were above 60 years of age. According to the National Health and Nutrition Examination Survey, the prevalence of MetS increases with age [26]. In a previous study, Ma et al. reported that the prevalence of MetS was lower among those with a higher level of education [5]. In this study, we discovered that factors such as age, sex, region of residence, per capita income, smoking habits, drinking habits, sugar consumption, BMI, hip circumference, and skinfold thickness correlated with MetS in older adults.

Dysregulation of KYN metabolism is presumably one of the mechanisms of MetS development [27]. Consistent with the results of a previous study [13], after adjusting for covariates, we found that higher levels of KYN, KA, and XA were associated with MetS. MetS induces obesity-associated immune-mediated systemic inflammation through the KP, and chronic immune-mediated inflammation induces the upregulation of IDO, which may serve as a key component in the initiation and transmission of obesity and MetS [28]. We discovered that the levels of KYN and XA positively correlated with WC and blood lipids. We also found that the levels of KYN increased in older adults with hypertension [29]. Generally, the metabolism of KYN to KA by KAT may affect the onset of hypertension, and higher levels of KA and XA may hamper the synthesis of proinsulin and the release of insulin from pancreatic islets, thus increasing the levels of FBG and contributing to the development of diabetes [30]. In this study, we confirmed previous findings regarding a positive correlation between the levels of KA and FBG. As previously indicated, a positive correlation was observed between the KYN/TRP ratio and the levels of TG in older adults with MetS [9]. Consistent with a study conducted in Finland, Pertovaara et al. reported that the KYN/TRP ratio positively correlated with WC and TG levels [31]. In addition, because of their pro-oxidant, prediabetic, and pro-obesity effects, higher levels of KYN and KA contributed to the development of MetS [32]. Statistically significant relationship was not observed between changes in the KYN/TRP ratio and the risk of MetS in this study. We assumed that these covariates, which included age, sex, and other factors, had a significant effect on MetS.

Generally, 5-HT is a multifunctional biogenic amine. In a previous study, Huang et al. reported that, during the induction and development of MetS, the plasma levels of 5-HT significantly decreased in obese C57BL/6J mice fed with a high-fat diet [14].We discovered that the 5-HT/TRP ratio and 5-HT levels negatively correlated with SBP. Thus, we assumed that the activity of TPH negatively correlated with the development of hypertension. Consistent with previous studies [33,34,35], the levels of 5-HT decreased in the MetS and central obesity groups and negatively correlated with FBG, WC, and HDL-C levels. 5-HT in the central nervous system controls mood and metabolism and plays a vital role in balancing energy. Inhibition of intestinal 5-HT production leads to decreased body weight and improved metabolic dysfunction [36]. We discovered that the 5-HT/TRP ratio decreased in the MetS and central obesity groups, suggesting that TPH may serve as a biomarker for MetS and central obesity. However, rather than being a direct diagnostic marker, TPH could be explored as a tool for better understanding the pathophysiology of MetS and central obesity. In contrast to a previous study [35], we observed no positive correlation between the levels of 5-HT and TGs, which may be due to a combination of factors such as differences in study population characteristics, measurement methods, or other unmeasured variables.

According to previous studies, indole metabolites, particularly IAA, exhibit protective effects against MetS complications [37, 38]. These protective effects of indoles may be attributable to their local action on the intestine, which involves promoting the production of interleukin-22 and stimulating the production of glucagon-like peptide-1 by enteroendocrine L cells [39]. Our results indicated that the IAA/TRP ratio was significantly lower in the central obesity group than in the control group, suggesting that the activity of TMO was suppressed in the central obesity group. In addition, we discovered that a higher IPA/TRP ratio, a marker of ArAT activity, was associated with a lower risk of MetS. These results suggest that the activity of TMO or ArAT may be associated with MetS, but longitudinal studies are required to establish whether these changes in TRP metabolism contribute to the development of MetS.

Consistent with a previous study [25], we discovered that MetS was more prevalent among females than among males. Badawy and Dougherty reported an increase in free plasma TRP in females, with no sex-related differences in the levels of KYN [40]. We discovered that higher levels of TRP and its metabolites in the KP, such as KYN, KA, and XA, increased the risk of MetS in older females, with potential factors adjusted for. In addition, the 5-HT/TRP ratio exhibited a protective effect against MetS, indicating that TPH influences the prevalence of MetS in females. By contrast, TA served as a risk factor for MetS in older males, and the IPA/TRP ratio played a protective role against MetS.

To the best of our knowledge, this is the first study to examine the potential effects of serum TRP, the key metabolites of its three major metabolic pathways, and the enzymes that promote its metabolic catabolism on the risk of MetS in older adults. Profiling serum TRP metabolites could offer additional, complementary insights by capturing biochemical changes at the molecular level that may not be reflected in traditional measures such as WC. In addition, the present study has some limitations that must be acknowledged. First, although traditional markers such as WC, weight, and triglycerides remain critical for diagnosing MetS, IDO, TPH, and ArAT may provide additional molecular insights and serve as complementary biomarkers, potentially identifying MetS in earlier or subtler stages. Additional clinical cases are needed to determine whether IDO, TPH, and ArAT can be used as diagnostic markers of MetS. Second, we did not verify the roles of TRP and its metabolites in vivo by using animal models. Although no causative relationship has yet been fully elucidated, our results confirmed that the metabolites of the TRP pathway play a key role as potential markers of MetS. Finally, the current study’s sample was drawn from a single region, and its cross-sectional design may limit the generalizability of the findings and the ability to draw causal inferences. Therefore, future research should consider adopting a multicenter, longitudinal design to include a more diverse group of older adults and provide deeper insights into the long-term progression of the disease.

Conclusion

In conclusion, changes in TRP and its metabolites (KYN, KA, XA) are linked to an increased risk of central obesity and hypertension, and show a positive correlation with MetS. Enzymes involved in the TRP metabolic pathway, such as IDO, TPH, and ArAT, may serve as potential biomarkers for MetS.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors would like to thank all the staff and students who contributed to the study. They would also like to thank all the study participants for their support. In addition, they would like to sincerely thank all the members of the experimental center platform of Anhui Medical University.

Funding

This work was supported by the National Natural Science Foundation of China (82073558), Research Fund for Scientific Research Level Improvement Plan of Anhui Medical University (2022xkjT007), the project from the Center for Big Data and Population Health of IHM Project in School of Public Health of Anhui Medical University (JKS2023018), Key Research and Development Plan of Anhui Province (2022e07020029), and MOE Key Laboratory of Population Health across Life Cycle (JK20215).

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Author notes

  1. Shujing Sun and Fangting Hu authors have contributed equally to this work and share first authorship.

Authors and Affiliations

  1. School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, Anhui, 230032, China

    Shujing Sun, Fangting Hu, Yanru Sang, Jiafeng Shi, Fangbiao Tao & Kaiyong Liu

  2. Center for Scientific Research, Anhui Medical University, Hefei, Anhui, 230032, China

    Sheng Wang

  3. Hefei Hospital affiliated to Anhui Medical University (Hefei Second People’s Hospital), Hefei, Anhui, 230011, China

    Xuechun Liu

  4. Lu’an Center of Disease Control and Prevention, Lu’an, Anhui, 237000, China

    Hongjuan Cao

  5. Center for Big Data and Population Health, Institute of Health and Medicine, Hefei, Anhui, 230032, China

    Fangbiao Tao & Kaiyong Liu

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  1. Shujing Sun
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Contributions

Shujing Sun contributed to formal analysis, data curation, and manuscript writing. Fangting Hu contributed to research investigation and data curation. Yanru Sang contributed to research investigation and data curation. Sheng Wang and Hongjuan Cao contributed to research investigation, data curation, and resource management. Xuechun Liu and Jiafeng Shi contributed to research investigation. Fangbiao Tao contributed to data validation, conceptualization, and study supervision. Kaiyong Liu contributed to research investigation, conceptualization, methodology, and study supervision.

Corresponding author

Correspondence to Kaiyong Liu.

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Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Human Research Committee of Anhui Medical University (ethical clearance number for the population study: 20170284; Approval date: 1 March 2016). Informed consent was obtained from all subjects involved in the study.

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Sun, S., Hu, F., Sang, Y. et al. Dysregulated tryptophan metabolism contributes to metabolic syndrome in Chinese community-dwelling older adults. BMC Endocr Disord 25, 7 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12902-024-01826-8

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Keywords

BMC Endocrine Disorders

ISSN: 1472-6823

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