Conjugated Bile Acids and Their Interactions With Abdominal Obesity for Increased Risk of Insulin Resistance in Chinese Childhood and Adolescence

Conjugated Bile Acids and Their Interactions With Abdominal Obesity for Increased Risk of Insulin Resistance in Chinese Childhood and Adolescence | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Conjugated Bile Acids and Their Interactions With Abdominal Obesity for Increased Risk of Insulin Resistance in Chinese Childhood and Adolescence Weijiao Wang, Xinyi Zhang, Zhenghao Zhao, Xuemei Zhang, Xianglin Guo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7441483/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective: This study aimed to explore associations of conjugated bile acids in childhood and adolescence with insulin resistance (IR), and whether high conjugated bile acids and abdominal obesity had interactive effects on the risk of IR. Methods: A cross-sectional study was conducted on 606 young individuals, aged 7 to18 years in Tianjin City, China. MS metabolomic analysis was used to measure conjugated bile acids levels. The Homeostasis Model Assessment was used to estimate insulin resistance. Waist circumference measurements were used to assess abdominal obesity. Logistic regression models were employed to explore the relationships between conjugated BAs and IR. Interactions between conjugated BAs and abdominal obesity for IR were examined using additive interaction measures. Results: Compared to their counterparts, six specific conjugated bile acids were significantly different in childhood and adolescence with IR. The high levels of serum GCA, TCA, GCDCA, TCDCA, GDCA, TDCA and GLCA were significantly associated with IR after adjustment (OR: 2.43(1.44-4.14), 0.65(0.40-0.72), 1.83 (1.10-3.09), 1.75 (1.04-2.95), 2.00(1.20-3.33) and 1.88 (1.14-3.11), respectively). The presence of abdominal obesity markedly increased the ORs of high GCA, GCDCA, GDCA and GLCA alone up to 11.31(5.11-25.07), 8.75(4.95-15.48), 8.56(3.19-13.50) and 7.85(4.13-11.38) for the risk of IR, with significant additive interaction. Conclusion: Serum GCA, GCDCA, TCDCA, GDCA and GLCA in childhood and adolescence were positively associated with the risk of IR, and serum TCA was negatively associated with the risk of IR. High levels of GDCA, GCDCA, GDCA and GLCA enhanced the risk association of abdominal obesity with IR. conjugated bile acids insulin resistance abdominal obesity childhood adolescence Figures Figure 1 INTRODUCTION Insulin Resistance (IR) is defined as the inability of known amounts of insulin to increase the utilization of glucose by peripheral tissues (muscle, liver, adipose tissue, etc.) [ 1 ] . In recent years, large amounts of studies have confirmed that IR is a common phenomenon in children and adolescents [ 2 ] , and the frequency of this condition is increasing dramatically in developed countries [ 3 ] . In addition, race also plays a role in sensitivity to IR, with Hispanics, South Asians, and Indians at higher risk than Non-Hispanic Blacks and Non-Hispanic Whites [ 4 ] . IR has been recognized for many years as a major contributor to impaired glucose metabolism, type 2 diabetes (T2DM), and cardiovascular disease [ 5 ] , and has been identified as a key link between obesity and increased risk of chronic disease. Currently, researches have found that the incidence of diabetes in China is trending towards younger ages. [ 6 ] The prevalence of pre-diabetes among the 7–17 age group in China is 14.9% [ 7 ] . It is worth noting that the incidence of diabetes in children under 5 years old in China has increased sharply, with an increase of 33.61% [ 7 ] . The increasing prevalence of metabolic diseases will inevitably bring heavy burden and great challenge to the life, health and social economy of Chinese residents. Bile Acids as an important component of bile, are the final products synthesized by a series of enzymatic reactions in the liver with cholesterol as raw material [ 8 – 9 ] . As a signaling molecule and metabolic regulator, bile acids can regulate hepatic lipid, glucose and energy homeostasis and maintain metabolic homeostasis [ 10 ] . BAs includes primary bile acids and secondary bile acids, and primary bile acids produce secondary bile acids under the action of intestinal flora [ 11 ] . According to the different structure, bile acids can be divided into two types: free bile acids and conjugated bile acids. The gut microbiome is able to conjugate glycine and taurine with free bile acids, representing a new group of " conjugated bile acids" ( As shown in Fig. 1) [ 12 ] . At first, it was found that bile acids play an important role in metabolic regulation and is closely related to the occurrence of diabetes [ 13 – 14 ] . Subsequently, studies have shown that abnormal metabolism of conjugated bile acids is also associated with T2DM and pre-diabetic states, including impaired glucose tolerance (IGT) and IR [ 15 ] , but most studies are limited to adults. IR tends to appear around puberty, and the increased accumulation of fat around the abdominal viscera plays a role in this process. Abdominal obesity is also a key indicator of metabolic syndrome and a key factor leading to IR. Recent studies have even found that conjugated bile acids play an important role in the digestive process, especially in the digestion and absorption of fat. Studies have reported that conjugated bile acids are closely related to liver fat inflammation, because abnormal accumulation of conjugated bile acids can affect liver fat inflammation [ 16 – 17 ] . Maintaining a normal balance of conjugated bile acids metabolism is essential for liver health and overall metabolism. In view of the existing studies, we believe that it is of great significance to investigate the effects of conjugated bile acids and abdominal obesity on metabolic abnormalities in early life for the prevention and treatment of human metabolic diseases in the future. In the present study, we used a cross-sectional study was conducted on 606 young individuals in Tianjin City, China to explore: (1) the association of conjugated bile acids levels and IR; and (2) the interactive effects between high conjugated bile acids levels and abdominal obesity on the risk of IR. MATERIALS AND METHOD Data collection This data was collected from outpatients and inpatients of the Department of Endocrinology, Pediatrics, Tianjin Medical University General Hospital from August 2022 to November 2023, with a total of 606 valid samples. All participants provided written informed consent prior to data collection. The data included basic information and blood biochemical testing. Blood biochemical testing was conducted in a specialized diagnostic laboratory and analyzed using a fully automated biochemical analyzer (Hitachi 7150, Tokyo, Japan). After fasting for 8 hours, venous blood was drawn from each participant between 8 am and 9:30 am. All staff members received training in a series of workshops before the field survey, standardizing all procedures and using a series of questionnaires to collect data. Basic information of children included two parts: individual information and biochemical information. Personal information of children included demographic information, physical examination results, medical history, etc. Additionally, we also gathered data on the children’s feeling upon waking (Energetic, Tired, Hard) and learning capabilities (Easy, General, Difficult, Others). Biochemical test information for the children included triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), fasting blood glucose, fasting insulin, etc. Metabolomics analysis of serum bile acid components Sample pretreatment The plasma was separated and stored at -80℃. The stored plasma sample was thawed at 4°C, 50 µL was absorbed, and 10 µL of internal standard solution with a concentration of 2 µg/ml was added. After swirling the mixture for 1 minutes, add 300 µL cold protein precipitate (methanol solution containing 0.1% ammonia) and swirl the mixture again for 1 minutes. After centrifugation at 12500 rpm for 10 minutes, the obtained supernatant was 200µL, dried with nitrogen, redissolved in a solution of 50µL mixed solution (methanol: acetonitrile 8:2). Take 5µL for each injection. LC-MS/MS analysis The LC-MS analysis was performed using the Eksigent ultra LC 100 liquid phase tandem Triple TOF 5600 (AB SCIEX) mass spectrometry system. Negative ion detection mode, C18 BEH column (2.1 * 100mm, 1.7 µ m; Waters) was selected as the chromatographic column, and the pressure of the gas curtain and ion source Gas1 and Gas2 was set to 30, 50, and 50 psi, respectively. The column temperature was 40 degrees Celsius. The ion source temperature was 550℃ and the ion spray floating voltage (ISVF) was set to -4500V. Scanning time set at 100 ms; TOF-MS collision energy and declustering voltage were set to -10 V and − 80 V respectively, while -IDA collision energy and declustering voltage were set to -45 V and − 80 V respectively. The mass-charge ratio ranges for mass spectrum scanning and ion fragment scanning were set to 200-800Da and 50-800Da, respectively. Mobile phase A was formic acid aqueous solution containing 10 mM amine acetate (0.1%, v/v), mobile phase B was methanol: acetonitrile 8: 2 Solution, total flow rate 0.4 mL/min, gradient elution Settings :0-0.5 minutes (35% B), 0.5-3 minutes (35–60% B), 3–10 minutes, (60–80% B), 10–16 minutes, (80–90% B), 16-20.5 minutes, (90 − 35% B), 20.5–23 minutes (35% B). Target bile acids were identified using Peak View 1.2 and quantified using Multiquant2.1. Clinical definition Abdominal obesity is estimated according to the critical waist circumference of Chinese (WS/T611—2018) children and adolescents [ 18 ] . IR was evaluated using HOMA-IR index, HOMA-IR = fasting insulin × fasting blood glucose ÷ 22.5 [ 19 ] . Statistical Analysis Statistical analysis was performed using R 4.1.0. Quantitative data are expressed as median (interquartile distance [IQR]) and categorical data as n (%) when appropriate. We used paired T-tests or Kruskal-Wallis signed rank tests (which reject a normal distribution by examining a Q-Q plot) to compare differences in continuous variables, and Chi-square tests or Fisher precision tests (where appropriate) to compare the proportion differences between groups with abdominal obesity and those without. In univariate and multivariate analyses, conditional binary logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for bile acid levels and risk of abdominal obesity. FDR was used to correct P-values. Binary logistic regression was performed to obtain bile acid odds ratio (OR) and 95% CI for IR. Because the conjugated bile acids were roughly linearly associated with the risk of IR, we divided them into 3 groups according to their tertiles. The confounding factors were controlled by structural adjustment scheme. First, we performed a univariate analysis to obtain unadjusted odds ratios (OR) and 95% confidence intervals (95% CI). Second, we adjusted for basic information, including age, sex, family income, waking feeling, learning capabilities, exercise status, systolic blood pressure (SBP), diastolic blood pressure (DBP), LDL-C, HDL-C, TG, TC. Finally, we used additive interaction to test the interaction effect of high bile acids and abdominal obesity on IR. Three metrics were used to test the relative excess risk of the interaction (RERI), interaction (AP), and synergy index (SI). If any of RERI > 0, AP > 0, or SI > 1 is statistically significant, the additive interaction is considered significant. RESULTS In this study, a total of 606 participants were included, with 283 children identified as having IR. The average age of the IR group was 12 years, with an average height of 155.3 cm, weight of 60.2 kg, waist circumference of 76 cm, and hip circumference of 90 cm. Furthermore, 51.9% of the children in the IR group were boys. In contrast, the average age of the non-IR group was lower (10 years), with smaller measurements of height (140.2 cm), weight (37.1 kg), waist circumference (62 cm), and hip circumference (73 cm). It is worth noting that there were significant differences in SBP, DBP, TC, Fasting blood glucose and insulin between the two groups, with higher values in the IR group. On the contrary, HDL-C was lower in the IR group Additionally, a higher proportion of children in the IR group had average or below-average learning ability and no exercise. There were no significant differences in other characteristics between the two groups. Regarding the differences in conjugated bile acids, the study results showed that the levels of GCA, GCDCA, TCDCA, GLCA and GDCA were significantly higher in the IR group than in the normal group. However, the level of TCA was lower in the IR group. There was no significant difference in TLCA and TDCA levels between the two groups. (Table 1 and Table 2 ). Table 1 Basic characteristics of the subjects. Characteristics Normal Insulin Resistance P value Number of subjects 323 283 Age (years) 10 (3) 12 (2) < 0.01 Boys 148 (45.8) 147 (51.9) 0.16 Height (cm) 140.2(17.8) 155.3 (13.4) < 0.01 Weight (kg) 37.1 (15.0) 60.2 (21.0) < 0.01 Waist (cm) 62[55, 69] 76 [66, 89.5] < 0.01 Hip (cm) 73 [65, 82] 90 [78, 103] < 0.01 DBP (mmHg) 67 [63, 72] 72 [67, 78] < 0.01 SBP (mmHg) 105 [99, 112] 116[106, 123] < 0.01 Income (thousand yuan) 0.16 ≤ 50 16 (5.0) 20 (7.1) 50 ~ 100 49 (15.2) 34 (12.0) 100 ~ 150 99 (30.7) 102 (36.0) 150 ~ 200 86 (26.6) 57 (20.1) ≥ 200 73 (22.6) 70 (24.7) Getting up 0.18 Energetic 86 (26.6) 58 (20.5) Tired 223 (69.0) 209 (73.9) Hard 14 (4.3) 16 (5.7) Sports 0.02 Yes 262 (81.1) 206 (72.8) No 61 (18.9) 77 (27.2) Study < 0.01 Easy 246 (76.2) 180 (63.6) General 59 (18.3) 73 (25.8) Difficult 16 (5.0) 21 (7.4) Others 2 (0.6) 9 (3.2) IQR: interquartile range; SBP: systolic blood pressure; DBP: diastolic blood pressure; TG: triglyceride; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; Getting up: the feeling when waking up; Sports: exercise status; Study: learning ability. The Kruskal Wallis rank sum test for continuous variables with skewed distribution, Chi-square test (or fisher test if appropriate) for categorical variables. Data are presented as means ± SD, median (IQR) or n (%). P-value < 0.05 was defined as statistically significant. Table 2 Biochemical information of the subjects. Characteristics Normal Insulin Resistance (IR) P-value Number of subjects 323 283 TG (mmol/L]) 4.39 [3.83, 4.95] 4.20 [3.72, 4.81] 0.12 TC (mmol/L) 0.92 [0.66, 1.31] 1.20 [0.88, 1.64] < 0.01 HDL-C (mmol/L) 1.30 [1.10, 1.56] 1.18 [1.02, 1.38] < 0.01 LDL-C (mmol/L) 2.40 [2.03, 2.86] 2.44 [2.08, 2.94] 0.03 Fasting blood glucose (mmol/L) 4.12 [3.54, 4.64] 4.96 [4.71, 5.22] < 0.01 Insulin (pmol/L) 7.30 [4.90, 9.80] 19.70 [16.20, 28.60] < 0.01 GCA (median [IQR]) 36.80 [17.71, 83.27] 57.73[27.25, 118.98] < 0.01 TCA (median [IQR]) 162.79[157.69, 174.95] 159.50[156.41,169.47] < 0.01 GCDCA (median [IQR]) 347.85 [176.84, 886.79] 567.16[259.87,1039.4] < 0.01 TCDCA (median [IQR]) 76.46 [57.45, 124.03] 89.18 [66.29, 136.97] < 0.01 GLCA (median [IQR]) 47.93 [30.49, 75.58] 62.52 [40.74, 91.37] < 0.01 TLCA (median [IQR]) 10.37 [7.53, 14.56] 10.85 [7.42, 15.25] 0.67 GDCA (median [IQR]) 27.57 [11.87, 62.12] 37.39 [15.42, 82.36] 0.01 TDCA (median [IQR]) 44.67 [40.91, 50.99] 45.68 [41.27, 52.95] 0.06 IQR: interquartile range; SBP: systolic blood pressure; DBP: diastolic blood pressure; TG: triglyceride; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; GCA: Glycocholic acid; TCA: Taurocholic acid; GCDCA: Glycinodeoxycholic acid; TCDCA: Taurocholic acid; GDCA: Glycodeoxycholic acid; TDCA: Taurodeoxycholic acid; GLCA: Glycinocholic acid; TLCA: Taurocholic acid. HOMA-IR greater than or equal to 2.69 is defined as IR. The Kruskal Wallis rank sum test for continuous variables with skewed distribution, Chi-square test (or fisher test if appropriate) for categorical variables. Data are presented as means ± SD, median (IQR) or n (%). P-value < 0.05 was defined as statistically significant. The P-values were FDR corrected. In the univariate analysis, individuals in the highest quartile of serum GCA, GCDCA, TCDCA, GDCA, and GLCA exhibited significantly higher odds of insulin resistance (IR) compared to those in the lowest quartile (ORs: 1.92 [1.29–2.87], 2.33 [1.56–3.51], 1.90 [1.28–2.85], 1.88 [1.27–2.79], and 2.11 [1.42–3.14], respectively). Conversely, serum TCA was associated with significantly lower odds of IR at the highest quartile (OR: 0.67 [0.54–0.74]). After adjustment for potential confounders, the associations for the highest quartiles of serum GCA, TCA, GCDCA, TCDCA, GDCA, and GLCA remained statistically significant, with ORs of 1.96 (1.26–3.08), 0.88 (0.71–0.93), 2.40 (1.54–3.78), 1.74 (1.10–2.77), 1.86 (1.19–2.92), and 1.43 (1.13–2.24), respectively. In addition, univariate analysis showed that participants with abdominal obesity had significantly greater odds of IR compared to those without (OR: 5.56 [3.88–8.03]), and this association remained robust after adjusting for confounding variables (OR: 4.16 [2.69–6.51]) (Table 3 ). Table 3 Odds ratios of Conjugated Bile Acids and abdominal obesity for the risk of Insulin Resistance. Univariable model Multivariable model OR (95%CI) OR (95%CI) GCA, nmol/L < 20.0 Reference Reference ≥ 20.0-<46.6 1.37(0.86–2.17) 1.35(0.81–2.24) ≥ 46.6 1.92(1.29–2.87) * 1.96(1.26–3.08) * TCA, nmol/L < 156.9 Reference Reference ≥ 156.9-<161.8 1.37(0.86–2.17) 1.42(0.85–2.36) ≥ 161.8 0.67(0.54–0.74) * 0.88(0.71–0.93) * GCDCA, nmol/L ≥ 205.6 Reference Reference ≥ 205.6-<455.0 1.45(0.91–2.32) 1.50(0.90–2.50) ≥ 455.0 2.33(1.56–3.51) * 2.40(1.54–3.78) * TCDCA, nmol/L < 60.0 Reference Reference ≥ 60.0-<82.9 1.74(1.10–2.77) * 1.73(0.97–2.92) ≥ 82.9 1.90(1.28–2.85) * 1.74(1.10–2.77) * GDCA, nmol/L < 31.4 Reference Reference ≥ 31.4-<72.1 1.09(0.73–1.62) 1.11(0.71–1.72) ≥ 72.1 1.88(1.27–2.79) * 1.86(1.19–2.92) * GLCA, nmol/L < 34.5 Reference Reference ≥ 34.5-<55.7 1.90(1.28–2.83) 1.33(0.86–2.06) ≥ 55.7 2.11(1.42–3.14) * 1.43(1.13–2.24) * Abdominal Obesity <NO Reference Reference ≥YES 5.56(3.88–8.03) * 4.16(2.69–6.51) * The multivariable model adjusted for age, sex, family income, feelings on waking, learning ability, exercise status, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and total cholesterol. Abbreviations: GCA: Glycocholic acid; TCA: Taurocholic acid; GCDCA: Glycinodeoxycholic acid; TCDCA: Taurocholic acid; GDCA: Glycodeoxycholic acid; GLCA: Glycinocholic acid. * was defined as statistically significant. GCA concentrations ≥ 46.6 nmol/mL were independently associated with insulin resistance (IR) (OR: 1.69 [1.12–2.18]), and when co-occurring with abdominal obesity (OR: 3.36 [2.09–5.40]), the combined presence of both factors was associated with markedly elevated odds of IR (OR: 11.31 [5.11–25.07]), indicating a significant additive interaction (Attributable Proportion due to interaction, AP: 0.24 [0.12–0.67]). Similarly, GCDCA levels ≥ 455.0 nmol/mL were significantly associated with IR (OR: 1.83 [1.33–2.12]), and in combination with abdominal obesity (OR: 3.69 [2.16–6.30]), the joint exposure yielded an OR of 8.75 (4.95–15.48), with evidence of a significant additive interaction (AP: 0.53 [0.12–0.71]). In the case of GLCA concentrations ≥ 55.7 nmol/mL, the association with IR was also significant (OR: 1.92 [1.52–2.02]), and when accompanied by abdominal obesity (OR: 4.31 [2.36–7.85]), the OR for IR was 7.85 (4.13–11.38), with a significant additive interaction (AP: 0.17 [0.09–0.44]). Although GDCA levels ≥ 72.1 nmol/mL alone were not significantly associated with IR (OR: 2.01 [0.86–3.46]), the combined exposure with abdominal obesity (OR: 4.56 [2.81–7.39]) corresponded to an OR of 8.56 (3.19–13.50), and a significant additive interaction was observed (AP: 0.46 [0.28–0.59]) (Table 4 ). Table 4 Additive interaction of Conjugated Bile Acids with Abdominal Obesity for the risk of Insulin Resistance. Univariable model Multivariable model OR (95%CI) OR (95%CI) GCA < 46.6 nmol/L and Non-abo Reference Reference GCA ≥ 46.6 nmol/L and Non-abo 1.65(1.09–1.84) * 1.69(1.12–2.18) * GCA < 46.6 nmol/L and Abo 4.19(2.77–6.34) * 3.36(2.09–5.40) * GCA ≥ 46.6 nmol/L and Abo 13.29(6.53–27.07) * 11.31(5.11–25.07) * Interaction measure Estimates Estimates RERI 9.01 (2.35–22.53) 3.41(0.66–12.31) AP 0.68 (0.28–0.82) 0.24(0.12–0.67) SI 3.75(1.58–8.89) 2.12(0.44–5.26) GCDCA < 455.0 nmol/L and Non-abo Reference Reference GCDCA ≥ 455.0 nmol/L and Non-abo 1.76(1.18–1.82) * 1.83(1.33–2.12) * GCDCA < 455.0 nmol/L and Abo 3.62(2.21–5.95) * 3.69(2.16–6.30) * GCDCA ≥ 455.0 nmol/L and Abo 9.65(5.69–16.38) * 8.75(4.95–15.48) * Interaction measure Estimates Estimates RERI 5.98(1.96–12.17) 4.12(0.75–10.26) AP 0.61(0.26–0.77) 0.53(0.12–0.71) SI 3.09(1.45–6.57) 2.53(1.18–5.40) GDCA < 72.1 nmol/L and Non-abo Reference Reference GDCA ≥ 72.1nmol/L and Non-abo 1.83(0.92–3.03) 2.01(0.86–3.46) GDCA < 72.1 nmol/L and Abo 5.64(3.70–8.59) * 4.56(2.81–7.39) * GDCA ≥ 72.1 nmol/L and Abo 9.96(4.72–17.02) * 8.56(3.19–13.50) * Interaction measure Estimates Estimates RERI 3.11(2.78–10.97) 2.49(2.25–10.28) AP 0.68(0.36–0.81) 0.46(0.28–0.59) SI 1.87(1.01–3.79) 1.46(0.68–3.14) GLCA < 55.7 nmol/L and Non-abo Reference Reference GLCA ≥ 55.7 nmol/L and Non-abo 1.94(1.44–2.22) * 1.92(1.52–2.02) * GLCA < 55.7 nmol/L and Abo 4.5(2.55–7.93) * 4.31(2.36–7.85) * GLCA ≥ 55.7 nmol/L and Abo 8.12(5.02–13.13) * 7.85(4.13–11.38) * Interaction measure Estimates Estimates RERI 3.18(0.67–7.78) 2.12(0.33–6.23) AP 0.39(0.11–0.65) 0.17(0.09–0.44) SI 1.81(0.89–3.69) 1.51(0.34–2.35) The multivariable model adjusted for age, sex, family income, feelings on waking, learning ability, exercise status, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and total cholesterol. Abbreviations: AP, attributable proportion due to interaction; RERI, relative excess risk due to interaction; SI, synergy index; GCA: Glycocholic acid; GCDCA: Glycinodeoxycholic acid; GDCA: Glycodeoxycholic acid; GLCA: Glycinocholic acid; Abo: Abdominal Obesity; Non-abo: No Abdominal Obesity. Statistically signifcant, with RERI > 0, AP > 0, or SI > 1 indicating signifcant additive interaction. * < 0.05 was defined as statistically significant. DISCUSSION In recent years, in the study of human bile acids level and metabolic diseases, it has been found that individual conjugated bile acids are related to IR. In terms of primary bile acids. Studies have found that GCA, TCA, GCDCA and TCDCA play an important role in glucose metabolism [ 13 – 14 ] . TCA has been found to improve insulin resistance in both human and animal studies [ 20 – 21 ] . In a population cohort, GCA and GCDCA in Nonalcoholic fatty liver (NAFLD) are positively correlated with insulin resistance index [ 22 ] . At the same time, serum GCA and GCDCA were significantly positively correlated with the occurrence and development of diabetes in two cohort studies, the Chinese Cardiometabolic and Malignant Tumor Cohort Study and the Finnish Diabetes Prevention Study [ 23 – 24 ] . In both population studies and mouse models, TCDCA has been found to increase the risk of type 2 diabetes [ 25 – 26 ] . The study also explored how dietary changes affect bile acid metabolism and its subsequent IR, particularly changes in conjugated bile acids such as GCDCA and TCDCA. Studies have found that the reduction of GCDCA and TCDCA under dietary regulation is related to the improvement of glucose and insulin metabolism, indicating their role in metabolic regulation [ 26 ] . For secondary bile acids, it was found that GDCA was positively correlated with insulin resistance index in NAFLD population [ 27 ] . There are few studies on GLCA, and current studies have found that GLCA in diabetic patients is higher than that in non-type 2 diabetic people [ 28 ] . It can be seen that the combined primary and secondary bile acids have different effects on the organism, which is similar to our results. Our findings suggest that high levels of GCA, GCDCA, TCDCA, GDCA, and GLCA are associated with an increased risk of developing IR, while high levels of TCA are associated with a reduced risk of developing IR. Abdominal obesity refers to excessive accumulation of fat in the abdominal area, and this type of obesity is associated with a series of health problems, including IR. Abdominal visceral fat is easy to release free Fatty Acid (FFA) through lipid interpretation, and high levels of FFA can increase liver IR and interfere with glucose uptake in muscle tissue [ 29 ] . At the same time, the increase in FFA leads to the accumulation of fat in the liver, further aggravating IR [ 30 ] . To sum up, abdominal obesity can promote fat accumulation and energy balance imbalance through a variety of ways, ultimately leading to the occurrence and development of IR. Therefore, restraining abdominal obesity is one of the important measures to prevent and treat IR. Our results showed that only glycine-type bile acids interact with abdominal obesity, which was biologically plausible. Firstly, it has been confirmed in animal experiment that TCDCA promotes the occurrence of IR through the FXR axis [ 31 ] , and TCA may improve IR by inhibiting the NLRP3 inflammasome signaling pathway [ 32 ] . Secondly, studies have found that GCA and GLCA are positively correlated with liver steatosis and inflammation, [ 25 , 33 ] and GCDCA and GDCA are also important metabolic markers of liver inflammation [ 34 ] . Studies have found that increased inflammation may be related to the inhibition of IRS1/PI3K/AKT pathway [ 35 ] . Studies have also shown that GCDCA can promote oxidative stress [ 36 ] . Oxidative stress can inhibit the PI3K/Akt signaling pathway [ 37 ] . In addition, insulin activates insulin receptor substrates by binding to its receptor, thereby activating the PI3K/Akt signaling pathway and promoting glucose transport and metabolism [ 38 ] . This process is disrupted in the state of abdominal obesity [ 38 ] . Studies have proved that IRS1 is closely related to insulin metabolism, and AKT plays a central role in the IRS1/PI3K/ AKT signaling pathway. If IRS1/PI3K/Akt pathway is inhibited, it will cause IR [ 39 ] . Therefore, we speculate that there may be a potential regulatory relationship between glycine bile acids and the signaling pathway of abdominal obesity, and they may share key signaling molecules such as IRS1, PI3K, and Akt to achieve signal coordination. Functional regulation between these signaling pathways may enhance or modulate the biological effects of BAs and abdominal obesity through synergistic mechanisms, thereby jointly promoting cell growth, differentiation, or metabolic processes. When studying the biological functions and metabolic mechanisms of bile acids in depth, our results have a very noteworthy point: there are significant differences in the effects and mechanisms of different conjugated bile acids in vivo. This difference may be closely related to the types of amino acids they combine with. Firstly, glycine-conjugate bile acids typically have strong hydrophilicity, which makes them highly soluble in aqueous solutions and may increase the risk of liver inflammation. Second, taurine-conjugate bile acids have strong hydrophobicity, which makes them more soluble in lipid environments and may have stronger effects in regulating inflammation. The differential effects of different binding forms of bile acids are a complex and interesting research area that involves the synthesis, metabolism, transport, and interaction with intestinal microbiota of bile acids. A deeper understanding of these differences not only helps us better understand the role of bile acids in digestion and metabolism, but also may provide important scientific basis for developing new treatment strategies and drugs. Another noteworthy point is that in animal experiments, it has been confirmed that GDCA administration improves IR [ 40 ] , however, in NAFLD populations, GDCA is positively correlated with insulin resistance index [ 27 ] . This result is similar to our findings, as our interaction results show that when the body has high levels of GDCA without abdominal obesity, there is no obvious relationship with IR, but when abdominal obesity exists, the risk of developing IR will increase significantly. This suggests that abdominal obesity may be a critical regulatory factor that affects the impact of GDCA on IR. If abdominal obesity is a key factor in increasing the risk of IR, reducing abdominal fat through diet and exercise may help lower the risk of IR, even if GDCA levels are high. These findings provide new insights into the complex mechanisms of IR. Firstly, they suggest that a single biomarker or metabolite may not be sufficient to fully explain the occurrence of insulin resistance, and that the interaction of multiple factors needs to be considered, especially those closely related to lifestyle, such as abdominal obesity. In addition, these results may also have important implications for clinical practice, suggesting that physicians and health professionals should consider not only binding bile acid levels but also other factors such as abdominal obesity when assessing an individual's risk of insulin resistance. Finally, our findings have major public health implications. For example, they highlight the importance of reducing abdominal obesity in preventing insulin resistance and may encourage the development of more prevention and interventions targeting abdominal obesity. At the same time, this suggests the direction of future research to further explore how binding levels and abdominal obesity together affect the risk of insulin resistance. With these studies, we hope to develop more effective strategies to prevent and manage health problems associated with insulin resistance. There are some limitations to our findings. There are two limitations to our study. Firstly, due to the nature of cross-sectional studies, our findings need to be confirmed by future research. Secondly, some confounding factors in our samples have not been fully collected, such as medical histories of (maternal) grandparents, siblings' medical histories, and personal information, we do not rule out genetic influences on abdominal obesity and IR. CONCLUSION In summary, our study identified five specific conjugated bile acids—GCA, GCDCA, TCDCA, GDCA, and GLCA—whose serum concentrations were significantly associated with insulin resistance (IR) in children and adolescents. Elevated levels of these bile acids were positively associated with the risk of IR, whereas higher serum levels of TCA were inversely associated with IR risk. Furthermore, GCA, GCDCA, GDCA, and GLCA demonstrated significant additive interactions with abdominal obesity in relation to IR. It is necessary to explore the biological mechanisms behind these interesting observations. Abbreviations GCA Glycocholic acid TCA Taurocholic acid GCDCA Glycochenodeoxycholic acid TCDCA Taurochenodeoxycholic acid GDCA Glycodeoxycholic acid TDCA Taurodeoxycholic acid GLCA Glycolithocholic acid TLCA Taurolithocholic acid Declarations DISCLOSURE OF STATEMENT The authors have nothing to disclose. Declaration OF INTEREST STATEMENT The authors declared no conflict of interest. AUTHOR OF CONTRIBUTIONS W-FW substantially contributed to the conception and design of the work. X-YZ, Z-HZ and W-JW substantially contributed to acquisition of the data. X-YZ, and W-JW analyzed the data and drafted the article. X-MZ and X-LG revised the article critically for important intellectual content. All authors edited the final version of the manuscript. All authors contributed to the article and approved the submitted version. ETHICS STATEMENT This study was approved by Medical Ethics Committee of Tianjin Medical University General Hospital and Department of Pediatrics, Tianjin Medical University General Hospital, and all research activities were conducted in accordance with the principles of the Declaration of Helsinki. Prior to any research activity, we provided all participants (or their guardians) with detailed information regarding the purpose, procedures, potential risks, and benefits of the study, and obtained their written informed consent. The privacy and personal information of participants were protected, and any published research data does not contain information that could identify individual participants. FUNDING This research was supported by the National Key Research and Development Program of China (2021YFA1301202), General hospital Clinical research project (22ZYYLCCG03), Tianjin Key Medical Discipline (Specialty) Construction Project (TJWJ2022XK008, TJYXZDXK-068C), Tianjin Science and Technology Plan Project (22KPHDRC00120), and National Natural Science Foundation of China (Grant No: 82200932 & 82273676). Acknowledgement The authors thank all the physicians, nurses and research staff at the Tianjin Medical University General Hospital who participated in the study and extended their support for data collection. Data Availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. References Chiarelli F, Marcovecchio ML. Insulin resistance and obesity in childhood. Eur J Endocrinol. 2008;159:S67–74. Tobisch B, Blatniczky L, Schusterova I, Kovács L, Barkai L. Insulin resistance and its effects in children and adolescents. Orv Hetil. 2021;162:403–12. Stąpor N, Beń-Skowronek I. Insulinooporność u dzieci [Insulin resistance in children]. Pediatr Endocrinol Diabetes Metab. 2015;20:107–15. Maffeis C, Morandi A. Body composition and insulin resistance in children. Eur J Clin Nutr. 2018;72:1239–45. Litwin SE. Childhood obesity and adulthood cardiovascular disease: quantifying the lifetime cumulative burden of cardiovascular risk factors. J Am Coll Cardiol. 2014;64:1588–90. Wang J, Wu W, Dong G, Huang K, Fu J. Pediatric diabetes in China: Challenges and actions. Pediatr Diabetes. 2022;23:545–50. Wu HB, Zhong JM, Hu RY, Wang H, Gong WW, Pan J, et al. Rapidly rising incidence of Type 1 diabetes in children and adolescents aged 0–19 years in Zhejiang, China, 2007 to 2013. Diabet Med. 2016;33(10):1339–46. Chiang JY. Bile acid metabolism and signaling. Compr Physiol. 2013;3:1191–212. Cai J, Rimal B, Jiang C, Chiang JYL, Patterson AD. Bile acid metabolism and signaling, the microbiota, and metabolic disease. Pharmacol Ther. 2022;237:108238. Fiorucci S, Carino A, Baldoni M, Santucci L, Costanzi E, Graziosi L, et al. Bile Acid Signaling in Inflammatory Bowel Diseases. Dig Dis Sci. 2021;66:674–93. Zeng H, Umar S, Rust B, Lazarova D, Bordonaro M. Secondary Bile Acids and Short Chain Fatty Acids in the Colon: A Focus on Colonic Microbiome, Cell Proliferation, Inflammation, and Cancer. Int J Mol Sci. 2019;20:1214. Guzior DV, Quinn RA. Review: microbial transformations of human bile acids. Microbiome. 2021;9:140. Harach T, Pols TW, Nomura M, Maida A, Watanabe M, Auwerx J, et al. TGR5 potentiates GLP-1 secretion in response to anionic exchange resins. Sci Rep. 2012;2:430. Rao A, Kosters A, Mells JE, Zhang W, Setchell KD, Amanso AM, et al. Inhibition of ileal bile acid uptake protects against nonalcoholic fatty liver disease in high-fat diet-fed mice. Sci Transl Med. 2016;8:357ra122. Garruti G, Di Ciaula A, Wang HH, Wang DQ, Portincasa P. Cross-Talk Between Bile Acids and Gastro-Intestinal and Thermogenic Hormones: Clues from Bariatric Surgery. Ann Hepatol. 2017;16:s68–82. Gottlieb A, Bechmann L, Canbay A. The Presence and Severity of Nonalcoholic Steatohepatitis Is Associated with Specific Changes in Circulating Bile Acids. Ann Hepatol. 2018;17:340–1. Lin H, An Y, Tang H, Wang Y. Alterations of Bile Acids and Gut Microbiota in Obesity Induced by High Fat Diet in Rat Model. J Agric Food Chem. 2019;67:3624–32. Ma, Guansheng. Jicheng ye, Ma Jun. A study of waist circumference threshold points in Chinese school children and adolescents aged 7–18 years [J]. Chin J Epidemiol. 2010;31:609–15. Yan XX, Ying YW. The diagnostic significance of homeostasis model assessment of insulin resistance in metabolic syndrome among subjects with different glucose tolerance. Chin J Diabetes. 2004;3:31–5. Wu T, Bound MJ, Standfield SD, Jones KL, Horowitz M, Rayner CK. Effects of taurocholic acid on glycemic, glucagon-like peptide-1, and insulin responses to small intestinal glucose infusion in healthy humans. J Clin Endocrinol Metab. 2013;98:E718–722. Cheng Z, Liu G, Zhang X, Bi D, Hu S. Improvement of Glucose Metabolism Following Long-Term Taurocholic Acid Gavage in a Diabetic Rat Model. Med Sci Monit. 2018;24:7206–12. Kimberly WT, O'Sullivan JF, Nath AK, Keyes M, Shi X, Larson MG, Yang Q, et al. Metabolite profiling identifies anandamide as a biomarker of nonalcoholic steatohepatitis. JCI Insight. 2017;2:e92989. Lu J, Wang S, Li M, Gao Z, Xu Y, Zhao X, 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. de Mello VD, Paananen J, Lindström J, Lankinen MA, Shi L, Kuusisto J, Pihlajamäki J, et al. Indolepropionic acid and novel lipid metabolites are associated with a lower risk of type 2 diabetes in the Finnish Diabetes Prevention Study. Sci Rep. 2017;7:46337. Prinz P, Hofmann T, Ahnis A, Elbelt U, Goebel-Stengel M, Klapp BF, et al. Plasma bile acids show a positive correlation with body mass index and are negatively associated with cognitive restraint of eating in obese patients. Front Neurosci. 2015;9:199. Siow Y, Schurr A, Vitale GC. Diabetes-induced bile acid composition changes in rat bile determined by high performance liquid chromatography. Life Sci. 1991;49:1301–8. Nimer N, Choucair I, Wang Z, Nemet I, Li L, Gukasyan J, et al. Bile acids profile, histopathological indices and genetic variants for non-alcoholic fatty liver disease progression. Metabolism. 2021;116:154457. Mantovani A, Dalbeni A, Peserico D, Cattazzo F, Bevilacqua M, Salvagno GL, et al. Plasma Bile Acid Profile in Patients with and without Type 2 Diabetes. Metabolites. 2021;11:453. Zhao WG, Zhu HJ. [Mechanism, treatment, and evaluation of obesity-induced insulin resistance and type 2 diabetes]. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2010;32:7–12. Chinese. Skoczen S, Wojcik M, Fijorek K, Siedlar M, Starzyk JB. Expression of the central obesity and Type 2 Diabetes mellitus genes is associated with insulin resistance in young obese children. Exp Clin Endocrinol Diabetes. 2015;123:252–9. Zhang SY, Li RJW, Lim YM, Batchuluun B, Liu H, Waise TMZ, et al. FXR in the dorsal vagal complex is sufficient and necessary for upper small intestinal microbiome-mediated changes of TCDCA to alter insulin action in rats. Gut. 2021;70:1675–83. Ko CY, Lo YM, Xu JH, Chang WC, Huang DW, Wu JS, Yang CH, Huang WC, Shen SC. Alpha-lipoic acid alleviates NAFLD and triglyceride accumulation in liver via modulating hepatic NLRP3 inflammasome activation pathway in type 2 diabetic rats. Food Sci Nutr. 2021;9:2733–42. Chen L, van den Munckhof ICL, Schraa K, et al. Genetic and Microbial Associations to Plasma and Fecal Bile Acids in Obesity Relate to Plasma Lipids and Liver Fat Content. Cell Rep. 2020;33:108212. Luo L, Aubrecht J, Li D, Warner RL, Johnson KJ, Kenny J, et al. Assessment of serum bile acid profiles as biomarkers of liver injury and liver disease in humans. PLoS ONE. 2018;13:e0193824. Wang Y, Guo Y, Xu Y, Wang W, Zhuang S, Wang R, et al. HIIT Ameliorates Inflammation and Lipid Metabolism by Regulating Macrophage Polarization and Mitochondrial Dynamics in the Liver of Type 2 Diabetes Mellitus Mice. Metabolites. 2022;13:14. Wu Z, Geng Y, Buist-Homan M, Moshage H. Scopoletin and umbelliferone protect hepatocytes against palmitate- and bile acid-induced cell death by reducing endoplasmic reticulum stress and oxidative stress. Toxicol Appl Pharmacol. 2022;436:115858. Li J, Wang T, Liu P, Yang F, Wang X, Zheng W, et al. Hesperetin ameliorates hepatic oxidative stress and inflammation via the PI3K/AKT-Nrf2-ARE pathway in oleic acid-induced HepG2 cells and a rat model of high-fat diet-induced NAFLD. Food Funct. 2021;12:3898–918. Choi K, Kim YB. Molecular mechanism of insulin resistance in obesity and type 2 diabetes. Korean J Intern Med. 2010;25:119–29. Huang X, Liu G, Guo J, Su Z. The PI3K/AKT pathway in obesity and type 2 diabetes. Int J Biol Sci. 2018;14:1483–96. Qi X, Yun C, Sun L, Xia J, Wu Q, Wang Y, et al. Gut microbiota-bile acid-interleukin-22 axis orchestrates polycystic ovary syndrome. Nat Med. 2019;25:1225–33. Additional Declarations No competing interests reported. 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15:47:58","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126582,"visible":true,"origin":"","legend":"","description":"","filename":"cc08b2a1573443d49aa9acbf2fab39351structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7441483/v1/2ddb14b5d63b144ebbf99138.xml"},{"id":92428991,"identity":"7852bbb3-36d8-4ba3-9358-6aad55a2bdb6","added_by":"auto","created_at":"2025-09-29 15:39:58","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":134822,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7441483/v1/a3414cd0d016440f98e5977b.html"},{"id":92428986,"identity":"910d3ec9-4a8e-4391-b707-277828d9a00d","added_by":"auto","created_at":"2025-09-29 15:39:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":131691,"visible":true,"origin":"","legend":"\u003cp\u003eClassification of bile acids.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7441483/v1/461849c9b1a14809ea9212a2.png"},{"id":92430557,"identity":"21ee6cc8-f14c-4750-a793-6d651f71085c","added_by":"auto","created_at":"2025-09-29 16:05:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":995413,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7441483/v1/a4821f25-f952-41c6-ac15-f492bc63c783.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Conjugated Bile Acids and Their Interactions With Abdominal Obesity for Increased Risk of Insulin Resistance in Chinese Childhood and Adolescence","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eInsulin Resistance (IR) is defined as the inability of known amounts of insulin to increase the utilization of glucose by peripheral tissues (muscle, liver, adipose tissue, etc.) \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. In recent years, large amounts of studies have confirmed that IR is a common phenomenon in children and adolescents \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, and the frequency of this condition is increasing dramatically in developed countries \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In addition, race also plays a role in sensitivity to IR, with Hispanics, South Asians, and Indians at higher risk than Non-Hispanic Blacks and Non-Hispanic Whites \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. IR has been recognized for many years as a major contributor to impaired glucose metabolism, type 2 diabetes (T2DM), and cardiovascular disease \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, and has been identified as a key link between obesity and increased risk of chronic disease. Currently, researches have found that the incidence of diabetes in China is trending towards younger ages. \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e The prevalence of pre-diabetes among the 7\u0026ndash;17 age group in China is 14.9% \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. It is worth noting that the incidence of diabetes in children under 5 years old in China has increased sharply, with an increase of 33.61% \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The increasing prevalence of metabolic diseases will inevitably bring heavy burden and great challenge to the life, health and social economy of Chinese residents.\u003c/p\u003e\u003cp\u003eBile Acids as an important component of bile, are the final products synthesized by a series of enzymatic reactions in the liver with cholesterol as raw material \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. As a signaling molecule and metabolic regulator, bile acids can regulate hepatic lipid, glucose and energy homeostasis and maintain metabolic homeostasis \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. BAs includes primary bile acids and secondary bile acids, and primary bile acids produce secondary bile acids under the action of intestinal flora \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. According to the different structure, bile acids can be divided into two types: free bile acids and conjugated bile acids. The gut microbiome is able to conjugate glycine and taurine with free bile acids, representing a new group of \" conjugated bile acids\" ( As shown in Fig.\u0026nbsp;1) \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. At first, it was found that bile acids play an important role in metabolic regulation and is closely related to the occurrence of diabetes \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Subsequently, studies have shown that abnormal metabolism of conjugated bile acids is also associated with T2DM and pre-diabetic states, including impaired glucose tolerance (IGT) and IR \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, but most studies are limited to adults. IR tends to appear around puberty, and the increased accumulation of fat around the abdominal viscera plays a role in this process. Abdominal obesity is also a key indicator of metabolic syndrome and a key factor leading to IR.\u003c/p\u003e\u003cp\u003eRecent studies have even found that conjugated bile acids play an important role in the digestive process, especially in the digestion and absorption of fat. Studies have reported that conjugated bile acids are closely related to liver fat inflammation, because abnormal accumulation of conjugated bile acids can affect liver fat inflammation \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Maintaining a normal balance of conjugated bile acids metabolism is essential for liver health and overall metabolism. In view of the existing studies, we believe that it is of great significance to investigate the effects of conjugated bile acids and abdominal obesity on metabolic abnormalities in early life for the prevention and treatment of human metabolic diseases in the future.\u003c/p\u003e\u003cp\u003eIn the present study, we used a cross-sectional study was conducted on 606 young individuals in Tianjin City, China to explore: (1) the association of conjugated bile acids levels and IR; and (2) the interactive effects between high conjugated bile acids levels and abdominal obesity on the risk of IR.\u003c/p\u003e"},{"header":"MATERIALS AND METHOD","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData collection\u003c/h2\u003e\u003cp\u003eThis data was collected from outpatients and inpatients of the Department of Endocrinology, Pediatrics, Tianjin Medical University General Hospital from August 2022 to November 2023, with a total of 606 valid samples. All participants provided written informed consent prior to data collection.\u003c/p\u003e\u003cp\u003eThe data included basic information and blood biochemical testing. Blood biochemical testing was conducted in a specialized diagnostic laboratory and analyzed using a fully automated biochemical analyzer (Hitachi 7150, Tokyo, Japan). After fasting for 8 hours, venous blood was drawn from each participant between 8 am and 9:30 am. All staff members received training in a series of workshops before the field survey, standardizing all procedures and using a series of questionnaires to collect data. Basic information of children included two parts: individual information and biochemical information. Personal information of children included demographic information, physical examination results, medical history, etc. Additionally, we also gathered data on the children\u0026rsquo;s feeling upon waking (Energetic, Tired, Hard) and learning capabilities (Easy, General, Difficult, Others). Biochemical test information for the children included triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), fasting blood glucose, fasting insulin, etc.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMetabolomics analysis of serum bile acid components\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eSample pretreatment\u003c/h2\u003e\u003cp\u003eThe plasma was separated and stored at -80℃. The stored plasma sample was thawed at 4\u0026deg;C, 50 \u0026micro;L was absorbed, and 10 \u0026micro;L of internal standard solution with a concentration of 2 \u0026micro;g/ml was added. After swirling the mixture for 1 minutes, add 300 \u0026micro;L cold protein precipitate (methanol solution containing 0.1% ammonia) and swirl the mixture again for 1 minutes. After centrifugation at 12500 rpm for 10 minutes, the obtained supernatant was 200\u0026micro;L, dried with nitrogen, redissolved in a solution of 50\u0026micro;L mixed solution (methanol: acetonitrile 8:2). Take 5\u0026micro;L for each injection.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLC-MS/MS analysis\u003c/h3\u003e\n\u003cp\u003eThe LC-MS analysis was performed using the Eksigent ultra LC 100 liquid phase tandem Triple TOF 5600 (AB SCIEX) mass spectrometry system. Negative ion detection mode, C18 BEH column (2.1 * 100mm, 1.7 \u0026micro; m; Waters) was selected as the chromatographic column, and the pressure of the gas curtain and ion source Gas1 and Gas2 was set to 30, 50, and 50 psi, respectively. The column temperature was 40 degrees Celsius. The ion source temperature was 550℃ and the ion spray floating voltage (ISVF) was set to -4500V. Scanning time set at 100 ms; TOF-MS collision energy and declustering voltage were set to -10 V and \u0026minus;\u0026thinsp;80 V respectively, while -IDA collision energy and declustering voltage were set to -45 V and \u0026minus;\u0026thinsp;80 V respectively. The mass-charge ratio ranges for mass spectrum scanning and ion fragment scanning were set to 200-800Da and 50-800Da, respectively. Mobile phase A was formic acid aqueous solution containing 10 mM amine acetate (0.1%, v/v), mobile phase B was methanol: acetonitrile 8: 2 Solution, total flow rate 0.4 mL/min, gradient elution Settings :0-0.5 minutes (35% B), 0.5-3 minutes (35\u0026ndash;60% B), 3\u0026ndash;10 minutes, (60\u0026ndash;80% B), 10\u0026ndash;16 minutes, (80\u0026ndash;90% B), 16-20.5 minutes, (90\u0026thinsp;\u0026minus;\u0026thinsp;35% B), 20.5\u0026ndash;23 minutes (35% B). Target bile acids were identified using Peak View 1.2 and quantified using Multiquant2.1.\u003c/p\u003e\n\u003ch3\u003eClinical definition\u003c/h3\u003e\n\u003cp\u003eAbdominal obesity is estimated according to the critical waist circumference of Chinese (WS/T611\u0026mdash;2018) children and adolescents\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. IR was evaluated using HOMA-IR index, HOMA-IR\u0026thinsp;=\u0026thinsp;fasting insulin \u0026times; fasting blood glucose\u0026thinsp;\u0026divide;\u0026thinsp;22.5\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analysis was performed using R 4.1.0. Quantitative data are expressed as median (interquartile distance [IQR]) and categorical data as n (%) when appropriate. We used paired T-tests or Kruskal-Wallis signed rank tests (which reject a normal distribution by examining a Q-Q plot) to compare differences in continuous variables, and Chi-square tests or Fisher precision tests (where appropriate) to compare the proportion differences between groups with abdominal obesity and those without. In univariate and multivariate analyses, conditional binary logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for bile acid levels and risk of abdominal obesity. FDR was used to correct P-values.\u003c/p\u003e\u003cp\u003eBinary logistic regression was performed to obtain bile acid odds ratio (OR) and 95% CI for IR. Because the conjugated bile acids were roughly linearly associated with the risk of IR, we divided them into 3 groups according to their tertiles. The confounding factors were controlled by structural adjustment scheme. First, we performed a univariate analysis to obtain unadjusted odds ratios (OR) and 95% confidence intervals (95% CI). Second, we adjusted for basic information, including age, sex, family income, waking feeling, learning capabilities, exercise status, systolic blood pressure (SBP), diastolic blood pressure (DBP), LDL-C, HDL-C, TG, TC. Finally, we used additive interaction to test the interaction effect of high bile acids and abdominal obesity on IR. Three metrics were used to test the relative excess risk of the interaction (RERI), interaction (AP), and synergy index (SI). If any of RERI\u0026thinsp;\u0026gt;\u0026thinsp;0, AP\u0026thinsp;\u0026gt;\u0026thinsp;0, or SI\u0026thinsp;\u0026gt;\u0026thinsp;1 is statistically significant, the additive interaction is considered significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e In this study, a total of 606 participants were included, with 283 children identified as having IR. The average age of the IR group was 12 years, with an average height of 155.3 cm, weight of 60.2 kg, waist circumference of 76 cm, and hip circumference of 90 cm. Furthermore, 51.9% of the children in the IR group were boys. In contrast, the average age of the non-IR group was lower (10 years), with smaller measurements of height (140.2 cm), weight (37.1 kg), waist circumference (62 cm), and hip circumference (73 cm). It is worth noting that there were significant differences in SBP, DBP, TC, Fasting blood glucose and insulin between the two groups, with higher values in the IR group. On the contrary, HDL-C was lower in the IR group Additionally, a higher proportion of children in the IR group had average or below-average learning ability and no exercise. There were no significant differences in other characteristics between the two groups. Regarding the differences in conjugated bile acids, the study results showed that the levels of GCA, GCDCA, TCDCA, GLCA and GDCA were significantly higher in the IR group than in the normal group. However, the level of TCA was lower in the IR group. There was no significant difference in TLCA and TDCA levels between the two groups. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBasic characteristics of the subjects.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInsulin Resistance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of subjects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e323\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e10 (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBoys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e148 (45.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e147 (51.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e140.2(17.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e155.3 (13.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e37.1 (15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.2 (21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaist (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e62[55, 69]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76 [66, 89.5]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHip (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e73 [65, 82]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90 [78, 103]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDBP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e67 [63, 72]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72 [67, 78]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSBP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e105 [99, 112]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e116[106, 123]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome (thousand yuan)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e16 (5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20 (7.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50\u0026thinsp;~\u0026thinsp;100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e49 (15.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e100\u0026thinsp;~\u0026thinsp;150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e99 (30.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e102 (36.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e150\u0026thinsp;~\u0026thinsp;200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e86 (26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57 (20.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e73 (22.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70 (24.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGetting up\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnergetic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e86 (26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58 (20.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e223 (69.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e209 (73.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHard\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e14 (4.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e262 (81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e206 (72.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e61 (18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e77 (27.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEasy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e246 (76.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e180 (63.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e59 (18.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDifficult\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e16 (5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2 (0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eIQR: interquartile range; SBP: systolic blood pressure; DBP: diastolic blood pressure; TG: triglyceride; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; Getting up: the feeling when waking up; Sports: exercise status; Study: learning ability.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eThe Kruskal Wallis rank sum test for continuous variables with skewed distribution, Chi-square test (or fisher test if appropriate) for categorical variables.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, median (IQR) or n (%).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eP-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was defined as statistically significant.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBiochemical information of the subjects.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInsulin Resistance (IR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of subjects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e323\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTG (mmol/L])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.39 [3.83, 4.95]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.20 [3.72, 4.81]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTC (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.92 [0.66, 1.31]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.20 [0.88, 1.64]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-C (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.30 [1.10, 1.56]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.18 [1.02, 1.38]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.40 [2.03, 2.86]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.44 [2.08, 2.94]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFasting blood glucose (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.12 [3.54, 4.64]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.96 [4.71, 5.22]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsulin (pmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.30 [4.90, 9.80]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.70 [16.20, 28.60]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36.80 [17.71, 83.27]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57.73[27.25, 118.98]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e162.79[157.69, 174.95]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e159.50[156.41,169.47]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCDCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e347.85 [176.84, 886.79]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e567.16[259.87,1039.4]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTCDCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76.46 [57.45, 124.03]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89.18 [66.29, 136.97]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.93 [30.49, 75.58]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62.52 [40.74, 91.37]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTLCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.37 [7.53, 14.56]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.85 [7.42, 15.25]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGDCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.57 [11.87, 62.12]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.39 [15.42, 82.36]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTDCA (median [IQR])\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44.67 [40.91, 50.99]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45.68 [41.27, 52.95]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eIQR: interquartile range; SBP: systolic blood pressure; DBP: diastolic blood pressure; TG: triglyceride; TC: total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; GCA: Glycocholic acid; TCA: Taurocholic acid; GCDCA: Glycinodeoxycholic acid; TCDCA: Taurocholic acid; GDCA: Glycodeoxycholic acid; TDCA: Taurodeoxycholic acid; GLCA: Glycinocholic acid; TLCA: Taurocholic acid. HOMA-IR greater than or equal to 2.69 is defined as IR.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe Kruskal Wallis rank sum test for continuous variables with skewed distribution, Chi-square test (or fisher test if appropriate) for categorical variables. Data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, median (IQR) or n (%).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eP-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was defined as statistically significant.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe P-values were FDR corrected.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the univariate analysis, individuals in the highest quartile of serum GCA, GCDCA, TCDCA, GDCA, and GLCA exhibited significantly higher odds of insulin resistance (IR) compared to those in the lowest quartile (ORs: 1.92 [1.29\u0026ndash;2.87], 2.33 [1.56\u0026ndash;3.51], 1.90 [1.28\u0026ndash;2.85], 1.88 [1.27\u0026ndash;2.79], and 2.11 [1.42\u0026ndash;3.14], respectively). Conversely, serum TCA was associated with significantly lower odds of IR at the highest quartile (OR: 0.67 [0.54\u0026ndash;0.74]). After adjustment for potential confounders, the associations for the highest quartiles of serum GCA, TCA, GCDCA, TCDCA, GDCA, and GLCA remained statistically significant, with ORs of 1.96 (1.26\u0026ndash;3.08), 0.88 (0.71\u0026ndash;0.93), 2.40 (1.54\u0026ndash;3.78), 1.74 (1.10\u0026ndash;2.77), 1.86 (1.19\u0026ndash;2.92), and 1.43 (1.13\u0026ndash;2.24), respectively. In addition, univariate analysis showed that participants with abdominal obesity had significantly greater odds of IR compared to those without (OR: 5.56 [3.88\u0026ndash;8.03]), and this association remained robust after adjusting for confounding variables (OR: 4.16 [2.69\u0026ndash;6.51]) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOdds ratios of Conjugated Bile Acids and abdominal obesity for the risk of Insulin Resistance.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnivariable model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultivariable model\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR (95%CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR (95%CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCA, nmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;20.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;20.0-\u0026lt;46.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.37(0.86\u0026ndash;2.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.35(0.81\u0026ndash;2.24)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;46.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.92(1.29\u0026ndash;2.87) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.96(1.26\u0026ndash;3.08) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTCA, nmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;156.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;156.9-\u0026lt;161.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.37(0.86\u0026ndash;2.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.42(0.85\u0026ndash;2.36)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;161.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.67(0.54\u0026ndash;0.74) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.88(0.71\u0026ndash;0.93) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCDCA, nmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;205.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;205.6-\u0026lt;455.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.45(0.91\u0026ndash;2.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.50(0.90\u0026ndash;2.50)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;455.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.33(1.56\u0026ndash;3.51) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.40(1.54\u0026ndash;3.78) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTCDCA, nmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;60.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;60.0-\u0026lt;82.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.74(1.10\u0026ndash;2.77) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.73(0.97\u0026ndash;2.92)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;82.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.90(1.28\u0026ndash;2.85) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.74(1.10\u0026ndash;2.77) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGDCA, nmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;31.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;31.4-\u0026lt;72.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.09(0.73\u0026ndash;1.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.11(0.71\u0026ndash;1.72)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;72.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.88(1.27\u0026ndash;2.79) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.86(1.19\u0026ndash;2.92) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLCA, nmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;34.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;34.5-\u0026lt;55.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.90(1.28\u0026ndash;2.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.33(0.86\u0026ndash;2.06)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;55.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.11(1.42\u0026ndash;3.14) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.43(1.13\u0026ndash;2.24) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbdominal Obesity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;NO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;YES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.56(3.88\u0026ndash;8.03) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.16(2.69\u0026ndash;6.51) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe multivariable model adjusted for age, sex, family income, feelings on waking, learning ability, exercise status, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and total cholesterol.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: GCA: Glycocholic acid; TCA: Taurocholic acid; GCDCA: Glycinodeoxycholic acid; TCDCA: Taurocholic acid; GDCA: Glycodeoxycholic acid; GLCA: Glycinocholic acid.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e* was defined as statistically significant.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eGCA concentrations\u0026thinsp;\u0026ge;\u0026thinsp;46.6 nmol/mL were independently associated with insulin resistance (IR) (OR: 1.69 [1.12\u0026ndash;2.18]), and when co-occurring with abdominal obesity (OR: 3.36 [2.09\u0026ndash;5.40]), the combined presence of both factors was associated with markedly elevated odds of IR (OR: 11.31 [5.11\u0026ndash;25.07]), indicating a significant additive interaction (Attributable Proportion due to interaction, AP: 0.24 [0.12\u0026ndash;0.67]). Similarly, GCDCA levels\u0026thinsp;\u0026ge;\u0026thinsp;455.0 nmol/mL were significantly associated with IR (OR: 1.83 [1.33\u0026ndash;2.12]), and in combination with abdominal obesity (OR: 3.69 [2.16\u0026ndash;6.30]), the joint exposure yielded an OR of 8.75 (4.95\u0026ndash;15.48), with evidence of a significant additive interaction (AP: 0.53 [0.12\u0026ndash;0.71]). In the case of GLCA concentrations\u0026thinsp;\u0026ge;\u0026thinsp;55.7 nmol/mL, the association with IR was also significant (OR: 1.92 [1.52\u0026ndash;2.02]), and when accompanied by abdominal obesity (OR: 4.31 [2.36\u0026ndash;7.85]), the OR for IR was 7.85 (4.13\u0026ndash;11.38), with a significant additive interaction (AP: 0.17 [0.09\u0026ndash;0.44]). Although GDCA levels\u0026thinsp;\u0026ge;\u0026thinsp;72.1 nmol/mL alone were not significantly associated with IR (OR: 2.01 [0.86\u0026ndash;3.46]), the combined exposure with abdominal obesity (OR: 4.56 [2.81\u0026ndash;7.39]) corresponded to an OR of 8.56 (3.19\u0026ndash;13.50), and a significant additive interaction was observed (AP: 0.46 [0.28\u0026ndash;0.59]) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAdditive interaction of Conjugated Bile Acids with Abdominal Obesity for the risk of Insulin Resistance.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnivariable model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultivariable model\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR (95%CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR (95%CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCA\u0026thinsp;\u0026lt;\u0026thinsp;46.6 nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCA\u0026thinsp;\u0026ge;\u0026thinsp;46.6 nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.65(1.09\u0026ndash;1.84) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.69(1.12\u0026ndash;2.18) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCA\u0026thinsp;\u0026lt;\u0026thinsp;46.6 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.19(2.77\u0026ndash;6.34) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.36(2.09\u0026ndash;5.40) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCA\u0026thinsp;\u0026ge;\u0026thinsp;46.6 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.29(6.53\u0026ndash;27.07) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.31(5.11\u0026ndash;25.07) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteraction measure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRERI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.01 (2.35\u0026ndash;22.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.41(0.66\u0026ndash;12.31)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.68 (0.28\u0026ndash;0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.24(0.12\u0026ndash;0.67)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.75(1.58\u0026ndash;8.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.12(0.44\u0026ndash;5.26)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCDCA\u0026thinsp;\u0026lt;\u0026thinsp;455.0 nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCDCA\u0026thinsp;\u0026ge;\u0026thinsp;455.0 nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.76(1.18\u0026ndash;1.82) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.83(1.33\u0026ndash;2.12) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCDCA\u0026thinsp;\u0026lt;\u0026thinsp;455.0 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.62(2.21\u0026ndash;5.95) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.69(2.16\u0026ndash;6.30) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCDCA\u0026thinsp;\u0026ge;\u0026thinsp;455.0 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.65(5.69\u0026ndash;16.38) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.75(4.95\u0026ndash;15.48) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteraction measure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRERI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.98(1.96\u0026ndash;12.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.12(0.75\u0026ndash;10.26)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.61(0.26\u0026ndash;0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.53(0.12\u0026ndash;0.71)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.09(1.45\u0026ndash;6.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.53(1.18\u0026ndash;5.40)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGDCA\u0026thinsp;\u0026lt;\u0026thinsp;72.1 nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGDCA\u0026thinsp;\u0026ge;\u0026thinsp;72.1nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.83(0.92\u0026ndash;3.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.01(0.86\u0026ndash;3.46)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGDCA\u0026thinsp;\u0026lt;\u0026thinsp;72.1 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.64(3.70\u0026ndash;8.59) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.56(2.81\u0026ndash;7.39) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGDCA\u0026thinsp;\u0026ge;\u0026thinsp;72.1 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.96(4.72\u0026ndash;17.02) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.56(3.19\u0026ndash;13.50) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteraction measure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRERI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.11(2.78\u0026ndash;10.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.49(2.25\u0026ndash;10.28)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.68(0.36\u0026ndash;0.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.46(0.28\u0026ndash;0.59)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.87(1.01\u0026ndash;3.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.46(0.68\u0026ndash;3.14)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLCA\u0026thinsp;\u0026lt;\u0026thinsp;55.7 nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLCA\u0026thinsp;\u0026ge;\u0026thinsp;55.7 nmol/L and Non-abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.94(1.44\u0026ndash;2.22) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.92(1.52\u0026ndash;2.02) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLCA\u0026thinsp;\u0026lt;\u0026thinsp;55.7 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.5(2.55\u0026ndash;7.93) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.31(2.36\u0026ndash;7.85) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLCA\u0026thinsp;\u0026ge;\u0026thinsp;55.7 nmol/L and Abo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.12(5.02\u0026ndash;13.13) *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.85(4.13\u0026ndash;11.38) *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInteraction measure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimates\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRERI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.18(0.67\u0026ndash;7.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.12(0.33\u0026ndash;6.23)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.39(0.11\u0026ndash;0.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.17(0.09\u0026ndash;0.44)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.81(0.89\u0026ndash;3.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.51(0.34\u0026ndash;2.35)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe multivariable model adjusted for age, sex, family income, feelings on waking, learning ability, exercise status, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and total cholesterol.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: AP, attributable proportion due to interaction; RERI, relative excess risk due to interaction; SI, synergy index; GCA: Glycocholic acid; GCDCA: Glycinodeoxycholic acid; GDCA: Glycodeoxycholic acid; GLCA: Glycinocholic acid; Abo: Abdominal Obesity; Non-abo: No Abdominal Obesity.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eStatistically signifcant, with RERI\u0026thinsp;\u0026gt;\u0026thinsp;0, AP\u0026thinsp;\u0026gt;\u0026thinsp;0, or SI\u0026thinsp;\u0026gt;\u0026thinsp;1 indicating signifcant additive interaction.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e* \u0026lt; 0.05 was defined as statistically significant.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn recent years, in the study of human bile acids level and metabolic diseases, it has been found that individual conjugated bile acids are related to IR. In terms of primary bile acids. Studies have found that GCA, TCA, GCDCA and TCDCA play an important role in glucose metabolism \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. TCA has been found to improve insulin resistance in both human and animal studies \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. In a population cohort, GCA and GCDCA in Nonalcoholic fatty liver (NAFLD) are positively correlated with insulin resistance index \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. At the same time, serum GCA and GCDCA were significantly positively correlated with the occurrence and development of diabetes in two cohort studies, the Chinese Cardiometabolic and Malignant Tumor Cohort Study and the Finnish Diabetes Prevention Study \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. In both population studies and mouse models, TCDCA has been found to increase the risk of type 2 diabetes \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. The study also explored how dietary changes affect bile acid metabolism and its subsequent IR, particularly changes in conjugated bile acids such as GCDCA and TCDCA. Studies have found that the reduction of GCDCA and TCDCA under dietary regulation is related to the improvement of glucose and insulin metabolism, indicating their role in metabolic regulation \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. For secondary bile acids, it was found that GDCA was positively correlated with insulin resistance index in NAFLD population \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. There are few studies on GLCA, and current studies have found that GLCA in diabetic patients is higher than that in non-type 2 diabetic people \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. It can be seen that the combined primary and secondary bile acids have different effects on the organism, which is similar to our results. Our findings suggest that high levels of GCA, GCDCA, TCDCA, GDCA, and GLCA are associated with an increased risk of developing IR, while high levels of TCA are associated with a reduced risk of developing IR.\u003c/p\u003e\u003cp\u003eAbdominal obesity refers to excessive accumulation of fat in the abdominal area, and this type of obesity is associated with a series of health problems, including IR. Abdominal visceral fat is easy to release free Fatty Acid (FFA) through lipid interpretation, and high levels of FFA can increase liver IR and interfere with glucose uptake in muscle tissue \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. At the same time, the increase in FFA leads to the accumulation of fat in the liver, further aggravating IR \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. To sum up, abdominal obesity can promote fat accumulation and energy balance imbalance through a variety of ways, ultimately leading to the occurrence and development of IR. Therefore, restraining abdominal obesity is one of the important measures to prevent and treat IR.\u003c/p\u003e\u003cp\u003eOur results showed that only glycine-type bile acids interact with abdominal obesity, which was biologically plausible. Firstly, it has been confirmed in animal experiment that TCDCA promotes the occurrence of IR through the FXR axis \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e, and TCA may improve IR by inhibiting the NLRP3 inflammasome signaling pathway \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Secondly, studies have found that GCA and GLCA are positively correlated with liver steatosis and inflammation, \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e and GCDCA and GDCA are also important metabolic markers of liver inflammation \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. Studies have found that increased inflammation may be related to the inhibition of IRS1/PI3K/AKT pathway \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Studies have also shown that GCDCA can promote oxidative stress \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Oxidative stress can inhibit the PI3K/Akt signaling pathway \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. In addition, insulin activates insulin receptor substrates by binding to its receptor, thereby activating the PI3K/Akt signaling pathway and promoting glucose transport and metabolism \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. This process is disrupted in the state of abdominal obesity \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. Studies have proved that IRS1 is closely related to insulin metabolism, and AKT plays a central role in the IRS1/PI3K/ AKT signaling pathway. If IRS1/PI3K/Akt pathway is inhibited, it will cause IR \u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Therefore, we speculate that there may be a potential regulatory relationship between glycine bile acids and the signaling pathway of abdominal obesity, and they may share key signaling molecules such as IRS1, PI3K, and Akt to achieve signal coordination. Functional regulation between these signaling pathways may enhance or modulate the biological effects of BAs and abdominal obesity through synergistic mechanisms, thereby jointly promoting cell growth, differentiation, or metabolic processes.\u003c/p\u003e\u003cp\u003eWhen studying the biological functions and metabolic mechanisms of bile acids in depth, our results have a very noteworthy point: there are significant differences in the effects and mechanisms of different conjugated bile acids in vivo. This difference may be closely related to the types of amino acids they combine with. Firstly, glycine-conjugate bile acids typically have strong hydrophilicity, which makes them highly soluble in aqueous solutions and may increase the risk of liver inflammation. Second, taurine-conjugate bile acids have strong hydrophobicity, which makes them more soluble in lipid environments and may have stronger effects in regulating inflammation. The differential effects of different binding forms of bile acids are a complex and interesting research area that involves the synthesis, metabolism, transport, and interaction with intestinal microbiota of bile acids. A deeper understanding of these differences not only helps us better understand the role of bile acids in digestion and metabolism, but also may provide important scientific basis for developing new treatment strategies and drugs. Another noteworthy point is that in animal experiments, it has been confirmed that GDCA administration improves IR \u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e, however, in NAFLD populations, GDCA is positively correlated with insulin resistance index \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. This result is similar to our findings, as our interaction results show that when the body has high levels of GDCA without abdominal obesity, there is no obvious relationship with IR, but when abdominal obesity exists, the risk of developing IR will increase significantly. This suggests that abdominal obesity may be a critical regulatory factor that affects the impact of GDCA on IR. If abdominal obesity is a key factor in increasing the risk of IR, reducing abdominal fat through diet and exercise may help lower the risk of IR, even if GDCA levels are high.\u003c/p\u003e\u003cp\u003eThese findings provide new insights into the complex mechanisms of IR. Firstly, they suggest that a single biomarker or metabolite may not be sufficient to fully explain the occurrence of insulin resistance, and that the interaction of multiple factors needs to be considered, especially those closely related to lifestyle, such as abdominal obesity. In addition, these results may also have important implications for clinical practice, suggesting that physicians and health professionals should consider not only binding bile acid levels but also other factors such as abdominal obesity when assessing an individual's risk of insulin resistance. Finally, our findings have major public health implications. For example, they highlight the importance of reducing abdominal obesity in preventing insulin resistance and may encourage the development of more prevention and interventions targeting abdominal obesity. At the same time, this suggests the direction of future research to further explore how binding levels and abdominal obesity together affect the risk of insulin resistance. With these studies, we hope to develop more effective strategies to prevent and manage health problems associated with insulin resistance. There are some limitations to our findings. There are two limitations to our study. Firstly, due to the nature of cross-sectional studies, our findings need to be confirmed by future research. Secondly, some confounding factors in our samples have not been fully collected, such as medical histories of (maternal) grandparents, siblings' medical histories, and personal information, we do not rule out genetic influences on abdominal obesity and IR.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn summary, our study identified five specific conjugated bile acids\u0026mdash;GCA, GCDCA, TCDCA, GDCA, and GLCA\u0026mdash;whose serum concentrations were significantly associated with insulin resistance (IR) in children and adolescents. Elevated levels of these bile acids were positively associated with the risk of IR, whereas higher serum levels of TCA were inversely associated with IR risk. Furthermore, GCA, GCDCA, GDCA, and GLCA demonstrated significant additive interactions with abdominal obesity in relation to IR. It is necessary to explore the biological mechanisms behind these interesting observations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlycocholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTaurocholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGCDCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlycochenodeoxycholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTCDCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTaurochenodeoxycholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGDCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlycodeoxycholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTDCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTaurodeoxycholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGLCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGlycolithocholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTLCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTaurolithocholic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003eDISCLOSURE OF STATEMENT\u003c/h2\u003e\n\u003cp\u003eThe authors have nothing to disclose.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003eDeclaration OF INTEREST STATEMENT\u003c/h2\u003e\n\u003cp\u003eThe authors declared no conflict of interest.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eAUTHOR OF CONTRIBUTIONS\u003c/h2\u003e\n\u003cp\u003eW-FW substantially contributed to the conception and design of the work. X-YZ, Z-HZ and W-JW substantially contributed to acquisition of the data. X-YZ, and W-JW analyzed the data and drafted the article. X-MZ and X-LG revised the article critically for important intellectual content. All authors edited the final version of the manuscript. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003ch2\u003eETHICS STATEMENT\u003c/h2\u003e\n\u003cp\u003eThis study was approved by Medical Ethics Committee of Tianjin Medical University General Hospital and Department of Pediatrics, Tianjin Medical University General Hospital, and all research activities were conducted in accordance with the principles of the Declaration of Helsinki. Prior to any research activity, we provided all participants (or their guardians) with detailed information regarding the purpose, procedures, potential risks, and benefits of the study, and obtained their written informed consent. The privacy and personal information of participants were protected, and any published research data does not contain information that could identify individual participants.\u003c/p\u003e\n\u003ch2\u003eFUNDING\u003c/h2\u003e\n\u003cp\u003eThis research was supported by the National Key Research and Development Program of China (2021YFA1301202), General hospital Clinical research project (22ZYYLCCG03), Tianjin Key Medical Discipline (Specialty) Construction Project (TJWJ2022XK008, TJYXZDXK-068C), Tianjin Science and Technology Plan Project (22KPHDRC00120), and National Natural Science Foundation of China (Grant No: 82200932 \u0026amp; 82273676).\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;\u003c/h2\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors thank all the physicians, nurses and research staff at the Tianjin Medical University General Hospital who participated in the study and extended their support for data collection.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChiarelli F, Marcovecchio ML. Insulin resistance and obesity in childhood. Eur J Endocrinol. 2008;159:S67\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTobisch B, Blatniczky L, Schusterova I, Kov\u0026aacute;cs L, Barkai L. Insulin resistance and its effects in children and adolescents. Orv Hetil. 2021;162:403\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStąpor N, Beń-Skowronek I. Insulinooporność u dzieci [Insulin resistance in children]. Pediatr Endocrinol Diabetes Metab. 2015;20:107\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaffeis C, Morandi A. Body composition and insulin resistance in children. Eur J Clin Nutr. 2018;72:1239\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLitwin SE. Childhood obesity and adulthood cardiovascular disease: quantifying the lifetime cumulative burden of cardiovascular risk factors. J Am Coll Cardiol. 2014;64:1588\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang J, Wu W, Dong G, Huang K, Fu J. Pediatric diabetes in China: Challenges and actions. Pediatr Diabetes. 2022;23:545\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu HB, Zhong JM, Hu RY, Wang H, Gong WW, Pan J, et al. Rapidly rising incidence of Type 1 diabetes in children and adolescents aged 0\u0026ndash;19 years in Zhejiang, China, 2007 to 2013. Diabet Med. 2016;33(10):1339\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChiang JY. Bile acid metabolism and signaling. Compr Physiol. 2013;3:1191\u0026ndash;212.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCai J, Rimal B, Jiang C, Chiang JYL, Patterson AD. Bile acid metabolism and signaling, the microbiota, and metabolic disease. Pharmacol Ther. 2022;237:108238.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFiorucci S, Carino A, Baldoni M, Santucci L, Costanzi E, Graziosi L, et al. Bile Acid Signaling in Inflammatory Bowel Diseases. Dig Dis Sci. 2021;66:674\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeng H, Umar S, Rust B, Lazarova D, Bordonaro M. Secondary Bile Acids and Short Chain Fatty Acids in the Colon: A Focus on Colonic Microbiome, Cell Proliferation, Inflammation, and Cancer. Int J Mol Sci. 2019;20:1214.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuzior DV, Quinn RA. Review: microbial transformations of human bile acids. Microbiome. 2021;9:140.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarach T, Pols TW, Nomura M, Maida A, Watanabe M, Auwerx J, et al. TGR5 potentiates GLP-1 secretion in response to anionic exchange resins. Sci Rep. 2012;2:430.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRao A, Kosters A, Mells JE, Zhang W, Setchell KD, Amanso AM, et al. Inhibition of ileal bile acid uptake protects against nonalcoholic fatty liver disease in high-fat diet-fed mice. Sci Transl Med. 2016;8:357ra122.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarruti G, Di Ciaula A, Wang HH, Wang DQ, Portincasa P. Cross-Talk Between Bile Acids and Gastro-Intestinal and Thermogenic Hormones: Clues from Bariatric Surgery. Ann Hepatol. 2017;16:s68\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGottlieb A, Bechmann L, Canbay A. The Presence and Severity of Nonalcoholic Steatohepatitis Is Associated with Specific Changes in Circulating Bile Acids. Ann Hepatol. 2018;17:340\u0026ndash;1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin H, An Y, Tang H, Wang Y. Alterations of Bile Acids and Gut Microbiota in Obesity Induced by High Fat Diet in Rat Model. J Agric Food Chem. 2019;67:3624\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa, Guansheng. Jicheng ye, Ma Jun. A study of waist circumference threshold points in Chinese school children and adolescents aged 7\u0026ndash;18 years [J]. Chin J Epidemiol. 2010;31:609\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYan XX, Ying YW. The diagnostic significance of homeostasis model assessment of insulin resistance in metabolic syndrome among subjects with different glucose tolerance. Chin J Diabetes. 2004;3:31\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu T, Bound MJ, Standfield SD, Jones KL, Horowitz M, Rayner CK. Effects of taurocholic acid on glycemic, glucagon-like peptide-1, and insulin responses to small intestinal glucose infusion in healthy humans. J Clin Endocrinol Metab. 2013;98:E718\u0026ndash;722.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng Z, Liu G, Zhang X, Bi D, Hu S. Improvement of Glucose Metabolism Following Long-Term Taurocholic Acid Gavage in a Diabetic Rat Model. Med Sci Monit. 2018;24:7206\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKimberly WT, O'Sullivan JF, Nath AK, Keyes M, Shi X, Larson MG, Yang Q, et al. Metabolite profiling identifies anandamide as a biomarker of nonalcoholic steatohepatitis. JCI Insight. 2017;2:e92989.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLu J, Wang S, Li M, Gao Z, Xu Y, Zhao X, 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\u0026ndash;510.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Mello VD, Paananen J, Lindstr\u0026ouml;m J, Lankinen MA, Shi L, Kuusisto J, Pihlajam\u0026auml;ki J, et al. Indolepropionic acid and novel lipid metabolites are associated with a lower risk of type 2 diabetes in the Finnish Diabetes Prevention Study. Sci Rep. 2017;7:46337.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrinz P, Hofmann T, Ahnis A, Elbelt U, Goebel-Stengel M, Klapp BF, et al. Plasma bile acids show a positive correlation with body mass index and are negatively associated with cognitive restraint of eating in obese patients. Front Neurosci. 2015;9:199.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSiow Y, Schurr A, Vitale GC. Diabetes-induced bile acid composition changes in rat bile determined by high performance liquid chromatography. Life Sci. 1991;49:1301\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNimer N, Choucair I, Wang Z, Nemet I, Li L, Gukasyan J, et al. Bile acids profile, histopathological indices and genetic variants for non-alcoholic fatty liver disease progression. Metabolism. 2021;116:154457.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMantovani A, Dalbeni A, Peserico D, Cattazzo F, Bevilacqua M, Salvagno GL, et al. Plasma Bile Acid Profile in Patients with and without Type 2 Diabetes. Metabolites. 2021;11:453.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao WG, Zhu HJ. [Mechanism, treatment, and evaluation of obesity-induced insulin resistance and type 2 diabetes]. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2010;32:7\u0026ndash;12. Chinese.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSkoczen S, Wojcik M, Fijorek K, Siedlar M, Starzyk JB. Expression of the central obesity and Type 2 Diabetes mellitus genes is associated with insulin resistance in young obese children. Exp Clin Endocrinol Diabetes. 2015;123:252\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang SY, Li RJW, Lim YM, Batchuluun B, Liu H, Waise TMZ, et al. FXR in the dorsal vagal complex is sufficient and necessary for upper small intestinal microbiome-mediated changes of TCDCA to alter insulin action in rats. Gut. 2021;70:1675\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKo CY, Lo YM, Xu JH, Chang WC, Huang DW, Wu JS, Yang CH, Huang WC, Shen SC. Alpha-lipoic acid alleviates NAFLD and triglyceride accumulation in liver via modulating hepatic NLRP3 inflammasome activation pathway in type 2 diabetic rats. Food Sci Nutr. 2021;9:2733\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen L, van den Munckhof ICL, Schraa K, et al. Genetic and Microbial Associations to Plasma and Fecal Bile Acids in Obesity Relate to Plasma Lipids and Liver Fat Content. Cell Rep. 2020;33:108212.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuo L, Aubrecht J, Li D, Warner RL, Johnson KJ, Kenny J, et al. Assessment of serum bile acid profiles as biomarkers of liver injury and liver disease in humans. PLoS ONE. 2018;13:e0193824.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang Y, Guo Y, Xu Y, Wang W, Zhuang S, Wang R, et al. HIIT Ameliorates Inflammation and Lipid Metabolism by Regulating Macrophage Polarization and Mitochondrial Dynamics in the Liver of Type 2 Diabetes Mellitus Mice. Metabolites. 2022;13:14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu Z, Geng Y, Buist-Homan M, Moshage H. Scopoletin and umbelliferone protect hepatocytes against palmitate- and bile acid-induced cell death by reducing endoplasmic reticulum stress and oxidative stress. Toxicol Appl Pharmacol. 2022;436:115858.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi J, Wang T, Liu P, Yang F, Wang X, Zheng W, et al. Hesperetin ameliorates hepatic oxidative stress and inflammation via the PI3K/AKT-Nrf2-ARE pathway in oleic acid-induced HepG2 cells and a rat model of high-fat diet-induced NAFLD. Food Funct. 2021;12:3898\u0026ndash;918.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoi K, Kim YB. Molecular mechanism of insulin resistance in obesity and type 2 diabetes. Korean J Intern Med. 2010;25:119\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang X, Liu G, Guo J, Su Z. The PI3K/AKT pathway in obesity and type 2 diabetes. Int J Biol Sci. 2018;14:1483\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQi X, Yun C, Sun L, Xia J, Wu Q, Wang Y, et al. Gut microbiota-bile acid-interleukin-22 axis orchestrates polycystic ovary syndrome. Nat Med. 2019;25:1225\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"conjugated bile acids, insulin resistance, abdominal obesity, childhood, adolescence","lastPublishedDoi":"10.21203/rs.3.rs-7441483/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7441483/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to explore associations of conjugated bile acids in childhood and adolescence with insulin resistance (IR), and whether high conjugated bile acids and abdominal obesity had interactive effects on the risk of IR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted on 606 young individuals, aged 7 to18 years in Tianjin City, China. MS metabolomic analysis was used to measure conjugated bile acids levels. The Homeostasis Model Assessment was used to estimate insulin resistance. Waist circumference measurements were used to assess abdominal obesity. Logistic regression models were employed to explore the relationships between conjugated BAs and IR. Interactions between conjugated BAs and abdominal obesity for IR were examined using additive interaction measures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared to their counterparts, six specific conjugated bile acids were significantly different in childhood and adolescence with IR. The high levels of serum GCA, TCA, GCDCA, TCDCA, GDCA, TDCA and GLCA were significantly associated with IR after adjustment (OR: 2.43(1.44-4.14), 0.65(0.40-0.72), 1.83 (1.10-3.09), 1.75 (1.04-2.95), 2.00(1.20-3.33) and 1.88 (1.14-3.11), respectively). The presence of abdominal obesity markedly increased the ORs of high GCA, GCDCA, GDCA and GLCA alone up to 11.31(5.11-25.07), 8.75(4.95-15.48), 8.56(3.19-13.50) and 7.85(4.13-11.38) for the risk of IR, with significant additive interaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum GCA, GCDCA, TCDCA, GDCA and GLCA in childhood and adolescence were positively associated with the risk of IR, and serum TCA was negatively associated with the risk of IR. High levels of GDCA, GCDCA, GDCA and GLCA enhanced the risk association of abdominal obesity with IR.\u003c/p\u003e","manuscriptTitle":"Conjugated Bile Acids and Their Interactions With Abdominal Obesity for Increased Risk of Insulin Resistance in Chinese Childhood and Adolescence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-29 15:39:53","doi":"10.21203/rs.3.rs-7441483/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-18T10:00:53+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-01T08:52:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-27T11:27:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-27T09:34:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Endocrine Disorders","date":"2025-08-27T09:30:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"31e4755d-34dd-4e8a-b96c-490d5f268e6e","owner":[],"postedDate":"September 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T15:39:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-29 15:39:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7441483","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7441483","identity":"rs-7441483","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}