Association of total bilirubin and indirect bilirubin content with metabolic syndrome among Kazakhs in Xinjiang

Hao, Hao; Guo, Huiling; Ma, Rulin; Yan, Yizhong; Hu, Yunhua; Ma, Junfeng; Zhang, Xianghui; Wang, Xinping; Wang, Kui; Mu, Lati; Song, Yanpeng; Zhang, Jingyu; He, Jia; Guo, Shuxia

doi:10.1186/s12902-020-00563-y

Cited by 11 publications

(13 citation statements)

References 38 publications

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“…Serum bilirubin levels, even within the normal range, might have graded associations with the prevalence of MS in children [37]. Similar results have also been reported in other studies conducted in Chinese [28,70], Korean [27,71], and Polish [57] adults.…”

Section: Discussionsupporting

confidence: 88%

Association of Serum Bilirubin Level with Metabolic Syndrome and Non-Alcoholic Fatty Liver Disease: A Cross-Sectional Study of 1672 Obese Children

Bellarosa

Bedogni

Bianco

et al. 2021

JCM

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As in adults, obesity also plays a central role in the development of metabolic syndrome (MS) in children. Non-alcoholic fatty liver disease (NAFLD) is considered a manifestation of MS. Not only MS but also NAFLD seem to be inversely associated with serum bilirubin concentrations, an important endogenous tissue protector when only mild elevated. The aim of the study was to evaluate the association between serum bilirubin levels and the prevalence of MS and NAFLD in Italian obese children and adolescents. A retrospective cross-sectional study was performed in 1672 patients aged from 5 to 18 years. Clinical and laboratory parameters were assessed. NAFLD was measured by liver ultrasonography. The study was approved by the Ethical Committee of the Istituto Auxologico Italiano (research project code 1C021_2020, acronym BILOB). MS was present in 24% and fatty liver (FL) in 38% of this population. Bilirubin was not associated with FL and MS as a whole, but it was inversely associated only with selected components of MS, i.e., large WC, high blood pressure and high triglycerides. Our data suggest that bilirubin is not protective against MS and NAFLD in the presence of severe obesity.

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Section: Discussionsupporting

confidence: 88%

Association of Serum Bilirubin Level with Metabolic Syndrome and Non-Alcoholic Fatty Liver Disease: A Cross-Sectional Study of 1672 Obese Children

Bellarosa

Bedogni

Bianco

et al. 2021

JCM

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“…Data from National Health and Nutrition Examination Survey (NHANES) suggested that bilirubin levels were related to 26% lower risk of MetS [ 48 , 49 ]. Congruent with our results, inverse relationship between serum bilirubin levels and MetS components were also shown in cross-sectional studies involving 12,342 Korean adults [ 15 ], 1568 Polish adults [ 50 ], and cohort study of 565 Kazakhs [ 51 ]. Moreover, bilirubin has been speculated to be a potential pre-disease biomarker for the development of MetS in asymptomatic Slovenian individuals [ 13 ], however, in comparison to our study, those studies had smaller sample size.…”

Section: Discussionsupporting

confidence: 89%

Bilirubin as an indicator of cardiometabolic health: a cross-sectional analysis in the UK Biobank

Khoei

Wagner

Sedlmeier

et al. 2022

Cardiovasc Diabetol

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Background Mildly elevated bilirubin, a by-product of hemoglobin breakdown, might mitigate cardiometabolic risk factors including adiposity, dyslipidemia, and high blood pressure (BP). We investigated the cross-sectional relationship between (total) bilirubin and baseline cardiometabolic risk factors in 467,519 UK Biobank study participants. Methods We used multivariable-adjusted linear regression to estimate associations between bilirubin levels and risk factors of cardiometabolic diseases including body mass index (BMI), waist and hip circumferences (WC, HC), waist-to-hip ratio (WHR), fat mass (FM), and trunk FM, and the blood lipids: apolipoprotein A-I (apoA-I), apolipoprotein B (apoB), apoB/apoA-I, lipoprotein (a), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), LDL/HDL, TC/HDL, triglycerides (TG). Log-transformed bilirubin was modelled with restricted cubic splines and predicted mean values with 99% confidence intervals (CI) for each risk marker were estimated, separately. Second, we applied principal component analysis (PCA) for dimension reduction to in turn six anthropometric traits (height, weight, BMI, WC, HC, and WHR) and all above lipids. Last, we estimated associations (99%CI) between bilirubin and three components of the metabolic syndrome, i.e. WC, TG, and BP using logistic regression. Results After multivariable adjustments, higher levels of bilirubin were inversely associated with indicators of general adiposity (BMI and FM) and of body fat distribution (WC, HC, WHR, and trunk FM) in both men and women. For example, women with mildly elevated bilirubin (95th percentile equal to 15.0 µmol/L), compared to women with low bilirubin (5th percentile equal to 4.5 µmol/L), had on average a 2.0 kg/m2 (99% CI 1.9–2.1) lower BMI. Inverse associations were also observed with dyslipidemia among men and women. For example, mildly elevated bilirubin among men (95th percentile equal to 19.4 µmol/L) compared to low levels of bilirubin (5th percentile equal to 5.5 µmol/L) were associated with approx. 0.55 mmol/L (99% CI 0.53–0.56) lower TG levels, with similar inverse associations among women. Multiple-trait analyses using PCA confirmed single-trait analyses. Men and women with mildly elevated bilirubin levels ≥ 17.1 µmol/L, compared to low-normal bilirubin < 10 µmol/L had 13% (99% CI 8%–18%) and 11% (99% CI 4%–17%) lower odds of exceeding systolic BP levels of ≥ 130 mm Hg, respectively. Conclusions Higher levels of bilirubin were inversely associated with cardiometabolic risk factors including adiposity, dyslipidemia, and hypertension.

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“…The serum total bilirubin concentrations in the present study were inversely associated with the insulin resistance risk. Previous studies also reported that serum total bilirubin concentrations are inversely related to the MetS risk in various ethnic groups [ 43 , 44 , 45 , 46 ]. It might be associated with the cholesterol metabolism in the liver.…”

Section: Discussionmentioning

confidence: 86%

Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea

Park

Kim

2022

Diagnostics

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Background: Insulin resistance is a common etiology of metabolic syndrome, but receiver operating characteristic (ROC) curve analysis shows a weak association in Koreans. Using a machine learning (ML) approach, we aimed to generate the best model for predicting insulin resistance in Korean adults aged > 40 of the Ansan/Ansung cohort using a machine learning (ML) approach. Methods: The demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8842 participants were included. The polygenetic risk scores (PRS) generated by a genome-wide association study were added to represent the genetic impact of insulin resistance. They were divided randomly into the training (n = 7037) and test (n = 1769) sets. Potentially important features were selected in the highest area under the curve (AUC) of the ROC curve from 99 features using seven different ML algorithms. The AUC target was ≥0.85 for the best prediction of insulin resistance with the lowest number of features. Results: The cutoff of insulin resistance defined with HOMA-IR was 2.31 using logistic regression before conducting ML. XGBoost and logistic regression algorithms generated the highest AUC (0.86) of the prediction models using 99 features, while the random forest algorithm generated a model with 0.82 AUC. These models showed high accuracy and k-fold values (>0.85). The prediction model containing 15 features had the highest AUC of the ROC curve in XGBoost and random forest algorithms. PRS was one of 15 features. The final prediction models for insulin resistance were generated with the same nine features in the XGBoost (AUC = 0.86), random forest (AUC = 0.84), and artificial neural network (AUC = 0.86) algorithms. The model included the fasting serum glucose, ALT, total bilirubin, HDL concentrations, waist circumference, body fat, pulse, season to enroll in the study, and gender. Conclusion: The liver function, regular pulse checking, and seasonal variation in addition to metabolic syndrome components should be considered to predict insulin resistance in Koreans aged over 40 years.

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Association of total bilirubin and indirect bilirubin content with metabolic syndrome among Kazakhs in Xinjiang

Cited by 11 publications

References 38 publications

Association of Serum Bilirubin Level with Metabolic Syndrome and Non-Alcoholic Fatty Liver Disease: A Cross-Sectional Study of 1672 Obese Children

Association of Serum Bilirubin Level with Metabolic Syndrome and Non-Alcoholic Fatty Liver Disease: A Cross-Sectional Study of 1672 Obese Children

Bilirubin as an indicator of cardiometabolic health: a cross-sectional analysis in the UK Biobank

Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea

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