Dataset Information

Hepatic Steatosis Index and the Risk of Type 2 Diabetes Mellitus in China: Insights from a General Population-Based Cohort Study.

ABSTRACT:

Purpose

In the Chinese population, we looked at the relationship between the hepatic steatosis index (HSI) and the risk of type 2 diabetes mellitus (T2DM).

Methods

To evaluate the association between HSI and the risk of T2DM, Cox regression models were employed. Hazard ratios (HR) and 95 percent confidence intervals (CI) were computed. A stratified analysis with interaction testing was also carried out. Additionally, we evaluated the incremental predictive value of the HSI over the established risk factors using the C-statistic, the IDI, and the NRI.

Results

During a median follow-up period of 2.97 years, 433 (1.97%) participants developed new-onset T2DM. The smoothing curve fit plot showed a positive correlation between HSI and the risk of T2DM. After adjusting for all noncollinear variables, the risk of T2DM increased by 62% for every 1 standard deviation (SD) increase in HSI. Subgroup analysis indicated that higher HSI levels were associated with a higher risk of T2DM in those aged < 40 years. The addition of HSI enhanced the reclassification and discrimination of established risk factors, with an IDI of 0.027 and an NRI of 0.348 (both P < 0.001).

Conclusion

Our findings suggest that an elevated HSI is substantially associated with a greater risk of T2DM in the Chinese population. HSI has the potential to be an available and supplementary monitoring method for the management of T2DM risk stratification in the Chinese population.

SUBMITTER: Cai X

PROVIDER: S-EPMC9365599 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Hepatic Steatosis Index and the Risk of Type 2 Diabetes Mellitus in China: Insights from a General Population-Based Cohort Study.

Cai Xintian X Gao Jing J Liu Shasha S Wang Mengru M Hu Junli J Hong Jing J Zhu Qing Q Tuerxun Guzailinuer G Dang Yujie Y Li Nanfang N

Disease markers 20220803

<h4>Purpose</h4>In the Chinese population, we looked at the relationship between the hepatic steatosis index (HSI) and the risk of type 2 diabetes mellitus (T2DM).<h4>Methods</h4>To evaluate the association between HSI and the risk of T2DM, Cox regression models were employed. Hazard ratios (HR) and 95 percent confidence intervals (CI) were computed. A stratified analysis with interaction testing was also carried out. Additionally, we evaluated the incremental predictive value of the HSI over th ...[more]

PMID: 35968500

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Project description:BackgroundThis study aims to identify early metabolomic biomarkers of gestational diabetes mellitus (GDM) and evaluate their association with hepatic steatosis.MethodsWe compared maternal serum metabolomic profiles between women who developed GDM (n = 118) and matched controls (n = 118) during the first (10-14 gestational weeks) and second (24-28 gestational weeks) trimesters using ultra-performance liquid chromatography coupled with mass spectrometry. Mediation analysis was performed to evaluate the mediating role of metabolic dysfunction-associated steatotic liver disease (MASLD) in the relationship between metabolites and subsequent development of GDM. A refined prediction model was developed to predict GDM using established clinical factors and selected metabolites.ResultsSignificant alterations in circulating metabolites, including amino acids, bile acids, and phospholipids, were observed in the GDM group compared to controls during early pregnancy. Mediation analysis revealed that several metabolites, including glycocholic acid (proportion mediated (PM) = 31.9%), butanoyl carnitine (PM = 25.7%), and uric acid (PM = 22.4%), had significant indirect effects on GDM incidence mediated by hepatic steatosis. The refined prediction model composed of clinical factors and selected metabolites in the first trimester demonstrated higher performance in predicting GDM development than the established prediction model composed solely of clinical factors (AUC, 0.85 vs. 0.63, p < 0.001).ConclusionsWomen who developed GDM exhibited altered metabolomic profiles from early pregnancy, which showed a significant correlation with GDM, with MASLD as a mediator. Selected metabolomic biomarkers may serve as predictive markers and potential targets for early risk assessment and intervention in GDM.Research insightsWHAT IS CURRENTLY KNOWN ABOUT THIS TOPIC?: Gestational diabetes mellitus (GDM) is a common pregnancy complication with significant health risks. Early identification of women at high risk for GDM is crucial for timely intervention and improved outcomes. WHAT IS THE KEY RESEARCH QUESTION?: What alterations in circulating metabolites during early pregnancy are associated with subsequent GDM development? Does metabolic dysfunction-associated steatotic liver disease (MASLD) mediate the association between specific metabolites and GDM risk? WHAT IS NEW?: Significant alterations in bile acids, amino acids, phosphatidylethanolamines, and phosphatidylinositols were observed in early pregnancy sera of women who later developed GDM. MASLD significantly mediated the effects of several metabolites on GDM risk, with mediation proportions ranging from 9.7 to 31.9%. A refined prediction model composed of clinical factors and metabolites significantly improved the performance in predicting GDM development. HOW MIGHT THIS STUDY INFLUENCE CLINICAL PRACTICE?: These results provide new insights into early metabolic alterations associated with GDM development and highlight the potential mediating role of MASLD. This comprehensive metabolomic approach may contribute to the development of improved risk prediction models and targeted interventions for GDM prevention.

Project description:Purpose-This study aimed to examine the association between periodontitis and diabetes mellitus.MethodsParticipants with natural teeth in one jaw from the Third United States National Health and Nutrition Examination Survey (1988-1994) were included in this analysis. Participants with moderate (> 4mm attachment loss in ≥ 2 mesial sites or 5mm pocket depth in ≥ 2 mesial sites) or severe (> 6mm attachment loss in ≥ 2 mesial sites and > 5mm pocket depth in ≥ 1 mesial site) periodontitis were classified as having periodontal disease. The rest of the participants were considered without periodontal disease. Diabetes mellitus was defined as fasting glucose ≥ 126mg/dL, hemoglobin A1c ≥ 6.5% or the use of antihyperglycemic medications. Multivariable logistic regression was used to examine the association between periodontitis and diabetes mellitus in all study population and subgroups stratified by demographics and comorbidities.ResultsThis analysis included 13,000 participants [mean age 43.8 ± 19.1 years, 47.5% male, 30% whites]. About 12.7% (n = 1,656) of the study population had periodontitis, and 9.2% (n = 1,200) had diabetes. In a multivariable-adjusted model, presence (vs. absence) of periodontitis was associated with 66% increased odds of diabetes (OR (95% CI):1.66 (1.43-1.94); p < 0.001). Compared to those without periodontitis, the odds of diabetes among those with severe periodontitis was much higher (OR (95% CI): 2.31(1.72-3.11); p < 0.001) than in those with moderate periodontitis (OR (95% CI): 1.54(1.30-1.82); p < 0.001).ConclusionsPeriodontitis is associated with prevalent diabetes in a dose-response fashion, suggesting a bidirectional relationship between those two diseases. Patients with periodontal disease should be counseled regarding their elevated risk of diabetes.Supplementary informationThe online version contains supplementary material available at 10.1007/s40200-022-01010-6.

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Project description:Plasma atherogenic index (AIP) reflects a novel intricate biochemical indicator of lipids' metabolism. The involvement of lipid metabolism for pathogenesis concerning nonalcoholic fatty liver disease (NAFLD) has been established. However, the precise association across AIP and hepatic steatosis and fibrosis remains unclear. This present investigation explored the potential correlation across AIP, hepatic steatosis and fibrosis. Data were acquired through National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020. Hepatic steatosis was detected through the controlled attenuation parameter (CAP), while hepatic fibrosis was examined via liver stiffness measurement (LSM). The study employed multiple linear, Fitted smoothed curves and subgroup analyses were used for investigating relationships between the AIP, CAP, and LSM. The study recruited 6239 participants. In multivariate linear regression analysis, findings indicated a remarkable correlation between AIP and exacerbated NAFLD risk [odds ratio (95% confidence interval), 1.17 (1.12, 1.21)]. Analysis further revealed a positive link across AIP and hepatic steatosis, as indicated through the CAP [β (95% CI), 4.07 (3.32, 4.82)]. Tests for non-linearity, revealed a non-linear correlation between AIP and CAP (inflection point = 0.22). Subgroup analyses assessed the consistency of the link across AIP and CAP, indicating that the association remained comparable across all subgroups. Following the adjustment for all relevant variables, the linear regression analysis revealed a lack of statistical significance across the AIP and hepatic fibrosis. [LSM, β (95% CI), -0.39 (-1.06, 0.28), P = .2501]. Smooth-fitting curves examined the link across AIP and LSM and showed a U-shaped pattern, indicating their positive correlation with AIP less than 0.48. However, no significant correlation was observed with AIP more than 0.48. This study highlighted a substantial positive relationship across AIP and hepatic steatosis, as measured through CAP, and suggests that it may be used as an efficient and rapid measure for clinical prediction of hepatic steatosis.

Dataset Information

Hepatic Steatosis Index and the Risk of Type 2 Diabetes Mellitus in China: Insights from a General Population-Based Cohort Study.

Purpose

Methods

Results

Conclusion

Publications

Hepatic Steatosis Index and the Risk of Type 2 Diabetes Mellitus in China: Insights from a General Population-Based Cohort Study.

Similar Datasets

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