Relationship between the dynamics of non-alcoholic fatty liver disease and incident diabetes mellitus - PubMed (original) (raw)

Relationship between the dynamics of non-alcoholic fatty liver disease and incident diabetes mellitus

Ji Eun Han et al. Sci Rep. 2022.

Abstract

The aim of the current study was to evaluate the association between changes in non-alcoholic fatty liver disease (NAFLD) over time and risk of incident diabetes mellitus (DM). In total, 3047 subjects without underlying DM were followed up for 14 years from the Anseong-Ansan cohort. NAFLD status was determined biennially using the hepatic steatosis index (HSI), and subjects were clustered into seven groups according to changes in HSI, body mass index (BMI), and homeostatic model assessment of insulin resistance (HOMA-IR): none, persistent, transient, transient resolved, resolved, incident, and recurrent NAFLD (Groups 1-7, respectively). Predictive abilities were compared between the dynamics of HSI and single time points. Regarding the changes in HSI, the risk of incident DM was highest in Group 2 (hazard ratio [HR] 2.710; P < 0.001), followed by Groups 7 (HR 2.062; P < 0.001) and 3 (HR 1.559; P = 0.027). The predictive ability for DM was powerful in order of HOMA-IR, HSI and BMI. The dynamics of NAFLD were less predictive of incident DM than single time-point NAFLD. In conclusion, NAFLD is more useful than BMI in predicting incident DM. However, NAFLD status at single time points can better predict incident DM than dynamic changes in HSI.

© 2022. The Author(s).

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1

Figure 1

Flow chart of subject inclusion and exclusion. HSI hepatic steatosis index, HOMA-IR homeostatic model assessment for insulin resistance, BMI body mass index.

Figure 2

Figure 2

Clustering analysis and heatmap visualization according to HSI clustering. (a) Clustering analysis according to change pattern of HSI, BMI, and HOMA-IR. Reference value for NAFLD, obesity, and insulin resistance were defined as an HSI of ≥ 36, BMI of ≥ 25 kg/m2, and HOMA-IR of ≥ 2.5, respectively. Subjects was divided into seven groups by clustering. Group 1, subjects who had no NAFLD; Group 2, subjects with persistent NAFLD; Group 3, subjects who had only NAFLD once at the mid-point of the follow-up period; Group 4, subjects who had NAFLD from the beginning and showed resolution only once at the mid-point of the follow-up period; Group 5, subjects who had NAFLD from the beginning but resolved in the last year; Group 6, subjects did not have NAFLD from the beginning but developed it in the last year; and Group 7, subjects with repeated development and improvement of NAFLD. (b) Heatmaps for clustering according to change pattern of HSI. The y-axis represents the observed year during the follow-up period and the x-axis represents the group classification. As the value for each year changed from lower to higher value, it is highlighted green to red on the heatmap. HSI hepatic steatosis index, BMI body mass index, HOMA-IR homeostatic model assessment for insulin resistance, NAFLD non-alcoholic fatty liver disease.

Figure 3

Figure 3

Comparison of diabetes mellitus development by Kaplan–Meier curves in included subjects according to groups divided by change pattern of non-alcoholic fatty liver disease (NAFLD) status as assessed by hepatic steatosis index (HSI), body mass index (BMI) and Homeostatic model assessment for insulin resistance (HOMA-IR). (a) Kaplan–Meier curves of diabetes mellitus (DM) development according to NAFLD status change. (b) Kaplan–Meier curves of DM development according to BMI status change. (c) Kaplan–Meier curves of DM development according to HOMA-IR status change.

Figure 4

Figure 4

Comparison of integrated AUC among change patterns of HSI, BMI, and HOMA-IR in predicting incident diabetes mellitus (DM). (a) Integrated area under the receiver operating characteristic curve (IAUC) plot based on change patterns of HOMA-IR and HSI in predicting incident DM. (b) IAUC plot based on change patterns of HSI and BMI in predicting incident DM. HSI hepatic steatosis index, HOMA-IR homeostatic model assessment for insulin resistance, BMI body mass index, AUC area under the receiver operating characteristic curve.

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