Non-Alcoholic Fatty Liver in Obesity with Deteriorating Glucose Control

doi:10.21203/rs.3.rs-2393464/v2

Background: The incidence of non-alcoholic fatty liver disease (NAFLD) is rising in parallel with increasing bodyweight and loss of glucose control, implicating a high risk of hepatic and extra-hepatic complications.

Subjects / Methods: This longitudinal observational study analysed several indicators for NAFLD in 240 overweight subjects (body mass index (BMI) > 28 kg/m²) at 2 visits within in average 16 months. Subjects were categorised according to their insulin sensitivity (HOMAIR) and diabetic status.

Methods: Liver fat and liver stiffness were measured with sonographic elastography (FibroScan®), and by calculation of Fatty Liver Index (FLI), and NAFLD Fibrosis Score (NFS).

Results: Parameters indicative for liver steatosis, i.e., the controlled attenuation parameter (CAP) and the FLI, were significantly higher in the T2DM group compared to the normal glucose tolerance (NGT) and impaired glucose tolerance (IGT) groups (p<0.05). FLI values and the HOMAIR significantly correlated with sonographic liver fat content (CAP) (r=0.53, p<0.0001; r=0.34, p<0.001, respectively). An inverse correlation was observed between serum adiponectin levels and CAP (r=-0.20; p<0.019) and adiponectin levels and FLI (r=-0.37; p<0.0001). Over 16 months, fasting insulin levels and HOMAIR score increased mainly driven by the group of obese subjects with T2DM. No significant change in liver fat or stiffness was observed that period.

Conclusions: In subjects with a BMI ≥ 28kg/m², the prevalence of NAFLD increases in line with increasing insulin resistance and loss of glucose control. Despite some ongoing deterioration in insulin sensitivity, liver fat content appeared relatively unchanged over 16 months.

Health sciences/Endocrinology

Health sciences/Medical research

Obesity

insulin resistance

non-alcoholic fatty liver disease

adipocytokines

Obesity emerged to the most prominent metabolic disorder with serious consequences for worldwide health care systems. In the meantime, medical societies recognize NAFLD as a huge challenge with a high need of early clinical detection and counteractions .

An increase in visceral adipose tissue and an increase in liver fat is usually associated with insulin resistance and the development of the metabolic syndrome. Increasing liver fat accumulation in more than 5% of hepatocytes, without a background of alcohol abuse, has been defined as non-alcoholic fatty liver disease (NAFLD). NAFLD can also be considered as metabolic dysfunction that results from insulin resistance induced hepatic lipogenesis. After treatment and prognosis of infective hepatitis have markedly improved during recent years, NAFLD developed to the most common cause of liver injury, with a high risk of progressing to steatohepatitis, liver cirrhosis, or hepatocellular carcinoma ¹^,². Beyond these hepatic complications, NAFLD markedly increases the risk of cardiovascular complications, heart failure or chronic kidney disease ^3-7. Most probably, insulin resistance is the main pathophysiological link between NAFLD and these non-hepatic complications ⁸.

The results presented here, are generated from a longitudinal observational study, assessing clinical and sonographic parameters for liver fat and liver fibrosis over time in overweight subjects categorized to different stages of insulin resistance and glucose control. The study design, methods and the baseline data of the study participants have been published in detail previously ⁹.

Patients and Study Design

The data presented here, are retrieved from a follow-up of an ongoing longitudinal study. The study is performed in accordance with the declaration of Helsinki. The study was approved by the local ethical review board and was registered in the German registry of clinical studies (DKRS, registration number DRKS00017516).

Informed consent was obtained from all subjects. Main inclusion criteria at baseline (V1) covered age between 18 and 80 years and a BMI above 28 kg/m². Subjects were excluded if they suffered from diabetes mellitus type 1, maltose-malabsorption, acute gastrointestinal disease, gastrointestinal resection, and systemic treatment with corticoids. At baseline visit (V1) and at the follow up visit (V2) approximately 16 months later, the study participants arrived at the study sites in the morning after being fasted overnight for at least 10 hours. Fasting blood samples were taken for the measurement of glucose, insulin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma glutamyl transpeptidase (gamma-GT), triglycerides, thrombocytes, and albumin. At V2, additional blood was drawn for the assessment of serum leptin and adiponectin concentrations.

Insulin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma glutamyl transpeptidase (gamma-GT), triglycerides, and albumin were measured in serum, fasted glucose were measured in sodium fluoride (NaF) plasma using the Cobas® 6000 analyzers (Roche, Germany). Thrombocytes were analyzed in EDTA blood using a Sysmex XN-1000 blood counter (Sysmex Deutschland GmbH, Germany). Leptin was analysed in serum with an ELISA assay from DRG Instruments. Total adiponectin was analysed in serum with an ELISA assay from R&D systems.

Clinical and Biomarker Scores

Fatty Liver index (FLI)

The FLI is an established score for the non-invasive judgement of the liver fat content ¹⁰. The FLI is calculated based on the laboratory markers triglycerides and gamma-GT and the body composition markers BMI and waist circumference according to the formula:

FLI = e^y divided by (1 + e^y) × 100.

where e is the Euler’s number 2.71828 and y is 0.953 × ln (triglycerides, mg/dL) + 0.139 × BMI, kg/m² + 0.718 × ln (gamma-GT, U/L) + 0.053 × waist circumference, cm – 15.745).¹¹

NAFLD Fibrosis Score (NFS)

The NFS is a validated marker to estimate severity of liver fibrosis ¹³^,¹⁴.

This composite score considers the factors age, hyperglycaemia (i.e., impaired fasting glucose [IFG]) /diabetes, BMI, platelet count (thrombocytes), the AST/ALT ratio (AAR), and albumin:

NFS = -1.675 + (0.037 × Age [years]) + (0.094 × BMI [kg/m²]) + (1.13× IFG/diabetes [yes= 1, no=0]) + (0.99× AAR) – (0.013 × thrombocytes [x10⁹/L]) – (0.66 × albumin [g/dL]).

HOMA_IRScore

The HOMA_IR score is an established sore for the estimation of insulin resistance¹². The HOMA_IR is calculated from fasting glucose and insulin concentrations as follows:

HOMA_IR = fasting insulin [µU/mL] × fasting glucose [mg/dL] divided by 405.

At both visits, participants without a history of diabetes mellitus type 2 (T2DM) underwent a standardised oral glucose tolerance test. Subjects were allocated to the IGT group in case of a blood glucose concentration at 120 min after glucose intake in between 140 mg/dL /7.8 mmol/L and 199 mg/dL / 11.0 mmol/L. Subjects with a glucose level above 199 two hours after glucose intake were allocated to the T2DM group.

Liver Fat and Stiffness

Liver fat and stiffness were measured in all participants using transient elastography and the use of an XL probe (FibroScan^®, Echosens, Paris, France). The FibroScan® device evaluates the liver fat content given by the controlled attenuation parameter (CAP) and expressed as decibel per meter (dB/m) and liver stiffness given as the as the Young’s modulus (E) and expressed as kilopascal (kPA) ¹³^,¹⁴.

Statistical Analysis:

For statistical comparisons between study groups and other variables of interest (e.g., HOMA_IR and Fibrosis categories), the type of analysis was chosen based on the type of data (numerical / categorical) and number of groups to be compared.

If more than two groups were compared regarding a numerical variable, 95% confidence intervals of the numerical variables by group were added to the summary statistics. An overall influence of the grouping variable was assessed by the p-value of the F-test of a simple analysis of variance (ANOVA) model with the grouping variable as the single independent variable. Pairwise differences were assessed by calculating the least square mean difference including 95% confidence interval. Statistical significance of differences was assessed by using the p-value of the corresponding t-test.

If two groups were compared regarding a numerical variable, 95% confidence intervals of the numerical variables by group were added to the summary statistics. Groups were compared by calculating arithmetic mean difference, parametric 95%-confidence interval, and the p-value of the corresponding t-test.

If two or more groups were compared regarding a binary variable, groups were compared overall and pairwise by using a Chi-square test.

Furthermore, linear regressions were performed with liver stiffness and liver fat as dependent variables and HOMA_IR, AST/ALT ratio, FLI and NFS as independent variables. Pearson correlation coefficients were calculated for all variables with a p-value < 0.05 in the regression analyses.

For group comparisons, raw p-values are given. A p-value < 0.05 was considered as statistically significant.

At baseline (V1), 301 overweight subjects with a BMI > 28 kg/m² were included in the study and were categorized according to their insulin sensitivity and diabetic status. 109 subjects had a diagnosed diabetes mellitus (T2DM), of the non-diabetic subjects, 42 were identified with an impaired glucose tolerance (IGT), and 150 with normal glucose tolerance (NGT) in the oral glucose tolerance test. First follow up was intended approximately one year after the baseline assessments. The COVID pandemic with several national and regional lock downs complicated scheduling of follow up visits, which resulted in 61 subjects being lost to follow up. Altogether 240 subjects were re-assessed after 471 ± 134 days (mean ± SD), i.e., approximately 16 months after V1.

The 240 subjects (101 women, 139 men) participating in V2 comprised of 107 subjects with NGT, 32 subjects with IGT, and 95 subjects with T2DM. Follow up after 16 months revealed that eighteen of the subjects from the NGT group switched to the IGT group. Four subjects from the NGT group (n = 150) and three subjects from the IGT group (n = 42) progressed to T2DM.

As shown in Table 1, mean body weight and BMI did not change notably from V1 to V2. Overall included overweight or obese subjects, fasting insulin levels significantly increased from baseline to follow up (p<0.05), and the HOMA_IR showed a tendency to increase over time (p=0.07). The overall increase in fasting insulin levels and the HOMA_IRscore, was mainly driven by an increase in the group of overweight subjects with manifest T2DM.

A significant increase in the overall mean AAR was observed from V1 to V2 (p<0.05). An AAR of 0.8 or higher was seen in 65% of the subjects at V1 and in 73% at V2.

The CAP was significantly higher in overweight subjects with T2DM compared to those in the IGT or NGT groups at V1 and V2 (p<0.05, Figure 1). Overall and within the groups, no significant change in CAP was observed from V1 to V2. FLI was significantly higher in patients with diabetes compared the NGT and the IGT group at V1 and V2 (p<0.05, Figure 2). No significant change in FLI could be observed from V1 to V2, neither in the overall overweight or obese population, nor in the specific groups. Consistently, the elastographic Youngs modulus E and the NFS score, as parameters for liver stiffness and fibrosis did not change from V1 to V2.

Multivariate regression analysis revealed a correlation between liver fat content (CAP) and FLI (r=0.53, p<0.0001; Figure 3) and between liver fat content (CAP) and the HOMA_IRscore (r=0.34, p<0.001; Figure 4).

Leptin and adiponectin concentrations were only measured at V2 in a cross-sectional sense. The serum concentrations of these 2 adipocytokines in the different groups are presented in table 2. Interestingly, significant higher adiponectin levels were observed in overweight subjects with IGT compared to those with NGT (p=0.0341). In subjects with T2DM, adiponectin levels were significantly lower compared to subjects with NGT (p=0.0209) and those with IGT (p=0.0003). No significant differences could be observed in leptin concentrations between the 3 overweight groups.
An inverse correlation was found for serum adiponectin levels with FLI (r=-0.37; p<0.0001), CAP (r=-0.20; p<0.01), and HOMA_IR (p=-0.21; p<0.01). Leptin levels correlated with FLI (r=0.15; p<0.05), HOMA_IR (r=0.30; p<0.0001) and the NFS (r=0.14; p<0.05).
The leptin/adiponectin ratio (LAR) was significantly higher in overweight subjects with T2DM compared to those with NGT or IGT.

According to a recent meta-analysis it is estimated that nearly one third of the overall population worldwide is affected by an increase in liver fat content ¹⁵. NAFLD has emerged to the most frequent liver disease with an estimated prevalence of approximately 25% in the overall population, rising up to 70%-80% in high risk groups like obese subjects or patients suffering from T2DM ^16-18.

Our data obtained from 240 overweight subjects (BMI ≥ 28 kg/m²), observed over 16 months, are in line with published data, showing an incidence of NAFLD in approximately 80% of overweight subjects with a BMI ≥ 28 kg/m² ⁹. In our study population, liver fat content as expressed by CAP or the FLI increases with deteriorating glucose control from the NGT group over IGT to patients with manifest diabetes mellitus type 2.

Insulin resistance is considered to represent a cornerstone pathway in the development of NAFLD and the common associated hepatic and extrahepatic complications ¹⁸^,¹⁹. Even in subjects without T2DM, insulin resistance was found to be strong predictor of NAFLD ²⁰. In our population of overweight or obese subjects, liver fat content as presented by liver elastography and the FLI strongly correlated with markers of insulin resistance. Even in overweight subjects with maintained glucose control, insulin resistance was found to be strongly predictive for liver steatosis. In the overall overweight population, insulin resistance deteriorated over 16 months, mostly driven by the group of overweight subjects with T2DM. Over a mean observational period of 16 months, three percent of the non-diabetic overweight subjects progressed to T2DM.

Leptin and adiponectin are important adipocytokines almost exclusively released from visceral adipocytes. Increased leptin and decreased adiponectin levels are well documented in overweight subjects. A decrease in adiponectin levels and an increase in the leptin/adiponectin ratio is considered as an indicator for adipocyte dysfunction with a shift to a proinflammatory and profibrotic adipose tissue remodeling ²¹^,²².

In addition to the well documented low adiponectin levels in overweight subjects, our data show even lower adiponectin levels in overweight subjects with T2DM compared to overweight subjects without T2DM. Adiponectin mediates insulin-sensitizing effects through binding to its receptors AdipoR1 and AdipoR2, leading to activation of adenosine monophosphate dependent kinase (AMPK), PPAR-α, and presumably other yet-unknown signaling pathways ²³. In accordance with this adiponectin signaling pathway, our data reveal an inverse association between adiponectin levels, liver fat content (CAP; FIB) and insulin resistance ass expressed by HOMA_IR. No association could be observed between adiponectin levels and our indicators of liver fibrosis (E; NFS).

In contrast to the reduced adiponectin levels found in association with T2DM, no additional increase in leptin could be found in obese subjects with T2DM compared to those with remained glucose control. This finding is in line with an observation by Thorand et al., showing a stronger association between adiponectin compared to leptin levels with T2DM in obese subjects ²⁴.

The LAR has been proposed as an even stronger indicator for insulin resistance and T2DM compared to each single adipocytokine for its own ²²^,²⁵. In our study, the LAR did not provide any further information compared to adiponectin levels alone.

There are some important limitations which need to be considered. Driven by the COVID pandemic and several lock downs, only about 80% of the originally recruited subjects could be followed. This reduces the power of this follow up analysis. Although we recognized some deterioration in insulin sensitivity, a follow up time of about 16 months might be too short to detect stronger changes in insulin resistance and liver fat overweight subjects with or without diabetes mellitus. A planed follow up of the same subjects after 36 months might allow us to gather more information about the progression of the metabolic disease over time.

The IGT group with thirty-three subjects is relatively small compared to the NGT group with 116 subjects and the T2DM group with 90 subjects. Therefore, comparisons between the IGT group and the NGT group or the T2DM group should be interpreted with caution.

Leptin and adiponectin levels have only been measured at V2. Therefore, only cross sectional and no longitudinal conclusions could be drawn.

In conclusion, in overweight or obese subjects with a BMI ≥ 28 kg/m², we found a continuous rising risk of NAFLD in line with increasing insulin resistance and loss of glucose control. While insulin sensitivity steadily declined over a time , no significant change in liver fat or liver stiffness could be observed in our overweight or obese study population with or without T2DM. Independent from the glucose control, adiponectin levels and the leptin/adiponectin ratio were found as valuable markers for insulin resistance and liver fat content in overweight or obese subjects.

CAP – Controlled attenuation parameter; E - Young’s modulus; FLI – fatty liver index; IGT – Impaired glucose tolerance; LAR – Leptin Adiponectin Ratio; NAFLD – Non-alcoholic fatty liver disease; NFS – NAFLD fibrosis score; NGT – normal glucose tolerance; T2DM - Type 2 diabetes mellitus

Conflict of Interest

The authors declare no conflicts of interest regarding the contents of the manuscript.

Author Contributions

Thomas Forst was involved in creating study design, performance of the study, and the preparation of the manuscript.

Sybille Baumann, Matthias Berse, Isabel Botz, Armin Schultz, and Mares-Elaine Strempler were involved in conducting the study and the manuscript preparation.

Stephan Voswinkel was involved in the analysis of the laboratory samples and the preparation of the manuscript.

Acknowledgments

The authors thank Marcos Marin-Galiano, M.A.R.C.O GmbH & Co. KG, Institute for Clinical Research and Statistics for data management and statistics, Düsseldorf and Nadja Faisst, CRS Mannheim for medical writing assistance.

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NGT

IGT

T2DM

Total

V1

V2

V2-V1

V1

V2

V2-V1

V1

V2

V2-V1

V1

V2

V2-V1

Body weight (kg)

95.7 ± 12.3

96.0 ± 13.3

0.4 ± 7.1

90.2 ±15.2

89.6 ± 16.0

-0.6 ± 6.1

100.3 ± 14.1

99.8 ± 014.7

-0.5 ±4.6

96.7 ± 13.8

96.6 ± 14.5

-0.1 ± 6.1

BMI (kg/m²)

31.5 ± 2.5

31.6 ± 3.0

0,1 ± 2.3

32.0 ± 3.5

31.9 ± 4.3

-0.2 ±2.3

33.7 ± 3.8

33.6 ± 4.2

-0.2 ± 1.5

32.4 ± 3.3

32.4 ± 3.7

-0.0 ± 2.0

Insulin (mU/L)

11.3 ± 5.7

12.3 ± 8.5

1.1 ±5.9

13.4 ± 7.0

13.8 ±8.3

0.35 ± 5.6

17.9 ± 13.2

20.2 ±22.6

2.31 ± 13.7

14.1 ± 9.8

15.5 ± 15.8

1.4 ± 9.6 ^●

HOMA_IR

2.8 ± 1.5

3.1 ±2.2 *

0.3 ±1.6

3.5 ± 2.0

3.5 ± 2.3

0.0 ± 1.6

6.9 ± 5.2

7.5 ± 6.6

0.62 ± 4.9

4.4 ± 3.9

4.8 ± 4.9

0.38 ± 3.3

AST / ALT Ratio

0.95 ± 0.32

1.00 ± 0.31*

0.04 ±0.21

0.92 ± 0.28

0.00 ±0.24

0.86 ±0.30

0.89 ± 0.27

0.03 ± 0.19

0.91 ± 0.31

0.95 ± 0.29 *

0.03 ± 0.21

FLI

69.7 ± 18.2

69.4 ± 20.8

-0.1 ±18.8

71.2 ± 22.2

70.0 ±24.8

-1.3 ±16.6

86.1 ± 12.5

85.4 ± 15.6

-0.7 ± 12.9

76.1 ±18.6

75.5 ± 21.0

-0.5 ± 16.4

NAFLD Fibrosis Score

-2.1 ± 1.0

-2.4 ± 3.0

-0.3 ± 3.0

-1.8 ± 1.1

-1.7 ± 1.0

0.1 ± 0.7

-0.3 ± 1.2

-0.1 ± 0.7

-1.4 ± -1.4

-1.5 ± 2.5

-0.2 ± 2.1

CAP (dB/m)

281.2 ± 49.8

270.5 ± 59.0

-10.9 ± 66.4

274.3 ± 72.2

286.0 ± 66.0

11.7 ± 74.9

321.3 ± 63.1

318.9 ± 58.1

-2.0 ± 61.7

295.3 ± 61.7

290.8 ± 63.5

-4.3 ± 66.1

E (kPA)

6.6 ± 6.1

6.12 ± 6.8

-0.51 ± 9.6

5.3 ± 3.4

5.9 ± 4.7

0.58 ± 5.8

8.5 ± 7.3

10.8 ±13.2

2.4 ± 14.5

7.1 ± 9.0

7.8 ± 9.8

0.73 ± 11.4

Table 1: Clinical parameters at Visit 1 and Visit 2 (mean ± SD; * p<0.05 vs baseline;)

	NGT	IGT	T2DM	Total
Adiponectin (µg/mL)	6.2 ± 3.4	7.8 ± 4.7 *	5.0 ± 3.4 *^,$	6.0 ± 3.7
Leptin (ng/mL)	10.7 ± 10.2	12.9 ± 10.0	12.3 ± 10.6	11.6 ± 10.3
Leptin/Adiponectin Ratio	2.1 ± 2.3	2.1 ± 1.9	3.1 ± 3.0 *^,$	2.5 ± 2.6

Table 2: Adiponectin, Leptin serum levels and the Leptin/Adiponectin Ratio at visit 2 (mean ± SD; * p<0.05 vs. NGT; ^$p<0.05 vs IGT)

There is NO conflict of interest to disclose

Non-Alcoholic Fatty Liver in Obesity with Deteriorating Glucose Control

Status:

Version 2

Abstract

Figures

Introduction

Methods

Patients and Study Design

Clinical and Biomarker Scores

Statistical Analysis:

Results

Discussion

Abbreviations

Declarations

Conflict of Interest

Author Contributions

Acknowledgments

References

Tables

Table 1: Clinical parameters at Visit 1 and Visit 2 (mean ± SD; * p<0.05 vs baseline;)

Additional Declarations

Status:

Version 2