Skip to main content

Increased serum carboxylesterase-1 levels are associated with metabolic dysfunction associated steatotic liver disease and metabolic syndrome in children with obesity

Abstract

Background

Carboxylesterase 1(CES1) is expressed mainly in the liver and adipose tissue and is highly hypothesized to play an essential role in metabolism. Our study aimed to investigate the association between CES1 and metabolic syndrome (MetS) and metabolic dysfunction associated steatotic liver disease (MASLD) in children with obesity in China.

Methods

This study included 72 children with obesity aged 6-13years (including 25(35%) diagnosed as MetS and 36(50%) diagnosed as MASLD). All subjects were measured in anthropometry, serum level of biochemical parameters related to obesity, circumstance levels of insulin-like growth factor1, adipokines (adiponectin, leptin and growth differentiation factor 15) and CES1.

Results

Higher serum CES1 level were found in the MetS group (P = 0.004) and the MASLD group (P < 0.001) of children with obesity. Serum CES1 levels were positively correlated with alanine aminotransferase, aspartate aminotransferase, triglyceride, cholesterol, low-density lipoprotein cholesterol, GDF15, Leptin and negatively correlated with high-density lipoprotein cholesterol, adiponectin and IGF1. We also found a multivariable logistic regression analysis of MASLD and MetS predicted by CES1 significantly (MASLD P < 0.01, MetS P < 0.05). The combination of CES1, sex, age and BMI Z-score showed a sensitivity and specificity of 92.7% for the identification of MASLD and 78.6% for the identification of MetS. The cutoff for CES1 of MASLD is 56.30 ng/mL and of MetS is 97.79 ng/mL.

Conclusions

CES1 is associated with an increasing risk of MetS and MASLD and can be established as a biomarker for metabolic syndrome and MASLD of children with obesity.

Backgound

Worldwide, the prevalence of childhood obesity is increasing year by year [1]. Childhood obesity is associated with many metabolic disorders, including metabolic dysfunction associated steatotic liver disease (MASLD) and metabolic syndrome (MetS) [2]. MASLD is defined as excess lipid infiltration of the hepatic parenchymal cells with one cardiometabolic risk factor (CMRF) and without other pathogenic factors [3, 4]. MetS is a group of clinical symptoms characterized by abdominal obesity, hyperglycemia, hypertension and dyslipidemia [5]. Both MASLD and MetS can have adverse consequences without early intervention, so it is necessary for children with obesity to identify risk factors as early as possible [6]. However, the exact diagnostic criteria for MetS in childhood and the exact therapeutic indications and strategies for pediatric MASLD are not variable. Thus, it is extremely important to define new biomarkers for the diagnosis of MetS and MASLD in children with obesity.

Carboxylesterase 1 (CES1) is a crucial serine hydrolase located mainly in parenchymal hepatic cells and adipocytes [7, 8]. CES1 works primarily on hydrolyzing endogenous lipids, including cholesterol esters, triglycerides, and promotes lipid storage [9]. Previous studies have demonstrated that CES1 gene expressions increased in adipose tissues of obese animals and during differentiation of adipocytes [8, 10]. CES1 could also be found in the medium supernatant of human brown adipocytes and increased after norepinephrine stimulation [11]. CES1 also participated in obesity-induced hepatic steatosis, inactivation, and CES1 deficiency in obesity animal models induced by high-fat diet could improve the development of liver steatosis and steatohepatitis [12]. Numerous studies in human adults have demonstrated that increased gene expression of CES1could be observed in MASLD, NASH patients and correlated with obesity and related cardiovascular risk factors [13]. However, studies focus on CES1 levels in the serum of objects with obesity are rare and it is unknown how CES1 levels changed in children with obesity.

In this study, we focus on investigating the association between serum CES1 level and MASLD, MetS, in children and adolescents in China with obesity. We found that levels of CES1 increased in both the MASLD and MetS group. Furthermore, we identified that the serum CES1 level had a diagnosis value for MASLD and MetS in children with obesity.

Methods

Subjects

A total of 72 children (44 boys, 28 girls) with obesity aged 6–13 years were recruited from the Department of Pediatrics at Tongji Hospital from January 2023 to September 2023. Parents of all children signed an informed consent before inclusion, and all procedures of this study were approved by the Tongji Hospital Ethics Committee. The criterion for the diagnosis of obesity in children and adolescents was using criteria of the World Health Organization [14]. The exclusion criteria were: being diagnosed with metabolic disease of heredity, taking drugs that could influence lipid metabolism and glucose metabolism, leading to liver function damage in the last 6 months, having acute infection, and having a history of alcohol drinking.

Anthropometric assessments

All subjects complemented the anthropometric assessments including height (cm), body weight (kg) and waist circumference (WC) (cm) by experienced physicians using standard procedures [15]. Body mass index (BMI) was calculated by weight (kg) divided by the square of one’s height (cm). BMI Z-score: Z = [(BMI/M) L − 1]/ (L × S) [the median (M), coefficient of variation (S) and skewness (L)] according to Chinese criteria [16]. The waist -to- height ratio was calculated by dividing waist circumference (cm) by height (cm). Blood pressure was measured after subjects had rested for 5 min and three times for each subject using the same mercury sphygmomanometer.

Biochemical evaluations and ELISAs

Blood samples were collected after fasting for 12 h and centrifuged at 3000 g for 15 min. Serum samples were stored at -80℃ for further biochemical and protein detection. Serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), fasting blood insulin (FBI) were measured by automatic biochemical analyzer. Homeostasis model assessment of insulin resistance (HOMA-IR) was done using the formula as follows: FBG (mmol/L) × FBI (mU/L)/22.5. Serum levels of adiponectin, leptin, GDF15, IGF-1, CES1 were measured using enzyme-linked immunosorbent assay ELESA kits (Boster Biological, Pleasanton, CA) following the manufacturer’s protocol.

Recruitment

Hepatic steatosis was checked by abdominal ultrasonography and MASLD was defined by standard criteria [3, 4]. MetS was defined using the criteria proposed by the International Diabetes Institute [17] for children age 10 to 16 years that consisted of central obesity (waist circumference ≥ 90th percentile of children of the same age and sex) and having any two of four risk factors: hyperglycemia, hypertension, low HDL-C and high triglycerides. For children between 6 and 10 years, the cut points for cardiovascular disease (CVD) risk factors were used to replace diagnosis of MetS which was composed of obesity (BMI ≥ 95th percentile or waist circumference ≥ 95th percentile) and having two of three risk factors: hypertension (blood pressure ≥ 95th percentile), dyslipidemia (HDL-C < 1.03 mmol/L, non-HDL-C ≥ 3.76 mmol/L, TG ≥ 1.47 mmol/L), hyperglycemia (FBG ≥ 5.6 mmol/L) [18].

Statistical analysis

Statistics were performed using SPSS 23 (SPSS, Chicago, Illinois) and a P value < 0.05 was considered significant. Shapiro-wilk tests were used to test the normality of the data distribution. Data for variables confirming a normal distribution were presented as mean ± standard deviation and Student’s t test was used for comparisons between two groups. Data for variable with a Skewed distribution were presented as median (interquartile range) and Mann–Whitney U tests were used for comparisons between two groups. Pearson’s correlations were performed to evaluate the association of serum CES1 levels with metabolic risk factor levels, adiponectin, leptin, GDF15, and IGF-1 levels in serum after the data for variables not confirming a normal distribution performed a logarithmic transformation. Partial correlation coefficients were used for data adjusted for sex and age.

Binary logistic regression was performed to identify variables independently associated with serum CES1 levels and confounders were chosen by 3 important criteria [19]. A binary logistic regression model was used to identify the value of serum carboxylesterase 1 levels on recognizing non-alcoholic fatty liver disease and metabolic syndrome. Receiver operating characteristic (ROC) curves were performed to determine the risk of MASLD and MetS according to serum levels of CES1.

Results

Clinical characteristics of subjects with obesity

A total of 72 children with obesity (44 boys and 28 girls) are included. Among these children, 50% (36/72) had MASLD and 34.7% (25/72) had metabolic syndrome (MetS). The clinical measurement and biochemical detection characteristics of the study objects are presented in Table 1. Boys were more likely to have MASLD (P = 0.004) and older children were more likely to have MetS (P = 0.036). As expected, the weight, waist circumference, and BMI values were significantly higher in both the MASLD group and the MetS group. Serum levels of ALT, AST, TG, LDL-C, fasting insulin, HOMA-IR were significantly higher and HDL-C were lower in both groups. However, TC levels and BMI Z-score were only significantly higher in children with MASLD. The circulating levels of GDF15 was markedly higher in subjects with MASLD (P < 0.001), MetS (P < 0.001). Interestingly, the serum level of CES1 was significantly higher in the MASLD group (P < 0.001) and the MetS group (P = 0.004) (Fig. 1). However, serum leptin levels were only significantly higher in patients with MASLD and serum adiponectin levels were lower in both the MASLD and MetS group, but there were no statistic differences.

Table 1 Characteristics of obesity subjects according to MASLD and MetS
Fig. 1
figure 1

Plasma levels of CES1 comparing non-MASLD to MASLD individuals and non-MetS to MetS individuals. Statistical assessment was considered statistically significant at *P < 0.05, **P < 0.01

Increased serum CES1 levels were associated with metabolic risk factors and adiposity in children with obesity

To analyze the relationship between serum CES1 and obesity-related factors, Pearson’s correlations were performed. As shown in Extend Table 1, the age of subjects with obesity was positively associated with serum CES1 levels (P = 0.024). In terms of anthropometric indices, such as WHtR, BMI Z-score were not associated with serum CES1 levels and weight (P = 0.028), WC (P = 0.026), BMI (P = 0.041) was positively associated with serum CES1 levels (Extend Table 1). Serum CES1 levels were positively correlated with ALT, AST, TG, TC, LDL-C, FBI, HOMA-IR and negatively correlated with HDL-C (Fig. 2). Surprisingly, circumstance CES1 levels were positively associated with leptin, GDF15 and negatively associated with adiponectin, IGF1 (Fig. 3). After adjusted for age and sex, most correlations remained (P < 0.05) beside weight, WC, BMI, leptin (P > 0.05).

Fig. 2
figure 2

Correlation analysis between CES1 and metabolic risk factors. (A) ALT, (B) AST, (C) TG, (D) TC, (E) H-DLC, (F) L-DLC, (G) FBI, (H) HOMA-IR. Statistical assessment was 2-sided and considered statistically significant at *P < 0.05, **P < 0.01, ***P < 0.001

Fig. 3
figure 3

Correlation analysis between CES1 and obesity-related secreted proteins. (A) Adiponectin, (B) Leptin, (C) GDF15, (D) IGF-1. Spearman correlation coefficient was used. Statistical assessment was 2-sided and considered statistically significant at *P < 0.05, **P < 0.01

Increased circumstance CES1 levels were related to increased risk of MASLD and MetS

To conform the relationship between serum CES1 levels and MASLD or MetS, binary logistic regression analyses (n = 72; Table 2) were further made to identify the risks of the diseases belong and correctly adjusted by confounders such as sex, age, weight, waist circumference and BMI (Table 2) [19]. The risk of MASLD was increased 1.95 times per 1 SD increase in serum CES1 levels (log transformed) (OR: 2.95; 95% CI, 1.598–5.443, P = 0.001). Increased serum CES1 was significantly associated with an increased risk of MetS (OR: 2.255; 95% CI, 1.277–3.981, P = 0.005). After adjustment for confounders, higher serum levels of CES1 were still independently related to higher MASLD risk (OR:3.561; 95% CI, 1.598–7.938, P = 0.002) and MetS risk (OR: 2.040; 95% CI, 1.103–3.773, P = 0.023).

Table 2 Effect of serum carboxylesterase 1 levels on metabolic dysfunction–associated steatotic liver disease and metabolic syndrome

Circulating concentrations of CES1 as a predictor for MASLD and MetS in children with obesity

Following, we used the ROC curve to assess the capacity of serum CES1 levels used to discriminate children with or without MASLD or MetS. The AUC of circulation CES1 levels in above-mentioned children with MASLD shown in Fig. 4 was 75% (ROC-AUC = 0.750, 95% CI, 0.638-0 0.862, P < 0.001); the optimal cutoff point of serum CES1 levels for diagnosing MASLD was 56.30 ng/ml (specificity = 0.806, sensitivity = 0.611; Youden’s index = 0.417). The AUC of serum CES1 levels in children diagnosed with MetS was 70.7% (ROC-AUC = 0.707, 95% CI, 0.581–0.833, P = 0.004); the optimal cutoff point of serum CES1 levels for diagnosis of MetS was 97.79 ng/ml (specificity = 0.872, sensitivity = 0.520, Youden’s index = 0.392).

Fig. 4
figure 4

Receiver operating characteristic (ROC) curve for metabolic dysfunction associated steatotic liver disease (MASLD) (A) and metabolism syndrome (MetS) (B) according to serum CES1 levels. Receiver operating characteristic (ROC) analyses of logistic regression prediction models after combination of CES1, age, sex and BMI Z-score for MASLD (C) and MetS (D)

After a combination of CES1, BMI Z-score, age and sex for the logistic regression prediction model, the percentage of correct predictions for MASLD was 88.9% (ROC-AUC = 0.927, 95% CI, 0.862–0.991, P < 0.001) and for MetS was72.6% (ROC-AUC = 0.786, 95% CI, 0.673–0.898, P < 0.001).

Discussion

In this study, we first presented a higher serum level of CES1 in both the MASLD and MetS groups of children with obesity and the serum CES1 levels were significantly associated with lipid metabolic disturbance, abnormal glucose metabolism and circulating adipokines. Furthermore, elevated serum CES1 levels were independently associated with higher risk of MASLD and MetS in children with obesity in China. These findings indicated that CES1 as a new biomarker of metabolic disorder in children with obesity may play a crucial role in the progression of MASLD and MetS.

Obesity is caused by excessive energy intake and large amounts of lipids deposited in fat tissue, leading to hypertrophy of adipocytes and inflammation of adipose tissue [20]. Adipokines are a group of proteins secreted by adipocytes that can be dysregulated during obesity and contribute to obesity-related disorders such as MASLD and MetS [21]. Therefore, the study of specific adipokines in patients with obesity of their secretion levels and mechanism pathways is helpful for the treatment or prevention of the development of metabolic disorders.

CES1 is a carboxylesterase that belongs to the α/β-hydrolase fold family of proteins and is expressed mainly in the liver and also express in adipose tissue. CES1 has hydrolase activity of triglyceride (TG), cholesteryl ester (CE) and also participates in the metabolism of lipid droplets (LDs) which is predicted to play a role in energy homeostasis [22,23,24]. CES1 expression was increased during the differentiation of adipocytes and is higher in adipose tissue of patients with obesity [8, 25]. Ces1 deficiency in mice leads to a decrease in blood triglyceride levels, an improvement glucose metabolism and increased energy expenditure [26, 27]. Treatment of Ces1 inhibitors to obesity mice induced by a high fat diet and db/db mice improved multiple features of metabolic disorders, including decreased weight gain, improved lipid and glucose metabolisms and improved liver steatosis [11]. All of the studies presented above illustrated that an increased level of CES1 may have harmful effect on the development of obesity-related disorders and inhibiting the activity of CES1 may improve metabolic disorders of obesity [28]. In our study, we found that serum CES1 levels were significantly higher in children with obesity diagnosed as MASLD or MetS which was consistent with previous studies [29].

It is well known that obesity can lead to excess lipid accumulation in liver and adipose tissues that is associated with metabolic risk factors such as waist circumstances, BMI, insulin resistance, hyperlipidemia, and abnormal liver function [20, 30]. In this study, we indicated that obesity indices (weight, WC, BMI) and metabolic risk factors (ALT, AST, TG, TC, LDL-C, FBI, HOMA-IR values) were higher in children with obesity with MASLD or MetS than without. Moreover, GDF15 which been positively associated with NAFLD-NASH progression, was increased in children with obesity of MASLD or MetS and leptin increased only in subjects of MASLD but not MetS [31].

The most interesting finding in this study was that serum CES1 levels were significantly associated with lipid metabolism (ALT, AST, TG, TC, LDL-C), glucose metabolism (FBI, HOMA-IR) and obesity-related secreted proteins (adiponectin, leptin, GDF15, IGF-1). As previously reported, CES1 could participate in triglyceride, cholesterol ester hydrolysis, and the lipid drop formation in liver parenchymal cells and adipocytes [9]. Overexpression of Ces1 in mice could increase liver lipolytic activity leading to higher TG level in serum [32]. Insulin resistance played a crucial role in development of MASLD, MetS and other metabolic disorders, and HOMA-IR is the most common method used to assess insulin resistance [33]. In studies in adult individuals, the serum leptin level is positively associated with metabolic indices including increased weight, insulin resistance, and inflammation [34]. Adiponectin is predicted as a possible antidiabetic adipokine which is considered as an important correlative marker of the sensitivity to systemic insulin resistance and the action of adipocytes [35]. GDF15 is a newly secreted adipokine by both liver and adipocytes, and could be a prognostic biomarker to predict fibrosis in NAFLD [36]. IGF-1 was secreted primarily by the liver and was decreased in patients with NAFLD, which could play a protective role in the liver fibrosis process [37]. According to the above, we believed that serum CES1 in children with obesity was mainly secreted from liver and adipose tissues and may play an irreplaceable role in the progression of insulin resistance and NAFLD fibrosis.

To further explore the association between serum CES1 level and the risk of MASLD and MetS in children with obesity, a binary logistic regression model was used to analyze including sex, age, and obesity indices (BMI, weight, WC). The risk of MASLD was increased 1.95 times and the risk of MetS was increased 1.25 times per 1 SD increase in serum CES1 levels. Furthermore, the ROC curve was conducted to assess the capacity of serum CES1 levels used to discriminate children with or without MASLD or MetS. And the cut-off point for CES1 of MASLD is 56.30 ng/ml and of MetS is 97.79 ng/ml.

Although our study found a new biomarker for both MASLD and MetS in children with obesity, it still has few limitations. First, the study used only children with obesity without normal individuals, which was insufficient to assess serum CES1 levels between the obesity group and normal individual groups. Second, it is difficult to diagnose MetS in children earlier than 10 years old, instead, we used CVD risk factors that may remain controversial. Third, we did not distinguish the different stage of MASLD by the limitation of ultrasound diagnosis. More studies are needed to test CES1 level in the development of MASLD.

Conclusion

In summary, this study indicated that serum CES1 levels were increased in children with obesity diagnosed as MASLD and MetS. This study also suggested that serum levels of CES1 had an association with the risk of MASLD, MetS and could be used as a biomarker for predictive value.

Data availability

The data used to support the findings of this study are included within the article and its additional files.

Abbreviations

MASLD:

Metabolic dysfunction associated steatotic liver disease

MetS:

Metabolic syndrome

WC:

Waist circumference

WHtR:

Waist to height ratio

SBP:

Systolic blood pressure

DBP:

Diastolic blood pressure

BMI:

Body mass index

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

TG:

Total triglyceride

TC:

Total cholesterol

HDL-C:

High-density lipoprotein cholesterol

LDL-C:

Low-density lipoprotein cholesterol

FBG:

Fasting blood glucose

FBI:

Fasting blood insulin

HOMA-IR:

Homeostasis model assessment of insulin resistance

IGF-1:

Insulin-like growth factor 1

GDF15:

Growth differentiation factor 15

CES1:

Carboxylesterase 1

OR:

Odds ratio

CI:

Confidence interval

AUC:

Area under the curve

References

  1. The Lancet Diabetes E. Childhood obesity: a growing pandemic. Lancet Diabetes Endocrinol. 2022;10(1):1.

    Article  Google Scholar 

  2. Smith JD, Fu E, Kobayashi MA. Prevention and Management of Childhood Obesity and its psychological and Health comorbidities. Annu Rev Clin Psychol. 2020;16:351–78.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Corte CD, Ferrari F, Villani A, Nobili V. Epidemiology and natural history of NAFLD. J Med Biochem. 2015;34(1):13–7.

    Article  PubMed  Google Scholar 

  4. Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J Hepatol. 2023;79(6):1542–56.

    Article  CAS  PubMed  Google Scholar 

  5. DeBoer MD. Assessing and managing the metabolic syndrome in children and adolescents. Nutrients. 2019;11(8).

  6. Weihrauch-Bluher S, Wiegand S. Risk factors and implications of childhood obesity. Curr Obes Rep. 2018;7(4):254–9.

    Article  PubMed  Google Scholar 

  7. Jones RD, Taylor AM, Tong EY, Repa JJ. Carboxylesterases are uniquely expressed among tissues and regulated by nuclear hormone receptors in the mouse. Drug Metab Dispos. 2013;41(1):40–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Jernas M, Olsson B, Arner P, Jacobson P, Sjostrom L, Walley A, et al. Regulation of carboxylesterase 1 (CES1) in human adipose tissue. Biochem Biophys Res Commun. 2009;383(1):63–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wei E, Gao W, Lehner R. Attenuation of adipocyte triacylglycerol hydrolase activity decreases basal fatty acid efflux. J Biol Chem. 2007;282(11):8027–35.

    Article  CAS  PubMed  Google Scholar 

  10. Steinberg GR, Kemp BE, Watt MJ. Adipocyte triglyceride lipase expression in human obesity. Am J Physiol Endocrinol Metab. 2007;293(4):E958–64.

    Article  CAS  PubMed  Google Scholar 

  11. Dominguez E, Galmozzi A, Chang JW, Hsu KL, Pawlak J, Li W, et al. Integrated phenotypic and activity-based profiling links Ces3 to obesity and diabetes. Nat Chem Biol. 2014;10(2):113–21.

    Article  CAS  PubMed  Google Scholar 

  12. Lian J, Wei E, Groenendyk J, Das SK, Hermansson M, Li L, et al. Ces3/TGH Deficiency attenuates Steatohepatitis. Sci Rep. 2016;6:25747.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Ashla AA, Hoshikawa Y, Tsuchiya H, Hashiguchi K, Enjoji M, Nakamuta M, et al. Genetic analysis of expression profile involved in retinoid metabolism in non-alcoholic fatty liver disease. Hepatol Res. 2010;40(6):594–604.

    Article  CAS  PubMed  Google Scholar 

  14. Tim J, Cole MCB, Katherine M, Flegal, William H, Dietz. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000;320(7244):1240–3.

    Article  Google Scholar 

  15. Shah M, Radia D, McCarthy HD. Waist circumference centiles for UK South Asian children. Arch Dis Child. 2020;105(1):80–5.

    Article  PubMed  Google Scholar 

  16. Li H, Ji C, Zhong X, Zhang Y. Body mass index growth curves for Chinese children and adolescents aged 0 to 18 years. Zhonghua Er Ke Za Zhi. 2009;47(7):493–8.

    PubMed  Google Scholar 

  17. Zimmet P, Alberti G, Kaufman F, Tajima N, Silink M, Arslanian S, et al. The metabolic syndrome in children and adolescents. Lancet. 2007;369(9579):2059–61.

    Article  PubMed  Google Scholar 

  18. Blood Institute, National Heart L. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics. 2011;128(Suppl 5):S213–56.

    Google Scholar 

  19. Demetrios N, Kyriacou, Lewis RJ. Confounding by indication in Clinical Research. JAMA. 2016;316(17):1818–9.

    Article  Google Scholar 

  20. Jia G, Jia Y, Sowers JR. Contribution of maladaptive adipose tissue expansion to Development of Cardiovascular Disease. Compr Physiol. 2016;7(1):253–62.

    Article  PubMed  Google Scholar 

  21. Sakers A, De Siqueira MK, Seale P, Villanueva CJ. Adipose-tissue plasticity in health and disease. Cell. 2022;185(3):419–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Alam M, Ho S, Vance DE, Lehner R. Heterologous expression, purification, and characterization of human triacylglycerol hydrolase. Protein Expr Purif. 2002;24(1):33–42.

    Article  CAS  PubMed  Google Scholar 

  23. Crow JA, Herring KL, Xie S, Borazjani A, Potter PM, Ross MK. Inhibition of carboxylesterase activity of THP1 monocytes/macrophages and recombinant human carboxylesterase 1 by oxysterols and fatty acids. Biochim Biophys Acta. 2010;1801(1):31–41.

    Article  CAS  PubMed  Google Scholar 

  24. Blais DR, Lyn RK, Joyce MA, Rouleau Y, Steenbergen R, Barsby N, et al. Activity-based protein profiling identifies a host enzyme, carboxylesterase 1, which is differentially active during hepatitis C virus replication. J Biol Chem. 2010;285(33):25602–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Dolinsky VW, Gilham D, Hatch GM, Agellon LB, Lehner R, Vance DE. Regulation of triacylglycerol hydrolase expression by dietary fatty acids and peroxisomal proliferator-activated receptors. Biochim Biophys Acta. 2003;1635(1):20–8.

    Article  CAS  PubMed  Google Scholar 

  26. Wei E, Ben Ali Y, Lyon J, Wang H, Nelson R, Dolinsky VW, et al. Loss of TGH/Ces3 in mice decreases blood lipids, improves glucose tolerance, and increases energy expenditure. Cell Metab. 2010;11(3):183–93.

    Article  CAS  PubMed  Google Scholar 

  27. Lian J, Wei E, Wang SP, Quiroga AD, Li L, Di Pardo A, et al. Liver specific inactivation of carboxylesterase 3/triacylglycerol hydrolase decreases blood lipids without causing severe steatosis in mice. Hepatology. 2012;56(6):2154–62.

    Article  CAS  PubMed  Google Scholar 

  28. Xu J, Yin L, Xu Y, Li Y, Zalzala M, Cheng G, et al. Hepatic carboxylesterase 1 is induced by glucose and regulates postprandial glucose levels. PLoS ONE. 2014;9(10):e109663.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Li Y, Zhou Y, Zhu L, Liu G, Wang X, Wang X, et al. Genome-wide analysis reveals that altered methylation in specific CpG loci is associated with childhood obesity. J Cell Biochem. 2018;119(9):7490–7.

    Article  CAS  PubMed  Google Scholar 

  30. Burhans MS, Hagman DK, Kuzma JN, Schmidt KA, Kratz M. Contribution of adipose tissue inflammation to the development of type 2 diabetes Mellitus. Compr Physiol. 2018;9(1):1–58.

    PubMed  PubMed Central  Google Scholar 

  31. Koo BK, Um SH, Seo DS, Joo SK, Bae JM, Park JH, et al. Growth differentiation factor 15 predicts advanced fibrosis in biopsy-proven non-alcoholic fatty liver disease. Liver Int. 2018;38(4):695–705.

    Article  CAS  PubMed  Google Scholar 

  32. Wei E, Alam M, Sun F, Agellon LB, Vance DE, Lehner R. Apolipoprotein B and triacylglycerol secretion in human triacylglycerol hydrolase transgenic mice. J Lipid Res. 2007;48(12):2597–606.

    Article  CAS  PubMed  Google Scholar 

  33. Asrih M, Jornayvaz FR. Metabolic syndrome and nonalcoholic fatty liver disease: is insulin resistance the link? Mol Cell Endocrinol. 2015;418:55–65.

    Article  CAS  PubMed  Google Scholar 

  34. Myers MG Jr., Heymsfield SB, Haft C, Kahn BB, Laughlin M, Leibel RL, et al. Challenges and opportunities of defining clinical leptin resistance. Cell Metab. 2012;15(2):150–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Fang H, Judd RL. Adiponectin regulation and function. Compr Physiol. 2018;8(3):1031–63.

    Article  PubMed  Google Scholar 

  36. Patel S, Alvarez-Guaita A, Melvin A, Rimmington D, Dattilo A, Miedzybrodzka EL, et al. GDF15 provides an Endocrine Signal of Nutritional Stress in mice and humans. Cell Metabol. 2019;29(3):707–e188.

    Article  CAS  Google Scholar 

  37. Takahashi Y. Nonalcoholic fatty liver disease and adult growth hormone deficiency: an under-recognized association? Best Pract Res Clin Endocrinol Metab. 2023;37(6):101816.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors are deeply grateful for these parents and their families.

Funding

This study was supported by the National Key Research and Development program of China (2023YFC2706300). The funder had no role in the design, data collection, data analysis, and reporting of this study.

Author information

Authors and Affiliations

Authors

Contributions

H.W., S.W., conceived and designed the study. H.W., S.W., Y.W., X.Y., L.H., Y.L., W.W., Y.Y., F.Y., contributed to data acquisition and assisted in data analysis. H.W and S.W wrote the manuscript. X.L obtained funding and provided critical revision of the manuscript for important intellectual content. All authors approved the submitted and published versions.

Corresponding authors

Correspondence to Shimin Wu or Xiaoping Luo.

Ethics declarations

Ethics approval and consent to participate

All procedures of this study were approved by the Tongji Hospital Ethics Committee, approval number TJ-IRB202401080. Parents of all children signed an informed consent before inclusion. All methods were performed in accordance with the ethical standards as laid down in the Declaration of Helsinki and its later amendments or comparable ethical standards.

Consent for publication

Not applicable.

Competing interests

No conflict of interest was declared.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, H., Wu, S., Weng, Y. et al. Increased serum carboxylesterase-1 levels are associated with metabolic dysfunction associated steatotic liver disease and metabolic syndrome in children with obesity. Ital J Pediatr 50, 162 (2024). https://doi.org/10.1186/s13052-024-01733-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13052-024-01733-7

Keywords