Does autophagy have a role in the pathogenesis of pediatric hepatic steatosis?

doi:10.21203/rs.3.rs-2962589/v1

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Research Article

Does autophagy have a role in the pathogenesis of pediatric hepatic steatosis?

https://doi.org/10.21203/rs.3.rs-2962589/v1

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Background and Objectives:

Hepatic steatosis has become the most common cause of chronic liver disease among children worldwide. Lipophagy has been considered as a pathway affecting steatosis development and progression. This study aimed to evaluate the immunohistochemical expression of Beclin1 and LC3A in pediatric hepatic tissues with steatosis and to correlate their expression with clinicopathological parameters.

Methods

This study included 81 Egyptian pediatric patients with hepatic steatosis. Also, 21 pediatric cases without hepatic steatosis were included. All specimens were stained by Beclin1 and LC3A antibodies.

Results

Higher beclin1 expression was significantly correlated with higher stages of fibrosis and distorted liver architecture in chronic liver diseases group, (P = 0.043) for both. The higher positivity, percentage and median values of H score of LC3A expression were seen in control group rather than in chronic liver disease group or the inborn error of metabolism group (P = 0.055, 0.001, 0.008 respectively). Higher positivity of LC3A was significantly associated with higher stages of fibrosis and distorted liver architecture in the studied inborn error of metabolism group (P = 0.021) for both.

Conclusions

Fluctuation of autophagy at different stages of pediatric hepatic steatosis and different disease etiology proved by different intensity grades of Beclin 1 and LC3A immunohistochemical expression.

Beclin 1

Immunohistochemistry

LC3A

Lipophagy

Non-alcoholic steatohepatitis

Children's hepatic steatosis has been rising everywhere. Making it difficult to discern between basic steatosis and a more complicated condition (1). Steatosis is primarily linked to metabolic storage illness, fatty liver disease, viral infection, and cancer in children under the age of 18 (2).

The most frequent cause of liver disease in children is metabolic associated fatty liver disease (MAFLD), a term used to describe a clinical spectrum of liver abnormalities linked to obesity. Since kids don't drink as much alcohol as adults do, the term "non-alcoholic fatty liver disease" (NAFLD) should be replaced with "MAFLD" (3). According to epidemiology, 3–10% of pediatric patients may have MAFLD, and the male-to-female ratio is 2:1 (4).

In addition to being an anti-aging strategy, autophagy is a catabolic process that aids the cell in eliminating damaged cytosolic organelles including mitochondria and aggregated proteins (6). The creation of autophagosomes from membranes that separate the cell structure(s) that must be destroyed is essential for autophagy (7). The autolysosome is created when late endosomes and lysosomes fuse with the autophagosome to finish the degradation process before continuing metabolism through the endoplasmic reticulum (ER) (8). Numerous pathological conditions, such as metabolic storage diseases, non-alcoholic fatty liver disease, and cancer, are known to exhibit dysregulation of autophagy (9).

Lipophagy is a specific form of autophagy that controls the breakdown of lipid droplets (LDs) in the liver in order to protect against lipotoxicity. Recently, lipophagy has emerged as a pathway affecting NAFLD development and progression (10).

The primary regulators of the autophagy process are Beclin 1 and LC3, however they function differently. The early process of autophagy and the development of the autophagosome are both facilitated by mammalian Beclin 1 (11). The class III phosphatidylinositol 3-kinase (PI3KC3) complexes are affected allosterically by it (PI3KC3-C1 and PI3KC3-C2). At the beginning of the autophagosome development, PI3KC3-C1 performs a role in autophagic vesicle enucleation (12). The Class III phosphatidylinositol 3-kinase (PI3KC3-C2) participates in the development of autophagolysosomes (13).

A microtubule-associated protein called LC3 is also arguably the most commonly used indicator of autophagic activity and flow because it has a post-translationally modified, lipidated form that may be connected to continuous phagophore production. The LC3 gene family has three paralogues in humans: LC3A, LC3B, and LC3C. The specialized targeting of mitochondria for mitophagy has been attributed to LC3A (14).

There is some disagreement over the precise function of the autophagic and lipophagic pathways in NAFLD despite the huge number of studies demonstrating a connection between lipophagy/autophagy and NAFLD (10).

The current study aims to evaluate Beclin 1 and LC3A autophagy markers' immunohistochemistry expression in fatty liver samples from pediatric patients in Egypt and to connect their expression with clinicopathological parameters to determine its clinical importance.

This retrospective case control study included 81 liver biopsy specimens from Egyptian pediatric patients presented with hepatic steatosis. They were divided into two groups according to final diagnosis obtained from Pediatric Hepatology Department into chronic liver disease (CLD) group that included 45 cases and inborn error of metabolism (IEM) group that included 36 cases. Also, 21 cases within the pediatric age group served as control liver tissue without steatosis were included. Specimens were retrieved from the archival material of Pathology Department, National Liver Institute (NLI), Menoufia University, during the period between 2015 and 2020. All samples were collected as part of the standard clinical management of the patients. The study was in accordance to an approved Institutional Review Board (IRB) protocol of the National Liver Institute (NLI) and Faculty of Medicine, Menoufia University

Evaluation of cases:

Clinical, laboratory and radiological data were collected from patients' medical reports including age, gender, liver enzymes, viral state (hepatitis A, B, C virus, Epstein Barr virus and cytomegalovirus), Serum Autoantibodies, fatty changes, hepatosplenomegaly, liver fibrosis/cirrhosis, ascites and obesity.

Histopathological evaluation:

Hematoxylin and eosin (H&E), Masson trichrom, Orcein, Perl's, PAS and D-PAS stained slides for hepatic steatosis specimens were reevaluated to assess steatosis grading, portal and lobular inflammation, stage of fibrosis, hepatic architecture, hepatocyte ballooning, granulomas, pigments, presence of cholestasis, neutrophils and giant cell change.

Immunohistochemistry:

The streptavidin-biotin amplified system using a DAKO automated immunostainer system (Autostainer Link 48) was used in this work. The primary antibodies were polyclonal antibodies raised against beclin 1 (concentrated form (100 ul), rabbit) SNF medical company, catalogue no. YPA1333, China, (dilution 1:50) and LC3A (concentrated form (50 ul), rabbit) AM biomedical company, catalogue no. A11438, China (dilution1:50). Ultra V block was applied to block non-specific background staining. Antigen retrieval was performed using tris-EDTA high PH. The detection kit was ultravision detection system antipolyvalent HRP/DAB (ready to use, cat. #TP-015-HD; Lab Vision Corporation, Fremont, California). Finally, the reaction can be visualized by appropriate substrate/chromogen (Diaminobenzidine, DAB) reagent with Mayer’s hematoxylin as a counterstain. The staining procedure included positive tissue control (human kidney for beclin 1 and Barrett's esophageal tissue for LC3A) and negative tissue control by omitting the primary antibodies.

Interpretation of immunostaining results:

Cytoplasmic immunoreactivity in any number of cells is required to assign either beclin 1 (15) or LC3A (16) positive expression in hepatocytes.

H score system was applied to evaluate the studied cases according to Fedchenko and Reifenrath (17) where both the intensity (scored 1 to 3 as 1 = mild, 2 = moderate, and 3 = strong) and percentage of positivity were considered using the following formula: H score = (3 strong intensity x percentage%) + (2 moderate intensity X percentage%) + (1 mild intensity x percentage%). The maximum score was 3 × 100 = 300 (17).

Statistical analysis:

Data were collected, tabulated, and statistically analyzed using a personal computer with the “Statistical Package for the Social Sciences” (SPSS) version 22 program. Fisher’s exact and chi-square tests were used for evaluation of qualitative data while Mann-Whitney and Kruskal Wallis test were used for evaluation of quantitative data. P-value 0.05 was considered statistically significant (18).

Number and Percentage of cases according to etiology of steatosis in CLD and IEM groups were shown in table 1.

Chronic Liver Disease group

N, %

Inborn Error of Metabolism group

N,%

Chronic hepatitis with undetermined etiology

Percentage within group

Percentage within all cases

42.2%

23.5%

Glycogen storage disease (GSD)

Percentage within group

Percentage within all cases

61.1%

27.1%

Autoimmune hepatitis

Percentage within group

Percentage within all cases

26.7%

14.8%

Wilson disease

Percentage within group

Percentage within all cases

16.7%

7.4%

Chronic hepatitis C

Percentage within group

Percentage within all cases

24.4%

13.6%

Lipid storage disease

Percentage within group

Percentage within all cases

8.3%

3.8%

Steatohepatitis

Percentage within group

Percentage within all cases

2.2%

1.2%

Progressive familial intrahepatic cholestasis (PFIC)

Percentage within group

Percentage within all cases

2.8%

1.4%

Simple fatty liver

Percentage within group

Percentage within all cases

2.2%

1.2%

Tyrosinemia

Percentage within group

Percentage within all cases

2.8%

1.4%

Drug induced liver injury

Percentage within group

Percentage within all cases

2.2%

1.2%

Mitochondrial cytopathy

Percentage within group

Percentage within all cases

2.8%

1.4%

Alpha 1 Anti-trypsin deficiency (A1ATD)

Percentage within group

Percentage within all cases

2.8%

1.4%

Hemochromatosis

Percentage within group

Percentage within all cases

2.8%

1.4%

Total number in each group

Percentage/total studied cases

55.5%

44.5%

CLD: Chronic liver diseases. IEM: Inborn errors of metabolism

The clinicopathological parameters of the studied cases were shown in table 2

		CLD (n = 45)		IEM (n = 36)
Age (months)	Min. – Max.	9.0 – 192.0		2.0 – 192.0
	Mean ± SD.	106.8 ± 50.67		45.67 ± 57.10
	Median (IQR)	120.0 (66.0 – 144.0)		13.50 (11.0 – 62.50)
Gender	Male	26	57.8%	24	66.7%
Gender	Female	19	42.2%	12	33.3%
Liver enzymes	Normal	8	17.8%	7	19.4%
Liver enzymes	High	37	82.2%	29	80.6%
Hepatotropic viruses	Negative	32	71.1%	34	94.4%
Hepatotropic viruses	Positive	13	28.9%	2	5.6%
Non Hepatotropic viruses	Negative	41	91.1%	33	91.7%
Non Hepatotropic viruses	Positive	4	8.9%	3	8.3%
Hepato-splenomegaly	Absent	21	46.7%	6	16.7%
Hepato-splenomegaly	Present	24	53.3%	30	83.3%
Ascites	No	45	100.0%	36	100.0%
Ascites	Yes	0	0.0%	0	0.0%
Obesity	Absent	35	77.8%	16	44.4%
Obesity	Present	10	22.2%	20	55.6%
Grade of steatosis	1	37	82.2%	30	83.3%
	2	7	15.6%	4	11.1%
	3	1	2.2%	2	5.6%
Inflammation	Minimal	2	4.4%	0	0.0%
	Mild	35	77.8%	33	91.7%
	Moderate	8	17.8%	3	8.3%
Fibrosis	Absent	1	2.2%	0	0.0%
	Minimal	1	2.2%	0	0.0%
	Mild	18	40.0%	16	44.4%
	Moderate	19	42.2%	15	41.7%
	Marked	6	134%	5	13.9%
	Absent, minimal and mild	20	44.4%	16	44.4%
	Moderate, marked	25	55.6%	20	55.6%
Liver architecture	Preserved	20	44.4%	16	44.4%
Liver architecture	Distorted	25	55.6%	20	55.6%
Hepatocyte ballooning	Absent	34	75.6%	6	16.7%
Hepatocyte ballooning	Present	11	24.4%	30	83.3%
Granuloma	Absent	45	100.0%	36	100.0%
Granuloma	Present	0	0.0%	0	0.0%
Pigments	Absent	44	97.8%	34	94.4%
Pigments	Present	1	2.2%	2	5.6%
Cholestasis	Absent	32	71.1%	22	61.1%
Cholestasis	Present	13	28.9%	14	38.9%
Neutrophils	Absent	35	77.8%	23	63.9%
Neutrophils	Present	10	22.2%	13	36.1%

Beclin1

SD:Standard deviation U: Mann Whitney test

c²: Chi square test FE: Fisher Exact MC: Monte Carlo

p: p value for comparing between CLD and IEM

**: Statistically highly significant at p ≤ 0.01

immunohistochemical (IHC) results

Beclin 1 IHC expression in all the studied groups (Figure 1):

Beclin 1 cytoplasmic expression was identified in 100% of control group and the cases with chronic liver disease while the cases with inborn errors of metabolism 86.1% showed positive beclin 1 expresion. In chronic liver disease group, H score mean ± SD was 227.8±80.87 and the median was 200 while in inborn errors of metabolism (IEM) group the mean± SD was 197.2±110.8 and the median was 200. In control group, the mean± SD was 233.8±60.62 and the median was 200.

Association between Beclin1 H.score of expression and clinicopathological parameters in chronic liver diseases group (n = 45) (Table 3):

Higher H.score of expression was observed to be associated with higher stages of fibrosis and distorted liver architecture in chronic liver diseases group, (P=0.043) for both.

Association between Beclin1 positivity and H.score and clinicopathological parameters in the studied inborn error of metabolism (IEM) group (n = 36)

There was no significant association between Beclin 1 positivity and H score of expression and any of clinicopathological parameters in inborn error of metabolism (IEM) group (Data was not tabulated).

Comparison between the three studied subgroups according to Beclin1 immunohistochemistry (Table 4):

There was a highly statistical significant difference between the three studied groups regarding Beclin1 positivity as it was positively expressed in all (100%) chronic hepatitis group and in all (100%) control group. However it was positively expressed in 86.1% of inborn errors of metabolism (IEM) group (P=0.011). Also, There was a statistical significant difference between the three studied groups regarding Beclin1 intensity and percentage of expression, as both of them were higher in chronic liver diseases group and control groups rather than inborn errors of metabolism (IEM) group (P=0.042, 0.004 respectively).

Beclin1		CLD (n = 45)		IEM (n = 36)		Control (n = 21)		Test of Sig.	p
		No.	%	No.	%	No.	%
Positivity	Negative	0	0.0	5	13.9	0	0.0	χ²= 7.442^*	^MCp= 0.011^*
	Positive	45	100.0	31	86.1	21	100.0
	Sig. bet. grps.	^FEp₁=0.015^*,p₂–,^FEp₃=0.146
Intensity	Negative	0	0.0	5	13.9	0	0.0	χ²= 11.971^*	^MCp= 0.042^*
	Mild	9	20.0	7	19.4	1	4.8
	Moderate	14	31.1	8	22.2	10	47.6
	Strong	22	48.9	16	44.4	10	47.6
	Sig. bet. grps.	^MCp₁=0.074,p₂=0.195,^MCp₃=0.055
	Min. – Max.	1.0 – 3.0		0.0 – 3.0		1.0 – 3.0		H= 1.984	0.371
	Mean ± SD.	2.29 ± 0.79		1.97 ± 1.11		2.43 ± 0.60
	Median (IQR)	2.0 (2.0 – 3.0)		2.0 (1.0 – 3.0)		2.0 (2.0 – 3.0)
	Sig. bet. grps.	p₁>0.05,p₂>0.05,p₃>0.05
Percentage	Min. – Max.	50.0 – 100.0		0.0 – 100.0		80.0 – 100.0		H= 10.990^*	0.004^**
	Mean ± SD.	98.89 ± 7.45		86.11 ± 35.07		96.19 ± 5.90
	Median (IQR)	100(100 – 100)		100(100 – 100)		100(90 – 100)
	Sig. bet. grps.	p₁=0.091,p₂=0.001^*,p₃=0.076
H score	Min. – Max.	50.0 – 300.0		0.0 – 300.0		100.0 – 300.0		H= 1.129	0.569
	Mean ± SD.	227.8 ± 80.87		197.2 ± 110.8		233.8 ± 60.62
	Median (IQR)	200(200 – 300)		200 (100 – 300)		200 (200 – 300)
	Sig. bet. grps.	p₁>0.05,p₂>0.05,p₃>0.05

CLD: Chronic liver diseases. IEM: Inborn errors of metabolism.

IQR: Inter quartile range SD: Standard deviation

c²: Chi square test MC: Monte Carlo

H: H for Kruskal Wallis test, Pairwise comparison bet. each 2 groups was done using Post Hoc Test (Dunn's for multiple comparisons test)

p: p value for comparing between the three studied subgroups

p₁: p value for comparing between CLD and IEM

p₂: p value for comparing between CLD and Control

p₃: p value for comparing between IEM and Control

*: Statistically significant at p ≤ 0.05 **:Statistically highly significant at p ≤ 0.01.

LC3A immunohistochemical (IHC) results:

LC3A immunohistochemical expression in the three studied groups (figure 2):

LC3A positive expression was seen in 51.1% of chronic liver diseases group and 52.8% of inborn errors of metabolism (IEM) group while 81% of control group showed positive LC3A expression. Regarding LC3A H-score of expression, in chronic liver diseases group the mean± SD was 48.22 ± 73.15 and the median was 10 while in inborn errors of metabolism (IEM) group the mean± SD was 63.89 ± 84.12 and the median was 15. And in control group, the mean± SD was 106.7 ± 79.90 and the median was 100.

Association between LC3A positivity and H-score of expression and clinicopathological parameters in the studied chronic liver disease group (n = 45)

There was no significant association between LC3A positivity and H-score of expression and any of clinicopathological parameters in the studied chronic liver disease group (Data was not tabulated).

Association between LC3A positivity and H-score of expression and clinicopathological parameters in the studied inborn error of metabolism (IEM) group (n = 36) (Table 5):

Higher positivity of LC3A was significantly associated with higher stages of fibrosis and distorted liver architecture in the studied inborn error of metabolism (IEM) group (P=0.021) for both.

Association between intensity and percentage of LC3A positive expression and clinicopathological parameters in all studied cases of pediatric steatosis (n = 42) (figure 3)

There was a statistical significant association between higher percentage of LC3A positive expression and presence of hepatocyte ballooning in all studied cases of pediatric steatosis (p=0.035).

Comparison between all studied groups regarding LC3A immunohistochemical expression (Table 6):

The higher positivity of LC3A expression was seen in control group rather than in chronic liver disease group and inborn error of metabolism (IEM) group (P=0.055). as well as higher percentage of LC3A expression was significantly observed in control group when compared with its expression in chronic liver disease group and inborn error of metabolism (IEM) group (P=0.001). Additionally, the mean and median values of H score of LC3A expression were significantly higher in control group in comparison to chronic liver disease group and inborn error of metabolism (IEM) group (P=0.008).

LC3A		CLD (n = 45)		IEM (n = 36)		Control (n = 21)		Test of Sig.	p
		No.	%	No.	%	No.	%
Positivity	Negative	22	48.9	17	47.2	4	19.0	χ²= 5.814	0.055
	Positive	23	51.1	19	52.8	17	81.0
	Sig. bet. grps.	p₁=0.881,p₂=0.021^,p₃=0.033^
Intensity	Negative	22	48.9	17	47.2	4	19.0	χ²= 7.629	^MCp= 0.257
	Mild	11	24.4	9	25.0	9	42.9
	Moderate	8	17.8	5	13.9	6	28.6
	Strong	4	8.9	5	13.9	2	9.5
	Sig. bet. grps.	p₁>0.05,p₂>0.05,p₃>0.05
	Min. – Max.	0 – 3		0 – 3		0 – 3		H= 3.590	0.166
	Mean ± SD.	0.87 ± 1.01		0.94 ± 1.09		1.29 ± 0.90
	Median (IQR)	1 (0 – 2)		1 (0 – 2)		1 (1 – 2)
	Sig. bet. grps.	p₁>0.05,p₂>0.05,p₃>0.05
Percentage	Min. – Max.	0 – 100		0 – 100		0 – 100		H= 13.023^*	0.001^**
	Mean ± SD.	27.33 ± 34.73		35.28 ± 39.96		67.62 ± 38.85
	Median (IQR)	10 (0 – 50)		10 (0 – 80)		80 (50 – 100)
	Sig. bet. grps.	p₁=0.498,p₂<0.001^,p₃=0.004^
H score	Min. – Max.	0 – 300		0 – 270		0 – 300		H= 9.614^*	0.008^**
	Mean ± SD.	48.22 ± 73.15		63.89 ± 84.12		106.7 ± 79.90
	Median (IQR)	10 (0 – 80)		15 (0 – 110)		100 (50 – 140)
	Sig. bet. grps.	p₁=0.485,p₂=0.002^,p₃=0.017^

IQR: Inter quartile range SD: Standard deviation c²: Chi square test MC: Monte Carlo

H: H for Kruskal Wallis test, Pairwise comparison bet. each 2 groups was done using Post Hoc Test (Dunn's for multiple comparisons test)

p: p value for comparing between the three studied subgroups

p₁: p value for comparing between CLD and IEM

p₂: p value for comparing between CLD and Control

p₃: p value for comparing between IEM and Control

**: Statistically highy significant at p ≤ 0.01

According to the current study, Beclin 1 was expressed positively in the cytoplasm of 86.1% of IEM cells, 100% of CLD cells, and 100% of normal liver tissue. It's interesting to note that the Glycogen Storage Disease (GSD) etiology is responsible for the 13.9% of the IEM group who showed negative Beclin 1 expression. The vast spectrum of the illness and the existence of 15 distinct GSD disorders may help to explain why Beclin 1 expression is reduced in some but not all cases of GSD. These findings corroborated those of Gautam et al. (19) and Nascimbeni et al. (20), who noted decreased autophagy in specific glycogen storage disorders (GSD) subtypes known as GSD 1a and GSD II, respectively. In agreement with Farah et al. (21) who claimed that a number of glycogen storage disorders had aberrant autophagy, which can impair normal mitochondrial and/or cellular metabolism.

High Beclin 1 H-score of expression was shown to be substantially correlated with advanced fibrosis stage and deformed liver architecture in the chronic liver disease cases evaluated in the current investigation. These findings may be attributed to the hypothesis put up by Tan et al. (22) that Arrestin, beta 1 (-arr1), a scaffolding protein that controls the transmission of G protein-coupled receptor (GPCR) signalling, promotes liver fibrosis through autophagy-mediated Snail signalling. In addition, Ye et al. (23) have shown that ursodeoxycholic acid (UDCA) has an anti-fibrotic impact on rats with liver fibrosis through inhibiting autophagy. However, Ni et al. (24) discovered that the loss of autophagy in hepatocytes leads to proteotoxicity and disruption of pro- and anti-apoptotic protein homeostasis, which results in liver fibrosis.

The study's findings showed no evidence of a statistical relationship between Beclin 1 expression and steatosis. However, Korovila et al. (25) demonstrated that liver fat deposition brought on by a high-fat diet is linked to autophagy failure, which disturbs proteostasis. This might promote the accumulation and stability of lipid droplets even more. The authors of that study employed an animal model that was dependent on a high-fat diet, which is distinct from the numerous etiologies in our study, therefore it does not match our investigated cases very well.

In terms of LC3A immunoexpression, our study's findings showed a statistically significant difference between the three groups: control, CLD, and IEM. In comparison to CLD and IEM groups, the control group had a higher percentage of LC3A immunohistochemical positive. Additionally, there was a notable difference between the three groups and the LC3A H-score. Compared to the normal control group, the IEM group showed lower autophagy activity by roughly 30%. The continued autophagy activity at later stages of the autophagy pathways is reflected in the expression of LC3A. Lower autophagosome content and lower LC3 are caused by reduced autophagy initiation or impaired autophagosome production. The decreased Beclin 1 levels seen in the metabolic storage disorder in the current study series may help to explain this.

However, we found that LC3A degrees on intensity varied widely between different cases, typically increasing or decreasing. This supports data demonstrating that impairment of autophagic activity can happen at various stages of autophagy regulation throughout the onset of fatty liver disease. Many writers contend that ER stress, which is frequently seen in lipid overload/lipotoxicity models, is the upstream indicator of decreased autophagic flux. It's interesting to note that Mitofusin-2 (Mfn2), which was recently reported by Hernández-Alvarez et al. (26), binds to phosphatidylserine and is in charge of phospholipid transfer between the ER and mitochondria to create phosphatidylethanolamine and phosphatidylcholine. Reduced Mfn2 content and abnormal lipid metabolism are found in mice fed on MCD and HFD as well as human NASH patients. While lipid metabolism was not corrected by preventing ER stress, indicators of fibrosis and inflammation were (26). Cellular lipid composition and mitochondrial phosphatidyl ethanolamine production are known to be needed for full autophagic activation, despite the fact that diminished Mfn2 has been strongly correlated with defective autophagic flux in numerous cell types and tissues (27; 28; 29; 30). Since ATG3 and ATG7, which stand for autophagy-related proteins, integrate phosphatidyl ethanolamine into LC3-I, decreased availability in NASH patients may also be a factor in impaired autophagic flux.

In the current investigation, the LC3A positive, advanced fibrosis, and deformed liver architecture in the inborn error of metabolism (IEM) group were statistically significantly correlated. The findings of Wan et al. (31) and Shu et al. (32) showing LC3-associated phagocytosis protects against hepatic fibrosis were in disagreement with this. Using multiple age groups and varying samples, this result can be explained.

The findings of this study clearly showed that steatosis in CLD differs from steatosis in IEM in terms of the various mechanistic pathologic processes involved. This difference may be attributed to the complexity of the cellular makeup of the liver and the variety in how these cells react to pathological or physiological stimuli, necessitating a cell type-specific approach for modulating autophagy function to achieve the desired effect.

Autophagy might be a double edged sword in pediatric hepatic steatosis as Beclin 1 and LC3A immunohistochemistry revealed different intensity grades reflecting fluctuation of autophagy at different stages of the disease and different disease etiology.

Ethical Approval

This paper was approved by ethical committee of faculty of medicine, Menofia university (191219PATH14)

Consent for publication

Not applicable

Ethics approval and consent to participate

All methods were carried out in accordance with relevant guidelines and regulations.

Informed consent was obtained from all subjects

Competing interests

No conflict of interest regarding this manuscript

Authors' contributions

Marwa Gadallah and Nanis Holah wrote the manuscript and results, Nermine Ehsan and Mona Kandil prepared the figures and discussion, Gihan Sobhycollected the clinical data, Mohamed Mohamadyprepared the slides , Shaymaa El-Gammal did the statistical analysis and results and all authors revised the paper.

Funding

No funding

Availability of data and materials

All data mentioned in this manuscript and methods are available at the corresponding author on request.

Acknowledgement

Not applicable

Karhan AN, Hizarcioglu-Gulsen H, Gumus E, Akçören Z, Demir H, Saltik-Temizel İN, Orhan D, et al. Distinctive Features of Hepatic Steatosis in Children: Is It Primary or Secondary to Inborn Errors of Metabolism?. Pediatric Gastroenterology, Hepatology & Nutrition. 2021 Nov;24(6):518.
Anderson EL, Howe LD, Jones HE, Higgins JP, Lawlor DA, Fraser A. The prevalence of non-alcoholic fatty liver disease in children and adolescents: a systematic review and meta-analysis. PloS one. 2015 Oct 29;10(10):e0140908.
Eslam M, Sanyal AJ, George J. Toward more accurate nomenclature for fatty liver diseases. Gastroenterology. 2019 Sep 1;157(3):590-3.
Zheng KI, Fan JG, Shi JP, Wong VW, Eslam M, George J, et al. From NAFLD to MAFLD: a" redefining" moment for fatty liver disease. Chinese medical journal. 2020 Oct 5;133(19):2271-3.
Deretic V, Saitoh T, Akira S. Autophagy in infection, inflammation and immunity. Nature Reviews Immunology. 2013 Oct;13(10):722-37.
Kaushik S, Cuervo AM. Degradation of lipid droplet-associated proteins by chaperone-mediated autophagy facilitates lipolysis. Nature cell biology. 2015 Jun;17(6):759-70.
Rubinsztein DC, Shpilka T, Elazar Z. Mechanisms of autophagosome biogenesis. Curr Biol (2012) 22(1):R29–34.
Mizushima N, Komatsu M. Autophagy, renovation of cells and tissues. Cell (2011) 147(4):728–41.
Mizumura K, Choi AM, Ryter SW. Emerging role of selective autophagy in human diseases. Frontiers in pharmacology. 2014 Nov 5;5:244.
Grefhorst A, van de Peppel I, Larsen L, Jonker J and Holleboom A. The role of lipophagy in the development and treatment of nonalcoholic fatty liver disease. Frontiers in Endocrinology (2021);11:1-12.
Cao Y, Klionsky DJ. Physiological functions of Atg6/Beclin 1: a unique autophagy-related protein. Cell research. 2007 Oct;17(10):839-49.
Sun D, Wu R, Zheng J, Li P, Yu L. Polyubiquitin chain-induced p62 phase separation drives autophagic cargo segregation. Cell research. 2018 Apr;28(4):405-15.
Zhong Y, Wang QJ, Li X, Yan Y, Backer JM, Chait BT, et al. Distinct regulation of autophagic activity by Atg14L and Rubicon associated with Beclin 1–phosphatidylinositol-3-kinase complex. Nature cell biology. 2009 Apr;11(4):468-76.
Baeken MW, Weckmann K, Diefenthäler P, Schulte J, Yusifli K, Moosmann B, et al. Novel insights into the cellular localization and regulation of the autophagosomal proteins LC3A, LC3B and LC3C. Cells. 2020 Oct;9(10):2315.
Al‐Shenawy HA. Expression of Beclin‐1, an autophagy‐related marker, in chronic hepatitis and hepatocellular carcinoma and its relation with apoptotic markers. Apmis. 2016 Mar;124(3):229-37.
Giatromanolaki A, Koukourakis MI, Harris AL, Polychronidis A, Gatter KC, Sivridis E. Prognostic relevance of light chain 3 (LC3A) autophagy patterns in colorectal adenocarcinomas. Journal of clinical pathology. 2010 Oct 1;63(10):867-72.
Fedchenko N, Reifenrath J. Different approaches for interpretation and reporting of immunohistochemistry analysis results in the bone tissue–a review. Diagnostic pathology. 2014 Dec;9(1):1-2.
Dawson LC, Romine GS, Trapp RJ, Baldwin ME. Verifying supercellular rotation in a convection-permitting ensemble forecasting system with radar-derived rotation track data. Weather and Forecasting. 2017 Apr 1;32(2):781-95.
Gautam S, Zhang L, Arnaoutova I, Lee C, Mansfield BC, Chou JY. The signaling pathways implicated in impairment of hepatic autophagy in glycogen storage disease type Ia. Human Molecular Genetics. 2020 Mar 1;29(5):834-44.
Nascimbeni AC, Fanin M, Masiero E, Angelini C, Sandri M. The role of autophagy in the pathogenesis of glycogen storage disease type II (GSDII). Cell Death & Differentiation. 2012 Oct;19(10):1698-708.
Farah BL, Yen PM, Koeberl DD. Links between autophagy and disorders of glycogen metabolism–Perspectives on pathogenesis and possible treatments. Molecular genetics and metabolism. 2020 Jan 1;129(1):3-12.
Tan S, Lu Y, Xu M, Huang X, Liu H, Jiang J, et al. β‐Arrestin1 enhances liver fibrosis through autophagy‐mediated Snail signaling. The FASEB Journal. 2019 Feb;33(2):2000-16.
Ye HL, Zhang JW, Chen XZ, Wu PB, Chen L, Zhang G. Ursodeoxycholic acid alleviates experimental liver fibrosis involving inhibition of autophagy. Life Sciences. 2020 Feb 1;242:117175.
Ni HM, Woolbright BL, Williams J, Copple B, Cui W, Luyendyk JP,et al. Nrf2 promotes the development of fibrosis and tumorigenesis in mice with defective hepatic autophagy. Journal of hepatology. 2014 Sep 1;61(3):617-25.
Korovila I, Höhn A, Jung T, Grune T, Ott C. Reduced Liver Autophagy in High-Fat Diet Induced Liver Steatosis in New Zealand Obese Mice. Antioxidants. 2021 Apr;10(4):501.
Hernández-Alvarez MI, Sebastián D, Vives S, Ivanova S, Bartoccioni P, Kakimoto P, et al. Deficient endoplasmic reticulum-mitochondrial phosphatidylserine transfer causes liver disease. Cell. 2019 May 2;177(4):881-95.
Muñoz JP, Ivanova S, Sánchez‐Wandelmer J, Martínez‐Cristóbal P, Noguera E, Sancho A, Díaz‐Ramos A, et al. Mfn2 modulates the UPR and mitochondrial function via repression of PERK. The EMBO journal. 2013 Aug 28;32(17):2348-61.
Sebastián D, Sorianello E, Segalés J, Irazoki A, Ruiz‐Bonilla V, Sala D, et al. Mfn2 deficiency links age‐related sarcopenia and impaired autophagy to activation of an adaptive mitophagy pathway. The EMBO journal. 2016 Aug 1;35(15):1677-93.
Koga H, Kaushik S, Cuervo AM. Altered lipid content inhibits autophagic vesicular fusion. The FASEB Journal. 2010 Aug;24(8):3052-65.
Thomas HE, Zhang Y, Stefely JA, Veiga SR, Thomas G, Kozma SC, et al. Mitochondrial complex I activity is required for maximal autophagy. Cell reports. 2018 Aug 28;24(9):2404-17.
Wan J, Weiss E, Ben Mkaddem S, Mabire M, Choinier PM, Picq O, et al. LC3-associated phagocytosis protects against inflammation and liver fibrosis via immunoreceptor inhibitory signaling. Science translational medicine. 2020 Apr 15;12(539):eaaw8523.
Shu Y, Liu X, Huang H, Wen Q, Shu J. Research progress of natural compounds in anti-liver fibrosis by affecting autophagy of hepatic stellate cells. Molecular Biology Reports. 2021 Feb;48(2):1915-24.

No competing interests reported.

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Does autophagy have a role in the pathogenesis of pediatric hepatic steatosis?

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