metricas
covid
Buscar en
Annals of Hepatology
Toda la web
Inicio Annals of Hepatology Hepatic mir-122-3p, mir-140-5p and mir-148b-5p expressions are correlated with c...
Journal Information
Vol. 27. Issue 6.
(November - December 2022)
Share
Share
Download PDF
More article options
Visits
1028
Vol. 27. Issue 6.
(November - December 2022)
Original article
Full text access
Hepatic mir-122-3p, mir-140-5p and mir-148b-5p expressions are correlated with cytokeratin-18 serum levels in MAFLD
Visits
1028
Guillermo N. López-Sáncheza, Eduardo Montalvo-Javéb,c,d, Mayra Domínguez-Pereze, Barbara Antuna-Puentef, Fredy O. Beltrán-Anayag, Alfredo Hidalgo-Mirandah, Norberto C. Chávez-Tapiaa,d, Misael Uribed,
Corresponding author
muribe@medicasur.org.mx

Corresponding authors.
, Natalia Nuño- Lámbarria,
Corresponding author
a Traslational Research Unit, Medica Sur Clinic & Foundation, Mexico City, Mexico
b Department of Surgery, Faculty of Medicine, The National Autonomous University of Mexico (UNAM), Mexico City, Mexico
c Hepato Pancreato and Biliary Clinic, Department of General Surgery, “Hospital General de Mexico”, Dr. Eduardo Liceaga. Mexico City, Mexico
d Obesity and Digestive Diseases Unit, Medica Sur Clinic & Foundation, Mexico City, Mexico
e Genomics of Cardiovascular Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
f Infection Disease Division, Department of Medicine, Queen's University, Kingston, ON, Canada
g Virology Laboratory, Faculty of Chemical Biological Sciences, UAGro. Lázaro Cárdenas
h Genomics of Cancer Diseases Laboratory, National Institute of Genomic Medicine. Mexico City, Mexico
This item has received
Article information
Abstract
Full Text
Bibliography
Download PDF
Statistics
Figures (1)
Tables (3)
Table 1. Anthropometric and biochemical characteristics
Table 2. Non-alcoholic Fatty Liver Disease Activity Score (NAS) of human liver biopsies
Table 3. Correlation analysis between miRNAs, MAFLD and CAP
Show moreShow less
Abstract
Introduction and objectives

Metabolic-associated fatty liver disease (MAFLD) is defined by steatosis in more than 5% of hepatocytes without other liver diseases. Patients with this disease can progress to multiple stages like liver fibrosis, cirrhosis, and hepatocellular carcinoma. miRNAs are single-stranded molecules that regulate metabolic homeostasis; their differential expression postulates them as potential circulating biomarkers for MAFLD. Previous research reported that hsa-miR-140-5p, hsa-miR-148-5p, and hsa-miR-122-3p have a differential expression in patients with MAFLD. This study aimed to investigate the correlation between liver hsa-miR-140-5p, hsa-miR-148-5p, and hsa-miR-122-3p and serum biomarkers CK-18, APOB, IL-6, IL-32, and TNF-α in patients with MAFLD compared with control patients.

Materials and methods

A cross-sectional study was carried out with 16 patients of both sexes, aged between 18-60 years, to determine the association between the levels of hsa-miR-140-5p, hsa-miR-148-5p, and hsa-miR-122-3p with MAFLD in liver biopsies of patients who underwent laparoscopic cholecystectomy.

Results

Twelve patients presented MAFLD, four without hepatic steatosis. Circulating levels of CK-18 showed a significant difference in patients with MAFLD, and a strong correlation was found between hsa-miR-122-3p, hsa-miR-140-5p, and hsa-miR-148b-5p versus the CAP value.

Conclusion

There is a correlation between elevated tissue expression of hsa-miR-122-3p, hsa-miR-140-5p, and hsa-miR-148b-3p with plasma levels of CK-18 in patients with simple steatosis compared with patients without the disease.

Keywords:
microRNA
Metabolic dysregulation
Biomarkers
Liver
Abbreviations:
ALP
ALT
APOB
AST
AUDIT
BMI
CAP
CK-18
GGT
hsa-miR
IL-6
IL-32
LDH
MAFLD
MASH
NAS
T2DM
TC
TG
TNF-α
Full Text
1Introduction

Metabolic (dysfunction) associated fatty liver disease (MAFLD) is defined by steatosis in more than 5% of hepatocytes in the absence of other liver diseases, and is also the novel term for hepatic steatosis. MAFLD's current diagnosis includes evidence of hepatic steatosis, plus one of the following three criteria: overweight/obesity, metabolic dysregulation, or type 2 diabetes mellitus (T2DM) [1]. Its progression is conformed by metabolic-associated steatohepatitis (MASH), characterized by steatosis, inflammation, and fibrosis, with a final and irreversible stage such as cirrhosis and hepatocellular carcinoma [2]. The metabolic dysregulation is characterized by macrovesicular hepatic steatosis, obesity or overweight, and insulin resistance [3]. The overall prevalence of MAFLD is 38.77% (95% CI 32.94-44.95), where 5.37% (95% CI 4.36-6.59) are lean individuals [4]. Among overweight/obese adults, the estimated global prevalence is 50.7% (95% CI 46.9-54.4); this shows how MAFLD affects more than a third of the world's population [5]. Metabolic complications such as diabetes and hypertension are significant associated factors [4].

Insulin resistance induces de novo hepatic lipogenesis and alters the inhibition of adipose tissue lipolysis, creating a lipotoxic environment in the liver [6]. The subsequent stage is the secretion of adipokines and inflammatory cytokines by adipose tissue, such as Apolipoprotein B (APOB), interleukin 6 (IL-6), interleukin 32 (IL-32), and tumor necrosis factor-α (TNF-α) which have also been proposed as potential biomarkers of the disease [7], as well as simultaneous predisposed genetic and epigenetic factors that modify the progression of MAFLD. Another potential biomarker is cytokeratin 18 (CK-18), a cytoskeleton protein in large amounts in the liver. It is an intermediate filament protein that represents 5% of hepatic proteins. This molecule has been reported to have a positive correlation with serum ALT levels, and with the controlled attenuation parameter of transient elastography in patients with MAFLD [8,7] CK-18 is the major intermediate filament protein in hepatocytes and is released at the initiation of cell death, this association has made circulating CK-18 a candidate marker to detect MASH and fibrosis as part of a multi-marker model [9].

Liver biopsy is the gold standard [10]; however, due to the high prevalence of the disease, this method cannot be considered optimal for screening the general population, which has generated significant interest in developing and researching non-invasive methods to identify the disease and its late progression stages. MicroRNAs have been proposed as diagnostic and prognostic biomarkers involved in adaptation to changes in the liver microenvironment, which could improve clinical intervention strategies in patients with MAFLD [11,12]. Previous data reported the hsa-miR-140-5p, hsa-miR-148-5p, and hsa-miR-122-3p have a differential expression in patients with MAFLD compared with control subjects without MAFLD [13]. The miR122-3p is the most abundant and studied hepatic microRNAs; it represents 70% of the total hepatic miRNAs [11,14–16], while little is known about miR-140-5p and miR-148-5p and their liver functions and results as novel non-coding microRNAs proposed as biological markers. In this study, we aimed to investigate the association between the levels of hsa-miR-140-5p, hsa-miR-148-5p, and hsa-miR-122-3p in liver biopsies in patients with MAFLD, which can be crucial to be candidate biomarkers for diagnosis.

2Methods

A cross-sectional study was carried out with 16 patients of both sexes, aged between 18-60, years to determine the association between the levels of hsa-miR-140-5p, hsa-miR-148-5p, and hsa-miR-122-3p with MAFLD in liver biopsies of patients who underwent laparoscopic cholecystectomy. Once they agreed to participate, informed consent was signed to obtain a liver biopsy of the right lobe (approximately 0.5-1.0 cm3), and a blood sample was obtained before surgery. The presence of other liver diseases, such as viral, autoimmune, toxicological, or drug-induced, was ruled out, and alcohol intake was not greater than 20g per day through the Alcohol Use Disorders Identification Test (AUDIT).

2.1Clinical evaluation

Anthropometric variables such as gender, age (years), weight (Kg), and height (m) were obtained from the patient's clinical record. Laboratory data were obtained: fasting glucose, triglycerides (TG), total cholesterol (TC), alanine, and aspartate aminotransferase (ALT-AST), gamma-glutamyltranspeptidase (GGT), lactate dehydrogenase (LDH), alkaline phosphatase (ALP) and albumin.

2.2Hepatic vibration-controlled transient elastography

Transient elastography was performed using Fibroscan® Touch 502 (Echosense, France) after a minimum of 4 hours of fasting with the M or XL probe. The patient was placed supine with the right arm adducted and the hand under the head; the rest of the limbs extended. Next, an imaginary line was drawn between the xiphoid apophysis and the mid-clavicular line, on which an optimal intercostal space was sought, and the transducer was placed. The study was completed with the following characteristics: at least ten valid measurements, 60% success (valid measurements/invalid measurements), and the interquartile/median range was 30%. The median Controlled Attenuation Parameter (CAP) in decibels per meter (dB/m), the median liver stiffness in kilopascals (kPa), and the interquartile range were obtained. Steatosis degree according to the CAP was determined, cutoff values were S0: <232 dB/m, S1: 232–256 dB/m, S2: 257–290 dB/m, S3: ≥290 dB/m, and hepatic fibrosis degree was determined according to LSM, were F2≥7.0 kPa, F3: ≥8.7 kPa, F4: ≥10.3 kPa.

2.3Liver histology

Liver biopsies were formalin-fixed, paraffin-embedded, and examined using hematoxylin-eosin staining. Two expert pathologists independently diagnosed the biopsy specimens blindly, without knowing the patient's clinical data. Any difference in observations was rectified by consensus. The Kleiner score [17] includes three semi-quantitative parameters, which are added to obtain a score of 0-8 points: steatosis according to the hepatocytes percentage lipid droplets (grade 0: <5%, 1: 5−33%, 2: 33−66%, and 3: >66%), lobular inflammation measured in foci per field (grade 0: none, 1: <2, 2: 2-4, 3: >4), hepatocytes ballooning (grade 0: none, 1: few cells, 2: many cells). Liver fibrosis was also assessed (grade 1: perisinusoidal or periportal, 1A: mild perisinusoidal fibrosis in zone 3, 1B: moderate perisinusoidal fibrosis in zone 3, 1C: only portal/periportal fibrosis, 2: perisinusoidal fibrosis in zone 3, with portal/periportal fibrosis, 3: fibrosis bridges, 4: cirrhosis).

2.4RNA extraction

Sixteen liver samples were selected based on their histology (4 without MAFLD and 12 MAFLD) to determine the level expression of the miR-140-5p, miR-148-5p, and miR-122-3p. Total RNA was extracted using TRIzol reagent (Invitrogen, USA) and chloroform. After that, RNA quality was determined using the Agilent 2100 bioanalyzer (Agilent Technologies, China).

2.5Quantitative Real-Time PCR

A reverse transcription assay was performed using TaqMan microRNA reagents (Applied Biosystems, USA), adding the small nucleolar RNA RNU-48 as an internal control. Total RNA was isolated from 16 independent samples (4 without MAFLD and 12 MAFLD). The Taqman Universal MasterMix NO UNG kit and the Taqman probes for each microRNA hsa-miR-122-3p, hsa-miR-140-5p, and hsa-miR-148-5p (Applied Biosystems, USA) were used. The assay was performed in triplicate, and the relative amount of change of each microRNA was calculated using equation 2 –(ΔCT), where ΔCT= Ct (miRNA MAFLD - CtRNU48-MAFLD) - Ct (miRNA control – CtRNU48-control). The rate of change and the p-value were calculated.

2.6Determination of circulating levels of CK-18, APO-B, IL-6, IL-32, TNF-a

An ELISA assay was used to measure circulating levels of human CK-18, APO-B, IL-6, IL-32, and TNF-α by Quantikine Immunoassays (R&D systems, Minneapolis, MN), following the manufacturer's instructions.

2.7Statistical analysis

Statistical analysis was performed using SPSS for Macintosh v20.0 (IBM, USA). Results are presented as median ± interquartile range or percentages. Due to the small sample size, the continuous variables were analyzed by a non-parametric U test to compare two groups, and the chi-square test was used to compare categorical variables. Spearman and Pearson's correlation was determined to analyze the relationship between expression levels of microRNAs and MAFLD. Statistical significance was defined as p≤0.05.

2.8Ethical declarations

The ethics committee of Medica Sur Hospital approved this study (2017-EXT-238). The patients signed the informed consent to obtain the liver biopsy and store the information in the database that was used in the research, which follows the basic principles of human research in the Helsinki Declaration (Helsinki Finland 1975, last amendment at the 52nd General Assembly in Fortaleza, Brazil, October 2013). The collected data were treated confidentially, with an attached privacy notice to the informed consent.

3Results

Table 1 describes the patient's anthropometric and biochemical characteristics, where 87.5% were women and 12.5% were men. The mean age was 49.4±10.6 years, the mean weight was 70.9±14.6 Kg, and the BMI 29±4Kg/m2. The BMI, CAP, and liver stiffness had a statistical difference between the groups. Sixteen liver samples were selected by histopathological evaluation; four patients did not present microscopic abnormalities with a Kleiner score equal to 0, forming the control group (Figure 1A), and twelve patients with a score of 1-4 formed the MAFLD group (Figure 1B). Patients with a NAS score ≥5 were discarded for this study. The histological characteristics are presented in Table 2.

Table 1.

Anthropometric and biochemical characteristics

  Without MAFLDMAFLDp value
  (n=4)(n=12)
  Median  1Q  3Q  Median  1Q  3Q   
Age (years)  47  33.7  57.2  51.5  40.2  58.2  0.521 
BMI (Kg/m223.8  22.5  24.8  31.1  30.1  32.1  0.004 
Fastin Glucose (mg/dL)  81  76.5  125.2  99.5  91.8  127.6  0.316 
Triglycerides (mg/dL)  161.5  101  267  177  95  388.2  0.9 
Total cholesterol (mg/dL)  186.5  171.7  296.5  196  171.2  238.4  0.862 
ALT (IU/L)  18.5  12.7  25.7  19  14  41.7  0.684 
AST (IU/L)  22  16.5  33.5  20  17  27  0.953 
GGT(IU/L)  15.5  12.5  100.2  31.5  17.5  276.9  0.262 
LDH (IU/L)  198.5  172  228.7  163.5  154.5  188.2  0.17 
ALP (IU/L)  103.5  54.7  138  76.5  58  102.5  0.521 
Albumin (mg/dL)  3.6  4.6  4.3  4.1  4.4  0.684 
CAP (dB)  119.5  118.2  120.7  299.5  290.2  311.7  0.001 
Liver stiffness (kPa)  2.6  2.1  2.9  3.9  3.2  5.2  0.004 

Mann-Whitney U test, differences were considered significant at p ≤ 0.05 between groups. MAFLD, Metabolic associated fatty liver disease; 1Q, first interquartile; 3Q, third interquartile; BMI, body mass index; ALT, alanine aminotransferase; AST, aspartate aminotransferase, GGT, gamma glutamyl transpeptidase; LDH, lactate dehydrogenase, ALP, alkaline phosphatase, CAP, Controlled Attenuation Parameter

Fig. 1.

Liver histology, potential MAFLD biomarkers and microRNA expression from liver biopsies. A) Liver without steatosis, B) Liver with MAFLD, representative images of sixteen hepatic tissues obtained from human biopsies, stained with H&E. Original magnification 100×. C) Cytokeratin-18 (CK-18) serum levels in patients with and without MAFLD, D) hsa-miR-122-3p change rate, E) hsa-miR-140-5p change rate, and F) hsa-miR-148-5p change rate (2−ΔΔCT) between patients with and without MAFLD. The differences (*) in the mean ± standard deviation were considered significant with a p ≤ 0.001 between groups. Fold Change (FC).

(0.49MB).
Table 2.

Non-alcoholic Fatty Liver Disease Activity Score (NAS) of human liver biopsies

Biopsy  Steatosis  Inflammation  Ballooning  NAS  Group 
Without MAFLD 
Without MAFLD 
Without MAFLD 
Without MAFLD 
MAFLD 
MAFLD 
MAFLD 
MAFLD 
MAFLD 
10  MAFLD 
11  MAFLD 
12  MAFLD 
13  MAFLD 
14  MAFLD 
15  MAFLD 
16  MAFLD 

NAS, Non-alcoholic Fatty Liver Disease Activity Score; MAFLD, Metabolic (dysfunction) Associated Fatty Liver Disease

Circulating levels of CK-18, APO-B, IL-6, IL-32, and TNF-α were evaluated; however, only CK-18 showed a significant difference (p≤ 0.001) when comparing patients without MAFLD (104.1pg/mL) against patients with MAFLD (230.2pg/mL). (Figure 1C) No differences were found between the groups in the remaining markers explored. On the other hand, the change rates (2−ΔΔCT) of hsa-miR-122-3p, hsa-miR-140-5p, and hsa-miR-148-5p were determined by qRT-PCR. When the 2−ΔΔCT was compared between groups, only hsa-miR-148a-5p showed a statistical difference; however, hsa-miR-122-3p and hsa-miR-140-5p had a higher fold change, showing the same behavioral trend as previous microarray differential expression data.[13] (Figure 1D-F)

The results of the Spearman analysis show a very strong correlation between hsa-miR-122-3p and MAFLD (rho= 0.751 p= 0.001), a good correlation for hsa-miR-148b-5p (rho= 0.689 p= 0.003) and acceptable for hsa-miR-140-5p (rho= 0.564 p= 0.023). On the other hand, through Pearson's analysis, a strong correlation was found between hsa-miR-122-3p, hsa-miR-140-5p, and hsa-miR-148b-5p versus the CAP value. While hsa-miR-122-3p, hsa-miR-140-5p and hsa-miR-148b-5p show a moderate correlation with CK-18 (r= 0.536; r= 0.404 and r= 0.504 respectively); however, the correlation between CK-18 and hsa-miR-140-5p was not statistically different. (Table 3)

Table 3.

Correlation analysis between miRNAs, MAFLD and CAP

Vs. MAFLD     
  Spearman's Rho  p-value 
hsa-miR-122-3p  0.751  0.001 
hsa-miR-140-5p  0.564  0.023 
hsa-miR-148b-5p  0.689  0.003 
Vs. CAP     
  Pearson's "r"  p-value 
hsa-miR-122-3p  0.923  <0.001 
hsa-miR-140-5p  0.749  0.001 
hsa-miR-148b-5p  0.757  0.001 
Vs. CK-18     
  Pearson's "r"  p-value 
hsa-miR-122-3p  0.536  0.032 
hsa-miR-140-5p  0.404  0.12 
hsa-miR-148b-5p  0.504  0.047 

Correlation analysis. The table shows the results of the Spearman correlation analysis between the MAFLD diagnosed by liver biopsy and hepatic expression levels of the 3 microRNAs, and the Pearson correlation between the CAP values versus the hepatic expression levels of the 3 microRNAs.

has-miR, Homosapiens-microRNA; CAP, Controlled Attenuation Parameter; CK-18, Cytokeratin-18

4Discussion

As obesity and metabolic syndrome increase, cases of MAFLD grow in parallel to the point that it is currently the liver disease with the highest incidence worldwide [18–20], which has aroused greater interest in establishing the pathophysiological mechanisms, in addition to promoting the exploration of new tools for early diagnosis and novel biomarkers that determine the risk of progression to more severe stages of the disease.

Circulating biomarkers levels, previously described and proposed as possible diagnostic tools, are CK-18, APO-B, IL-6, IL-32, and TNF-α. Among these, a difference was found in CK-18 levels in our cohort study [7,21]. CK-18 is a protein related to apoptotic processes through caspase-3 and has been evaluated as a differentiating factor between subjects with simple steatosis and those with steatohepatitis; also a potential hepatocellular marker [22–24]. In this study, we corroborated the potential of this circulating protein fragment as a biomarker of steatosis in patients with a chronic inflammatory process.

MicroRNAs are currently considered potential molecular biomarkers to diagnose multiple diseases, including MAFLD [11,25–27] Using liver samples from patients with MAFLD, we demonstrated a strong correlation between hepatic expression levels of hsa-miR-122-3p, hsa-miR-140-5, and hsa-miR-148b-5p, and the disease. Due to MAFLD complexity, there is high variability between patients and therefore in the expression levels of miR-122-3p and miR-140-5p; however, these miRNAs presented values above double when comparing the levels with the control group. Possibly, there is no statistical difference because of the reduced sample. Elevated levels of miR-122 are associated with several cellular processes such as hepatocyte lipogenesis and triglycerides and cholesterol accumulation through the repression of Sirt1 and the inactivation of the LKB1/AMPK pathway that enhances the accumulation of intrahepatic fat [28].

Elevated levels of hsa-miR-122 are associated with several cellular processes such as lipogenesis in the hepatocyte and its accumulation of intracellular triglycerides and cholesterol through the repression of Sirt1 and the inactivation of the LKB1/AMPK pathway that enhances intrahepatic fat accumulation. Increased levels of this microRNA are associated with progression to a pro-inflammatory state due to activation of the TLR4/MyD88 signaling pathway and increased NFκ-Bp65 [16], which could position it as a potential biomarker for liver disease.

Little has been reported about hsa-mirR-140-5p, and its relationship with MAFLD is still unknown, so it is a novel molecule in this disease. It is known from previous experiments that its overexpression is associated with negative regulation of the LDLR receptor in human hepatocytes, decreasing cholesterol uptake and causing triglyceride accumulation [29]. Another observational study found this microRNA elevated in adolescents with obesity and insulin resistance [30]. The complex mechanisms of progression to more severe stages probably involve one or more cellular pathways where hsa-miR-140-5p has interaction targets. The hsa-miR-148b-5p has been associated with various epigenetic mechanisms, B and T cell differentiation, tumorigenesis [31], and biological processes such as adipogenesis, [32] but its relationship with liver diseases has not yet been explored: So far it is known that the isoform hsa-miR-148b-3p controls the expression of DTYMK, a potential oncogene related to the development of HCC [33]. Our study is the first to show the potential usefulness of this molecule as a novel liver biomarker.

Our study has limitations since, in order to propose some of these microRNAs as biomarkers, it is necessary to explore them in the bloodstream, so we intend to recruit more patients to determine the expression of these microRNAs and their target genes.

5Conclusions

In conclusion, this study describes the correlation between elevated tissue expression of hsa-miR-122-3p, hsa-miR-140-5p, and hsa-miR-148b-3p with plasma levels of CK-18 in patients with simple steatosis compared with patients without the disease. These molecules may play a vital role in the pathogenesis of the disease with non-invasive diagnostic power.

Funding

Guillermo N. López-Sánchez was a CONACyT scholarship holder with number 164209. Fundación Clínica Médica Sur provided the resources for this research.

Author's contributions

All authors contributed to the article's realization and improvement and agreed on the manuscript's content. Dr. López-Sánchez, Dr. Nuño Lámbarri and Dr. Uribe design, carried out the study and drafted the article. Dr. Montalvo-Javé was the surgeon who provided the patient's biopsies, contributed with diverse ideas, and corrected the final version of the manuscript; Dr. Domínguez-Perez, Dr. Antua-Puente, Dr. Beltrán-Anaya, Dr. Hidalgo-Miranda, Dr. Chávez-Tapia, and Dr. Uribe revised, contributed with diverse ideas, and corrected the final version of the manuscript. The definitive version has been read and approved by all authors.

Acknowledgments

We appreciate the support of Medica Sur Clinic and Foundation and Gastroenterology and Obesity Clinic so that this article could be carried out. We also thank the UNAM PAEP 2020 program for supporting this work.

References
[1]
M Eslam, PN Newsome, SK Sarin, QM Anstee, G Targher, M Romero-Gomez, et al.
A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement.
[2]
MS Kuchay, A. Misra.
From non-alcoholic fatty liver disease (NAFLD) to metabolic-associated fatty liver disease (MAFLD): A journey over 40 years.
Diabetes Metab Syndr, 14 (2020), pp. 695-696
[3]
H Jarvis, D Craig, R Barker, G Spiers, D Stow, QM Anstee, et al.
Metabolic risk factors and incident advanced liver disease in non-alcoholic fatty liver disease (NAFLD): a systematic review and meta-analysis of population-based observational studies.
[4]
KE Chan, TJL Koh, ASP Tang, J Quek, JN Yong, P Tay, et al.
Global prevalence and clinical characteristics of metabolic-associated fatty liver disease: a meta-analysis and systematic review of 10 739 607 individuals.
J Clin Endocrinol Metab, (2022),
[5]
J Liu, I Ayada, X Zhang, L Wang, Y Li, T Wen, et al.
Estimating global prevalence of metabolic dysfunction-associated fatty liver disease in overweight or obese adults.
Clin Gastroenterol Hepatol, 20 (2022), pp. e573-e582
[6]
E Buzzetti, M Pinzani, EA. Tsochatzis.
The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD).
Metabolism, 65 (2016), pp. 1038-1048
[7]
S Kosasih, W Zhi Qin, R Abdul Rani, N Abd Hamid, N Chai Soon, S Azhar Shah, et al.
Relationship between serum cytokeratin-18, control attenuation parameter, nafld fibrosis score, and liver steatosis in nonalcoholic fatty liver disease.
Int J Hepatol, (2018), pp. 2018
[8]
B Altaf, A Rehman, S Jawed, A. Raouf.
Association of liver biomarkers and cytokeratin-18 in Nonalcoholic fatty liver disease patients.
[9]
J Lee, Y Vali, J Boursier, K Duffin, J Verheij, M Julia Brosnan, et al.
Accuracy of cytokeratin 18 (M30 and M65) in detecting non-alcoholic steatohepatitis and fibrosis: a systematic review and meta-analysis.
[10]
A. Engin.
Non-alcoholic fatty liver disease.
Adv Exp Med Biol, 960 (2017), pp. 443-467
[11]
GN López-Sánchez, M Dóminguez-Pérez, M Uribe, NC Chávez-Tapia, N. Nuño-Lámbarri.
Non-alcoholic fatty liver disease and microRNAs expression, how it affects the development and progression of the disease.
[12]
KKW To, CWS Tong, W Mingxia, WCS. Cho.
MicroRNAs in the prognosis and therapy of colorectal cancer: from bench to bedside.
World J Gastroenterol, 24 (2018), pp. 2949-2973
[13]
The International Liver CongressTM 2020, London, UK. J Hepatol 2020;72:ii. https://doi.org/10.1016/S0168-8278(19)30682-8.
[14]
W-C Tsai, S-D Hsu, C-S Hsu, T-C Lai, S-J Chen, R Shen, et al.
MicroRNA-122 plays a critical role in liver homeostasis and hepatocarcinogenesis.
J Clinical Investigation, 122 (2012), pp. 2884-2897
[15]
M Thomas, A. Deiters.
MicroRNA miR-122 as a therapeutic target for oligonucleotides and small molecules.
Curr Med Chem, 20 (2013), pp. 3629-3640
[16]
Y Hu, G Du, G Li, X Peng, Z Zhang, Y. Zhai.
The miR-122 inhibition alleviates lipid accumulation and inflammation in NAFLD cell model.
Arch Physiol Biochem, 127 (2021), pp. 385-389
[17]
DE Kleiner, EM Brunt, M Van Natta, C Behling, MJ Contos, OW Cummings, et al.
Design and validation of a histological scoring system for nonalcoholic fatty liver disease.
Hepatology, 41 (2005), pp. 1313-1321
[18]
Z Younossi, QM Anstee, M Marietti, T Hardy, L Henry, M Eslam, et al.
Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention.
Nat Rev Gastroenterol Hepatol, 15 (2018), pp. 11-20
[19]
Z Younossi, F Tacke, M Arrese, B Chander Sharma, I Mostafa, E Bugianesi, et al.
Global perspectives on nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.
Hepatology, 69 (2019), pp. 2672-2682
[20]
I Rodríguez-Antonio, GN López-Sánchez, VA Reyes-Gómez, EH Contreras-Flores, F Farías-García, M Espejel-Deloiza, et al.
Laparoscopic cholecystectomy: Histopathological analysis of metabolic associated fatty liver disease and fibrosis.
[21]
N Alkhouri, C Carter-Kent, AE. Feldstein.
Apoptosis in nonalcoholic fatty liver disease: diagnostic and therapeutic implications.
Http://DxDoiOrg/101586/Egh116, 5 (2014), pp. 201-212
[22]
M Kawanaka, K Nishino, J Nakamura, N Urata, T Oka, D Goto, et al.
Correlation between serum cytokeratin-18 and the progression or regression of non-alcoholic fatty liver disease.
Ann Hepatol, 14 (2015), pp. 837-844
[23]
GN López-Sánchez, M Dóminguez-Pérez, M Uribe, N. Nuño-Lámbarri.
The fibrogenic process and the unleashing of acute-on-chronic liver failure.
Clin Mol Hepatol, 26 (2020), pp. 7-15
[24]
E Fitzpatrick, RR Mitry, A Quaglia, MJ Hussain, R DeBruyne, A. Dhawan.
Serum levels of CK18 M30 and leptin are useful predictors of steatohepatitis and fibrosis in paediatric NAFLD.
J Pediatr Gastroenterol Nutr, 51 (2010), pp. 500-506
[25]
TX Lu, Rothenberg ME. MicroRNA.
J Aller Clin Immunol, 141 (2018), pp. 1202-1207
[26]
MA Mori, RG Ludwig, R Garcia-Martin, BB Brandão, CR. Kahn.
Extracellular miRNAs: from biomarkers to mediators of physiology and disease.
Cell Metab, 30 (2019), pp. 656-673
[27]
K Saliminejad, HR Khorram Khorshid, SH Ghaffari.
Why have microRNA biomarkers not been translated from bench to clinic?.
Future Oncol, 15 (2019), pp. 801-803
[28]
J-K Long, W Dai, Y-W Zheng, S-P. Zhao.
miR-122 promotes hepatic lipogenesis via inhibiting the LKB1/AMPK pathway by targeting Sirt1 in non-alcoholic fatty liver disease.
[29]
Y Xu, M Zalzala, J Xu, Y Li, L Yin, Y. Zhang.
A metabolic stress-inducible miR-34a-HNF4α pathway regulates lipid and lipoprotein metabolism.
Nat Commun, 6 (2015), pp. 7466
[30]
Al-Rawaf HA.
Circulating microRNAs and adipokines as markers of metabolic syndrome in adolescents with obesity.
Clin Nutr, 38 (2019), pp. 2231-2238
[31]
M Friedrich, K Pracht, M-F Mashreghi, H-M Jäck, A Radbruch, B. Seliger.
The role of the miR-148/-152 family in physiology and disease.
Eur J Immunol, 47 (2017), pp. 2026-2038
[32]
YM Cho, T-M Kim, D Hun Kim, D Hee Kim, S-W Jeong, O-J Kwon.
miR-148a is a downstream effector of X-box-binding protein 1 that silences Wnt10b during adipogenesis of 3T3-L1 cells.
Exp Mol Med, 48 (2016), pp. e226
[33]
G He, J Qiu, C Liu, B Tian, D Cai, S. Liu.
MiR-148b-3p regulates the expression of dtymk to drive hepatocellular carcinoma cell proliferation and metastasis.
Copyright © 2022. Fundación Clínica Médica Sur, A.C.
Download PDF
Article options
es en pt

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?

Você é um profissional de saúde habilitado a prescrever ou dispensar medicamentos