Analysis of Post-Translational Modifications (PTMs) in the Urinary Proteome of Patients with Metabolic-Associated Fatty Liver Disease (MAFLD)
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YanSu1
YouheGao1✉Emailgaoyouhe@bnu.edu.cn
1Gene Engineering Drug and Biotechnology Beijing Key Laboratory, College of Life SciencesBeijing Normal University100875BeijingChina
Yan Suz,2, Youhe Gao1*
(1. Gene Engineering Drug and Biotechnology Beijing Key Laboratory, College of Life Sciences, Beijing Normal University, Beijing 100875, China)
z,2oundation: National Key R&D Program of China (2023YFA1801900), Beijing Natural Science Foundation (L246002), Beijing Normal University (11100704)
*Corresponding author: Youhe Gao, male, professor, doctoral supervisor, main research direction: urinary proteomics and urinary biomarkers. E-mail: gaoyouhe@bnu.edu.cn.
Abstract
Metabolic-associated fatty liver disease (MAFLD) is a highly prevalent chronic liver disease worldwide, and its progression poses substantial risks. Based on publicly available raw urinary proteome data, this study comparatively analyzed the differential characteristics of post-translational modifications (PTMs) in urinary proteins among the healthy control group, mild hepatic steatosis group (MRI-PDFF 5%–10%), and severe hepatic steatosis group (MRI-PDFF > 10%). The results showed that a total of 281 differential modifications were identified between the mild steatosis group and the healthy control group, 445 differential modifications between the severe steatosis group and the healthy control group, and 181 differential modifications between the mild and severe steatosis groups. Among these, multiple proteins with differential modifications have been reported to function or undergo changes in MAFLD, and 6 of these proteins exhibited simultaneous alterations in both expression levels and modification status in both mild and severe steatosis groups. The findings indicate that the urinary proteome PTMs of patients with mild or severe hepatic steatosis differ from those of healthy individuals, providing a novel perspective for the diagnosis and mechanism exploration of MAFLD.
Key words:
Metabolic-associated fatty liver disease (MAFLD)
Urinary proteome
Post-translational modifications (PTMs)
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1 Introduction
Metabolic associated fatty liver disease (MAFLD) is the most prevalent chronic liver disease worldwide. Its core definition refers to intracellular lipid accumulation in hepatocytes exceeding 5% of liver weight after excluding other factors such as excessive alcohol consumption and viral hepatitis, which is directly associated with metabolic abnormalities including obesity, insulin resistance, or type 2 diabetes mellitus[1]. Since the first discovery of this disease in 1987, its global prevalence has risen sharply, currently affecting approximately 25% of the adult population worldwide[2]. From 1990 to 2021, the global burden of MAFLD in adolescents and young adults increased significantly, especially in the 15–39 age group. The estimated global prevalence increased by 75.31% compared with 1990, making it a global public health challenge[3].
The progression of MAFLD is significantly harmful. It can progress from simple hepatic steatosis to non-alcoholic steatohepatitis (NASH), and further develop into hepatic fibrosis and cirrhosis. It even increases the risk of hepatocellular carcinoma (HCC) and is closely associated with extrahepatic complications[4]. Beyond the liver, MAFLD affects multiple organ systems and regulatory mechanisms, and is linked to an increased risk of cardiovascular diseases, cardiac issues, and chronic kidney diseases[5]. The main lipid abnormality in MAFLD is elevated triglycerides. Its pathological mechanisms involve multiple links of abnormalities, including imbalanced hepatic lipid metabolism, activation of oxidative stress, and increased production of reactive oxygen species (ROS) leading to hepatocyte damage[6].
Urine is not regulated by homeostatic mechanisms and can more sensitively capture dynamic changes in the physiological and pathological states of the body. Urinary proteomics, with prominent advantages of non-invasive sampling and continuous monitoring, enriches low-molecular-weight proteins and peptides in samples, providing important technical support for systematically analyzing the physiological and pathological processes of the body[7]. In recent years, with the development of liquid chromatography-mass spectrometry (LC-MS)-based proteomics technology, high-precision identification of low-abundance modified proteins in urine has been achieved[8]. Post-translational modifications (PTMs) refer to the process of adding chemical groups through enzymatic reactions after protein synthesis. Common types include phosphorylation, acetylation, methylation, and ubiquitination. Their core function is to regulate key biological processes such as cell signal transduction and metabolic pathway activation by altering protein structure, activity, or localization[9]. As key molecular mechanisms regulating cell function, PTMs play important regulatory roles in the pathological processes of many diseases. In MAFLD, abnormal PTMs have been confirmed to be closely associated with disease progression. For example, phosphorylation of AMP-activated protein kinase (AMPK) at Thr172 in the liver activates lipid oxidation and inhibits lipogenesis[10]. In contrast, phosphorylated NF-κB drives the production of inflammatory cytokines, exacerbating steatosis and fibrosis[11]. Acetylation can enhance the DNA-binding affinity of sterol regulatory element-binding protein 1c (SREBP1c) to lipid biosynthesis genes, thereby leading to triglyceride accumulation[12]. However, systematic studies on PTMs in the urinary proteome of MAFLD patients are still relatively scarce.
Currently, the screening and severity assessment of MAFLD mainly rely on serological indicators and imaging methods. Among them, magnetic resonance imaging proton density fat fraction (MRI-PDFF), as an emerging quantitative imaging technique, can accurately and precisely assess hepatic triglyceride content and the degree of steatosis, and has been adopted as an endpoint indicator in multiple early clinical trials and observational studies[13]. Clinically, MRI-PDFF between 5% and 10% is usually defined as mild hepatic steatosis, while greater than 10% is defined as severe steatosis. The latter is also often used as one of the inclusion criteria for interventional clinical trials[14].
Therefore, this study compared the differences in urinary proteome PTMs among MAFLD patients with mild hepatic steatosis, severe steatosis (classified by MRI-PDFF) and healthy individuals to explore protein modification changes in different stages of MAFLD, aiming to provide new perspectives for the research on MAFLD diagnostic methods and related mechanisms.
2 Materials and Methods
2.1 Data Source and Sample Information
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The raw urinary proteome data of MAFLD groups and the healthy group in this study were derived from a cross-sectional study conducted at West China Hospital, Sichuan University, and deposited in the ProteomeXchange Consortium database (accession number: PXD026333). The original study recruited a total of 57 participants, and this study mainly used 27 urine samples from its discovery set for in-depth analysis. All participants were divided into three groups based on MRI-PDFF results: healthy control group (n = 7), mild hepatic steatosis group (MRI-PDFF 5%–10%) (n = 8), and severe hepatic steatosis group (MRI-PDFF > 10%) (n = 12). A
The diagnosis of MAFLD strictly followed international guidelines, and all participants were excluded from other liver diseases, renal insufficiency, cancer, and other comorbidities that might interfere with the study results.2.2 Sample Preparation and Mass Spectrometry Acquisition of Raw Data
The overview of sample processing and mass spectrometry acquisition procedures for the data used in this study is as follows:
Urine sample pretreatment: Midstream morning urine was centrifuged to remove debris, then concentrated, reduced, and alkylated using 10 kDa ultrafiltration tubes, followed by double enzymatic hydrolysis with trypsin and Lys-C.
Liquid chromatography-mass spectrometry (LC-MS/MS) analysis: The enzymatically hydrolyzed peptides were separated using an EASY-nLC 1200 liquid chromatography system and subjected to data-independent acquisition (DIA) on an Orbitrap Exploris 480 mass spectrometer equipped with a FAIMS interface. The raw mass spectrometry data (raw files) had passed quality control by the original research team.
2.3 Open-pFind Unrestricted Modification Search
pFind Studio software (version 3.2.1, Institute of Computing Technology, Chinese Academy of Sciences) was used for unrestricted modification search of raw mass spectrometry data (raw files) from each sample with default parameters. The database was the Rattus norvegicus protein database downloaded from UniProt (https://www.uniprot.org) with a version date of September 2024. The instrument type was set to HCD-FTMS, the enzyme was trypsin, the enzymatic cleavage specificity was set to complete, and the maximum number of missed cleavages was set to 2. The mass error tolerance for both precursor ions and fragment ions was set to ± 20 ppm, and the search mode was open search. The false discovery rate (FDR) filtering threshold at the peptide level was set to 1%.
2.4 Bioinformatics Analysis of Post-Translational Modifications
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After completing the unrestricted modification search, the modification identification results (PROTEIN files) of each sample were obtained. Subsequently, the Python script pFind_protein_contrast_script was retrieved from the GitHub platform (https://github.com/daheitu/scripts_for_pFind3_protocol.io) to integrate the modification identification information from different samples. On this basis, inter-group comparisons were performed between the experimental groups and the control group to screen for differentially modified proteins. The screening criteria were: fold change (FC) ≥ 1.5 or ≤ 0.67, and P-value < 0.05 by heteroscedastic independent t-test. The UniProt database was used for annotation and functional query of proteins with differential modifications, and relevant literature was retrieved through PubMed (https://pubmed.ncbi.nlm.nih.gov) to further analyze the potential functions of differential modifications.3 Results
3.1
Comparative Analysis of Post-Translational Modifications in Urinary Proteome Between the Mild Hepatic Steatosis Group and the Healthy Control Group
Post-translational modifications (PTMs) in the urinary proteome were compared between the mild hepatic steatosis group and the healthy control group. Results showed that a total of 281 differential modifications were identified, involving 161 differentially modified proteins. Detailed information is listed
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in Supplementary Table 1.A total of 82 proteins harbored PTMs with fold change (FC) ≥ 10 or ≤ 0.01. A literature search was performed in the PubMed database, revealing that 32% of these proteins or other members of their families have been reported to be associated with MAFLD, hepatic steatosis, or lipid metabolism. Due to space limitations, only a few examples are presented below. The modified proteins and relevant literature are detailed in Table 1:
P19440: Glutathione hydrolase 1 proenzyme (GGT1) (FC = 0, P = 3.82E-02). Studies have shown that GGT1 is one of the proteins significantly associated with the risk of metabolic dysfunction-associated steatotic liver disease (MASLD). Specifically, elevated levels of GGT1 are linked to an increased risk of MASLD, and may serve as an early predictive biomarker for MASLD onset, indicating its potential crucial role in the development of fatty liver[16].
P19652: Alpha-1-acid glycoprotein 2 (FC = 0, P = 4.65E-02). As an acute-phase reactant, this protein plays an important role in inflammation and metabolic disorders. Studies have found that its level is significantly correlated with the degree of hepatic steatosis[18].
Q08380: Galectin-3-binding protein (FC = 0, P = 4.88E-02). Its expression is increased in the serum and visceral adipose tissue (VAT) of high-fat diet-fed mice, and is highly expressed in VAT macrophages. Its level is significantly associated with the incidence of metabolic syndrome, and increased expression in adipose tissue may be related to lipid metabolism disorders[21].
Q03154: Aminoacylase-1 (FC = 23.63, P = 3.54E-02). Its expression is significantly increased in NAFLD patients. Studies have indicated that increased expression of this protein in hepatic lipid droplets may be involved in metabolic regulation and the development of fatty liver[27].
P07288: Prostate-specific antigen (PSA) (FC=∞, indicating that no modified form of this protein was detected in the healthy control group, but it was detected in the mild hepatic steatosis group; P = 4.79E-02). Studies have found that its expression is decreased in the liver of NAFLD patients. Loss of PSA exacerbates diet-induced triglyceride accumulation by enhancing lipogenesis and inhibiting fatty acid β-oxidation. Additionally, PSA can activate the NRF2 signaling pathway by stabilizing NRF2 protein expression, thereby reducing oxidative stress and lipid overload[31].
P25311: Zinc-alpha-2-glycoprotein (FC=∞, P = 4.92E-02). It plays an important role in lipid metabolism. It alleviates NAFLD by negatively regulating tumor necrosis factor-α (TNF-α), and may regulate body weight by inhibiting lipogenic enzymes to reduce fat accumulation[36].
Uniprot ID | Protein names | Fold change | P value | Related to MAFLD |
|---|---|---|---|---|
P07602 | Prosaposin | 0.00 | 4.65E-02 | [15] |
P19440 | Glutathione hydrolase 1 proenzyme | 0.00 | 3.82E-02 | [16] |
P19652 | Alpha-1-acid glycoprotein 2 | 0.00 | 4.65E-02 | [17][18] |
P35052 | Glypican-1 | 0.00 | 3.00E-02 | [19] |
P98095 | Fibulin-2 | 0.00 | 4.72E-02 | [20] |
Q08380 | Galectin-3-binding protein | 0.00 | 4.88E-02 | [21] |
P07911 | Uromodulin | 0.02 | 3.35E-02 | [22] |
P07477 | Serine protease 1 | 0.03 | 1.64E-02 | [23] |
P05090 | Apolipoprotein D | 13.13 | 2.04E-02 | [24] |
P00450 | Ceruloplasmin | 14.88 | 4.07E-02 | [25] |
P08697 | Alpha-2-antiplasmin | 19.25 | 4.45E-02 | [26] |
Q03154 | Aminoacylase-1 | 23.63 | 3.54E-02 | [27] |
P02768 | Albumin | ∞ | 4.92E-02 | [28][29] |
P04004 | Vitronectin | ∞ | 4.04E-03 | [30] |
P07288 | Prostate-specific antigen | ∞ | 4.79E-02 | [31] |
P08571 | Monocyte differentiation antigen CD14 | ∞ | 4.92E-02 | [32] |
P08603 | Complement factor H | ∞ | 5.03E-03 | [33] |
P12109 | Collagen alpha-1 | ∞ | 4.79E-02 | [34] |
P17900 | Ganglioside GM2 activator | ∞ | 4.67E-02 | [35] |
P25311 | Zinc-alpha-2-glycoprotein | ∞ | 4.92E-02 | [36] |
P41222 | Prostaglandin-H2 D-isomerase | ∞ | 4.12E-02 | [37] |
P53634 | Dipeptidyl peptidase 1 | ∞ | 3.79E-02 | [38] |
Q14344 | Guanine nucleotide-binding protein subunit alpha-13 | ∞ | 2.77E-02 | [39] |
Q15113 | Procollagen C-endopeptidase enhancer 1 | ∞ | 4.99E-02 | [40] |
Q8NBJ4 | Golgi membrane protein 1 | ∞ | 4.92E-02 | [41] |
Q9H2M3 | S-methylmethionine–homocysteine S-methyltransferase BHMT2 | ∞ | 4.79E-02 | [42] |
| Note: ∞ indicates that no modified form of this protein was detected in the healthy control group, but it was detected in the mild hepatic steatosis group. | ||||
3.2
Comparative Analysis of Post-Translational Modifications in Urinary Proteome Between the Severe Hepatic Steatosis Group and the Healthy Control Group
Post-translational modifications (PTMs) in the urinary proteome were compared between the severe hepatic steatosis group and the healthy control group. Results showed that a total of 445 differential modifications were identified, involving 183 differentially modified proteins. Detailed information is listed in Supplementary Table 2.
A total of 112 proteins harbored PTMs with fold change (FC) ≥ 10 or ≤ 0.01. A literature search was performed in the PubMed database, revealing that 36% of these proteins or other members of their families have been reported to be associated with MAFLD, hepatic steatosis, or lipid metabolism.
P07195: L-lactate dehydrogenase B chain (LDHB) (FC = 0.08, P = 2.45E-02). Studies have shown that acetylation of this protein is closely associated with NAFLD progression. P300/CBP-associated factor-mediated acetylation of LDHB at K82 significantly reduces LDHB activity, impairs hepatic lactate clearance, and leads to lactate accumulation. This exacerbates lipid deposition and inflammatory responses by activating histone hyperacetylation[44].
P04004: Vitronectin (FC = 19.25, P = 4.02E-03). In a non-alcoholic steatohepatitis (NASH)-induced mouse model, its deficiency significantly alleviates hepatic fibrosis[30].
P17900: Ganglioside GM2 activator (FC=∞, P = 1.15E-02). It can bind and transfer various lipid molecules, including gangliosides GM2, GM1, and GM3, as well as at least one phosphatidylglycerol. This protein not only acts as a cofactor for β-hexosaminidase A in lysosomes to participate in GM2 hydrolysis but also functions as a lipid transporter both intracellularly and extracellularly[35].
Q99519: Sialidase-1 (FC=∞, P = 2.51E-02). Its expression and activity are significantly increased in obese patients or obese mice, and inhibition of its activity can significantly reduce lipid accumulation in the liver of high-fat diet-fed or obese mice[51].
P12821: Angiotensin-converting enzyme (ACE) (FC=∞, P = 2.65E-02). Studies have found that ACE2 gene knockout mouse models exhibit an obvious fatty liver phenotype with significantly increased hepatic fat accumulation. The ACE2/Angiotensin-(1–7)/Mas axis can improve hepatic steatosis by activating the Akt signaling pathway[54].
P02751: Fibronectin (FC=∞, P = 3.88E-02). Circulating plasma fibronectin levels are associated with tissue insulin sensitivity and promote obesity-related metabolic disorders. Studies have indicated that increased expression of fibronectin in adipose tissue and liver is related to insulin resistance and the development of fatty liver[59].
P02788: Lactotransferrin (FC=∞, P = 4.37E-02). It improves hepatic lipid metabolism by reducing fatty acid synthesis and increasing lipolysis, and can significantly ameliorate NAFLD induced by a high-fat, high-cholesterol diet in mice[64].
Q8IWU5: Extracellular sulfatase Sulf-2 (FC=∞, P = 4.56E-02). In a NAFLD mouse model induced by a high-fat, high-cholesterol, and high-fructose diet, Sulf2 gene knockout significantly alleviated diet-induced weight gain, dyslipidemia, steatohepatitis, and hepatic fibrosis. Studies have also found that the expression level of Sulf2 is significantly increased in wild-type mice, while Sulf2 gene knockout mice show lower weight gain and dyslipidemia. Sulf2 plays an important role in the development of NAFLD, and its gene knockout can significantly mitigate the progression of steatohepatitis and hepatic fibrosis[66].
Q07654: Trefoil factor 3 (FC=∞, P = 4.69E-02). It can alleviate high-fat diet-induced hepatic steatosis in mice by increasing peroxisome proliferator-activated receptor-α (PPAR-α)-mediated fatty acid oxidation[68].
Due to space limitations, only a few examples are presented below. The modified proteins and relevant literature are detailed in Table 2.
Uniprot ID | Protein names | Fold change | P value | Related to MAFLD |
|---|---|---|---|---|
P35052 | Glypican-1 | 0 | 3.00E-02 | [19] |
P98095 | Fibulin-2 | 0 | 4.72E-02 | [20] |
P02452 | Collagen alpha-1 | 0.04 | 4.93E-03 | [43] |
P07195 | L-lactate dehydrogenase B chain | 0.08 | 2.45E-02 | [44] |
P28799 | Progranulin | 11.08 | 2.18E-03 | [45] |
P51884 | Lumican | 17.50 | 1.94E-02 | [46] |
P04004 | Vitronectin | 19.25 | 4.02E-03 | [30] |
Q03591 | Complement factor H-related protein 1 | ∞ | 1.75E-03 | [47] |
P08603 | Complement factor H | ∞ | 1.81E-03 | [33] |
P19652 | Alpha-1-acid glycoprotein 2 | ∞ | 5.30E-03 | [17][18] |
P17900 | Ganglioside GM2 activator | ∞ | 1.15E-02 | [35] |
P00747 | Plasminogen | ∞ | 1.21E-02 | [48] |
P01033 | Metalloproteinase inhibitor 1 | ∞ | 1.31E-02 | [49] |
P01034 | Cystatin-C | ∞ | 1.37E-02 | [50] |
P07288 | Prostate-specific antigen | ∞ | 2.33E-02 | [31] |
Q99519 | Sialidase-1 | ∞ | 2.51E-02 | [51] |
P25311 | Zinc-alpha-2-glycoprotein | ∞ | 2.61E-02 | [36] |
P55290 | Cadherin-13 | ∞ | 2.61E-02 | [52] |
P01019 | Angiotensinogen | ∞ | 2.61E-02 | [53] |
P00450 | Ceruloplasmin | ∞ | 2.61E-02 | [25] |
P12821 | Angiotensin-converting enzyme | ∞ | 2.65E-02 | [54] |
Q96FE7 | Phosphoinositide-3-kinase-interacting protein 1 | ∞ | 2.70E-02 | [55] |
P01024 | Complement C3 | ∞ | 2.71E-02 | [56] |
O94919 | Endonuclease domain-containing 1 protein | ∞ | 3.24E-02 | [57] |
P41222 | Prostaglandin-H2 D-isomerase | ∞ | 3.53E-02 | [37] |
P10909 | Clusterin | ∞ | 3.73E-02 | [58] |
P08571 | Monocyte differentiation antigen CD14 | ∞ | 3.88E-02 | [32] |
P02751 | Fibronectin | ∞ | 3.88E-02 | [59] |
P39060 | Collagen alpha-1 | ∞ | 3.88E-02 | [60] |
P09525 | Annexin A4 | ∞ | 4.25E-02 | [61] |
P02765 | Alpha-2-HS-glycoprotein | ∞ | 4.33E-02 | [62] |
P02787 | Serotransferrin | ∞ | 4.37E-02 | [63] |
P02788 | Lactotransferrin | ∞ | 4.37E-02 | [64] |
Q16270 | Insulin-like growth factor-binding protein 7 | ∞ | 4.48E-02 | [65] |
P05090 | Apolipoprotein D | ∞ | 4.51E-02 | [24] |
Q8IWU5 | Extracellular sulfatase Sulf-2 | ∞ | 4.56E-02 | [66] |
P98164 | Low-density lipoprotein receptor-related protein 2 | ∞ | 4.63E-02 | [67] |
P00450 | Ceruloplasmin | ∞ | 4.63E-02 | [25] |
Q07654 | Trefoil factor 3 | ∞ | 4.69E-02 | [68] |
P02768 | Albumin | ∞ | 4.93E-02 | [28][29] |
| Note: ∞ indicates that no modified form of this protein was detected in the mild hepatic steatosis group, but it was detected in the severe hepatic steatosis group. | ||||
3.3
Comparative Analysis of Post-Translational Modifications in Urinary Proteome Between the Mild Hepatic Steatosis Group and the Severe Hepatic Steatosis Group
Post-translational modifications (PTMs) in the urinary proteome were compared between the mild hepatic steatosis group and the severe hepatic steatosis group. Results showed that a total of 181 differential modifications were identified, involving 112 differentially modified proteins. Detailed information is listed in Supplementary Table 3.
A total of 54 proteins harbored PTMs with fold change (FC) ≥ 10 or ≤ 0.01. A literature search was performed in the PubMed database, revealing that 33% of these proteins or other members of their families have been reported to be associated with MAFLD, hepatic steatosis, or lipid metabolism. Due to space limitations, only a few examples are presented below. The modified proteins and relevant literature are detailed in Table 3:
P04066: Tissue alpha-L-fucosidase (FC = 0, P = 3.83E-02). Its level is positively correlated with metabolic syndrome and its five components—central obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol, hypertension, and elevated fasting blood glucose. Elevated alpha-L-fucosidase level is an independent risk factor for NAFLD and may serve as a potential biomarker for NAFLD[70].
P19835: Bile salt-activated lipase (FC = 0, P = 4.92E-02). It plays a dominant role in neonatal fat digestion and is also present in breast milk, facilitating fat absorption in infants[72].
Q9HD89: Resistin (FC = 0, P = 4.99E-02). It is a cytokine secreted by adipocytes and macrophages. Its expression in the liver increases with the progression of liver injury, and its serum level in NAFLD patients is significantly higher than that in the control group[73].
P10451: Osteopontin (OPN) (FC = 14, P = 3.61E-02). Macrophage-derived OPN exerts a protective effect in NASH by regulating inflammatory responses and lipid metabolism to alleviate NASH progression[74].
Uniprot ID | Protein names | Fold change | P value | Related to MAFLD |
|---|---|---|---|---|
P35900 | Keratin, type I cytoskeletal 20 | 0 | 1.12E-02 | [69] |
P04066 | Tissue alpha-L-fucosidase | 0 | 3.83E-02 | [70] |
P02768 | Albumin | 0 | 4.12E-02 | [28][29] |
Q06830 | Peroxiredoxin-1 | 0 | 4.79E-02 | [71] |
P19835 | Bile salt-activated lipase | 0 | 4.92E-02 | [72] |
P07195 | L-lactate dehydrogenase B chain | 0 | 4.92E-02 | [44] |
Q9HD89 | Resistin | 0 | 4.99E-02 | [73] |
P07477 | Serine protease 1 | 12.00 | 4.37E-02 | [23] |
P10451 | Osteopontin | 14.00 | 3.61E-02 | [74] |
P07911 | Uromodulin | 32.67 | 5.56E-03 | [22] |
P04004 | Vitronectin | ∞ | 2.17E-04 | [30] |
O75144 | ICOS ligand | ∞ | 2.51E-02 | [75] |
P06727 | Apolipoprotein A-IV | ∞ | 3.41E-02 | [76] |
Q96FE7 | Phosphoinositide-3-kinase-interacting protein 1 | ∞ | 3.53E-02 | [55] |
P02751 | Fibronectin | ∞ | 3.88E-02 | [59] |
P02787 | Serotransferrin | ∞ | 4.04E-02 | [63] |
P07602 | Prosaposin | ∞ | 4.25E-02 | [15] |
Q8IWU5 | Extracellular sulfatase Sulf-2 | ∞ | 4.56E-02 | [66] |
P00450 | Ceruloplasmin | ∞ | 4.63E-02 | [25] |
| Note: ∞ indicates that no modified form of this protein was detected in the mild hepatic steatosis group, but it was detected in the severe hepatic steatosis group. | ||||
3.4
Analysis of Post-Translational Modifications Among the Healthy Control Group, Mild Hepatic Steatosis Group, and Severe Hepatic Steatosis Group
Analysis of urinary proteome PTMs across the aforementioned three groups (healthy control vs. mild hepatic steatosis, healthy control vs. severe hepatic steatosis, mild hepatic steatosis vs. severe hepatic steatosis) revealed that key proteins closely associated with the pathological progression of MAFLD were detected with PTMs in all experimental groups. These proteins include insulin-like growth factor binding protein complex acid labile subunit (ALS), galectin-3 binding protein (Gal-3BP), patatin-like phospholipase domain-containing protein 3 (PNPLA3), AMP-activated protein kinase (AMPK), sterol regulatory element-binding protein 1c (SREBP1c), carbohydrate response element-binding protein (ChREBP), and acetyl-CoA carboxylase (ACC). However, the types of modifications differed significantly from the functionally relevant PTMs reported in previous studies[77]. Specifically, previous studies have confirmed that modifications such as phosphorylation of AMPK at Thr172, acetylation and phosphorylation of SREBP1c, acetylation of ChREBP at Lys672, and phosphorylation of ACC at Ser79 can directly regulate hepatic lipid metabolism, inflammatory activation, and fibrosis progression[78][79][80][81]. In contrast, the unrestricted modification search in this study showed that the modification forms of the aforementioned proteins were mainly concentrated in basic modification types such as oxidation, dehydration, deamidation, and pyroglutamination. No functional PTM signals that have been reported to be directly related to the pathological regulation of MAFLD were detected.
3.5 Comparison of Differentially Expressed Proteins and Post-Translational Modifications
A cross-study correlation analysis was performed between the differentially expressed proteins (DEPs) screened from urinary proteome data in the original literature (screening criterion: p < 0.05) among healthy controls, patients with mild hepatic steatosis, and patients with severe hepatic steatosis, and the differentially modified proteins obtained by unrestricted modification search in this study (screening criterion: fold change (FC) ≥ 1.5 or ≤ 0.67, P < 0.01).
The intersection and union of the two datasets were visualized by drawing a Venn diagram, as shown in Fig. 1. It was found that 6 proteins showed significant changes in both differential expression and differential modification analyses: Thyroxine-binding globulin, Immunoglobulin heavy constant gamma 2, Peptidase inhibitor 16, Ceruloplasmin, Alpha-1B-glycoprotein, and Alpha-1-acid glycoprotein 1. This suggests that these proteins may regulate protein function through post-translational modifications during the pathological progression of MAFLD, serving as key molecular nodes linking abnormal gene expression and phenotypic changes. Among them, Thyroxine-binding globulin, Ceruloplasmin, and Alpha-1-acid glycoprotein 1 have been reported in existing literature to be associated with MAFLD and hepatic steatosis[25][82][83].
Fig. 1
Venn diagram of differentially expressed proteins from the original literature and differentially modified proteins from this study
(Note: DEPs refers to differentially expressed proteins from the original literature; HC-M refers to differentially modified proteins between the mild hepatic steatosis group and the healthy control group; HC-S refers to differentially modified proteins between the severe hepatic steatosis group and the healthy control group; M-S refers to differentially modified proteins between the severe hepatic steatosis group and the mild hepatic steatosis group)
4 Discussion
Based on public urinary proteomics data, this study systematically explored the differential PTM characteristics of the urinary proteome among healthy controls, MAFLD patients with mild hepatic steatosis, and those with severe hepatic steatosis through unrestricted modification search and bioinformatics analysis. It provides a new molecular perspective for the analysis of the pathological mechanism and diagnosis of MAFLD. Changes in protein concentration and post-translational modifications are complementary information, which can depict the effects of subtle and short-term interventions from two different dimensions. The original literature focused on differences in protein expression levels, while this study focuses on changes in protein modification status. The combined analysis of the two provides more clues for understanding the molecular network of MAFLD.
From the perspective of modification profile characteristics, this study found significant heterogeneity in urinary protein modifications across different pathological stages of MAFLD: 281 differential modifications (involving 161 proteins) were identified between the mild hepatic steatosis group and the healthy control group, 445 differential modifications (involving 183 proteins) between the severe hepatic steatosis group and the healthy control group, and 181 differential modifications (involving 112 proteins) between the mild and severe steatosis groups. This result suggests that changes in urinary protein PTMs are correlated with the severity of MAFLD to a certain extent. Moreover, a large number of differentially modified proteins have been confirmed in existing studies to be directly associated with MAFLD, hepatic steatosis, or lipid metabolism, further verifying the reliability of the results of this study.
Notably, this study identified various types of post-translational modifications in key regulatory proteins of MAFLD (such as AMPK, SREBP1c, etc.), but did not detect the functionally relevant modification sites reported in previous studies. This discrepancy may stem from two points: first, the particularity of sample type—most proteins in urine are metabolic products or tissue secretions of the body, and their modification characteristics may reflect the protein degradation status or transport process; second, the functional annotation of most identified post-translational modifications in MAFLD is still incomplete in the field, which objectively restricts the depth of analysis of specific modification events in this study. The above results indicate that MAFLD-related core proteins exhibit specific expression of modification characteristics in urine samples. The enrichment of their basic modification types may reflect the body's regulation of hepatic metabolic disorders, providing new clues for further exploring non-invasive biomarkers and modification regulatory mechanisms of MAFLD. Future studies can expand the sample size and include multi-center, longitudinal cohort data to improve the reliability and clinical transformation value of the results.
5 Conclusion
In summary, from the perspective of PTMs, this study systematically analyzed the differential modification characteristics of the urinary proteome among healthy individuals, MAFLD patients with mild hepatic steatosis, and those with severe hepatic steatosis. A large number of MAFLD-related proteins were identified to have changes in post-translational modifications, providing new clues for the diagnosis and mechanism exploration of the disease.
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