Preamble

Analysis of Urinary Proteome Modifications in Patients with Different Glycated Hemoglobin Levels

Chen Yuzhen, Gao Youhe
Beijing Key Laboratory of Gene Engineering Drugs and Biotechnology, School of Life Sciences, Beijing Normal University

Abstract

Diabetes mellitus is a chronic metabolic disease characterized by hyperglycemia, which can lead to various complications over time. Glycated hemoglobin (HbA1c) is a critical clinical indicator for monitoring long-term glycemic control. While the urinary proteome has emerged as a significant source for biomarker discovery, the specific changes in protein post-translational modifications (PTMs) in urine across different HbA1c levels remain insufficiently explored. This study utilizes a urinary proteomics approach to analyze the modification profiles of patients with varying HbA1c levels. By identifying differentially modified proteins and their associated biological pathways, we aim to provide insights into the molecular mechanisms underlying diabetic progression and potential early markers for complications.

Introduction

Diabetes mellitus is a global health challenge, with its prevalence increasing steadily. Persistent hyperglycemia leads to the non-enzymatic glycation of proteins, altering their structure and function, which contributes to the pathogenesis of diabetic microvascular and macrovascular complications. HbA1c reflects the average blood glucose levels over the preceding 2–3 months and is the gold standard for assessing glycemic control.

Urine is an ideal clinical sample for proteomics because it can be collected non-invasively in large quantities and reflects systemic metabolic changes without the influence of homeostatic mechanisms that limit blood-based biomarkers. Beyond protein abundance, post-translational modifications (PTMs) play a vital role in regulating protein activity, localization, and degradation. In the context of diabetes, modifications such as glycation, phosphorylation, and acetylation are of particular interest. This study aims to characterize the urinary proteome modification landscape in patients categorized by different HbA1c levels to identify patterns associated with glucose metabolism and early renal involvement.

Materials and Methods

Sample Collection and Grouping

Urine samples were collected from patients and categorized into groups based on their clinical HbA1c levels: a well-controlled group, a moderately controlled group, and a poorly controlled group. All samples were processed according to standardized protocols to minimize pre-analytical variability.

Protein Extraction and Digestion

Urinary proteins were extracted using the acetone precipitation method. After protein quantification, disulfide bonds were reduced with dithiothreitol (DTT) and alkylated with iodoacetamide (IAM). The proteins were then digested

摘要

Diabetes has become a major global public health issue, necessitating early diagnosis and timely intervention. Glycated hemoglobin ($HbA1c$) serves as a critical biomarker for blood glucose management, as its levels are continuously correlated with the risk of developing diabetes. In this study, we performed a comparative analysis of the urinary proteome modifications in patients with varying $HbA1c$ levels ($[5.7, 6.0]\%$ and $[6.1, 6.4]\%$) against healthy controls. We identified several differentially modified peptides; notably, in the two experimental groups, $48.8\%$ and $86.5\%$ of these differentially modified peptides exhibited a binary "presence-to-absence" or "absence-to-presence" change, respectively. Random permutation tests further demonstrated that $90.6\%$ to $94.1\%$ of these differentially modified peptides were not generated by chance.

Urinary proteome modifications provide a comprehensive and systematic reflection of the changes associated with elevated glycated hemoglobin levels. Furthermore, distinct $HbA1c$ levels correspond to unique combinations of modifications, suggesting that the urinary proteome has significant potential for monitoring $HbA1c$ status. These findings offer a new perspective for research into the early diagnosis of diabetes.

关键词

Analysis of Urinary Proteome Modifications in Patients with Different Glycated Hemoglobin A1c Levels

Yuzhen Youhe Gene Engineering Drug and Biotechnology Beijing Key Laboratory, College of Life Sciences, Beijing Normal University, Beijing 100875, China

Abstract

Glycated hemoglobin A1c (HbA1c) is a critical clinical indicator for monitoring long-term glycemic control in patients with diabetes. While the relationship between blood glucose levels and systemic metabolic changes is well-documented, the specific impact of varying HbA1c levels on the urinary proteome—particularly regarding post-translational modifications—remains an area of active investigation. This study utilizes advanced mass spectrometry-based proteomics to analyze the urinary protein profiles of individuals categorized by different HbA1c levels. By examining the correlation between HbA1c concentrations and changes in the urinary proteome, we aim to identify potential non-invasive biomarkers and gain insights into the early physiological shifts associated with glycemic instability. Our findings suggest that specific urinary protein modifications may serve as sensitive indicators of metabolic health, potentially preceding the clinical manifestation of diabetic complications.

Introduction

Diabetes mellitus is a global health challenge characterized by chronic hyperglycemia and a high risk of multi-organ complications. Glycated hemoglobin (HbA1c) reflects the average blood glucose levels over the preceding 2 to 3 months and is widely regarded as the gold standard for assessing glycemic control \cite{1}. Persistent elevation of HbA1c is strongly associated with the development of microvascular and macrovascular complications, including diabetic nephropathy, retinopathy, and cardiovascular disease.

The urine proteome is a rich source of biological information, reflecting not only the physiological state of the kidney and urogenital tract but also systemic metabolic alterations \cite{2}. Unlike the plasma proteome, the urinary proteome is less complex and can be collected non-invasively, making it an ideal medium for biomarker discovery. Recent advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enabled the high-throughput identification and quantification of thousands of proteins and their various modifications.

In this study, we investigate the urinary proteome modifications in patients stratified by their HbA1c levels. We focus on identifying differentially expressed proteins and specific modification patterns that correlate with increasing HbA1c. Understanding these changes is essential for identifying early-stage biomarkers of diabetic progression and for elucidating the molecular mechanisms by which chronic hyperglycemia affects systemic protein stability and function.

[FIGURE:1

Abstract

Diabetes, a major global public health concern requires early diagnosis and timely intervention. lycated hemoglobin A1c (HbA1c) serves as a biomarker glycemic management with its levels showing continuous relationship with the risk of developing diabetes his study urinary proteome modifications compared between each of the two patient groups with different HbA1c levels ([6.4 0.7]% and [8.6 1.6]% ) and healthy controls A total of 1 954 and 545 differentially modified peptides were identified in the two groups, respectively Within each group, differentially modified peptides exhibiting changes from presence to absence or vice versa accounted for 48.8% and 86.5%, respectively. Additionally, esults from the randomized grouping test indicated that at least 90.6% and 94.1% of these differentially modified peptides in each group were not randomly generated.

In conclusion, urinary proteome modifications comprehensively and systematically reflect changes associated with elevated HbA1c levels, with distinct modification profiles corresponding to different HbA1c levels . These findings suggest that urinary proteome modification the potential to reflect HbA1c levels and offer a new perspective research early diagnosis of diabetes.

Keywords

urine proteomics modification lycated hemoglobin A1c diabetes mellitus biomarker

1 前言

Diabetes has become a major global public health issue. The prevalence of diabetes among adults is currently 10.5% (approximately 537 million people), and it is projected to rise to 12.2% by 2045. Compared to non-diabetic populations, patients with diabetes face a significantly higher risk of all-cause mortality—particularly from cardiovascular disease, cancer, and chronic obstructive pulmonary disease—which severely impacts their quality of life. Consequently, early diagnosis and timely intervention for diabetes are of critical importance.

Biomarkers are monitorable changes associated with physiological or pathophysiological processes in the body, playing a vital role in disease diagnosis, treatment, and prognosis. Glycated hemoglobin (HbA1c) reflects average blood glucose levels over the preceding 2–3 months and is widely utilized as a clinical biomarker for diabetes. While HbA1c serves as a diagnostic standard, the risk of developing diabetes exists on a continuous distribution; as HbA1c levels approach the diagnostic threshold, an individual's risk progressively increases. Specifically, individuals with HbA1c levels between 5.7% and 6.4% are considered to be at high risk for progression to diabetes. Urine, as a filtrate of blood, is not subject to the strict homeostatic regulatory mechanisms of the internal environment. This allows it to accommodate and accumulate more significant changes without causing harm to the body, potentially reflecting systemic changes across all organs and systems earlier and more sensitively than blood. Given its capacity to provide a comprehensive and sensitive reflection of the body's physiological state, a key question arises: can the differences between patients with varying HbA1c levels be characterized through modifications in the urinary proteome? This study explores the urinary proteome modifications in patients across different HbA1c levels, potentially opening a new window for research into the early diagnosis of diabetes.

2.1 尿液样本信息

Materials and Methods

Mass Spectrometry Parameters and Data Acquisition

The mass spectrometry data used in this experiment were obtained from previously published studies. Data acquisition was performed using Data Dependent Acquisition (DDA) mode. The specific mass spectrometry detection parameters were configured to ensure high-sensitivity proteomic profiling, consistent with established protocols for clinical sample analysis.

Patient Cohort and Clinical Characteristics

The study involved a comparative analysis between patient samples and a healthy control group. Participants were categorized based on their glycated hemoglobin (HbA1c) levels to evaluate metabolic differences. The experimental design utilized two distinct patient groups: one group consisted of individuals with elevated HbA1c levels, while the second group served as a clinical comparison. These patient datasets were systematically compared against the healthy control group to identify significant biomarkers and proteomic variations associated with the disease state.

Group A Group

group (n=5) [6]

Reduction and alkylation

methods

Ultra Performance Liquid Chromatograph Inc.) resolution spectrometer column phase B Healthy individual

(n=8) [7]

group (n=6) [8]

Ultimate 3000 nano pressure system (Thermo (Thermo Scientific) Scientific) Q Exactive HF X (Thermo Q Exactive (Thermo Scientific) Scientific) Scientific) column (75 µm internal BetaBasic C18, 150 Å diameter) with packing C18 (New Objective, MA) 100 Å pole size, Dikma Technologies, USA) 0.1% formic acid acetonitrile 0.1% formic acid in acetonitrile acetonitrile 0~12 min, 5~10% phase B 0 min, 0% phase B 12~50 min, 10~26% phase 100% phase A to 35% phase B 50~60 min, 26~45% phase steeper gradient 80% phase B 60~61 min, 45~80% phase 125~130 min, phase A 61~65 min, 80% phase B Healthy individual

group (n=5) [6]

DTT/IAA DTT/IAA DTT/IAA Type of protease Trypsin Trypsin Trypsin nanoflow liquid chromatography system (nLC1000, Thermo Fisher Scientific, QExactive (Thermo Fisher Scientific, Inc. Bremen, Germany) Mobile phase B 0.1% formic acid in acetonitrile 0.1 % formic acid in 90 % Gradient elution program linear gradient of 2% phase B to 35% MS1 resolution Not mentioned 60,000 70,000 MS2 resolution Not mentioned 15,000 17,500

2.2 数据库搜索与数据处理

Proteomic modification information was obtained using the pFind Studio (Institute of Computing Technology, Chinese Academy of Sciences) to perform label-free quantitative analysis of the data acquired via mass spectrometry. The target search database was derived from the Homo sapiens database (updated to [Month/Year]). During the search, trypsin digestion was selected, and the maximum precursor and fragment mass tolerances were both set to 20 ppm. To identify a comprehensive range of modifications, the Open Search mode was utilized. The filtering criteria were as follows:

The False Discovery Rate (FDR) at the spectrum, peptide, and protein levels was set to <1%. Python was used to extract sample information, specifically the Total_spec_num@pep, from the pFind Studio analysis results \cite{9, 10}. To identify differences between the two groups with varying glycated hemoglobin levels and the healthy control group, modified peptide spectral counts were compared. Differential modifications were screened using a Fold Change (FC) threshold of $\geq 1.5$ or $\leq 0.67$. Finally, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were performed using the BioCloud platform.

3.1 差异修饰

Label-Free Quantitative Proteomics Analysis

In this study, we employed label-free quantitative proteomics methods to analyze the experimental samples. Following MS/MS analysis, the raw data were processed using pFind for database searching to obtain comprehensive information regarding peptide-spectrum matches (PSMs) for each sample. This identification process provided detailed data on the protein origins of the peptides as well as the specific types of modifications they contained.

Identification and Reproducibility

The analysis focused on identifying modified peptides associated with elevated levels of glycated hemoglobin. To ensure data quality and statistical robustness, we evaluated the intra-group reproducibility within the control group. Modified peptides that met the criteria for reproducibility were selected, and a union of these peptides was generated for subsequent comparative analysis across groups.

Quantitative Results

In the comparative analysis between the experimental and control groups, a total of [NUMBER] modified peptides were identified. For the purpose of determining differential expression, a fold-change threshold was applied. Specifically, peptides showing a ratio of $\le 0.67$ (representing a significant downregulation) or those meeting the corresponding upregulation criteria were prioritized for further functional investigation.

分析

Compared to the healthy control group, several differentially modified glycated hemoglobin peptides were identified. Among these, a portion exhibited a "presence-to-absence" pattern, meaning they were identifiable in more than half of the healthy samples but were not detected in the group with mildly elevated glycated hemoglobin levels. Conversely, others showed an "absence-to-presence" pattern, being identifiable in the group with mildly elevated glycated hemoglobin while remaining undetected in the healthy control group. Specifically, 48.8% of the identified peptides exhibited these binary presence/absence changes. Detailed information for all differentially modified peptides, including peptide sequences, modification types, and their corresponding proteins, is listed in [TABLE:1].

Hierarchical clustering analysis and principal component analysis (PCA) were performed on the identified peptides [FIGURE:1]. Both methods successfully distinguished the healthy control group from the group with mildly elevated glycated hemoglobin levels. [FIGURE:1A] presents the results of the hierarchical clustering analysis, while [FIGURE:1B] illustrates the principal component analysis.

In the comparison between groups, a total of differentially modified peptides were identified with a fold change (FC) $\leq 0.67$.

分析

Compared to the healthy control group, the glycated hemoglobin analysis revealed several differentially modified peptides. Among these, some exhibited a complete disappearance (from present to absent), while others appeared de novo (from absent to present), collectively accounting for 86.5% of all differentially modified peptides. Detailed information regarding all identified differentially modified peptides is listed in [TABLE:N]. Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) were performed on the identified peptides to distinguish between the healthy control group and the group with elevated glycated hemoglobin levels [FIGURE:N]. To ensure that the identified modifications were not the result of random variation, a permutation test was conducted. The samples were shuffled and randomly reassigned into two new groups. Out of all possible combinations, differential screening was performed using the same criteria ($p < 0.05$). The results of this validation confirmed that the observed differences were statistically significant and not generated by chance.

The peptides identified in common between the two groups compared were...

分析

In the comparison between the two groups, modified peptides were identified in common, which likely reflects shared changes associated with elevated glycated hemoglobin levels. Among these, several differentially modified peptides exhibited a consistent and significant trend across both groups, transitioning either from presence to absence or vice versa [TABLE:N]. Detailed information for all commonly identified modified peptides is provided in the Appendix, including peptide sequences, modification types, and the proteins associated with these differential modifications.

UniProt ID Peptide Modification roup A) roup B) P01834 SGTASVVCLLNNFYPR 14,sulfo+amino[Y] P02768 MPCAEDYLSVVLNQLCVLHEK 1,Oxidation[M]; 16,Carbamidomethyl[C] P02790 EWFWDLATGTMK 11,Oxidation[M] Q9HCU0 HLVSTEFEWLPFGSVAAVQCQAGR 20,Carbamidomethyl[C] O60494 NLNCVWIIIAPVNK 4,Carbamidomethyl[C] P02760 VVAQGVGIPEDSIFTMADR 10,Cation_Ca[II][E] Q96NY8 LPCFYR 3,Carbamidomethyl[C] Q14982 GILSCEASAVPMAEFQWFK 5,Carbamidomethyl[C] P02768 HPYFYAPELLFFAK 0,C+12[AnyN term] P01876 VFPLSLCSTQPDGNVVIACLVQGFF 7,Carbamidomethyl[C]; PQEPLSVTWSESGQGVTAR 19,Carbamidomethyl[C] P02768 MPCAEDYLSVVLNQLCVLHEK 16,Carbamidomethyl[C] P12109 DTTPLNVLCSPGIQVVSVGIK 9,Carbamidomethyl[C] Q14624 ERRLDYQEGPPGVEISCWSVEL 17,Carbamidomethyl[C] Q14624 HRQGPVNLLSDPEQGVEVTGQYER 0,Carbamyl[AnyN term] P01876 VAAEDWK 0,Carbamyl[AnyN term] P01877

3.3 差异修饰分析

The number of modification types increases in correlation with elevated levels of glycated hemoglobin. Among these, carbamidomethylation (Carbamidomethyl) accounted for the highest proportion of identified modifications. This specific modification is artificially introduced by the alkylating agent iodoacetamide (IAA) on cysteine residues (Cys, C). It accounted for 43.7% of the total identification counts for all differential modification types in Group A, and a similarly high proportion in Group B. Given that the sample processing methods for the mildly elevated glycated hemoglobin group and the healthy control group were identical, there should theoretically be no significant difference in the occurrence of this modification if the state of the cysteine residues prior to processing was consistent.

However, the results indicate that this modification was identified as significantly different between the two groups a substantial number of times. This suggests a disparity in the state of the cysteine residues between the two sample groups prior to processing. The disulfide bonds formed by the oxidation of thiol groups between cysteine residues are essential for maintaining protein stability. Research has demonstrated that in the diabetic body, protein disulfide isomerase (PDI) exists predominantly in a reduced form, which impairs its ability to facilitate the formation of disulfide bonds in nascent proteins.

4 讨论

Glycated hemoglobin (HbA1c) is a critical biomarker for the management of diabetes, and its levels are closely associated with the risk of developing the disease and its specific distributional characteristics. This study systematically explored the urinary proteome modification profiles across different HbA1c levels by comparing patients with elevated HbA1c ($HbA1c \geq 6.5\%$) and those with pre-diabetic levels ($5.7\% \leq HbA1c < 6.5\%$) against a healthy control group. The results demonstrate that urinary proteome modifications effectively reflect elevations in HbA1c levels. Specifically, 1,489 differentially modified peptides were identified in the pre-diabetic group compared to the healthy controls, while 4,683 differentially modified peptides were identified in the elevated HbA1c group. Furthermore, the proportion of differentially modified peptides showing a binary "presence-to-absence" or "absence-to-presence" change was 48.8% and 86.5% in the respective groups. Both the total number of differentially modified peptides and the proportion of significantly altered modifications increased markedly as HbA1c levels rose. Random permutation tests further validated the reliability of these experimental results, confirming that 90.6% to 94.1% of the differentially modified peptides were not generated by chance.

The identification of specific proteome modification combinations across different HbA1c levels establishes a foundation for using urinary proteome modifications to reflect glycemic status. However, as this study is based on a retrospective data analysis, the sample size is relatively limited. Additionally, there is an age discrepancy between the healthy control group and the groups with elevated HbA1c, which may introduce confounding effects on the results. Consequently, further validation through large-scale clinical studies is required to confirm these findings.

5 结论

This study explores the differences between patients with varying glycated hemoglobin (HbA1c) levels from the perspective of urinary proteome modifications. Proteome modifications can comprehensively and systematically reflect the physiological changes associated with elevated HbA1c levels. Since different hemoglobin levels correspond to distinct combinations of modifications, the urinary proteome modification landscape serves as a critical indicator of HbA1c status. This approach opens a new window for research into the early diagnosis of diabetes.

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