Identification of Serum Biomarkers and Pathways of Systemic Lupus Erythematosus with Skin Involvement Through GC/MS-Based Metabolomics Analysis

The effect and mechanism of Qingre Huashi formula in the treatment of chronic hepatitis B with Gan-dan-shi-Re syndrome: An integrated transcriptomic and targeted metabolomic analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Qingre Huashi (QRHS) formula is an empirical prescription for the treatment of Gan-Dan-Shi-Re syndrome (GDSR) syndrome in traditional Chinese medicine (TCM). GDSR is one of the typical TCM syndromes in chronic hepatitis B (CHB). However, little is known about the mechanism of the QRHS formula in treating CHB patients with GDSR. The biological basis of GDSR also remains largely unknown.

AIM OF THE STUDY

GDSR mostly occurs in the acute and early stages of chronic liver disease. Effectively alleviating GDSR stalls disease development and benefits patients. The purpose of this study was to explore the molecular basis of GDSR in CHB and then study the mechanism of the QRHS formula treating GDSR using transcriptomics and metabolomics.

MATERIALS AND METHODS

The transcriptome and metabolome of CHB patients with GDSR syndrome were detected using RNA microarray combined with ultra-high performance liquid chromatography/mass spectrometry and information mining. The potential biomarkers were identified from differentially expressed genes and metabolites, and the metabolic pathway was analyzed. We also investigated the callback of metabolic biomarkers after treatment with the QRHS formula, an empirical prescription for the treatment of GDSR syndrome. RT-PCR analysis was carried out in an independent patient cohort of CHB for validation.

RESULTS

Four candidate genes-GPT2, HK2, DDIT3, and HIF1A-and 14 candidate metabolic biomarkers, including L-alpha-aminobutyric acid, selenomethionine, and fructose 1,6-bisphosphate, were identified and validated. All four transcripts of GPT2, HK2, DDIT3, and HIF1A were significantly differentially expressed between the GDSR and non-GDSR groups through independent microarray data and RT-PCR. After treatment with the QRHS formula, the clinical indexes and TCM syndrome were significantly improved, and the 14 disturbed biomarkers were obviously corrected. Three metabolic pathways were confirmed to be perturbed in CHB GDSR patients: alanine, aspartate, and glutamate metabolism, arginine biosynthesis, and aminoacyl-tRNA biosynthesis.

CONCLUSION

Using integrated transcriptomic and targeted metabolomic methods, we identified the potential biomarkers and dysregulated metabolic pathways in CHB patients with GDSR syndrome, which was alleviated by the QRHS formula treatment. These results may provide the mechanism of metabolic dysregulation in GDSR syndrome as well as that underlying the curative effect of the QRHS formula.

Metabolic profiling of urinary exosomes for systemic lupus erythematosus discrimination based on HPL-SEC/MALDI-TOF MS

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease which leads to the formation of immune complex deposits in multiple organs and has heterogeneous clinical manifestations. Currently, exosomes for liquid biopsy have been applied in diagnosis and monitoring of diseases, whereas SLE discrimination based on exosomes at the metabolic level is rarely reported. Herein, we constructed a protocol for metabolomic study of urinary exosomes from SLE patients and healthy controls (HCs) with high efficiency and throughput. Exosomes were first obtained by high-performance liquid size-exclusion chromatography (HPL-SEC), and then metabolic fingerprints of urinary exosomes were extracted by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with high throughput and high efficency. With the statistical analysis by orthogonal partial least-squares discriminant analysis (OPLS-DA) model, SLE patients were efficiently distinguished from HCs, the area under the curve (AUC) of the receiver characteristic curve (ROC) was 1.00, and the accuracy of the unsupervised clustering heatmap was 90.32%. In addition, potential biomarkers and related metabolic pathways were analyzed. This method, with the characteristics of high throughput, high efficiency, and high accuracy, will provide the broad prospect of exosome-driven precision medicine and large-scale screening in clinical applications.

Serum Metabolomics Analysis of Skin-Involved Systemic Lupus Erythematosus: Association of Anti-SSA Antibodies with Photosensitivity

Purpose

Systemic lupus erythematosus is a heterogeneous autoimmune disease in which skin involvement is a common manifestation. It is currently thought that the photosensitivity of SLE skin involvement is associated with anti-SSA antibodies. This study aimed to expand the current state of knowledge surrounding the molecular pathophysiology of SLE skin photosensitivity through Serum metabolomics analysis.

Patients and Methods

The serum metabolites of 23 cases of skin-involved SLE (SI) group, 14 cases of no SI (NSI) group, and 30 cases of healthy controls (HC) were analyzed by using UPLC-MS/MS technology, and subgroup analysis was performed according to the expression of anti-SSA antibodies in SI. MetaboAnalyst 5.0 was used for enrichment analysis and ROC curve construction, identifying serum metabolic markers of skin-involved SLE associated with anti-SSA antibodies.

Results

We identified several metabolites and metabolic pathways associated with SLE photosensitivity. Two metabolites, SM (d18:1/24:0) and gamma-CEHC can distinguish between anti-SSA antibody-positive and negative SI, with AUC of 0.829 and 0.806. These two photosensitization-related substances may be potential markers of skin involvement in SLE associated with anti-SSA antibody.

Conclusion

This study provides new insights into the pathogenesis of SI patients, and provides a new molecular biological basis for the association between anti-SSA antibodies and skin photoallergic manifestations of SLE.

Advanced methods and novel biomarkers in autoimmune diseases ‑ a review of the recent years progress in systemic lupus erythematosus

There are several autoimmune and rheumatic diseases affecting different organs of the human body. Multiple sclerosis (MS) mainly affects brain, rheumatoid arthritis (RA) mainly affects joints, Type 1 diabetes (T1D) mainly affects pancreas, Sjogren's syndrome (SS) mainly affects salivary glands, while systemic lupus erythematosus (SLE) affects almost every organ of the body. Autoimmune diseases are characterized by production of autoantibodies, activation of immune cells, increased expression of pro-inflammatory cytokines, and activation of type I interferons. Despite improvements in treatments and diagnostic tools, the time it takes for the patients to be diagnosed is too long, and the main treatment for these diseases is still non-specific anti-inflammatory drugs. Thus, there is an urgent need for better biomarkers, as well as tailored, personalized treatment. This review focus on SLE and the organs affected in this disease. We have used the results from various rheumatic and autoimmune diseases and the organs involved with an aim to identify advanced methods and possible biomarkers to be utilized in the diagnosis of SLE, disease monitoring, and response to treatment.

Metabolomic and Proteomic Identification of Serum Exosome for Hypoxic Preconditioning Participants

Background

In high-altitude areas, hypoxic stress can elicit a series of physiological responses in humans. Exosomes play important roles in both local and distal cellular communications.

Methods

We used ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) studies to analyze the differentially expressed metabolomics and proteomics in serum exosome of hypoxic preconditioning participants and control subjects in the hypoxic conditions.

Results

Fifty-seven military personnel were divided into hypoxic preconditioning group (n = 27) and control group (n = 30). One hundred thirty-six differentially expressed serum exosomal metabolites were found between the hypoxic preconditioning and control groups in the hypoxic conditions, and these differentially expressed metabolites were enriched in pathways related to lysine degradation, butanoate metabolism, GABAergic synapse, histidine metabolism, and linoleic acid metabolism. In addition, hypoxic preconditioning participants showed 102 excellent differential expressions of proteomics compared to controls, which involved actin cytoskeleton organization, hemostasis, complement and coagulation cascades, vesicle-medicated transport, wound healing, etc.

Conclusions

We revealed that the expression of exosomal metabolites and proteomics in hypoxic preconditioning participants was significantly different compared to controls in hypoxic conditions.

Integration of metabolomics and lipidomics reveals serum biomarkers for systemic lupus erythematosus with different organs involvement

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects various organs or systems. We performed metabolomic and lipidomic profiles analyses of 133 SLE patients and 30 HCs. Differential metabolites and lipids were integrated, and then the biomarker panel was identified using binary logistic regression. We found that a combination of four metabolites or lipids could distinguish SLE from HC with an AUC of 0.998. Three lipids were combined to differentiate inactive SLE and active SLE. The AUC was 0.767. In addition, we also identified the biomarkers for different organ phenotypes of SLE. The AUCs for diagnosing SLE patients with only kidney involvement, skin involvement, blood system involvement, and multisystem involvement were 0.766, 0.718, 0.951, and 0.909, respectively. Our study succeeded in identifying biomarkers associated with different clinical phenotypes in SLE patients, which could facilitate a more precise diagnosis and assessment of disease progression in SLE.