Search

Systemic lupus erythematosus (SLE) is an autoimmune disease that is characterized by multi-organ involvement leading to significant morbidity and mortality in predominantly young women. The underlying pathogenesis involves the emergence of autoreactive T and B lymphocytes, production of autoantibodies, formation and deposition of immune complexes in various tissues leading to inflammation and organ damage. Recently, growing evidence suggests that the functions of hematopoietic stem cells (HSCs) and mesenchymal stem cells (MSCs) are disrupted in SLE pathology. And HSC or MSC transplantation (HSCT/MSCT) can offer an effective and safe therapy for the severe SLE patients, resulting in disease clinical remission and improvement of organ dysfunction. In this article, we provide a brief overview of current research of autologous or allogeneic HSCT/MSCT in SLE and describe our current understanding of the mechanisms by which it plays a part in treating SLE, for better understanding of the pathogenesis, diagnosis and treatment for SLE.

Renal transplant success is closely tied to the ability to monitor transplant recipients. However, transplant monitoring still depends on relatively dated technologies. Thus, we applied a novel method of proton nuclear magnetic resonance (NMR)-based metabolomics to investigate the altered metabolic pattern in serum, seeking to identify biomarkers involved to different periods of renal transplant patients. Serum was obtained from 28 healthy controls (class 4) and from 20 renal transplant patients in different periods: pretransplant (class 1) and on the 1st (class 2) and the 7th day (class 3) after transplantation. After performing proton NMR spectroscopy, multivariate pattern recognition was applied to cluster the groups and establish disease-specific metabolite biomarker profiles. Compared with class 4, 19 different peaks and 10 potential biomarkers were identified in class 1, class 2, and class 3 (p0.0001). Nevertheless, there was no obvious difference between class 1, class 2, and class 3 (p0.05). Partial least squares-discriminant analysis models were able to identify patients with sensitivity and specificity of 98.7% and 95.4%, respectively. These results not only indicate that this novel method has sufficient sensitivity to distinguish renal transplant patients from controls but also identify biomarkers to monitor graft function, which could be developed to a clinically useful diagnostic tool.

OBJECTIVES: Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile. METHODS: Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification. RESULTS: Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-Inositol, lactate, L6 lipids ( = CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β -glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine. CONCLUSIONS: These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis.