Metabolomic Profiling in Neuromyelitis Optica Spectrum Disorder Biomarker Discovery

Thoman, Maxton E; McKarns, Susan C.

doi:10.3390/metabo10090374

Cited by 8 publications

(5 citation statements)

References 219 publications

(366 reference statements)

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“…Previous metabolomic studies have shown an association between a disturbance of amino acid metabolism and autoimmune disease and a certain amino acid profile might have a diagnostic potential ( Fernández-Ochoa et al, 2019 ; Thoman and McKarns, 2020 ; Yan et al, 2020 ). Similarly, we found that amino acids were differentially expressed in urine from VKH patients and they were the most abundant differential metabolites in the present study.…”

Section: Discussionmentioning

confidence: 99%

Identification of Urine Metabolic Biomarkers for Vogt-Koyanagi-Harada Disease

Chang

Zhu

et al. 2021

Front. Cell Dev. Biol.

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The diagnosis of Vogt-Koyanagi-Harada (VKH) disease is mainly based on a complex clinical manifestation while it lacks objective laboratory biomarkers. To explore the potential molecular biomarkers for diagnosis and disease activity in VKH, we performed an untargeted urine metabolomics analysis by ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS). Through univariate and multivariate statistical analysis, we found 9 differential metabolites when comparing VKH patients with healthy controls, and 26 differential metabolites were identified when comparing active VKH patients with inactive VKH patients. Pathway enrichment analysis showed that glycine, serine and threonine metabolism, and arginine and proline metabolism were significantly altered in VKH versus healthy controls. Lysine degradation and biotin metabolism pathways were significantly altered in active VKH versus inactive VKH. Furthermore, the receiver operating characteristic (ROC) curve analysis revealed that the combination of acetylglycine and gamma-glutamylalanine could differentiate VKH from healthy controls with an area under the curve (AUC) of 0.808. A combination of ureidopropionic acid and 5′-phosphoribosyl-5-amino-4-imidazolecarboxamide (AICAR) had an excellent AUC of 0.958 for distinguishing active VKH from inactive VKH. In summary, this study identified abnormal metabolites in urine of patients with VKH disease. Further studies are needed to confirm whether these metabolites are specific for this disease.

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Section: Discussionmentioning

confidence: 99%

Identification of Urine Metabolic Biomarkers for Vogt-Koyanagi-Harada Disease

Chang

Zhu

et al. 2021

Front. Cell Dev. Biol.

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“…With the backing of mass spectrometry and bioinformatics technologies, a highresolution and high-accuracy proteomics technique has been established to identify new MS and NMOSD biomarkers [11,12] in CSF [13][14][15][16][17], sera [18], and urine [19]. These investigations demonstrate the considerable diagnostic potential of this approach in clinical diagnostics.…”

Section: Introductionmentioning

confidence: 99%

Diagnostic Potential of Two Novel Biomarkers for Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis

Shi

Zheng

et al. 2023

Diagnostics

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Background: Currently, no tests can definitively diagnose and distinguish neuromyelitis optica spectrum disorder (NMOSD) from multiple sclerosis (MS). Methods: Initially, cerebrospinal fluid (CSF) proteomics were employed to uncover the novel biomarkers that differentiate NMOSD from MS into cohorts of 10 MS and 10 NMOSD patients. Subsequently, screening biomarkers were validated using an enzyme-linked immunosorbent assay method and CSF and serum samples from 20 MS patients, 20 NMOSD patients, 20 non-inflammatory neurological controls, and 20 healthy controls. Results: In study cohort, insulin-like growth factor-binding protein 7 (IGFBP7) and lysosome-associated membrane glycoprotein 2 (LAMP2) were screened. In validation cohort, serum and CSF IGFBP7 not only exhibited higher levels in MS and NMOSD patients than controls, but also had greatest area under the curve (AUC, above or equal to 0.8) in MS and NMOSD diagnoses. Serum IGFBP7 (0.945) and CSF IGFBP7 (0.890) also had the greatest AUCs for predicting MS progression, while serum LAMP2 had a moderate curve (0.720). Conclusions: IGFBP7 was superior in diagnosing MS and NMOSD, and IGFBP7 and serum LAMP2 performed exceptionally well in predicting the MS progression. These results offered reasons for further investigations into the functions of IGFBP7 and LAMP2 in MS and NMOSD.

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“…In addition to blood biomarkers, biomarkers from urine, feces and cerebrospinal fluid can be used to identify diseases. One such biomarker in the spinal fluid is myelin oligodendrocyte glycoprotein (MOG-IgG) and aquaporin-4 (AQP4), which are used to identify neuromyelitis optica spectrum disorders (30). In the field of ophthalmology, imaging findings and artificial intelligence analysis have been used as biomarkers for prediction and therapy response of choroidal diseases (31)(32)(33), and intraretinal cysts can be used for the prognosis of neovascular age-related macular (AMD) disease (34).…”

Section: Introductionmentioning

confidence: 99%

Novel Potential Biomarkers for Retinopathy of Prematurity

Tan

Wang

et al. 2022

Front. Med.

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Retinopathy of prematurity (ROP) is the main risk factor for vision-threatening disease in premature infants with low birth weight. An accumulating number of independent studies have focused on ROP pathogenesis and have demonstrated that laser photocoagulation therapy and/or anti-VEGF treatment are effective. However, early diagnosis of ROP is still critical. At present, the main method of ROP screening is based on binocular indirect ophthalmoscopy. However, the judgment of whether ROP occurs and whether treatment is necessary depends largely on ophthalmologists with a great deal of experience. Therefore, it is essential to develop a simple, accurate and effective diagnostic method. This review describes recent findings on novel biomarkers for the prediction, diagnosis and prognosis of ROP patients. The novel biomarkers were separated into the following categories: metabolites, cytokines and growth factors, non-coding RNAs, iconography, gut microbiota, oxidative stress biomarkers, and others. Biomarkers with high sensitivity and specificity are urgently needed for the clinical applications of ROP. In addition, using non-invasive or minimally invasive methods to obtain samples is also important. Our review provides an overview of potential biomarkers of ROP.

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Metabolomic Profiling in Neuromyelitis Optica Spectrum Disorder Biomarker Discovery

Cited by 8 publications

References 219 publications

Identification of Urine Metabolic Biomarkers for Vogt-Koyanagi-Harada Disease

Identification of Urine Metabolic Biomarkers for Vogt-Koyanagi-Harada Disease

Diagnostic Potential of Two Novel Biomarkers for Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis

Novel Potential Biomarkers for Retinopathy of Prematurity

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