ABSTRACT
Neurodegenerative diseases (ND) mainly include Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, ataxia, and other diseases. The number of patients with ND is increasing, but the proportion of patients who can be diagnosed and treated early is less than 30% and the cause of ND is still unclear. In order to intervene in the disease as early as possible, researchers are committed to finding biomarkers that facilitate the early diagnosis of ND. Among them, cerebrospinal fluid (CSF) closely reflects the composition of the extracellular space of the brain, and may be the most sensitive biomarker for evaluating ND. However, the method of taking cerebrospinal fluid is more complicated, and it is not a common method in primary care or elderly medical institutions for the treatment of ND patients. Imaging examinations are expensive and difficult to spread among the community. The peripheral blood collection is convenient and less traumatic, which is a potential early screening and follow-up method. There are many components in the blood for analysis and research. This article reviews the research progress of the changes of apolipoprotein in the blood of ND patients as markers.
ABSTRACT
@#Background & Objective: Circulating microRNAs (miRNAs) expressions have been suggested as potential biomarkers for Parkinson’s Disease (PD). Identification of early biomarkers for PD is important and crucial as PD symptoms occur at a late stage. Hence, these biomarkers could be used in molecular diagnosis for early detection. We therefore examined and compared the expression of circulating miRNAs between PD patients and controls. We also compared the miRNAs expression between early-onset PD (EOPD) and late-onset PD (LOPD). Methods: RNA was extracted from the plasma of EOPD (onset age <50 years; n=14), LOPD (onset age < 60 years; n=14) and healthy controls (n=11). The miRNAs expression was determined using the Affymetrix GeneChip microarray. Differential analysis was performed using the R software. Significantly differentiated miRNAs were subsequently analyzed for functional enrichment and biological pathway using the FunRich v1.3 software based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The Omics.net was used to determine the predicted target mRNAs of these miRNAs, and their interactions, based on the five most differentially expressed miRNAs. Results: In total, 273 miRNAs were upregulated in PD patients compared to controls. The most significant miRNAs were hsa-miR-301a-3p, 100-5p, 140-5p, 486-3p, 143-3p (fold change ranging from 11.2 – 32.0). A total of 140 circulating miRNAs were differentially expressed in EOPD compared to LOPD. Five of these miRNAs (one upregulated miRNA (hsa-miR-29b-3p) and four downregulated miRNAs (hsa-miR-297, 4462, 1909-5p and 346) belonged exclusively to the EOPD patients. The predicted gene targets of these miRNAs involved in dopaminergic synapse regulation, crucial to the pathogenesis of PD. Conclusion: Circulating miRNAs differ between PD patients and controls, and between EOPD and LOPD patients. A validation study with a larger and more diverse multi-ethnic population should be conducted to confirm our results.
ABSTRACT
PURPOSE: We aimed to evaluate the clinical significance of a disintegrin and metalloproteinase 8 (ADAM 8) as a potential blood biomarker for gastric cancer (GC). MATERIALS AND METHODS: Blood ADAM 8 was measured by ELISA. Cytokines/chemokines [interleukin-23 (IL-23), stromal cell-derived factor 1α/CXC chemokine ligand 12 (SDF-1α/CXCL12), interleukin-8 (IL-8), and soluble CD40 ligand (sCD40L)] were measured by chemiluminescent immunoassay. They were compared among five groups; normal/gastritis, high-risk, early GC (EGC), advanced GC (AGC) without distant metastasis, and AGC with distant metastasis by one-way analysis of variance in both training (n=80) and validation dataset (n=241). Clinicopathological features of GC and GC-associated cytokines were evaluated for their correlations with blood ADAM 8. To evaluate the diagnostic accuracy to predict GC, receiver operating characteristic (ROC) curve and logistic regression were used. RESULTS: Blood ADAM 8 significantly increased along GC carcinogenesis in both training (ANOVA, p<0.001) and validation dataset (p<0.001). It was significantly higher in EGC compared to high-risk (post-hoc Bonferroni, p=0.041) and normal (p<0.001). It was also higher in AGC compared with high-risk (p<0.001) and normal (p<0.001) groups. However, no significant difference was found between cancer groups. Blood ADAM 8 was correlated with N-stage (Spearman's correlation, γs=0.320, p=0.011), but not with T-stage or M-stage. Pearson's correlations showed blood ADAM 8 was closely correlated with pre-inflammatory cytokines, IL-23 (p=0.036) and SDF-1α/CXCL12 (p=0.037); however, it was not correlated with pro-angiogenic cytokine IL-8 (p=0.313), and sCD40L (p=0.702). ROC curve and logistic regression demonstrated that blood ADAM 8 showed higher diagnostic accuracy (sensitivity, 73.7%; specificity, 86.2%) than CEA (sensitivity, 23.1%; specificity, 91.4%). Combination of ADAM 8 and CEA further increased the diagnostic accuracy to predict GC (sensitivity, 81.8%; specificity, 84.0%). CONCLUSION: Blood ADAM 8 is a promising biomarker for early detection of GC.