Biomarkers For Clinical Diagnosis Research Articles

A new finding in the key prognosis-related proto-oncogene FYN in hepatocellular carcinoma based on the WGCNA hub-gene screening trategy

BackgroundHepatocellular carcinoma (HCC) is the third-most deadly cancer worldwide. More breakthroughs are needed in the clinical practice for liver cancer are needed, and new treatment strategies are required. This study aims to determine the significant differences in genes associated with LIHC and further analyze its prognostic value further.MethodsHere, we used the TCGA-LIHC database and the profiles of GSE25097 from GEO to explore the differentially co-expressed genes in HCC tissues compared with paratumor (or healthy) tissues. Then, we utilized WGCNA to screen differentially co-expressed genes. Finally, we explored the function of FYN in HCC cells and xenograft tumor models.ResultsWe identified ten hub genes in the protein–protein interaction (PPI) network, but only three (COLEC10, TGFBR3, and FYN) appeared closely related to the prognosis. The expression of FYN was positively correlated with the prognosis of HCC patients. The xenograft model showed that overexpression of FYN could significantly inhibit malignant tumor behaviors and promote tumor cell apoptosis.ConclusionThus, FYN may be central to the development of LIHC and maybe a novel biomarker for clinical diagnosis and treatment.

Exploring the Change of Host and Microorganism in Chronic Obstructive Pulmonary Disease Patients Based on Metagenomic and Metatranscriptomic Sequencing.

BackgroundChronic obstructive pulmonary disease (COPD) is a universal respiratory disease resulting from the complex interactions between genes and environmental conditions. The process of COPD is deteriorated by repeated episodes of exacerbations, which are the primary reason for COPD-related morbidity and mortality. Bacterial pathogens are commonly identified in patients’ respiratory tracts both in the stable state and during acute exacerbations, with significant changes in the prevalence of airway bacteria occurring during acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Therefore, the changes in microbial composition and host inflammatory responses will be necessary to investigate the mechanistic link between the airway microbiome and chronic pulmonary inflammation in COPD patients.MethodsWe performed metatranscriptomic and metagenomic sequencing on sputum samples for twelve AECOPD patients before treatment and for four of them stable COPD (stabilization of AECOPD patients after treatment). Sequencing reads were classified by Kraken2, and the host gene expression was analyzed by Hisat2 and HTseq. The correlation between genes was obtained by the Spearman correlation coefficient. Mann–Whitney U-test was applied to identify microbes that exhibit significantly different distribution in two groups.ResultsAt the phyla level, the top 5 dominant phyla were Firmicutes, Actinobacteria, Proteobacteria, Bacteroidetes, and Fusobacteria. The proportion of dominant gates in metagenomic data was similar in metatranscriptomic data. There were significant differences in the abundance of specific microorganisms at the class level between the two methods. No significant difference between AECOPD and stable COPD was found. However, the different expression levels of 5 host genes were significantly increased in stable COPD and were involved in immune response and inflammatory pathways, which were associated with macrophages.ConclusionOur study may provide a clue to investigate the mechanism of COPD and potential biomarkers in clinical diagnosis and treatment.

Clinical significance of LAG-3 on microvessel density in primary hepatocellular carcinoma.

We aimed to determine whether lymphocyte activation gene 3 (LAG-3), also known as CD223, is associated with microvessel density (MVD) in primary hepatocellular carcinoma (HCC), as well as their clinical significance in predicting survival. One hundred and twenty-seven patients were enrolled in the study. Samples were obtained on resection at the Department of Hepatobiliary Surgery of the Qingdao Municipal Hospital from June 2014 to June 2016. Immunohistochemistry was used to determine vessel density and LAG-3 abundance. Statistical analyses were performed to test for correlation of LAG-3 density and other clinicopathological variables with overall survival (OS). High LAG-3 abundance was significantly correlated with increased MVD in primary HCC (P < 0.05). The χ2 test revealed a significant association of LAG-3 with preoperative AFP level, tumor diameter, N stage, and the presence of HBV infection (P < 0.05). Patients with high LAG-3 expression had shorter OS compared to those with low LAG-3 expression (P < 0.05). The Cox proportional hazards model showed that both higher LAG-3 and MVD density, age, the number of tumors, preoperative AFP level, tissue differentiation, Child-Pugh grade, and lymph node metastasis correlated with survival. High expression of LAG-3 is associated with angiogenesis and poor prognosis in HCC patients. With the deepening of research, LAG-3 is likely to become a novel biomarker for clinical diagnosis and prognosis and can even be a therapeutic target of HCC.

Study on plasma exosome biomarkers of pregnant women with intrahepatic cholestasis of pregnancy

Objective and aims Serum total bile acid (TBA) level as the main index for the diagnosis of intrahepatic cholestasis of pregnancy (ICP) has some limitations. The early diagnosis and new treatment of ICP still need to be further strengthened. Materials and methods Plasma samples were collected, and exosomes were isolated. Key differential proteins were screened by bioinformatics methods. ELISA method was used to detect the concentration of the key differential protein in plasma samples, and the receiver operating characteristic curve (ROC) curve was drawn to find out the best critical value. Results There were 138 differentially expressed proteins between the ICP and the normal groups by quantitative analysis. Cluster protein (CLU) was screened as a clinical validation index. The CLU concentration of plasma exosomes in the ICP group was significantly higher than that in the normal group (p < .0001). ROC curve analysis showed that the best critical point for diagnosing ICP according to the plasma exosomes CLU concentration of pregnant women was 255.28 ng/ml. In the ICP group, the best crucial point for predicting ICP with premature delivery is 286.72 ng/ml. Conclusions The plasma exosomes CLU in pregnant women with ICP is an important biomarker for clinical diagnosis and prediction of premature delivery of ICP.

Integrated analysis of transcriptome profiling of lncRNAs and mRNAs in livers of type 2 diabetes mellitus.

Long noncoding RNAs (lncRNAs) influence the progression of almost all human diseases, but the participation of lncRNAs in type 2 diabetes mellitus (T2DM) has not been fully elucidated. This study aimed to systematically compare the transcriptome profiling of lncRNAs and mRNAs in livers between patients with T2DM and controls, to identify key genes associated with T2DM pathogenesis, and to predict the underlying molecular mechanisms. As a result, a total of 1,512 differentially expressed (DE) lncRNAs and 1,923 DE mRNAs were identified through microarray analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that multiple metabolic processes were dysregulated such as small molecule, organic acid, lipid, and branched chain amino acid metabolism. Protein-protein interaction network was constructed, and 10 hub mRNAs were identified, including EHHADH, ATM, ACOX1, PIK3R1, EGFR, UQCRFS1, HMGCL, UQCRC2, NDUFS3, and F2. RT-qPCR was conducted to verify the validity of microarray results. Then, coding-noncoding co-expression network and competing endogenous RNA (ceRNA) network were analyzed to predict the lncRNA-mRNA and lncRNA-miRNA-mRNA regulatory patterns. Subsequently, 10 key intermediating miRNAs in ceRNA networks with a node degree >80 were identified, including hsa-miR-5692a, hsa-miR-12136, hsa-miR-5680, hsa-miR-1305, hsa-miR-6833-5p, hsa-miR-7159-5p, hsa-miR-548as-3p, hsa-miR-6873-3p, hsa-miR-1290, and hsa-miR-4768-5p. In conclusion, this study evaluated the transcriptome profiling of lncRNAs and mRNAs in livers from patients with T2DM, with a value for understanding the molecular mechanism of disease pathogenesis and identifying effective biomarkers in clinical diagnosis.

Whole Genome Assembly of Human Papillomavirus by Nanopore Long-Read Sequencing

Human papillomavirus (HPV) is a causal agent for most cervical cancers. The physical status of the HPV genome in these cancers could be episomal, integrated, or both. HPV integration could serve as a biomarker for clinical diagnosis, treatment, and prognosis. Although whole-genome sequencing by next-generation sequencing (NGS) technologies, such as the Illumina sequencing platform, have been used for detecting integrated HPV genome in cervical cancer, it faces challenges of analyzing long repeats and translocated sequences. In contrast, Oxford nanopore sequencing technology can generate ultra-long reads, which could be a very useful tool for determining HPV genome sequence and its physical status in cervical cancer. As a proof of concept, in this study, we completed whole genome sequencing from a cervical cancer tissue and a CaSki cell line with Oxford Nanopore Technologies. From the cervical cancer tissue, a 7,894 bp-long HPV35 genomic sequence was assembled from 678 reads at 97-fold coverage of HPV genome, sharing 99.96% identity with the HPV sequence obtained by Sanger sequencing. A 7904 bp-long HPV16 genomic sequence was assembled from data generated from the CaSki cell line at 3857-fold coverage, sharing 99.99% identity with the reference genome (NCBI: U89348). Intriguingly, long reads generated by nanopore sequencing directly revealed chimeric cellular–viral sequences and concatemeric genomic sequences, leading to the discovery of 448 unique integration breakpoints in the CaSki cell line and 60 breakpoints in the cervical cancer sample. Taken together, nanopore sequencing is a unique tool to identify HPV sequences and would shed light on the physical status of HPV genome in its associated cancers.

Comprehensive Analysis of Myoferlin in Human Pancreatic Cancer via Bioinformatics.

Pancreatic cancer is the fourth leading cause of cancer-related death and urgently needs biomarkers for clinical diagnosis and prognosis. It has been reported that myoferlin (MYOF) is implicated in the regulation of proliferation, invasion, and migration of tumor cells in many cancers including pancreatic cancer. To confirm the prognostic value of MYOF in pancreatic cancer, a comprehensive cancer versus healthy people analysis was conducted using public data. MYOF mRNA expression levels were compared in many kinds of cancers including pancreatic cancer via the Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The results have shown that MYOF mRNA expression levels were upregulated in most types of cancers, especially in pancreatic cancer, compared with healthy people's tissues. Data from the Cancer Cell Line Encyclopedia (CCLE) and European Bioinformatics Institute (EMBL-EML) database also revealed that MYOF mRNA is highly expressed in most cancer cells, particularly in pancreatic cancer cell lines. Furthermore, the prognostic value of MYOF was evaluated using GEPIA and Long-term Outcome and Gene Expression Profiling Database of pan-cancers (LOGpc) database. Higher expression of MYOF was associated with poorer overall survival, especially in the lower stage and lower grade. Coexpressed genes, possible regulators, and the correlation between MYOF expressions were analyzed via the GEPIA and LinkedOmics database. Nineteen coexpressed genes were identified, and most of these genes were related to cancer. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the correlation between MYOF and immune response. Notably, we found that MYOF might have a potential novel immune regulatory role in tumor immunity. These results support that MYOF is a candidate prognostic biomarker for pancreatic cancer, which calls for further genomics research of pancreatic cancer and deeply functional studies on MYOF.

A novel self-enhancement NCNDs-BPEI-Ru nanocomposite with highly efficient electrochemiluminescence as signal probe for ultrasensitive detection of MTB

Herein, a novel self-enhanced Ru(Ⅱ)-based nanocomposite (NCNDs-BPEI-Ru), synthesized by covalently connecting nitrogen-doped carbon nanodots (NCNDs) and tris (4,4′-dicarboxylicacid-2,2′-bipyridyl) ruthenium (II) dichloride (Ru(dcbpy)3Cl2) through branched polyethyleneimine (BPEI), could be used as an electrochemiluminescence (ECL) signal probe for ultrasensitive detection of mycobacterium tuberculosis (MTB) DNA fragment. Without any extraneous coreactants, NCNDs-BPEI-Ru could generate an ultra-strong initial ECL signal on the glassy carbon electrode (GCE) (signal-on) due to the coreaction from BPEI and NCNDs to Ru(dcbpy)3Cl2. Then, self-assembled DNA nanotubes embedding methylene blue molecules (MB-DNANTs) were modified on the nanocomposite to effectively quench the ECL intensity of NCNDs-BPEI-Ru owing to the quenching effect of MB for Ru(dcbpy)3Cl2 (signal-off). Finally, the 3D DNA nanomachine, formed by a DNA-functionalized magnetic beads (DNA-MBs) could transform trace target MTB into massive output DNA, and the MB-DNANTs could be disintegrated to get ECL signal recovery (signal-on) due to hybridization of output DNA and the S2 in DNANTs. Therefore, the proposed biosensor exhibited predominant performance for the detection of MTB DNA fragment with a low detection limit of 1.4 aM, which showed great application value in the detection of biomarkers in clinical diagnosis.

Establishment of Effective Biomarkers for Depression Diagnosis With Fusion of Multiple Resting-State Connectivity Measures.

Major depressive disorder (MDD) is a severe mental disorder and is lacking in biomarkers for clinical diagnosis. Previous studies have demonstrated that functional abnormalities of the unifying triple networks are the underlying basis of the neuropathology of depression. However, whether the functional properties of the triple network are effective biomarkers for the diagnosis of depression remains unclear. In our study, we used independent component analysis to define the triple networks, and resting-state functional connectivities (RSFCs), effective connectivities (EC) measured with dynamic causal modeling (DCM), and dynamic functional connectivity (dFC) measured with the sliding window method were applied to map the functional interactions between subcomponents of triple networks. Two-sample t-tests with p < 0.05 with Bonferroni correction were used to identify the significant differences between healthy controls (HCs) and MDD. Compared with HCs, the MDD showed significantly increased intrinsic FC between the left central executive network (CEN) and salience network (SAL), increased EC from the right CEN to left CEN, decreased EC from the right CEN to the default mode network (DMN), and decreased dFC between the right CEN and SAL, DMN. Moreover, by fusion of the changed RSFC, EC, and dFC as features, support vector classification could effectively distinguish the MDD from HCs. Our results demonstrated that fusion of the multiple functional connectivities measures of the triple networks is an effective way to reveal functional disruptions for MDD, which may facilitate establishing the clinical diagnosis biomarkers for depression.

DNA-Based Smart Reagent for Detecting Alzheimer's Associated MicroRNAs.

Alzheimer's disease (AD) is the most common neurodegenerative disorder, with significant research efforts devoted to identifying new biomarkers for clinical diagnosis and treatment. MicroRNAs have emerged as likely disease regulators and biomarkers for AD, now implicated as having roles in several biological processes related to progression of the disease. In this work, we use the miRacles assay (microRNA activated conditional looping of engineered switches) for single-step detection of AD-related microRNAs. The technology is based on conformationally responsive DNA nanoswitches that loop upon recognition of a target microRNA and report their on/off status through an electrophoretic readout. Unlike many methods, our approach directly detects native microRNAs without amplification or labeling, eliminating the need for expensive enzymes, reagents, and equipment. For known AD-related microRNA miR-107, we demonstrated sensitivity of ∼8 fM, specificity among four similar microRNAs of the same family, and simultaneous multiplexed detection of those four microRNA targets. Toward clinical use, we screened 56 AD-related microRNAs and found four that showed detectable differences between total RNA extracts derived from human healthy and AD brain samples. In the context of AD, this "smart reagent" could facilitate biomarker discovery, accelerate efforts to understand the role of microRNAs in AD, and have clinical potential as a diagnostic or monitoring tool for validated biomarkers.

P–290 Time-course analysis of endometrial miR/isomiR expression dynamics during hCG-primed menstrual-cycle phase transitions

Abstract Study question What is the qualitative and quantitative profile of microRNAs (miR) and their sequence variants - isomiRs, and how it changes during the menstrual-cycle phase transitions? Summary answer Time-course analysis of endometrial miR/isomiR profiles has shown that menstrual-phase transitions cause widespread and complex changes in miR gene expression and processing. What is known already Embryo implantation depends on the receptivity of the endometrium during the window of implantation, when ovarian hormones and genetic factors coordinate the development of the uterine lining and prepare it for embryo implantation. The most important factors for successful implantation studied so far are the embryo itself, the histological dating of the endometrium and its molecular genetic characteristics, including miRs. With the rapid development of next-generation sequencing technologies, it has become clear that miR genes have the potential to produce not only miR but also variants (isomiRs) thereof, which can differ in sequence and length and can be functionally significant. Study design, size, duration miR/isomiR landscape was assessed by small RNA sequencing of endometrial biopsy samples at 4 time points of endometrial cycle covering the proliferative and secretory phases. Healthy, fertile, female volunteers took part in the study lasting one and a half years. For accurate phase dating, human chorionic gonadotropin (hCG) was administrated, and ultrasonic, histological and hormonal assessments were done at each time point. Statistically significant data of miR/isomiR identification and expression dynamics was considered for analysis. Participants/materials, setting, methods Participant choice criteria - at least one child born, problem-free pregnancies, no diseases or allergies; hCG application time determined according follicle and endometrium ultrasound scanning, and ovarian hormone levels; endometrial biopsies taken at hGC (before hormone application), hGC+2, hGC+7, hGC+9 time points; small RNAseq completed by Karolinska Institute, Sweden; miR/isomiR identified using local Galaxy instance with an in-built workflow and tools developed by our laboratory; differential expression and target prediction evaluated with DESeq2 and miRDB,resp. Main results and the role of chance Within the cohort of patients, across the four study time points, the small RNAseq data revealed numbers of miRs and isomiRs to be changed. The largest statistically significant changes in their expression were found at LH + 9. The miR families that showed the largest number of members with altered expression were miR125a, miR30d, miR449c, miR92a/b and miR99a. The expression levels tended to decrease in the miR125a and miR92a families and to increase in the miR10a and miR449c families during the three studied time points of the cycle compared to the proliferative phase. Among those affected, the number of isomiRs, including templated and non-templated isomiRs, was much higher than that of miRs. For example, the ratio of the significantly altered miRs/templated isomiRs/non-templated isomiRs was 6/16/11 at LH + 9. Templated isomiRs of hsa-miR–148a–3p, hsa-miR–30d–5p and hsa-miR–449c–5p were among the most upregulated, while several templated and non-templated isomiRs of hsa-miR–125–5p were the most downregulated at LH + 9. Of particular interest are those isomiRs, in which the seed site is shifted compared to the reference miRs and results in altered target transcripts. Target prediction of the most affected isomiR of hsa-miR–449c–5p identified new targets of target scores much higher than of the reference miR. Limitations, reasons for caution IsomiRs are a source of novel biomarkers for clinical diagnosis. An important next step is the validation of the in-silico predicted miRs/isomiRs and their target transcripts by RT-qPCR in larger number of individuals. Expression profiles should be associated with the dominant cell type in the endometrial biopsy preparation. Wider implications of the findings: MiR/isomiR signatures, together with those of their target mRNAs, can be applied to distinguish the endometrial phases, especially the implantation window, as well as for diagnosing endometrial dysfunction. It is worth investigating the possibility of miRs/isomiRs being used as biomarkers not only in endometrial biopsy but also in liquid biopsy. Trial registration number The Bulgarian National Science Fund КП–06 Н31/2

Transcriptomic Analysis of Gene Networks Regulated by U11 Small Nuclear RNA in Bladder Cancer.

Small nuclear RNA is a class of non-coding RNA that widely exist in the nucleus of eukaryotes. Accumulated evidences have shown that small nuclear RNAs are associated with the regulation of gene expression in various tumor types. To explore the gene expression changes and its potential effects mediated by U11 snRNA in bladder cancer cells, U11 snRNA knockout and overexpressed cell lines were constructed and further used to analyze the gene expression changes by RNA sequencing. The differentially expressed genes were found to be mainly enriched in tumor-related pathways both in the U11 knockout and overexpression cell lines, such as NF-kappa B signaling pathway, bladder cancer and PI3K-Akt signaling pathway. Furthermore, alternative splicing events were proposed to participate in the potential regulatory mechanism induced by the U11 knockout or overexpression. In conclusion, U11 may be involved in the regulation of gene expression in bladder cancer cells, which may provide a potentially new biomarker for clinical diagnosis and treatment of bladder cancer.

Sensitive and Specific Detecting Biomarker of Radiation-Resistant Nasopharyngeal Carcinoma by TpTta-COF Nanosheet

An important attribute of microRNA-205 (MiR-205) is their potential use as predictive biomarker for anti-radiation of nasopharyngeal carcinoma (NPC), and it is pivotal to monitor the dynamic change of MiR-205 for personalized precise treatment strategies. So far, there are several methods aiming at detecting MiR-205 while rarely has worked out questions such as limited complex detection processes, poor sample detection limit or spending lots of time. Therefore, a method for detecting MiR-205 based on 2D COF nanosheets and fluorescent oligonucleotide probe was constructed and investigated in this study. The 2D COF nanosheet quenches the fluorescence of the fluorescent single-stranded DNA (ss-DNA) probes through fluorescence resonance energy transfer (FRET). The method enables to capture MiR-205 sensitively in aqueous solution with a detection limit of 4.78[Formula: see text]nM in the range 0–500[Formula: see text]nM and [Formula: see text], and the method offers great specificity in that it can distinguish the target miRNA from mismatch nontarget miRNAs. Considering its simple operability and excellent specificity, it has great application prospects in the detection of miRNA biomarker in clinical diagnosis and personalized treatment plan.

In situ determination of secretory kinase Fam20C from living cells using fluorescence correlation spectroscopy

Secretory proteins constitute a biologically crucial subset of proteins for regulation of some pathological and physiological processes, and they have become very important biomarkers in clinical diagnosis and therapeutic targets. So far, secretory protein functions and mechanisms have not been fully understood due to methodological limitations in detection of low-abundance proteins against medium background. Here, we propose a strategy to determine secretory protein from living cells in situ using fluorescence correlation spectroscopy (FCS). In this study, the recombinant protein Fam20C with SNAP-tag was used as a model protein, and O6-benzylguanine (BG) derivatives bearing fluorescent dye as probes. We synthesized three fluorescent probes and investigated their fluorescent properties and diffusion behaviors in solution, and found the probe BG-Bodipy-561 more suitable for in situ labeling of Fam20C. We confirmed the specific binding of the probe to the target protein by combining FCS and in-gel fluorescence scanning methods. We studied the effects of some factors of the secretory Fam20C, and found that RNA interference significantly inhibited the synthesis of secretory fused Fam20C, and myriocin had no significant effect on the expression of secretory Fam20C, which indirectly illustrated that sphingolipid signaling can regulate the Fam20C activity. We believe that FCS is a very promising method to analyze secretory proteins from living cells in situ.

Quadrupole-Linear Ion Trap Tandem Mass Spectrometry System for Clinical Biomarker Analysis

The accurate and efficient measurement of small molecule disease markers for clinical diagnosis is of great importance. In this study, a quadrupole-linear ion trap (Q-LIT) tandem mass spectrometer was designed and built in our laboratory. Target precursor ions were first selected in the quadrupole, and then injected, trapped, and fragmented simultaneously in the linear ion trap (LIT) to reduce the space charge effect, enrich the target product ions, and promote sensitivity. The targeted analytes were measured with selected reaction monitoring using a positive scan mode with electrospray ionization (ESI). Ions with a mass-to-charge ratio ( m / z ) ranging from 195 to 2022 were demonstrated. When scanning at 1218 amu·s −1 , unit resolution and an accuracy of higher than m/z 0.28 was obtained for m / z up to 2000. The dimensionless Mathieu parameter ( q ) value used in this study was 0.40 for collision-induced dissociation (CID), which was activated by resonance excitation. And an overall CID efficiency of 64% was achieved (activation time, 50 ms). Guanidinoacetic acid (GAA) and creatine (CRE) were used as model compounds for small molecule clinical biomarkers. The limits of quantification were 1.0 and 0.2 nmol·L −1 for GAA and CRE, respectively. A total of 77 actual samples were successfully analyzed by the home-built ESI-Q-LIT tandem mass spectrometry system. The developed method can reduce matrix interference, minimize space charge effects, and avoid the chromatographic separation of complex samples to simplify the pretreatment process. This novel Q-LIT system is expected to be a good candidate for the determination of biomarkers in clinical diagnosis and therapeutics.

Redox changes in obesity, metabolic syndrome, and diabetes

"Life is an instantaneous encounter of circulating matter and flowing energy" (Jean Giaja, Serbian physiologist), is one of the most elegant definitions not only of life but the relationship of redox biology and metabolism. Their evolutionary liaison has created inseparable yet dynamic homeostasis in health, which, when disrupted, leads to disease. This interconnection is even more pertinent today, in an era of increasing metabolic diseases of epidemic proportions such as obesity, metabolic syndrome, and diabetes. Despite great advances in understanding the molecular mechanisms of redox and metabolic regulation, we face significant challenges in preventing, diagnosing, and treating metabolic diseases. The etiological association and temporal overlap of these syndromes present significant challenges for the discrimination of appropriate clinical biomarkers for diagnosis, treatment, and outcome prediction. These multifactorial, multiorgan metabolic syndromes with complex etiopathogenic mechanisms are accompanied by disturbed redox equilibrium in target tissues and circulation. Free radicals and reactive species are considered both a causal factor and a consequence of disease status. Thus, determining the subtypes and levels of free radicals and reactive species, oxidatively damaged biomolecules (lipids, proteins, and nucleic acids) and antioxidant defense components as well as redox-sensitive transcription factors and fluxes of redox-dependent metabolic pathways will help define existing and establish novel redox biomarkers for stratifying metabolic diseases. This review aims to discuss diverse redox/metabolic aspects in obesity, metabolic syndrome, and diabetes, with the imperative to help establish a platform for emerging and future redox-metabolic biomarkers research in precision medicine. Future research warrants detailed investigations into the status of redox biomarkers in healthy subjects and patients, including the use of emerging 'omic' profiling technologies (e.g., redox proteomes, lipidomes, metabolomes, and transcriptomes), taking into account the influence of lifestyle (diet, physical activity, sleep, work patterns) as well as circadian ~24h fluctuations in circulatory factors and metabolites.

Identification of key candidate biomarkers for severe influenza infection by integrated bioinformatical analysis and initial clinical validation.

One of the key barriers for early identification and intervention of severe influenza cases is a lack of reliable immunologic indicators. In this study, we utilized differentially expressed genes screening incorporating weighted gene co‐expression network analysis in one eligible influenza GEO data set (GSE111368) to identify hub genes associated with clinical severity. A total of 10 genes (PBI, MMP8, TCN1, RETN, OLFM4, ELANE, LTF, LCN2, DEFA4 and HP) were identified. Gene set enrichment analysis (GSEA) for single hub gene revealed that these genes had a close association with antimicrobial response and neutrophils activity. To further evaluate these genes' ability for diagnosis/prognosis of disease developments, we adopted double validation with (a) another new independent data set (GSE101702); and (b) plasma samples collected from hospitalized influenza patients. We found that 10 hub genes presented highly correlation with disease severity. In particular, BPI and MMP8 encoding proteins in plasma achieved higher expression in severe and dead cases, which indicated an adverse disease development and suggested a frustrating prognosis. These findings provide new insight into severe influenza pathogenesis and identify two significant candidate genes that were superior to the conventional clinical indicators. These candidate genes or encoding proteins could be biomarker for clinical diagnosis and therapeutic targets for severe influenza infection.

Magnetic-graphene oxide based molecular imprinted polymers for selective extraction of glycoprotein at physiological pH

Glycoproteins are extensively used as biomarkers in clinical diagnosis. Therefore, it is a critical requirement to develop efficient methods for ultrasensitive detection and extraction of glycoprotein from physiological fluids. In this paper, by combination of surface imprinting, phenylboronic affinity, and magnetic graphene oxide, a novel type of magnetic molecularly imprinted polymers (MGO/MIPs) was prepared for selective extraction of glycoprotein at physiological pH. During the preparation process, 2,4-difluoro-3-formyl phenylboronic acid – modified magnetic graphene oxide (MGO/DFFPBA) were used as supporting matrices for glycoprotein (horseradish peroxidase, HRP) immobilization, and acrylamide (AAm) was chosen as functional monomer. The polymerization conditions and binding properties of MGO/MIPs were investigated. The results indicated that MGO/MIPs exhibited outstanding binding capacity (200.88 mg/g calculated by Langmuir isotherm equation), fast capture kinetics (35 min), and favorable regeneration ability toward HRP. More importantly, benefitting from low pKa value of DFFPBA, the binding experiment was carried out under physiological pH. Successful extraction of HRP from human serum samples further confirmed the practical utility of the obtained material. Besides, the obtained material could be separated easily by a magnet. All those features make MGO/MIPs promising in separation of glycoprotein from complex samples.

Exosomal miR-23a and miR-192, Potential Diagnostic Biomarkers for Type 2 Diabetes.

Type 2 diabetes mellitus (T2D) is a common chronic disease, which lacks a specific diagnostic method. A substantial body of literature has demonstrated that the molecular constituents of extracellular vesicles (EVs) are promising as a novel biomarker for clinical diagnosis, especially exosomal miRNAs in biological fluids. To find a diagnostic biomarker for T2D, we isolated exosomes from plasma and then quantitative PCR (qPCR) was used to detect the miRNA expression in plasma and exosomes from control subjects and T2D subjects. The ROC (receiver operating characteristic) curve and AUC (area under curve) were used to evaluate the diagnostic value of exosomal miRNAs. We found the exosomal levels of miR-23a and miR-192 were both significantly higher in T2D subjects. The AUC of miR-23a and miR-192 were 0.828 and 0.717, respectively. Further bioinformatics analysis was performed to speculate possible mechanisms. In conclusion, exosomal miR-23a and miR-192 have good potential as diagnostic biomarkers for type 2 diabetes.

Metabonomics Study on Serum Characteristic Metabolites of Psoriasis Vulgaris Patients With Blood-Stasis Syndrome.

Psoriasis is a chronic, refractory, systemic inflammatory skin disease. Traditional Chinese medicine (TCM) shows unique advantage in the treatment of psoriasis based on syndrome differentiation. An untargeted high-throughput metabonomics method based on liquid chromatography coupled to mass spectrometry was applied to study the serum metabolic characteristics in different TCM syndrome types in patients with psoriasis vulgaris (PV), and to discover potential serum biomarkers for its pathogenesis on the endogenous metabolite differentiation basis. The serum metabolic profiles of 45 healthy controls and 124 patients with PV (50 in the blood-stasis group, 30 in the blood-heat group, and 44 in the blood-dryness group) were acquired. The raw spectrometric data were processed using multivariate statistical analysis, and 14 biomarkers related to TCM syndrome differentiation and psoriasis types were screened and identified. The blood-stasis syndrome group showed abnormal lipid metabolism, which was characterized by a low level of phosphatidylcholine (PC) and a high level of lysophosphatidylcholine (LPC). We propose that platelet-activating factor can be applied as a potential biomarker in clinical diagnosis and differentiation of PV with blood-stasis syndrome. The difference in the serum metabolites among PV types with different TCM syndromes and healthy control group illustrated the objective material basis in TCM syndrome differentiation and classification of psoriasis.