Serum Circulating microRNA Profiling for Identification of Potential Type 2 Diabetes and Obesity Biomarkers

Background and Aim

MicroRNAs are small non-coding RNAs that play important regulatory roles in a variety of biological processes, including complex metabolic processes, such as energy and lipid metabolism, which have been studied in the context of diabetes and obesity. Some particular microRNAs have recently been demonstrated to abundantly and stably exist in serum and to be potentially disease-specific. The aim of this profiling study was to characterize the expression of miRNA in serum samples of obese, nonobese diabetic and obese diabetic individuals to determine whether miRNA expression was deregulated in these serum samples and to identify whether any observed deregulation was specific to either obesity or diabetes or obesity with diabetes.

Patients and Methods

Thirteen patients with type 2 diabetes, 20 obese patients, 16 obese patients with type 2 diabetes and 20 healthy controls were selected for this study. MiRNA PCR panels were employed to screen serum levels of 739 miRNAs in pooled samples from these four groups. We compared the levels of circulating miRNAs between serum pools of each group. Individual validation of the twelve microRNAs selected as promising biomarkers was carried out using RT-qPCR.

Results

Three serum microRNAs, miR-138, miR-15b and miR-376a, were found to have potential as predictive biomarkers in obesity. Use of miR-138 or miR-376a provides a powerful predictive tool for distinguishing obese patients from normal healthy controls, diabetic patients, and obese diabetic patients. In addition, the combination of miR-503 and miR-138 can distinguish diabetic from obese diabetic patients.

Conclusion

This study is the first to show a panel of serum miRNAs for obesity, and compare them with miRNAs identified in serum for diabetes and obesity with diabetes. Our results support the use of some miRNAs extracted from serum samples as potential predictive tools for obesity and type 2 diabetes.     

Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma

Objective

To investigate discriminating protein patterns and serum biomarkers between clear cell renal cell carcinoma (ccRCC) patients and healthy controls, as well as between paired pre- and post-operative ccRCC patients.

Methods

We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to identify patients with ccRCC. A total of 162 serum samples were analyzed in this study, among which there were 58 serum samples from ccRCC patients, 40 from additional paired pre- and post-operative ccRCC patients (n = 20), and 64 from healthy volunteers as healthy controls. ClinProTools software identified several distinct markers between ccRCC patients and healthy controls, as well as between pre- and post-operative patients.

Results

Patients with ccRCC could be identified with a mean sensitivity of 88.38% and a mean specificity of 91.67%. Of 67 m/z peaks that differed among the ccRCC, healthy controls, pre- and post-operative ccRCC patients, 24 were significantly different (P<0.05). Three candidate peaks, which were upregulated in ccRCC group and showed a tendency to return to healthy control values after surgery, were identified as peptide regions of RNA-binding protein 6 (RBP6), tubulin beta chain (TUBB), and zinc finger protein 3 (ZFP3) with the m/z values of 1466.98, 1618.22, and 5905.23, respectively.

Conclusion

MB-MALDI-TOF-MS method could generate serum peptidome profiles of ccRCC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.     

Identification of Serum Biomarkers for Gastric Cancer Diagnosis Using a Human Proteome Microarray

We aimed to globally discover serum biomarkers for diagnosis of gastric cancer (GC). GC serum autoantibodies were discovered and validated using serum samples from independent patient cohorts encompassing 1,401 participants divided into three groups, i.e. healthy, GC patients, and GC-related disease group. To discover biomarkers for GC, the human proteome microarray was first applied to screen specific autoantibodies in a total of 87 serum samples from GC patients and healthy controls. Potential biomarkers were identified via a statistical analysis protocol. Targeted protein microarrays with only the potential biomarkers were constructed and used to validate the candidate biomarkers using 914 samples. To provide further validation, the abundance of autoantibodies specific to the biomarker candidates was analyzed using enzyme-linked immunosorbent assays. Receiver operating characteristic curves were generated to evaluate the diagnostic accuracy of the serum biomarkers. Finally, the efficacy of prognosis efficacy of the final four biomarkers was evaluated by analyzing the clinical records. The final panel of biomarkers consisting of COPS2, CTSF, NT5E, and TERF1 provides high diagnostic power, with 95% sensitivity and 92% specificity to differentiate GC patients from healthy individuals. Prognosis analysis showed that the panel could also serve as independent predictors of the overall GC patient survival. The panel of four serum biomarkers (COPS2, CTSF, NT5E, and TERF1) could serve as a noninvasive diagnostic index for GC, and the combination of them could potentially be used as a predictor of the overall GC survival rate.Gastric cancer (GC)¹ is the second leading cause of cancer-related deaths. A total of 952,000 new GC cases (6.8% of the total of the new cancer case) and 723,000 deaths (8.8% of the total new cancer case) occurred in 2012 (1). The highest mortality rates have been reported in East Asia, including China, Japan, and Korea (2–4), and ∼60% of new GC cases and deaths worldwide occur in this region. As GC has a 5-year survival rate of less than 15%, accurate diagnosis and prognostic assessment of patients are essential for optimizing therapeutic strategies, predicting the outcome of treatment, extending the survival period of patients, and potentially healing to reduce cancer mortality (5).A variety of serum antigen biomarkers has been used for GC diagnosis and prognosis, e.g. carcinoembryonic antigen, carbohydrate antibody 19-9 (CA19-9), carbohydrate antibody 72-4 (CA72-4), and carbohydrate antibody 50 (CA50); the protein levels of these antigens in serum are usually used as signatures indicating cancer risk. However, generally, these serum antigen biomarkers lack sufficient sensitivity and specificity (6–8).Autoantibodies against proteins that result from abnormal gene expression and gene mutation in patients with various tumors represent another type of serum biomarker (9–12). The corresponding antigens of the autoantibodies are usually recognized as tumor-specific antigens or tumor-associated antigens (13–16). There is particular interest in these autoantibodies due to the potential diagnostic and prognostic applications of the autoantibodies and their corresponding antigens. Indeed, there is a need to identify novel autoantibody-based biomarkers to improve the sensitivity and specificity for the diagnosis of GC.In this study, we used a human proteome microarray containing 16,368 proteins to discover and independently validate serum autoantibodies with potential for diagnosis and prognosis of GC in a set of 1,401 serum samples. The samples were from 537 GC patients, 550 healthy controls, and 314 individuals of GC-related diseases. Four autoantigen serum biomarkers, COP9 constitutive photomorphogenic homolog subunit 2 (COPS2), CTSF, ecto-5′-nucleotidase (NT5E), and telomeric repeat binding factor 1 (TERF1), were identified with a combined diagnostic sensitivity of 95% and specificity of 92%. Furthermore, our data suggested COPS2, CTSF, NT5E, and TERF1 could also serve as potential predictors for prognostic assessment.     

Identification and Validation of Potential Biomarkers for the Detection of Dysregulated microRNA by qPCR in Patients with Colorectal Adenocarcinoma

Colorectal cancer represents a lethal disease that has raised concern and has attracted significant attention. Adenocarcinoma is the most common type of colorectal cancer (CRC). MicroRNAs are thought to be potential biomarkers of CRC. Many researchers have focused on the expression pattern of miRNAs in CRC. However, previous studies did not pay particular attention to the effects of the degree of differentiation of the cancer with respect to the miRNA expression profile. First, this study compared the expression level of 1547 miRNAs by qRT-PCR in Colorectal adenocarcinoma tissues to that in paired normal tissues. In all, 93 miRNAs were identified that were significantly dysregulated in Colorectal adenocarcinoma relative to normal tissues (P<0.05). Then, we analyzed their potential as cancer biomarkers by ROC analysis, and the result revealed that three miRNAs with high sensitivity and specificity are suitable as biomarkers for the diagnosis of CRC (the value of the AUC was greater than 0.7). Interestingly, previous reports of 23 of these miRNAs have been scarce. Furthermore, we wanted to analyze the difference between well- and moderately differentiated cancers, and as expected, 58 miRNAs showed significant dysregulation. Importantly, 32 miRNAs were able to not only distinguish cancer tissues from normal tissues, but they were also able to identify well- and moderately differentiated cancers. In conclusion, the degree of differentiation has an important influence on the miRNA expression pattern. To avoid misdiagnoses and missed diagnoses, tumors of different degrees of differentiation should be treated differently when miRNAs are used as cancer biomarkers.     

Biodosimetry estimate for high-LET irradiation

The purpose of this paper is to prepare for an easy and reliable biodosimeter protocol for radiation accidents involving high-linear energy transfer (LET) exposure. Human peripheral blood lymphocytes were irradiated using carbon ions (LET: 34.6 keV μm⁻¹), and the chromosome aberrations induced were analyzed using both a conventional colcemid block method and a calyculin A induced premature chromosome condensation (PCC) method. At a lower dose range (0–4 Gy), the measured dicentric (dics) and centric ring chromosomes (cRings) provided reasonable dose information. At higher doses (8 Gy), however, the frequency of dics and cRings was not suitable for dose estimation. Instead, we found that the number of Giemsa-stained drug-induced G2 prematurely condensed chromosomes (G2-PCC) can be used for dose estimation, since the total chromosome number (including fragments) was linearly correlated with radiation dose (r = 0.99). The ratio of the longest and the shortest chromosome length of the drug-induced G2-PCCs increased with radiation dose in a linear-quadratic manner (r = 0.96), which indicates that this ratio can also be used to estimate radiation doses. Obviously, it is easier to establish the dose response curve using the PCC technique than using the conventional metaphase chromosome method. It is assumed that combining the ratio of the longest and the shortest chromosome length with analysis of the total chromosome number might be a valuable tool for rapid and precise dose estimation for victims of radiation accidents.     

Identification of plant microRNA homologs

MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs that regulate gene and protein expression in plants and animals. MiRNAs have so far been identified mostly by specific cloning of small RNA molecules, complemented by computational methods. We present a computational identification approach that is able to identify candidate miRNA homologs in any set of sequences, given a query miRNA. The approach is based on a sequence similarity search step followed by a set of structural filters.     

Release of Inorganic Phosphate from Irradiated Yeast: Radiation Biodosimetry and Evaluation of Radioprotective Compounds

When cells of bakers' yeast, Saccharomyces cerevisiae, were irradiated with ionizing radiation, inorganic phosphate, ninhydrin-reactive material, and substances absorbing at 260 mmu were released into the suspending medium. The amount of inorganic phosphate released depended on the radiation dose and on the temperature and pH during irradiation. The concentration of yeast cells did not affect the phosphate yield per milligram of yeast. It is suggested that the release of phosphate may serve as an index of the total radiation environment (i.e., as a biodosimeter) where radiation inactivation of microrganisms is of primary importance, e.g., in radiation preservation of foods. The somewhat limited range of the yeast biodosimeter (ca. 0.5 to 1.75 Mrad) may be extended by use of other more resistant microorganisms, such as bacterial spores. Compounds which have been reported as protecting microorganisms and mammals against the lethal effect of ionizing radiation also inhibited the radiation-induced release of inorganic phosphate from yeast. This phosphate release system is proposed as the basis for an economical, rapid supplement to screening procedures in the evaluation of radioprotective compounds.     

Serum microRNA biomarkers for detection of non-small cell lung cancer

Non small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality world-wide and the majority of cases are diagnosed at late stages of disease. There is currently no cost-effective screening test for NSCLC, and the development of such a test is a public health imperative. Recent studies have suggested that chest computed tomography screening of patients at high risk of lung cancer can increase survival from disease, however, the cost effectiveness of such screening has not been established. In this Phase I/II biomarker study we examined the feasibility of using serum miRNA as biomarkers of NSCLC using RT-qPCR to examine the expression of 180 miRNAs in sera from 30 treatment naive NSCLC patients and 20 healthy controls. Receiver operating characteristic curves (ROC) and area under the curve were used to identify differentially expressed miRNA pairs that could distinguish NSCLC from healthy controls. Selected miRNA candidates were further validated in sera from an additional 55 NSCLC patients and 75 healthy controls. Examination of miRNA expression levels in serum from a multi-institutional cohort of 50 subjects (30 NSCLC patients and 20 healthy controls) identified differentially expressed miRNAs. A combination of two differentially expressed miRNAs miR-15b and miR-27b, was able to discriminate NSCLC from healthy controls with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 100% in the training set. Upon further testing on additional 130 subjects (55 NSCLC and 75 healthy controls), this miRNA pair predicted NSCLC with a specificity of 84% (95% CI 0.73-0.91), sensitivity of 100% (95% CI; 0.93-1.0), NPV of 100%, and PPV of 82%. These data provide evidence that serum miRNAs have the potential to be sensitive, cost-effective biomarkers for the early detection of NSCLC. Further testing in a Phase III biomarker study in is necessary for validation of these results.     

Identification of Serum Biomarkers for Systemic Lupus Erythematosus Using a Library of Phage Displayed Random Peptides and Deep Sequencing

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Highlights

• •A phage displayed random peptide library and deep sequencing were combined and applied to screen biomarkers for SLE.
• •A statistical analysis protocol was set up for the identification of peptides as potential biomarkers.
• •A panel of four-peptide (SLE2018Val) was discovered with high diagnostic power to differentiate SLE patients from healthy controls.

     

乙肝患者血清标志物与肝纤维化血清学指标的相关性分析

目的:探讨乙肝患者血清标志物与肝纤维化血清学指标的相关性。方法:收集我院收治的136例乙型病毒肝炎患者,根据轻中重程度分为轻度组、中度组以及重度组,每组42例。观察并比较所有患者乙肝血清标志物、HBV-DNA水平、透明质酸(HA),血清Ⅲ型前胶原肽(PCⅢ),Ⅳ型胶原(CIV)水平以及层粘连蛋白(LN)水平。结果:三组患者的HBV-DNA水平依次升高,与轻度组相比,中度组、重度组患者HBV-DNA水平较高,与中度组患者相比,重度组患者HBV-DNA水平较高,差异具有统计学意义(P0.05)。与轻度组相比,中度组、重度组患者HA、PCⅢ、CIV、LN水平较高,与中度组患者相比,重度组患者HA、PCⅢ水平较高,差异具有统计学意义(P0.05);HBV-DNA水平与HA、PCⅢ、CIV、LN水平均呈显著正相关。结论:乙肝患者的血清学检测指标与血清肝纤维化测定有助于对乙肝的纤维化过程的进展情况进行评估。     

Serum Albumin and Body Weight as Biomarkers for the Antemortem Identification of Bone and Gastrointestinal Disease in the Common Marmoset

The increasing use of the common marmoset (Callithrix jacchus) in research makes it important to diagnose spontaneous disease that may confound experimental studies. Bone disease and gastrointestinal disease are two major causes of morbidity and mortality in captive marmosets, but currently no effective antemortem tests are available to identify affected animals prior to the terminal stage of disease. In this study we propose that bone disease and gastrointestinal disease are associated disease entities in marmosets and aim to establish the efficacy of several economical antemortem tests in identifying and predicting disease. Tissues from marmosets were examined to define affected animals and unaffected controls. Complete blood count, serum chemistry values, body weight, quantitative radiographs, and tissue-specific biochemical markers were evaluated as candidate biomarkers for disease. Bone and gastrointestinal disease were associated, with marmosets being over seven times more likely to have either concurrent bone and gastrointestinal disease or neither disease as opposed to lesions in only one organ system. When used in tandem, serum albumin <3.5 g/dL and body weight <325 g identified 100% of the marmosets affected with concurrent bone and gastrointestinal disease. Progressive body weight loss of 0.05% of peak body weight per day predicted which marmosets would develop disease prior to the terminal stage. Bone tissue-specific tests, such as quantitative analysis of radiographs and serum parathyroid hormone levels, were effective for distinguishing between marmosets with bone disease and those without. These results provide an avenue for making informed decisions regarding the removal of affected marmosets from studies in a timely manner, preserving the integrity of research results.     

Biodosimetry and assessment of radiation dose

Aim

When investigating radiation accidents, it is very important to determine the exposition dose to the individuals. In the case of exposures over 1 Gy, clinicians may expect deterministic effects arising the following weeks and months, in these cases dose estimation will help physicians in the planning of therapy. Nevertheless, for doses below 1 Gy, biodosimetry data are important due to the risk of developing late stochastic effects. Finally, some accidental overexposures are lack of physical measurements and the only way of quantifying dose is by biological dosimetry.

Background

The analysis of chromosomal aberrations by different techniques is the most developed method of quantifying dose to individuals exposed to ionising radiations.^1,2 Furthermore, the analysis of dicentric chromosomes observed in metaphases from peripheral lymphocytes is the routine technique used in case of acute exposures to assess radiation doses.

Materials and methods

Solid stain of chromosomes is used to determine dicentric yields for dose estimation. Fluorescence in situ hybridization (FISH) for translocations analysis is used when delayed sampling or suspected chronically irradiation dose assessment. Recommendations in technical considerations are based mainly in the IAEA Technical Report No. 405.²

Results

Experience in biological dosimetry at Gregorio Marañón General Hospital is described, including own calibration curves used for dose estimation, background studies and real cases of overexposition.

Conclusion

Dose assessment by biological dosimeters requires a large previous standardization work and a continuous update. Individual dose assessment involves high qualification professionals and its long time consuming, therefore requires specific Centres. For large mass casualties cooperation among specialized Institutions is needed.     

Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction

Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2>1 and P value <0.05) between first‐day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up‐regulated and 41 down‐regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up‐regulated and 1173 down‐regulated DEGs. The comparison of the DEGs in two datasets revealed four common up‐regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (P < 0.05). The DEGs, especially the four up‐regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650–658, 2018. © 2017 Wiley Periodicals, Inc.     

Identification of Predictive Early Biomarkers for Sterile-SIRS after Cardiovascular Surgery

Systemic inflammatory response syndrome (SIRS) is a common complication after cardiovascular surgery that in severe cases can lead to multiple organ dysfunction syndrome and even death. We therefore set out to identify reliable early biomarkers for SIRS in a prospective small patient study for timely intervention. 21 Patients scheduled for planned cardiovascular surgery were recruited in the study, monitored for signs of SIRS and blood samples were taken to investigate biomarkers at pre-assigned time points: day of admission, start of surgery, end of surgery, days 1, 2, 3, 5 and 8 post surgery. Stored plasma and cryopreserved blood samples were analyzed for cytokine expression (IL1β, IL2, IL6, IL8, IL10, TNFα, IFNγ), other pro-inflammatory markers (sCD163, sTREM-1, ESM-1) and response to endotoxin. Acute phase proteins CRP, PCT and pro-inflammatory cytokines IL6 and IL8 were significantly increased (p<0.001) at the end of surgery in all patients but could not distinguish between groups. Normalization of samples revealed significant increases in IL1β changes (p<0.05) and decreased responses to endotoxin (p<0.01) in the SIRS group at the end of surgery. Soluble TREM-1 plasma concentrations were significantly increased in patients with SIRS (p<0.01). This small scale patient study could show that common sepsis markers PCT, CRP, IL6 and TNFα had low predictive value for early diagnosis of SIRS after cardiovascular surgery. A combination of normalized IL1β plasma levels, responses to endotoxin and soluble TREM-1 plasma concentrations at the end of surgery are predictive markers of SIRS development in this small scale study and could act as an indicator for starting early therapeutic interventions.     

Serum microRNA expression profile as a biomarker for the diagnosis of pertussis

Pertussis is a highly contagious, respiratory disease associated with substantial morbidity and mortality. A rapid and reliable diagnostic method is essential for appropriate treatment and prevention. Expression profiles of circulating microRNAs (miRNAs) have been proven as new non-invasive biomarkers for infectious diseases. We aimed to investigated the serum miRNA profile in pertussis patients and explored its potential as a novel diagnostic biomarker for pertussis. Among 664 different miRNAs analyzed using a miRNA array, 50 were overexpressed and 81 were underexpressed in the serum of pertussis patients. Expression levels of seven candidate miRNAs were further evaluated by real-time qRT-PCR. A panel of five miRNAs (miR-202, miR-342-5p, miR-206, miR-487b, miR-576-5p) was confirmed overexpressed in pertussis patients (p < 0.05). Risk score and receiver-operating characteristic (ROC) analysis showed that the area under the curve of the five-member miRNA profile was 0.980. At an optimal cutoff value (0.707), this panel of miRNAs yielded a sensitivity of 97.4 % and a specificity of 94.3 %. These data suggest that the five-member serum miRNA profile may serve as a new biomarker for pertussis diagnosis with high specificity and sensitivity.     

Principal Component Analysis Based Feature Extraction Approach to Identify Circulating microRNA Biomarkers

The discovery and characterization of blood-based disease biomarkers are clinically important because blood collection is easy and involves relatively little stress for the patient. However, blood generally reflects not only targeted diseases, but also the whole body status of patients. Thus, the selection of biomarkers may be difficult. In this study, we considered miRNAs as biomarker candidates for several reasons. First, since miRNAs were discovered relatively recently, they have not yet been tested extensively. Second, since the number of miRNAs is relatively limited, selection is expected to be easy. Third, since they are known to play critical roles in a wide range of biological processes, their expression may be disease specific. We applied a newly proposed method to select combinations of miRNAs that discriminate between healthy controls and each of 14 diseases that include 5 cancers. A new feature selection method is based on principal component analysis. Namely this method does not require knowledge of whether each sample was derived from a disease patient or a healthy control. Using this method, we found that hsa-miR-425, hsa-miR-15b, hsa-miR-185, hsa-miR-92a, hsa-miR-140-3p, hsa-miR-320a, hsa-miR-486-5p, hsa-miR-16, hsa-miR-191, hsa-miR-106b, hsa-miR-19b, and hsa-miR-30d were potential biomarkers; combinations of 10 of these miRNAs allowed us to discriminate each disease included in this study from healthy controls. These 12 miRNAs are significantly up- or downregulated in most cancers and other diseases, albeit in a cancer- or disease-specific combinatory manner. Therefore, these 12 miRNAs were also previously reported to be cancer- and disease-related miRNAs. Many disease-specific KEGG pathways were also significantly enriched by target genes of up−/downregulated miRNAs within several combinations of 10 miRNAs among these 12 miRNAs. We also selected miRNAs that could discriminate one disease from another or from healthy controls. These miRNAs were found to be largely overlapped with miRNAs that discriminate each disease from healthy controls.