Severe Decline in Mir-20a and Mir-92a in the Context of the Mir-17-92 Cluster: Ideal Biomarkers of Various COPD Subtypes

Chronic obstructive pulmonary disease (COPD) is going to be the third leading cause of death by 2020. Circulating miRNAs are among the most beneficial feasible non-aggressive biomarkers for diagnosis and treatment of many diseases. Among members of the significant miR-17-92 cluster, miR-20a and miR-92a are greatly involved in both inflammation and hypoxia (known as the main reasons for COPD comorbidities). Thus, the expression of these miRNAs was evaluated in the serum of 26 patients and 19 controls using the sensitive stem-loop RT-qPCR approach. The results revealed a significant reduction of these miRNAs in patients relative to controls (P<0.001). Decreased expression of miR-20a in a patient might reflect a progressive stage of the disease. MiR-92a might be used as an early-detection biomarker of COPD. These miRNAs can be used as therapeutic targets specifically in the context of the miR-17-92 cluster to address the various clinicopathological aspects of the disease

NDRG4 methylation change, a promising biomarker in colorectal cancer diagnosis

Background: Colorectal cancer (CRC) is the third common type of cancer with rising prevalence worldwide. Despite the diagnoses and treatments developed over the past four decades, the survival rate of patients has improved somewhat, but still has a 5-year survival rate of less than 50%.  In this study hypermethylation of NDRG4 gene was evaluated as a biomarker in screening of CRC.Method: A total of 70 individuals enrolled in this case-control study (45 CRC patients vs. 25 normal controls) and Methylation-Specific PCR was used to evaluate methylation status of NDRG4 in plasma samples.Result: Mean age in the control group and CRC patients was 58.4±3.4 years and 64.6±4.4 years respectively. Male to female ratio in the control group and CRC patients was 1.5:1 and 1.1:1 respectively. Gastrointestinal disease history was positive in 12% and 33% of patients in the control group and CRC patients respectively. 53.3% of CRC patients showed hypermethylation in NDRG4 gene vs. only 23.3% of controls.Conclusion: The results showed that NDRG4 can be a promising biomarker in screening and diagnosis of CRC as a noninvasive blood-based biomarker

Novel directions in data pre-processing and genome-wide association study (GWAS) methodologies to overcome ongoing challenges

A genome-wide association study (GWAS) is a standard population-based technique for identifying the heritable genetic basis of complex diseases by discovering correlations between trait variations and allele frequencies of genetic markers. This article aims to help fill gaps in data pre-processing and GWAS methodologies by reviewing novel techniques and methodologies. Data pre-processing performed prior to a GWAS presents challenges in Hardy-Weinberg (H–W) estimation, genotyping and accounting for factors such as sample structure. Recent developments towards overcoming these challenges are presented: the likelihood ratio test for H–W estimation, sequencing for genotyping, and techniques for dealing with sample structure. Traditional statistical methods cannot provide a way to insightfully interpret the data generated from high-throughput techniques; therefore, novel directions in GWAS methodologies are reviewed using efficient statistical methods, which are flexible techniques for performing genetic association analysis when factors such as non-random sampling or population structure occur. Despite the development of these methods, genotyping costs and an increased capacity for large dataset analysis have motivated researchers to examine tissue-specific signals. This review discusses how prospective and retrospective association analyses can be used to consider binary traits, address non-random ascertainment, and increase the capacity for large dataset analysis. Importantly, for disease susceptibility, rare variants can represent a large portion of genetic markers, and this article reviews some association methods for rare variant detection. In conclusion, the recent developments in GWAS data preparation and methodologies reviewed in this article can overcome most current challenges in the field and will also address future challenges

Identification of Reliable Reference Genes for Quantification of MicroRNAs in Serum Samples of

Objective: In spite of accumulating information about pathological aspects of sulfur mustard (SM), the precise mechanism responsible for its effects is not well understood. Circulating microRNAs (miRNAs) are promising biomarkers for disease diagnosis and prognosis. Accurate normalization using appropriate reference genes, is a critical step in miRNA expression studies. In this study, we aimed to identify appropriate reference gene for microRNA quantification in serum samples of SM victims. Materials and Methods: In this case and control experimental study, using quantitative real-time polymerase chain reaction (qRT-PCR), we evaluated the suitability of a panel of small RNAs including SNORD38B, SNORD49A, U6, 5S rRNA, miR-423-3p, miR-191, miR-16 and miR-103 in sera of 28 SM-exposed veterans of Iran-Iraq war (1980-1988) and 15 matched control volunteers. Different statistical algorithms including geNorm, Normfinder, best-keeper and comparative delta-quantification cycle (Cq) method were employed to find the least variable reference gene. Results: miR-423-3p was identified as the most stably expressed reference gene, and miR- 103 and miR-16 ranked after that. Conclusion: We demonstrate that non-miRNA reference genes have the least stability in serum samples and that some house-keeping miRNAs may be used as more reliable reference genes for miRNAs in serum. In addition, using the geometric mean of two reference genes could increase the reliability of the normalizers