Learning gene regulatory networks using gaussian process emulator and graphical LASSO.

Large amounts of research efforts have been focused on learning gene regulatory networks (GRNs) based on gene expression data to understand the functional basis of a living organism. Under the assumption that the joint distribution of the gene expressions of interest is a multivariate normal distribution, such networks can be constructed by assessing the nonzero elements of the inverse covariance matrix, the so-called precision matrix or concentration matrix. This may not reflect the true connectivity between genes by considering just pairwise linear correlations. To relax this limitative constraint, we employ Gaussian process (GP) model which is well known as computationally efficient non-parametric Bayesian machine learning technique. GPs are among a class of methods known as kernel machines which can be used to approximate complex problems by tuning their hyperparameters. In fact, GP creates the ability to use the capacity and potential of different kernels in constructing precision matrix and GRNs. In this paper, in the first step, we choose the GP with appropriate kernel to learn the considered GRNs from the observed genetic data, and then we estimate kernel hyperparameters using rule-of-thumb technique. Using these hyperparameters, we can also control the degree of sparseness in the precision matrix. Then we obtain kernel-based precision matrix similar to GLASSO to construct kernel-based GRN. The findings of our research are used to construct GRNs with high performance, for different species of Drosophila fly rather than simply using the assumption of multivariate normal distribution, and the GPs, despite the use of the kernels capacity, have a much better performance than the multivariate Gaussian distribution assumption.

miR-559 polymorphism rs58450758 is linked to breast cancer.

Background: MicroRNAs (miRNAs) participate in gene regulation and the control of cancer-related mechanisms such as apoptosis, invasion and differentiation. Single nucleotide polymorphisms (SNP) of the miRNA encoding genes may influence the development of cancer. We hypothesized a link between miR-559 SNP rs58450758 and breast cancer.Materials & methods: Bioinformatics analyses were performed to predict the miR-559 target genes and the effect of the rs58450758 SNP on the stem-loop structure. A total of 129 breast cancer cases and 153 controls were genotyped using PCR-RFLP.Results: The recessive genotype (TT) was more common among breast cancer patients (23.3%) than among controls (2%). The non-dominant genotypes (CT+TT) were associated with breast cancer in patients (OR 3.62; 95% CI, 1.95-6.69; p < 0.0001). Bioinformatics analyses suggested that rs58450758 changes miR-559 secondary structure and forms new DICER sites in the pre-miRNA.Conclusion: The miR-559 rs58450758 variant is linked to breast cancer.

Coronary Artery Disease Risk Factors in an Urban and Peri-urban Setting, Kerman, Southeastern Iran (KERCADR Study): Methodology and Preliminary Report.

BACKGROUND: This article was to present the sampling and measurements methods and the main preliminary findings of the KERCADR cohort study (first round) in an urban and peri-urban setting, Kerman, southeastern Iran 2009-11. METHOD: 5900 (3238 female) people aged between 15 to 75 years were recruited in the household survey by non-proportional to size one-stage cluster sampling. Trained internal specialists, general practitioners, clinical psychologists and dentists have assessed the study subjects by person-assisted questionnaires regarding different NCD risk factors including cigarette and opium smoking, physical activity, nutrition habits, anxiety, depression, obesity, hypertension and oral health. Blood samples were also collected for determining FBS, HbA1c, cholesterol and triglyceride. Weighted standardized prevalence estimates were calculated by STATA 10 survey analysis package. RESULTS: The participation rate was more than 95% in all subgroups. Cigarette smoking (18.4% vs. 1.2%), opium use (17.8% vs. 3.0%) and triglyceridemia (16.1% vs. 12.0%) were significantly higher among men than women. In contrast, women were presented with higher level of sever anxiety (29.1% vs. 16.7%), obesity (16.8% vs. 9.2%), low-physical activity (45.1% vs. 39.2%) and uncontrolled diabetes (60.2% vs. 31.0%). More than 68% of all subjects have presented with moderate to severe gingival index scores. CONCLUSION: The first round of the KERCADR cohort with sufficient sample size and response rate provided precise estimates for the main clinical and para-clinical NCD risk factors. These evidences need to be translated into public health interventions and monitored in the next rounds of the cohort.

The Association between Y Chromosome Microdeletion and Recurrent Pregnancy Loss.

BACKGROUND: To date, the role of male factor contributing in evaluation of spontaneous recurrent pregnancy loss (RPL) has been less investigated and there is discrepancy in the role of Y chromosome microdeltions in RPL. Therefore, the current study was designed to examine whether Y chromosome microdeletions were associated with RPL in an Iranian population. METHODS: One hundred men from couples, experiencing three or more RPLs, and one hundred normal men from couples with at least one child and no history of miscarriages as control group were included. Genomic DNA was extracted from peripheral blood and tested for Y chromosome microdeletions in AZFa, AZFb and AZFc regions using two multiplex PCR. RESULTS: None of the men in the case and control groups had any microdeletions in the AZFa, AZFb and AZFc regions. CONCLUSION: It seems that Y chromosome microdeletion is not associated with recurrent pregnancy loss, therefore performing this test in Iranian couples with RPL is not recommended.