Identification of reference genes for quantitative RT-PCR in ascending aortic aneurysms.

Hypertension and congenital aortic valve malformations are frequent causes of ascending aortic aneurysms. The molecular mechanisms of aneurysm formation under these circumstances are not well understood. Reference genes for gene activity studies in aortic tissue that are not influenced by aortic valve morphology and its hemodynamic consequences, aortic dilatation, hypertension, or antihypertensive medication are not available so far. This study determines genes in ascending aortic tissue that are independent of these parameters. Tissue specimens from dilated and undilated ascending aortas were obtained from 60 patients (age ≤70 years) with different morphologies of the aortic valve (tricuspid undilated n = 24, dilated n = 11; bicuspid undilated n = 6, dilated n = 15; unicuspid dilated n = 4). Of the studied individuals, 36 had hypertension, and 31 received ACE inhibitors or AT1 receptor antagonists. The specimens were obtained intraoperatively from the wall of the ascending aorta. We analyzed the expression levels of 32 candidate reference genes by quantitative RT-PCR (RT-qPCR). Differential expression levels were assessed by parametric statistics. The expression analysis of these 32 genes by RT-qPCR showed that EIF2B1, ELF1, and PPIA remained constant in their expression levels in the different specimen groups, thus being insensitive to aortic valve morphology, aortic dilatation, hypertension, and medication with ACE inhibitors or AT1 receptor antagonists. Unlike many other commonly used reference genes, the genes EIF2B1, ELF1, and PPIA are neither confounded by aortic comorbidities nor by antihypertensive medication and therefore are most suitable for gene expression analysis of ascending aortic tissue.

Selection of Reference Genes for Quantitative Real Time PCR (qPCR) Assays in Tissue from Human Ascending Aorta.

Dilatation of the ascending aorta (AAD) is a prevalent aortopathy that occurs frequently associated with bicuspid aortic valve (BAV), the most common human congenital cardiac malformation. The molecular mechanisms leading to AAD associated with BAV are still poorly understood. The search for differentially expressed genes in diseased tissue by quantitative real-time PCR (qPCR) is an invaluable tool to fill this gap. However, studies dedicated to identify reference genes necessary for normalization of mRNA expression in aortic tissue are scarce. In this report, we evaluate the qPCR expression of six candidate reference genes in tissue from the ascending aorta of 52 patients with a variety of clinical and demographic characteristics, normal and dilated aortas, and different morphologies of the aortic valve (normal aorta and normal valve n = 30; dilated aorta and normal valve n = 10; normal aorta and BAV n = 4; dilated aorta and BAV n = 8). The expression stability of the candidate reference genes was determined with three statistical algorithms, GeNorm, NormFinder and Bestkeeper. The expression analyses showed that the most stable genes for the three algorithms employed were CDKN1β, POLR2A and CASC3, independently of the structure of the aorta and the valve morphology. In conclusion, we propose the use of these three genes as reference genes for mRNA expression analysis in human ascending aorta. However, we suggest searching for specific reference genes when conducting qPCR experiments with new cohort of samples.

Characterization of microevolution events in Mycobacterium tuberculosis strains involved in recent transmission clusters.

Under certain circumstances, it is possible to identify clonal variants of Mycobacterium tuberculosis infecting a single patient, probably as a result of subtle genetic rearrangements in part of the bacillary population. We systematically searched for these microevolution events in a different context, namely, recent transmission chains. We studied the clustered cases identified using a population-based universal molecular epidemiology strategy over a 5-year period. Clonal variants of the reference strain defining the cluster were found in 9 (12%) of the 74 clusters identified after the genotyping of 612 M. tuberculosis isolates by IS6110 restriction fragment length polymorphism analysis and mycobacterial interspersed repetitive units-variable-number tandem repeat typing. Clusters with microevolution events were epidemiologically supported and involved 4 to 9 cases diagnosed over a 1- to 5-year period. The IS6110 insertion sites from 16 representative isolates of reference and microevolved variants were mapped by ligation-mediated PCR in order to characterize the genetic background involved in microevolution. Both intragenic and intergenic IS6110 locations resulted from these microevolution events. Among those cases of IS6110 locations in intergenic regions which could have an effect on the regulation of adjacent genes, we identified the overexpression of cytochrome P450 in one microevolved variant using quantitative real-time reverse transcription-PCR. Our results help to define the frequency with which microevolution can be expected in M. tuberculosis transmission chains. They provide a snapshot of the genetic background of these subtle rearrangements and identify an event in which IS6110-mediated microevolution in an isogenic background has functional consequences.

Trends in qualifying biomarkers in drug safety. Consensus of the 2011 meeting of the spanish society of clinical pharmacology.

In this paper we discuss the consensus view on the use of qualifying biomarkers in drug safety, raised within the frame of the XXIV meeting of the Spanish Society of Clinical Pharmacology held in Málaga (Spain) in October, 2011. The widespread use of biomarkers as surrogate endpoints is a goal that scientists have long been pursuing. Thirty years ago, when molecular pharmacogenomics evolved, we anticipated that these genetic biomarkers would soon obviate the routine use of drug therapies in a way that patients should adapt to the therapy rather than the opposite. This expected revolution in routine clinical practice never took place as quickly nor with the intensity as initially expected. The concerted action of operating multicenter networks holds great promise for future studies to identify biomarkers related to drug toxicity and to provide better insight into the underlying pathogenesis. Today some pharmacogenomic advances are already widely accepted, but pharmacogenomics still needs further development to elaborate more precise algorithms and many barriers to implementing individualized medicine exist. We briefly discuss our view about these barriers and we provide suggestions and areas of focus to advance in the field.

Application of Molecular Diagnostic Techniques for Viral Testing.

Nucleic acid amplification techniques are commonly used currently to diagnose viral diseases and manage patients with this kind of illnesses. These techniques have had a rapid but unconventional route of development during the last 30 years, with the discovery and introduction of several assays in clinical diagnosis. The increase in the number of commercially available methods has facilitated the use of this technology in the majority of laboratories worldwide. This technology has reduced the use of some other techniques such as viral culture based methods and serological assays in the clinical virology laboratory. Moreover, nucleic acid amplification techniques are now the methods of reference and also the most useful assays for the diagnosis in several diseases. The introduction of these techniques and their automation provides new opportunities for the clinical laboratory to affect patient care. The main objectives in performing nucleic acid tests in this field are to provide timely results useful for high-quality patient care at a reasonable cost, because rapid results are associated with improvements in patients care. The use of amplification techniques such as polymerase chain reaction, real-time polymerase chain reaction or nucleic acid sequence-based amplification for virus detection, genotyping and quantification have some advantages like high sensitivity and reproducibility, as well as a broad dynamic range. This review is an up-to-date of the main nucleic acid techniques and their clinical applications, and special challenges and opportunities that these techniques currently provide for the clinical virology laboratory.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.