An introduction to low-level analysis methods of DNA microarray data

This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray data and incorporation of quality information in subsequent analyses, the combination of information across arrays and across sets of experiments, the discovery and recognition of patterns in expression at the single gene and multiple gene levels, and the assessment of significance of these findings, considering the fact that there is a lot of noise and thus random features in the data. For all of these components, access to a flexible and efficient statistical computing environment is an essential aspect.

Error models for microarray intensities

We derive the additive-multiplicative error model for microarray intensities, and describe two applications. For the detection of differentially expressed genes, we obtain a statistic whose variance is approximately independent of the mean intensity. For the post hoc calibration (normalization) of data with respect to experimental factors, we describe a method for parameter estimation.

No evidence for an association of posttraumatic stress disorder with circulating levels of CRP and IL-18 in a population-based study.

Several studies have shown associations of posttraumatic stress disorder (PTSD) with the development of cardiometabolic diseases. The underlying psychopathological mechanisms, including potential links to inflammatory processes, have been discussed but remain elusive. Therefore, the aim of the present study was to evaluate the association of PTSD symptoms with the inflammatory biomarkers C-reactive protein (CRP) and interleukin-18 (IL-18). The study population consisted of 3012 participants aged 32-81years drawn from the population-based KORA F4 study conducted in 2006-08 in the Augsburg region (Southern Germany). PTSD symptoms were measured by the Impact of Event Scale, the Posttraumatic Diagnostic Scale and interview data and classified as no, partial or full PTSD. The associations of PTSD with CRP and IL-18 concentrations were estimated by multiple regression analyses with adjustments for age, sex and cardiometabolic risk factors. Linear regression analyses showed no significant association between PTSD and CRP or IL-18 concentration: adjusted for age and sex, the geometric mean concentrations in participants with full PTSD was for CRP 9% lower and for IL-18 1% higher than in participants with no PTSD (p values 0.53 and 0.89). However, further analyses indicated that individuals with partial PTSD had an increased chance of belonging to the highest quartile of the IL-18 concentration. No significant association was observed for any of the three subscales intrusion, avoidance or hyperarousal with CRP or IL-18 concentration. This large, population-based study could not find an association of full PTSD with CRP and IL-18 concentrations. Further research is needed to analyse these relationships.

Das israelitische Recht, in seinen Grundzügen dargest.

von J. Schnell

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