Biomedical subjects

Anders Sjögren

Publications and source records attributed to Anders Sjögren.

5 recordsLinked to original sources

PubMed2006

Separation of human adipocytes by size: hypertrophic fat cells display distinct gene expression.

Enlarged adipocytes are associated with insulin resistance and are an independent predictor of type 2 diabetes. To understand the molecular link between these diseases and adipocyte hypertrophy, we developed a technique to separate human adipocytes from an adipose tissue sample into populations of small cells (mean 57.6+/-3.54 microm) and large cells (mean 100.1+/-3.94 microm). Microarray analysis of the cell populations separated from adipose tissue from three subjects identified 14 genes, of which five immune-related, with more than fourfold higher expression in large cells than small cells. Two of these genes were serum amyloid A (SAA) and transmembrane 4 L six family member 1 (TM4SF1). Real-time RT-PCR analysis of SAA and TM4SF1 expression in adipocytes from seven subjects revealed 19-fold and 22-fold higher expression in the large cells, respectively, and a correlation between adipocyte size and both SAA and TM4SF1 expression. The results were verified using immunohistochemistry. In comparison with 17 other human tissues and cell types by microarray, large adipocytes displayed by far the highest SAA and TM4SF1 expression. Thus, we have identified genes with markedly higher expression in large, compared with small, human adipocytes. These genes may link hypertrophic obesity to insulin resistance/type 2 diabetes.

Adipocytes↗

PubMed2006

Quality optimised analysis of general paired microarray experiments.

In microarray experiments, several steps may cause sub-optimal quality and the need for quality control is strong. Often the experiments are complex, with several conditions studied simultaneously. A linear model for paired microarray experiments is proposed as a generalisation of the paired two-sample method by Kristiansson et al. (2005). Quality variation is modelled by different variance scales for different (pairs of) arrays, and shared sources of variation are modelled by covariances between arrays. The gene-wise variance estimates are moderated in an empirical Bayes approach. Due to correlations all data is typically used in the inference of any linear combination of parameters. Both real and simulated data are analysed. Unequal variances and strong correlations are found in real data, leading to further examination of the fit of the model and of the nature of the datasets in general. The empirical distributions of the test-statistics are found to have a considerably improved match to the null distribution compared to previous methods, which implies more correct p-values provided that most genes are non-differentially expressed. In fact, assuming independent observations with identical variances typically leads to optimistic p-values. The method is shown to perform better than the alternatives in the simulation study.

Animals↗

PubMed2005

Weighted analysis of paired microarray experiments.

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.

Journal Article↗

PubMed2005

Evaluation of reference genes for studies of gene expression in human adipose tissue.

OBJECTIVE: The aim of this study was to evaluate reference genes for expression studies of human adipose tissue. RESEARCH METHODS AND PROCEDURES: Using 52 human adipose tissue expression profiles (HU95), 10 putative reference genes with the lowest variation in expression levels were selected for further studies. Expression stability of these 10 novel and 5 previously established reference genes was evaluated by real-time reverse transcriptase-polymerase chain reaction analysis. For this purpose, 44 adipose tissue biopsies from 27 subjects were chosen to include a wide range of parameters such as sex, age, BMI, depot origin, biopsy procedure, and effects of nutrition. RESULTS: LRP10 was identified as the gene with the least variation in expression levels. The frequently used reference genes RPLP0, 18S rRNA, PPIA, ACTB, and GAPD were ranked as 4, 6, 7, 8, and 10, respectively. DISCUSSION: Our results suggest that LRP10 is a better choice as reference for expression studies of human adipose tissue compared with the most frequently used reference genes.

Adipose Tissue↗

PubMed2004

Gene profiling reveals increased expression of uteroglobin and other anti-inflammatory genes in glucocorticoid-treated nasal polyps.

BACKGROUND: Treatment with local glucocorticoids (GCs) decreases symptoms and the size of nasal polyps. This might depend on the downregulation of proinflammatory genes, as well as the upregulation of anti-inflammatory genes. OBJECTIVE: We sought to identify GC-regulated anti-inflammatory genes in nasal polyps. METHODS: Affymetrix DNA microarrays were used to analyze the expression of 22,283 genes in 4 nasal polyps before and after local treatment with fluticasone (400 microg/d). Expression of uteroglobin and mammaglobin B was analyzed with real-time PCR in 6 nasal polyps and in nasal biopsy specimens from 6 healthy control subjects. RESULTS: Two hundred three genes had changed in expression in treated polyps, and 139 had known functions: 54 genes were downregulated, and 85 were upregulated. Genes associated with inflammation constituted the largest single functional group. These genes affected key steps in inflammation (eg, immunoglobulin production; antigen processing and presentation; and the chemoattraction and activation of granulocytes, T cells, and B cells). Several proinflammatory genes were downregulated. In contrast, some anti-inflammatory genes were upregulated. The gene that increased most in terms of expression was uteroglobin. This was confirmed with real-time PCR. By contrast, expression of uteroglobin was lower in untreated polyps than in healthy nasal mucosa. Immunohistochemical investigation showed staining of uteroglobin in the epithelium and in seromucous glands in control subjects and in nasal polyps. CONCLUSION: Upregulation of anti-inflammatory genes, such as uteroglobin, might contribute to the effects of local treatment with GCs in nasal polyps.

Adult↗