Ciliary Genes Are Down-Regulated in Bronchial Tissue of Primary Ciliary Dyskinesia Patients

Primary ciliary dyskinesia (PCD) is a rare, genetically heterogeneous disease characterized by recurrent respiratory tract infections, sinusitis, bronchiectasis and male infertility. The pulmonary phenotype in PCD is caused by the impaired motility of cilia in the respiratory epithelium, due to ultrastructural defects of these organelles. We hypothesized that defects of multi-protein ciliary complexes should be reflected by gene expression changes in the respiratory epithelium. We have previously found that large group of genes functionally related to cilia share highly correlated expression pattern in PCD bronchial tissue. Here we performed an explorative analysis of differential gene expression in the bronchial tissue from six PCD patients and nine non-PCD controls, using Illumina HumanRef-12 Whole Genome BeadChips. We observed 1323 genes with at least 2-fold difference in the mean expression level between the two groups (t-test p-value <0.05). Annotation analysis showed that the genes down-regulated in PCD biopsies (602) were significantly enriched for terms related to cilia, whereas the up-regulated genes (721) were significantly enriched for terms related to cell cycle and mitosis. We assembled a list of human genes predicted to encode ciliary proteins, components of outer dynein arms, inner dynein arms, radial spokes, and intraflagellar transport proteins. A significant down-regulation of the expression of genes from all the four groups was observed in PCD, compared to non-PCD biopsies. Our data suggest that a coordinated down-regulation of the ciliome genes plays an important role in the molecular pathomechanism of PCD

Human Primary Adipocytes Exhibit Immune Cell Function: Adipocytes Prime Inflammation Independent of Macrophages

BACKGROUND: Obesity promotes inflammation in adipose tissue (AT) and this is implicated in pathophysiological complications such as insulin resistance, type 2 diabetes and cardiovascular disease. Although based on the classical hypothesis, necrotic AT adipocytes (ATA) in obese state activate AT macrophages (ATM) that then lead to a sustained chronic inflammation in AT, the link between human adipocytes and the source of inflammation in AT has not been in-depth and systematically studied. So we decided as a new hypothesis to investigate human primary adipocytes alone to see whether they are able to prime inflammation in AT. METHODS AND RESULTS: Using mRNA expression, human preadipocytes and adipocytes express the cytokines/chemokines and their receptors, MHC II molecule genes and 14 acute phase reactants including C-reactive protein. Using multiplex ELISA revealed the expression of 50 cytokine/chemokine proteins by human adipocytes. Upon lipopolysaccharide stimulation, most of these adipocyte-associated cytokines/chemokines and immune cell modulating receptors were up-regulated and a few down-regulated such as (ICAM-1, VCAM-1, MCP-1, IP-10, IL-6, IL-8, TNF-α and TNF-β highly up-regulated and IL-2, IL-7, IL-10, IL-13 and VEGF down-regulated. In migration assay, human adipocyte-derived chemokines attracted significantly more CD4+ T cells than controls and the number of migrated CD4+ cells was doubled after treating the adipocytes with LPS. Neutralizing MCP-1 effect produced by adipocytes reduced CD4+ migration by approximately 30%. CONCLUSION: Human adipocytes express many cytokines/chemokines that are biologically functional. They are able to induce inflammation and activate CD4+ cells independent of macrophages. This suggests that the primary event in the sequence leading to chronic inflammation in AT is metabolic dysfunction in adipocytes, followed by production of immunological mediators by these adipocytes, which is then exacerbated by activated ATM, activation and recruitment of immune cells. This study provides novel knowledge about the prime of inflammation in human obese adipose tissue, opening a new avenue of investigations towards obesity-associated type 2 diabetes

Blood Eosinophil Count and Metabolic, Cardiac and Pulmonary Outcomes: A Mendelian Randomization Study.

Blood eosinophil count is associated with a variety of common complex outcomes in epidemiological observation. The aim of this study was to explore the causal association between determined blood eosinophil count and 20 common complex outcomes (10 metabolic, 6 cardiac, and 4 pulmonary). Through Mendelian randomization, we investigated genetic evidence for the genetically determined eosinophil in association with each outcomes using individual-level LifeLines cohort data (n = 13,301), where a weighted eosinophil genetic risk score comprising five eosinophil associated variants was created. We further examined the associations of the genetically determined eosinophil with those outcomes using summary statistics obtained from genome-wide association study consortia (6 consortia and 14 outcomes). Blood eosinophil count, by a 1-SD genetically increased, was not statistically associated with common complex outcomes in the LifeLines. Using the summary statistics, we showed that a higher genetically determined eosinophil count had a significant association with lower odds of obesity (odds ratio (OR) 0.81, 95% confidence interval (CI) [0.74, 0.89]) but not with the other traits and diseases. To conclude, an elevated eosinophil count is unlikely to be causally associated to higher risk of metabolic, cardiac, and pulmonary outcomes. Further studies with a stronger genetic risk score for eosinophil count may support these results

Co-expressed immune and metabolic genes in visceral and subcutaneous adipose tissue from severely obese individuals are associated with plasma HDL and glucose levels: a microarray study

<p>Abstract</p> <p>Background</p> <p>Excessive accumulation of body fat, in particular in the visceral fat depot, is a major risk factor to develop a variety of diseases such as type 2 diabetes. The mechanisms underlying the increased risk of obese individuals to develop co-morbid diseases are largely unclear.</p> <p>We aimed to identify genes expressed in subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) that are related to blood parameters involved in obesity co-morbidity, such as plasma lipid and glucose levels, and to compare gene expression between the fat depots.</p> <p>Methods</p> <p>Whole-transcriptome SAT and VAT gene expression levels were determined in 75 individuals with a BMI >35 kg/m². Modules of co-expressed genes likely to be functionally related were identified and correlated with BMI, plasma levels of glucose, insulin, HbA_1c, triglycerides, non-esterified fatty acids, ALAT, ASAT, C-reactive protein, and LDL- and HDL cholesterol.</p> <p>Results</p> <p>Of the approximately 70 modules identified in SAT and VAT, three SAT modules were inversely associated with plasma HDL-cholesterol levels, and a fourth module was inversely associated with both plasma glucose and plasma triglyceride levels (p < 5.33 × 10^-5). These modules were markedly enriched in immune and metabolic genes. In VAT, one module was associated with both BMI and insulin, and another with plasma glucose (p < 4.64 × 10^-5). This module was also enriched in inflammatory genes and showed a marked overlap in gene content with the SAT modules related to HDL. Several genes differentially expressed in SAT and VAT were identified.</p> <p>Conclusions</p> <p>In obese subjects, groups of co-expressed genes were identified that correlated with lipid and glucose metabolism parameters; they were enriched with immune genes. A number of genes were identified of which the expression in SAT correlated with plasma HDL cholesterol, while their expression in VAT correlated with plasma glucose. This underlines both the singular importance of these genes for lipid and glucose metabolism and the specific roles of these two fat depots in this respect.</p

Complex nature of SNP genotype effects on gene expression in primary human leucocytes

<p>Abstract</p> <p>Background</p> <p>Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown.</p> <p>Methods</p> <p>We correlated gene expression and genetic variation in untouched primary leucocytes (n = 110) from individuals with celiac disease – a common condition with multiple risk variants identified. We compared our observations with an EBV-transformed HapMap B cell line dataset (n = 90), and performed a meta-analysis to increase power to detect non-tissue specific effects.</p> <p>Results</p> <p>In celiac peripheral blood, 2,315 SNP variants influenced gene expression at 765 different transcripts (< 250 kb from SNP, at FDR = 0.05, <it>cis </it>expression quantitative trait loci, eQTLs). 135 of the detected SNP-probe effects (reflecting 51 unique probes) were also detected in a HapMap B cell line published dataset, all with effects in the same allelic direction. Overall gene expression differences within the two datasets predominantly explain the limited overlap in observed <it>cis</it>-eQTLs. Celiac associated risk variants from two regions, containing genes <it>IL18RAP </it>and <it>CCR3</it>, showed significant <it>cis </it>genotype-expression correlations in the peripheral blood but not in the B cell line datasets. We identified 14 genes where a SNP affected the expression of different probes within the same gene, but in opposite allelic directions. By incorporating genetic variation in co-expression analyses, functional relationships between genes can be more significantly detected.</p> <p>Conclusion</p> <p>In conclusion, the complex nature of genotypic effects in human populations makes the use of a relevant tissue, large datasets, and analysis of different exons essential to enable the identification of the function for many genetic risk variants in common diseases.</p

Comparative analysis of the human hepatic and adipose tissue transcriptomes during LPS-induced inflammation leads to the identification of differential biological pathways and candidate biomarkers

<p>Abstract</p> <p>Background</p> <p>Insulin resistance (IR) is accompanied by chronic low grade systemic inflammation, obesity, and deregulation of total body energy homeostasis. We induced inflammation in adipose and liver tissues <it>in vitro </it>in order to mimic inflammation <it>in vivo </it>with the aim to identify tissue-specific processes implicated in IR and to find biomarkers indicative for tissue-specific IR.</p> <p>Methods</p> <p>Human adipose and liver tissues were cultured in the absence or presence of LPS and DNA Microarray Technology was applied for their transcriptome analysis. Gene Ontology (GO), gene functional analysis, and prediction of genes encoding for secretome were performed using publicly available bioinformatics tools (DAVID, STRING, SecretomeP). The transcriptome data were validated by proteomics analysis of the inflamed adipose tissue secretome.</p> <p>Results</p> <p>LPS treatment significantly affected 667 and 483 genes in adipose and liver tissues respectively. The GO analysis revealed that during inflammation adipose tissue, compared to liver tissue, had more significantly upregulated genes, GO terms, and functional clusters related to inflammation and angiogenesis. The secretome prediction led to identification of 399 and 236 genes in adipose and liver tissue respectively. The secretomes of both tissues shared 66 genes and the remaining genes were the differential candidate biomarkers indicative for inflamed adipose or liver tissue. The transcriptome data of the inflamed adipose tissue secretome showed excellent correlation with the proteomics data.</p> <p>Conclusions</p> <p>The higher number of altered proinflammatory genes, GO processes, and genes encoding for secretome during inflammation in adipose tissue compared to liver tissue, suggests that adipose tissue is the major organ contributing to the development of systemic inflammation observed in IR. The identified tissue-specific functional clusters and biomarkers might be used in a strategy for the development of tissue-targeted treatment of insulin resistance in patients.</p

Large-Scale Gene-Centric Meta-Analysis across 39 Studies Identifies Type 2 Diabetes Loci

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with similar to 2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 x 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p <2.4 x 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 x 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 x 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 x 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups