Monocyte gene-expression profile in men with familial combined hyperlipidemia and its modification by atorvastatin treatment

Systematic analysis of nutrigenomic effects of polyphenols related to cardiometabolic health in humans - Evidence from untargeted mRNA and miRNA studies

Cardiovascular and metabolic disorders present major causes of mortality in the ageing population. Polyphenols present in human diets possess cardiometabolic protective properties, however their underlying molecular mechanisms in humans are still not well identified. Even though preclinical and in vitro studies advocate that these bioactives can modulate gene expression, most studies were performed using targeted approaches. With the objective to decipher the molecular mechanisms underlying polyphenols cardiometabolic preventive properties in humans, we performed integrative multi-omic bioinformatic analyses of published studies which reported improvements of cardiometabolic risk factors following polyphenol intake, together with genomic analyses performed using untargeted approach. We identified 5 studies within our criteria and nearly 5000 differentially expressed genes, both mRNAs and miRNAs, in peripheral blood cells. Integrative bioinformatic analyses (e.g. pathway and gene network analyses, identification of transcription factors, correlation of gene expression profiles with those associated with diseases and drug intake) revealed that these genes are involved in the processes such as cell adhesion and mobility, immune system, metabolism, or cell signaling. We also identified 27 miRNAs known to regulate processes such as cell cytoskeleton, chemotaxis, cell signaling, or cell metabolism. Gene expression profiles negatively correlated with expression profiles of cardiovascular disease patients, while a positive correlation was observed with gene expression profiles following intake of drugs against cardiometabolic disorders. These analyses further advocate for health protective effects of these bioactives against age-associated diseases. In conclusion, polyphenols can exert multi-genomic modifications in humans and use of untargeted methods coupled with bioinformatic analyses represent the best approach to decipher molecular mechanisms underlying healthy-ageing effects of these bioactives.

An Integrative Co-localization (INCO) Analysis for SNV and CNV Genomic Features With an Application to Taiwan Biobank Data

Genomic studies have been a major approach to elucidating disease etiology and to exploring potential targets for treatments of many complex diseases. Statistical analyses in these studies often face the challenges of multiplicity, weak signals, and the nature of dependence among genetic markers. This situation becomes even more complicated when multi-omics data are available. To integrate the data from different platforms, various integrative analyses have been adopted, ranging from the direct union or intersection operation on sets derived from different single-platform analysis to complex hierarchical multi-level models. The former ignores the biological relationship between molecules while the latter can be hard to interpret. We propose in this study an integrative approach that combines both single nucleotide variants (SNVs) and copy number variations (CNVs) in the same genomic unit to co-localize the concurrent effect and to deal with the sparsity due to rare variants. This approach is illustrated with simulation studies to evaluate its performance and is applied to low-density lipoprotein cholesterol and triglyceride measurements from Taiwan Biobank. The results show that the proposed method can more effectively detect the collective effect from both SNVs and CNVs compared to traditional methods. For the biobank analysis, the identified genetic regions including the gene VNN2 could be novel and deserve further investigation.

A compendium of monocyte transcriptome datasets to foster biomedical knowledge discovery

Systems-scale profiling approaches have become widely used in translational research settings. The resulting accumulation of large-scale datasets in public repositories represents a critical opportunity to promote insight and foster knowledge discovery. However, resources that can serve as an interface between biomedical researchers and such vast and heterogeneous dataset collections are needed in order to fulfill this potential. Recently, we have developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). This tool can be used to overlay deep molecular phenotyping data with rich contextual information about analytes, samples and studies along with ancillary clinical or immunological profiling data. In this note, we describe a curated compendium of 93 public datasets generated in the context of human monocyte immunological studies, representing a total of 4,516 transcriptome profiles. Datasets were uploaded to an instance of GXB along with study description and sample annotations. Study samples were arranged in different groups. Ranked gene lists were generated based on relevant group comparisons. This resource is publicly available online at http://monocyte.gxbsidra.org/dm3/landing.gsp.

A curated compendium of monocyte transcriptome datasets of relevance to human monocyte immunobiology research

Systems-scale profiling approaches have become widely used in translational research settings. The resulting accumulation of large-scale datasets in public repositories represents a critical opportunity to promote insight and foster knowledge discovery. However, resources that can serve as an interface between biomedical researchers and such vast and heterogeneous dataset collections are needed in order to fulfill this potential. Recently, we have developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). This tool can be used to overlay deep molecular phenotyping data with rich contextual information about analytes, samples and studies along with ancillary clinical or immunological profiling data. In this note, we describe a curated compendium of 93 public datasets generated in the context of human monocyte immunological studies, representing a total of 4,516 transcriptome profiles. Datasets were uploaded to an instance of GXB along with study description and sample annotations. Study samples were arranged in different groups. Ranked gene lists were generated based on relevant group comparisons. This resource is publicly available online at http://monocyte.gxbsidra.org/dm3/landing.gsp.

Lipid-lowering efficacy of atorvastatin

BACKGROUND

This represents the first update of this review, which was published in 2012. Atorvastatin is one of the most widely prescribed drugs and the most widely prescribed statin in the world. It is therefore important to know the dose-related magnitude of effect of atorvastatin on blood lipids.

OBJECTIVES

Primary objective To quantify the effects of various doses of atorvastatin on serum total cholesterol, low-density lipoprotein (LDL)-cholesterol, high-density lipoprotein (HDL)-cholesterol and triglycerides in individuals with and without evidence of cardiovascular disease. The primary focus of this review was determination of the mean per cent change from baseline of LDL-cholesterol. Secondary objectives • To quantify the variability of effects of various doses of atorvastatin.• To quantify withdrawals due to adverse effects (WDAEs) in placebo-controlled randomised controlled trials (RCTs).

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (Issue 11, 2013), MEDLINE (1966 to December Week 2 2013), EMBASE (1980 to December Week 2 2013), Web of Science (1899 to December Week 2 2013) and BIOSIS Previews (1969 to December Week 2 2013). We applied no language restrictions.

SELECTION CRITERIA

Randomised controlled and uncontrolled before-and-after trials evaluating the dose response of different fixed doses of atorvastatin on blood lipids over a duration of three to 12 weeks.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed eligibility criteria for studies to be included and extracted data. We collected information on withdrawals due to adverse effects from placebo-controlled trials.

MAIN RESULTS

In this update, we found an additional 42 trials and added them to the original 254 studies. The update consists of 296 trials that evaluated dose-related efficacy of atorvastatin in 38,817 participants. Included are 242 before-and-after trials and 54 placebo-controlled RCTs. Log dose-response data from both trial designs revealed linear dose-related effects on blood total cholesterol, LDL-cholesterol, HDL-cholesterol and triglycerides. The Summary of findings table 1 documents the effect of atorvastatin on LDL-cholesterol over the dose range of 10 to 80 mg/d, which is the range for which this systematic review acquired the greatest quantity of data. Over this range, blood LDL-cholesterol is decreased by 37.1% to 51.7% (Summary of findings table 1). The slope of dose-related effects on cholesterol and LDL-cholesterol was similar for atorvastatin and rosuvastatin, but rosuvastatin is about three-fold more potent. Subgroup analyses suggested that the atorvastatin effect was greater in females than in males and was greater in non-familial than in familial hypercholesterolaemia. Risk of bias for the outcome of withdrawals due to adverse effects (WDAEs) was high, but the mostly unclear risk of bias was judged unlikely to affect lipid measurements. Withdrawals due to adverse effects were not statistically significantly different between atorvastatin and placebo groups in these short-term trials (risk ratio 0.98, 95% confidence interval 0.68 to 1.40).

AUTHORS' CONCLUSIONS

This update resulted in no change to the main conclusions of the review but significantly increases the strength of the evidence. Studies show that atorvastatin decreases blood total cholesterol and LDL-cholesterol in a linear dose-related manner over the commonly prescribed dose range. New findings include that atorvastatin is more than three-fold less potent than rosuvastatin, and that the cholesterol-lowering effects of atorvastatin are greater in females than in males and greater in non-familial than in familial hypercholesterolaemia. This review update does not provide a good estimate of the incidence of harms associated with atorvastatin because included trials were of short duration and adverse effects were not reported in 37% of placebo-controlled trials.

Pharmacogenomics in the development and characterization of atheroprotective drugs

Atherosclerosis is the main cause of cardiovascular disease (CVD) and can lead to stroke, myocardial infarction, and death. The clinically available atheroprotective drugs aim mainly at reducing the levels of circulating low-density lipoprotein (LDL), increasing high-density lipoprotein (HDL), and attenuating inflammation. However, the cardiovascular risk remains high, along with morbidity, mortality, and incidence of adverse drug events. Pharmacogenomics is increasingly contributing towards the characterization of existing atheroprotective drugs, the evaluation of novel ones, and the identification of promising, unexplored therapeutic targets, at the global molecular pathway level. This chapter presents highlights of pharmacogenomics investigations and discoveries that have contributed towards the elucidation of pharmacological atheroprotection, while opening the way to new therapeutic approaches.

Lipid lowering efficacy of atorvastatin

BACKGROUND

Atorvastatin is one of the most widely prescribed drugs and the most widely prescribed statin in the world. It is therefore important to know the dose-related magnitude of effect of atorvastatin on blood lipids.

OBJECTIVES

To quantify the dose-related effects of atorvastatin on blood lipids and withdrawals due to adverse effects (WDAE).

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL) on The Cochrane Library Issue 4, 2011, MEDLINE (1966 to November 2011), EMBASE (1980 to November 2011), ISI Web of Science (1899 to November 2011) and BIOSIS Previews (1969 to November 2011). No language restrictions were applied.

SELECTION CRITERIA

Randomised controlled and uncontrolled before-and-after trials evaluating the dose response of different fixed doses of atorvastatin on blood lipids over a duration of 3 to 12 weeks.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed trial quality and extracted data. WDAE information was collected from the placebo-controlled trials.

MAIN RESULTS

Two hundred fifty-four trials evaluated the dose-related efficacy of atorvastatin in 33,505 participants. Log dose-response data revealed linear dose-related effects on blood total cholesterol, low-density lipoprotein (LDL)-cholesterol and triglycerides. Combining all the trials using the generic inverse variance fixed-effect model for doses of 10 to 80 mg/day resulted in decreases of 36% to 53% for LDL-cholesterol. There was no significant dose-related effects of atorvastatin on blood high-density lipoprotein (HDL)-cholesterol. WDAE were not statistically different between atorvastatin and placebo for these short-term trials (risk ratio 0.99; 95% confidence interval 0.68 to 1.45).

AUTHORS' CONCLUSIONS

Blood total cholesterol, LDL-cholesterol and triglyceride lowering effect of atorvastatin was dependent on dose. Log dose-response data was linear over the commonly prescribed dose range. Manufacturer-recommended atorvastatin doses of 10 to 80 mg/day resulted in 36% to 53% decreases of LDL-cholesterol. The review did not provide a good estimate of the incidence of harms associated with atorvastatin because of the short duration of the trials and the lack of reporting of adverse effects in 37% of the placebo-controlled trials.

Regulation of gene expression in atherosclerosis: insights from microarray studies in monocytes/macrophages

Atherosclerosis is a pathological phenomenon in which the walls of large arteries thicken and lose elasticity as a result of the growth of atheromatous lesions. It is a complex, multifactorial disease that involves several cell types and various pathobiological processes. Its genetic basis has not yet been deciphered, but it is related to complex multigene patterns influenced by environmental interactions. In this review, we focus specifically on the application of microarrays to atherosclerosis research using monocytes and monocyte-derived macrophages, as these are key cells in all phases of atherosclerosis, from the formation of foam cells to the destabilization and rupture of the atherosclerotic plaque. These studies have provided relevant information on genes involved in atherosclerosis development, contributing to our understanding of the molecular mechanisms that underlie this complex disease.

Identification of factors contributing to variability in a blood-based gene expression test

BACKGROUND

Corus CAD is a clinically validated test based on age, sex, and expression levels of 23 genes in whole blood that provides a score (1-40 points) proportional to the likelihood of obstructive coronary disease. Clinical laboratory process variability was examined using whole blood controls across a 24 month period: Intra-batch variability was assessed using sample replicates; inter-batch variability examined as a function of laboratory personnel, equipment, and reagent lots.

METHODS/RESULTS

To assess intra-batch variability, five batches of 132 whole blood controls were processed; inter-batch variability was estimated using 895 whole blood control samples. ANOVA was used to examine inter-batch variability at 4 process steps: RNA extraction, cDNA synthesis, cDNA addition to assay plates, and qRT-PCR. Operator, machine, and reagent lots were assessed as variables for all stages if possible, for a total of 11 variables. Intra- and inter-batch variations were estimated to be 0.092 and 0.059 Cp units respectively (SD); total laboratory variation was estimated to be 0.11 Cp units (SD). In a regression model including all 11 laboratory variables, assay plate lot and cDNA kit lot contributed the most to variability (p = 0.045; 0.009 respectively). Overall, reagent lots for RNA extraction, cDNA synthesis, and qRT-PCR contributed the most to inter-batch variance (52.3%), followed by operators and machines (18.9% and 9.2% respectively), leaving 19.6% of the variance unexplained.

CONCLUSION

Intra-batch variability inherent to the PCR process contributed the most to the overall variability in the study while reagent lot showed the largest contribution to inter-batch variability.

Differentially expressed genes in human peripheral blood as potential markers for statin response

There is a considerable inter-individual variation in response to statin therapy and one third of patients do not meet their treatment goals. We aimed to identify differentially expressed genes that might be involved in the effects of statin treatment and to suggest potential markers to guide statin therapy. Forty-six healthy Korean subjects received atorvastatin; their whole-genome expression profiles in peripheral blood were analyzed before and after atorvastatin administration in relation with changes in lipid profiles. The expression patterns of the differentially expressed genes were also compared with the data of familial hypercholesterolemia (FH) patients and controls. Pairwise comparison analyses revealed differentially expressed genes involved in diverse biological processes and molecular functions related with immune responses. Atorvastain mainly affected antigen binding, immune or inflammatory response including interleukin pathways. Similar expression patterns of the genes were observed in patients with FH and controls. The Charcol-Leyden crystal (CLC), CCR2, CX3CR1, LRRN3, FOS, LDLR, HLA-DRB1, ERMN, and TCN1 genes were significantly associated with cholesterol levels or statin response. Interestingly, the CLC gene, which was significantly altered by atorvastatin administration and differentially expressed between FH patients and controls, showed much bigger change in high-responsive group than in low-responsive group. We identified differentially expressed genes that might be involved in mechanisms underlying the known pleiotropic effects of atorvastatin, baseline cholesterol levels, and drug response. Our findings suggest CLC as a new candidate marker for statin response, and further validation is needed.

Tissue factor pathway inhibitor 2 is induced by thrombin in human macrophages

Tissue factor pathway inhibitor 2 (TFPI2) is a serine protease inhibitor critical for the regulation of extracellular matrix remodeling and atherosclerotic plaque stability. Previously, we demonstrated that TFPI2 expression is increased in monocytes from patients with familial combined hyperlipidemia (FCH). To gain insight into the molecular mechanisms responsible for this upregulation, we examined TFPI2 expression in THP-1 macrophages exposed to lipoproteins and thrombin. Our results showed that TFPI2 expression was not affected by treatment with very low density lipoproteins (VLDL), but was induced by thrombin (10 U/ml) in THP-1 (1.9-fold increase, p<0.001) and human monocyte-derived macrophages (2.3-fold increase, p<0.005). The specificity of the inductive effect was demonstrated by preincubation with the thrombin inhibitors hirudin and PPACK, which ablated thrombin effects. TFPI2 induction was prevented by pre-incubation with MEK1/2 and JNK inhibitors, but not by the EGF receptor antagonist AG1478. In the presence of parthenolide, an inhibitor of NFκB, but not of SR-11302, a selective AP-1 inhibitor, thrombin-mediated TFPI2 induction was blunted. Our results also show that thrombin treatment increased ERK1/2, JNK and IκBα phosphorylation. Finally, we ruled out the possibility that TFPI2 induction by thrombin was mediated by COX-2, as preincubation with a selective COX-2 inhibitor did not prevent the inductive effect. In conclusion, thrombin induces TFPI2 expression by a mechanism involving ERK1/2 and JNK phosphorylation, leading finally to NFkB activation. In the context of atherosclerosis, thrombin-induced macrophage TFPI2 expression could represent a means of avoiding excessive activation of matrix metalloproteases at sites of inflammation.

Genetic and environmental pathways to complex diseases

BACKGROUND

Pathogenesis of complex diseases involves the integration of genetic and environmental factors over time, making it particularly difficult to tease apart relationships between phenotype, genotype, and environmental factors using traditional experimental approaches.

RESULTS

Using gene-centered databases, we have developed a network of complex diseases and environmental factors through the identification of key molecular pathways associated with both genetic and environmental contributions. Comparison with known chemical disease relationships and analysis of transcriptional regulation from gene expression datasets for several environmental factors and phenotypes clustered in a metabolic syndrome and neuropsychiatric subnetwork supports our network hypotheses. This analysis identifies natural and synthetic retinoids, antipsychotic medications, Omega 3 fatty acids, and pyrethroid pesticides as potential environmental modulators of metabolic syndrome phenotypes through PPAR and adipocytokine signaling and organophosphate pesticides as potential environmental modulators of neuropsychiatric phenotypes.

CONCLUSION

Identification of key regulatory pathways that integrate genetic and environmental modulators define disease associated targets that will allow for efficient screening of large numbers of environmental factors, screening that could set priorities for further research and guide public health decisions.