Investigating the Effects of Statins on Cellular Lipid Metabolism Using a Yeast Expression System

In humans, defects in lipid metabolism are associated with a number of severe diseases such as atherosclerosis, obesity and type II diabetes. Hypercholesterolemia is a primary risk factor for coronary artery disease, the major cause of premature deaths in developed countries. Statins are inhibitors of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR), the key enzyme of the sterol synthesis pathway. Since yeast Saccharomyces cerevisiae harbours many counterparts of mammalian enzymes involved in lipid-synthesizing pathways, conclusions drawn from research with this single cell eukaryotic organism can be readily applied to higher eukaryotes. Using a yeast strain with deletions of both HMG1 and HMG2 genes (i.e. completely devoid of HMGR activity) with introduced wild-type or mutant form of human HMGR (hHMGR) gene we investigated the effects of statins on the lipid metabolism of the cell. The relative quantification of mRNA demonstrated a different effect of simvastatin on the expression of the wild-type and mutated hHMGR gene. GC/MS analyses showed a significant decrease of sterols and enhanced conversion of squalene and sterol precursors into ergosterol. This was accompanied by the mobilization of ergosterol precursors localized in lipid particles in the form of steryl esters visualized by confocal microscopy. Changes in the level of ergosterol and its precursors in cells treated with simvastatin depend on the mutation in the hHMGR gene. HPLC/MS analyses indicated a reduced level of phospholipids not connected with the mevalonic acid pathway. We detected two significant phenomena. First, cells treated with simvastatin develop an adaptive response compensating the lower activity of HMGR. This includes enhanced conversion of sterol precursors into ergosterol, mobilization of steryl esters and increased expression of the hHMGR gene. Second, statins cause a substantial drop in the level of glycerophospholipids

Short-term fatty acid intervention elicits differential gene expression responses in adipose tissue from lean and overweight men

The goal of this study was to investigate the effect of a short-term nutritional intervention on gene expression in adipose tissue from lean and overweight subjects. Gene expression profiles were measured after consumption of an intervention spread (increased levels of polyunsaturated fatty acids, conjugated linoleic acid and medium chain triglycerides) and a control spread (40 g of fat daily) for 9 days. Adipose tissue gene expression profiles of lean and overweight subjects were distinctly different, mainly with respect to defense response and metabolism. The intervention resulted in lower expression of genes related to energy metabolism in lean subjects, whereas expression of inflammatory genes was down-regulated and expression of lipid metabolism genes was up-regulated in the majority of overweight subjects. Individual responses in overweight subjects were variable and these correlated better to waist–hip ratio and fat percentage than BMI

Genetic variants in the KIF6 region and coronary event reduction from statin therapy

A single nucleotide polymorphism (SNP) in KIF6, a member of the KIF9 family of kinesins, is associated with differential coronary event reduction from statin therapy in four randomized controlled trials; this SNP (rs20455) is also associated with the risk for coronary heart disease (CHD) in multiple prospective studies. We investigated whether other common SNPs in the KIF6 region were associated with event reduction from statin therapy. Of the 170 SNPs in the KIF6 region investigated in the Cholesterol and Recurrent Events trial (CARE), 28 were associated with differential event reduction from statin therapy (Pinteraction < 0.1 in Caucasians, adjusted for age and sex) and were further investigated in the Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis In Myocardial Infarction 22 (PROVE IT-TIMI22) and West of Scotland Coronary Prevention Study (WOSCOPS). These analyses revealed that two SNPs (rs9462535 and rs9471077), in addition to rs20455, were associated with event reduction from statin therapy (Pinteraction < 0.1 in each of the three studies). The relative risk reduction ranged from 37 to 50% (P < 0.01) in carriers of the minor alleles of these SNPs and from −4 to 13% (P > 0.4) in non-carriers. These three SNPs are in high linkage disequilibrium with one another (r2 > 0.84). Functional studies of these variants may help to understand the role of KIF6 in the pathogenesis of CHD and differential response to statin therapy

A mouse model of sitosterolemia: absence of Abcg8/sterolin-2 results in failure to secrete biliary cholesterol

BACKGROUND: Mutations in either of two genes comprising the STSL locus, ATP-binding cassette (ABC)-transporters ABCG5 (encoding sterolin-1) and ABCG8 (encoding sterolin-2), result in sitosterolemia, a rare autosomal recessive disorder of sterol trafficking characterized by increased plasma plant sterol levels. Based upon the genetics of sitosterolemia, ABCG5/sterolin-1 and ABCG8/sterolin-2 are hypothesized to function as obligate heterodimers. No phenotypic difference has yet been described in humans with complete defects in either ABCG5 or ABCG8. These proteins, based upon the defects in humans, are responsible for regulating dietary sterol entry and biliary sterol secretion. METHODS: In order to mimic the human disease, we created, by a targeted disruption, a mouse model of sitosterolemia resulting in Abcg8/sterolin-2 deficiency alone. Homozygous knockout mice are viable and exhibit sitosterolemia. RESULTS: Mice deficient in Abcg8 have significantly increased plasma and tissue plant sterol levels (sitosterol and campesterol) consistent with sitosterolemia. Interestingly, Abcg5/sterolin-1 was expressed in both liver and intestine in Abcg8/sterolin-2 deficient mice and continued to show an apical expression. Remarkably, Abcg8 deficient mice had an impaired ability to secrete cholesterol into bile, but still maintained the ability to secrete sitosterol. We also report an intermediate phenotype in the heterozygous Abcg8+/- mice that are not sitosterolemic, but have a decreased level of biliary sterol secretion relative to wild-type mice. CONCLUSION: These data indicate that Abcg8/sterolin-2 is necessary for biliary sterol secretion and that loss of Abcg8/sterolin-2 has a more profound effect upon biliary cholesterol secretion than sitosterol. Since biliary sitosterol secretion is preserved, although not elevated in the sitosterolemic mice, this observation suggests that mechanisms other than by Abcg8/sterolin-2 may be responsible for its secretion into bile

Enteric Microbiome Metabolites Correlate with Response to Simvastatin Treatment

Although statins are widely prescribed medications, there remains considerable variability in therapeutic response. Genetics can explain only part of this variability. Metabolomics is a global biochemical approach that provides powerful tools for mapping pathways implicated in disease and in response to treatment. Metabolomics captures net interactions between genome, microbiome and the environment. In this study, we used a targeted GC-MS metabolomics platform to measure a panel of metabolites within cholesterol synthesis, dietary sterol absorption, and bile acid formation to determine metabolite signatures that may predict variation in statin LDL-C lowering efficacy. Measurements were performed in two subsets of the total study population in the Cholesterol and Pharmacogenetics (CAP) study: Full Range of Response (FR), and Good and Poor Responders (GPR) were 100 individuals randomly selected from across the entire range of LDL-C responses in CAP. GPR were 48 individuals, 24 each from the top and bottom 10% of the LDL-C response distribution matched for body mass index, race, and gender. We identified three secondary, bacterial-derived bile acids that contribute to predicting the magnitude of statin-induced LDL-C lowering in good responders. Bile acids and statins share transporters in the liver and intestine; we observed that increased plasma concentration of simvastatin positively correlates with higher levels of several secondary bile acids. Genetic analysis of these subjects identified associations between levels of seven bile acids and a single nucleotide polymorphism (SNP), rs4149056, in the gene encoding the organic anion transporter SLCO1B1. These findings, along with recently published results that the gut microbiome plays an important role in cardiovascular disease, indicate that interactions between genome, gut microbiome and environmental influences should be considered in the study and management of cardiovascular disease. Metabolic profiles could provide valuable information about treatment outcomes and could contribute to a more personalized approach to therapy

Genome-Wide Study of Gene Variants Associated with Differential Cardiovascular Event Reduction by Pravastatin Therapy

Statin therapy reduces the risk of coronary heart disease (CHD), however, the person-to-person variability in response to statin therapy is not well understood. We have investigated the effect of genetic variation on the reduction of CHD events by pravastatin. First, we conducted a genome-wide association study of 682 CHD cases from the Cholesterol and Recurrent Events (CARE) trial and 383 CHD cases from the West of Scotland Coronary Prevention Study (WOSCOPS), two randomized, placebo-controlled studies of pravastatin. In a combined case-only analysis, 79 single nucleotide polymorphisms (SNPs) were associated with differential CHD event reduction by pravastatin according to genotype (P<0.0001), and these SNPs were analyzed in a second stage that included cases as well as non-cases from CARE and WOSCOPS and patients from the PROspective Study of Pravastatin in the Elderly at Risk/PHArmacogenomic study of Statins in the Elderly at risk for cardiovascular disease (PROSPER/PHASE), a randomized placebo controlled study of pravastatin in the elderly. We found that one of these SNPs (rs13279522) was associated with differential CHD event reduction by pravastatin therapy in all 3 studies: P = 0.002 in CARE, P = 0.01 in WOSCOPS, P = 0.002 in PROSPER/PHASE. In a combined analysis of CARE, WOSCOPS, and PROSPER/PHASE, the hazard ratio for CHD when comparing pravastatin with placebo decreased by a factor of 0.63 (95% CI: 0.52 to 0.75) for each extra copy of the minor allele (P = 4.8×10−7). This SNP is located in DnaJ homolog subfamily C member 5B (DNAJC5B) and merits investigation in additional randomized studies of pravastatin and other statins

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance

Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Background: Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is important, but current approaches tackle average methylation within a genomic locus and are often limited to specific genomic regions. Results: We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict CpG site methylation levels using as features neighboring CpG site methylation levels and genomic distance, and co-localization with coding regions, CGIs, and regulatory elements from the ENCODE project, among others. Our approach achieves 91% -- 94% prediction accuracy of genome-wide methylation levels at single CpG site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs. Our classifier outperforms state-of-the-art methylation classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation status, CpG island status, co-localized DNase I hypersensitive sites, and specific transcription factor binding sites were found to be most predictive of methylation levels. Conclusions: Our observations of DNA methylation patterns led us to develop a classifier to predict site-specific methylation levels that achieves the best DNA methylation predictive accuracy to date. Furthermore, our method identified genomic features that interact with DNA methylation, elucidating mechanisms involved in DNA methylation modification and regulation, and linking different epigenetic processes

Prediction of LDL cholesterol response to statin using transcriptomic and genetic variation

BACKGROUND: Statins are widely prescribed for lowering LDL-cholesterol (LDLC) levels and risk of cardiovascular disease. There is, however, substantial inter-individual variation in the magnitude of statin-induced LDLC reduction. To date, analysis of individual DNA sequence variants has explained only a small proportion of this variability. The present study was aimed at assessing whether transcriptomic analyses could be used to identify additional genetic contributions to inter-individual differences in statin efficacy. RESULTS: Using expression array data from immortalized lymphoblastoid cell lines derived from 372 participants of the Cholesterol and Pharmacogenetics clinical trial, we identify 100 signature genes differentiating high versus low statin responders. A radial-basis support vector machine prediction model of these signature genes explains 12.3% of the variance in statin-mediated LDLC change. Addition of SNPs either associated with expression levels of the signature genes (eQTLs) or previously reported to be associated with statin response in genome-wide association studies results in a combined model that predicts 15.0% of the variance. Notably, a model of the signature gene associated eQTLs alone explains up to 17.2% of the variance in the tails of a separate subset of the Cholesterol and Pharmacogenetics population. Furthermore, using a support vector machine classification model, we classify the most extreme 15% of high and low responders with high accuracy. CONCLUSIONS: These results demonstrate that transcriptomic information can explain a substantial proportion of the variance in LDLC response to statin treatment, and suggest that this may provide a framework for identifying novel pathways that influence cholesterol metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0460-9) contains supplementary material, which is available to authorized users