Elizabeth Theusch

HNRNPA1 regulates HMGCR alternative splicing and modulates cellular cholesterol metabolism

3-hydroxy-3-methylglutaryl-Coenzyme A reductase (HMGCR) encodes the rate-limiting enzyme in the cholesterol biosynthesis pathway and is inhibited by statins, a class of cholesterol-lowering drugs. Expression of an alternatively spliced HMGCR transcript lacking exon 13, HMGCR13(-), has been implicated in the variation of plasma LDL-cholesterol (LDL-C) and is the single most informative molecular marker of LDL-C response to statins. Given the physiological importance of this transcript, our goal was to identify molecules that regulate HMGCR alternative splicing. We recently reported gene expression changes in 480 lymphoblastoid cell lines (LCLs) after in vitro simvastatin treatment, and identified a number of statin-responsive genes involved in mRNA splicing. Heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1) was chosen for follow-up since rs3846662, an HMGCR SNP that regulates exon 13 skipping, was predicted to alter an HNRNPA1 binding motif. Here, we not only demonstrate that rs3846662 modulates HNRNPA1 binding, but also that sterol depletion of human hepatoma cell lines reduced HNRNPA1 mRNA levels, an effect that was reversed with sterol add-back. Overexpression of HNRNPA1 increased the ratio of HMGCR13(-) to total HMGCR transcripts by both directly increasing exon 13 skipping in an allele-related manner and specifically stabilizing the HMGCR13(-) transcript. Importantly, HNRNPA1 overexpression also diminished HMGCR enzyme activity, enhanced LDL-C uptake and increased cellular apolipoprotein B (APOB). rs1920045, an SNP associated with HNRNPA1 exon 8 alternative splicing, was also associated with smaller statin-induced reduction in total cholesterol from two independent clinical trials. These results suggest that HNRNPA1 plays a role in the variation of cardiovascular disease risk and statin response.

RHOA Is a Modulator of the Cholesterol-Lowering Effects of Statin

Although statin drugs are generally efficacious for lowering plasma LDL-cholesterol levels, there is considerable variability in response. To identify candidate genes that may contribute to this variation, we used an unbiased genome-wide filter approach that was applied to 10,149 genes expressed in immortalized lymphoblastoid cell lines (LCLs) derived from 480 participants of the Cholesterol and Pharmacogenomics (CAP) clinical trial of simvastatin. The criteria for identification of candidates included genes whose statin-induced changes in expression were correlated with change in expression of HMGCR, a key regulator of cellular cholesterol metabolism and the target of statin inhibition. This analysis yielded 45 genes, from which RHOA was selected for follow-up because it has been found to participate in mediating the pleiotropic but not the lipid-lowering effects of statin treatment. RHOA knock-down in hepatoma cell lines reduced HMGCR, LDLR, and SREBF2 mRNA expression and increased intracellular cholesterol ester content as well as apolipoprotein B (APOB) concentrations in the conditioned media. Furthermore, inter-individual variation in statin-induced RHOA mRNA expression measured in vitro in CAP LCLs was correlated with the changes in plasma total cholesterol, LDL-cholesterol, and APOB induced by simvastatin treatment (40 mg/d for 6 wk) of the individuals from whom these cell lines were derived. Moreover, the minor allele of rs11716445, a SNP located in a novel cryptic RHOA exon, dramatically increased inclusion of the exon in RHOA transcripts during splicing and was associated with a smaller LDL-cholesterol reduction in response to statin treatment in 1,886 participants from the CAP and Pravastatin Inflamation and CRP Evaluation (PRINCE; pravastatin 40 mg/d) statin clinical trials. Thus, an unbiased filter approach based on transcriptome-wide profiling identified RHOA as a gene contributing to variation in LDL-cholesterol response to statin, illustrating the power of this approach for identifying candidate genes involved in drug response phenotypes.

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

BackgroundStatins 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.ResultsUsing 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.ConclusionsThese 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.

Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines

Variation in the expression level and activity of genes involved in drug disposition and action (‘pharmacogenes’) can affect drug response and toxicity, especially when in tissues of pharmacological importance. Previous studies have relied primarily on microarrays to understand gene expression differences, or have focused on a single tissue or small number of samples. The goal of this study was to use RNA-sequencing (RNA-seq) to determine the expression levels and alternative splicing of 389 Pharmacogenomics Research Network pharmacogenes across four tissues (liver, kidney, heart and adipose) and lymphoblastoid cell lines, which are used widely in pharmacogenomics studies. Analysis of RNA-seq data from 139 different individuals across the 5 tissues (20–45 individuals per tissue type) revealed substantial variation in both expression levels and splicing across samples and tissue types. Comparison with GTEx data yielded a consistent picture. This in-depth exploration also revealed 183 splicing events in pharmacogenes that were previously not annotated. Overall, this study serves as a rich resource for the research community to inform biomarker and drug discovery and use.

Individual and combined associations of genetic variants in CYP3A4, CYP3A5, and SLCO1B1 with simvastatin and simvastatin acid plasma concentrations

Abstract: Our objective was to evaluate the associations of genetic variants affecting simvastatin (SV) and simvastatin acid (SVA) metabolism [the gene encoding cytochrome P450, family 3, subfamily A, polypeptide 4 (CYP3A4)*22 and the gene encoding cytochrome P450, family 3, subfamily A, polypeptide 5 (CYP3A5)*3] and transport [the gene encoding solute carrier organic anion transporter family member 1B1 (SLCO1B1) T521C] with 12-hour plasma SV and SVA concentrations. The variants were genotyped, and the concentrations were quantified by high performance liquid chromatography-tandem mass spectrometry in 646 participants of the Cholesterol and Pharmacogenetics clinical trial of 40 mg/d SV for 6 weeks. The genetic variants were tested for association with 12-hour plasma SV, SVA, or the SVA/SV ratio using general linear models. CYP3A5*3 was not significantly associated with 12-hour plasma SV or SVA concentration. CYP3A4*1/*22 participants had 58% higher 12-hour plasma SV concentration compared with CYP3A4*1/*1 participants (P = 0.006). SLCO1B1 521T/C and 521C/C participants had 71% (P < 0.001) and 248% (P < 0.001) higher 12-hour plasma SVA compared with SLCO1B1 521T/T participants, respectively. CYP3A4 and SLCO1B1 genotypes combined categorized participants into low (<1), intermediate (≈1), and high (>1) SVA/SV ratio groups (P = 0.001). In conclusion, CYP3A4*22 and SLCO1B1 521C were significantly associated with increased 12-hour plasma SV and SVA concentrations, respectively. CYP3A5*3 was not significantly associated with 12-hour plasma SV or SVA concentrations. The combination of CYP3A4*22 and SLCO1B1 521C was significantly associated with SVA/SV ratio, which may translate into different clinical SV risk/benefit profiles.

Ancestry and other genetic associations with plasma PCSK9 response to simvastatin

Objective Statins stimulate transcription of proprotein convertase subtilisin/kexin type 9 (PCSK9), a negative regulator of the low-density lipoprotein receptor, thus blunting the cholesterol-lowering effects of statin treatment. Although there is interindividual variation in PCSK9 statin response, little is known about ancestral and other genetic factors that could contribute to this variation. Methods We measured plasma PCSK9 levels before and after 6 weeks of treatment with 40 mg/day simvastatin in 901 participants of the Cholesterol and Pharmacogenetics clinical trial and tested phenotypic and genetic factors for correlation with PCSK9 statin response. Results Statin-induced changes in plasma low-density lipoprotein cholesterol, total cholesterol, and apolipoprotein B were all significantly correlated with statin-induced changes in PCSK9. A detailed examination of the associations of genetic ancestry with PCSK9 statin response revealed that Ashkenazi Jews had smaller statin-induced increases in PCSK9 levels than other self-reported Caucasians (P=0.016). Using genomewide association analysis, we found that the ‘G’ minor allele of rs13064411 in the WD repeat domain 52 (WDR52) gene was significantly associated with greater statin-induced increases in plasma PCSK9 in Caucasians (P=8.2×10–8) in the Cholesterol and Pharmacogenetics trial. Conclusion Overall, these results suggest that genetic ancestry and the rs13064411 genotype contribute to interindividual variation in PCSK9 statin response in Caucasians.

Human genetic variation in VAC14 regulates Salmonella invasion and typhoid fever through modulation of cholesterol

Significance Salmonella enterica serovar Typhi (S. Typhi) causes ∼20 million cases of typhoid fever every year. We carried out a genome-wide association study to identify genetic differences that correlate with the susceptibility of cells from hundreds of individuals to S. Typhi invasion. A SNP in VAC14 was associated with susceptibility to S. Typhi invasion and VAC14 expression. Cells mutated for VAC14 displayed increased S. Typhi docking due to increased plasma membrane cholesterol levels. The same SNP was associated with risk of typhoid fever in a Vietnamese population. Furthermore, treating zebrafish with a cholesterol-lowering drug reduced their susceptibility to S. Typhi infection. Therefore, this work demonstrates the power of coupling multiple genetic association studies with mechanistic dissection for understanding infectious disease susceptibility. Risk, severity, and outcome of infection depend on the interplay of pathogen virulence and host susceptibility. Systematic identification of genetic susceptibility to infection is being undertaken through genome-wide association studies, but how to expeditiously move from genetic differences to functional mechanisms is unclear. Here, we use genetic association of molecular, cellular, and human disease traits and experimental validation to demonstrate that genetic variation affects expression of VAC14, a phosphoinositide-regulating protein, to influence susceptibility to Salmonella enterica serovar Typhi (S. Typhi) infection. Decreased VAC14 expression increased plasma membrane cholesterol, facilitating Salmonella docking and invasion. This increased susceptibility at the cellular level manifests as increased susceptibility to typhoid fever in a Vietnamese population. Furthermore, treating zebrafish with a cholesterol-lowering agent, ezetimibe, reduced susceptibility to S. Typhi. Thus, coupling multiple genetic association studies with mechanistic dissection revealed how VAC14 regulates Salmonella invasion and typhoid fever susceptibility and may open doors to new prophylactic/therapeutic approaches.

Transmembrane Protein 55B Is a Novel Regulator of Cellular Cholesterol Metabolism

Objective— Interindividual variation in pathways affecting cellular cholesterol metabolism can influence levels of plasma cholesterol, a well-established risk factor for cardiovascular disease. Inherent variation among immortalized lymphoblastoid cell lines from different donors can be leveraged to discover novel genes that modulate cellular cholesterol metabolism. The objective of this study was to identify novel genes that regulate cholesterol metabolism by testing for evidence of correlated gene expression with cellular levels of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) mRNA, a marker for cellular cholesterol homeostasis, in a large panel of lymphoblastoid cell lines. Approach and Results— Expression array profiling was performed on 480 lymphoblastoid cell lines established from participants of the Cholesterol and Pharmacogenetics (CAP) statin clinical trial, and transcripts were tested for evidence of correlated expression with HMGCR as a marker of intracellular cholesterol homeostasis. Of these, transmembrane protein 55b (TMEM55B) showed the strongest correlation (r=0.29; P=4.0E−08) of all genes not previously implicated in cholesterol metabolism and was found to be sterol regulated. TMEM55B knockdown in human hepatoma cell lines promoted the decay rate of the low-density lipoprotein receptor, reduced cell surface low-density lipoprotein receptor protein, impaired low-density lipoprotein uptake, and reduced intracellular cholesterol. Conclusions— Here, we report identification of TMEM55B as a novel regulator of cellular cholesterol metabolism through the combination of gene expression profiling and functional studies. The findings highlight the value of an integrated genomic approach for identifying genes that influence cholesterol homeostasis.

Statin-induced expression change of INSIG1 in lymphoblastoid cell lines correlates with plasma triglyceride statin response in a sex-specific manner

Statins are widely prescribed to lower plasma low-density lipoprotein (LDL) cholesterol levels. They also modestly reduce plasma triglyceride (TG), an independent cardiovascular disease risk factor, in most people. The mechanism and inter-individual variability of TG statin response is poorly understood. We measured statin-induced gene expression changes in lymphoblastoid cell lines derived from 150 participants of a simvastatin clinical trial and identified 23 genes (false discovery rate, FDR=15%) with expression changes correlated with plasma TG response. The correlation of insulin-induced gene 1 (INSIG1) expression changes with TG response (rho=0.32, q=0.11) was driven by men (interaction P=0.0055). rs73161338 was associated with INSIG1 expression changes (P=5.4 × 10−5) and TG response in two statin clinical trials (P=0.0048), predominantly in men. A combined model including INSIG1 expression level and splicing changes accounted for 29.5% of plasma TG statin response variance in men (P=5.6 × 10−6). Our results suggest that INSIG1 variation may contribute to statin-induced changes in plasma TG in a sex-specific manner.

RP1-13D10.2 Is a Novel Modulator of Statin-Induced Changes in Cholesterol

Background— Numerous genetic contributors to cardiovascular disease risk have been identified through genome-wide association studies; however, identifying the molecular mechanism underlying these associations is not straightforward. The Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) trial of rosuvastatin users identified a sub–genome-wide association of rs6924995, a single-nucleotide polymorphism ≈10 kb downstream of myosin regulatory light chain interacting protein (MYLIP, aka IDOL and inducible degrader of low-density lipoprotein receptor [LDLR]), with LDL cholesterol statin response. Interestingly, although this signal was initially attributed to MYLIP, rs6924995 lies within RP1-13D10.2, an uncharacterized long noncoding RNA. Methods and Results— Using simvastatin and sham incubated lymphoblastoid cell lines from participants of the Cholesterol and Pharmacogenetics (CAP) simvastatin clinical trial, we found that statin-induced change in RP1-13D10.2 levels differed between cell lines from the tails of the white and black low-density lipoprotein cholesterol response distributions, whereas no difference in MYLIP was observed. RP1-13D10.2 overexpression in Huh7 and HepG2 increased LDLR transcript levels, increased LDL uptake, and decreased media levels of apolipoprotein B. In addition, we found a trend of slight differences in the effects of RP1-13D10.2 overexpression on LDLR transcript levels between hepatoma cells transfected with the rs6924995 A versus G allele and a suggestion of an association between rs6924995 and RP1-10D13.2 expression levels in the CAP lymphoblastoid cell lines. Finally, RP1-13D10.2 expression levels seem to be sterol regulated, consistent with its potential role as a novel lipid regulator. Conclusions— RP1-13D10.2 is a long noncoding RNA that regulates LDLR and may contribute to low-density lipoprotein cholesterol response to statin treatment. These findings highlight the potential role of noncoding RNAs as determinants of interindividual variation in drug response.