Mechanism of the Regulation of Plasma Cholesterol Levels by PI(4,5)P2.

Elevated low-density lipoprotein (LDL) cholesterol (LDLc) is one of the most well-established risk factors for cardiovascular disease, while high levels of high-density lipoprotein (HDL) cholesterol (HDLc) have been associated with protection from cardiovascular disease. Cardiovascular disease remains one of the leading causes of death worldwide; thus it is important to understand mechanisms that impact LDLc and HDLc metabolism. In this chapter, we will discuss molecular processes by which phosphatidylinositol-(4,5)-bisphosphate, PI(4,5)P2, is thought to modulate LDLc or HDLc. Section 1 will provide an overview of cholesterol in the circulation, discussing processes that modulate the various forms of lipoproteins (LDL and HDL) carrying cholesterol. Section 2 will describe how a PI(4,5)P2 phosphatase, transmembrane protein 55B (TMEM55B), impacts circulating LDLc levels through its ability to regulate lysosomal decay of the low-density lipoprotein receptor (LDLR), the primary receptor for hepatic LDL uptake. Section 3 will discuss how PI(4,5)P2 interacts with apolipoprotein A-I (apoA1), the key apolipoprotein on HDL. In addition to direct mechanisms of PI(4,5)P2 action on circulating cholesterol, Sect. 4 will review how PI(4,5)P2 may indirectly impact LDLc and HDLc by affecting insulin action. Last, as cholesterol is controlled through intricate negative feedback loops, Sect. 5 will describe how PI(4,5)P2 is regulated by cholesterol.

Modest effect of statins on fasting glucose in a longitudinal electronic health record based cohort.

BACKGROUND: Prior studies of the glycemic effect of statins have been inconsistent. Also, most studies have only considered a short duration of statin use; the effect of long-term statin use on fasting glucose (FG) has not been well examined. The aim of this work is to investigate the effect of long-term statin exposure on FG levels. METHODS: Using electronic health record (EHR) data from a large and diverse longitudinal cohort, we defined long-term statin exposure in two ways: the cumulative years of statin use (cumulative supply) and the years' supply-weighted sum of doses (cumulative dose). Simvastatin, lovastatin, atorvastatin and pravastatin were included in the analysis. The relationship between statin exposure and FG was examined using linear regression with mixed effects modeling, comparing statin users before and after initiating statins and statin never-users. RESULTS: We examined 593,130 FG measurements from 87,151 individuals over a median follow up of 20 years. Of these, 42,678 were never-users and 44,473 were statin users with a total of 730,031 statin prescriptions. FG was positively associated with cumulative supply of statin but not comulative dose when both measures were in the same model. While statistically significant, the annual increase in FG attributable to statin exposure was modest at only 0.14 mg/dl, with only slight and non-significant differences among statin types. CONCLUSIONS: Elevation in FG level is associated with statin exposure, but the effect is modest. The results suggest that the risk of a clinically significant increase in FG attributable to long-term statin use is small for most individuals.

GeneFishing to reconstruct context specific portraits of biological processes.

Rapid advances in genomic technologies have led to a wealth of diverse data, from which novel discoveries can be gleaned through the application of robust statistical and computational methods. Here, we describe GeneFishing, a semisupervised computational approach to reconstruct context-specific portraits of biological processes by leveraging gene-gene coexpression information. GeneFishing incorporates multiple high-dimensional statistical ideas, including dimensionality reduction, clustering, subsampling, and results aggregation, to produce robust results. To illustrate the power of our method, we applied it using 21 genes involved in cholesterol metabolism as "bait" to "fish out" (or identify) genes not previously identified as being connected to cholesterol metabolism. Using simulation and real datasets, we found that the results obtained through GeneFishing were more interesting for our study than those provided by related gene prioritization methods. In particular, application of GeneFishing to the GTEx liver RNA sequencing (RNAseq) data not only reidentified many known cholesterol-related genes, but also pointed to glyoxalase I (GLO1) as a gene implicated in cholesterol metabolism. In a follow-up experiment, we found that GLO1 knockdown in human hepatoma cell lines increased levels of cellular cholesterol ester, validating a role for GLO1 in cholesterol metabolism. In addition, we performed pantissue analysis by applying GeneFishing on various tissues and identified many potential tissue-specific cholesterol metabolism-related genes. GeneFishing appears to be a powerful tool for identifying related components of complex biological systems and may be used across a wide range of applications.

Phosphatidylinositol-(4,5)-Bisphosphate Regulates Plasma Cholesterol Through LDL (Low-Density Lipoprotein) Receptor Lysosomal Degradation.

OBJECTIVE: TMEM55B (transmembrane protein 55B) is a phosphatidylinositol-(4,5)-bisphosphate (PI[4,5]P2) phosphatase that regulates cellular cholesterol, modulates LDLR (low-density lipoprotein receptor) decay, and lysosome function. We tested the effects of Tmem55b knockdown on plasma lipids in mice and assessed the roles of LDLR lysosomal degradation and change in (PI[4,5]P2) in mediating these effects. Approach and Results: Western diet-fed C57BL/6J mice were treated with antisense oligonucleotides against Tmem55b or a nontargeting control for 3 to 4 weeks. Hepatic Tmem55b transcript and protein levels were reduced by ≈70%, and plasma non-HDL (high-density lipoprotein) cholesterol was increased ≈1.8-fold (P<0.0001). Immunoblot analysis of fast protein liquid chromatography (FPLC) fractions revealed enrichment of ApoE-containing particles in the LDL size range. In contrast, Tmem55b knockdown had no effect on plasma cholesterol in Ldlr-/- mice. In primary hepatocytes and liver tissues from Tmem55b knockdown mice, there was decreased LDLR protein. In the hepatocytes, there was increased lysosome staining and increased LDLR-lysosome colocalization. Impairment of lysosome function (incubation with NH4Cl or knockdown of the lysosomal proteins LAMP1 or RAB7) abolished the effect of TMEM55B knockdown on LDLR in HepG2 (human hepatoma) cells. Colocalization of the recycling endosome marker RAB11 (Ras-related protein 11) with LDLR in HepG2 cells was reduced by 50% upon TMEM55B knockdown. Finally, knockdown increased hepatic PI(4,5)P2 levels in vivo and in HepG2 cells, while TMEM55B overexpression in vitro decreased PI(4,5)P2. TMEM55B knockdown decreased, whereas overexpression increased, LDL uptake in HepG2 cells. Notably, the TMEM55B overexpression effect was reversed by incubation with PI(4,5)P2. Conclusions: These findings indicate a role for TMEM55B in regulating plasma cholesterol levels by affecting PI(4,5)P2-mediated LDLR lysosomal degradation.

Genetic variants modulate gene expression statin response in human lymphoblastoid cell lines.

BACKGROUND: Statins are widely prescribed to lower plasma low-density lipoprotein cholesterol levels. Though statins reduce cardiovascular disease risk overall, statin efficacy varies, and some people experience adverse side effects while on statin treatment. Statins also have pleiotropic effects not directly related to their cholesterol-lowering properties, but the mechanisms are not well understood. To identify potential genetic modulators of clinical statin response, we looked for genetic variants associated with statin-induced changes in gene expression (differential eQTLs or deQTLs) in lymphoblastoid cell lines (LCLs) derived from participants of the Cholesterol and Pharmacogenetics (CAP) 40 mg/day 6-week simvastatin clinical trial. We exposed CAP LCLs to 2 µM simvastatin or control buffer for 24 h and performed polyA-selected, strand-specific RNA-seq. Statin-induced changes in gene expression from 259 European ancestry or 153 African American ancestry LCLs were adjusted for potential confounders prior to association with genotyped and imputed genetic variants within 1 Mb of each gene's transcription start site. RESULTS: From the deQTL meta-analysis of the two ancestral populations, we identified significant cis-deQTLs for 15 genes (TBC1D4, MDGA1, CHI3L2, OAS1, GATM, ASNSD1, GLUL, TDRD12, PPIP5K2, OAS3, SERPINB1, ANKDD1A, DTD1, CYFIP2, and GSDME), eight of which were significant in at least one of the ancestry subsets alone. We also conducted eQTL analyses of the endogenous (control-treated), statin-treated, and average of endogenous and statin-treated LCL gene expression levels. We identified eQTLs for approximately 6000 genes in each of the three (endogenous, statin-treated, and average) eQTL meta-analyses, with smaller numbers identified in the ancestral subsets alone. CONCLUSIONS: Several of the genes in which we identified deQTLs have functions in human health and disease, such as defense from viruses, glucose regulation, and response to chemotherapy drugs. This suggests that DNA variation may play a role in statin effects on various health outcomes. These findings could prove useful to future studies aiming to assess benefit versus risk of statin treatment using individual genetic profiles.

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

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.

Generalized correlation measure using count statistics for gene expression data with ordered samples.

Motivation: Capturing association patterns in gene expression levels under different conditions or time points is important for inferring gene regulatory interactions. In practice, temporal changes in gene expression may result in complex association patterns that require more sophisticated detection methods than simple correlation measures. For instance, the effect of regulation may lead to time-lagged associations and interactions local to a subset of samples. Furthermore, expression profiles of interest may not be aligned or directly comparable (e.g. gene expression profiles from two species). Results: We propose a count statistic for measuring association between pairs of gene expression profiles consisting of ordered samples (e.g. time-course), where correlation may only exist locally in subsequences separated by a position shift. The statistic is simple and fast to compute, and we illustrate its use in two applications. In a cross-species comparison of developmental gene expression levels, we show our method not only measures association of gene expressions between the two species, but also provides alignment between different developmental stages. In the second application, we applied our statistic to expression profiles from two distinct phenotypic conditions, where the samples in each profile are ordered by the associated phenotypic values. The detected associations can be useful in building correspondence between gene association networks under different phenotypes. On the theoretical side, we provide asymptotic distributions of the statistic for different regions of the parameter space and test its power on simulated data. Availability and implementation: The code used to perform the analysis is available as part of the Supplementary Material. Contact: msw@usc.edu or hhuang@stat.berkeley.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

A statin-dependent QTL for GATM expression is associated with statin-induced myopathy.

Statins are prescribed widely to lower plasma low-density lipoprotein (LDL) concentrations and cardiovascular disease risk and have been shown to have beneficial effects in a broad range of patients. However, statins are associated with an increased risk, albeit small, of clinical myopathy and type 2 diabetes. Despite evidence for substantial genetic influence on LDL concentrations, pharmacogenomic trials have failed to identify genetic variations with large effects on either statin efficacy or toxicity, and have produced little information regarding mechanisms that modulate statin response. Here we identify a downstream target of statin treatment by screening for the effects of in vitro statin exposure on genetic associations with gene expression levels in lymphoblastoid cell lines derived from 480 participants of a clinical trial of simvastatin treatment. This analysis identified six expression quantitative trait loci (eQTLs) that interacted with simvastatin exposure, including rs9806699, a cis-eQTL for the gene glycine amidinotransferase (GATM) that encodes the rate-limiting enzyme in creatine synthesis. We found this locus to be associated with incidence of statin-induced myotoxicity in two separate populations (meta-analysis odds ratio = 0.60). Furthermore, we found that GATM knockdown in hepatocyte-derived cell lines attenuated transcriptional response to sterol depletion, demonstrating that GATM may act as a functional link between statin-mediated lowering of cholesterol and susceptibility to statin-induced myopathy.

SUGP1 is a novel regulator of cholesterol metabolism.

A large haplotype on chromosome 19p13.11 tagged by rs10401969 in intron 8 of SURP and G patch domain containing 1 (SUGP1) is associated with coronary artery disease (CAD), plasma LDL cholesterol levels, and other energy metabolism phenotypes. Recent studies have suggested that TM6SF2 is the causal gene within the locus, but we postulated that this locus could harbor additional CAD risk genes, including the putative splicing factor SUGP1 Indeed, we found that rs10401969 regulates SUGP1 exon 8 skipping, causing non-sense-mediated mRNA decay. Hepatic Sugp1 overexpression in CD1 male mice increased plasma cholesterol levels 20-50%. In human hepatoma cell lines, SUGP1 knockdown stimulated 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) alternative splicing and decreased HMGCR transcript stability, thus reducing cholesterol synthesis and increasing LDL uptake. Our results strongly support a role for SUGP1 as a novel regulator of cholesterol metabolism and suggest that it contributes to the relationship between rs10401969 and plasma cholesterol.

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.

Statin-induced changes in gene expression in EBV-transformed and native B-cells.

Human lymphoblastoid cell lines (LCLs), generated through Epstein-Barr Virus (EBV) transformation of B-lymphocytes (B-cells), are a commonly used model system for identifying genetic influences on human diseases and on drug responses. We have previously used LCLs to examine the cellular effects of genetic variants that modulate the efficacy of statins, the most prescribed class of cholesterol-lowering drugs used for the prevention and treatment of cardiovascular disease. However, statin-induced gene expression differences observed in LCLs may be influenced by their transformation, and thus differ from those observed in native B-cells. To assess this possibility, we prepared LCLs and purified B-cells from the same donors, and compared mRNA profiles after 24 h incubation with simvastatin (2 µm) or sham buffer. Genes involved in cholesterol metabolism were similarly regulated between the two cell types under both the statin and sham-treated conditions, and the statin-induced changes were significantly correlated. Genes whose expression differed between the native and transformed cells were primarily implicated in cell cycle, apoptosis and alternative splicing. We found that ChIP-seq signals for MYC and EBNA2 (an EBV transcriptional co-activator) were significantly enriched in the promoters of genes up-regulated in the LCLs compared with the B-cells, and could be involved in the regulation of cell cycle and alternative splicing. Taken together, the results support the use of LCLs for the study of statin effects on cholesterol metabolism, but suggest that drug effects on cell cycle, apoptosis and alternative splicing may be affected by EBV transformation. This dataset is now uploaded to GEO at the accession number GSE51444.

A common polymorphism in the LDL receptor gene has multiple effects on LDL receptor function.

A common synonymous single nucleotide polymorphism in exon 12 of the low-density lipoprotein receptor (LDLR) gene, rs688, has been associated with increased plasma total and LDL cholesterol in several populations. Using immortalized lymphoblastoid cell lines from a healthy study population, we confirmed an earlier report that the minor allele of rs688 is associated with increased exon 12 alternative splicing (P < 0.05) and showed that this triggered nonsense-mediated decay (NMD) of the alternatively spliced LDLR mRNA. However, since synonymous single nucleotide polymorphisms may influence structure and function of the encoded proteins by co-translational effects, we sought to test whether rs688 was also functional in the full-length mRNA. In HepG2 cells expressing LDLR cDNA constructs engineered to contain the major or minor allele of rs688, the latter was associated with a smaller amount of LDLR protein at the cell surface (-21.8 ± 0.6%, P = 0.012), a higher amount in the lysosome fraction (+25.7 ± 0.3%, P = 0.037) and reduced uptake of fluorescently labeled LDL (-24.3 ± 0.7%, P < 0.01). Moreover, in the presence of exogenous proprotein convertase subtilisin/kexin type 9 (PCSK9), a protein that reduces cellular LDL uptake by promoting lysosomal degradation of LDLR, the minor allele resulted in reduced capacity of a PCSK9 monoclonal antibody to increase LDL uptake. These findings are consistent with the hypothesis that rs688, which is located in the ß-propeller region of LDLR, has effects on LDLR activity beyond its role in alternative splicing due to impairment of LDLR endosomal recycling and/or PCSK9 binding, processes in which the ß-propeller is critically involved.

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.

Individual and Combined Associations of Genetic Variants in CYP3A4, CYP3A5, and SLCO1B1 With Simvastatin and Simvastatin Acid Plasma Concentrations.

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.

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.

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.

CYP3A4*22 and CYP3A5*3 are associated with increased levels of plasma simvastatin concentrations in the cholesterol and pharmacogenetics study cohort.

OBJECTIVE: Simvastatin is primarily metabolized by CYP3A4. A combined CYP3A4/5 genotype classification, combining the decrease-of-function CYP3A4*22 and the loss-of-function CYP3A5*3, has recently been reported. We aim to determine whether CYP3A4*22 and CYP3A5*3 alleles are associated with increased plasma concentrations of simvastatin lactone (SV) and simvastatin acid (SVA). This is the first report evaluating associations between in-vivo simvastatin concentrations and CYP3A4*22, alone or in a combined CYP3A4/5 genotype-defined classification. PARTICIPANTS AND METHODS: Genotypes and simvastatin concentrations were determined for 830 participants (555 Whites and 275 African-Americans) in the Cholesterol and Pharmacogenomics clinical trial with 40 mg/day simvastatin for 6 weeks. Concentrations were determined in 12-h postdose samples. Associations between simvastatin concentrations and CYP3A4*22 and CYP3A5*3 alleles were tested separately and in a combined CYP3A4/5 genotype-defined classification system. RESULTS: In Whites, CYP3A4*22 carriers (n=42) had 14% higher SVA (P=0.04) and 20% higher SV (P=0.06) compared with noncarriers (n=513). CYP3A5*3 allele status was not significantly associated with SV or SVA in Whites. In African-Americans, CYP3A4*22 carriers (n=8) had 170% higher SV (P<0.01) than noncarriers (n=267), but no significant difference was detected for SVA. African-American CYP3A5 nonexpressors (n=28) had 33% higher SV (P=0.02) than CYP3A5 expressors (n=247), but no significant difference was detected for SVA. For both races, SV appeared to decrease across the rank-ordered combined CYP3A4/5 genotype-defined groups (poor, intermediate, and extensive metabolizers); however, similar trends were not observed for SVA. CONCLUSION: Genetic variation in CYP3A4 was associated with plasma simvastatin concentrations in self-reported Whites. Genetic variations in CYP3A4 and CYP3A5 were associated with plasma simvastatin concentrations in self-reported African-Americans.

Alternative splicing in the regulation of cholesterol homeostasis.

PURPOSE OF REVIEW: With the advent of whole-transcriptome sequencing, or RNA-seq, we now know that alternative splicing is a generalized phenomenon, with nearly all multiexonic genes subject to alternative splicing. In this review, we highlight recent studies examining alternative splicing as a modulator of cellular cholesterol homeostasis and as an underlying mechanism of dyslipidemia. RECENT FINDINGS: A number of key genes involved in cholesterol metabolism are known to undergo functionally relevant alternative splicing. Recently, we have identified coordinated changes in alternative splicing in multiple genes in response to alterations in cellular sterol content. We and others have implicated several splicing factors as regulators of lipid metabolism. Furthermore, a number of cis-acting human gene variants that modulate alternative splicing have been implicated in a variety of human metabolic diseases. SUMMARY: Alternative splicing is of importance in various types of genetically influenced dyslipidemias and in the regulation of cellular cholesterol metabolism.

X chromosome dosage drives statin-induced dysglycemia and mitochondrial dysfunction.

Statin drugs lower blood cholesterol levels for cardiovascular disease prevention. Women are more likely than men to experience adverse statin effects, particularly new-onset diabetes (NOD) and muscle weakness. Here we find that impaired glucose homeostasis and muscle weakness in statin-treated female mice are associated with reduced levels of the omega-3 fatty acid, docosahexaenoic acid (DHA), impaired redox tone, and reduced mitochondrial respiration. Statin adverse effects are prevented in females by administering fish oil as a source of DHA, by reducing dosage of the X chromosome or the Kdm5c gene, which escapes X chromosome inactivation and is normally expressed at higher levels in females than males. As seen in female mice, we find that women experience more severe reductions than men in DHA levels after statin administration, and that DHA levels are inversely correlated with glucose levels. Furthermore, induced pluripotent stem cells from women who developed NOD exhibit impaired mitochondrial function when treated with statin, whereas cells from men do not. These studies identify X chromosome dosage as a genetic risk factor for statin adverse effects and suggest DHA supplementation as a preventive co-therapy.

Development and application of an algorithm for statin-induced myopathy based on electronic health record-derived structured elements.

Objective: Considering the non-specific nature of muscle symptoms, studies of statin-induced myopathy (SIM) in electronic health records require accurate algortihms that can reliably identify true statin-related cases. However, prior algorithms have been constructed in study populations that preclude broad applicability. Here we developed and validated an algorithm that accurately defines SIM from electronic health records using structured data elements and conducted a study of determinants of SIM after applying the algorithm. Materials and Methods: We used electronic records from an integrated health care delivery system (including comprehensive pharmacy dispensing records) and defined SIM as elevated creatine kinase (CK) ≥4 x upper limit of normal. A diverse cohort of participants receiving a variety of statin regimens met the criteria for study inclusion. Results: We identified multiple conditions strongly associated with elevated CK independent of statin use. A 2-step algorithm was developed using these all-cause conditions as secondary causes (step 1) along with evidence of a statin regimen change (step 2). We identified 1,262 algorithm-derived statin-induced elevated CK cases. Gold standard SIM cases determined from manual chart reviews on a random subset of the all-cause elevated CK cases were used to validate the algorithm, which had a 76% sensitivity and 77% specificity for detecting the most certain cases. Pravastatin use was associated with a 2.18 odds (95% confidence interval 1.39-3.40, P=0.0007) for statin-induced CK elevation compared to lovastatin use after adjusting for dose and other factors. Conclusions: We have produced an efficient, easy-to-apply methodological tool that can improve the quality of future research on statin-induced myopathy.