Meta-GWAS of PCSK9 levels detects two novel loci at APOB and TM6SF2.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player in lipid metabolism, as it degrades low-density lipoprotein (LDL) receptors from hepatic cell membranes. So far, only variants of the PCSK9 gene locus were found to be associated with PCSK9 levels. Here we aimed to identify novel genetic loci that regulate PCSK9 levels and how they relate to other lipid traits. Additionally, we investigated to what extend the causal effect of PCSK9 on coronary artery disease (CAD) is mediated by low-density lipoprotein-cholesterol (LDL-C). METHODS AND RESULTS: We performed a genome-wide association study meta-analysis of PCSK9 levels in up to 12 721 samples of European ancestry. The estimated heritability was 10.3%, which increased to 12.6% using only samples from patients without statin treatment. We successfully replicated the known PCSK9 hit consisting of three independent signals. Interestingly, in a study of 300 African Americans, we confirmed the locus with a different PCSK9 variant. Beyond PCSK9, our meta-analysis detected three novel loci with genome-wide significance. Co-localization analysis with cis-eQTLs and lipid traits revealed biologically plausible candidate genes at two of them: APOB and TM6SF2. In a bivariate Mendelian Randomization analysis, we detected a strong effect of PCSK9 on LDL-C, but not vice versa. LDL-C mediated 63% of the total causal effect of PCSK9 on CAD. CONCLUSION: Our study identified novel genetic loci with plausible candidate genes affecting PCSK9 levels. Ethnic heterogeneity was observed at the PCSK9 locus itself. Although the causal effect of PCSK9 on CAD is mainly mediated by LDL-C, an independent direct effect also occurs.

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.

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.

Statin-induced LDL cholesterol response and type 2 diabetes: a bidirectional two-sample Mendelian randomization study.

It remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, nmax = 40,914) and DIAGRAM (nmax = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (rgenetic = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.

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.

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.

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.

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.

TOMM40 and TOMM22 of the Translocase Outer Mitochondrial Membrane Complex rescue statin-impaired mitochondrial dynamics, morphology, and mitophagy in skeletal myotubes.

Background: Statins are the drugs most commonly used for lowering plasma low-density lipoprotein (LDL) cholesterol levels and reducing cardiovascular disease risk. Although generally well tolerated, statins can induce myopathy, a major cause of non-adherence to treatment. Impaired mitochondrial function has been implicated as a cause of statin-induced myopathy, but the underlying mechanism remains unclear. We have shown that simvastatin downregulates transcription of TOMM40 and TOMM22 , genes that encode major subunits of the translocase of outer mitochondrial membrane (TOM) complex which is responsible for importing nuclear-encoded proteins and maintaining mitochondrial function. We therefore investigated the role of TOMM40 and TOMM22 in mediating statin effects on mitochondrial function, dynamics, and mitophagy. Methods: Cellular and biochemical assays and transmission electron microscopy were used to investigate effects of simvastatin and TOMM40 and TOMM22 expression on measures of mitochondrial function and dynamics in C2C12 and primary human skeletal cell myotubes. Results: Knockdown of TOMM40 and TOMM22 in skeletal cell myotubes impaired mitochondrial oxidative function, increased production of mitochondrial superoxide, reduced mitochondrial cholesterol and CoQ levels, disrupted mitochondrial dynamics and morphology, and increased mitophagy, with similar effects resulting from simvastatin treatment. Overexpression of TOMM40 and TOMM22 in simvastatin-treated muscle cells rescued statin effects on mitochondrial dynamics, but not on mitochondrial function or cholesterol and CoQ levels. Moreover, overexpression of these genes resulted in an increase in number and density of cellular mitochondria. Conclusion: These results confirm that TOMM40 and TOMM22 are central in regulating mitochondrial homeostasis and demonstrate that downregulation of these genes by statin treatment mediates disruption of mitochondrial dynamics, morphology, and mitophagy, effects that may contribute to statin-induced myopathy.

Participant-derived cell line transcriptomic analyses and mouse studies reveal a role for ZNF335 in plasma cholesterol statin response.

Background: Statins lower circulating low-density lipoprotein cholesterol (LDLC) levels and reduce cardiovascular disease risk. Though highly efficacious in general, there is considerable inter-individual variation in statin efficacy that remains largely unexplained. Methods: To identify novel genes that may modulate statin-induced LDLC lowering, we used RNA-sequencing data from 426 control- and 2 µM simvastatin-treated lymphoblastoid cell lines (LCLs) derived from European and African American ancestry participants of the Cholesterol and Pharmacogenetics (CAP) 40 mg/day 6-week simvastatin clinical trial (ClinicalTrials.gov Identifier: NCT00451828). We correlated statin-induced changes in LCL gene expression with plasma LDLC statin response in the corresponding CAP participants. For the most correlated gene identified (ZNF335), we followed up in vivo by comparing plasma cholesterol levels, lipoprotein profiles, and lipid statin response between wild-type mice and carriers of a hypomorphic (partial loss of function) missense mutation in Zfp335 (the mouse homolog of ZNF335). Results: The statin-induced expression changes of 147 human LCL genes were significantly correlated to the plasma LDLC statin responses of the corresponding CAP participants in vivo (FDR=5%). The two genes with the strongest correlations were zinc finger protein 335 (ZNF335 aka NIF-1, rho=0.237, FDR-adj p=0.0085) and CCR4-NOT transcription complex subunit 3 (CNOT3, rho=0.233, FDR-adj p=0.0085). Chow-fed mice carrying a hypomorphic missense (R1092W; aka bloto) mutation in Zfp335 had significantly lower non-HDL cholesterol levels than wild type C57BL/6J mice in a sex combined model (p=0.04). Furthermore, male (but not female) mice carrying the Zfp335R1092W allele had significantly lower total and HDL cholesterol levels than wild-type mice. In a separate experiment, wild-type mice fed a control diet for 4 weeks and a matched simvastatin diet for an additional 4 weeks had significant statin-induced reductions in non-HDLC (-43±18% and -23±19% for males and females, respectively). Wild-type male (but not female) mice experienced significant reductions in plasma LDL particle concentrations, while male mice carrying Zfp335R1092W allele(s) exhibited a significantly blunted LDL statin response. Conclusions: Our in vitro and in vivo studies identified ZNF335 as a novel modulator of plasma cholesterol levels and statin response, suggesting that variation in ZNF335 activity could contribute to inter-individual differences in statin clinical efficacy.

Genome-wide study of families with absolute pitch reveals linkage to 8q24.21 and locus heterogeneity.

Absolute pitch (AP) is the rare ability to instantaneously recognize and label tones with their musical note names without using a reference pitch for comparison. The etiology of AP is complex. Prior studies have implicated both genetic and environmental factors in its genesis, yet the molecular basis for AP remains unknown. To locate regions of the human genome that may harbor AP-predisposing genetic variants, we performed a genome-wide linkage study on 73 multiplex AP families by genotyping them with 6090 SNP markers. Nonparametric multipoint linkage analyses were conducted, and the strongest evidence for linkage was observed on chromosome 8q24.21 in the subset of 45 families with European ancestry (exponential LOD score = 3.464, empirical genome-wide p = 0.03). Other regions with suggestive LOD scores included chromosomes 7q22.3, 8q21.11, and 9p21.3. Of these four regions, only the 7q22.3 linkage peak was also evident when 19 families with East Asian ancestry were analyzed separately. Though only one of these regions has yet reached statistical significance individually, we detected a larger number of independent linkage peaks than expected by chance overall, indicating that AP is genetically heterogeneous.

Absolute pitch twin study and segregation analysis.

Absolute pitch is a rare pitch-naming ability with unknown etiology. Some scientists maintain that its manifestation depends solely on environmental factors, while others suggest that genetic factors contribute to it. We sought to further investigate the hypothesis that genetic factors support the acquisition of absolute pitch and to better elucidate the inheritance pattern of this trait. To this end, we conducted a twin study and a segregation analysis using data collected from a large population of absolute pitch possessors. The casewise concordance rate of 14 monozygotic twin pairs, 78.6%, was significantly different from that of 31 dizygotic twin pairs, 45.2%, assuming single ascertainment (x(2) = 5.57, 1 df, p = .018), supporting a role for genetics in the development of absolute pitch. Segregation analysis of 1463 families, assuming single ascertainment, produced a segregation ratio p(D) = .089 with SEp(D) = 0.006. Unlike an earlier segregation analysis on a small number of absolute pitch probands from musically educated families, our study indicates that absolute pitch is not inherited in a simple Mendelian fashion. Based on these data, absolute pitch is likely genetically heterogeneous, with environmental, epigenetic, and stochastic factors also perhaps contributing to its genesis. These findings are in agreement with the results of our recent linkage analysis.

Identifying genetic modulators of statin response using subject-derived lymphoblastoid cell lines.

Although statins (3-hydroxy-3-methylglutaryl-CoA reductase inhibitors) have proven effective in reducing plasma low-density lipoprotein levels and risk of cardiovascular disease, their lipid lowering efficacy is highly variable among individuals. Furthermore, statin treatment carries a small but significant risk of adverse effects, most notably myopathy and new onset diabetes. Hence, identification of biomarkers for predicting patients who would most likely benefit from statin treatment without incurring increased risk of adverse effects can have a significant public health impact. In this review, we discuss the rationale for the use of subject-derived lymphoblastoid cell lines in studies of statin pharmacogenomics and describe a variety of approaches we have employed to identify novel genetic markers associated with interindividual variation in statin response.

A unified framework identifies new links between plasma lipids and diseases from electronic medical records across large-scale cohorts.

Plasma lipids are known heritable risk factors for cardiovascular disease, but increasing evidence also supports shared genetics with diseases of other organ systems. We devised a comprehensive three-phase framework to identify new lipid-associated genes and study the relationships among lipids, genotypes, gene expression and hundreds of complex human diseases from the Electronic Medical Records and Genomics (347 traits) and the UK Biobank (549 traits). Aside from 67 new lipid-associated genes with strong replication, we found evidence for pleiotropic SNPs/genes between lipids and diseases across the phenome. These include discordant pleiotropy in the HLA region between lipids and multiple sclerosis and putative causal paths between triglycerides and gout, among several others. Our findings give insights into the genetic basis of the relationship between plasma lipids and diseases on a phenome-wide scale and can provide context for future prevention and treatment strategies.

The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction.

Background: The pharmacogenetic effect on cardiovascular disease reduction in response to statin treatment has only been assessed in small studies. In a pharmacogenetic genome wide association study (GWAS) analysis within the Genomic Investigation of Statin Therapy (GIST) consortium, we investigated whether genetic variation was associated with the response of statins on cardiovascular disease risk reduction. Methods: The investigated endpoint was incident myocardial infarction (MI) defined as coronary heart disease death and definite and suspect non-fatal MI. For imputed single nucleotide polymorphisms (SNPs), regression analysis was performed on expected allelic dosage and meta-analysed with a fixed-effects model, inverse variance weighted meta-analysis. All SNPs with p-values <5.0 × 10-4 in stage 1 GWAS meta-analysis were selected for further investigation in stage-2. As a secondary analysis, we extracted SNPs from the Stage-1 GWAS meta-analysis results based on predefined hypotheses to possibly modifying the effect of statin therapy on MI. Results: In stage-1 meta-analysis (eight studies, n = 10,769, 4,212 cases), we observed no genome-wide significant results (p < 5.0 × 10-8). A total of 144 genetic variants were followed-up in the second stage (three studies, n = 1,525, 180 cases). In the combined meta-analysis, no genome-wide significant hits were identified. Moreover, none of the look-ups of SNPs known to be associated with either CHD or with statin response to cholesterol levels reached Bonferroni level of significance within our stage-1 meta-analysis. Conclusion: This GWAS analysis did not provide evidence that genetic variation affects statin response on cardiovascular risk reduction. It does not appear likely that genetic testing for predicting effects of statins on clinical events will become a useful tool in clinical practice.