Mendelian randomization to assess causal effects of blood lipids on coronary heart disease: lessons from the past and applications to the future

PURPOSE OF REVIEW: Mendelian randomization is a technique for judging the causal impact of a risk factor on an outcome from observational data using genetic variants. Although evidence from Mendelian randomization for the effects of major lipids and lipoproteins on coronary heart disease (CHD) risk has been around for a relatively long time, new data resources and new methodological approaches have given fresh insight into these relationships. The lessons from these analyses are likely to be highly relevant when it comes to lipidomics and the analyses of lipid subspecies whose biology is less well understood. RECENT FINDINGS: Although analyses of low-density lipoprotein cholesterol and lipoprotein(a) are unambiguous as there are genetic variants that associate exclusively with these risk factors and have well understood biology, analyses for triglycerides, and high-density lipoprotein cholesterol (HDL-c) are less clear. For example, a subset of genetic variants having specific associations with HDL-c are not associated with CHD risk, but an allele score including all variants associated with HDL-c does associate with CHD risk. Recently developed methods, such as multivariable Mendelian randomization, Mendelian randomization-Egger, and a weighted median method, suggest that the relationship between HDL-c and CHD risk is null, thus confirming experimental evidence. SUMMARY: Robust methods for Mendelian randomization have important utility for understanding the causal relationships between major lipids and CHD risk, and are likely to play an important role in judging the causal relevance of lipid subspecies and other metabolites measured on high-dimensional phenotyping platforms.S.B. is supported by the Wellcome Trust (grant number 100114)

Social Media and Cardiovascular Disease

Personality subtypes and systolic blood pressure (SBP) at night are recognized predictors of cardiovascular disease among social media users. Healthy individuals (n=88, 77% female, 31% African American) were surveyed using the Media and Technology Usage and Attitudes Scale (MTUAS). Demographics, 24-hours SBP, and personality types (e.g., introvert, extravert, and blended) were used. Personality (B= 5.37, t= 2.86, p=.005) significantly predicted elevated SBP in social media users (r2= .157, F(4, 72)=3.37, p=.014). There was a significant gradient increase in nighttime SBP by personality [introvert (M=100, SD=2.1), extrovert (M=102, SD=1.7), and blended (M=111, SD=4.4); all ps.<0.05]. Negative attitudes toward using technology (B= -5.093, t= -2.390, p= .019) also significantly predicted elevated overnight SBP. Higher anxiety/dependence with mobile phones (B=.400, t= 2.49, p=.019) significantly predicted elevated nighttime SBP [r2 = 0.342 F(4, 27) = 3.505, p=.020]. Our findings indicate that a blended personality type and anxiety due to separation from or dependence on a mobile phone or internet use elevate SBP at night, increasing the risk of developing cardiovascular disease

Genomics of lipid metabolism: Identifying novel causal pathways and new therapeutic targets for reducing risk of coronary heart disease

Coronary heart disease (CHD) is one of the leading causes of death worldwide; mortality rates are expected to continue to rise over the coming decades. Circulating lipids have been shown to be strongly and linearly associated with risk of CHD; however, despite considerable efforts to demonstrate causality, available evidence is conflicting and insufficient. Study of the underlying metabolic pathways implicated in the association between lipids and CHD would help to disentangle and elucidate these complex relationships. Direct infusion high-resolution mass spectrometry was performed on 5,551 participants from the Pakistan Risk of Myocardial Infarction Study; raw data were then processed, cleaned, and normalized to extract signals corresponding to 444 known lipid metabolites. Cross-correlations of lipid metabolites and their correlations with circulating lipids were examined, and the association of principal components of lipid metabolites with CHD risk factors was assessed. Genome-wide analyses were conducted to analyze the association of each lipid metabolite with 7.2 million genotyped and imputed single nucleotide polymorphisms (SNPs). Following conditional analyses on the lead SNP within each loci, we identified genome-wide significant associations at 148 independent metabolic loci and 54 novel loci. We then used functional annotation to link the variants associated with each metabolite to the most probable causal genes, and two-sample Mendelian randomization to examine the causal effect of lipid metabolites on risk of CHD. Analyses of circulating lipid metabolites in large epidemiological studies could lead to enhanced understanding of mechanisms for CHD development and identification of novel causal pathways and new therapeutic targets

An unbiased lipid phenotyping approach to study the genetic determinants of lipids and their association with coronary heart disease risk factors

Direct infusion high-resolution mass spectrometry (DIHRMS) is a novel, high-throughput approach to rapidly and accurately profile hundreds of lipids in human serum without prior chromatography, facilitating in-depth lipid phenotyping for large epidemiological studies to reveal the detailed associations of individual lipids with coronary heart disease (CHD) risk factors. Intact lipid profiling by DIHRMS was performed on 5662 serum samples from healthy participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS). We developed a novel semi-targeted peak-picking algorithm to detect mass-to-charge ratios in positive and negative ionization modes. We analyzed lipid partial correlations, assessed the association of lipid principal components with established CHD risk factors and genetic variants, and examined differences between lipids for a common genetic polymorphism. The DIHRMS method provided information on 360 lipids (including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids), with a median coefficient of variation of 11.6% (range: 5.4–51.9). The lipids were highly correlated and exhibited a range of associations with clinical chemistry biomarkers and lifestyle factors. This platform can provide many novel insights into the effects of physiology and lifestyle on lipid metabolism, genetic determinants of lipids, and the relationship between individual lipids and CHD risk factors

Genomics of lipid metabolism: Identification of genetic determinants of lipid metabolites and the effect of perturbations of lipid levels on coronary heart disease risk factors

Background: Coronary heart disease (CHD) is one of the leading causes of death worldwide, and global mortality rates are expected to continue to rise over the coming decades. In Pakistan in particular, chronic diseases are responsible for 50% of the total disease burden. Circulating lipids are strongly and linearly associated with risk of CHD; however, despite considerable efforts to demonstrate causality, available evidence is conflicting and insufficient. Study of the underlying metabolic pathways implicated in the association between lipids and CHD would help to disentangle and elucidate these complex relationships. Objectives: The primary objectives of this dissertation were to (1) identify the genetic determinants of lipid metabolites and (2) advance understanding of the effect of perturbations in lipid metabolite levels on CHD and its risk factors. Methods: Direct infusion high-resolution mass spectrometry was performed on 5662 participants from the Pakistan Risk of Myocardial Infarction Study to obtain signals for 444 known lipid metabolites. Correlations and associations of the lipids with smoking, physical activity, circulating biomarkers, and other CHD risk factors were assessed. Genome-wide analyses were conducted to analyse the association of each lipid with over 6.7 million imputed single nucleotide polymorphisms. Functional annotation and Gaussian Graphical Modelling were used to link the variants associated with each lipid to the most likely mediating gene, discern the underlying metabolic pathways, and provide a visual representation of the genetic determinants of human metabolism. Mendelian randomisation was also implemented to examine the causal effect of lipids on risk of CHD. Results: The lipids were highly correlated with each other and with levels of major circulating lipids, and they exhibited significant associations with several CHD risk factors. There were 254 lipids that had significant associations with one or more genetic variants and 355 associations between lipids and variants, with a total of 89 sentinel variants from 23 independent loci. The analyses described in this dissertation resulted in the discovery of four novel loci, identified novel relationships between genetic variants and lipids, and revealed new biological insights into lipid metabolism. Conclusion: Analyses of lipid metabolites in large epidemiological studies can contribute to enhanced understanding of mechanisms for CHD development and identification of novel causal pathways and new therapeutic targets

From lipid locus to drug target through human genomics

In the last decade, over 175 genetic loci have robustly been associated to levels of major circulating blood lipids. Most loci are specific to one or two lipids, whereas some (SUGP1, ZPR1, TRIB1, HERPUD1, and FADS1) are associated to all. While exposing the polygenic architecture of circulating lipids and the underpinnings of dyslipidaemia, these genome-wide association studies (GWAS) have provided further evidence of the critical role that lipids play in coronary heart disease (CHD) risk, as indicated by the 2.7-fold enrichment for macrophage gene expression in atherosclerotic plaques and the association of 25 loci (such as PCSK9, APOB, ABCG5-G8, KCNK5, LPL, HMGCR, NPC1L1, CETP, TRIB1, ABO, PMAIP1-MC4R, and LDLR) with CHD. These GWAS also confirmed known and commonly used therapeutic targets, including HMGCR (statins), PCSK9 (antibodies), and NPC1L1 (ezetimibe). As we head into the post-GWAS era, we offer suggestions for how to move forward beyond genetic risk loci, towards refining the biology behind the associations and identifying causal genes and therapeutic targets. Deep phenotyping through lipidomics and metabolomics will refine and increase the resolution to find causal and druggable targets, and studies aimed at demonstrating gene transcriptional and regulatory effects of lipid associated loci will further aid in identifying these targets. Thus, we argue the need for deeply phenotyped, large genetic association studies to reduce costs and failures and increase the efficiency of the drug discovery pipeline. We conjecture that in the next decade a paradigm shift will tip the balance towards a data-driven approach to therapeutic target development and the application of precision medicine where human genomics takes centre stage

Stenting for symptomatic vertebral artery stenosis: a preplanned pooled individual patient data analysis

Background Symptomatic vertebral artery stenosis is associated with a high risk of recurrent stroke, with higher risks for intracranial than for extracranial stenosis. Vertebral artery stenosis can be treated with stenting with good technical results, but whether it results in improved clinical outcome is uncertain. We aimed to compare vertebral stenting with medical treatment for symptomatic vertebral stenosis. Methods We did a preplanned pooled individual patient data analysis of three completed randomised controlled trials comparing stenting with medical treatment in patients with symptomatic vertebral stenosis. The primary outcome was any fatal or non-fatal stroke. Analyses were performed for vertebral stenosis at any location and separately for extracranial and intracranial stenoses. Data from the intention-to-treat analysis were used for all studies. We estimated hazard ratios (HRs) with 95% CIs using Cox proportional-hazards regression models stratified by trial. Findings Data were from 354 individuals from three trials, including 179 patients from VIST (148 with extracranial stenosis and 31 with intracranial stenosis), 115 patients from VAST (96 with extracranial stenosis and 19 with intracranial stenosis), and 60 patients with intracranial stenosis from SAMMPRIS (no patients had extracranial stenosis). Across all trials, 168 participants (46 with intracranial stenosis and 122 with extracranial stenosis) were randomly assigned to medical treatment and 186 to stenting (64 with intracranial stenosis and 122 with extracranial stenosis). In the stenting group, the frequency of periprocedural stroke or death was higher for intracranial stenosis than for extracranial stenosis (ten (16%) of 64 patients vs one (1%) of 121 patients; p&lt;0·0001). During 1036 person-years of follow-up, the hazard ratio (HR) for any stroke in the stenting group compared with the medical treatment group was 0·81% CI 0·45–1·44; p=0·47). For extracranial stenosis alone the HR was 0·63 (95% CI 0·27–1·46) and for intracranial stenosis alone it was 1·06 (0·46–2·42; pinteraction=0·395). Interpretation Stenting for vertebral stenosis has a much higher risk for intracranial, compared with extracranial, stenosis. This pooled analysis did not show evidence of a benefit for stroke prevention for either treatment. There was no evidence of benefit of stenting for intracranial stenosis. Stenting for extracranial stenosis might be beneficial, but further larger trials are required to determine the treatment effect in this subgroup. Funding None.</p

Stenting for symptomatic vertebral artery stenosis: a preplanned pooled individual patient data analysis

Background Symptomatic vertebral artery stenosis is associated with a high risk of recurrent stroke, with higher risks for intracranial than for extracranial stenosis. Vertebral artery stenosis can be treated with stenting with good technical results, but whether it results in improved clinical outcome is uncertain. We aimed to compare vertebral stenting with medical treatment for symptomatic vertebral stenosis. Methods We did a preplanned pooled individual patient data analysis of three completed randomised controlled trials comparing stenting with medical treatment in patients with symptomatic vertebral stenosis. The primary outcome was any fatal or non-fatal stroke. Analyses were performed for vertebral stenosis at any location and separately for extracranial and intracranial stenoses. Data from the intention-to-treat analysis were used for all studies. We estimated hazard ratios (HRs) with 95% CIs using Cox proportional-hazards regression models stratified by trial. Findings Data were from 354 individuals from three trials, including 179 patients from VIST (148 with extracranial stenosis and 31 with intracranial stenosis), 115 patients from VAST (96 with extracranial stenosis and 19 with intracranial stenosis), and 60 patients with intracranial stenosis from SAMMPRIS (no patients had extracranial stenosis). Across all trials, 168 participants (46 with intracranial stenosis and 122 with extracranial stenosis) were randomly assigned to medical treatment and 186 to stenting (64 with intracranial stenosis and 122 with extracranial stenosis). In the stenting group, the frequency of periprocedural stroke or death was higher for intracranial stenosis than for extracranial stenosis (ten (16%) of 64 patientsandnbsp;vsandnbsp;one (1%) of 121 patients; pandlt;0andmiddot;0001). During 1036 person-years of follow-up, the hazard ratio (HR) for any stroke in the stenting group compared with the medical treatment group was 0andmiddot;81% CI 0andmiddot;45andndash;1andmiddot;44; p=0andmiddot;47). For extracranial stenosis alone the HR was 0andmiddot;63 (95% CI 0andmiddot;27andndash;1andmiddot;46) and for intracranial stenosis alone it was 1andmiddot;06 (0andmiddot;46andndash;2andmiddot;42; pinteraction=0andmiddot;395). Interpretation Stenting for vertebral stenosis has a much higher risk for intracranial, compared with extracranial, stenosis. This pooled analysis did not show evidence of a benefit for stroke prevention for either treatment. There was no evidence of benefit of stenting for intracranial stenosis. Stenting for extracranial stenosis might be beneficial, but further larger trials are required to determine the treatment effect in this subgroup. Funding None.</p