Mendelian Randomization of Blood Lipids for CHD
Mendelian Randomization of Blood Lipids for CHD
This Mendelian randomization analysis was based on individual participant level data including 62 199 individuals from 17 studies and used a multiple SNP instrumental variable meta-analysis approach. We reconfirmed the causal role of LDL-C in CHD risk and provided additional support for a causal role of triglycerides in CHD. The causal association of HDL-C with CHD remains possible, but less certain.
A key problem in trying to understand the causal relevance of HDL-C and triglycerides in CHD risk has been the close epidemiological and biological interrelationship between the two. Both associate with CHD events in observational studies, yet statistical adjustment for one attenuates the association of the other. Incomplete biological understanding makes interpretation of this observational evidence challenging. Multiple instrument Mendelian randomization studies utilizing SNPs affecting the levels of these two traits offer a new route to understand their causal relevance and many such SNPs have been identified by recent genome-wide and gene-centric association studies, including the set of SNPs used in the present analysis. Although, multiple instruments Mendelian randomization analysis reduces the non-specificity, it does not abolish it. For this reason, we generated two different allele scores. First, an unrestricted score that includes all genetic determinants of each lipid trait, which can be conceived as being more comprehensive in biological terms, as well as more powerful (e.g. R of unrestricted score for HDL-C was 3.8%). In contrast, the restricted score, though substantially increasing specificity for the target lipid, is both less biologically comprehensive and statistically less powerful (e.g. R of restricted score for HDL-C was 0.3%). Owing to these limitations, we also undertook instrumental variable analyses using the unrestricted scores in which adjustments were made for the non-target lipids. We then compared the effect estimates from these different approaches to draw inferences on the causal role of HDL-C and triglycerides using LDL-C, whose aetiological role in CHD is established, as a positive control. This strategy, comparing the consistency of potentially causal estimates derived from instrumental variable analysis that used three different approaches, each of them with different underlying assumptions, in individual participant data sets, we believe has not been employed before and thus represents a novel aspect of the current analysis.
The estimates of LDL-C from instrumental variable analysis showed that a long-term genetically increased LDL-C, regardless of the analytical strategy used (unrestricted, restricted, or unrestricted score plus sequential adjustments) resulted in an increased causal OR for CHD, which is similar in magnitude to that reported in randomized trials of statin-lowering therapies in individuals at low risk of vascular disease and is further evidence of the validity of our various analytical approaches. The instrumental variable analysis of LDL-C on cIMT is also in keeping with recent findings, and supports the use of cIMT as an appropriate surrogate marker of therapies that modulate LDL-C.
For triglycerides, the findings for the unrestricted and restricted allele scores were concordant, with both showing association with CHD. However, the unrestricted score adjusted for HDL-C diminished the association to null. Thus, two out of the three approaches provided evidence of a causal role of triglycerides in CHD, making it likely that triglycerides are causally related to CHD. It is intriguing that the association of the unrestricted score for triglycerides with CHD events diminished to null when adjusted for HDL-C. This could mean that a treatment that targets a triglyceride pathway that has no effect on HDL-C may not be beneficial, whereas a treatment that targets a triglyceride pathway that both reduces triglycerides and increases HDL-C could have a role in prevention of CHD events. An alternative explanation is that HDL-C could mark long-term triglyceride concentrations, but this hypothesis requires further investigation. As recently suggested by Wurtz et al. in response to a Mendelian randomization analysis of remnant cholesterol by Varbo et al., access to metabolomics data will enable partitioning of triglyceride containing lipoproteins according to size and composition (e.g. apolipoprotein B content) and facilitate investigation of the role of these subcomponents individually in CHD pathogenesis.
For HDL-C, only one of the approaches provided evidence that genetic determinants of HDL-C are causally related to CHD. The unrestricted HDL-C allele score (which did not impose constraints on the pathways that the genes in the allele score encode for) showed strong evidence of an association with CHD. But this unrestricted HDL-C allele score also showed association with triglycerides (and to a lesser extent LDL-C). In contrast, the restricted HDL-C allele score did not show an association with CHD. The restricted HDL-C allele score was more selective for HDL-C (showing only a very weak association with triglycerides and no effect on LDL-C), but also explained less of the variance of the index trait, HDL-C (even when compared with other restricted scores), so it remains uncertain if this attenuation in the effect estimate implies that an intervention that solely modifies HDL-C would not reduce risk of CHD, or whether it is due to a reduction in statistical power. This former interpretation is in agreement with findings from our unrestricted allele score adjusted for triglycerides, and with a previous multiple SNPs Mendelian randomization analysis that, using different genetic instruments (Supplementary material online, Figure S13http://eurheartj.oxfordjournals.org/content/suppl/2014/01/27/eht571.DC1), also failed to identify a clear causal role of HDL-C in CHD.
Our study has a number of possible limitations. First, of the 17 contributing studies, 13 were a subsample of the 32 studies that contributed towards the gene-centric discovery meta-analysis on blood lipid traits. Thus, it is theoretically possible that using a partially overlapping set of studies for the discovery and Mendelian randomization analysis may potentially result in model over-fitting. Secondly, our allele scores were designed to proxy total levels of blood lipid and lipoprotein traits, and therefore do not address whether there are subtypes of these traits (e.g. HDL subparticles) that could play contrasting roles in vascular disease. For example, we cannot exclude the possibility that the restricted HDL-C allele score may have lacked genes that are present in the unrestricted allele score that encode subparticles of HDL that do have a causal role in CHD. This requires further investigation with Mendelian randomization using SNPs or allele scores that are specific for HDL subtypes. Thirdly, it is possible that some of the null findings could be due to limited power, including the analysis for cIMT. Examination of these findings in other data sets is therefore warranted.
In conclusion, the findings from a multiple SNP Mendelian randomization analysis in over 62 000 participants with >12 000 CHD events support a causal effect of triglycerides but evidence on the causal role, if any, of HDL-C on CHD risk remains uncertain.
Discussion
This Mendelian randomization analysis was based on individual participant level data including 62 199 individuals from 17 studies and used a multiple SNP instrumental variable meta-analysis approach. We reconfirmed the causal role of LDL-C in CHD risk and provided additional support for a causal role of triglycerides in CHD. The causal association of HDL-C with CHD remains possible, but less certain.
A key problem in trying to understand the causal relevance of HDL-C and triglycerides in CHD risk has been the close epidemiological and biological interrelationship between the two. Both associate with CHD events in observational studies, yet statistical adjustment for one attenuates the association of the other. Incomplete biological understanding makes interpretation of this observational evidence challenging. Multiple instrument Mendelian randomization studies utilizing SNPs affecting the levels of these two traits offer a new route to understand their causal relevance and many such SNPs have been identified by recent genome-wide and gene-centric association studies, including the set of SNPs used in the present analysis. Although, multiple instruments Mendelian randomization analysis reduces the non-specificity, it does not abolish it. For this reason, we generated two different allele scores. First, an unrestricted score that includes all genetic determinants of each lipid trait, which can be conceived as being more comprehensive in biological terms, as well as more powerful (e.g. R of unrestricted score for HDL-C was 3.8%). In contrast, the restricted score, though substantially increasing specificity for the target lipid, is both less biologically comprehensive and statistically less powerful (e.g. R of restricted score for HDL-C was 0.3%). Owing to these limitations, we also undertook instrumental variable analyses using the unrestricted scores in which adjustments were made for the non-target lipids. We then compared the effect estimates from these different approaches to draw inferences on the causal role of HDL-C and triglycerides using LDL-C, whose aetiological role in CHD is established, as a positive control. This strategy, comparing the consistency of potentially causal estimates derived from instrumental variable analysis that used three different approaches, each of them with different underlying assumptions, in individual participant data sets, we believe has not been employed before and thus represents a novel aspect of the current analysis.
The estimates of LDL-C from instrumental variable analysis showed that a long-term genetically increased LDL-C, regardless of the analytical strategy used (unrestricted, restricted, or unrestricted score plus sequential adjustments) resulted in an increased causal OR for CHD, which is similar in magnitude to that reported in randomized trials of statin-lowering therapies in individuals at low risk of vascular disease and is further evidence of the validity of our various analytical approaches. The instrumental variable analysis of LDL-C on cIMT is also in keeping with recent findings, and supports the use of cIMT as an appropriate surrogate marker of therapies that modulate LDL-C.
For triglycerides, the findings for the unrestricted and restricted allele scores were concordant, with both showing association with CHD. However, the unrestricted score adjusted for HDL-C diminished the association to null. Thus, two out of the three approaches provided evidence of a causal role of triglycerides in CHD, making it likely that triglycerides are causally related to CHD. It is intriguing that the association of the unrestricted score for triglycerides with CHD events diminished to null when adjusted for HDL-C. This could mean that a treatment that targets a triglyceride pathway that has no effect on HDL-C may not be beneficial, whereas a treatment that targets a triglyceride pathway that both reduces triglycerides and increases HDL-C could have a role in prevention of CHD events. An alternative explanation is that HDL-C could mark long-term triglyceride concentrations, but this hypothesis requires further investigation. As recently suggested by Wurtz et al. in response to a Mendelian randomization analysis of remnant cholesterol by Varbo et al., access to metabolomics data will enable partitioning of triglyceride containing lipoproteins according to size and composition (e.g. apolipoprotein B content) and facilitate investigation of the role of these subcomponents individually in CHD pathogenesis.
For HDL-C, only one of the approaches provided evidence that genetic determinants of HDL-C are causally related to CHD. The unrestricted HDL-C allele score (which did not impose constraints on the pathways that the genes in the allele score encode for) showed strong evidence of an association with CHD. But this unrestricted HDL-C allele score also showed association with triglycerides (and to a lesser extent LDL-C). In contrast, the restricted HDL-C allele score did not show an association with CHD. The restricted HDL-C allele score was more selective for HDL-C (showing only a very weak association with triglycerides and no effect on LDL-C), but also explained less of the variance of the index trait, HDL-C (even when compared with other restricted scores), so it remains uncertain if this attenuation in the effect estimate implies that an intervention that solely modifies HDL-C would not reduce risk of CHD, or whether it is due to a reduction in statistical power. This former interpretation is in agreement with findings from our unrestricted allele score adjusted for triglycerides, and with a previous multiple SNPs Mendelian randomization analysis that, using different genetic instruments (Supplementary material online, Figure S13http://eurheartj.oxfordjournals.org/content/suppl/2014/01/27/eht571.DC1), also failed to identify a clear causal role of HDL-C in CHD.
Our study has a number of possible limitations. First, of the 17 contributing studies, 13 were a subsample of the 32 studies that contributed towards the gene-centric discovery meta-analysis on blood lipid traits. Thus, it is theoretically possible that using a partially overlapping set of studies for the discovery and Mendelian randomization analysis may potentially result in model over-fitting. Secondly, our allele scores were designed to proxy total levels of blood lipid and lipoprotein traits, and therefore do not address whether there are subtypes of these traits (e.g. HDL subparticles) that could play contrasting roles in vascular disease. For example, we cannot exclude the possibility that the restricted HDL-C allele score may have lacked genes that are present in the unrestricted allele score that encode subparticles of HDL that do have a causal role in CHD. This requires further investigation with Mendelian randomization using SNPs or allele scores that are specific for HDL subtypes. Thirdly, it is possible that some of the null findings could be due to limited power, including the analysis for cIMT. Examination of these findings in other data sets is therefore warranted.
In conclusion, the findings from a multiple SNP Mendelian randomization analysis in over 62 000 participants with >12 000 CHD events support a causal effect of triglycerides but evidence on the causal role, if any, of HDL-C on CHD risk remains uncertain.
Source...