Causal relationship of susceptibility genes to ischemic stroke: comparison to ischemic heart disease and biochemical determinants

Abstract

Interrelationships between genetic and biochemical factors underlying ischemic stroke and ischemic heart disease are poorly understood. We: 1) undertook the most comprehensive meta-analysis of genetic polymorphisms in ischemic stroke to date; 2) compared genetic determinants of ischemic stroke with those of ischemic heart disease, and 3) compared effect sizes of gene-stroke associations with those predicted from independent biochemical data using a mendelian randomization strategy. Electronic databases were searched up to January 2009. We identified: 1) 187 ischemic stroke studies (37,481 cases; 95,322 controls) interrogating 43 polymorphisms in 29 genes; 2) 13 meta-analyses testing equivalent polymorphisms in ischemic heart disease; and 3) for the top five gene-stroke associations, 146 studies (65,703 subjects) describing equivalent gene-biochemical relationships, and 28 studies (46,928 subjects) describing biochemical-stroke relationships. Meta-analyses demonstrated positive associations with ischemic stroke for factor V Leiden Gln506, ACE I/D, MTHFR C677T, prothrombin G20210A, PAI-1 5G allele and glycoprotein IIIa Leu33Pro polymorphisms (ORs: 1.11 - 1.60). Most genetic associations show congruent levels of risk comparing ischemic stroke with ischemic heart disease, but three genes--glycoprotein IIIa, PAI-1 and angiotensinogen--show significant dissociations. The magnitudes of stroke risk observed for factor V Leiden, ACE, MTHFR and prothrombin, but not PAI-1, polymorphisms, are consistent with risks associated with equivalent changes in activated protein C resistance, ACE activity, homocysteine, prothrombin, and PAI-1 levels, respectively. Our results demonstrate causal relationships for four of the most robust genes associated with stroke while also showing that PAI-1 4G/5G polymorphism influences cardiovascular risk via a mechanism not simply related to plasma levels of PAI-1 (or tPA) alone.

Figure 1. Forest plots showing positive associations of ischemic stroke with the following genetic polymorphisms: Factor V Leiden Arg506Gln.

Figure 2. Forest plots showing positive associations of ischemic stroke with the following genetic polymorphisms: ACE D/I.

Figure 3. Forest plots showing positive associations of ischemic stroke with the following genetic polymorphisms: MTHFR C677T.

Figure 4. Forest plots showing positive associations of ischemic stroke with the following genetic polymorphisms: prothrombin G20210A.

Figure 5. Forest plots showing positive associations of ischemic stroke with the following genetic polymorphisms: PAI 5G allele.

Figure 6. Forest plots showing positive associations of ischemic stroke with the following genetic polymorphisms: glycoprotein IIIa Leu33Pro.

Figure 7. Summary of meta-analyses testing associations of candidate genetic polymorphisms with ischemic stroke.

Table reports genetic model tested (D – dominant; R – recessive); numbers of studies; numbers of pooled cases and controls; ORs with 95% confidence intervals, and at-risk genotype frequency.

Figure 8. Trends in success of candidate gene approach.

A: Numbers of pooled cases published over time testing for polymorphisms positively associated with stroke according to the present meta-analyses. B: As for A, but for polymorphisms found to show no stroke association according to the present meta-analysis. C: Changes in time of probability that cases were tested for polymorphism subsequently found to show association (red) or no association (green) with stroke.

Figure 9. Risk of genetic polymorphisms compared between ischemic stroke (IS) and ischemic heart disease (IH) or myocardial infarction (MI).

Contrasts represent per-allele effects except where indicated. Polymorphisms are grouped into those showing consistent associations for both types of disease; those showing dissociated effects; and those showing a significant risk of heart disease but not stroke. For the latter the minimum sample numbers estimated to achieve 90% power based upon each polymorphism's effect size for ischemic heart disease are shown.

Figure 10. Forest plots showing quantitative relationship between genetic polymorphisms and associated biochemical variables for: Factor V Leiden and activated Protein C resistance ratio.

Additional forest plots are shown in Figures 10, and 13– 15 that relate set changes in biochemical variables (determined from the first set of meta-analyses within each figure) with risk of stroke. For MTHFR and ACE this relationship is determined from a single study each.

Figure 11. Forest plots showing quantitative relationship between genetic polymorphisms and associated biochemical variables for: ACE D/I and ACE activity.

Additional forest plots are shown in Figures 10, and 13– 15 that relate set changes in biochemical variables (determined from the first set of meta-analyses within each figure) with risk of stroke. For MTHFR and ACE this relationship is determined from a single study each.

Figure 12. Forest plots showing quantitative relationship between genetic polymorphisms and associated biochemical variables for: MTHFR and homocysteine levels.

Additional forest plots are shown in Figures 10, and 13– 15 that relate set changes in biochemical variables (determined from the first set of meta-analyses within each figure) with risk of stroke. For MTHFR and ACE this relationship is determined from a single study each.

Figure 13. Forest plots showing quantitative relationship between genetic polymorphisms and associated biochemical variables for: Prothrombin G20210A and prothrombin levels.

Additional forest plots are shown in Figures 10, and 13– 15 that relate set changes in biochemical variables (determined from the first set of meta-analyses within each figure) with risk of stroke. For MTHFR and ACE this relationship is determined from a single study each.

Figure 14. Forest plots showing quantitative relationship between genetic polymorphisms and associated biochemical variables for: PAI-1 5G/4G and PAI-1 levels.

Additional forest plots are shown in Figures 10, and 13– 15 that relate set changes in biochemical variables (determined from the first set of meta-analyses within each figure) with risk of stroke. For MTHFR and ACE this relationship is determined from a single study each.

Figure 15. Forest plots showing quantitative relationship between genetic polymorphisms and associated biochemical variables for: PAI-1 5G/4G and tPA levels.

Additional forest plots are shown in Figures 10, and 13– 15 that relate set changes in biochemical variables (determined from the first set of meta-analyses within each figure) with risk of stroke. For MTHFR and ACE this relationship is determined from a single study each.

Figure 16. Comparison of estimated risk with observed risk for ischemic stroke-associated genetic polymorphisms.

Estimated ORs (green) are calculated from 1) meta-analyses relating risk-genotype with biochemical variation (ΔX), and 2) single studies or meta-analyses relating biochemical variation with stroke risk (scaled log-linearly). Observed ORs are derived from meta-analyses of the equivalent genotype contrast using the current datasets.