See article vol. 26: 136–144
Understandings from Causal Associations between Biomarkers and Clinical Outcomes
To establish a causal association between a biomarker and an outcome, randomized controlled trials (RCT) are the gold standard. On the other hand, the Mendelian randomization trial is a technique that uses genotypes as instruments to assess causal associations between biomarkers and outcomes1). In a Mendelian randomization trial, a genetic variant associated with a particular biomarker is used as a proxy for the biomarker. Outcomes are compared between the group with the effect allele and a group with the reference allele. This approach can be considered a proxy for an RCT, in which the randomized groups have similar confounding variables. Accordingly, a Mendelian randomization trial can be regarded as a natural RCT. Using this technique, a causal association between LDL cholesterol and atherosclerotic diseases have been firmly confirmed. With respect to triglycerides, they have been associated with atherosclerotic diseases in numerous epidemiological studies2). Establishing triglyceride as a causal factor of atherosclerotic diseases has been difficult because it is difficult to distinguish the effects of triglyceride on atherosclerotic diseases from those of LDL cholesterol and HDL cholesterol by RCT or by Mendelian randomization trials. To overcome this issue, an interesting study creating a framework to observed whether triglyceride causally influences the risk of atherosclerotic diseases was published in 20133). They constructed a model adjusting for the effects of LDL cholesterol and/or HDL cholesterol levels on the risk of atherosclerotic diseases, and found that the genetic impact of single nucleotide polymorphisms (SNPs) on triglyceride levels was independently associated with the risk of atherosclerotic diseases. This study suggested that triglycerides causally affect the risk of atherosclerotic diseases. In this issue, Liu et al. described an extremely rare case of severe hypertriglyceridemia caused by lipase maturation factor 1 (LMF1) mutations exhibiting atherosclerotic changes4). In addition, rare as well as common genetic variations in lipoprotein lipase (LPL) and apolipoprotein C3 (APOC3) genes have been associated with coronary artery disease5, 6). We strongly believe that consistent directions regarding the effects on phenotype between common as well as rare genetic variations definitely ascertain the truth of nature (Fig. 1). Those observations collectively suggest that triglyceride could be regarded as a causal factor for atherosclerosis, rather than a biomarker.
Fig. 1.
Scheme of human genetic variations and diseases
Upper panel. X-axis represents allele frequency. Y-axis represents effect sizes.
Lower panel. Consistent directions between rare as well as common genetic variations definitely ascertain the truth of nature.
Biology, Genetics, and Outcomes
Although human genetics could potentially illustrate the causal associations between biomarkers and outcomes, underlying biology should also be considered. We have previously shown that rare genetic variations lowering triglyceride were consistently associated with lowering the risk for coronary atherosclerosis, although we could not have enough power to show this favorable association in LMF1 gene (Table 1)7). Interestingly, the effect on the risk of developing diabetes were inconsistent across those genes, suggesting that functions based on biology should be carefully considered when assessing such genetic association studies.
Table 1. Impact of triglyceride lowering genes on CAD and T2DM.
| Gene | Number of variants | Triglyceride | HDL cholesterol | LDL cholesterol | CAD Odds ratio | T2DM Odds ratio |
|---|---|---|---|---|---|---|
| LPL | 7 | −0.138 ± 0.002 (<1.0 × 10−237) |
0.939 ± 0.011 (<1.0 × 10−237) |
0.025 ± 0.012 (0.03) |
0.66 | 0.8 |
| ANGPTL4 | 1 | −0.273 ± 0.01 (4.2 × 10−175) |
0.891 ± 0.035 (4.8 × 10−146) |
−0.014 ± 0.036 (0.7) |
0.6 | 0.67 |
| APOA5 | 7 | −0.227 ± 0.002 (<1.0 × 10−237) |
0.453 ± 0.009 (<1.0 × 10−237) |
−0.145 ± 0.009 (8.4 × 10−59) |
0.76 | 0.88 |
| APOC3 | 3 | −1.069 ± 0.032 (3.2 × 10−237) |
0.695 ± 0.03 (9.0 × 10−120) |
−0.106 ± 0.03 (4.7 × 10−4) |
0.85 | 1.07 |
| ANGPTL3 | 1 | −0.077 ± 0.003 (6.1 × 10−170) |
−0.136 ± 0.035 (1.2 × 10−4) |
−0.588 ± 0.037 (4.8 × 10−58) |
0.89 | 1.18 |
| ANGPTL8 | 1 | −0.353 ± 0.051 (2.8 × 10−12) |
1.221 ± 0.141 (5.0 × 10−18) |
−0.167 ± 0.146 (0.25) |
0.74 | 1.58 |
Value are expressed as effect size ± S.E. (p-value). LPL = lipoprotein lipase; ANGPTL4 = angiopoietin-like 4; APOA5 = apolipoprotein A5; APOC3 = apolipoprotein C3; ANGPTL3 = Angiopoietin-like 3; ANGPTL8 = Angiopoietin-like 8; CAD = coronary artery disease; T2DM = type 2 diabetes mellitus
Conclusion
Dyslipidemias, including hypertriglyceridemia, are important causal factors of atherosclerosis. Genetic analyses in Mendelian dyslipidemias as well as Mendelian randomization trials using common genetic variants have contributed to our understanding of lipids and atherosclerotic diseases. Investigation on extreme cases caused by rare genetic variants can lead to the development of novel drugs for the general population, especially when the on-target/off-target directions of rare variants and common variants exhibit the same directions8). We do hope that such cases could be verified in other genes, including LMF1, based on the accumulations of those extreme cases.
Acknowledgments
None.
Conflict of Interest
None.
Sources of Funding
None.
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