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Challenges and novel approaches for investigating molecular mediation

View Article: PubMed Central - PubMed

ABSTRACT

Understanding mediation is useful for identifying intermediates lying between an exposure and an outcome which, when intervened upon, will block (some or all of) the causal pathway between the exposure and outcome. Mediation approaches used in conventional epidemiology have been adapted to understanding the role of molecular intermediates in situations of high-dimensional omics data with varying degrees of success. In particular, the limitations of observational epidemiological study including confounding, reverse causation and measurement error can afflict conventional mediation approaches and may lead to incorrect conclusions regarding causal effects. Solutions to analysing mediation which overcome these problems include the use of instrumental variable methods such as Mendelian randomization, which may be applied to evaluate causality in increasingly complex networks of omics data.

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Schematic diagram of two-step, two-sample Mendelian randomization In the smaller Sample 1, the association of the exposure to the intermediate is established using an MR approach (using the exposure-related G1); and the association of an additional variant (G2, not related to the exposure) with the same intermediate is established. G1 and G2 should be identified in an independent study. In the larger Sample 2, the intermediate is shown to influence the outcome through the use of G2, which is related to the outcome. N.B. the dotted arrows represent the fact that these genetic variants, G1 and G2, influence the intermediate or outcome indirectly through the exposure or intermediate, rather than having a pleiotropic effect. In theory, G1 would also be found to influence the outcome indirectly through both the exposure and intermediate.
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ddw197-F6: Schematic diagram of two-step, two-sample Mendelian randomization In the smaller Sample 1, the association of the exposure to the intermediate is established using an MR approach (using the exposure-related G1); and the association of an additional variant (G2, not related to the exposure) with the same intermediate is established. G1 and G2 should be identified in an independent study. In the larger Sample 2, the intermediate is shown to influence the outcome through the use of G2, which is related to the outcome. N.B. the dotted arrows represent the fact that these genetic variants, G1 and G2, influence the intermediate or outcome indirectly through the exposure or intermediate, rather than having a pleiotropic effect. In theory, G1 would also be found to influence the outcome indirectly through both the exposure and intermediate.

Mentions: In addition, with regards to asserting mediation in an exposure-outcome setting, the two-step MR approach could be combined with the two-sample approach to powerfully and efficiently examine the extent of mediation in causal networks (5). First, the causal associations of both the exposure on the intermediate and of an independent variant on the intermediate could be established, and then in a larger population-based sample, the genetic associations with the disease outcome delineated (Fig. 6). This gives two-step MR an advantage over traditional mediation approaches which require the exposure, mediator and outcome to be measured in the same subset of individuals.Figure 6.


Challenges and novel approaches for investigating molecular mediation
Schematic diagram of two-step, two-sample Mendelian randomization In the smaller Sample 1, the association of the exposure to the intermediate is established using an MR approach (using the exposure-related G1); and the association of an additional variant (G2, not related to the exposure) with the same intermediate is established. G1 and G2 should be identified in an independent study. In the larger Sample 2, the intermediate is shown to influence the outcome through the use of G2, which is related to the outcome. N.B. the dotted arrows represent the fact that these genetic variants, G1 and G2, influence the intermediate or outcome indirectly through the exposure or intermediate, rather than having a pleiotropic effect. In theory, G1 would also be found to influence the outcome indirectly through both the exposure and intermediate.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036871&req=5

ddw197-F6: Schematic diagram of two-step, two-sample Mendelian randomization In the smaller Sample 1, the association of the exposure to the intermediate is established using an MR approach (using the exposure-related G1); and the association of an additional variant (G2, not related to the exposure) with the same intermediate is established. G1 and G2 should be identified in an independent study. In the larger Sample 2, the intermediate is shown to influence the outcome through the use of G2, which is related to the outcome. N.B. the dotted arrows represent the fact that these genetic variants, G1 and G2, influence the intermediate or outcome indirectly through the exposure or intermediate, rather than having a pleiotropic effect. In theory, G1 would also be found to influence the outcome indirectly through both the exposure and intermediate.
Mentions: In addition, with regards to asserting mediation in an exposure-outcome setting, the two-step MR approach could be combined with the two-sample approach to powerfully and efficiently examine the extent of mediation in causal networks (5). First, the causal associations of both the exposure on the intermediate and of an independent variant on the intermediate could be established, and then in a larger population-based sample, the genetic associations with the disease outcome delineated (Fig. 6). This gives two-step MR an advantage over traditional mediation approaches which require the exposure, mediator and outcome to be measured in the same subset of individuals.Figure 6.

View Article: PubMed Central - PubMed

ABSTRACT

Understanding mediation is useful for identifying intermediates lying between an exposure and an outcome which, when intervened upon, will block (some or all of) the causal pathway between the exposure and outcome. Mediation approaches used in conventional epidemiology have been adapted to understanding the role of molecular intermediates in situations of high-dimensional omics data with varying degrees of success. In particular, the limitations of observational epidemiological study including confounding, reverse causation and measurement error can afflict conventional mediation approaches and may lead to incorrect conclusions regarding causal effects. Solutions to analysing mediation which overcome these problems include the use of instrumental variable methods such as Mendelian randomization, which may be applied to evaluate causality in increasingly complex networks of omics data.

No MeSH data available.


Related in: MedlinePlus