Page 231 - Special Topic Session (STS) - Volume 4

STS582 Mariza de A.
However there are many risk factors that may increase the levels of CRP and
the risk of CHD. First these factors need to be identified. In this particular
situation one of the potential confounders was fibrinogen, a soluble blood
plasma glycoprotein, that enables blood-clotting, that belongs to the
inflammation pathway. This leads to the conclusion that the elevated levels of
CRP are caused to changes in fibrinogen. However by using one genetic
variant of Fibrinogen gene, it was concluded that fibrinogen does not play a
role in CHD (4). In the era of the genome whole association studies (GWAS),
the use of genetic variants as the instrumental variables to estimate the
relationship between the mediators or confounders and the outcome variable,
the use of Mendelian Randomization in genetic epidemiology turns up to be
the way to estimate interactions (1). One can also include other omics
information such as gene expression, structural variation, pathways from
whole genome sequencing (WGS) (5, 6). The advantage to use Mendelian
Randomization is that to make causal inferences about modifiable (non-
genetic) risk factors for disease and health-related outcomes, where in these
studies on can exploit the law of independt assortment, i.e., the inheritance of
one trait is independent (or randomized with respect to) the inheritance of
other traits as already described. In this paper I will introduce the MR models,
causal estimation, and statistical approaches as well as presented real data
analyses, and the list of software available for Mendelian Randomization.

2. Methodology
There are limitations of observational epidemiology for making causal
inference despite the fact that conventional observational epidemiology has
made relevant contributions to understanding disease etiology. For example,
the identification of the link between cigarette smoking and lung cancer (3),
heart disease among others as well as the limitations of randomized controlled
trials (RCTs). The most common explanations are confounding by lifestyle and
socioeconomic factors or by baseline health status and prescriptions, together
with reverse causation and selection bias (4). Mendelian randomization is the
term has been given to studies that use genetic variants in observational study
of genetic epidemiology to make causal inferences about modifiable risk
factors for disease and health-related outcomes (5). The issue of Mendel’s law
of independent assortment is not always valid due to the fact that
independent assortment is generally true for genes found on non-
homologous chromosomes; however it is not true for genes found in non-
homologous chromosomes mainly if the genes are located close to each
other, which lead to the terrn linkage disequilibrium (LD) that represents a
departure from the situation that all alleles are in complete independence (LE,
linkage equilibrium). Thus, many genetic association including Mendelian
randomization studies exploit LD to their advantage by using genetic markers
or single-nucleotide polymorphism (SNP) that are in LD with functional

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