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Abstract
The objective of a genetic association study, is to determine whether a potential
genetic polymorphism contributes to an individual's susceptibility to a particular
disease or characteristic. In scientific way, an association is typically described
as a statistically significant difference between two groups (case and control) concerning
a set of study variables. In genetic association studies, researchers examine the
genotypic and allelic frequencies of a particular polymorphism in both the case and
control groups to identify any possible associations. STrengthening the REporting
of Genetic Association Studies (STREGA) [1]. recommends that researchers investigate
the Hardy-Weinberg Equilibrium (HWE) through the examination of their control subjects'
genotypes. According to HWE, there should not be any significant difference between
the observed and expected values for genotypes of a given genetic polymorphism in
a large population with random mating, and in the absence of mutation, migration,
and natural selection. Deviation from these assumptions resulted in observed and expected
value differences that may have reached statistical significance.
The presence of evolutionary factors, such as mutation, migration, natural selection,
genetic drift, and non-random mating, can result in a noteworthy difference between
the anticipated and observed genotypic outcomes. It should be noted that this is not
the only factor at play and other factors contribute as well. Studies indicate that
researchers’ mistakes, like genotyping errors, are commonly responsible in such instances.
Another critical error is the inclusion of individuals from at least two separate
gene pools in the study groups, which results in a sampling error. This undermines
trust in the comparison of genotypic frequencies between the case and control groups.
The main purpose of comparing observed and expected genotypic frequencies under the
Hardy-Weinberg equilibrium is to assist researchers in recognizing potential issues
with their work. Researchers can subsequently take corrective action to address identified
errors (genotyping / sampling errors). Regrettably, some researchers fail to compare
observed and expected frequencies, make calculation errors, or fail to consider statistical
significance. Many of them are unaware that such oversimplification leads to a significant
number of published articles that lack credibility. Accordingly, it is of utmost importance
that studies presenting findings adhere to strict standards. Since the issuance of
the STREGA statement in 2009, there has been no decline in the occurrence of this
issue in genetic association study reports. It is essential for researchers interested
in genetic association studies to compare the observed and HWE-expected genotypic
values, as stated in the STREGA statement. It is hoped that following the recommendations
of the STREGA statement will improve the quality of genetic association studies.
Declaration of competing interest:
None
Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy–Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.
[1]Department of Biology, School of Science, Shiraz University, Shiraz, Iran
Author notes
[*
]Corresponding Author: Department of Biology, School of Science, Shiraz University,
Shiraz 71467-13565, Iran
Fax:+98 71 32280916; Email: saadat@shirazu.ac.ir AND msaadat41@yahoo.com
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