Page 172 - EJMO-9-2

Eurasian Journal of
Medicine and Oncology Genetic insights into CAD drug targets

with LPL deficiency or hypertriglyceridemia. FES, as affinities with artemisinin and TNF, as well as lovastatin
an immune regulator, may be relevant for patients with and FES, indicating especially promising interactions. This
heightened systemic inflammation and could be explored comprehensive approach provides strong evidence for
in combination with immunomodulatory agents. To these candidate genes as therapeutic targets for CA, laying
facilitate clinical decision-making, integrating these a foundation for targeted therapies that could lead to more
biomarkers into treatment algorithms is essential. Genetic effective and personalized CA treatments.
testing, lipid profiling, and inflammatory marker panels
could guide therapy selection, enabling biomarker- 4.1. Study limitations
driven precision medicine approaches. Future research This study has several limitations that should be noted.
should focus on embedding these strategies into precision First, MR assumes a linear relationship between low-
medicine clinical trials, utilizing multi-omics data to refine dose drug exposure and outcomes. This assumption may
patient selection and optimize treatment responses. These not accurately reflect real-world complexities, especially
findings provide a foundation for shifting from generalized during short-term evaluations involving high-dose drugs.
CA treatment toward a personalized, biomarker-guided Therefore, MR results may not fully predict the effects
therapeutic framework. observed in actual clinical settings.
In resource-limited health-care settings, issues related Second, the study primarily relied on data from
to gene screening technologies and the accessibility individuals of European ancestry, which limits the
of expensive medications are particularly prominent. generalizability of the findings. Although the eQTL analysis
Artemisinin, as an antimalarial drug, has relatively included data from different populations, the cohort
good affordability in low-income regions, but long-term used for CA analysis was mainly European, potentially
treatment for CA may face challenges related to treatment introducing bias due to differences in genetic backgrounds.
costs and drug tolerance. Moreover, the use of lovastatin Further validation in more diverse populations is warranted
still requires addressing its side effects (such as muscle pain to enhance the applicability of the results.
and liver enzyme abnormalities) on patients. Resource- In addition, this study used blood eQTLs for MR
constrained regions may need to develop more affordable analysis; however, gene regulation mechanisms may vary
and accessible treatment options. Furthermore, clinical significantly across different tissues. Relying solely on
drug development typically takes several years or even blood data may not comprehensively reveal the complex
longer, leading to a lag in drug implementation. Long- mechanisms of CA. Future research should integrate
term clinical trials are crucial for verifying the safety and gene data from multiple tissues to gain a more complete
efficacy of new drugs; however, for existing drugs such as understanding.
lovastatin and artemisinin, rapid drug approval and market
introduction are needed for widespread application in a Although this study identified potential targets
shorter time frame. Interdisciplinary collaboration and associated with CA based on genetic association data, we
rapid response from regulatory agencies will play a critical did not fully consider the potential impact of environmental
role in advancing early-stage clinical trials for these drugs. factors and gene-environment interactions on the results.
Environmental factors, such as lifestyle, diet, and pollution,
Our study contributes to the development of new
therapeutic strategies for CA by MR to identify druggable as well as gene-environment interactions, may have a
genes that may influence CA outcomes, utilizing large potential influence on the findings to some extent.
GWAS datasets. Among the nine identified druggable genes, Finally, the accuracy of molecular docking analysis
four (DHX36, FES, LPL, and TNF) demonstrated evidence largely depends on the quality of protein structures and
of colocalization with CA, supporting their potential ligands. Although this method helps identify potential drug
causal roles. These findings were validated in independent targets, its clinical validity requires further experimental
cohorts, enhancing robustness and reducing the likelihood validation and clinical trials.
of false positives, which is crucial for improving future
clinical trial success rates. Enrichment analysis highlighted 4.2. Future research directions
the roles of these genes in lipid metabolism and immune To advance the clinical application of these discoveries,
response. PPI analysis indicated that these genes, future research should focus on the following specific
particularly TNF and LPL, play central roles in a complex directions:
interaction network, offering opportunities for drug (i) In vivo validation: Researchers could conduct animal
development. Furthermore, candidate drug prediction and model studies to validate the functions of genes, such
molecular docking studies revealed significant binding as DHX36, FES, LPL, and TNF, and assess their impact

Volume 9 Issue 2 (2025) 164 doi: 10.36922/ejmo.7387