Does Your DNA Determine Aspirin’s Effect? A Deep Dive into Aspirin Resistance Genetics

aspirin resistance genetics

Does Your DNA Determine Aspirin’s Effect? A Deep Dive into Aspirin Resistance Genetics

Last Updated: July 31, 2025

Personalized medicine promises a future where treatments are tailored to our unique genetic makeup. For a drug as common as aspirin, understanding who will benefit and who won’t is a critical goal. Millions take aspirin to prevent cardiovascular events, but a significant portion of users display “aspirin resistance,” where the drug fails to provide its antiplatelet protection. This has led scientists to ask a crucial question: is our response to aspirin written in our DNA?

A comprehensive 2019 doctoral thesis provides fascinating insight into aspirin resistance genetics. By examining specific genetic markers in a Pakistani population, the research challenges some widely held assumptions and underscores the complexity of how our genes influence drug efficacy. This post analyzes the study’s core findings on two key genes, COX-1 and COX-2, to see if they hold the answer.

The Genetic Basis of Aspirin Action: A Primer

To understand aspirin resistance genetics, we first need to know how aspirin works. Aspirin’s primary targets are the cyclo-oxygenase (COX) enzymes, specifically COX-1 and COX-2. By inhibiting these enzymes in platelets, aspirin halts the production of thromboxane A2, a substance that makes platelets sticky and prone to clotting.

Genetic variations, known as Single Nucleotide Polymorphisms (SNPs), can alter the structure or expression of these enzymes. It’s been hypothesized that certain SNPs could make the COX enzymes less susceptible to aspirin’s effects, leading to resistance. This study focused on two well-known SNPs:

  • rs1330344 in the COX-1 gene
  • rs20417 in the COX-2 gene

Investigating COX-1 Gene Polymorphism (rs1330344)

The COX-1 enzyme is the main target for aspirin’s antiplatelet action. The study investigated whether the rs1330344 SNP in the COX-1 gene was associated with aspirin resistance in the 384 patients.

From the thesis abstract:

“The findings of our project support the phenomenon of aspirin resistance… Our genotypic findings confirm the presence of SNPs of COX1(rs1330344) and COX2 (rs20147) genes, moreover none of these SNPs contributed in the existence of aspirin resistance in our population.“

Prevalence and Response Rates for COX-1 Variants

The study genotyped all 384 patients, categorizing them based on the rs1330344 SNP:

  • Wild Type (CC): 24.21% of patients (93 individuals)
  • Heterozygous (CT): 57.81% of patients (222 individuals)
  • Homozygous (TT): 17.96% of patients (69 individuals)

Despite the different genetic makeups, the rate of aspirin resistance was remarkably similar across all three groups.

  • CC Group: 14.0% were resistant.
  • CT Group: 14.4% were resistant.
  • TT Group: 11.6% were resistant.

The statistical analysis confirmed that there was no significant difference in aspirin response among these genotypes (p=0.837). This indicates that, within this specific population, the COX-1 polymorphism rs1330344 was not a reliable predictor of aspirin failure. This is a crucial finding, as other studies in different ethnic groups, particularly Chinese populations, had previously suggested a link. This discrepancy highlights that the impact of genetic factors in aspirin response can vary significantly between different populations.

Did COX-2 Genetics (rs20417) Predict Resistance?

While COX-1 is the primary target for antiplatelet therapy, the COX-2 enzyme is also involved in inflammatory and clotting pathways. The study also explored the COX-2 rs20417 polymorphism to see if it influenced aspirin’s effectiveness.

Prevalence and Response Rates for COX-2 Variants

The patient genotypes for the rs20417 SNP were as follows:

  • Wild Type (GG): 55.46% of patients (213 individuals)
  • Heterozygous (CG): 34.11% of patients (131 individuals)
  • Homozygous (CC): 10.41% of patients (40 individuals)

Once again, the results were contrary to what might be expected based on some prior research. The rate of aspirin resistance did not show a clear, statistically significant pattern based on the COX-2 genotype.

  • GG Group: 11.7% were resistant.
  • CG Group: 15.3% were resistant.
  • CC Group: 20.0% were resistant.

Although there was a slight trend towards higher resistance in the CC group, the overall statistical analysis found no significant association between the rs20417 SNP and aspirin resistance (p=0.318). This further reinforces the study’s main conclusion: the pharmacogenetics of aspirin are incredibly complex and population-dependent.

Conclusion: Genetics Are Complex and Population-Specific

The key takeaway from this deep dive into aspirin resistance genetics is that there is no simple answer. In this large-scale study of a Pakistani population, two of the most frequently studied genetic polymorphisms related to aspirin’s mechanism of action—rs1330344 (COX-1) and rs20417 (COX-2)—failed to predict who would be resistant to the drug.

This “null result” is incredibly important. It tells us that:

  1. Aspirin resistance is likely polygenic, meaning it’s influenced by multiple genes, not just one or two.
  2. Environmental factors (like smoking, as shown in the previous post) may play an equal or even greater role than these specific SNPs.
  3. Genetic associations found in one ethnic group may not apply to others. This emphasizes the critical need for diverse, population-specific research before genetic markers can be used for clinical decision-making.

While your DNA contains the blueprint for your body, this study shows that predicting a drug’s effect is far from straightforward. The journey toward truly personalized medicine requires us to appreciate this complexity.

Author Bio: This analysis is based on the doctoral research of Dr. Mudassar Noor, conducted at the Department of Pharmacology & Therapeutics, Army Medical College, a constituent college of the National University of Medical Sciences (NUMS) in Rawalpindi, Pakistan.

Source & Citations

Disclaimer: Some sentences have been lightly edited for SEO and readability. For the full, original research, please refer to the complete thesis PDF.

This research shows how complex genetics can be, with different results in different populations. What do you think this means for the future of personalized medicine? Share your thoughts below!

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