[Population characterization of mutations for sickle cell anemia and its treatment: One step towards personalized medicine for the disease]

Andes Pediatr. 2024 Feb;95(1):41-52. doi: 10.32641/andespediatr.v95i1.4752.
[Article in Spanish]

Abstract

Sickle cell anemia (SCA) is the most common genetic disease worldwide. There are countries with massive public health programs for early detection of this condition. In the literature, several specific haplotypes or single-base polymorphic variants (SNPs) have been associated with the SCA prognosis.

Objective: To demonstrate the significant correlation of SNPs relevant to the diagnosis and prognosis of SCA among different ethnic groups.

Methodology: we analyzed population frequencies and correlations of several SNPs related to the prognosis of SCA (i.e., baseline fetal hemoglobin levels), response to hydroxyurea treatment, and response to other drugs used in the SCA treatment, collected from validated genomic databases among different ethnic groups.

Results: The calculation of the Hardy-Weinberg equilibrium and the logistic regression was successful in classifying the ethnic groups as African (0 = 0.78, 1 = 0.89), and with a lower efficiency as American (AMR) (0 = 0.88, 1 = 0.00), East Asian (EAS) (0 = 0.80, 1 = 0.00), European (EUR) (0 = 0.79, 1 = 0.00), and South Asian (SAS) (0 = 0.80, 1 = 0.00).

Conclusions: The results extend those from previous reports and show that the profile of most of the SNPs studied presented statistically significant distributions among general ethnic groups, pointing to the need to carry out massive early screening of relevant SNPs for SCA in patients diagnosed with this disease. It is concluded that the application of a broad mutation detection program will lead to a more personalized and efficient response in the treatment of SCA.

Publication types

  • English Abstract

MeSH terms

  • Anemia, Sickle Cell* / diagnosis
  • Anemia, Sickle Cell* / genetics
  • Anemia, Sickle Cell* / therapy
  • Ethnicity / genetics
  • Humans
  • Mutation
  • Precision Medicine*
  • Prognosis