The rs1801280 SNP is associated with non-small cell lung carcinoma by exhibiting a highly deleterious effect on N-acetyltransferase 2

The landscape of very important pharmacogenes variants and potential clinical relevance in the Chinese Jingpo population: a comparative study with worldwide populations

BACKGROUND

Pharmacogenomics is a facet of personalized medicine that explores how genetic variants affect drug metabolism and adverse drug reactions. Therefore, this study aims to detect distinct pharmacogenomic variations among the Jingpo population and explore their clinical correlation with drug metabolism and toxicity.

METHODS

Agena MassARRAY Assay was used to genotype 57 VIP variants in 28 genes from 159 unrelated Jingpo participants. Subsequently, the chi-squared test and Bonferroni's statistical tests were utilized to conduct a comparative analysis of genotypes and allele frequencies between the Jingpo population and the other 26 populations from the 1000 Genome Project.

RESULTS

We discovered that the KHV (Kinh in Ho ChiMinh City, Vietnam), CHS (Southern Han Chi-nese, China) and JPT (Japanese in Tokyo, Japan) exhibited the smallest differences from the Jingpo with only 4 variants, while ESN (Esan in Nigeria) exhibited the largest differences with 30 variants. Besides, a total of six considerably different loci (rs4291 in ACE, rs20417 in PTGS2, rs1801280 and rs1799929 in NAT2, rs2115819 in ALOX5, rs1065852 in CYP2D6, p < 3.37 × 10-5) were identified in this study. According to PharmGKB, rs20417 (PTGS2), rs4291 (ACE), rs2115819 (ALOX5) and rs1065852 (CYP2D6) were found to be associated with the metabolism efficiency of non-steroidal anti-inflammatory drugs (NSAIDs), aspirin, montelukast and tamoxifen, respectively. Meanwhile, rs1801280 and rs1799929 (NAT2) were found to be related to drug poisoning with slow acetylation.

CONCLUSION

Our study unveils distinct pharmacogenomic variants in the Jingpo population and discovers their association with the metabolic efficiency of NSAIDs, montelukast, and tamoxifen.

Mastering DNA chromatogram analysis in Sanger sequencing for reliable clinical analysis

BACKGROUND

Sanger dideoxy sequencing is vital in clinical analysis due to its accuracy, ability to analyze genetic markers like SNPs and STRs, capability to generate reliable DNA profiles, and its role in resolving complex clinical cases. The precision and robustness of Sanger sequencing contribute significantly to the scientific basis of clinical investigations. Though the reading of chromatograms seems to be a routine step, many errors conducted in PCR may lead to consequent limitations in the readings of AGCT peaks. These errors are possibly associated with improper DNA amplification and its subsequent interpretation of DNA sequencing files, such as noisy peaks, artifacts, and confusion between double-peak technical errors, heterozygosity, and double infection potentials. Thus, it is not feasible to read nucleic acid sequences without giving serious attention to these technical problems. To ensure the accuracy of DNA sequencing outcomes, it is also imperative to detect and rectify technical challenges that may lead to misinterpretation of the DNA sequence, resulting in errors and incongruities in subsequent analyses.

SHORT CONCLUSION

This overview sheds light on prominent technical concerns that can emerge prior to and during the interpretation of DNA chromatograms in Sanger sequencing, along with offering strategies to address them effectively. The significance of identifying and tackling these technical limitations during the chromatogram analysis is underscored in this review. Recognizing these concerns can aid in enhancing the quality of downstream analyses for Sanger sequencing results, which holds notable improvement in accuracy, reliability, and ability to provide crucial genetic information in clinical analysis.