Genetic variation in genes involved in folate and drug metabolism in a south Indian population

Background: Genetic variations represented as single nucleotide polymorphisms (SNPs) vary across the world population. This genetic polymorphism (such as SNPs) plays an important role in pharmacogenomics. SNPs that affects cellular metabolism, by altering the enzyme activity, have an important role in therapeutic outcome. Allele frequencies in number of clinically relevant SNPs within south Indian populations are not yet known. Hence, we genotyped randomly selected unrelated south Indian subjects from different locations of south India representing the heterogeneous ethnic background of the population. Materials and Methods: Common variants of MTHFD1, TYMS, SHMT1, MTR, MTRR, CBS and SULT1A1 gene polymorphisms were screened from healthy unrelated south Indian volunteers. Genotypes were determined using RFLP analysis of polymerase chain reaction-amplified products and confirmed by DNA sequencing. Chi-square test was performed to test for deviation from the Hardy-Weinberg equilibrium for each locus. Results: Gene allele frequency for several polymorphisms in our study differed significantly between the populations of other nations reported for several of the SNPs. These results demonstrate that the populations in different geographic regions may have widely varying genetic allele frequencies for clinically relevant SNPs. Conclusion: The present study reports, for the first time, the frequency distribution of MTHFD1, TYMS, SHMT1, MTR, MTRR, CBS and SULTIA1 gene polymorphisms in a south Indian population. Population-specific genetic polymorphism studies will help in practicing pharmacogenomic principles in the clinics

Global comparative transcriptomes uncover novel and population-specific gene expression in esophageal squamous cell carcinoma

Background Esophageal squamous cell carcinoma (ESCC) has a poor prognosis and is one of the deadliest gastrointestinal malignancies. Despite numerous transcriptomics studies to understand its molecular basis, the impact of population-specific differences on this disease remains unexplored.Aims This study aimed to investigate the population-specific differences in gene expression patterns among ESCC samples obtained from six distinct global populations, identify differentially expressed genes (DEGs) and their associated pathways, and identify potential biomarkers for ESCC diagnosis and prognosis. In addition, this study deciphers population specific microbial and chemical risk factors in ESCC.Methods We compared the gene expression patterns of ESCC samples from six different global populations by analyzing microarray datasets. To identify DEGs, we conducted stringent quality control and employed linear modeling. We cross-compared the resulting DEG lists of each populations along with ESCC ATLAS to identify known and novel DEGs. We performed a survival analysis using The Cancer Genome Atlas Program (TCGA) data to identify potential biomarkers for ESCC diagnosis and prognosis among the novel DEGs. Finally, we performed comparative functional enrichment and toxicogenomic analysis.Results Here we report 19 genes with distinct expression patterns among populations, indicating populationspecific variations in ESCC. Additionally, we discovered 166 novel DEGs, such as ENDOU, SLCO1B3, KCNS3, IFI35, among others. The survival analysis identified three novel genes (CHRM3, CREG2, H2AC6) critical for ESCC survival. Notably, our findings showed that ECM-related gene ontology terms and pathways were significantly enriched among the DEGs in ESCC. We also found population-specific variations in immune response and microbial infection-related pathways which included genes enriched for HPV, Ameobiosis, Leishmaniosis, and Human Cytomegaloviruses. Our toxicogenomic analysis identified tobacco smoking as the primary risk factor and cisplatin as the main drug chemical interacting with the maximum number of DEGs across populations.Conclusion This study provides new insights into population-specific differences in gene expression patterns and their associated pathways in ESCC. Our findings suggest that changes in extracellular matrix (ECM) organization may be crucial to the development and progression of this cancer, and that environmental and genetic factors play important roles in the disease. The novel DEGs identified may serve as potential biomarkers for diagnosis, prognosis and treatment.Peer reviewe