Association between intelectin-1 variation and human kidney stone disease in northeastern Thai population

Association of single nucleotide polymorphisms in ITLN1 gene with ischemic stroke risk in Xi'an population, Shaanxi province

Background

Ischemic stroke (IS) is the main cause of death and adult disability. However, the pathogenesis of this complicated disease is unknown. The present study aimed to assess the relationship between ITLN1 single nucleotide polymorphisms (SNPs) and the susceptibility to IS in Xi'an population, Shaanxi province.

Methods

In this study, we designed polymerase chain reaction (PCR) primers located at -3,308 bp upstream of the transcription initiation site within promoter region of the ITLN1 gene. The target fragment was amplified by PCR and identified by agarose gel electrophoresis. Sanger sequencing was then performed in the samples extracted from a cohort comprising 1,272 participants (636 controls and 636 cases), and the obtained sequences were compared with the reference sequences available on the National Center for Biotechnology Information (NCBI) website to detect SNPs in the ITLN1 gene promoter region. Logistic regression analysis was employed to assess the relationship between ITLN1 polymorphisms and IS risk, with adjustments for age and gender. Significant positive results were tested by false-positive report probability (FPRP) and false discovery rate (FDR). The interaction among noteworthy SNPs and their predictive relationship with IS risk were explored using the Multi-Factor Dimensionality Reduction (MDR) software.

Results

The results of Sanger sequencing were compared with the reference sequences on the NCBI website, and we found 14 SNPs in ITLN1 gene promoter satisfied Hardy-Weinberg equilibrium (HWE). Logistic regression analysis showed that ITLN1 was associated with a decreased risk of IS (rs6427553: Homozygous C/C: adjusted OR: 0.69, 95% CI [0.48-0.97]; Log-additive: adjusted OR: 0.83, 95% CI [0.70-0.98]; rs7411035: Homozygous G/G: adjusted OR: 0.66, 95% CI [0.47-0.94]; Dominant G/T-G/G: adjusted OR: 0.78, 95% CI [0.62-0.98]; Log-additive: adjusted OR: 0.81, 95% CI [0.69-0.96]; rs4656958: Heterozygous G/A: adjusted OR: 0.74, 95% CI [0.59-0.94]; Homozygous A/A: adjusted OR: 0.51, 95% CI [0.31-0.84]; Dominant G/A-A/A: adjusted OR: 0.71, 95% CI [0.57-0.89]; Recessive A/A: adjusted OR: 0.59, 95% CI [0.36-0.96]; Log-additive: adjusted OR: 0.73, 95% CI [0.61-0.88]), especially in people aged less than 60 years and males.

Conclusions

In short, our study revealed a correlation between ITLN1 variants (rs6427553, rs7411035 and rs4656958) and IS risk in Xi'an population, Shaanxi province, laying a foundation for ITLN1 gene as a potential biomarker for predicting susceptibility to IS.

Genetics of Chronic Kidney Disease in Low-Resource Settings

Advances in kidney genomics in the past 20 years has opened the door for more precise diagnosis of kidney disease and identification of new and specific therapeutic agents. Despite these advances, an imbalance exists between low-resource and affluent regions of the world. Individuals of European ancestry from the United States, United Kingdom, and Iceland account for 16% of the world's population, but represent more than 80% of all genome-wide association studies. South Asia, Southeast Asia, Latin America, and Africa together account for 57% of the world population but less than 5% of genome-wide association studies. Implications of this difference include limitations in new variant discovery, inaccurate interpretation of the effect of genetic variants in non-European populations, and unequal access to genomic testing and novel therapies in resource-poor regions. It also further introduces ethical, legal, and social pitfalls, and ultimately may propagate global health inequities. Ongoing efforts to reduce the imbalance in low-resource regions include funding and capacity building, population-based genome sequencing, population-based genome registries, and genetic research networks. More funding, training, and capacity building for infrastructure and expertise is needed in resource-poor regions. Focusing on this will ensure multiple-fold returns on investments in genomic research and technology.