Dataset Information

Single nucleotide polymorphisms in the ANGPTL4 gene and the SNP-SNP interactions on the risk of atherosclerotic Ischaemic stroke

ABSTRACT:

Objectives

The purpose of this study was to investigate the impact of single nucleotide polymorphisms (SNPs) in the ANGPTL4 gene and the SNP–SNP interactions on atherosclerotic ischemic stroke (IS) risk.

Patients and methods

A case-control study was conducted. A total of 360 patients with atherosclerotic IS and 342 controls between December 2018 and December 2019 from Longyan First Hospital affiliated to Fujian Medical University were included. A logistic regression model was used to examine the association between SNPs and atherosclerotic IS risk. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Generalized multifactor dimensionality reduction was employed to analyze the SNP-SNP interaction.

Results

Logistic regression analysis showed that atherosclerotic IS risk was significantly lower in carriers with the rs11672433-T allele than those with the CC genotype (CT+ TT vs. CC); adjusted OR, 0.005; 95% CI, 0.02–0.11. We found a significant 2-locus model (P?=?0.0010) involving rs11672433 and rs4076317; the cross-validation consistency of this model was 10 of 10, and the testing accuracy was 57.96%. Participants with the CT or TT of rs11672433 and CC of rs4076317 genotype have the lowest atherosclerotic IS risk, compared to subjects with CC of rs11672433 and the CC of rs4076317 genotype, OR (95%CI) was 0.06(0.02–0.22), after covariates adjustment for gender, age, smoking and alcohol status, hypertension, Diabetes mellitus, TG, TC, HDL-C, LDL-C, Uric acid.

Conclusions

We found that rs11672433 was associated with decreased atherosclerotic IS risk; we also found that gene–gene interaction between rs11672433 and rs4076317 was associated with decreased atherosclerotic IS risk.

SUBMITTER: Shen C

PROVIDER: S-EPMC7941969 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J) has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci (<10 Mb) the identification of candidate functional DNA sequence changes remains challenging due to the high density of sequence variation between strains.DescriptionTo help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs) that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at http://bioinfo.embl.it/SnpApplet/). For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function.ConclusionWe have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously uncharacterized QTL for response to morphine in the 129/Sv strain.

Project description:Surfactant proteins (SPs) are important for normal lung function and innate immunity of the lungs and their genes have been identified with significant genetic variability. Changes in quantity or quality of SPs due to genetic mutations or natural genetic variability may alter their functions and contribute to the host susceptibility for particular diseases. Alternatively, SP single nucleotide polymorphisms (SNPs) can serve as markers to identify disease risk or response to therapies, as shown for other genes in a number of other studies. In the current study, we evaluated associations of SFTP SNPs with idiopathic pulmonary fibrosis (IPF) by studying novel computational models where the epistatic effects (dominant, additive, recessive) of SNP-SNP interactions could be evaluated, and then compared the results with a previously published hypersensitivity pneumonitis (HP) study where the same novel models were used. Mexican Hispanic patients (IPF=84 & HP=75) and 194 healthy control individuals were evaluated. The goal was to identify SP SNPs and SNP-SNP interactions that associate with IPF as well as SNPs and interactions that may be unique to each of these interstitial diseases or common between them. We observed: 1) in terms of IPF, i) three single SFTPA1 SNPs to associate with decreased IPF risk, ii) three SFTPA1 haplotypes to associate with increased IPF risk, and iii) a number of three-SNP interactions to associate with IPF susceptibility. 2) Comparison of IPF and HP, i) three SFTPA1 and one SFTPB SNP associated with decreased risk in IPF but increased risk in HP, and one SFTPA1 SNP associated with decreased risk in both IPF and HP, ii) a number of three-SNP interactions with the same or different effect pattern associated with IPF and/or HP susceptibility, iii) one of the three-SNP interactions that involved SNPs of SFTPA1, SFTPA2, and SFTPD, with the same effect pattern, was associated with a disease-specific outcome, a decreased and increased risk in HP and IPF, respectively. This is the first study that compares the SP gene variants in these two phenotypically similar diseases. Our findings indicate that SNPs of all SFTPs may play an important role in the genetic susceptibility to IPF and HP. Importantly, IPF and HP share some SP genetic variants, suggesting common pathophysiological mechanisms and pathways regarding surfactant biogenesis, but also some differences, highlighting the diverse underlying pathogenic mechanisms between an inflammatory-driven fibrosis (HP) and an epithelial-driven fibrosis (IPF). Alternatively, the significant SNPs identified here, along with SNPs of other genes, could serve as markers to distinguish these two devastating diseases.