Purpose: Genetic variants in cytochrome P450 () platelet membrane receptor ( and glycoprotein IIIa () genes are associated with the efficacy of clopidogrel and adverse clinical events on ischemic stroke (IS) patients. However, few studies have assessed whether gene-gene interactions among these genes influence the risk of IS. The aim of the present study was to investigate the association of fifteen variants with IS and to determine whether these gene-gene interactions increase the risk of IS.
Methods: Fifteen variants in , and genes were examined using mass spectrometry methods in 396 patients with IS and 378 controls. Gene-gene interactions were analyzed using generalized multifactor dimensionality reduction (GMDR) methods.
Results: Single-gene variant analysis showed no significant differences in the genotype distributions of the fifteen variants between IS patients and controls using the single-locus analytical approach. However, GMDR analysis showed a significant gene-gene interaction among rs17110453A>C, rs2317676A>G, and rs16863323C>T, which scored 10 for cross-validation consistency and 9 for the sign test ( = 0.016). Logistic regression analysis showed that high-risk interactions among rs17110453A>C, rs2317676A>G, and rs16863323C>T were independent risk factor for IS after adjusting for age, hypertension, diabetes mellitus, and hemoglobin A1C (=2.24, 95% : 1.17-5.62, =0.005).
Conclusions: The rs17110453A>C, rs2317676A>G, and rs16863323C>T three-loci interaction may confer a higher risk for IS. The combinatorial analysis used in this study may be helpful to elucidate complex genetic risk factors for IS.
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http://dx.doi.org/10.18632/oncotarget.19991 | DOI Listing |
Neurogenetics
January 2025
School of Clinical Medicine, Fujian Medical University, Fuzhou, China.
PLoS One
January 2025
Department of Statistics and Probability, Michigan State University, East Lansing, MI, United States of America.
The genetic basis of complex traits involves the function of many genes with small effects as well as complex gene-gene and gene-environment interactions. As one of the major players in complex diseases, the role of gene-environment interactions has been increasingly recognized. Motivated by epidemiology studies to evaluate the joint effect of environmental mixtures, we developed a functional varying-index coefficient model (FVICM) to assess the combined effect of environmental mixtures and their interactions with genes, under a longitudinal design with quantitative traits.
View Article and Find Full Text PDFBiology (Basel)
January 2025
Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing 100141, China.
The shape of the skull plays a crucial role in the evolution and adaptation of species to their environments. In the case of aquaculture fish, the size of the head is also an important economic trait, as it is linked to fillet yield and ornamental value. This study applies our GRAMMAR-Lambda method to perform a genome-wide association study analysis on loci related to head size in catfish.
View Article and Find Full Text PDFSpatially resolved transcriptomics (SRT) provides an invaluable avenue for examining cell-cell interactions within native tissue environments. The development and evaluation of analytical tools for SRT data necessitate tools for generating synthetic datasets with known ground truth of cell-cell interaction induced features. To address this gap, we introduce sCCIgen, a novel real-data-based simulator tailored to generate high-fidelity SRT data with a focus on cell-cell interactions.
View Article and Find Full Text PDFPLoS One
January 2025
Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Background: Rheumatoid arthritis (RA) is a degenerative autoimmune disease, often managed through symptomatic treatment. The co-occurrence of the reported extra-articular comorbidities such as inflammatory bowel disease (IBD), and dementia may complicate the pathology of the disease as well as the treatment strategies. Therefore, in our study, we aim to elucidate the key genes, and regulatory elements implicated in the progression and association of these diseases, thereby highlighting the linked potential therapeutic targets.
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