Multiple Single Nucleotide Polymorphisms Research Articles

Natural selection on feralization genes contributed to the invasive spread of wild pigs throughout the United States.

Despite a long presence in the contiguous United States (US), the distribution of invasive wild pigs (Sus scrofa × domesticus) has expanded rapidly since the 1980s, suggesting a more recent evolutionary shift towards greater invasiveness. Contemporary populations of wild pigs represent exoferal hybrid descendants of domestic pigs and European wild boar, with such hybridization expected to enrich genetic diversity and increase the adaptive potential of populations. Our objective was to characterize how genetic enrichment through hybridization increases the invasiveness of populations by identifying signals of selection and the ancestral origins of selected loci. Our study focused on invasive wild pigs within Great Smoky Mountains National Park, which represents a hybrid population descendent from the admixture of established populations of feral pigs and an introduction of European wild boar to North America. Accordingly, we genotyped 881 wild pigs with multiple high-density single-nucleotide polymorphism (SNP) arrays. We found 233 markers under putative selection spread over 79 regions across 16 out of 18 autosomes, which contained genes involved in traits affecting feralization. Among these, genes were found to be related to skull formation and neurogenesis, with two genes, TYRP1 and TYR, also encoding for crucial melanogenesis enzymes. The most common haplotypes associated with regions under selection for the Great Smoky Mountains population were also common among other populations throughout the region, indicating a key role of putatively selective variants in the fitness of invasive populations. Interestingly, many of these haplotypes were absent among European wild boar reference genotypes, indicating feralization through genetic adaptation.

Novel progressive deep learning algorithm for uncovering multiple single nucleotide polymorphism interactions to predict paclitaxel clearance in patients with nonsmall cell lung cancer

AbstractBackgroundThe rate at which the anticancer drug paclitaxel is cleared from the body markedly impacts its dosage and chemotherapy effectiveness. Importantly, paclitaxel clearance varies among individuals, primarily because of genetic polymorphisms. This metabolic variability arises from a nonlinear process that is influenced by multiple single nucleotide polymorphisms (SNPs). Conventional bioinformatics methods struggle to accurately analyze this complex process and, currently, there is no established efficient algorithm for investigating SNP interactions.MethodsWe developed a novel machine‐learning approach called GEP‐CSIs data mining algorithm. This algorithm, an advanced version of GEP, uses linear algebra computations to handle discrete variables. The GEP‐CSI algorithm calculates a fitness function score based on paclitaxel clearance data and genetic polymorphisms in patients with nonsmall cell lung cancer. The data were divided into a primary set and a validation set for the analysis.ResultsWe identified and validated 1184 three‐SNP combinations that had the highest fitness function values. Notably, SERPINA1, ATF3 and EGF were found to indirectly influence paclitaxel clearance by coordinating the activity of genes previously reported to be significant in paclitaxel clearance. Particularly intriguing was the discovery of a combination of three SNPs in genes FLT1, EGF and MUC16. These SNPs‐related proteins were confirmed to interact with each other in the protein–protein interaction network, which formed the basis for further exploration of their functional roles and mechanisms.ConclusionWe successfully developed an effective deep‐learning algorithm tailored for the nuanced mining of SNP interactions, leveraging data on paclitaxel clearance and individual genetic polymorphisms.

Exploring the causality between intestinal flora and hyperplastic scars of human based on two-sample Mendelian randomization analysis

Objective: To investigate the causality between intestinal flora and hypertrophic scars (HS) of human. Methods: This study was a study based on two-sample Mendelian randomization (TSMR) analysis. The data on intestinal flora (n=18 473) and HS (n=208 248) of human were obtained from the genome-wide association study database. Genetically variable genes at five levels (phylum, class, order, family, and genus) of known intestinal flora, i.e., single nucleotide polymorphisms (SNPs), were extracted as instrumental variables for linkage disequilibrium (LD) analysis. Human genotype-phenotype association analysis was performed using PhenoScanner V2 database to exclude SNPs unrelated to HS in intestinal flora and analyze whether the selected SNPs were weak instrumental variables. The causal relationship between intestinal flora SNPs and HS was analyzed through four methods of TSMR analysis, namely inverse variance weighted (IVW), MR-Egger regression, weighted median, and weighted mode. Scatter plots of significant results from the four aforementioned analysis methods were plotted to analyze the correlation between intestinal flora SNPs and HS. Both IVW test and MR-Egger regression test were used to assess the heterogeneity of intestinal flora SNPs, MR-Egger regression test and MR-PRESSO outlier test were used to assess the horizontal multiplicity of intestinal flora SNPs, and leave-one-out sensitivity analysis was used to determine whether HS was caused by a single SNP in the intestinal flora. Reverse TSMR analyses were performed for HS SNPs and genus Intestinimonas or genus Ruminococcus2, respectively, to detect whether there was reverse causality between them. Results: A total of 196 known intestinal flora, belonging to 9 phyla, 16 classes, 20 orders, 32 families, and 119 genera, were obtained, and multiple SNPs were obtained from each flora as instrumental variables. LD analysis showed that the SNPs of the intestinal flora were consistent with the hypothesis that genetic variation was strongly associated with exposure factors, except for rs1000888, rs12566247, and rs994794. Human genotype-phenotype association analysis showed that none of the selected SNPs after LD analysis was excluded and there were no weak instrumental variables. IVW, MR-Egger regression, weighted median, and weighted mode of TSMR analysis showed that both genus Intestinimonas and genus Ruminococcus2 were causally associated with HS. Among them, forest plots of IVW and MR-Egger regression analyses also showed that 16 SNPs (the same SNPs number of this genus below) of genus Intestinimonas and 15 SNPs (the same SNPs number of this genus below) of genus Ruminococcus2 were protective factors for HS. Further, IVW analysis showed that genus Intestinimonas SNPs (with odds ratio of 0.62, 95% confidence interval of 0.41-0.93, P<0.05) and genus Ruminococcus2 SNPs (with odds ratio of 0.62, 95% confidence interval of 0.40-0.97, P<0.05) were negatively correlated with the risk of HS. Scatter plots showed that SNPs of genus Intestinimonas and genus Ruminococcus2 were protective factors of HS. Both IVW test and MR-Egger regression test showed that SNPs of genus Intestinimonas (with Q values of 5.73 and 5.76, respectively, P>0.05) and genus Ruminococcus2 (with Q values of 13.67 and 15.61, respectively, P>0.05) were not heterogeneous. MR-Egger regression test showed that the SNPs of genus Intestinimonas and genus Ruminococcus2 had no horizontal multiplicity (with intercepts of 0.01 and 0.06, respectively, P>0.05); MR-PRESSO outlier test showed that the SNPs of genus Intestinimonas and genus Ruminococcus2 had no horizontal multiplicity (P>0.05). Leave-one-out sensitivity analysis showed that no single intestinal flora SNP drove the occurrence of HS. Reverse TSMR analysis showed no reverse causality between HS SNPs and genus Intestinimonas or genus Ruminococcus2 (with odds ratios of 1.01 and 0.99, respectively, 95% confidence intervals of 0.97-1.06 and 0.96-1.04, respectively, P>0.05). Conclusions: There is a causal relationship between intestinal flora and HS of human, in which genus Intestinimonas and genus Ruminococcus2 have a certain effect on inhibiting HS.

Genome-wide sequencing reveals geographical variations in the thermal adaptation of an aquaculture species with frequent seedling introductions

Climate change and human activity are essential factors affecting marine biodiversity and aquaculture, and understanding the impacts of human activities on the genetic structure to increasing high temperatures is crucial for sustainable aquaculture and marine biodiversity conservation. As a commercially important bivalve, the Manila clam Ruditapes philippinarum is widely distributed along the coast of China, and it has been frequently introduced from Fujian Province, China, to other regions for aquaculture. In this study, we collected four populations of Manila clams from different areas to evaluate their thermal tolerance by measuring cardiac performance and genetic variations using whole-genome resequencing. The upper thermal limits of the clams showed high variations within and among populations. Different populations displayed divergent genetic compositions, and the admixed population was partly derived from the Zhangzhou population in Fujian Province, implying a complex genomic landscape under the influence of local genetic sources and human introductions. Multiple single nucleotide polymorphisms (SNPs) were associated with the cardiac functional traits, and some of these SNPs can affect the codon usage and the structural stability of the resulting protein. This study shed light on the importance of establishing long-term ecological and genetic monitoring programs at the local level to enhance resilience to future climate change.

Modifying Effects of Genetic Variations on the Association Between Dietary Isothiocyanate Exposure and Non-muscle Invasive Bladder Cancer Prognosis in the Be-Well Study.

Dietary isothiocyanate (ITC) exposure from cruciferous vegetable (CV) intake may improve non-muscle invasive bladder cancer (NMIBC) prognosis. This study aims to investigate whether genetic variations in key ITC-metabolizing/functioning genes modify the associations between dietary ITC exposure and NMIBC prognosis outcomes. In the Bladder Cancer Epidemiology, Wellness, and Lifestyle Study (Be-Well Study), a prospective cohort of 1472 incident NMIBC patients, dietary ITC exposure is assessed by self-reported CV intake and measured in plasma ITC-albumin adducts. Using Cox proportional hazards regression models, stratified by single nucleotide polymorphisms (SNPs) in nine key ITC-metabolizing/functioning genes, it is calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for recurrence and progression. The rs15561 in N-acetyltransferase 1 (NAT1) is alter the association between CV intake and progression risk. Multiple SNPs in nuclear factor E2-related factor 2 (NRF2) and nuclear factor kappa B (NFκB) are modify the associations between plasma ITC-albumin adduct level and progression risk (pint < 0.05). No significant association is observed with recurrence risk. Overall, >80% study participants are present with at least one protective genotype per gene, showing an average 65% reduction in progression risk with high dietary ITC exposure. Despite that genetic variations in ITC-metabolizing/functioning genes may modify the effect of dietary ITCs on NMIBC prognosis, dietary recommendation of CV consumption may help improve NMIBC survivorship.

Detection of Single Nucleotide Polymorphisms of Circulating Tumor DNA by Strand Displacement Amplification Coupled with Liquid Chromatography.

The detection of multiple single nucleotide polymorphisms (SNPs) of circulating tumor DNA (ctDNA) is still a great challenge. In this study, we designed enzyme-assisted nucleic acid strand displacement amplification combined with high-performance liquid chromatography (HPLC) for the simultaneous detection of three ctDNA SNPs. First, the trace ctDNA could be hybridized to the specially designed template strand, which initiated the strand displacement nucleic acid amplification process under the synergistic action of DNA polymerase and restriction endonuclease. Then, the targets would be replaced with G-quadruplex fluorescent probes with different tail lengths. Finally, the HPLC-fluorescence assay enabled the separation and quantification of multiple signals. Notably, this method can simultaneously detect both the wild type (WT) and mutant type (MT) of multiple ctDNA SNPs. Within a linear range of 0.1 fM-0.1 nM, the detection limits of BRAF V600E-WT, EGFR T790M-WT, and KRAS 134A-WT and BRAF V600E-MT, EGFR T790M-MT, and KRAS 134A-MT were 29, 31, and 11 aM and 22, 29, and 33 aM, respectively. By using this method, the mutation rates of multiple ctDNA SNPs in blood samples from patients with lung or breast cancer can be obtained in a simple way, providing a convenient and highly sensitive analytical assay for the early screening and monitoring of lung cancer.

NEW MULTIPLEX SNP GENOTYPING ASSAY TO SIMUTANEOUSLY SCREEN FOR EIGHT VOLTAGE-GATED SODIUM CHANNEL MUTATIONS IN AEDES AEGYPTI

Aedes aegypti has been implicated as the vector responsible for transmission of dengue, chikungunya, and Zika viruses during disease outbreaks in Florida within the past 15 years. Recently, locally acquired dengue cases have increased dramatically, with more than 450 cases documented in Florida since 2019. This mosquito is known to be resistant to pyrethroid-based insecticides in Florida. Resistance of insects to pyrethroids due to knockdown resistance (kdr) is the result of single nucleotide polymorphisms (SNPs) in the voltage-gated sodium channel gene (vgsc). Recently, two novel SNPs, F174I and E478K, and four known SNPs, V410L, S723T, D1763Y, and Q1853R were reported circulating in Floridian Ae. aegypti populations for the first time. The present study provides a more comprehensive estimate of these SNP frequencies through the screening of a larger number of Floridian Ae. aegypti samples using a new custom multiplex SNP assay we developed using the Agena Biosciences iPLEX Assay platform to facilitate the rapid screening of multiple SNPs at an affordable cost. Our assay was successful in screening 162 Ae. aegypti mosquitoes for 8 SNPs from 4 counties in Southern Florida (Broward, Collier, Palm Beach, and Monroe Counties). This new assay can be used for studies examining the association between genetic mutations and pyrethroid-resistant phenotypes in Ae. aegypti populations such as increased time of survival after insecticide exposure.

Association between multiple sclerosis and cancer risk: A two-sample Mendelian randomization study.

Multiple Sclerosis (MS) is an immune-related disease and the relationship between MS and cancer has raised attention. Previous studies of the relationship between MS and cancer have reached conflicting conclusions. In this study, the two-sample MR method is used to investigate whether MS has a causal correlation with cancers and offer scientific evidence for cancer prevention. Single nucleotide polymorphisms (SNPs) related to MS were obtained from the genome-wide association study (GWAS) based on International Multiple Sclerosis Genetics Consortium (IMSGC) and SNPs related to 15 types of cancers were obtained from the GWASs based on UK Biobank. Inverse variance weighted (IVW) method was mainly used to assess causal effects. Sensitivity analyses were conducted with Cochran's Q-test, MR Egger intercept, leave-one-out test, and MR Steiger method. IVW analysis showed that MS was only associated with a marginal increased risk of cervical cancer (OR 1.0004, 95% CI 1.0002-1.0007, p = 0.0003). Sensitivity analyses showed that the results of MR analysis were robust and found no heterogeneity, no pleiotropy, and no reverse causation. In conclusion, this study finds no causal relationship between MS and 15 types of cancers except cervical cancer.

DeepRisk: A deep learning approach for genome-wide assessment of common disease risk

The potential for being able to identify individuals at high disease risk solely based on genotype data has garnered significant interest. Although widely applied, traditional polygenic risk scoring methods fall short, as they are built on additive models that fail to capture the intricate associations among single nucleotide polymorphisms (SNPs). This presents a limitation, as genetic diseases often arise from complex interactions between multiple SNPs. To address this challenge, we developed DeepRisk, a biological knowledge-driven deep learning method for modeling these complex, nonlinear associations among SNPs, to provide a more effective method for scoring the risk of common diseases with genome-wide genotype data. Evaluations demonstrated that DeepRisk outperforms existing PRS-based methods in identifying individuals at high risk for four common diseases: Alzheimer's disease, inflammatory bowel disease, type 2 diabetes, and breast cancer.

Genetic variants in the 6p21.3 region influence hepatitis B virus clearance and chronic hepatitis B risk in the Han Chinese population

Background and aimA genome-wide association study has indicated the association of numerous genes in the 6p21.3 region with chronic hepatitis B virus (HBV) infection. In this study, we screened 12 representative single-nucleotide polymorphisms (SNPs) from the 6p21.3 region and investigated their association with the risk of chronic hepatitis B (CHB) to better understand the molecular etiology underlying CHB risk in the Han Chinese population. MethodsBetween March 2021 and November 2022, we included 183 patients with CHB (case group) and 196 with natural HBV clearance (control group). Allele typing of the selected SNPs was performed using snapshot technology. The correlation between the 12 chosen SNPs and the risk of chronic HBV infection was examined using binary logistic regression analysis. Interacting genes of the variants were identified, and expression quantitative trait loci (eQTL) were analyzed using the 3DSNP database. ResultsWe validated 12 previously reported CHB susceptibility sites, including rs1419881 of transcription factor 19 (TCF19), rs3130542 and rs2853953 of human leukocyte antigen (HLA)-C, rs652888 of euchromatic histone-lysine-methyltransferase 2 (EHMT2), rs2856718, rs9276370, rs7756516, and rs7453920 of HLA-DQ, rs378352 of HLA-DOA, and rs3077, rs9277535, and rs9366816 of HLA-DP. Logistic regression analyses revealed that polymorphisms such as rs9276370, rs7756516, rs7453920, rs3077, rs9277535, and rs9366816 were positively correlated with natural HBV clearance in the dominant model. Conversely, rs3130542 and rs378352 were identified as risk factors for CHB. Haplotype analysis revealed that rs9276370, rs7756516, and rs7453920 in HLA-DQ were TTG and GCA haplotypes. Although the TTG haplotype was positively correlated with a higher risk of CHB, the GCA haplotype significantly influenced the natural clearance of HBV. Bioinformatics analysis demonstrated that rs378352, rs3077, and rs9366816 were located within enhancer states; rs3077 and rs9366816 overlapped with nine transcription factor-binding sites, whereas rs378352 altered five sequence motifs. Furthermore, eQTL analysis demonstrated the functional tendencies of eight statistically significant SNPs (rs3130542, rs9276370, rs7756516, rs7453920, rs378352, rs3077, rs9277535, and rs9366816). ConclusionsGenetic variations within the 6p21.3 region were associated with chronic HBV infection in the Han Chinese population in southern China. Furthermore, the GCA haplotype including rs9276370, rs7756516, and rs7453920 of HLA-DQ contributed significantly to natural HBV clearance, implying that multiple SNPs exert a cumulative allelic effect on HBV infection.

Interaction of genetic variation at ADH1B and MLXIPL with alcohol consumption for elevated serum urate level and gout among people of European ethnicity

BackgroundAlcohol consumption is a risk factor for hyperuricaemia and gout. Multiple single-nucleotide polymorphisms (SNPs) have been identified as associated with both alcohol consumption and serum urate or gout in separate genome-wide association studies (GWAS). This study aimed to identify and characterise interactions between these shared signals of genetic association and alcohol consumption for serum urate level, hyperuricaemia, and gout.MethodsThis research was conducted using the UK Biobank resource. The association of alcohol consumption with serum urate and gout was tested among 458,405 European participants. Candidate SNPs were identified by comparing serum urate, gout, and alcohol consumption GWAS for shared signals of association. Multivariable-adjusted linear and logistic regression analyses were conducted with the inclusion of interaction terms to identify SNP-alcohol consumption interactions for association with serum urate level, hyperuricaemia, and gout. The nature of these interactions was characterised using genotype-stratified association analyses.ResultsAlcohol consumption was associated with elevated serum urate and gout. For serum urate level, non-additive interactions were identified between alcohol consumption and rs1229984 at the ADH1B locus (P = 3.0 × 10−44) and rs6460047 at the MLXIPL locus (P = 1.4 × 10−4). ADH1B also demonstrated interaction with alcohol consumption for hyperuricaemia (P = 7.9 × 10−13) and gout (P = 8.2 × 10−9). Beer intake had the most significant interaction with ADH1B for association with serum urate and gout among men, while wine intake had the most significant interaction among women. In the genotype-stratified association analyses, ADH1B and MLXIPL were associated with serum urate level and ADH1B was associated with hyperuricaemia and gout among consumers of alcohol but not non-consumers.ConclusionsIn this large study of European participants, novel interactions with alcohol consumption were identified at ADH1B and MLXIPL for association with serum urate level and at ADH1B for association with hyperuricaemia and gout. The association of ADH1B with serum urate and gout may occur through the modulation of alcohol metabolism rate among consumers of alcohol.

Genome-Wide Interaction Study of Dietary Intake and Colorectal Cancer Risk in the UK Biobank

Candidate gene analysis approaches have shown that colorectal cancer (CRC) risk attributable to diet may differ according to genotype. A genome-wide approach further allows for the exploration of underlying pathways for associations between diet and CRC risk across the genome. To identify genetic variants that modify diet-CRC associations and to further explore the underlying pathways in the cause of CRC. This nested case-control study used data on White British participants from the prospective cohort UK Biobank. Participants were recruited between March 13, 2006, and October 1, 2010, and data were censored June 25, 2021. The average frequency intake of 11 dietary factors in the year preceding baseline was obtained via a touchscreen questionnaire. After quality control for more than 93 million variants of imputed genetic data, 4 122 345 variants remained. Colorectal cancer cases were identified according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Genome-wide interaction analysis was performed to test interactions between dietary factors and variants using a conditional logistic regression model. Summary statistics of interactions at the variant level were used to calculate empirical P values for interactions at gene and gene-set levels in gene-based and gene-set enrichment analyses. A total of 4686 participants with CRC (mean [SD] age, 60.7 [6.6] years; 2707 men [57.8%]) received a new diagnosis during a median of 12.4 years (IQR, 11.6-13.1 years) of follow-up. Once a case was detected, 3 matched controls were identified, for a total of 14 058 controls (mean [SD] age, 60.4 [6.6] years; 8121 men [57.8%]). A total of 324 variants were identified that interacted with diet consumption at the suggestive threshold (P < 1 × 10-5). In gene-based analysis, aggregation of multiple EPDR1 gene variants was found to interact with fish intake regarding CRC risk. Furthermore, gene-set enrichment analysis found that several sets of protein-coding genes, which were overrepresented with particular functions and pathways, interacted with the consumption of milk (ART), cheese (OR), tea (KRT), and alcohol (PRM and TNP). In this nested case-control study, the risk of CRC associated with fish intake was modified by multiple single-nucleotide polymorphisms of the EPDR1 gene. The findings further suggested possible functions and pathways that might link the consumption of milk, cheese, tea, and alcohol with CRC development.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study.

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

A novel AllGlo probe-quantitative PCR method for detecting single nucleotide polymorphism in CYP2C19 to evaluate the antiplatelet activity of clopidogrel

CYP2C19 gene has multiple single nucleotide polymorphism (SNP), which is the major determinant for clopidogrel treatment responses. Therefore, CYP2C19 SNP detection is essential for predicting clopidogrel efficacy. Currently, there is still no quick and effective method for routine detection of common CYP2C19 SNPs in clinical laboratories, which is critically needed prior to clopidogrel treatment. AllGlo™ based quantitative PCR was used to develop a novel genotyping method for CYP2C19 SNP detection, termed CyPAllGlo. The performance of CyPAllGlo was compared with that of the commonly used fluorescence in situ hybridization (FISH) method, and the data was verified by DNA sequencing. CyPallGlo was used to identify CYP2C19 polymorphisms in 363 patients with coronary heart disease. The univariate analysis was used to access the antiplatelet efficacy of clopidogrel in patients. The associations between CYP2C19 polymorphisms and clopidogrel efficacy were analyzed. Using CyPAllGlo to detect CYP2C19*2 and CYP2C19*3 alleles was highly specific and fast. The detection limit was approximately 0.07 µg/µl and 0.7 µg/µl for CYP2C19*2 and CYP2C19*3, respectively. The consistency between FISH and CyPAllGlo were 98.07% for CYP2C19*2 and 99.17% for CYP2C19*3. DNA sequencing showed that the accuracy of CyPAllGlo was 100%. The analysis time for the whole CyPAllGlo procedure was approximately 60 min. Univariate analysis showed that the anticoagulation efficacy of clopidogrel was related to patient age, CYP2C19 genotype, metabolic phenotype, and LDL level. The logistic regression analysis showed that the genotype of CYP2C19 and metabolic phenotype was the two risk factors for clopidogrel antiplatelet ineffectiveness. This novel CyPAllGlo is a rapid and accurate method for detection of CYP2C19 SNP. The specificity and consistency of CyPAllGlo are comparable with that of widely used DNA sequencing. These findings provide valuable rapid method for predicting clopidogrel efficacy, which can be quickly translated to improve personalized precision medicine for coronary heart disease treatment.

P1196 Genomic structural variation and polygenic risk score for Inflammatory Bowel Disease

Abstract Background Genome-wide association studies (GWAS) of patients with inflammatory bowel disease (IBD) have identified multiple single-nucleotide polymorphisms (SNPs) and genetic variants involving structural changes in the DNA sequence. SNPs and structural variants (SVs) can play a crucial role in IBD pathogenesis. In this study, we evaluated large deletions induced by SVs in patients with IBD. Additionally, we evaluated the ethnic contribution to a polygenic risk score (PRS) for IBD. Methods Seventy-five Patients with IBD of Korean ancestry from Seoul National University Bundang Hospital (SNUBH) were subjected to whole-genome sequencing (49 patients with UC and 26 patients with CD). SVs involving large deletions were detected and analyzed by using the Genome Aggregation Database (gnomAD) and AnnotSV. The SVs were prioritized based on a list of 241 IBD-associated SNPs identified in the previous GWAS. The prediction performance of European- and Korean-derived PRSs for IBD was also evaluated. For calculating PRS, we applied previously published models derived from the European and Korean populations, respectively, and used Korean Genome and Epidemiology Study (KoGES) database as the Korean controls. Results We found a total of 146 SVs involving large deletions in the IBD cohort. Among them, 10 SVs were annotated as likely pathogenic, according to AnnotSV and American College of Medical Genetics and Genomics guidelines; 24 SVs had the probability of being loss-of-function intolerant (pLI ≥ 0.9). We found that the frequency of large deletions that overlapped with the regions coding NOTCH1, HGF, PTPN2, and SENP7 were rare in the IBD cohort compared to the gnomAD population (Table). The large deletions that overlapped with the regions coding IL2RA, ITGA4, BANK1, and STAT3 were identified in the IBD cohort but not in the gnomAD population. The PRS for IBD in the IBD cohort was significantly higher than that in the Korean controls under the Korean- or European-derived model (Figure A). However, the PRSs for CD or UC were not able to distinguish patients with CD and UC in the IBD cohort (Figure B and C). Conclusion Our finding suggests that SVs involving large deletion may be an important genomic variability in predicting the development of IBD. The PRS for IBD can predict IBD development without ethnic specificity.

Association between PRKG1 Gene and Gene-Environment Interactions with Pediatric Asthma

ABSTRACT Objective To investigate the relationship between single nucleotide polymorphisms (SNPs) of cGMP-dependent protein kinase I (PRKG1) gene and gene-environment interactions with bronchial asthma in children. Methods 109 asthma patients and 158 healthy controls from the General Hospital of Northern Theater Command were enrolled, based case–control study. The iMLDR® multiple SNP typing technique was applied to detect the genotypes of rs7903366, rs7081864, rs7070958 and rs7897633 in PRKG1 gene. The percentage of eosinophils (EOS%) in peripheral blood and serum immunoglobulin E (IgE) in the case group were also measured. Gene-environment interactions were examined using the generalized multi-factor dimensionality reduction (GMDR) method. Results There were polymorphisms in four SNPs of PRKG1 gene in the case and control groups. The genotype and allele frequencies distribution of rs7897633 demonstrated statistical significance (p < 0.05). There were no statistically significant differences in EOS% and IgE among genotypes at the four SNPs of PRKG1 gene (p > 0.05). The haplotypes CAGA and TGAC presented significant association with asthma risk (p < 0.05). The four-factor model indicated a potential gene-environment interaction in rs7897633, allergen exposure, residence, and environmental tobacco smoke (ETS) exposure (p < 0.05). Conclusions The rs7897633 in PRKG1 gene was associated with susceptibility to childhood asthma, and C allele is a protective factor. The haplotype CAGA had a protective effect against asthma risk and TGAC was linked to the high risk of developing asthma. Moreover, the interaction of rs7897633, allergen exposure, residence, and ETS exposure conferred susceptibility to childhood asthma.

Genome-wide functional integration identified MAZ-controlled RPS14 dysregulation in hepatocellular carcinoma.

Chronic infection with Hepatitis B virus (HBV) significantly increases the risk of hepatocellular carcinoma (HCC), particularly in Eastern Asia. However, only a subset of individuals with chronic HBV infection develop HCC, suggesting the role for genetic factors in HCC etiology. Despite genome-wide association studies (GWASs) identifying multiple single nucleotide polymorphisms (SNPs) associated with HBV-related HCC susceptibility, the underlying mechanisms and causal genetic polymorphisms remain largely unclear. To address this, we developed The Updated Integrative Functional Genomics Approach (TUIFGA), an methodology that combines data from transcription factor (TF) cistromics, ATAC-seq, DNAase-seq, and the 1000 Genomes Project to identify cancer susceptibility SNPs within TF-binding sites across human genome. Using TUIFGA, we discovered SNP rs13170300 which located in the TF MAZ binding motif of RPS14. The RPS14 rs13170300 was significantly associated with HCC risk in two case-control sets, with the T allele as the protective allele (Shandong discovery set: TT OR = 0.60, 95% CI = 0.49-0.74, P = 1.0 × 10-6; CT OR = 0.69, 95% CI = 0.55-0.86, P = 0.001; Jiangsu validation set: TT OR = 0.70, 95% CI = 0.56-0.87, P = 0.001; CT OR = 0.65, 95% CI = 0.53-0.82, P = 1.6 × 10-4). SNP rs13170300 affected MAZ binding in the RPS14 promoter, resulting in allele-specific changes in gene expression. RPS14 functions as a novel oncogene in HCC, specifically via activating the AKT signaling. Our findings present important insights into the functional genetics underlying HBV-related HCC development and may contribute to personalized approaches for cancer prevention and novel therapeutics.

Phage-driven coevolution reveals trade-off between antibiotic and phage resistance in Salmonella anatum.

Phage therapy faces challenges against multidrug-resistant (MDR) Salmonella due to rapid phage-resistant mutant emergence. Understanding the intricate interplay between antibiotics and phages is essential for shaping Salmonella evolution and advancing phage therapy. In this study, MDR Salmonella anatum (S. anatum) 2089b coevolved with phage JNwz02 for 30 passages (60days), then the effect of coevolution on the trade-off between phage and antibiotic resistance in bacteria was investigated. Our results demonstrated antagonistic coevolution between bacteria and phages, transitioning from arms race dynamics (ARD) to fluctuating selection dynamics (FSD). The fitness cost of phage resistance, manifested as reduced competitiveness, was observed. Bacteria evolved phage resistance while simultaneously regaining sensitivity to amoxicillin, ampicillin, and gentamicin, influenced by phage selection pressure and bacterial competitiveness. Moreover, the impact of phage selection pressure on the trade-off between antibiotic and phage resistance was more pronounced in the ARD stage than in the FSD stage. Whole genome analysis revealed mutations in the btuB gene in evolved S. anatum strains, with a notably higher mutation frequency in the ARD stage compared to the FSD stage. Subsequent knockout experiments confirmed BtuB as a receptor for phage JNwz02, and the deletion of btuB resulted in reduced bacterial competitiveness. Additionally, the mutations identified in the phage-resistant strains were linked to multiple single nucleotide polymorphisms (SNPs) associated with membrane components. This correlation implies a potential role of these SNPs in reinstating antibiotic susceptibility. These findings significantly advance our understanding of phage-host interactions and the impact of bacterial adaptations on antibiotic resistance.

Altered larval activation response associated with multidrug resistance in the canine hookworm Ancylostoma caninum.

Parasitic gastrointestinal nematodes pose significant health risks to humans, livestock, and companion animals, and their control relies heavily on the use of anthelmintic drugs. Overuse of these drugs has led to the emergence of resistant nematode populations. Herein, a naturally occurring isolate (referred to as BCR) of the dog hookworm, Ancylostoma caninum, that is resistant to 3 major classes of anthelmintics is characterized. Various drug assays were used to determine the resistance of BCR to thiabendazole, ivermectin, moxidectin and pyrantel pamoate. When compared to a drug-susceptible isolate of A. caninum, BCR was shown to be significantly resistant to all 4 of the drugs tested. Multiple single nucleotide polymorphisms have been shown to impart benzimidazole resistance, including the F167Y mutation in the β-tubulin isotype 1 gene, which was confirmed to be present in BCR through molecular analysis. The frequency of the resistant allele in BCR was 76.3% following its first passage in the lab, which represented an increase from approximately 50% in the founding hookworm population. A second, recently described mutation in codon 134 (Q134H) was also detected at lower frequency in the BCR population. Additionally, BCR exhibits an altered larval activation phenotype compared to the susceptible isolate, suggesting differences in the signalling pathways involved in the activation process which may be associated with resistance. Further characterization of this isolate will provide insights into the mechanisms of resistance to macrocyclic lactones and tetrahydropyrimidine anthelmintics.

Association Between Multiple Single Nucleotide Polymorphisms in Folate Metabolism Pathway and Breast Cancer Risk in Georgian Women: A Case-Control Study.

The folate metabolism pathway plays an integral part in DNA synthesis, methylation, and repair. Methylenetetrahydrofolate reductase (MTHFR) and methylenetetrahydrofolate dehydrogenase (MTHFD1) are both enzymes that are involved in this pathway, and the single nucleotide polymorphisms (SNPs) in genes coding for them have modulatory effects on DNA expression. This study aimed to investigate the relationship between MTHFR C677T (rs1801133) and MTHFD1 G1958A (rs2236225) polymorphisms and the risk of developing breast cancer in Georgian women. A case-control study was performed examining the MTHFR C677T and MTHFD1 G1958A SNP in breast cancer-confirmed cases and healthy matched controls. Real time-polymerase chain reaction (PCR) was used to genotype SNPs. The case individuals' pathology reports were obtained following surgeries for cancer characteristic data. Statistical analysis was performed to investigate the significance of the acquired data. Statistical analysis of MTHFR C677T SNP revealed that the CT genotype increased the risk of breast cancer by 2.17 folds in the over-dominant model. Statistical analysis of MTHFD1 G1958A SNP showed that the GA genotype increased the risk of breast cancer by 4.12 folds in the codominant model and 2.41 folds in the over-dominant model. No statistically significant link was found between genotypes and lymph node status, however, patients with the CT genotype had higher percentages of proliferative activity. Breast cancer seems to have a statistically significant association with the CT genotype in MTHFR C677T and the GA genotype in MTHFD1 G1958A in Georgian women.