Multiple Single Nucleotide Polymorphisms Research Articles

Gene polymorphisms of miR-323b and miR-1343 that regulate kininogen L are associated with schizophrenia susceptibility: A preliminary population‑based study.

miR-SNP is a type of functional single nucleotide polymorphism (SNP) that affects the regulatory functions of miRNA genes, miRNA binding sites, or components of miRNA biogenesis. This study aimed to explore the relationship between miRNA gene polymorphisms that regulate the kininogen L protein and schizophrenia (SCZ). Bioinformatics methods predicted miRNA gene polymorphism sites regulating the kininogen L protein. The polymorphisms of rs56103835, rs6513496, rs651349, and rs2986407 were detected using imLDR multiple SNP typing technologies in 513 SCZ patients and 509 controls. The association of miR-SNP variations with SCZ susceptibility and symptoms was evaluated using SNPstat to determine the optimal inheritance model. Generalized multifactor dimensionality reduction (GMDR) analysis and logistic regression were used to calculate miR-SNP interactions. The association between hsa-miR-323b-rs56103835 and SCZ was statistically significant under the dominant model. The result of gene-gene interaction showed that the three-factor model (rs56103835 / rs2986407 / rs2155248) was the best, but it could not be considered significantly related to SCZ. Additionally, SCZ patients with the CC or CT genotype on rs2986407 were more likely to experience auditory hallucinations than those with the TT genotype. Our data revealed that the mutation of hsa-miR-323b-rs56103835 from C to T was associated with susceptibility to SCZ. The mutation of hsa-miR-1343-rs2986407 from T to C increases the risk of auditory hallucinations in SCZ patients.

Exploring the interaction mechanisms between cervical carcinoma in situ and antibody-mediated immune responses through Mendelian randomization analysis

ObjectiveThis study aims to investigate the causal relationship between cervical carcinoma in situ and antibody-mediated immune responses, providing a scientific basis for the prevention and treatment of cervical carcinoma in situ.MethodsA bidirectional Mendelian Randomization (MR) approach was utilized, leveraging two Genome-Wide Association Studies (GWAS) related to cervical carcinoma in situ and antibody-mediated immune responses to collect Single Nucleotide Polymorphism (SNP) data. Multiple statistical methods, including the inverse-variance weighted (IVW) method, MR-Egger regression, weighted median, and weighted mode, were utilized. Antibody-mediated immune response-related SNPs were used as instrumental variables (IVs) for a forward MR analysis of cervical carcinoma in situ, while cervical carcinoma in situ-related SNPs served as IVs for a reverse MR analysis of antibody-mediated immune responses.ResultsThe forward MR analysis revealed significant causal associations between two SNPs, GCST90006901 (P = 0.012, OR (95%CI) = 1.167(1.034–1.317)) and GCST90006909 (P < 0.001, OR (95%CI) = 1.805(1.320–2.467)), within antibody-mediated immune responses and the occurrence of cervical carcinoma in situ. The reverse MR analysis demonstrated that cervical carcinoma in situ exerts influence on multiple SNPs associated with antibody-mediated immune responses. Specifically, GCST90006891 (P = 0.018, OR (95%CI) = 1.164(1.027–1.319)) and GCST90006894 (P = 0.048, OR (95%CI) = 1.074 (1.001–1.153)) showed positive effects, while GCST90006899 (P = 0.022, OR (95%CI) = 0.935(0.882–0.990)) and GCST90006911 (P = 0.0193, OR (95%CI) = 1.226(1.034–1.454)) exhibited distinct trends of influence.ConclusionThe Mendelian Randomization analysis indicates a clear causal relationship between antibody-mediated immune responses and the prevalence of cervical carcinoma in situ, with cervical carcinoma in situ also exerting a certain degree of influence on antibody-mediated immune responses. This finding provides important insights into the interaction mechanism between the two and suggests avenues for developing effective prevention and control strategies.

Associations between antagonistic SNPs for neuropsychiatric disorders and human brain structure

A previously published genome-wide association study (GWAS) meta-analysis across eight neuropsychiatric disorders identified antagonistic single-nucleotide polymorphisms (SNPs) at eleven genomic loci where the same allele was protective against one neuropsychiatric disorder and increased the risk for another. Until now, these antagonistic SNPs have not been further investigated regarding their link to brain structural phenotypes. Here, we explored their associations with cortical surface area and cortical thickness (in 34 brain regions and one global measure each) as well as the volumes of eight subcortical structures using summary statistics of large-scale GWAS of brain structural phenotypes. We assessed if significantly associated brain structural phenotypes were previously reported to be associated with major neuropsychiatric disorders in large-scale case-control imaging studies by the ENIGMA consortium. We further characterized the effects of the antagonistic SNPs on gene expression in brain tissue and their association with additional cognitive and behavioral phenotypes, and performed an exploratory voxel-based whole-brain analysis in the FOR2107 study (n = 754 patients with major depressive disorder and n = 847 controls). We found that eight antagonistic SNPs were significantly associated with brain structural phenotypes in regions such as anterior parts of the cingulate cortex, the insula, and the superior temporal gyrus. Case-control differences in implicated brain structural phenotypes have previously been reported for bipolar disorder, major depressive disorder, and schizophrenia. In addition, antagonistic SNPs were associated with gene expression changes in brain tissue and linked to several cognitive-behavioral traits. In our exploratory whole-brain analysis, we observed significant associations of gray matter volume in the left superior temporal pole and left superior parietal region with the variants rs301805 and rs1933802, respectively. Our results suggest that multiple antagonistic SNPs for neuropsychiatric disorders are linked to brain structural phenotypes. However, to further elucidate these findings, future case-control genomic imaging studies are required.

High Polygenic Risk Scores Positively Associated with Gastric Cancer Risk Interact with Coffee and Polyphenol Intake and Smoking Status in Korean Adults.

This study investigated the relationship between single nucleotide polymorphisms (SNPs) and gastric cancer (GC) risk, while also examining the interaction of genetic factors with lifestyle variables including the nutrient and bioactive compound intake in Korean adults of a large hospital-based cohort. We conducted a genome-wide association study (GWAS) comparing GC patients (n = 312) with healthy controls without cancers (n = 47,994) to identify relevant genetic variants. Generalized multifactor dimensionality reduction (GMDR) was employed to detect SNP interactions between diets and lifestyles. We utilized polygenic risk scores (PRSs) to assess individuals' GC risk based on multiple SNP loci. Among the selected SNPs, since SEMA3C_rs1527482 was a missense mutation, bioactive compounds which decrease the binding energy were found with its wild and mutated proteins by molecular docking analysis. Individuals with high PRSs exhibited a 4.12-fold increased risk of GC compared to those with low PRSs. Additional factors associated with elevated GC risk included a low white blood cell count (OR = 5.13), smoking (OR = 3.83), and low coffee consumption (OR = 6.30). The SEMA3C_rs1527482 variant showed a positive correlation with GC risk. Molecular docking analyses suggested that certain polyphenols, including theaflavate, rugosin E, vitisifuran B, and plantacyanin, reduced the binding free energy in both wild-type and mutated SEMA3C_rs1527482. However, some polyphenols exhibited differential binding energies between its wild and mutated forms, suggesting they might modulate wild and mutated proteins differently. High PRSs and SEMA3C_rs1527482 interact with immune function, coffee intake, polyphenol consumption, and smoking status to influence GC risk. These findings could contribute to developing personalized nutrition and lifestyle interventions to reduce GC risk.

Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections.

Significant variations have been observed in viral copies generated during SARS-CoV-2 infections. However, the factors that impact viral copies and infection dynamics are not fully understood, and may be inherently dependent upon different viral and host factors. Here, we conducted virus whole genome sequencing and measured viral copies using RT-qPCR from 9,902 SARS-CoV-2 infections over a 2-year period to examine the impact of virus genetic variation on changes in viral copies adjusted for host age and vaccination status. Using a genome-wide association study (GWAS) approach, we identified multiple single-nucleotide polymorphisms (SNPs) corresponding to amino acid changes in the SARS-CoV-2 genome associated with variations in viral copies. We further applied a marginal epistasis test to detect interactions among SNPs and identified multiple pairs of substitutions located in the spike gene that have non-linear effects on viral copies. We also analyzed the temporal patterns and found that SNPs associated with increased viral copies were predominantly observed in Delta and Omicron BA.2/BA.4/BA.5/XBB infections, whereas those associated with decreased viral copies were only observed in infections with Omicron BA.1 variants. Our work showcases how GWAS can be a useful tool for probing phenotypes related to SNPs in viral genomes that are worth further exploration. We argue that this approach can be used more broadly across pathogens to characterize emerging variants and monitor therapeutic interventions.

Associations between cuprotosis-related genes and the spectrum of metabolic dysfunction-associated fatty liver disease: An exploratory study.

To explore the associations between cuprotosis-related genes (CRGs) across different stages of liver disease in metabolic dysfunction-associated fatty liver disease (MAFLD), including hepatocellular carcinoma (HCC). We analysed several bulk RNA sequencing datasets from patients with MAFLD (n = 331) and MAFLD-related HCC (n = 271) and two MAFLD single-cell RNA sequencing datasets. To investigate the associations between CRGs and MAFLD, we performed differential correlation, logistic regression and functional enrichment analyses. We also validated the findings in an independent Wenzhou PERSONS cohort of MAFLD patients (n = 656) used for a genome-wide association study (GWAS). GLS, GCSH and ATP7B genes showed significant differences across the MAFLD spectrum and were significantly associated with liver fibrosis stages. GLS was closely associated with fibrosis stages in patients with MAFLD and those with MAFLD-related HCC. GLS is predominantly expressed in monocytes and T cells in MAFLD. During the progression of metabolic dysfunction-associated fatty liver to metabolic-associated steatohepatitis, GLS expression in T cells decreased. GWAS revealed that multiple single nucleotide polymorphisms in GLS were associated with clinical indicators of MAFLD. GLS may contribute to liver inflammation and fibrosis in MAFLD mainly through cuprotosis and T-cell activation, promoting the progression of MAFLD to HCC. These findings suggest that cuprotosis may play a role in MAFLD progression, potentially providing new insights into MAFLD pathogenesis.

Abstract P205: Single-nucleus Sequencing Reveals Endothelial Cell-specific Dysregulation in the Kidney in Multiple Models of Hypertension

The kidney plays a crucial role in the onset and progression of hypertension. To investigate the roles of different renal cell types in hypertension, we applied single-nucleus sequencing and spatial transcriptome sequencing to kidney samples from three well-established hypertension models: C57BL/6 mice treated with Ang II, the Dahl salt-sensitive (SS) rat on high-salt diets, and the spontaneously hypertensive rat (SHR), along with their respective controls including Sprague-Dawley (SD) and Wistar Kyoto (WKY) rats. Our dataset comprised 179,637 nuclei from 24 samples across 12 experimental conditions, identifying 17 major cell types including various epithelial cells, endothelial cells, vascular smooth muscle cells, fibroblasts, and immune cells. At baseline, differentially expressed genes between the SS and SD groups were specifically enriched in endothelial cell pathways related to vascular development. This included expression deficiencies in genes involved in angiogenesis in SS rats, such as Arhgap24 and Nox4. Compensatory expression changes in these genes were observed in the SS rats after a high-salt diet and in 26-week-old SHR, but not in their respective controls. These genes were also associated with multiple blood pressure-associated single-nucleotide polymorphisms (SNPs). Furthermore, changes in endothelial cell communication were most prominent upon stimuli, with impaired PTPRM (Protein Tyrosine Phosphatase Receptor Type M) signaling being a robust feature in hypertension models, involving angiogenic endothelial cells in the SS model and proliferating capillary endothelial cells in the SHR model. Our study highlights the critical role of renal endothelial cell angiogenic dysfunction in the pathogenesis of hypertension and suggests a link between specific renal endothelial cell subtype dysregulation and hypertension development.

The molecular basis of lactase persistence: Linking genetics and epigenetics.

Lactase persistence (LP) - the genetic trait that determines the continued expression of the enzyme lactase into adulthood - has undergone recent, rapid positive selection since the advent of animal domestication and dairying in some human populations. While underlying evolutionary explanations have been widely posited and studied, the molecular basis of LP remains less so. This review considers the genetic and epigenetic bases of LP. Multiple single-nucleotide polymorphisms (SNPs) in an LCT enhancer in intron 13 of the neighbouring MCM6 gene are associated with LP. These SNPs alter binding of transcription factors (TFs) and likely prevent age-related increases in methylation in the enhancer, maintaining LCT expression into adulthood to cause LP. However, the complex relationship between the genetics and epigenetics of LP is not fully characterised, and the mode of action of methylation quantitative trait loci (meQTLs) (SNPs affecting methylation) generally remains poorly understood. Here, we examine published LP data to propose a model describing how methylation in the LCT enhancer is prevented in LP adults. We argue that this occurs through altered binding of the TF Oct-1 (encoded by the gene POU2F1) and neighbouring TFs GATA-6 (GATA6), HNF-3A (FOXA1) and c-Ets1 (ETS1) acting in concert. We therefore suggest a plausible new model for LCT downregulation in the context of LP, with wider relevance for future work on the mechanisms of other meQTLs.

BjuB05.GS1.4 promotes nitrogen assimilation and participates in the domestication of shoot NUE in Brassica juncea

Elucidating crops' physiological and molecular mechanisms to adapt to low nitrogen environment and promoting nitrogen transfer from senescent leaves to new leaves is crucial in improving Brassica's nitrogen use efficiency (NUE). Glutamine synthetase (GS), a vital gene that helps plants to reassimilate ammonium released from protein degradation in leaves, was the focus of our research. In this study, we identified high (H141) and low NUE genotype (L65) genotypes of Brassica juncea with different responses to low-nitrogen stress. We observed that H141 has a lower nitrate content but higher ammonium and free amino acid contents as well as higher nitrate reductase and GS activities in the shoots. These physiological indicators are responsible for the high NUE of H141. Whole-genome resequencing data revealed that 5,880 genes associated with NUE are polymorphic between H141 and L65. These genes participate in amino acid, carbohydrate, and energy metabolic pathways. Haplotype analysis revealed two haplotypes for BjuB05.GS1.4. Hap1 and Hap2 have multiple single nucleotide polymorphisms or insertions/deletions in the regulatory regions of 5′ and 3′ untranslated regions and introns. Furthermore, the shoot NUE of Hap1 is significantly lower than that of Hap2. The two haplotypes of BjuB05.GS1.4 led to differences in the shoot NUEs of different genetic populations of mustard and are associated with the local soil nitrogen content, suggesting that they might help mustard to adapt to different geographies. In conclusion, the results of our study shed light on the physiological and molecular mechanisms underlying different mustard NUE genotypes and demonstrate the enormous potential of NUE breeding in B.juncea.

CRISPR-mediated ablation of TP53 and EGFR mutations enhances gefitinib sensitivity and anti-tumor efficacy in lung cancer

Multiple pathogenic single-nucleotide polymorphism (SNP)s have been identified as contributing factors in the aggravation of cancer prognosis and emergence of drug resistance in various cancers. Here we targeted a mutated EGFR and TP53 oncogene harboring a single-nucleotide missense mutation (EGFR-T790M and TP53-R273H), that associated with gefitinib resistance. Co-delivery of adenine base editor and EGFR and TP53 SNP-specific single-guide RNA via adenovirus resulted in precise correction at the oncogenic mutation site with high accuracy and efficiency in vitro and in vivo. Importantly, compared to a control group treated only with a gefitinib, an EGFR inhibitor, co-treatment of Ad/ABE targeting SNPs in TP53 and EGFR in combination of gefitinib increased the drug sensitivity and suppressed abnormal tumor growth more efficiently. Taken together, these results indicate that ABE-mediated correction of dual oncogenic SNPs can be effective strategy for the treatment of drug-resistant cancers.

Evidence of gene-nutrient interaction association with waist circumference, cross-sectional analysis

Background and aimsWaist circumference (WC) is a significant indicator of body adiposity and is associated with increased mortality and morbidity of cardiovascular diseases. Although, single nutrient intake and candidate genes were previously associated with WC. Little is known about WC association with overall diet quality, genetic risk score and gene-nutrient interaction. This study aims to investigate the influence of overall diet quality and multiple WC-associated single nucleotide polymorphisms on WC. In addition to investigating gene-nutrient interaction association with WC.MethodsThis study explored cross-sectional data from two large sample-size studies, to provide reproducible results. As a representation of the UK population, the Airwave Health Monitoring Study (n = 6,502) and the UK-Biobank Cohort Study (n = 171,129) were explored for factors associated with WC. Diet quality was evaluated based on the Mellen Index for Dietary Approaches to Stop Hypertension (Mellen-DASH). The genetic risk score for WC (GRS-Waist) was calculated by screening the population genotype for WC-associated single nucleotide polymorphisms. Multivariate linear regression models were built to explore WC association with diet quality and genetic risk score. Gene-nutrient interaction was explored by introducing the interaction term (GRS-Waist X Mellen-DASH score) to multivariate linear regression analysis.ResultsThe prevalence of high WC (Female > 80 cm, Male > 94 cm) was 46.5% and 51.7% in both populations. Diet quality and genetic risk score of WC were significantly associated with WC. There was no evidence of interaction between GRS-Waist, DASH diet scores and nutrient intake on WC.ConclusionThis study’s findings provided reproducible results on waist circumference association with diet and genetics and tested the possibility of gene-nutrient interaction. These reproducible results are successful in building the foundation for using diet and genetics for early identification of those at risk of having high WC and WC-associated diseases. In addition, evidence on gene-diet interactions on WC is limited and lacks replication, therefore our findings may guide future research in investigating this interaction and investigating its application in precision nutrition.

Validating genetic variants in innate immunity linked to infectious events in acute myeloid leukemia post-induction chemotherapy

Infectious events, such as sepsis and invasive fungal disease (IFD), pose significant risks in patients with acute myeloid leukemia (AML). Previous studies, including our own, have suggested a potential role of single nucleotide polymorphisms (SNPs) within the innate immune system in influencing individual infection susceptibility. However, many of these associations lack validation in independent cohorts. This study sought to validate the impact of 11 candidate SNPs across 6 genes (TLR2, TLR4, Dectin-1, DC-SIGN, PTX3, L-Ficolin) in an independent cohort of patients. Two cohorts with newly diagnosed AML patients receiving intensive induction chemotherapy were analyzed: a stratification cohort comprising 186 patients and a validation cohort consisting of 138 patients. Multiple SNPs in each cohort were found to be associated to infectious complications, notably the DC-SIGN SNP rs4804800 demonstrated a significant association with sepsis in both cohorts. SNPs within the PTX3 and Dectin-1 genes were linked to IFD development in one cohort each. This study represents the first validation study of candidate genes associated with infectious events in AML patients after intensive induction chemotherapy. Identifying genetic predispositions to infections could significantly impact the management of antimicrobial prophylaxis and treatment in AML patients.

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.

The 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. We 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. We 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. We 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.

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.