Effects Of Single Nucleotide Polymorphisms Research Articles

Identifying the genetic association between severe autoimmune type 2 diabetes and the risk of focal epilepsy.

Observational studies suggested a bidirectional relationship between severe autoimmune type 2 diabetes and focal epilepsy. However, it remains debated whether and in which direction a causal association exists. This genetics-based study aimed to explore the relationships of severe autoimmune type 2 diabetes (T2DM) and focal epilepsy outcomes with two sample Mendelian randomization (TSMR) method. Genetic instruments were obtained from large-scale genome-wide meta-analysis of severe autoimmune T2DM (Ncase = 452, Ncontrol = 2,744), and focal epilepsy (Ncase = 929, Ncontrol = 212,532) of European ancestry. A series of analyses were performed to select eligible genetic instruments robustly associated with each of the traits using summary-level statistics. Inverse variance weighted was used for primary analysis, with alternative 11 MR methods. A scatter plot was utilized to illustrate the association between single nucleotide polymorphism (SNP) effects on the exposure and SNP effects on the outcome. The Wald ratio for individual SNPs and their cumulative effects was depicted using a forest plot. And diagnostics and sensitivity analyses were used to evaluate if the causal estimates are robust to violations of MR underlying assumptions, including pleiotropy, heterogeneity assessment, and leave-one-out analysis. Then the results were validated using CURATED database of DisGeNET platform. For forward analysis, genetic predisposition to severe autoimmune T2DM was associated with an increased risk of focal epilepsy (Inverse variance weighted (IVW) method: OR = 1.11, 95% CI = 1.03-1.18, p = 0.012). For reverse analysis, there was no enough instrument variables of focal epilepsy on severe autoimmune T2DM. Further, the interrelation between severe autoimmune T2DM and focal epilepsy was demonstrated via variant-disease association network analysis using the instrument SNPs. This MR study supports a causal link between severe autoimmune T2DM and focal epilepsy. More effort should be made to screen seizure in severe autoimmune T2DM, unravel its clinical implications, and explore its role as a putative modifiable risk factor.

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.

Comprehensive genome-wide analysis of genetic loci and candidate genes associated with litter traits in purebred Berkshire pigs of Korea.

The objective of this study was to identify genomic regions and candidate genes associated with the total number of piglets born (TNB), number of piglets born alive (NBA), and total number of stillbirths (TNS) in Berkshire pigs. This study used a total of 11,228 records and 2,843 single-nucleotide polymorphism (SNP) data obtained from Illumina porcine 60 K and 80 K chips. The estimated genomic breeding values (GEBVs) and SNP effects were estimated using weighted single-step genomic BLUP (WssGBLUP). The heritabilities of the TNB, NBA, and TNS were determined using single-step genomic best linear unbiased prediction (ssGBLUP). The heritability estimates were 0.13, 0.12, and 0.015 for TNB, NBA, and TNS, respectively. When comparing the accuracy of breeding value estimates, the results using pedigree-based BLUP (PBLUP) were 0.58, 0.60, and 0.31 for TNB, NBA, and TNS, respectively. In contrast, the accuracy increased to 0.67, 0.66, and 0.42 for TNB, NBA, and TNS, respectively, when using WssGBLUP, specifically in the last three iterations. The results of weighted single-step genome-wide association studies (WssGWAS) showed that the highest variance explained for each trait was predominantly located in the Sus scrofa chromosome 5 (SSC5) region. Specifically, the variance exceeded 4% for TNB, 3% for NBA, and 6% for TNS. Within the SSC5 region (12.26 to 12.76 Mb), which exhibited the highest variance for TNB, 20 SNPs were identified, and five candidate genes were identified: TIMP3, SYN3, FBXO7, BPIFC, and RTCB. The identified SNP markers for TNB, NBA, and TNS were expected to provide valuable information for genetic improvement as an understanding of their expression and genetic architecture in Berkshire pigs. With the accumulation of more phenotype and SNP data in the future, it is anticipated that more effective SNP markers will be identified.

A brief clinical genetics review: stepwise diagnostic processes of a monogenic disorder-hypertriglyceridemia.

The completion of the Human Genome Project and tremendous advances in automated high-throughput genetic analysis technologies have enabled explosive progress in the field of genetics, which resulted in countless discoveries of novel genes and pathways. Many phenotype- or disease-associated single nucleotide polymorphisms (SNPs) with a high statistical significance have been identified through numerous genome-wide association studies (GWAS), and various polygenic risk scoring (PRS) schemes have been proposed to identify individuals with a high risk for a certain trait or disorder. Meanwhile, medical education in genetics has lagged far behind, leaving many physicians and healthcare providers unprepared in the genomic era. Thus, there is an urgent need to educate physicians and healthcare providers with basic knowledge and skills in genetics. To facilitate this, some basic terminologies and concepts are discussed in this review. In addition, some important considerations in delineating and incorporating clinical genetic testing in the diagnosis and management of a monogenic disorder are illustrated in a stepwise fashion. Furthermore, the effects of disease-associated SNPs represented by a PRS scheme clearly demonstrated that even the phenotypes of a monogenic disorder due to the same pathogenic variant in family members are modulated by the polygenic background. In human genetics, despite these explosive advancements, we are still far from clearly deciphering the interplay of gene variants to effect unique characteristics in an individual. In addition, sophisticated genome or gene directed therapies are being investigated for numerous disorders. Therefore, evolution in the field of genetics is likely to continue into the foreseeable future. In the meantime, much emphasis should be placed on educating physicians and healthcare professionals to be well-versed and skillful in the clinical use of genetics so that they can fully embrace the new era of precision medicine.

Mitochondrial sequence variants: testing imputation accuracy and their association with dairy cattle milk traits

BackgroundMitochondrial genomes differ from the nuclear genome and in humans it is known that mitochondrial variants contribute to genetic disorders. Prior to genomics, some livestock studies assessed the role of the mitochondrial genome but these were limited and inconclusive. Modern genome sequencing provides an opportunity to re-evaluate the potential impact of mitochondrial variation on livestock traits. This study first evaluated the empirical accuracy of mitochondrial sequence imputation and then used real and imputed mitochondrial sequence genotypes to study the role of mitochondrial variants on milk production traits of dairy cattle.ResultsThe empirical accuracy of imputation from Single Nucleotide Polymorphism (SNP) panels to mitochondrial sequence genotypes was assessed in 516 test animals of Holstein, Jersey and Red breeds using Beagle software and a sequence reference of 1883 animals. The overall accuracy estimated as the Pearson’s correlation squared (R2) between all imputed and real genotypes across all animals was 0.454. The low accuracy was attributed partly to the majority of variants having low minor allele frequency (MAF < 0.005) but also due to variants in the hypervariable D-loop region showing poor imputation accuracy. Beagle software provides an internal estimate of imputation accuracy (DR2), and 10 percent of the total 1927 imputed positions showed DR2 greater than 0.9 (N = 201). There were 151 sites with empirical R2 > 0.9 (of 954 variants segregating in the test animals) and 138 of these overlapped the sites with DR2 > 0.9. This suggests that the DR2 statistic is a reasonable proxy to select sites that are imputed with higher accuracy for downstream analyses. Accordingly, in the second part of the study mitochondrial sequence variants were imputed from real mitochondrial SNP panel genotypes of 9515 Australian Holstein, Jersey and Red dairy cattle. Then, using only sites with DR2 > 0.900 and real genotypes, we undertook a genome-wide association study (GWAS) for milk, fat and protein yields. The GWAS mitochondrial SNP effects were not significant.ConclusionThe accuracy of imputation of mitochondrial genotypes from the SNP panel to sequence was generally low. The Beagle DR2 statistic enabled selection of sites imputed with higher empirical accuracy. We recommend building larger reference populations with mitochondrial sequence to improve the accuracy of imputing less common variants and ensuring that SNP panels include common variants in the D-loop region.

Assessment of LINC-PINT genetic polymorphisms and esophageal squamous cell carcinoma risk in the Hainan Han population

Objectives Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high incidence and mortality rates worldwide. This study aimed to investigate the correlation between LINC-PINT polymorphisms and ESCC risk in the Hainan Han population. Methods A total of 391 patients with ESCC and 452 healthy controls were enrolled to evaluate the effect of LINC-PINT SNPs (single nucleotide polymorphisms) on ESCC susceptibility. Associations were evaluated by calculating odds ratios (OR) and 95% confidence intervals (CIs). Multifactor dimensionality reduction analysis was performed to explore the association between SNP-SNP interactions and ESCC susceptibility. We further determined the correlation between clinical indicators and SNP in patients with ESCC. Results Our study showed that rs157916 (OR 0.63, p = 0.011) and rs157928 (OR 0.80, p = 0.021) were associated with a decreased risk of ESCC. Stratified analysis indicated that rs157916 could decrease the risk of ESCC in people aged >64 years, in males, and non-drinkers (OR 0.58, p = 0.042; OR 0.58, p = 0.010; OR 0.62, p = 0.025, respectively). Rs16873842 was related to a decreased risk of ESCC in males (OR 0.70, p = 0.015). Rs7801029 was associated with ESCC risk in females (OR 0.39, p = 0.033) and non-drinkers (OR 0.68, p = 0.040). Rs7781295 decreased the ESCC risk in smokers (OR 0.58, p = 0.046) and drinkers (OR 0.58, p = 0.046). In addition, rs157928 played a protective role in ESCC risk in females (OR 0.39, p = 0.033) and non-smokers (OR 0.32, p = 0.006). Additionally, the best predictive model for ESCC was a combination of rs157916, rs16873842, rs7801029, rs7781295, rs28662387, and rs157928. Conclusion Our study revealed that LINC-PINT polymorphisms were associated with ESCC risk.

Functional Polymorphisms Regulate FOXO1 Transcript Expression and Contribute to the Risk and Symptom Severity of HDM-Induced Allergic Rhinitis

Introduction: FOXO1 plays an important role in regulating immune processes that contribute to allergic inflammation; however, genetic variants influencing FOXO1 expression in AR pathogenesis remains unclear. This study aimed to investigate the functional effect of FOXO1 single nucleotide polymorphisms (SNPs) on AR development by performing genetic association and functional analysis studies. Methods: This study belongs to a part of an ongoing Singapore/Malaysia cross-sectional genetics and epidemiological study (SMCSGES). We assessed the associations of FOXO1 transcript expression levels in peripheral blood mononuclear cells (PBMC) with AR phenotype, total nasal symptom score (TNSS), and SNP genotype in a sub-cohort of n = 658 individuals from the SMCSGES population. Associations of FOXO1 SNPs with AR were assessed in a cohort of n = 5,072 individuals from the SMCSGES population. In vitro promoter luciferase assay was used to evaluate the effect of AR-associated SNPs on FOXO1 promoter activity. Results: FOXO1 transcript expression in PBMC was significantly associated with the risk of AR (p < 0.05) and TNSS among AR patients (p < 0.0001). We identified a significant association between tag-SNPs rs9549246 and FOXO1 transcript expression in PBMC from the SMCSGES sub-cohort and the multiethnic eQTLGen consortium (false discovery rate-adjusted p < 0.05). The minor allele “A” of tag-SNP rs9549246 was significantly associated with a higher risk of AR (p = 0.04422, odds ratio = 1.21, 95% confidence interval = 1.01–1.45) in the SMCSGES genotyping cohort (n = 5,072). In vitro luciferase assay showed the minor allele “A” of rs35594717 (tagged by rs9549246) was significantly associated with a higher FOXO1 promoter activity (p < 0.05). Conclusion: FOXO1 transcript expression in PBMC has a strong association with the risk and symptom severity of AR. Genetic variants tagged by rs9549246 were shown to affect the expression of FOXO1 and contribute to the development of AR in the SMCSGES population.

Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study.

We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect ofsingle-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.

In silico analysis of the effects of non-synonymous SNPs associated with human GSK3B gene on its structure and function

Single Nucleotide Polymorphisms (SNPs) are abundantly identified by next generation sequencing (NGS) technology. Glycogen synthase kinase-3 beta (GSK3B), a widely expressed protein kinase, plays pivotal roles in cellular pathways. However, study on SNPs associated with GSK3B and their functional consequences is lacking. In this study, we analysed non-synonymous SNPs of GSK3B gene and their implications using computational tools. From NCBI dbSNP, 103,087 SNPs of GSK3B were initially gathered, later narrowed down to 255 unique nsSNPs. Around one-third of the nsSNPs resulted in charge and polarity change of the amino acids of the protein. 41 nsSNPs were found to significantly alter the stability of GSK3B protein (ΔΔG ≤ -1 or ≥ 1 kcal/mol) and few of them also affected the disorderness at the mutation site. Evolutionary conservation of the nsSNPs in the protein revealed 25 nsSNP may be deleterious to GSK3B protein function. Finally, 4 critical nsSNPs (Y161C, R167G, P225L and Y234D) were identified that can significantly alter both the stability and function of GSK3B. Furthermore, this study predicted 60 post-translational modification sites in GSK3B among which 26 sites contained nsSNPs. Interestingly, 7 upstream ORFs (uORFs) with high ribosomal occupancy were also detected in GSK3B mRNA that can reduce the expression of GSK3B protein. Altogether, this study has employed various in silico methods to characterize GSK3B nsSNPs, but they have limitations. These tools often overlook the cellular context, interacting partners, PTMs and the dynamic nature of proteins, which can affect protein behaviour and function. Despite these limitations, in silico tools are valuable for initial screening and prioritizing SNPs. The prioritized SNPs obtained in this study (Y161C, R167G, P225L and Y234D) should be experimentally validated using techniques like genome editing, biochemical assays, interactome analysis in cell lines and animal models to confirm their biological relevance.Clinical trial registration: Not Applicable.

Association of Functional Genetic Variations in Uric Acid Transporters with the Risk of Idiopathic Male Infertility: A Genetic Association Study and Bioinformatic Analysis.

Uric acid plays an important role in sustaining and improving sperm morphology, viability, and motility. It is known that SLC2A9 and ABCG2 protein are the main urate transporter and genetic variations in these genes could be associated with the levels of serum uric acid. This study aimed to investigate the association between single-nucleotide polymorphisms (SNPs) SLC2A9-rs16890979, SLC2A9-rs3733591, ABCG2-rs2231142, and ABCG2-rs2231137 with male infertility. Additionally, the correlation of these SNPs with the uric acid level in seminal plasma of infertile men was examined. Subsequently, an in silico analysis was performed. In a case-control study, 193 infertile and 154 healthy controls were recruited. After semen sample collection, the uric acid level of seminal plasma was measured by a commercial kit. After genomic DNA extraction from sperm samples, SNPs genotyping was performed by PCR-RFLP method. Lastly, the effects of SNPs on the SLC2A9 and ABCG2 gene function were evaluated by bioinformatics tools. The genetic association study revealed that there are significant associations between rs16890979, rs3733591, rs2231142, and rs2231137 genetic variations and increased risk of male infertility. Also, these variations were associated with oligozoospermia and teratozoospermia, and sometimes with asthenozoospermia. Also, we found that four studied SNPs could be associated with a decreased level of uric acid of seminal plasma in teratozoospermia and asthenozoospermia. Bioinformatic analysis revealed that the mentioned polymorphisms could affect molecular aspects of SLC2A9 and ABCG2 genes. In this preliminary study, the rs16890979, rs3733591, rs2231142, and rs2231137 genetic variations could be considered as genetic risk factors for male infertility by interfering with the uric acid level of seminal plasma.

Explainable artificial intelligence identifies an AQP4 polymorphism-based risk score associated with brain amyloid burden

Aquaporin-4 (AQP4) is hypothesized to be a component of the glymphatic system, a pathway for removing brain interstitial solutes like amyloid-β (Aβ). Evidence exists that genetic variation of AQP4 impacts Aβ clearance, clinical outcome in Alzheimer’s disease as well as sleep measures. We examined whether a risk score calculated from several AQP4 single-nucleotide polymorphisms (SNPs) is related to Aβ neuropathology in older cognitively unimpaired white individuals. We used a machine learning approach and explainable artificial intelligence to extract information on synergistic effects of AQP4 SNPs on brain amyloid burden from the ADNI cohort. From this information, we formulated a sex-specific AQP4 SNP-based risk score and evaluated it using data from the screening process of the A4 study. We found in both cohorts significant associations of the risk score with brain amyloid burden. The results support the hypothesis of an involvement of the glymphatic system, and particularly AQP4, in brain amyloid aggregation pathology. They suggest also that different AQP4 SNPs exert a synergistic effect on the build-up of brain amyloid burden.

Data-driven guidelines for phylogenomic analyses using SNP data.

There is a general lack of consensus on the best practices for filtering of single-nucleotide polymorphisms (SNPs) and whether it is better to use SNPs or include flanking regions (full "locus") in phylogenomic analyses and subsequent comparative methods. Using genotyping-by-sequencing data from 22 Glycine species, we assessed the effects of SNP vs. locus usage and SNP retention stringency. We compared branch length, node support, and divergence time estimation across 16 datasets with varying amounts of missing data and total size. Our results revealed five aspects of phylogenomic data usage that may be generally applicable: (1) tree topology is largely congruent across analyses; (2) filtering strictly for SNP retention (e.g., 90-100%) reduces support and can alter some inferred relationships; (3) absolute branch lengths vary by two orders of magnitude between SNP and locus datasets; (4) data type and branch length variation have little effect on divergence time estimation; and (5) phylograms alter the estimation of ancestral states and rates of morphological evolution. Using SNP or locus datasets does not alter phylogenetic inference significantly, unless researchers want or need to use absolute branch lengths. We recommend against using excessive filtering thresholds for SNP retention to reduce the risk of producing inconsistent topologies and generating low support.

Investigating the genomic background of calving-related traits in Canadian Jersey cattle

Traits related to calving have a significant impact on animal welfare and farm profitability in dairy production systems. Identifying genomic regions associated with calving traits could contribute to refining dairy cattle breeding programs and management practices in the dairy industry. Therefore, the primary objectives of this study were to estimate genetic parameters and perform genome-wide association studies (GWAS) and functional enrichment analyses for stillbirth, gestation length, calf size, and calving ease traits in North American Jersey cattle. A total of 40,503 animals with phenotypic records and 5,398 animals genotyped for 45,101 single nucleotide polymorphisms (SNPs) were included in the analyses. Genetic parameters were estimated based on animal models and Bayesian methods. The effects of SNPs were estimated using the Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) method. The heritability (standard error) estimates ranged from 0.01 (0.01) for stillbirths (SB) in heifers to 0.11 (0.01) for gestation length (GL) in cows. The genetic correlations ranged from -0.58 (0.11) between calving ease (CE) and SB in heifers to 0.44 (0.14) between calving ease and calf size (CZ) in cows. CE showed the highest genetic correlation between heifers and cows, 0.8 (0.22) respectively. The candidate genes identified, including MTHFR, SERPINA5, IGFBP3, and ZRANB1, are involved in key biological processes and metabolic pathways related to the studied traits. Reducing environmental variation and identifying novel indicators of reproduction traits in the Jersey breed are needed given the low heritability estimates for most traits evaluated in this study. In conclusion, this study provides a characterization of the genetic background of calving-related traits in Jersey cattle. The estimates obtained can be used to improve or build selection indexes in Jersey cattle breeding programs in North America.

Comparative transcriptomics identifies genes underlying growth performance of the Pacific black-lipped pearl oyster Pinctada margaritifera

BackgroundIn bivalves, the rate at which organisms grow is a major functional trait underlying many aspects of their commercial production. Growth is a highly polygenic trait, which is typically regulated by many genes with small to moderate effects. Due to its complexity, growth variability in such shellfish remains poorly understood. In this study, we aimed to investigate differential gene expression among spat of the pearl oyster Pinctada margaritifera with distinct growth phenotypes.ResultsWe selected two groups of P. margaritifera spat belonging to the same F2 cohort based on their growth performance at 5.5 months old. Transcriptome profile analysis identified a total of 394 differentially expressed genes between these Fast-growing (F) and Slow-growing (S) phenotypes. According to functional enrichment analysis, S oysters overexpressed genes associated with stress-pathways and regulation of innate immune responses. In contrast, F oysters up-regulated genes associated with cytoskeleton activity, cell proliferation, and apoptosis. Analysis of genome polymorphism identified 16 single nucleotide polymorphisms (SNPs) significantly associated with the growth phenotypes. SNP effect categorization revealed one SNP identified for high effect and annotated for a stop codon gained mutation. Interestingly, this SNP is located within a gene annotated for scavenger receptor class F member 1 (SRF1), which is known to modulate apoptosis. Our analyses also revealed that all F oysters showed up-regulation for this gene and were homozygous for the stop-codon mutation. Conversely, S oysters had a heterozygous genotype and a reduced expression of this gene.ConclusionsAltogether, our findings suggest that differences in growth among the same oyster cohort may be explained by contrasted metabolic allocation between regulatory pathways for growth and the immune system. This study provides a valuable contribution towards our understanding of the molecular components associated with growth performance in the pearl oyster P. margaritifera and bivalves in general.

Novel associations between MTDH gene polymorphisms and invasive ductal breast cancer: a case–control study

ObjectiveTo reveal the contributing effects of MTDH gene SNPs in the risk of invasive ductal breast cancer (IDC).Patients and methodsA case–control study was conducted, recruiting a total of 300 cases of IDC and 565 cancer-free controls from East China. Genotyping of three single-nucleotide polymorphisms (SNPs) in the MTDH gene was performed. Genomic DNA was extracted from peripheral blood samples of patients. The three SNPs (rs1311 T > C, rs16896059 G > A, rs2449512 A > G) in the MTDH gene were selected for detection using a TaqMan real-time polymerase chain reaction assay. The association between MTDH and the risk of IDC was analyzed employing an epidemiology case–control study and a multinomial logistic regression model.ResultsAmong the three evaluated SNPs, rs1311 T > C, rs16896059 G > A, and rs2449512 A > G demonstrated a significant association with an increased risk of IDC. Furthermore, stratified analysis revealed that individuals carrying the rs1311 CC genotype, rs16896059 GA/AA genotypes, and rs2449512 GG genotype were more susceptible to developing IDC in subgroups of patients younger than 53 years, without family history of IDC, pre-menopause status, clinical stage 2, high grade, with no distant metastasis or invasion, Her2-positive type, ER positive, PR positive, and Ki67 cells less than 10%. However, carriers of the rs16896059 GA/AA genotypes and rs2449512 GG genotype had an elevate the risk of IDC in patients with tumor size larger than 2 cm, post-menopause status, clinical stage 3, with invasion, lymph node infiltration, ER negative, PR negative, Her2 negative, and Ki67 cells exceeding 10%. Compared to the reference haplotype TGA, haplotypes TAA, TAG, and TGG were significantly associated with an increased IDC risk.ConclusionIn this study, we demonstrated a significant association between MTDH gene polymorphisms and an increased risk of IDC. Moreover, our findings suggested that MTDH gene polymorphisms could serve as a potential biomarker for IDC subtyping and therapeutic selection.

Relationship Between Cytotoxic T-Lymphocyte-associated Antigen-4: Programmed Death-1 Genes Polymorphisms and Susceptibility to Pediatric B-Cell Acute Lymphoblastic Leukemia.

Programmed death-1 (PD1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) have a vital role in immune checkpoint pathways. Single nucleotide polymorphisms (SNPs) of PD1 and CTLA4 have been reported to be associated with susceptibility to certain autoimmune diseases and cancers. The potential association between SNPs in these immune checkpoint genes and risk of acute lymphoblastic leukemia (ALL) still unclear. The aim of this study is to clarify the effect of PD1 and CTLA4 SNPs on the risk of developing ALL and the prognosis of the disease. The study was performed on 100 pediatric B-ALL patients and 100 controls. The PD1 and CTLA4 SNPs were examined by RFLP technique. The study revealed that CTLA4 (rs11571316) was associated with high risk of B-ALL developments OR 1.492 (CI: 1157 to 1924) ( P =0.002). PD1 (rs36084323) GA genotype was significantly associated with protective effect against nonremission ( P =0.007). PD1 (rs36084323) A allele were associated with protective effect against relapse ( P =0.008). CTLA4 and PD1 genotypes did not have significant impact on B-ALL patients outcome. The current study displayed for the first time that genetic variations of the CTLA-4, was associated with susceptibility to B-ALL and that PD1 (rs36084323) GA genotype was significantly associated with protective effect against nonremission, while PD1 (rs36084323) A allele was associated with protective effect against relapse.

Effect of SNPs on Litter Size in Swine.

Although sows do not directly enter the market, they play an important role in piglet breeding on farms. They consume large amounts of feed, resulting in a significant environmental burden. Pig farms can increase their income and reduce environmental pollution by increasing the litter size (LS) of swine. PCR-RFLP/SSCP and GWAS are common methods to evaluate single-nucleotide polymorphisms (SNPs) in candidate genes. We conducted a systematic meta-analysis of the effect of SNPs on pig LS. We collected and analysed data published over the past 30 years using traditional and network meta-analyses. Trial sequential analysis (TSA) was used to analyse population data. Gene set enrichment analysis and protein-protein interaction network analysis were used to analyse the GWAS dataset. The results showed that the candidate genes were positively correlated with LS, and defects in PCR-RFLP/SSCP affected the reliability of candidate gene results. However, the genotypes with high and low LSs did not have a significant advantage. Current breeding and management practices for sows should consider increasing the LS while reducing lactation length and minimizing the sows' non-pregnancy period as much as possible.

Association of single nucleotide polymorphisms (SNPs) in inflammatory pathways with breast cancer (BC) risk: A multi-ethnic scoping review.

1617 Background: Breast cancer is the most prevalent cancer affecting women of every ethnic group in the United States. This is a scoping review assessing SNPs in inflammatory pathways posited to modify BC risk by ethnicity. Methods: We followed PRISMA guidelines for scoping reviews. PubMed, Medline, and OVID databases were interrogated for publications between 1/2000-12/2023 using search terms “breast cancer” AND [BMI OR “body mass index” OR elevated BMI OR obesity] AND [SNP OR “single nucleotide polymorphism” OR polymorphism OR mutation] AND [inflammation OR cytokines OR IL-1 OR IL-2 OR IL-4 OR IL-6 OR IL-8 OR IL-10 OR IL-12 OR TNF-A or TGFB OR CRP] AND [Asian, Black or Hispanic]. A single reviewer assessed 72 unique publications and determined that 42 met inclusion criteria. Two reviewers extracted the following data: demographics, SNP, number of cases and controls by ethnicity. Disagreements were resolved by consensus with a third reviewer. Results: Data were extractable from 42 studies, all case controls. In analyses stratified by ethnicity, we detected effects of SNPs on BC risk (Table). IL-1β rs1143634 and IL-10 (1082 A/G) had a significantly increased BC risk in Asian populations but insignificant in white populations. There were minimal publications for Black and Hispanic populations. Conclusions: The association of inflammatory SNPs and BC risk is complex and can be both protective and predisposing to BC, with ethnicity modifying SNP risk. Future research can be directed at assessment of SNPs and BC risk in diverse populations. [Table: see text]

Protease activated receptor-4: ready to be part of the antithrombosis spectrum.

Cardiovascular disease is a major cause of death worldwide. Platelets play a key role in this pathological process. The serine protease thrombin is a critical regulator of platelet reactivity through protease activated receptors-1 (PAR1) and PAR4. Since targeting PAR4 comes with a low chance for bleeding, strategies blocking PAR4 function have great antithrombotic potential. Here, we reviewed the literature on platelet PAR4 with a particular focus on its role in thromboinflammation. Functional PAR4 variants are associated with reduced venous thrombosis risk (rs2227376) and increased risk for ischemic stroke (rs773902). Recent advances have allowed for the creation of humanized mouse lines in which human PAR4 is express instead of murine PAR4. This has led to a better understanding of the discrepancies between human and murine PAR4. It also made it possible to introduce single nucleotide polymorphisms (SNPs) in mice allowing to directly test the in vivo functional effects of a specific SNP and to develop in vivo models to study mechanistic and pharmacologic alterations induced by a SNP. PAR4 plays an important role in cardiovascular diseases including stroke, myocardial infarction and atherosclerosis. Targeting PAR4 hold great potential as a safe antithrombotic strategy.

Unraveling genetic causality between metformin and myocardial infarction on the basis of Mendelian randomization.

In recent years, several studies have explored the effect of metformin on myocardial infarction (MI), but whether metformin has an improvement effect in patients with MI is controversial. This study was aimed to investigate the causal relationship between metformin and MI using Mendelian randomization (MR) analysis. The genome-wide significant (P<5×10-8) single-nucleotide polymorphisms (SNPs) in patients with metformin and patients with MI were screened from the Open genome-wide association study (GWAS) project as instrumental variables (IVs). The study outcomes mainly included MI, old MI, acute MI, acute transmural MI of inferior wall, and acute transmural MI of anterior wall. The inverse variance weighted (IVW) method was applied to assess the main causal effect, and weighted median, simple mode, weighted mode methods, and MR-Egger regression were auxiliary applied for supplementary proof. The causal relationship between metformin and MI was assessed using odds ratios (OR) and 95% confidence intervals (95% CI). A leave-one-out method was used to explore the effect of individual SNPs on the results of IVW analyses, and a funnel plot was used to analyze the potential bias of the study results, thus ensuring the robustness of the results. In total, 16, 84, 39, 26, and 34 SNPs were selected as IVs to assess the genetic association between metformin and outcomes of MI, old MI, acute MI, acute transmural MI of inferior wall, and acute transmural MI of anterior wall, respectively. Treatment with metformin does not affect the risk of acute transmural MI of anterior wall at the genetic level (P>0.05; OR for inverse variance weighted was 1.010). In the cases of MI, old MI, acute MI, and acute transmural MI of inferior wall, metformin may even be a risk factor for patients (P<0.05; ORs for inverse variance weighted were 1.078, 1.026, 1.022 and 1.018 respectively). There was no horizontal pleiotropy or heterogeneity among IVs. The results were stable when removing the SNPs one by one. Metformin is not protective against the risk of myocardial infarction in patients and may even be a risk factor for MI, old MI, acute MI, and acute transmural MI of inferior wall.