Genome-wide Significant Single Nucleotide Polymorphisms Research Articles

Impact of gene-by-trauma interaction in MDD-related multimorbidity clusters

BackgroundMajor depressive disorder (MDD) is considerably heterogeneous in terms of comorbidities, which may hamper the disentanglement of its biological mechanism. In a previous study, we classified the lifetime trajectories of MDD-related multimorbidities into seven distinct clusters, each characterized by unique genetic and environmental risk-factor profiles. The current objective was to investigate genome-wide gene-by-environment (G × E) interactions with childhood trauma burden, within the context of these clusters. MethodsWe analyzed 77,519 participants and 6,266,189 single-nucleotide polymorphisms (SNPs) of the UK Biobank database. Childhood trauma burden was assessed using the Childhood Trauma Screener (CTS). For each cluster, Plink 2.0 was used to calculate SNP × CTS interaction effects on the participants' cluster membership probabilities. We especially focused on the effects of 31 candidate genes and associated SNPs selected from previous G × E studies for childhood maltreatment's association with depression. ResultsAt SNP-level, only the high-multimorbidity Cluster 6 revealed a genome-wide significant SNP rs145772219. At gene-level, MPST and PRH2 were genome-wide significant for the low-multimorbidity Clusters 1 and 3, respectively. Regarding candidate SNPs for G × E interactions, individual SNP results could be replicated for specific clusters. The candidate genes CREB1, DBH, and MTHFR (Cluster 5) as well as TPH1 (Cluster 6) survived multiple testing correction. LimitationsCTS is a short retrospective self-reported measurement. Clusters could be influenced by genetics of individual disorders. ConclusionsThe first G × E GWAS for MDD-related multimorbidity trajectories successfully replicated findings from previous G × E studies related to depression, and revealed risk clusters for the contribution of childhood trauma.

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.

Novel insights into rosacea's role in cancer risk: A Mendelian randomization approach.

Chronic inflammation has been shown to promote cancer progression. Rosacea is indeed a long-term inflammatory skin condition and had been reported to link with increased risk for several types of malignancies, but evidence for causality is lacking. To systematically estimate the causal relationship between rosacea and several types of cancer, including cutaneous malignant melanoma (CMM), cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), actinic keratosis (AK), thyroid cancer, breast cancer, glioma and hepatic cancer, as well as explore the potential underlying pathogenesis. We conducted a bidirectional two-sample Mendelian randomization study to probe the potential causal relationships between rosacea and several types of cancer. Instrumental variables were established using genome-wide significant single nucleotide polymorphisms associated with rosacea and cancers. The assessment of causality was carried out through multiple methods, and the robustness of the results was evaluated via sensitivity analyses. There was no significant indication of causal effects of rosacea on CMM (pivw=0.71), cSCC (pivw=0.45), BCC (pivw=0.90), AK (pivw=0.73), thyroid cancer (pivw=0.59), glioma (pivw=0.15), and hepatic cancer (pivw=0.07), but the genetic risk of rosacea was associated with an increased susceptibility to human epidermal growth factor receptor (HER)-negative malignant neoplasm of breast (odds ratio [OR], 1.10; 95% confidence interval [CI], 1.02-1.18; pivw=0.01). TANK (TRAF family member associated nuclear factor kappa B (NFKB) activator) was identified as a common protective gene for both rosacea (OR, 0.90; 95% CI, 0.82-0.99; pivw=0.048) and HER-negative malignant neoplasm of the breast (OR, 0.86; 95% CI, 0.75-0.98; pivw=0.032), which was primarily enriched in the negative regulation of NF-κB signal transduction and may contribute to the genetic links between rosacea and this subtype of breast cancer. Our findings provide suggestive evidence for causal links between rosacea and HER-negative malignant neoplasm of the breast risk.

Causal association of metformin treatment with diverse cardiovascular diseases: a Mendelian randomization analysis.

The cardiovascular effects of metformin continue to be a subject of debate within the medical community. The Mendelian randomization (MR) study used data from genome-wide association studies (GWAS) to explore the causal association with six diseases that are associated with bimatoprost treatment and myocardial infarction, chronic heart failure, atrial fibrillation, hypertrophic and dilated cardiomyopathy, and valvular disease. Genome-wide significant single nucleotide polymorphisms (SNPs), that are associated with metformin use were selected as the instrumental variables. To determine the causal relationship between metformin use and various cardiovascular diseases, MR analysis was conducted, employing methods such as Instrumental Variable Weighting (IVW). The IVW analysis demonstrated a positive association between metformin treatment and the risk of myocardial infarction (OR = 22.67, 95% CI 3.22-34.01; P = 0.002). Conversely, metformin treatment exhibited a negative association with the risk of developing valvular disease (OR = 0.98, 95% CI 0.95-1.00; P = 0.046) and hypertrophic cardiomyopathy (OR = 0.01, 95% CI 0.00-0.22; P = 0.016). Multiple test correction found that metformin treatment was causally associated with the risk of both hypertrophic cardiomyopathy (PFDR = 0.048) and myocardial infarction (PFDR = 0.012). The analysis revealed limited heterogeneity in the individual results, absence of pleiotropy evidence, and indications of stability in the findings. The MR study discovered from a genetic standpoint that metformin may lower the risk of hypertrophic cardiomyopathy and valvular heart disease, yet it could elevate the risk of myocardial infarction.

PM2.5 associates with blood pressure: a Mendelian randomization analysis

ABSTRACT The relationship between fine particulate matter (PM2.5) and blood pressure (BP) is a controversial issue. We conducted a two-sample Mendelian randomization (MR) analysis and identified 58 genome-wide significant single-nucleotide polymorphisms associated with PM2.5 as instrument variables. Inverse-variance weighted (IVW) was used as the primary analysis approach. MR-Egger, weighted median, simple model, and weighted model methods were selected for quality control. We found a significant negative causal association of higher genetically predicted PM2.5 levels with lower systolic BP (SBP), while no causal relationship was identified between PM2.5 and diastolic BP (DBP). For each 1 standard deviation increase in genetically predicted PM2.5 levels, the beta value (95% CI) of SBP was -0.14 (-0.25, -0.03) for IVW (p=0.02), and -0.13 (-0.22, -0.04) for weighted median (p=0.005). Increased PM2.5 concentrations can lead to decreased SBP levels. Our findings provided novel insights into the controversial topic on the causal relationship between PM2.5 and BP.

Genome-wide association study identifies a novel candidate gene for egg production traits in chickens.

Qingyuan partridge chicken is a renowned indigenous yellow broiler breed in China. Egg production traits are important economic traits for chickens. With the decreasing cost of whole genome resequencing, identifying candidate genes with more precision has become possible. In order to identify molecular markers and candidate genes associated with egg production traits, we conducted genome-wide association studies based on the resequencing data of 287 female Qingyuan partridge chickens. For each hen, age at first egg and egg laying rate were recorded and calculated, respectively. With a univariate linear mixed model, we detected one genome-wide significant single nucleotide polymorphism (SNP) and three chromosome-wide significant SNPs associated with egg laying rate. MTA2 is highly likely to be a functional gene for egg laying rate. Our study identifies MTA2 as the first time to be associated with egg laying rate. Findings in our study will advance our understanding of the genetic basis of egg production and have the potential to improve the efficiency of genomic selection in chickens.

Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes

Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10−7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.

Genome-wide association studies of egg production traits by whole genome sequencing of Laiwu Black chicken

Compared to high-yield commercial laying hens, Chinese indigenous chicken breeds have poor egg laying capacity due to the lack of intensive selection. However, as these breeds have not undergone systematic selection, it is possible that there is a greater abundance of genetic variations related to egg laying traits. In this study, we assessed 5 egg number (EN) traits at different stages of the egg-laying period: EN1 (from the first egg to 23 wk), EN2 (from 23 to 35 wk), EN3 (from 35 to 48 wk), EN4 (from the first egg to 35 wk), and EN5 (from the first egg to 48 wk). To investigate the molecular mechanisms underlying egg number traits in a Chinese local chicken breed, we conducted a genome-wide association study (GWAS) using data from whole-genome sequencing (WGS) of 399 Laiwu Black chickens. We obtained a total of 3.01 Tb of raw data with an average depth of 7.07 × per individual. A total of 86 genome-wide suggestive or significant single-nucleotide polymorphisms (SNP) contained within a set of 45 corresponding candidate genes were identified and found to be associated with stages EN1-EN5. The genes vitellogenin 2 (VTG2), lipase maturation factor 1 (LMF1), calcium voltage-gated channel auxiliary subunit alpha2delta 3 (CACNA2D3), poly(A) binding protein cytoplasmic 1 (PABPC1), programmed cell death 11 (PDCD11) and family with sequence similarity 213 member A (FAM213A) can be considered as the candidate genes associated with egg number traits, due to their reported association with animal reproduction traits. Noteworthy, results suggests that VTG2 and PDCD11 are not only involved in the regulation of EN3, but also in the regulation of EN5, implies that VTG2 and PDCD11 have a significant influence on egg production traits. Our study offers valuable genomic insights into the molecular genetic mechanisms that govern egg number traits in a Chinese indigenous egg-laying chicken breed. These findings have the potential to enhance the egg-laying performance of chickens.

Elucidation of the genetic determination of body weight and size in Chinese local chicken breeds by large-scale genomic analyses.

Body weight and size are important economic traits in chickens. While many growth-related quantitative trait loci (QTLs) and candidate genes have been identified, further research is needed to confirm and characterize these findings. In this study, we investigate genetic and genomic markers associated with chicken body weight and size. This study provides new insights into potential markers for genomic selection and breeding strategies to improve meat production in chickens. We performed whole-genome resequencing of and Wenshang Barred (WB) chickens (n = 596) and three additional breeds with varying body sizes (Recessive White (RW), WB, and Luxi Mini (LM) chickens; (n = 50)). We then used selective sweeps of mutations coupled with genome-wide association study (GWAS) to identify genomic markers associated with body weight and size. We identified over 9.4million high-quality single nucleotide polymorphisms (SNPs) among three chicken breeds/lines. Among these breeds, 287 protein-coding genes exhibited positive selection in the RW and WB populations, while 241 protein-coding genes showed positive selection in the LM and WB populations. Genomic heritability estimates were calculated for 26 body weight and size traits, including body weight, chest breadth, chest depth, thoracic horn, body oblique length, keel length, pelvic width, shank length, and shank circumference in the WB breed. The estimates ranged from 0.04 to 0.67. Our analysis also identified a total of 2,522 genome-wide significant SNPs, with 2,474 SNPs clustered around two genomic regions. The first region, located on chromosome 4 (7.41-7.64Mb), was linked to body weight after ten weeks and body size traits. LCORL, LDB2, and PPARGC1A were identified as candidate genes in this region. The other region, located on chromosome 1 (170.46-171.53Mb), was associated with body weight from four to eighteen weeks and body size traits. This region contained CAB39L and WDFY2 as candidate genes. Notably, LCORL, LDB2, and PPARGC1A showed highly selective signatures among the three breeds of chicken with varying body sizes. Overall this study provides a comprehensive map of genomic variants associated with body weight and size in chickens. We propose two genomic regions, one on chromosome 1 and the other on chromosome 4, that could helpful for developing genome selection breeding strategies to enhance meat yield in chickens.

Integration of genome-wide association and genomic prediction for dissecting seed protein and amino acid in foxtail millet

ContextThe exploitation and utilization of genetic variation in crop germplasm benefit genomics-informed breeding programs. The integration of genome-wide association study (GWAS) and genomic prediction (GP) holds promise for illustrating genetic basis of phenotypic variation. Currently, the use of this integrative approach for dissecting grain protein and amino acid traits remains limited in crop species. ObjectiveThe research objectives were to identify significant single nucleotide polymorphisms (SNPs) associated with seed protein and amino acids and to assess the genomic predictive ability for nutritional traits in natural population of foxtail millet. MethodsIn this study, the concentrations of seed protein and 17 amino acids were assessed in a training population consisting of 238 diverse accessions of foxtail millet. The significant SNPs associated with these phenotypes were identified by GWAS with a mix-linear model. Extensive cross-validation was performed to evaluate the accuracy of genomic prediction of seed nutritional traits. Furthermore, the genomic prediction model was optimized and externally validated in 211 untested materials with the most significant SNPs obtained from GWAS. ResultsA significant genotype variance was detected for seed protein and amino acids and broad-sense heritability (h2) ranged from 0.45 to 0.87 (P < 0.05). The GWAS identified 39 significant SNPs associated with 15 amino acids (p < 1e-06), explaining an average of 12.2% phenotypic variation per locus. The number of significant SNPs ranged from 1 (Asp, Ile, Glu) to 23 for Phe amino acid, including six SNPs associated with one or multiple amino acids. In the training population, the prediction accuracies of protein and amino acids, tested using the 10-fold cross-validation model with whole genome-wide SNPs, ranged from 0.23 (Glu) to 0.60 (Lys) with an average value of 0.44%. Population structure had little effect on the prediction accuracy. In an empirical validation experiment involving 211 untested accessions, the averaged prediction accuracy increased by 12.3% across all traits when using the 1000 top SNPs obtained from GWAS, compared with the same number of randomly selected SNPs from the entire genome. ConclusionsLarge variations of seed protein and amino acids were found in a natural population of foxtail millet. GWAS identified 39 significant SNPs associated with 15 amino acids, and six SNPs were linked to more than one trait. The 10-fold cross-validation model produced the relatively higher prediction accuracies in seed quality traits of diverse accessions. By applying the significant SNPs from GWAS to the untested accessions, the use of 1000 GWAS-top SNPs resulted in more powerful predictions for complex nutritional traits than those using the same number of randomly selected SNPs across the genome. SignificanceThe research highlights the importance and effectiveness of integrative GWAS and genomic prediction in revealing the genetic architecture of seed protein and amino acid variation in foxtail millet. The results provide valuable insights into assessment and improvement of germplasm resources for advancing precision crop phenotyping and enhancing breeding programs for crop nutritional traits.

Investigating the causal associations between five anthropometric indicators and nonalcoholic fatty liver disease: Mendelian randomization study

BACKGROUND Although the etiology of nonalcoholic fatty liver disease (NAFLD) has not been thoroughly understood, the emerging roles of anthropometric indicators in assessing and predicting the risk of NAFLD have been highlighted by accumulating evidence. AIM To evaluate the causal relationships between five anthropometric indicators and NAFLD employing Mendelian randomization (MR) design. METHODS The Anthropometric Consortium provided genetic exposure data for five anthropometric indicators, including hip circumference (HC), waist circumference (WC), waist-to-hip ratio (WHR), body mass index (BMI), and body fat percentage (BF). Genetic outcome data for NAFLD were obtained from the United Kingdom Biobank and FinnGen Consortium. Genome-wide significant single nucleotide polymorphisms were chosen as instrumental variables. Univariable MR (UVMR) and multivariable MR (MVMR) designs with analytical approaches, including inverse variance weighted (IVW), MR-Egger, weighted median (WM), and weighted mode methods, were used to assess the causal relationships between anthropometric indicators and NAFLD. RESULTS Causal relationships were revealed by UVMR, indicating that a higher risk of NAFLD was associated with a per-unit increase in WC [IVW: odds ratio (OR) = 2.67, 95%CI: 1.42-5.02, P = 2.25 × 10−3], and BF was causally associated with an increased risk of NAFLD (WM: OR = 2.23, 95%CI: 1.07-4.66, P = 0.033). The presence of causal effects of WC on the decreased risk of NAFLD was supported by MVMR after adjusting for BMI and smoking. However, no causal association between BF and NAFLD was observed. In addition, other causal relationships of HC, WHR (BMI adjusted), and BMI with the risk of NAFLD were not retained after FDR correction. CONCLUSION This study establishes a causal relationship, indicating that an increase in WC is associated with a higher risk of NAFLD. This demonstrates that a suitable decrease in WC is advantageous for preventing NAFLD.

Causal Associations of Modifiable Risk Factors With Migraine: Evidence From Mendelian Randomization Analysis.

Background and objectives The exact etiology of migraine is unknown; however, it is likely a mixture of genetic and non-genetic factors including lifestyle variables like smoking and diet. This study aims to assess the causal effect of modifiable risk factors on the risk of migraine using two-sample Mendelian randomization. Materials and methods The study used publicly available genome-wide significant single nucleotide polymorphisms (SNPs). The study evaluated a diverse smoking exposure, encompassing age at smoking initiation, smoking intensity, and maternal smoking, alongside other pertinent risk factors, namely key dietary aspects, coffee consumption, BMI, and physical activity. Self-reported migraine was the outcome of the study. The genetic data for migraine were obtained from the FinnGen (Finland) and the UK Biobank (United Kingdom) cohorts. Results With sample sizes ranging from 64,949 to 632,802 for each risk factor collected from several consorts, the study included a total of 282 SNPs for all risk factors. The findings demonstrated that in the FinnGen consortium, genetically estimated dietary factors as well as BMI, were significantly associated with the risk of migraine (OR 0.765 per single unit of BMI, p = 0.011; OR 0.468 per one SD higher cheese intake, p = 0.012; OR 0.286 per one SD higher salad intake, p = 0.004, and 0.625 per one SD higher coffee consumption, p = 0.003, respectively). The results also showed that in the UK Biobankspecifically, a genetically estimated history of maternal smoking was significantly associated with an elevated risk of migraine (OR=1.02, p=0.004). Conclusions The latest study implies a connection between maternal smoking and a heightened risk of migraines, whereas cheese intake, salad intake, coffee consumption, BMI, and physical activity are associated with a lower risk of migraine development.

Severe COVID-19 and chronic kidney disease: bidirectional mendelian randomization study

Traditional observational research has revealed an association between severe COVID-19 and chronic kidney disease (CKD). It is unclear whether there is a causative connection between them. Our goal was to determine whether genetically predicted CKD is associated with the risk of critical COVID-19. We aimed to investigate potential underlying genetic mechanisms that could explain this relationship, paving the way for personalized risk assessment and targeted interventions to mitigate the effects of COVID-19 on individuals with CKD. Using combined data from a GWAS on European ancestry and CKD (n = 117,165) and critical COVID-19 (n = 1,059,456), bidirectional Mendelian randomization analysis was performed. Four single nucleotide polymorphisms (SNPs) were chosen from the genome as CKD instrumental variables (IVs). In addition to MR‒Egger regression, weighted mode approaches, and weighted medians, we employed the inverse-variance weighted estimate as our primary analytical method. A significant association of CKD with critical COVID-19 (OR = 1.28, 95% confidence interval [CI]: 1.04–1.58, p = 0.01811) was found. However, using 6 genome-wide significant SNPs as IVs for critical COVID‐19, we could not discover a meaningful correlation between severe COVID‐19 and CKD (OR = 1.03, 95% CI: 0.96–1.10, p = 0.3947). We found evidence to support a causal relationship between CKD and severe COVID-19 in European population. This underscores the need for comprehensive monitoring and specialized care strategies for individuals with CKD to mitigate the heightened risk and severity of COVID-19 complications.

Elucidating the causal association between gut microbiota and intrahepatic cholangiocarcinoma through Mendelian randomization analysis.

Intrahepatic cholangiocarcinoma (ICC) is an aggressive liver cancer with poor prognosis. The gut microbiota has been linked to ICC, but evidence for causality is lacking. Elucidating causal gut microbiota-ICC links could inform prevention and treatment strategies. We performed a bidirectional two-sample Mendelian randomization (MR) study to investigate causal associations between gut microbiota and ICC risk. Genome-wide significant single nucleotide polymorphisms (SNPs) associated with gut microbiota abundances were utilized as instrumental variables (IVs). Multiple methods assessed causality and sensitivity analyses evaluated result robustness. Bioinformatics analysis of genetic loci linked to gut microbiota and ICC examined potential mechanisms. Genetically predicted increases in Veillonellaceae, Alistipes, Enterobacteriales, and Firmicutes were suggestively associated with higher ICC risk, while increases in Anaerostipes, Paraprevotella, Parasutterella, and Verrucomicrobia appeared protective. Bioinformatics analysis revealed differentially expressed genes near gut microbiota-associated loci may influence ICC through regulating pathways and tumor immune microenvironment. Our findings provide suggestive evidence for causal links between specific gut microbiota and ICC risk.

Ethnic-specific associations between body mass index and gastric cancer: a Mendelian randomization study in European and Korean populations.

Given the uncertainties surrounding the associations in previous epidemiological studies, we conducted linear and nonlinear Mendelian randomization (MR) studies to evaluate whether body mass index (BMI) associated with gastric cancer (GC) risk in European and Korean. Genome-wide association study-summary statistics were used from the Pan-UK Biobank, the Genetic Investigation of Anthropometric Traits consortium, the K-CHIP consortium, and BioBank Japan. BMI-associated single nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs) in MR to identify the association between BMI and GC. Both linear and nonlinear MR analyses were performed. Sensitivity analyses were also conducted for individuals below or above a BMI of 24kg/m2. The study used 22 and 55 SNPs as IVs for BMI in European and Korean populations, respectively. Genetically predicted BMI was positively associated with GC risk in the European population (Odds ratio per 1kg/m2 increase; 95% CI = 1.17; 1.01-1.36 using simple median method), but no significant association was observed in the Korean population. However, the nonlinear MR identified a U-shaped association between BMI and GC in the Korean population, with both low and high BMIs associated with increased GC risk. A BMI of 24kg/m2 presented the lowest risk. Sensitivity analyses did not yield any genome-wide significant SNPs. While MR analysis suggests a linear association between BMI and GC in those of European ancestry, nonlinear MR hints at a U-shaped association in Koreans. This suggests the association between BMI and GC risk may vary according to ethnic ancestry.

Genome wide association study of growth and feed efficiency traits in rabbits

Feed efficiency is a major production trait in animal genetic breeding schemes. To further investigate the genetic control of feed efficiency in rabbits, we performed a genome-wide association study (GWAS) for growth and feed efficiency on 679 rabbits genotyped with the Affimetrix Axiom Rabbit 200K Genotyping Array. After quality control, 127 847 single-nucleotide polymorphisms (SNP) were retained for association analyses. The GWAS were performed using GEMMA software, applying a mixed univariate animal model with a linear regression on each SNP allele. The traits analysed were weight at weaning and at 63 days of age, average daily gain, total individual feed intake, feed conversion ratio and residual feed intake. No significant SNP was found for growth traits or feed intake. Fifteen genome-wide significant SNPs were detected for feed conversion ratio on OCU7, spanning from 124.8 Mbp to 126.3 Mbp, plus two isolated SNP on OCU2 (77.3 Mbp) and OCU8 (16.5 Mbp). For residual feed intake, a region on OCU18 (46.1-53.0 Mbp) was detected, which contained a putative functional candidate gene, GOT1.

Angular limb deformity associated with TSPAN18, NRG3 and NOVA2 in Rambouillet rams

Angular limb deformity (ALD) affects many species of livestock and companion animals. The mechanisms of ALD development are not well understood, but previous research suggests the involvement of genetic risk factors. A case-control genome-wide association study (GWAS) was conducted with 40 ALD-affected and 302 unaffected Rambouillet rams and 40,945 single nucleotide polymorphisms (SNPs). Forelimbs of 6 ALD-affected rams were examined and diagnosed with osteochondrosis. Genome-wide or chromosome-wide significant SNPs were positioned exonic, intronic or within the 3′UTR of genes TSPAN18, NRG3 and NOVA2, respectively. These genes have previously described roles related to angiogenesis and osteoblast, osteoclast and chondrocyte proliferation and differentiation, which suggests the possibility for their involvement in the pathogenesis of osteochondrosis. Functional consequences of SNPs were evaluated through transcription factor binding site analysis, which predicted binding sites for transcription factors of known importance to bone growth, including SOX6, SOX9 and RUNX2. The identification of genetic risk factors for ALD may help to improve animal welfare and production in Rambouillet, a breed known to be at risk for ALD development. This study proposes genes TSPAN18, NRG3 and NOVA2 as targets for further research towards understanding the etiology of ALD in Rambouillet sheep.

Birth weight influences cardiac structure, function, and disease risk: evidence of a causal association.

Low birth weight is a common pregnancy complication, which has been associated with higher risk of cardiometabolic disease in later life. Prior Mendelian randomization (MR) studies exploring this question do not distinguish the mechanistic contributions of variants that directly influence birth weight through the foetal genome (direct foetal effects), vs. variants influencing birth weight indirectly by causing an adverse intrauterine environment (indirect maternal effects). In this study, MR was used to assess whether birth weight, independent of intrauterine influences, is associated with cardiovascular disease risk and measures of adverse cardiac structure and function. Uncorrelated (r2 < .001), genome-wide significant (P < 5 × 10-8) single nucleotide polymorphisms were extracted from genome-wide association studies summary statistics for birth weight overall, and after isolating direct foetal effects only. Inverse-variance weighted MR was utilized for analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischaemic stroke, and 16 measures of cardiac structure and function. Multiple comparisons were accounted for by Benjamini-Hochberg correction. Lower genetically-predicted birth weight, isolating direct foetal effects only, was associated with an increased risk of coronary artery disease (odds ratio 1.21, 95% confidence interval 1.06-1.37; P = .031), smaller chamber volumes, and lower stroke volume, but higher contractility. The results of this study support a causal role of low birth weight in cardiovascular disease, even after accounting for the influence of the intrauterine environment. This suggests that individuals with a low birth weight may benefit from early targeted cardiovascular disease prevention strategies, independent of whether this was linked to an adverse intrauterine environment during gestation.

Causal associations of gut microbiota and metabolites on sepsis: a two-sample Mendelian randomization study.

Sepsis stands as a dire medical condition, arising when the body's immune response to infection spirals into overdrive, paving the way for potential organ damage and potential mortality. With intestinal flora's known impact on sepsis but a dearth of comprehensive data, our study embarked on a two-sample Mendelian randomization analysis to probe the causal link between gut microbiota and their metabolites with severe sepsis patients who succumbed within a 28-day span. Leveraging data from Genome-wide association study (GWAS) and combining it with data from 2,076 European descendants in the Framingham Heart Study, single-nucleotide polymorphisms (SNPs) were employed as Instrumental Variables (IVs) to discern gene loci affiliated with metabolites. GWAS summary statistics for sepsis were extracted from the UK Biobank consortium. In this extensive exploration, 93 distinct genome-wide significant SNPs correlated with gut microbial metabolites and specific bacterial traits were identified for IVs construction. Notably, a substantial link between Coprococcus2 and both the incidence (OR of 0.80, 95% CI: 0.68-0.94, P=0.007) and the 28-day mortality rate (OR 0.48, 95% CI: 0.27-0.85, P=0.013) of sepsis was observed. The metabolite α-hydroxybutyrate displayed a marked association with sepsis onset (OR=1.08, 95% CI: 1.02-1.15, P=0.006) and its 28-day mortality rate (OR=1.17, 95% CI: 1.01-1.36, P=0.029). This research unveils the intricate interplay between the gut microbial consortium, especially the genus Coprococcus, and the metabolite α-hydroxybutyrate in the milieu of sepsis. The findings illuminate the pivotal role of intestinal microbiota and their metabolites in sepsis' pathogenesis, offering fresh insights for future research and hinting at novel strategies for sepsis' diagnosis, therapeutic interventions, and prognostic assessments.

Genome-wide association study in 404,302 individuals identifies 7 significant loci for reaction time variability

Reaction time variability (RTV), reflecting fluctuations in response time on cognitive tasks, has been proposed as an endophenotype for many neuropsychiatric disorders. There have been no large-scale genome-wide association studies (GWAS) of RTV and little is known about its genetic underpinnings. Here, we used data from the UK Biobank to conduct a GWAS of RTV in participants of white British ancestry (n = 404,302) as well as a trans-ancestry GWAS meta-analysis (n = 44,873) to assess replication. We found 161 genome-wide significant single nucleotide polymorphisms (SNPs) distributed across 7 genomic loci in our discovery GWAS. Functional annotation of the variants implicated genes involved in synaptic function and neural development. The SNP-based heritability (h2SNP) estimate for RTV was 3%. We investigated genetic correlations between RTV and selected neuropsychological traits using linkage disequilibrium score regression, and found significant correlations with several traits, including a positive correlation with mean reaction time and schizophrenia. Despite the high genetic correlation between RTV and mean reaction time, we demonstrate distinctions in the genetic underpinnings of these traits. Lastly, we assessed the predictive ability of a polygenic score (PGS) for RTV, calculated using PRSice and PRS-CS, and found that the RTV-PGS significantly predicted RTV in independent cohorts, but that the generalisability to other ancestry groups was poor. These results identify genetic underpinnings of RTV, and support the use of RTV as an endophenotype for neurological and psychiatric disorders.