Separate Genome-wide Association Studies Research Articles

The identification of plasma and cerebrospinal fluid metabolites causally associated with mental disorders from a genetic perspective.

Metabolomics research is a promising orientation for the diagnosis and intervention of several diseases, and observational studies have found many metabolic profiles to be associated with mental disorders. However, the causal relationship between plasma and cerebrospinal fluid (CSF) metabolites and mental disorders has not been established. We identified independent genetic variants associated with plasma, CSF metabolites, and mental disorders from pooled data in the published Genome-wide association studies (GWASs) and performed Mendelian randomization (MR) to investigate causal relationships. Genetic information on the screened mental disorders were derived from separate GWAS data sources as exploratory and validation datasets. Inverse variance weighting (IVW) was adopted as the primary method for MR analysis. We also applied sensitivity analyses to examine the reliability of the MR analysis results. Further enrichment analyses provided a deeper insight into the biological mechanisms of the three mental disorders. A dual analysis of the exploratory and validation datasets identified eight plasma metabolites and three CSF metabolites causally associated with MDD, two plasma metabolites and one CSF metabolite causally associated with anxiety disorders, and four plasma metabolites and two CSF causally associated with ASD. Horizontal pleiotropy and heterogeneity tests indicate the validity of our MR studies. Enrichment analysis uncovered metabolic pathways associated with disease. Our study identified plasma and cerebrospinal fluid metabolites that were causally associated with 3 mental disorders. Characterization of disease-associated metabolites not only deepens the understanding of pathological mechanisms, but also supports clinical diagnosis and prognosis.

Effect of L-Carnitine Level on the Risk of Neuromyelitis Optica Spectrum Disorders: A Two-Sample Mendelian Randomization Study.

Previous research has often focused on studying the CNS damage in neuromyelitis optica spectrum disorders (NMOSD), while the role of the peripheral blood in the development of NMOSD is also of significant importance. The relationship between metabolites in blood and cerebrospinal fluid (CSF) with neuroimmune is receiving increasing attention. L-carnitine, whose astrocytic accumulation is associated with neuroinflammation and demyelination, may participate in the pathogenesis of NMOSD. However, whether circulating L-carnitine level has a causal effect on NMOSD risk needs elucidation. With large data sets now available, we used two-sample Mendelian randomization (MR) to determine whether circulating L-carnitine level is causally associated with the risk of NMOSD. Genetic variants associated with circulating L-carnitine levels were derived from a genome-wide association study (GWAS) of 7797 individuals from TwinsUK and KORA F4 cohorts. NMOSD summary statistics, including 215 cases and 1244 controls, were obtained from a separate GWAS. Subgroup analyses included aquaporin-4 (AQP4)-IgG-seropositive NMOSD (132 cases) and AQP4-IgG-seronegative NMOSD (83 cases). We used two-sample MR to explore associations between circulating L-carnitine levels and NMOSD risk, as well as its seropositive and seronegative subtypes. 16 SNPs (single nucleotide polymorphisms) were significantly associated with circulating L-carnitine level (P < 5 × 10-8), all of which were independent and available in the NMOSD dataset, after 1 SNP removed for being palindromic with intermediate allele frequencies in harmonization. Finally, a high circulating L-carnitine level conferred a protective effect against combined NMOSD (OR = 2.216 × 10-4, 95% confidence interval [CI] = 2.335 × 10-7-2.104 × 10-1, P = 0.0161) as well as AQP4-IgG-seronegative NMOSD (OR = 7.678 × 10-7, 95% CI = 2.233 × 10-11-2.640 × 10-2, P = 0.0082). There is no causal effect on AQP4-IgG-seropositive NMOSD risk (OR = 5.471 × 10-3, CI = 1.090 × 10-6-27.465, P = 0.2798) by circulating L-carnitine. Results remained positive and robust after the horizontal pleiotropy test, heterogeneity test, and Bonferroni test. In the reverse MR analysis, there was no causal effect of NMOSD and its subtypes on circulating L-carnitine levels. Our findings suggest that higher circulating L-carnitine levels may reduce the risk of NMOSD, particularly in AQP4-IgG-seronegative patients. L-carnitine could serve as a valuable biomarker and potential therapeutic target for NMOSD, especially in cases without AQP4-IgG. The genetic evidence from this study supports further exploration of L-carnitine's role in managing NMOSD.

Association between immune cells and membranous nephropathy: a two-sample Mendelian randomization study

IntroductionMultiple studies have indicated that immune cells play a significant role in the occurrence and development of membranous nephropathy (MN). However, the causal relationship between the two has not been fully established. To further investigate this, we employed a Mendelian randomization (MR) study design.Material and methodsGenetic instrumental variables for immune cells were sourced from an extensive genome-wide association study (GWAS). MN summary statistics, involving 2,150 cases and 5,829 controls, were obtained from a separate GWAS. The primary analysis employed the inverse-variance weighted (IVW) method. To explore reverse causation, a reverse MR analysis was undertaken. Rigorous sensitivity analyses were conducted to ensure the resilience and reliability of the study's findings.ResultsWe identified eight immunophenotypes associated with a reduced risk of MN and all of them were the protective factors for MN. The sensitivity analyses consistently yielded similar results for these immune traits. In the reverse MR analysis, we did not observe any statistically significant associations between MN and these eight immunophenotypes.ConclusionsOur study, utilizing genetic approaches, provides evidence for a causal relationship between immune cells and MN, which has implications for clinical diagnosis and treatment. Further comprehensive investigations are needed to explore the detailed mechanisms underlying the impact of immune cells on MN.

Cysteine cathepsins and autoimmune diseases: A bidirectional Mendelian randomization.

Cysteine cathepsins are proteolytic enzymes crucial in various physiological and pathological processes, primarily operating within lysosomes. Their functions include protein degradation, immune system regulation, and involvement in various diseases. While some cysteine cathepsins play important roles in the immune system, their connection to autoimmune diseases remains unclear. This study proposes using Mendelian randomization to explore the causal relationship between cysteine cathepsins and autoimmune diseases. Single nucleotide polymorphisms (SNPs) for cysteine cathepsins were obtained from a publicly available genome-wide association study (GWAS) dataset, while outcome SNP data were sourced from 10 separate GWAS datasets. Mendelian randomization (MR) analysis employed the Wald ratio (WR) and inverse variance weighted (IVW) approach as primary methods, supplemented by the weighted median and MR-Egger methods. Heterogeneity was assessed using Cochran Q test, and sensitivity analysis was conducted using the MR-PRESSO method. The association strength between exposure and outcome was evaluated using odds ratios (OR) with 95% confidence intervals (CI). The study identified a potential positive correlation between elevated cathepsin B and psoriasis (Wald ratio OR = 1.449, 95% CI: 1.053-1.993, P = .0227). Elevated cathepsin F was potentially linked to ulcerative colitis (WR OR = 1.073, 95% CI: 1.021-1.127, P = .0056), ankylosing spondylitis (WR OR = 1.258, 95% CI: 1.082-1.463, P = .0029), and primary biliary cholangitis(PBC) (WR OR = 1.958, 95% CI: 1.326-2.889, P = .0007). Conversely, cathepsin H appeared protective against celiac disease (WR OR = 0.881, 95% CI: 0.838-0.926, P = 6.5e-7), though elevated levels may increase the risk of type 1 diabetes (IVW OR = 1.121, 95% CI: 1.053-1.194, P = .0003) and PBC (WR OR = 1.792, 95% CI: 1.062-3.024, P = .0288). Cathepsin Z was also associated with an increased risk of type 1 diabetes (IVW OR = 1.090, 95% CI: 1.006-1.181, P = .0349). The MR analysis suggests potential risks of cathepsin B with psoriasis, cathepsin F with ulcerative colitis, ankylosing spondylitis, and PBC, and cathepsin Z with type 1 diabetes. Conversely, cathepsin H may protect against celiac disease but could increase the risk of type 1 diabetes and PBC.

Trait imputation enhances nonlinear genetic prediction for some traits.

The expansive collection of genetic and phenotypic data within biobanks offers an unprecedented opportunity for biomedical research. However, the frequent occurrence of missing phenotypes presents a significant barrier to fully leveraging this potential. In our target application, on one hand, we have only a small and complete dataset with both genotypes and phenotypes to build a genetic prediction model, commonly called a polygenic (risk) score (PGS or PRS); on the other hand, we have a large dataset of genotypes (e.g. from a biobank) without the phenotype of interest. Our goal is to leverage the large dataset of genotypes (but without the phenotype) and a separate genome-wide association studies summary dataset of the phenotype to impute the phenotypes, which are then used as an individual-level dataset, along with the small complete dataset, to build a nonlinear model as PGS. More specifically, we trained some nonlinear models to 7 imputed and observed phenotypes from the UK Biobank data. We then trained an ensemble model to integrate these models for each trait, resulting in higher R2 values in prediction than using only the small complete (observed) dataset. Additionally, for 2 of the 7 traits, we observed that the nonlinear model trained with the imputed traits had higher R2 than using the imputed traits directly as the PGS, while for the remaining 5 traits, no improvement was found. These findings demonstrate the potential of leveraging existing genetic data and accounting for nonlinear genetic relationships to improve prediction accuracy for some traits.

Assessment of the causal relationship between inflammatory bowel diseases and chronic kidney diseases: A two-sample bidirectional mendelian randomization study among European population.

Kidney function can be impaired in patients with inflammatory bowel diseases (IBD), including Crohn's diseases (CD) and ulcerative colitis (UC). However, the causal relationship between IBD and chronic kidney diseases (CKD) remains unclear. We determined the causal association between IBD and CKD by performing two-sample bidirectional mendelian randomization (MR) analyses. Independent genetic variants were selected as instrumental variables (IVs) of the exposure from open-access genome-wide association studies (GWAS) among European ancestry. IVs-outcome estimates were extracted from three separate GWAS for IBD and two for CKD, respectively. Inverse-variance-weighted model was used as the primary MR method. The pleiotropic effect and heterogeneity were evaluated. For either direction, analyses were performed per outcome database and were subsequently meta-analysed. Genetically predicted IBD was associated with higher risk of CKD (OR: 1.045, 95% CI: 1.016-1.073, P = 0.002) by including 42 344 IBD cases and 229 164 controls. Further analyses showed genetic liability to CD increased the risk of CKD (OR: 1.057, 95% CI: 1.027-1.087, p < 0.001) whereas UC did not (OR: 0.999, 95% CI:0.969-1.031, p = 0.970). In contrast, genetically predicted CKD was not associated with IBD (OR: 1.010, 95% CI: 0.965-1.056, p = 0.676), UC (OR: 1.011, 95% CI: 0.948-1.078, p = 0.746) and CD (OR: 1.024; 95% CI: 0.963-1.089, p = 0.447). We concluded that CD, but not UC, can increase the risk of CKD causally. CD, but not UC, can increase the risk of chronic kidney disease causally. These findings enhance our understanding of the differential impact of IBD subtypes on CKD. It may be necessary to monitor kidney function regularly in patients with CD.

Association between blood metabolites and basal cell carcinoma risk: a two-sample Mendelian randomization study.

Circulating metabolites, which play a crucial role in our health, have been reported to be disordered in basal cell carcinoma (BCC). Despite these findings, evidence is still lacking to determine whether these metabolites directly promote or prevent BCC's progression. Therefore, our study aims to examine the potential effects of circulating metabolites on BCC progression. We conducted a two-sample Mendelian randomization (MR) analysis using data from two separate genome-wide association studies (GWAS). The primary study included data for 123 blood metabolites from a GWAS with 25,000 Finnish individuals, while the secondary study had data for 249 blood metabolites from a GWAS with 114,000 UK Biobank participants.GWAS data for BCC were obtained from the UK Biobank for the primary analysis and the FinnGen consortium for the secondary analysis. Sensitivity analyses were performed to assess heterogeneity and pleiotropy. In the primary analysis, significant causal relationships were found between six metabolic traits and BCC with the inverse variance weighted (IVW) method after multiple testing [P < 4 × 10-4 (0.05/123)]. Four metabolic traits were discovered to be significantly linked with BCC in the secondary analysis, with a significance level of P < 2 × 10-4 (0.05/249). We found that all the significant traits are linked to Polyunsaturated Fatty Acids (PUFAs) and their degree of unsaturation. Our research has revealed a direct link between the susceptibility of BCC and Polyunsaturated Fatty Acids and their degree of unsaturation. This discovery implies screening and prevention of BCC.

Assessing causal relationships between gut microbiota and psoriasis: evidence from two sample Mendelian randomization analysis

Mounting data hints that the gut microbiota's role may be pivotal in understanding the emergence of psoriasis. However, discerning a direct causal link is yet elusive. In this exploration, we adopted a Mendelian randomization (MR) strategy to probe the prospective causal interplay between the gut's microbial landscape and the predisposition to psoriasis. Genetic markers acting as instrumental variables for gut microbiota were extrapolated from a genome-wide association study (GWAS) encompassing 18,340 individuals. A separate GWAS yielded summary data for psoriasis, which covered 337,159 patients and 433,201 control subjects. The primary analysis hinged on inverse variance weighting (IVW). Additional methods like the weighted median approach and MR-Egger regression were employed to validate the integrity of our findings. Intriguing correlations emerged between psoriasis risk and eight specific bacterial traits. To illustrate: Mollicutes presented an odds ratio (OR) of 1.003 with a 95% confidence interval (CI) spanning 1.001–1.005 (p = 0.016), while the family. Victivallaceae revealed an OR of 0.998 with CI values between 0.997 and 0.999 (p = 0.023). Eubacterium (coprostanoligenes group) revealed an OR of 0.997 with CI values between 0.994 and 0.999 (p = 0.027). Eubacterium (fissicatena group) revealed an OR of 0.997 with CI values between 0.996 and 0.999 (p = 0.005). Holdemania revealed an OR of 1.001 with CI values 1–1.003 (p = 0.034). Lachnospiraceae (NK4A136 group) revealed an OR of 0.997 with CI values between 0.995 and 0.999 (p = 0.046). Lactococcus revealed an OR of 0.998 with CI values between 0.996 and 0.999 (p = 0.008). Tenericutes revealed an OR of 1.003 with CI values between 1.001 and 1.006 (p = 0.016). Sensitivity analysis for these bacterial features yielded congruent outcomes, reinforcing statistically significant ties between the eight bacterial entities and psoriasis. This comprehensive probe underscores emerging evidence pointing towards a plausible causal nexus between diverse gut microbiota and the onset of psoriasis. It beckons further research to unravel the intricacies of how the gut's microbial constituents might sway psoriasis's pathogenesis.

Methotrexate and the Risk of Dementia: A Two-Sample Mendelian Randomization Study.

Recent studies have suggested a potential association between methotrexate use and an increased risk of dementia. However, the causal relationship between methotrexate and dementia remains unclear. This study aims to investigate the potential causal effect of methotrexate use on the risk of dementia using a two-sample Mendelian randomization (TSMR) approach. We conducted a TSMR study using summary statistics from genome-wide association studies (GWAS) of methotrexate use and dementia. We obtained genetic instruments for methotrexate use from a large-scale GWAS meta-analysis and genetic instruments for dementia from a separate GWAS meta-analysis. We performed several statistical analyses, including inverse-variance weighted (IVW), weighted median (WM1), weighted mode (WM2), and MR-Egger regression methods, to estimate the causal effect of methotrexate on dementia risk. Our TSMR analysis showed a significant positive association between genetic predisposition to methotrexate use and dementia risk. The IVW method estimated a causal odds ratio (OR) of 0.476 [95% confidence interval (CI) 0.362-0.626] per unit increase in the log odds ratio of methotrexate use. WM1, WM2, and MR-Egger methods provided consistent results. The findings of this mendelian randomization (MR) study suggest a potential causal effect of methotrexate use on the risk of dementia. However, further research is needed to validate these findings and explore the underlying mechanisms. Since methotrexate is widely prescribed for various autoimmune diseases, a better understanding of its potential impact on dementia risk is crucial for optimizing treatment strategies and addressing potential adverse effects.

Evaluating the causal effect of atherosclerosis on the risk of intervertebral disc degeneration.

Intervertebral disc degeneration (IDD) and atherosclerosis are two common age-related conditions that can cause significant morbidity. While previous studies have suggested an association between the two conditions, the nature of this association remains unclear. We used Mendelian randomization (MR) to investigate the causal relationship between IDD and atherosclerosis. We identified genetic variants associated with IDD using summary statistics from a large genome-wide association study (GWAS). These variants were then used as instrumental variables to infer causal relationships with atherosclerosis in summary statistics from a separate GWAS. Our MR analysis provided evidence for a causal relationship between IDD and atherosclerosis. We found that the genetic predisposition to atherosclerosis was associated with a higher risk of IDD (odds ratio [OR] = 3.55, 95% confidence interval [CI]: 1.07-11.74, p = 0.04). The IVW estimates were consistent with the observational findings and other robust MR methods. Sensitivity analyses suggested that our findings were robust to potential sources of bias. Our study provides evidence for a causal link between IDD and atherosclerosis, suggesting that interventions targeting atherosclerosis could have potential benefits for reducing the risk of IDD. Further research is needed to explore the underlying mechanisms that link these two conditions and to investigate potential therapeutic interventions.

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

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

Evaluating methods for integrating single-cell data and genetics to understand inflammatory disease complexity.

Understanding genetic underpinnings of immune-mediated inflammatory diseases is crucial to improve treatments. Single-cell RNA sequencing (scRNA-seq) identifies cell states expanded in disease, but often overlooks genetic causality due to cost and small genotyping cohorts. Conversely, large genome-wide association studies (GWAS) are commonly accessible. We present a 3-step robust benchmarking analysis of integrating GWAS and scRNA-seq to identify genetically relevant cell states and genes in inflammatory diseases. First, we applied and compared the results of three recent algorithms, based on pathways (scGWAS), single-cell disease scores (scDRS), or both (scPagwas), according to accuracy/sensitivity and interpretability. While previous studies focused on coarse cell types, we used disease-specific, fine-grained single-cell atlases (183,742 and 228,211 cells) and GWAS data (Ns of 97,173 and 45,975) for rheumatoid arthritis (RA) and ulcerative colitis (UC). Second, given the lack of scRNA-seq for many diseases with GWAS, we further tested the tools' resolution limits by differentiating between similar diseases with only one fine-grained scRNA-seq atlas. Lastly, we provide a novel evaluation of noncoding SNP incorporation methods by testing which enabled the highest sensitivity/accuracy of known cell-state calls. We first found that single-cell based tools scDRS and scPagwas called superior numbers of supported cell states that were overlooked by scGWAS. While scGWAS and scPagwas were advantageous for gene exploration, scDRS effectively accounted for batch effect and captured cellular heterogeneity of disease-relevance without single-cell genotyping. For noncoding SNP integration, we found a key trade-off between statistical power and confidence with positional (e.g. MAGMA) and non-positional approaches (e.g. chromatin-interaction, eQTL). Even when directly incorporating noncoding SNPs through 5' scRNA-seq measures of regulatory elements, non disease-specific atlases gave misleading results by not containing disease-tissue specific transcriptomic patterns. Despite this criticality of tissue-specific scRNA-seq, we showed that scDRS enabled deconvolution of two similar diseases with a single fine-grained scRNA-seq atlas and separate GWAS. Indeed, we identified supported and novel genetic-phenotype linkages separating RA and ankylosing spondylitis, and UC and crohn's disease. Overall, while noting evolving single-cell technologies, our study provides key findings for integrating expanding fine-grained scRNA-seq, GWAS, and noncoding SNP resources to unravel the complexities of inflammatory diseases.

Bidirectional Mendelian Randomization of Causal Relationship between Inflammatory Cytokines and Different Pathological Types of Lung Cancer.

Prior research has proposed a potential association between lung cancer and inflammatory cytokines, yet the specific causal relationship remains unclear, especially across various lung cancer pathologies. This study utilized bidirectional Mendelian randomization (MR) to explore these causal connections, unveiling novel insights. Our research revealed distinctive inflammatory cytokine profiles for each subtype of lung cancer and identified potential biomarkers that could refine diagnostic and therapeutic approaches. We applied two-sample Mendelian randomization, leveraging genetic variance data from three extensive genome-wide association studies (GWAS) focusing on different lung cancer types (lung adenocarcinoma: 1590 cases and 314,193 controls of healthy individuals of European descent; lung squamous cell carcinoma: 1510 cases and 314,193 controls of European ancestry; small cell lung cancer: 717 cases and 314,193 controls of European ancestry). A separate GWAS summary on inflammatory cytokines from 8,293 healthy participants was also included. The inverse variance weighting method was utilized to examine causal relationships, with robustness confirmed through multiple sensitivity analyses, including MR-Egger, weighted median, and MR-PRESSO. Our analysis revealed that elevated levels of IL_1RA were associated with an increased risk of lung adenocarcinoma (OR: 1.29, 95% CI: 1.02-1.64, p = 0.031), while higher MCP_1_MCAF levels correlated with a decreased risk of lung squamous cell carcinoma (OR: 0.77, 95% CI: 0.61-0.98, p = 0.031). Furthermore, IL_10, IL_13, and TRAIL levels were positively associated with lung squamous cell carcinoma risk (IL_10: OR: 1.27, 95% CI: 1.06-1.53, p = 0.012; IL_13: OR: 1.15, 95% CI: 1.06-1.53, p = 0.036; TRAIL: OR: 1.15, 95% CI: 1.06-1.53, p = 0.043). No association was found between inflammatory cytokine levels and small cell lung cancer development, whereas SDF_1A and B-NGF were linked to an increased risk of this cancer type (SDF_1A: OR: 1.13, 95% CI: 1.05-1.21, p = 0.001; B-NGF: OR: 1.13, 95% CI: 1.01-1.27, p = 0.029). No significant relationship was observed between the 41 circulating inflammatory cytokines and lung adenocarcinoma or squamous cell carcinoma development. Our findings indicate distinct associations between specific inflammatory cytokines and different types of lung cancer. Elevated IL_1RA levels are a risk marker for lung adenocarcinoma, whereas higher MCP_1_MCAF levels appear protective against lung squamous cell carcinoma. Conversely, elevated levels of IL_10, IL_13, and TRAIL are linked with an increased risk of lung squamous cell carcinoma. The relationships of SDF_1A and B-NGF with small-cell lung cancer highlight the complexity of inflammatory markers in cancer development. This study provides a nuanced understanding of the role of inflammatory cytokines in lung cancer, underscoring their potential in refining diagnosis and treatment strategies.

GWAS reveals a rapidly evolving candidate avirulence effector in the Cercospora leaf spot pathogen.

The major resistance gene BvCR4 recently bred into sugar beet hybrids provides a high level of resistance to Cercospora leaf spot caused by the fungal pathogen Cercospora beticola. The occurrence of pathogen strains that overcome BvCR4 was studied using field trials in Switzerland conducted under natural disease pressure. Virulence of a subset of these strains was evaluated in a field trial conducted under elevated artificial disease pressure. We created a new C. beticola reference genome and mapped whole genome sequences of 256 isolates collected in Switzerland and Germany. These were combined with virulence phenotypes to conduct three separate genome-wide association studies (GWAS) to identify candidate avirulence genes. We identified a locus associated with avirulence containing a putative avirulence effector gene named AvrCR4. All virulent isolates either lacked AvrCR4 or had nonsynonymous mutations within the gene. AvrCR4 was present in all 74 isolates from non-BvCR4 hybrids, whereas 33 of 89 isolates from BvCR4 hybrids carried a deletion. We also mapped genomic data from 190 publicly available US isolates to our new reference genome. The AvrCR4 deletion was found in only one of 95 unique isolates from non-BvCR4 hybrids in the United States. AvrCR4 presents a unique example of an avirulence effector in which virulent alleles have only recently emerged. Most likely these were selected out of standing genetic variation after deployment of BvCR4. Identification of AvrCR4 will enable real-time screening of C. beticola populations for the emergence and spread of virulent isolates.

212 Genome-Wide Association Study Investigating the Genomic Components of Efficiency in Beef Cows

Abstract Efficiency of mature beef cows consuming high-forage diets is not comparable with standard definitions of beef cattle efficiency such as feed conversion or residual feed intake in the feedlot setting. This study aimed to conduct a genome-wide association study (GWAS) to identify regions of the bovine genome associated with efficiency in mature beef cows. Ninety-eight black Angus cows were managed under extensive feeding programs over a two-year period. Using rump fat at calving, calving date, and calf weaning weight as a percentage of the body weight of the dam, a weighted percentile scoring system was used to rank efficiency. Eighty-three of the cows were retained for the GWAS. The 20 most and 20 least efficient cows (HD dataset, n=40) were genotyped with the Illumina BovineHD BeadChip (777,000 SNPs) while the remaining cows were genotyped with the Neogen GGP Bovine 100K chip (LD dataset, n = 43). The LD dataset was imputed to the HD SNP array density using Beagle5.4 (FULL dataset, n = 83). Three separate GWAS were conducted using GAPIT (version3). The first GWAS was performed on the HD dataset using a quantitative phenotype determined by the ranking system. The second GWAS was performed with the HD dataset using a qualitative phenotype (efficient vs non-efficient cows). For the final GWAS, the FULL dataset with ranked phenotypes was used. Five models were evaluated for each GWAS, including the general linear model (GLM), mixed linear model (MLM), multiple loci mixed model (MLMM), fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK). The model that best represented each dataset as determined by quantile-quantile plots was used for downstream analysis. Although results of the GWAS were not significant (Bonferroni threshold), associations were identified on BTA10, 16, 17, 25, 27 and 29. Positional candidate genes in the associated regions include: FOXN3, UPB1, SNX29, DDX54, LOC112444612, RITA1, and TACC1. Further functional analyses are required to confirm these findings; however, this work provides a foundation for identifying genes and gene mutations influencing this newly described phenotype.

Genome-Wide Analysis of Sheep Artificially or Naturally Infected with Gastrointestinal Nematodes.

The anthelmintic resistance of gastrointestinal nematodes (GINs) poses a significant threat to sheep worldwide, but genomic selection can serve as an alternative to the use of chemical treatment as a solution for parasitic infection. The objective of this study is to conduct genome-wide association studies (GWASs) to identify single nucleotide polymorphisms (SNPs) in Rambouillet (RA) and Dorper × White Dorper (DWD) lambs associated with the biological response to a GIN infection. All lambs were genotyped with a medium-density genomic panel with 40,598 markers used for analysis. Separate GWASs were conducted using fecal egg counts (FECs) from lambs (<1 year of age) that acquired their artificial infections via an oral inoculation of 10,000 Haemonchus contortus larvae (n = 145) or naturally while grazing on pasture (n = 184). A GWAS was also performed for packed cell volume (PCV) in artificially GIN-challenged lambs. A total of 26 SNPs exceeded significance and 21 SNPs were in or within 20 kb of genes such as SCUBE1, GALNT6, IGF1R, CAPZB and PTK2B. The ontology analysis of candidate genes signifies the importance of immune cell development, mucin production and cellular signaling for coagulation and wound healing following epithelial damage in the abomasal gastric pits via H. contortus during GIN infection in lambs. These results add to a growing body of the literature that promotes the use of genomic selection for increased sheep resistance to GINs.

Abstract 560: Genetics Of Physical Activity And Risk Of Cardiovascular Disease

Objective: Sedentary lifestyle with minimal physical activity is a well-established risk factor for poor metabolic health outcomes. Atherosclerotic cardiovascular diseases (ASCVD) are often thought to be associated with physical inactivity, although observational studies may be limited by residual confounding which makes causal inference challenging. Mendelian Randomization (MR) is a method which leverages the naturally random allocation of genetic variants as a natural experiment, permitting causal inference. To better characterize sedentary lifestyle behaviors, we performed a genome-wide association study (GWAS) of sedentary behaviors using genomic structural equation modeling (SEM) and conducted a MR study using this phenotype to characterize the relationship of physical inactivity to ASCVD. Methods: Genomic SEM was performed to integrate three separate GWAS of physical activity and sedentary behavior into a common factor model. Following this, two-sample univariate and multivariable MR testing the effect of sedentary behavior on ASCVD traits was performed. Outcome data was taken from the Million Veteran Program (MVP) for PAD and CAD, and the GIGASTROKE consortium for stroke. Results: The common factor GWAS of sedentary behavior identified 44 genomic risk loci. 32 of the 44 lead variants were not significantly associated with the original sedentary traits, pointing toward possible new genetic mechanisms. On gene-based testing, the CADM2 gene was implicated as the strongest risk locus of 156 mapped genes; this gene has been associated with impulsivity, substance use and obesity in prior studies. MR experiments revealed sedentary behaviors were associated with a significantly increased risk of CAD, PAD, and ischemic stroke; these effects were no longer significant when controlling for smoking, BMI, and diabetes as confounders. Conclusions: This study takes the largest available GWASs of PAD, CAD, and Stroke, and compares them against a novel GWAS of sedentary behavior traits. The findings suggest that the effects of sedentary behavior on ASCVD traits are likely not independent from other contributing factors (smoking; BMI), but that there is a shared causal pathway between these traits that has implications on the development of ASCVD.

A Common Variant in GRK5 Reveals a PAR1-Specific Mechanism for Its Regulation of Platelet Function

Two separate genome wide association studies (GWAS), recently conducted by our group and another group, have identified the variant rs10886430 in the G protein-coupled receptor kinase 5 (GRK5) gene with a minor allele frequency of ~14% in Caucasians. Both studies show that the variant resides in a megakaryocyte-specific enhancer that alters the binding of the transcription factors GATA1 and MEIS1. In contrast to the major allele (A), the minor allele (G) is associated with decreased GRK5 mRNA expression, increased platelet reactivity, and greater risk of cardiovascular disease. However, the effect of the variant on protein expression has not been investigated by either group. In addition, there is an inconsistency between the findings of each of the studies regarding the specific role of GRK5 in thrombin receptor PAR1- and PAR4-mediated platelet activation. Further studies are needed to clarify whether, and how, GRK5 regulates platelet activity via PAR1, PAR4, or both. Here we introduce the A>G mutation into a megakaryoblastic cell line, Meg-01, by CRISPR-Cas9 genome editing. GRK5 protein expression is decreased by 80% in A>G mutant Meg-01 cells compared to WT control cells. To determine whether GRK5 regulates PAR1, PAR4, or both, we have isolated human platelets and specifically blocked GRK5 activity with compound CCG273261 to compare platelet responses to PAR1- and PAR4-specific agonists. Our data show that pharmacological inhibition of GRK5 increases markers of platelet activation such as integrin activation and P-selectin surface exposure in response to PAR1 receptor agonist peptide. Platelet activation in response to PAR4 receptor agonist peptide is normal. Furthermore, this inhibition increases Ca2+ mobilization in response to PAR1 receptor agonist, but not to PAR4 receptor agonist. Consistent with the results of our functional assays, mass spectrometry analysis revealed an interaction between GRK5 and PAR1 but did not detect an interaction with PAR4. Collectively, our data show that 1) this GRK5 intronic variant regulates GRK5 expression at both transcriptional and translational levels, 2) GRK5 preferentially regulates PAR-1 over PAR4-mediated signaling, and 3) GRK5 has a binding interaction with PAR1 (Fig 1). Our findings will enable us to develop superior therapeutics for cardiovascular risk groups especially those individuals who carry the intronic variant in GRK5 and as a result are more likely to experience thrombotic events. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Genome-Wide Association Study of Adhesive Capsulitis Suggests Significant Genetic Risk Factors.

Adhesive capsulitis of the shoulder involves loss of passive range of motion with associated pain and can develop spontaneously, with no obvious injury or inciting event. The pathomechanism of this disorder remains to be elucidated, but known risk factors for adhesive capsulitis include diabetes, female sex, and thyroid dysfunction. Additionally, transcriptional profiling and pedigree analyses have suggested a role for genetics. Identification of elements of genetic risk for adhesive capsulitis using population-based techniques can provide the basis for guiding both the personalized treatment of patients based on their genetic profiles and the development of new treatments by identification of the pathomechanism. A genome-wide association study (GWAS) was conducted using the U.K. Biobank (a collection of approximately 500,000 patients with genetic data and associated ICD-10 [International Classification of Diseases, 10th Revision] codes), comparing 2,142 patients with the ICD-10 code for adhesive capsulitis (M750) to those without. Separate GWASs were conducted controlling for 2 of the known risk factors of adhesive capsulitis-hypothyroidism and diabetes. Logistic regression analysis was conducted controlling for factors including sex, thyroid dysfunction, diabetes, shoulder dislocation, smoking, and genetics. Three loci of significance were identified: rs34315830 (in WNT7B; odds ratio [OR] = 1.28; 95% confidence interval [CI], 1.22 to 1.39), rs2965196 (in MAU2; OR = 1.67; 95% CI, 1.39 to 2.00), and rs1912256 (in POU1F1; OR = 1.22; 95% CI, 1.14 to 1.31). These loci retained significance when controlling for thyroid dysfunction and diabetes. The OR for total genetic risk was 5.81 (95% CI, 4.08 to 8.31), compared with 1.70 (95% CI, 1.18 to 2.36) for hypothyroidism and 4.23 (95% CI, 2.32 to 7.05) for diabetes. The total genetic risk associated with adhesive capsulitis was significant and similar to the risks associated with hypothyroidism and diabetes. Identification of WNT7B, POU1F1, and MAU2 implicates the Wnt pathway and cell proliferation response in the pathomechanism of adhesive capsulitis. Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

Sprague Dawley (SD) rats are among the most widely used outbred laboratory rat populations. Despite this, the genetic characteristics of SD rats have not been clearly described, and SD rats are rarely used for experiments aimed at exploring genotype-phenotype relationships. In order to use SD rats to perform a genome-wide association study (GWAS), we collected behavioral data from 4,625 SD rats that were predominantly obtained from two commercial vendors, Charles River Laboratories and Harlan Sprague Dawley Inc. Using double-digest genotyping-by-sequencing (ddGBS), we obtained dense, high-quality genotypes at 291,438 SNPs across 4,061 rats. This genetic data allowed us to characterize the variation present in Charles River vs. Harlan SD rats. We found that the two populations are highly diverged (FST > 0.4). Furthermore, even for rats obtained from the same vendor, there was strong population structure across breeding facilities and even between rooms at the same facility. We performed multiple separate GWAS by fitting a linear mixed model that accounted for population structure and using meta-analysis to jointly analyze all cohorts. Our study examined Pavlovian conditioned approach (PavCA) behavior, which assesses the propensity for rats to attribute incentive salience to reward-associated cues. We identified 46 significant associations for the various metrics used to define PavCA. The surprising degree of population structure among SD rats from different sources has important implications for their use in both genetic and non-genetic studies.