scholarly journals Using the MR-Base platform to investigate risk factors and drug targets for thousands of phenotypes

2019 ◽  
Vol 4 ◽  
pp. 113 ◽  
Author(s):  
Venexia M Walker ◽  
Neil M Davies ◽  
Gibran Hemani ◽  
Jie Zheng ◽  
Philip C Haycock ◽  
...  
Keyword(s):  
Risk Factors ◽  
Web Application ◽  
Drug Targets ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
R Package ◽  
Sensitivity Analyses ◽  
Link Type ◽  
Genome Wide ◽  
Study Results

Mendelian randomization (MR) uses genetic information to strengthen causal inference concerning the effect of exposures on outcomes. This method has a broad range of applications, including investigating risk factors and appraising potential targets for intervention. MR-Base has become established as a freely accessible, online platform, which combines a database of complete genome-wide association study results with an interface for performing Mendelian randomization and sensitivity analyses. This allows the user to explore millions of potentially causal associations. MR-Base is available as a web application or as an R package. The technical aspects of the tool have previously been documented in the literature. The present article is complimentary to this as it focuses on the applied aspects. Specifically, we describe how MR-Base can be used in several ways, including to perform novel causal analyses, replicate results and enable transparency, amongst others. We also present three use cases, which demonstrate important applications of Mendelian randomization and highlight the benefits of using MR-Base for these types of analyses.

scholarly journals Using the MR-Base platform to investigate risk factors and drug targets for thousands of phenotypes

2019 ◽  
Vol 4 ◽  
pp. 113 ◽  
Author(s):  
Venexia M Walker ◽  
Neil M Davies ◽  
Gibran Hemani ◽  
Jie Zheng ◽  
Philip C Haycock ◽  
...  
Keyword(s):  
Risk Factors ◽  
Web Application ◽  
Drug Targets ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
R Package ◽  
Sensitivity Analyses ◽  
Link Type ◽  
Study Results

Mendelian randomization (MR) estimates the causal effect of exposures on outcomes by exploiting genetic variation to address confounding and reverse causation. This method has a broad range of applications, including investigating risk factors and appraising potential targets for intervention. MR-Base has become established as a freely accessible, online platform, which combines a database of complete genome-wide association study results with an interface for performing Mendelian randomization and sensitivity analyses. This allows the user to explore millions of potentially causal associations. MR-Base is available as a web application or as an R package. The technical aspects of the tool have previously been documented in the literature. The present article is complementary to this as it focuses on the applied aspects. Specifically, we describe how MR-Base can be used in several ways, including to perform novel causal analyses, replicate results and enable transparency, amongst others. We also present three use cases, which demonstrate important applications of Mendelian randomization and highlight the benefits of using MR-Base for these types of analyses.

scholarly journals Periodontal disease increases the host susceptibility to COVID-19 and its severity: a Mendelian randomization study

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yi Wang ◽  
Hui Deng ◽  
Yihuai Pan ◽  
Lijian Jin ◽  
Rongdang Hu ◽  
...  
Keyword(s):  
Periodontal Disease ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Host Susceptibility ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Inverse Variance ◽  
Weighted Median ◽  
First Time

Abstract Background Emerging evidence shows that periodontal disease (PD) may increase the risk of Coronavirus disease 2019 (COVID-19) complications. Here, we undertook a two-sample Mendelian randomization (MR) study, and investigated for the first time the possible causal impact of PD on host susceptibility to COVID-19 and its severity. Methods Summary statistics of COVID-19 susceptibility and severity were retrieved from the COVID-19 Host Genetics Initiative and used as outcomes. Single nucleotide polymorphisms associated with PD in Genome-wide association study were included as exposure. Inverse-variance weighted (IVW) method was employed as the main approach to analyze the causal relationships between PD and COVID-19. Three additional methods were adopted, allowing the existence of horizontal pleiotropy, including MR-Egger regression, weighted median and weighted mode methods. Comprehensive sensitivity analyses were also conducted for estimating the robustness of the identified associations. Results The MR estimates showed that PD was significantly associated with significantly higher susceptibility to COVID-19 using IVW (OR = 1.024, P = 0.017, 95% CI 1.004–1.045) and weighted median method (OR = 1.029, P = 0.024, 95% CI 1.003–1.055). Furthermore, it revealed that PD was significantly linked to COVID-19 severity based on the comparison of hospitalization versus population controls (IVW, OR = 1.025, P = 0.039, 95% CI 1.001–1.049; weighted median, OR = 1.030, P = 0.027, 95% CI 1.003–1.058). No such association was observed in the cohort of highly severe cases confirmed versus those not hospitalized due to COVID-19. Conclusions We provide evidence on the possible causality of PD accounting for the susceptibility and severity of COVID-19, highlighting the importance of oral/periodontal healthcare for general wellbeing during the pandemic and beyond.

scholarly journals Genomic and multi-tissue proteomic integration for understanding the biology of disease and other complex traits

2020 ◽  
Author(s):  
Chengran Yang ◽  
Fabiana G. Farias ◽  
Laura Ibanez ◽  
Brooke Sadler ◽  
Maria Victoria Fernandez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Drug Targets ◽  
Genetic Architecture ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Protein Levels ◽  
Genome Wide ◽  
Novel Biomarkers ◽  
Potential Drug Targets

AbstractExpression quantitative trait loci (eQTL) mapping has successfully resolved some genome-wide association study (GWAS) loci for complex traits1–6. However, there is a need for implementing additional “omic” approaches to untangle additional loci and provide a biological context for GWAS signals. We generated a detailed landscape of the genomic architecture of protein levels in multiple neurologically relevant tissues (brain, cerebrospinal fluid (CSF) and plasma), by profiling thousands of proteins in a large and well-characterized cohort. We identified 274, 127 and 32 protein quantitative loci (pQTL) for CSF, plasma and brain respectively. We demonstrated that cis-pQTL are more likely to be shared across tissues but trans-pQTL are tissue-specific. Between 78% to 87% of pQTL are not eQTL, indicating that protein levels have a different genetic architecture than gene expression. By combining our pQTL with Mendelian Randomization approaches we identified potential novel biomarkers and drug targets for neurodegenerative diseases including Alzheimer disease and frontotemporal dementia. In the context of personalized medicine, these results highlight the need for implementing additional functional genomic approaches beyond gene expression in order to understand the biology of complex traits, and to identify novel biomarkers and potential drug targets for those traits.

scholarly journals Genetic determinants of daytime napping and effects on cardiometabolic health

2020 ◽  
Author(s):  
Hassan S. Dashti ◽  
Iyas Daghlas ◽  
Jacqueline M. Lane ◽  
Yunru Huang ◽  
Miriam S. Udler ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Drug Targets ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Cardiometabolic Health ◽  
Genetic Determinants ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

AbstractDaytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remains unclear. Here, we performed a genome-wide association study of self-reported daytime napping in the UK Biobank (n=452,633) and identified 123 loci of which 60 replicated in 23andMe research participants (n=541,333). Findings included missense variants in established drug targets (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Signals were concordant with accelerometer-measured daytime inactivity duration and 33 signals colocalized with signals for other sleep phenotypes. Cluster analysis identified 3 clusters suggesting distinct nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization showed potential causal links between more frequent daytime napping and higher systolic blood pressure, diastolic blood pressure, and waist circumference.

scholarly journals Correlation AnalyzeR: functional predictions from gene co-expression correlations

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Henry E. Miller ◽  
Alexander J. R. Bishop
Keyword(s):  
Web Application ◽  
Bone Cancer ◽  
R Package ◽  
Limited Range ◽  
Web Interface ◽  
Generating Functional ◽  
Link Type ◽  
Genome Wide ◽  
User Friendly

Abstract Background Co-expression correlations provide the ability to predict gene functionality within specific biological contexts, such as different tissue and disease conditions. However, current gene co-expression databases generally do not consider biological context. In addition, these tools often implement a limited range of unsophisticated analysis approaches, diminishing their utility for exploring gene functionality and gene relationships. Furthermore, they typically do not provide the summary visualizations necessary to communicate these results, posing a significant barrier to their utilization by biologists without computational skills. Results We present Correlation AnalyzeR, a user-friendly web interface for exploring co-expression correlations and predicting gene functions, gene–gene relationships, and gene set topology. Correlation AnalyzeR provides flexible access to its database of tissue and disease-specific (cancer vs normal) genome-wide co-expression correlations, and it also implements a suite of sophisticated computational tools for generating functional predictions with user-friendly visualizations. In the usage example provided here, we explore the role of BRCA1-NRF2 interplay in the context of bone cancer, demonstrating how Correlation AnalyzeR can be effectively implemented to generate and support novel hypotheses. Conclusions Correlation AnalyzeR facilitates the exploration of poorly characterized genes and gene relationships to reveal novel biological insights. The database and all analysis methods can be accessed as a web application at https://gccri.bishop-lab.uthscsa.edu/correlation-analyzer/ and as a standalone R package at https://github.com/Bishop-Laboratory/correlationAnalyzeR.

scholarly journals Genetic architectures of proximal and distal colorectal cancer are partly distinct

Gut ◽  
2021 ◽  
pp. gutjnl-2020-321534
Author(s):  
Jeroen R Huyghe ◽  
Tabitha A Harrison ◽  
Stephanie A Bien ◽  
Heather Hampel ◽  
Jane C Figueiredo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Factors ◽  
Drug Targets ◽  
Genome Wide Association Study ◽  
Proximal Colon ◽  
European Ancestry ◽  
Molecular Characteristics ◽  
Genome Wide ◽  
Mechanisms Of Carcinogenesis ◽  
Meta Analyses

ObjectiveAn understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined.DesignTo identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling.ResultsWe identified 13 loci that reached genome-wide significance (p<5×10−8) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer.ConclusionGenetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.

Association of telomere length with risk of rheumatoid arthritis: a meta-analysis and Mendelian randomization

Rheumatology ◽  
2019 ◽  
Vol 59 (5) ◽  
pp. 940-947 ◽  
Author(s):  
Zhen Zeng ◽  
Wanting Zhang ◽  
Yu Qian ◽  
Huijun Huang ◽  
David J H Wu ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Sensitivity Analyses ◽  
Causal Association ◽  
Genome Wide ◽  
Inverse Variance ◽  
A Genome ◽  
Mean Differences

Abstract Objective To evaluate the telomere length (TL) in patients with RA relative to that in controls and to test whether TL is causally associated with risk of RA. Methods Systematic review and meta-analysis of relevant literature was conducted to evaluate the association between TL and RA. Standardized mean differences with 95% CIs of TL in RA patients relative to controls were pooled using fixed or random-effects models. TL-related single-nucleotide polymorphisms were selected from a genome-wide association study of 37 684 individuals, and summary statistics of RA were obtained from a genome-wide association study meta-analysis including 14 361 RA patients and 43 923 controls. Mendelian randomization was performed using the inverse-variance weighted, weighted-median and likelihood-based methods. Sensitivity analyses were performed to test the robustness of the association. Results In the meta-analysis of 911 RA patients and 2498 controls, we found that patients with RA had a significantly shorter TL compared with controls (standardized mean differences = −0.50; 95% CI −0.88, −0.11; P = 0.012). In the Mendelian randomization analysis, we found that genetically predicted longer TL was associated with a reduced risk of RA [odds ratio = 0.68; 95% CI 0.54, 0.86; P = 0.002 using the inverse-variance weighted method]. Sensitivity analyses using alternative Mendelian randomization approaches yielded similar findings, suggesting the robustness of the causal association. Conclusion Our study provides evidence for a negative causal association of TL with risk of RA. Further studies are warranted to elucidate the underlying mechanism for the role of telomeres in the development of RA.

scholarly journals Causal Associations between Serum Urea and Cancer: A Mendelian Randomization Study

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 498
Author(s):  
Yandi Sun ◽  
Jingjia Li ◽  
Zihao Qu ◽  
Ze Yang ◽  
Xueyao Jia ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Serum Urea ◽  
Urea Level ◽  
Genome Wide ◽  
Inverse Variance ◽  
Weighted Median ◽  
First Time

Urea is largely derived from the urea cycle reactions through hepatic detoxification of free ammonia and cleared by urination, and the serum urea level is a crucial medical indicator for measuring the kidney function in patients with nephropathy; however, investigative revelations pointing to the serum urea level as a risk factor for cancer are very scarce, and relevant studies are restricted by potential biases. We aimed to explore the causal relationships of the serum urea level with cancer development by focusing on renal cell carcinoma (RCC) using the Mendelian randomization (MR) analyses. Summary estimates were collected from the inverse-variance weighted (IVW) method based on six single nucleotide polymorphisms (SNPs). The selected SNPs related to the serum urea were obtained from a large genome-wide association study (GWAS) of 13,312 European participants. The summary statistics of RCC were also available from public databases (IARC, n = 5219 cases, n = 8011 controls). Sensitivity analyses included the weighted median and MR-Egger methods. Serum urea was inversely associated with RCC in females (effect = 1.93; 95% CI: 1.24 to 3.01; p = 0.004) but exhibited null association with RCC in males, breast cancer (BRCA) in both genders and prostate cancer (PCa) in males. Similar conclusions were also drawn from the weighted median and MR-Egger. These findings reveal an intriguing link between serum urea and cancer risks for the very first time. Without ambiguity, the serum urea is causatively related to RCC specifically in females, although the mechanism(s) by which urea is involved in RCC development remains to be experimentally/clinically investigated. Our studies may well provide novel insights for RCC diagnosis, intervention and/or therapy.

scholarly journals Appraising the Causal Association of Plasma Homocysteine Levels With Atrial Fibrillation Risk: A Two-Sample Mendelian Randomization Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Songzan Chen ◽  
Fangkun Yang ◽  
Tian Xu ◽  
Yao Wang ◽  
Kaijie Zhang ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Plasma Homocysteine ◽  
Fixed Effect ◽  
Sensitivity Analyses ◽  
Causal Association ◽  
Genome Wide ◽  
A Genome ◽  
Increased Risk

BackgroundAlthough several observational studies have suggested an association of elevated plasma homocysteine (Hcy) levels with increased risk of atrial fibrillation (AF), it remains unclear whether this association reflects causality. In this study, we aimed to investigate the causal association of plasma Hcy levels with AF risk.MethodsA two-sample Mendelian randomization (MR) study was designed to investigate the causal association of Hcy with AF. Summary data on association of single nucleotide polymorphisms (SNPs) with Hcy were extracted from the hitherto largest genome-wide association study (GWAS) with up to 44,147 individuals, and statistics data on association of SNPs with AF were obtained from another recently published GWAS with up to 1,030,836 individuals. SNPs were selected at a genome-wide significance threshold (p &lt; 5 × 10–8). Fixed-effect inverse variance weighting (IVW) method was used to calculate the causal estimate. Other statistical methods and leave-one-out analysis were applied in the follow-up sensitivity analyses. MR-Egger intercept test was conducted to detect the potential directional pleiotropy.ResultsIn total, nine SNPs were identified as valid instrumental variables in our two-sample MR analysis. Fixed-effect IVW analysis indicated no evidence of causal association of genetically predicted Hcy with AF. The odds ratio (OR) and 95% confidence interval (CI) of AF per standard deviation (SD) increase in Hcy were 1.077 (0.993, 1.168), p = 0.075. Similar results were observed in the sensitivity analyses. MR-Egger intercept test suggested no evidence of potential horizonal pleiotropy.ConclusionsThis two-sample MR analysis found no evidence to support causal association of Hcy with AF.

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