scholarly journals CONQUER: an interactive toolbox to understand functional consequences of GWAS hits

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Gerard A Bouland ◽  
Joline W J Beulens ◽  
Joey Nap ◽  
Arno R van der Slik ◽  
Arnaud Zaldumbide ◽  
...  
Keyword(s):  
Risk Factors ◽  
Association Studies ◽  
R Package ◽  
Integrative Approach ◽  
Individual Risk ◽  
Genome Wide Association Studies ◽  
Genome Database ◽  
Intergenic Regions ◽  
Functional Consequences ◽  
Individual Risk Factors

Abstract Numerous large genome-wide association studies have been performed to understand the influence of genetics on traits. Many identified risk loci are in non-coding and intergenic regions, which complicates understanding how genes and their downstream pathways are influenced. An integrative data approach is required to understand the mechanism and consequences of identified risk loci. Here, we developed the R-package CONQUER. Data for SNPs of interest are acquired from static- and dynamic repositories (build GRCh38/hg38), including GTExPortal, Epigenomics Project, 4D genome database and genome browsers. All visualizations are fully interactive so that the user can immediately access the underlying data. CONQUER is a user-friendly tool to perform an integrative approach on multiple SNPs where risk loci are not seen as individual risk factors but rather as a network of risk factors.

scholarly journals Understanding functional consequences of type 2 diabetes risk loci using the universal data integration and visualization R package CONQUER

2020 ◽  
Author(s):  
Gerard A Bouland ◽  
Joline WJ Beulens ◽  
Joey Nap ◽  
Arno R van der Slik ◽  
Arnaud Zaldumbide ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Ribosomal Proteins ◽  
Association Studies ◽  
R Package ◽  
Diabetes Risk ◽  
Genome Wide Association Studies ◽  
Genome Database ◽  
Intergenic Regions ◽  
Functional Consequences

ABSTRACTBackgroundNumerous large genome-wide association studies (GWASs) have been performed to understand the genetic factors of numerous traits, including type 2 diabetes. Many identified risk loci are located in non-coding and intergenic regions, which complicates the understanding how genes and their downstream pathways are influenced. An integrative data approach is required to understand the mechanism and consequences of identified risk loci.ResultsHere, we developed the R-package CONQUER. Data for SNPs of interest (build GRCh38/hg38) were acquired from static- and dynamic repositories, such as, GTExPortal, Epigenomics Project, 4D genome database and genome browsers such as ENSEMBL. CONQUER modularizes SNPs based on the underlying co-expression data and associates them with biological pathways in specific tissues. CONQUER was used to analyze 403 previously identified type 2 diabetes risk loci. In all tissues, the majority of SNPs (mean = 13.50, SD = 11.70) were linked to metabolism. A tissue-shared effect was found for four type 2 diabetes-associated SNPs (rs601945, rs1061810, rs13737, rs4932265) that were associated with differential expression of HLA-DQA2, HSD17B12, MAN2C1 and AP3S2 respectively. Seven SNPs were identified that influenced the expression of seven ribosomal proteins in multiple tissues. Finally, one SNP (rs601945) was found to influence multiple HLA genes in all twelve tissues investigated.ConclusionWe present an universal R-package that aggregates and visualizes data in order to better understand functional consequences of GWAS loci. Using CONQUER, we showed that type 2 diabetes risk loci have many tissue-shared effects on multiple pathways including metabolism, the ribosome and HLA pathway.

scholarly journals GARFIELD - GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction

2016 ◽  
Author(s):  
Valentina Iotchkova ◽  
Graham R.S. Ritchie ◽  
Matthias Geihs ◽  
Sandro Morganella ◽  
Josine L. Min ◽  
...  
Keyword(s):  
Association Studies ◽  
R Package ◽  
Genome Wide Association Studies ◽  
Protein Coding ◽  
Functional Annotations ◽  
Novel Approach ◽  
Genome Wide ◽  
Functional Consequences ◽  
Genomic Regions ◽  
Coding Variants

Loci discovered by genome-wide association studies (GWAS) predominantly map outside protein-coding genes. The interpretation of functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages GWAS findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding that current methods do not offer. We further assess enrichment statistics for 27 GWAS traits within regulatory regions from the ENCODE and Roadmap projects. We characterise unique enrichment patterns for traits and annotations, driving novel biological insights. The method is implemented in standalone software and R package to facilitate its application by the research community.

scholarly journals An integrative approach to detect epigenetic mechanisms that putatively mediate the influence of lifestyle exposures on disease susceptibility

2019 ◽  
Vol 48 (3) ◽  
pp. 887-898 ◽  
Author(s):  
Tom G Richardson ◽  
Rebecca C Richmond ◽  
Teri-Louise North ◽  
Gibran Hemani ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Gene Expression ◽  
Risk Factors ◽  
Dna Methylation ◽  
Complex Traits ◽  
Disease Susceptibility ◽  
Association Studies ◽  
Integrative Approach ◽  
Prenatal Smoking ◽  
Genome Wide Association Studies ◽  
Cpg Sites

Abstract Background There is mounting evidence that our environment and lifestyle has an impact on epigenetic regulatory mechanisms, such as DNA methylation. It has been suggested that these molecular processes may mediate the effect of risk factors on disease susceptibility, although evidence in this regard has been challenging to uncover. Using genetic variants as surrogate variables, we have used two-sample Mendelian randomization (2SMR) to investigate the potential implications of putative changes to DNA methylation levels on disease susceptibility. Methods To illustrate our approach, we identified 412 CpG sites where DNA methylation was associated with prenatal smoking. We then applied 2SMR to investigate potential downstream effects of these putative changes on 643 complex traits using findings from large-scale genome-wide association studies. To strengthen evidence of mediatory mechanisms, we used multiple-trait colocalization to assess whether DNA methylation, nearby gene expression and complex trait variation were all influenced by the same causal genetic variant. Results We identified 22 associations that survived multiple testing (P < 1.89 × 10–7). In-depth follow-up analyses of particular note suggested that the associations between DNA methylation at the ASPSCR1 and REST/POL2RB gene regions, both linked with reduced lung function, may be mediated by changes in gene expression. We validated associations between DNA methylation and traits using independent samples from different stages across the life course. Conclusion Our approach should prove valuable in prioritizing CpG sites that may mediate the effect of causal risk factors on disease. In-depth evaluations of findings are necessary to robustly disentangle causality from alternative explanations such as horizontal pleiotropy.

scholarly journals UKB.COVID19: an R package for UK Biobank COVID-19 data processing and analysis

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 830
Author(s):  
Longfei Wang ◽  
Victoria E Jackson ◽  
Liam G Fearnley ◽  
Melanie Bahlo
Keyword(s):  
Risk Factors ◽  
Genomic Sequence ◽  
Association Studies ◽  
R Package ◽  
Aged Care ◽  
Blood Type ◽  
Hospital Inpatient ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Potential Risk Factors

COVID-19 caused by SARS-CoV-2 has resulted in a global pandemic with a rapidly developing global health and economic crisis. Variations in the disease have been observed and have been associated with the genomic sequence of either the human host or the pathogen. Worldwide scientists scrambled initially to recruit patient cohorts to try and identify risk factors. A resource that presented itself early on was the UK Biobank (UKBB), which is investigating the respective contributions of genetic predisposition and environmental exposure to the development of disease. To enable COVID-19 studies, UKBB is now receiving COVID-19 test data for their participants every two weeks. In addition, UKBB is delivering more frequent updates of death and hospital inpatient data (including critical care admissions) on the UKBB Data Portal. This frequently changing dataset requires a tool that can rapidly process and analyse up-to-date data. We developed an R package specifically for the UKBB COVID-19 data, which summarises COVID-19 test results, performs association tests between COVID-19 susceptibility/severity and potential risk factors such as age, sex, blood type, comorbidities and generates input files for genome-wide association studies (GWAS). By applying the R package to data released in April 2021, we found that age, body mass index, socioeconomic status and smoking are positively associated with COVID-19 susceptibility, severity, and mortality. Males are at a higher risk of COVID-19 infection than females. People staying in aged care homes have a higher chance of being exposed to SARS-CoV-2. By performing GWAS, we replicated the 3p21.31 genetic finding for COVID-19 susceptibility and severity. The ability to iteratively perform such analyses is highly relevant since the UKBB data is updated frequently. As a caveat, users must arrange their own access to the UKBB data to use the R package.

Estimating average attributable fractions with confidence intervals for cohort and case–control studies

2016 ◽  
Vol 27 (4) ◽  
pp. 1141-1152 ◽  
Author(s):  
John Ferguson ◽  
Alberto Alvarez-Iglesias ◽  
John Newell ◽  
John Hinde ◽  
Martin O’Donnell
Keyword(s):  
Risk Factors ◽  
Confidence Intervals ◽  
R Package ◽  
Case Control ◽  
Estimation Methods ◽  
Individual Risk ◽  
Case Control Studies ◽  
Sample Average ◽  
Attributable Fractions ◽  
Individual Risk Factors

Chronic diseases tend to depend on a large number of risk factors, both environmental and genetic. Average attributable fractions were introduced by Eide and Gefeller as a way of partitioning overall disease burden into contributions from individual risk factors; this may be useful in deciding which risk factors to target in disease interventions. Here, we introduce new estimation methods for average attributable fractions that are appropriate for both case–control designs and prospective studies. Confidence intervals, derived using Monte Carlo simulation, are also described. Finally, we introduce a novel approximation for the sample average attributable fraction that will ensure a computationally tractable approach when the number of risk factors is large. An R package, [Formula: see text], implementing the methods described in this manuscript can be downloaded from the CRAN repository.

A Model for Analyzing Suicide Prevention

Crisis ◽  
2000 ◽  
Vol 21 (2) ◽  
pp. 80-89 ◽  
Author(s):  
Maila Upanne
Keyword(s):  
Risk Factors ◽  
Theoretical Model ◽  
Protective Factors ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Practical Work ◽  
Individual Risk ◽  
Self Assessment ◽  
Prevention Project ◽  
Individual Risk Factors

This study monitored the evolution of psychologists' (n = 31) conceptions of suicide prevention over the 9-year course of the National Suicide Prevention Project in Finland and assessed the feasibility of the theoretical model for analyzing suicide prevention developed in earlier studies [ Upanne, 1999a , b ]. The study was formulated as a retrospective self-assessment where participants compared their earlier descriptions of suicide prevention with their current views. The changes in conceptions were analyzed and interpreted using both the model and the explanations given by the subjects themselves. The analysis proved the model to be a useful framework for revealing the essential features of prevention. The results showed that the freely-formulated ideas on prevention were more comprehensive than those evolved in practical work. Compared to the earlier findings, the conceptions among the group had shifted toward emphasizing a curative approach and the significance of individual risk factors. In particular, greater priority was focused on the acute suicide risk phase as a preventive target. Nonetheless, the overall structure of prevention ideology remained comprehensive and multifactorial, stressing multistage influencing. Promotive aims (protective factors) also remained part of the prevention paradigm. Practical working experiences enhanced the psychologists' sense of the difficulties of suicide prevention as well as their criticism and feeling of powerlessness.

scholarly journals Multitrait genetic association analysis identifies 50 new risk loci for gastro-oesophageal reflux, seven new loci for Barrett’s oesophagus and provides insights into clinical heterogeneity in reflux diagnosis

Gut ◽  
2021 ◽  
pp. gutjnl-2020-323906
Author(s):  
Jue-Sheng Ong ◽  
Jiyuan An ◽  
Xikun Han ◽  
Matthew H Law ◽  
Priyanka Nandakumar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Testing ◽  
Association Studies ◽  
Barrett’S Oesophagus ◽  
Oesophageal Reflux ◽  
Oesophageal Adenocarcinoma ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Disease Heterogeneity ◽  
Barrett's Oesophagus

ObjectiveGastro-oesophageal reflux disease (GERD) has heterogeneous aetiology primarily attributable to its symptom-based definitions. GERD genome-wide association studies (GWASs) have shown strong genetic overlaps with established risk factors such as obesity and depression. We hypothesised that the shared genetic architecture between GERD and these risk factors can be leveraged to (1) identify new GERD and Barrett’s oesophagus (BE) risk loci and (2) explore potentially heterogeneous pathways leading to GERD and oesophageal complications.DesignWe applied multitrait GWAS models combining GERD (78 707 cases; 288 734 controls) and genetically correlated traits including education attainment, depression and body mass index. We also used multitrait analysis to identify BE risk loci. Top hits were replicated in 23andMe (462 753 GERD cases, 24 099 BE cases, 1 484 025 controls). We additionally dissected the GERD loci into obesity-driven and depression-driven subgroups. These subgroups were investigated to determine how they relate to tissue-specific gene expression and to risk of serious oesophageal disease (BE and/or oesophageal adenocarcinoma, EA).ResultsWe identified 88 loci associated with GERD, with 59 replicating in 23andMe after multiple testing corrections. Our BE analysis identified seven novel loci. Additionally we showed that only the obesity-driven GERD loci (but not the depression-driven loci) were associated with genes enriched in oesophageal tissues and successfully predicted BE/EA.ConclusionOur multitrait model identified many novel risk loci for GERD and BE. We present strong evidence for a genetic underpinning of disease heterogeneity in GERD and show that GERD loci associated with depressive symptoms are not strong predictors of BE/EA relative to obesity-driven GERD loci.

scholarly journals Cardio-Metabolic Risk Factors in Scottish South Asian and Caucasian Youth

2021 ◽  
Vol 18 (9) ◽  
pp. 4667
Author(s):  
Meizi Wang ◽  
Jianhua Ying ◽  
Ukadike Chris Ugbolue ◽  
Duncan S. Buchan ◽  
Yaodong Gu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Waist Circumference ◽  
Body Mass ◽  
South Asian ◽  
Metabolic Risk Factors ◽  
Individual Risk ◽  
Metabolic Risk ◽  
Asian Adolescents ◽  
Individual Risk Factors

(1) Background: Scotland has one of the highest rates of obesity in the Western World, it is well established that poor weight profiles, and particularly abdominal obesity, is strongly associated with Type II diabetes and cardiovascular diseases. Whether these associations are apparent in ethnic population groups in Scotland is unclear. The purpose of this study was to examine the associations between different measures of fatness with clustered cardio metabolic risk factors between Scottish South Asian adolescents and Scottish Caucasian adolescents; (2) Methods: A sample of 208 Caucasian adolescents and 52 South Asian adolescents participated in this study. Stature, waist circumference, body mass index, blood pressure, physical activity, and cardiovascular disease (CVD) risk were measured; (3) Results: Significant, partial correlations in the South Asian cohort between body mass index (BMI) and individual risk factors were generally moderate. However, correlations between Waist circumference (WC) and individual risk factors were significant and strong. In the Caucasian cohort, a significant yet weak correlation between WC and total cholesterol (TG) was noted although no other associations were evident for either WC or BMI. Multiple regression analysis revealed that both BMI and WC were positively associated with CCR (p < 0.01) in the South Asian group and with the additional adjustment of either WC or BMI, the independent associations with clustered cardio-metabolic risk (CCR) remained significant (p < 0.005); (4) Conclusions: No positive relationships were found between BMI, WC, and CCR in the Caucasian group. Strong and significant associations between measures of fatness and metabolic risk were evident in Scottish South Asian adolescents.

How Community and Individual Risk Factors Mutually Impact Youth’s Perceived Safety: A Syndemic Analysis Using Structural Equation Modeling

2021 ◽  
pp. 088626052110283
Author(s):  
Yingwei Yang ◽  
Karen D. Liller ◽  
Martha Coulter ◽  
Abraham Salinas-Miranda ◽  
Dinorah Martinez Tyson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Community Safety ◽  
Equation Modeling ◽  
Individual Risk ◽  
Latent Factor ◽  
Community Factors ◽  
Individual Risk Factors ◽  
Syndemic Theory

The purpose of this study was to evaluate the mutual impact of community and individual factors on youth’s perceptions of community safety, using structural equation modeling (SEM) conceptualized by syndemic theory. This study used survey data collected from a county wide sample of middle and high school students (N=25,147) in West Central Florida in 2015. The outcome variable was youth’s perceptions of community safety. Predictors were latent individual and community factors constructed from 14 observed variables including gun accessibility, substance use, depressive symptoms, and multiple neighborhood disadvantage questions. Three structural equation models were conceptualized based on syndemic theory and analyzed in Mplus 8 using weighted least squares (WLS) estimation. Each model’s goodness of fit was assessed. Approximately seven percent of youth reported feeling unsafe in their community. After model modifications, the final model showed a good fit of the data and adhered to the theoretical assumption. In the final SEM model, an individual latent factor was implied by individual predictors measuring gun accessibility without adult’s permission (β=0.70), sadness and hopelessness (β=0.52), alcohol use (β=0.79), marijuana use (β=0.94), and illegal drug use (β=0.77). Meanwhile, a community latent factor was indicated by multiple community problems including public drinking (β=0.88), drug addiction (β=0.96), drug selling (β=0.97), lack of money (β=0.83), gang activities (β=0.90), litter and trash (β=0.79), graffiti (β=0.91), deserted houses (β=0.86), and shootings (β=0.93). A second-order syndemic factor that represented the individual and community factors showed a very strong negative association with youth’s safe perception (β=-0.98). This study indicates that individual risk factors and disadvantaged community conditions interacted with each other and mutually affected youth’s perceptions of community safety. To reduce these co-occurring effects and improve safe perceptions among youth, researchers and practitioners should develop and implement comprehensive strategies targeting both individual and community factors.

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