scholarly journals Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank

2017 ◽  
Vol 49 (9) ◽  
pp. 1311-1318 ◽  
Author(s):  
Adrian Cortes ◽  
Calliope A Dendrou ◽  
Allan Motyer ◽  
Luke Jostins ◽  
Damjan Vukcevic ◽  
...  
Keyword(s):  
Bayesian Analysis ◽  
Genetic Association ◽  
Uk Biobank ◽  
Healthcare Data ◽  
The Uk

scholarly journals Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank

2017 ◽  
Author(s):  
Adrian Cortes ◽  
Calliope A. Dendrou ◽  
Allan Motyer ◽  
Luke Jostins ◽  
Damjan Vukcevic ◽  
...  
Keyword(s):  
Bayesian Analysis ◽  
Statistical Power ◽  
Heterogeneous Data ◽  
Uk Biobank ◽  
Genetic Associations ◽  
Critical Question ◽  
Healthcare Data ◽  
Immune Mediated ◽  
The Hierarchical Structure ◽  
The Uk

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data has the ability to radically transform our understanding of the human phenome, thereby accelerating progress towards precision medicine. However, a critical question when analysing high-dimensional and heterogeneous data is how to interrogate increasingly specific subphenotypes whilst retaining statistical power to detect genetic associations. Here we develop and employ a novel Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to jointly analyse genetic variants against UK Biobank healthcare phenotypes. Our method displays a more than 20% increase in power to detect genetic effects over other approaches, such that we uncover the broader burden of genetic variation: we identify associations with over 2,000 diagnostic terms. We find novel associations with common immune-mediated diseases (IMD), we reveal the extent of genetic sharing between specific IMDs, and we expose differences in disease perception or diagnosis with potential clinical implications.

scholarly journals A robust example of collider bias in a genetic association study

2015 ◽  
Author(s):  
Felix Day ◽  
Robert Scott ◽  
Ken Ong ◽  
John Perry
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Positive Association ◽  
Uk Biobank ◽  
False Positive Association ◽  
Genome Wide ◽  
The Uk ◽  
Study Inclusion ◽  
Collider Bias

Recent studies have described the potential for ″collider bias″ to modify the magnitude of genotype-phenotype associations, however the extent to which this effect can induce a completely false-positive association remains unclear. In a sample of 142,630 individuals from the UK Biobank study, inclusion of height (a ″collider″) as a covariate induces biologically spurious, but genome-wide significant, associations between autosomal genetic variants and sex. These associations are non-significant in models unadjusted for height. Our study underpins the importance of causal inference modeling in the design and interpretation of genetic (and non-genetic) association studies.

Low birthweight is associated with poorer limb muscle mass and grip strength in middle age: findings from the UK Biobank Imaging Enhancement

2019 ◽  
Author(s):  
Elizabeth Curtis ◽  
Justin Liu ◽  
Kate Ward ◽  
Karen Jameson ◽  
Zahra Raisi-Estabragh ◽  
...  
Keyword(s):  
Grip Strength ◽  
Muscle Mass ◽  
Low Birthweight ◽  
Middle Age ◽  
Limb Muscle ◽  
Uk Biobank ◽  
The Uk

Contrasting Broad- and Clinically- defined Polygenic Indicators of Depression and Depression-related Phenotypes in Adults and Children

2020 ◽  
Author(s):  
John E. McGeary ◽  
Chelsie Benca-Bachman ◽  
Victoria Risner ◽  
Christopher G Beevers ◽  
Brandon Gibb ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Cognitive Reappraisal ◽  
Twin Studies ◽  
European Ancestry ◽  
Summary Statistics ◽  
Depression Severity ◽  
Uk Biobank ◽  
Polygenic Scores ◽  
Adults And Children ◽  
The Uk

Twin studies indicate that 30-40% of the disease liability for depression can be attributed to genetic differences. Here, we assess the explanatory ability of polygenic scores (PGS) based on broad- (PGSBD) and clinical- (PGSMDD) depression summary statistics from the UK Biobank using independent cohorts of adults (N=210; 100% European Ancestry) and children (N=728; 70% European Ancestry) who have been extensively phenotyped for depression and related neurocognitive phenotypes. PGS associations with depression severity and diagnosis were generally modest, and larger in adults than children. Polygenic prediction of depression-related phenotypes was mixed and varied by PGS. Higher PGSBD, in adults, was associated with a higher likelihood of having suicidal ideation, increased brooding and anhedonia, and lower levels of cognitive reappraisal; PGSMDD was positively associated with brooding and negatively related to cognitive reappraisal. Overall, PGS based on both broad and clinical depression phenotypes have modest utility in adult and child samples of depression.

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