Dataset Information

Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

ABSTRACT: Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.

SUBMITTER: Corbin LJ

PROVIDER: S-EPMC5818506 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

Corbin Laura J LJ Tan Vanessa Y VY Hughes David A DA Wade Kaitlin H KH Paul Dirk S DS Tansey Katherine E KE Butcher Frances F Dudbridge Frank F Howson Joanna M JM Jallow Momodou W MW John Catherine C Kingston Nathalie N Lindgren Cecilia M CM O'Donavan Michael M O'Rahilly Stephen S Owen Michael J MJ Palmer Colin N A CNA Pearson Ewan R ER Scott Robert A RA van Heel David A DA Whittaker John J Frayling Tim T Tobin Martin D MD Wain Louise V LV Smith George Davey GD Evans David M DM Karpe Fredrik F McCarthy Mark I MI Danesh John J Franks Paul W PW Timpson Nicholas J NJ

Nature communications 20180219 1

Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. W ...[more]

PMID: 29459775

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Project description:ImportanceChildhood asthma is characterized by disparities in the experience of morbidity, including the risk for readmission to the hospital after an initial hospitalization. African American children have been shown to have more than 2 times the hazard of readmission when compared with their white counterparts.ObjectiveTo explain why African American children are at greater risk for asthma-related readmissions than white children.Design, setting, and participantsThis study was completed as part of the Greater Cincinnati Asthma Risks Study, a population-based, prospective, observational cohort. From August 2010 to October 2011, it enrolled 695 children, aged 1 to 16 years, admitted for asthma or wheezing who identified as African American (n = 441) or white (n = 254) in an inpatient setting of an urban, tertiary care children's hospital.Main outcomes and measuresThe main outcome was time to asthma-related readmission and race was the predictor. Biologic, environmental, disease management, access, and socioeconomic hardship variables were measured; their roles in understanding racial readmission disparities were conceptualized using a directed acyclic graphic. Inverse probability of treatment weighting balanced African American and white children with respect to key measured variables. Racial differences in readmission hazard were assessed using weighted Cox proportional hazards regression and Kaplan-Meier curves.ResultsThe sample was 65% male (n = 450), and the median age was 5.4 years. African American children were 2.26 times more likely to be readmitted than white children (95% CI, 1.56-3.26). African American children significantly differed with respect to nearly every measured biologic, environmental, disease management, access, and socioeconomic hardship variable. Socioeconomic hardship variables explained 53% of the observed disparity (hazard ratio, 1.47; 95% CI, 1.05-2.05). The addition of biologic, environmental, disease management, and access variables resulted in 80% of the readmission disparity being explained. The difference between African American and white children with respect to readmission hazard no longer reached the level of significance (hazard ratio, 1.18; 95% CI, 0.87-1.60; Cox P = .30 and log-rank P = .39).Conclusions and relevanceA total of 80% of the observed readmission disparity between African American and white children could be explained after statistically balancing available biologic, environmental, disease management, access to care, and socioeconomic and hardship variables across racial groups. Such a comprehensive, well-framed approach to exposures that are associated with morbidity is critical as we attempt to better understand and lessen persistent child asthma disparities.

Dataset Information

Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

Publications

Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

Similar Datasets

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