Dataset Information

Genotype-Based Recall Studies in Complex Cardiometabolic Traits.

ABSTRACT: In genotype-based recall (GBR) studies, people (or their biological samples) who carry genotypes of special interest for a given hypothesis test are recalled from a larger cohort (or biobank) for more detailed investigations. There are several GBR study designs that offer a range of powerful options to elucidate (1) genotype-phenotype associations (by increasing the efficiency of genetic association studies, thereby allowing bespoke phenotyping in relatively small cohorts), (2) the effects of environmental exposures (within the Mendelian randomization framework), and (3) gene-treatment interactions (within the setting of GBR interventional trials). In this review, we overview the literature on GBR studies as applied to cardiometabolic health outcomes. We also review the GBR approaches used to date and outline new methods and study designs that might enhance the utility of GBR-focused studies. Specifically, we highlight how GBR methods have the potential to augment randomized controlled trials, providing an alternative application for the now increasingly accepted Mendelian randomization methods usually applied to large-scale population-based data sets. Further to this, we consider how functional and basic science approaches alongside GBR designs offer intellectually intriguing and potentially powerful ways to explore the implications of alterations to specific (and potentially druggable) biological pathways.

SUBMITTER: Franks PW

PROVIDER: S-EPMC6813040 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Genotype-Based Recall Studies in Complex Cardiometabolic Traits.

Franks Paul W PW Timpson Nicholas J NJ

Circulation. Genomic and precision medicine 20180801 8

In genotype-based recall (GBR) studies, people (or their biological samples) who carry genotypes of special interest for a given hypothesis test are recalled from a larger cohort (or biobank) for more detailed investigations. There are several GBR study designs that offer a range of powerful options to elucidate (1) genotype-phenotype associations (by increasing the efficiency of genetic association studies, thereby allowing bespoke phenotyping in relatively small cohorts), (2) the effects of en ...[more]

PMID: 30354344

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Project description:ObjectiveTranscriptome profiling of human tissues has revealed thousands of long intergenic noncoding RNAs (lincRNAs) at loci identified through large-scale genome-wide studies for complex cardiometabolic traits. This raises the question of whether genetic variation at nonconserved lincRNAs has any systematic association with complex disease, and if so, how different this pattern is from conserved lincRNAs. We evaluated whether the associations between nonconserved lincRNAs and 8 complex cardiometabolic traits resemble or differ from the pattern of association for conserved lincRNAs. Approach and Results: Our investigation of over 7000 lincRNA annotations from GENCODE Release 33-GRCh38.p13 for complex trait genetic associations leveraged several large, established meta-analyses genome-wide association study summary data resources, including GIANT (Genetic Investigation of Anthropometric Traits), UK Biobank, GLGC (Global Lipids Genetics Consortium), Cardiogram (Coronary Artery Disease Genome Wide Replication and Meta-Analysis), and DIAGRAM (Diabetes Genetics Replication and Meta-Analysis)/DIAMANTE (Diabetes Meta-Analysis of Trans-Ethnic Association Studies). These analyses revealed that (1) nonconserved lincRNAs associate with a range of cardiometabolic traits at a rate that is generally consistent with conserved lincRNAs; (2) these findings persist across different definitions of conservation; and (3) overall across all cardiometabolic traits, approximately one-third of genome-wide association study-associated lincRNAs are nonconserved, and this increases to about two-thirds using a more stringent definition of conservation.ConclusionsThese findings suggest that the traditional notion of conservation driving prioritization for functional and translational follow-up of complex cardiometabolic genomic discoveries may need to be revised in the context of the abundance of nonconserved long noncoding RNAs in the human genome and their apparent predilection to associate with complex cardiometabolic traits.

Dataset Information

Genotype-Based Recall Studies in Complex Cardiometabolic Traits.

Publications

Genotype-Based Recall Studies in Complex Cardiometabolic Traits.

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