ReviewCirculation. Genomic and precision medicine2018
Genotype-Based Recall Studies in Complex Cardiometabolic Traits.
Review in Circulation. Genomic and precision medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Five tenets for advancing evidence-based precision medicine.Nature medicine · 2026Review
- Genetic and epidemiologic assessment of mandibular cortical indices and bone mineral density in peripubertal children: the Generation R study.Clinical oral investigations · 2025Article
- Precision nutrition for cardiometabolic diseases.Nature medicine · 2025Review
- How to communicate and what to disclose to participants in a recall-by-genotype research approach: a multistep empirical study.Journal of community genetics · 2024Article
- Systematic review and meta-analysis of the genetics of peripheral arterial disease.JVS-vascular science · 2024Review
- Socioeconomic Disparities Across the Spectrum of Genetic Burden in Type 2 Diabetes and Obesity Risk.Diabetes care · 2023Article
- PNPLA3 rs738409 risk genotype decouples TyG index from HOMA2-IR and intrahepatic lipid content.Cardiovascular diabetology · 2023Article
- Ethical, legal and social/societal implications (ELSI) of recall-by-genotype (RbG) and genotype-driven-research (GDR) approaches: a scoping review.European journal of human genetics : EJHG · 2022Article
- Next-generation epidemiology: the role of high-resolution molecular phenotyping in diabetes research.Diabetologia · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.