Discovery and Refinement of Genetic loci Associated with Cardiometabolic Risk Using Dense Imputation Maps


In a large-scale study recently published in Nature Genetics, scientists from the Wellcome Trust Sanger Institute and their collaborators analyzed the genomes of approximately 36,000 healthy individuals, looking for rare genetic risk variants associated with various cardiometabolic and hematological traits. Whole genome sequence data was used to create a dense imputation panel to fill in gaps - or ‘impute’ missing data -  from lower resolution genetic results available from these individuals.

Using this approach, scientists identified 17 new genetic risk variants associated with traits such as platelet count, red blood cell indices and cholesterol level. Of these variants, 16 would have been difficult to detect without the imputation panel data generated from 1000 Genomes samples. By applying fine-mapping analysis to 233 known and new loci associated with these traits, researchers were able to resolve the associations of 59 additional loci to credible sets of 20 or fewer variants and describe trait enrichments within gene regulatory regions.

The full study can be found in the article, “Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps” by Iotchkova et al. published in Nature Genetics. A summary of this study is available on the Science Daily website.

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