Work

Utility of family history in disease prediction in the era of polygenic scores

Year: 2021

Type: preprint

Abstract: Clinicians have historically used family history and other risk prediction algorithms to guide patient care and preventive treatment such as statin therapeutics for coronary artery disease. As polygenic scores move towards clinical use, we have begun to consider the interplay of these scores with other predictors for optimal second generation risk prediction. Here, we assess the use of family history and polygenic scores as independent predictors of coronary artery disease and type 2 diabetes. We highlight considerations for use of family history as a predictor of these two diseases after evaluating their effectiveness in the Trøndelag Health Study and the UK Biobank. From these, we advocate for collection of high resolution family history variables in biobanks for future prediction models.

Source: medRxiv

DOI: 10.1101/2021.06.25.21259158

Authors: Brooke N. Wolford, Ida Surakka, Sarah E. Graham, Jonas B. Nielsen, Wei Zhou, Maiken Elvestad Gabrielsen, Anne Heidi Skogholt, Ben M. Brumpton, Nicholas Douville, Whitney E. Hornsby, Lars G. Fritsche, Michael Boehnke, Seunggeun Lee, Hyun M. Kang, Kristian Hveem, Cristen J. Willer

Institutions: University of Michigan, Michigan Medicine, Norwegian University of Science and Technology, Broad Institute, Massachusetts General Hospital, Stanley Center for Psychiatric Research, St Olav's University Hospital, Seoul National University

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Science Foundation, Foundation for Anesthesia Education and Research, University of Michigan, Stiftelsen Kristian Gerhard Jebsen, Norges Teknisk-Naturvitenskapelige Universitet, School of Public Health, University of Michigan, Helse Midt-Norge, National Institutes of Health, Medical School, University of Michigan, Fakultet for medisin og helsevitenskap, Norges Teknisk-Naturvitenskapelige Universitet, Faculty of Medicine and Health, University of Sydney, Norwegian Institute of Public Health, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of Diabetes and Digestive and Kidney Diseases

Awards: Using genetic variation to study biology of blood lipids & coronary heart disease, G2101069996, G2357065241, Identifying Genes for Type 2 Diabetes: FUSION, Using Genetics to Inform Mechanism of Cardiovascular Disease, Graduate Research Fellowship Program (GRFP), Design and Analysis of Human Gene Mapping Studies, G8883008220, G9000189254, G9000277595, University of Michigan Training Program in Genomic Science

OpenAlex ID: W3176125325

Cites: 45

Cited by: 1

Related to: 10