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Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study.

PLoS Medicine. 2020;17(7):e1003152 DOI 10.1371/journal.pmed.1003152

 

Journal Homepage

Journal Title: PLoS Medicine

ISSN: 1549-1277 (Print); 1549-1676 (Online)

Publisher: Public Library of Science (PLoS)

LCC Subject Category: Medicine

Country of publisher: United States

Language of fulltext: English

Full-text formats available: PDF, HTML, XML

 

AUTHORS


Vincenzo Forgetta

Julyan Keller-Baruch

Marie Forest

Audrey Durand

Sahir Bhatnagar

John P Kemp

Maria Nethander

Daniel Evans

John A Morris

Douglas P Kiel

Fernando Rivadeneira

Helena Johansson

Nicholas C Harvey

Dan Mellström

Magnus Karlsson

Cyrus Cooper

David M Evans

Robert Clarke

John A Kanis

Eric Orwoll

Eugene V McCloskey

Claes Ohlsson

Joelle Pineau

William D Leslie

Celia M T Greenwood

J Brent Richards

EDITORIAL INFORMATION

Peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 32 weeks

 

Abstract | Full Text

BACKGROUND:Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)-a heritable risk factor for osteoporotic fracture-can identify low-risk individuals who can safely be excluded from a fracture risk screening program. METHODS AND FINDINGS:A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed "gSOS", and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)-based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. CONCLUSIONS:Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention.