Autoři: Vincenzo Forgetta aff001; Julyan Keller-Baruch aff002; Marie Forest aff001; Audrey Durand aff003; Sahir Bhatnagar aff001; John P. Kemp aff004; Maria Nethander aff006; Daniel Evans aff008; John A. Morris aff001; Douglas P. Kiel aff009; Fernando Rivadeneira aff010; Helena Johansson aff011; Nicholas C. Harvey aff013; Dan Mellström aff007; Magnus Karlsson aff015; Cyrus Cooper aff013; David M. Evans aff004; Robert Clarke aff017; John A. Kanis aff011; Eric Orwoll aff018; Eugene V. McCloskey aff020; Claes Ohlsson aff007; Joelle Pineau aff003; William D. Leslie aff021; Celia M. T. Greenwood aff001; J. Brent Richards aff001 Působiště autorů: Centre for Clinical Epidemiology, Department of Medicine, Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec, Canada aff001; Department of Human Genetics, McGill University, Montreal, Quebec, Canada aff002; School of Computer Science, McGill University, Montréal, Québec, Canada aff003; University of Queensland Diamantina Institute, University of Queensland, Woolloongabba, Queensland, Australia aff004; Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom aff005; Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden aff006; Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute for Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden aff007; California Pacific Medical Center Research Institute, San Francisco, California, United States of America aff008; Institute for Aging Research, Hebrew SeniorLife, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Broad Institute of MIT & Harvard University, Boston, Massachusetts, United States of America aff009; Department of Internal Medicine, Erasmus Medical Center, Rotterdam, Netherlands aff010; Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, United Kingdom aff011; Australian Catholic University, Melbourne, Victoria, Australia aff012; Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom aff013; National Institute for Health Research Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom aff014; Department of Orthopaedics and Clinical Sciences, Lund University, Skane University Hospital, Malmö, Sweden aff015; National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom aff016; Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, United Kingdom aff017; Bone and Mineral Unit, Oregon Health & Science University, Portland, Oregon, United States of America aff018; Department of Medicine, Oregon Health & Science University, Portland, Oregon, United States of America aff019; Mellanby Centre for Bone Research, Centre for Integrated Research in Musculoskeletal Ageing, University of Sheffield and Sheffield Teaching Hospitals Foundation Trust, Sheffield, United Kingdom aff020; Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada aff021; Gerald Bronfman Department of Oncology, McGill University, Montréal, Québec, Canada aff022; Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montréal, Québec, Canada aff023; Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom aff024 Vyšlo v časopise: Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study. PLoS Med 17(7): e32767. doi:10.1371/journal.pmed.1003152 Kategorie: Research Article doi: https://doi.org/10.1371/journal.pmed.1003152
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.
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.
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.
Bone fracture – Genetic screens – Genome-wide association studies – Genotyping – Medical risk factors – Osteoporosis – Screening guidelines – Traumatic injury risk factors
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