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Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
by
Forest, Marie
, Kemp, John P.
, Karlsson, Magnus
, McCloskey, Eugene V.
, Leslie, William D.
, Kiel, Douglas P.
, Kanis, John A.
, Harvey, Nicholas C.
, Cooper, Cyrus
, Greenwood, Celia M. T.
, Evans, David M.
, Rivadeneira, Fernando
, Evans, Daniel
, Mellström, Dan
, Orwoll, Eric
, Richards, J. Brent
, Keller-Baruch, Julyan
, Forgetta, Vincenzo
, Bhatnagar, Sahir
, Clarke, Robert
, Ohlsson, Claes
, Nethander, Maria
, Morris, John A.
, Pineau, Joelle
, Johansson, Helena
, Durand, Audrey
in
Aged
/ Arthritis
/ association
/ Basic Medicine
/ Biology and Life Sciences
/ Biomedical research
/ Bone Density
/ Bone diseases
/ Bone mineral density
/ Calcaneus - diagnostic imaging
/ Clinical Medicine
/ Cohort Studies
/ Computer science
/ cost-effectiveness
/ Councils
/ Databases, Genetic
/ diagnosis
/ Epidemiology
/ Female
/ Fractures
/ Fractures (Injuries)
/ General & Internal Medicine
/ Genetic aspects
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Health risk assessment
/ Health sciences
/ Health screening
/ Heel - diagnostic imaging
/ Hospitals
/ Humans
/ Internal medicine
/ Klinisk medicin
/ Machine Learning
/ Male
/ management
/ Mass Screening - methods
/ Medical and Health Sciences
/ Medical Genetics and Genomics (including Gene Therapy)
/ Medical research
/ Medicin och hälsovetenskap
/ Medicine
/ Medicine and Health Sciences
/ Medicinsk genetik och genomik (Här ingår: Genterapi)
/ Medicinska och farmaceutiska grundvetenskaper
/ Metabolism
/ Middle Aged
/ Multifactorial Inheritance
/ Nutrition
/ older women
/ Orthopaedics
/ Ortopedi
/ Osteoporosis
/ Osteoporosis - genetics
/ osteoporotic fractures
/ Osteoporotic Fractures - genetics
/ Osteoporotic Fractures - prevention & control
/ Population
/ Prediction models
/ quantitative ultrasound
/ Research and Analysis Methods
/ Risk assessment
/ Risk Assessment - methods
/ Risk Factors
/ Software
/ strategies
/ uk biobank
/ Ultrasonography
/ Ultrasound
/ United Kingdom
2020
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Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
by
Forest, Marie
, Kemp, John P.
, Karlsson, Magnus
, McCloskey, Eugene V.
, Leslie, William D.
, Kiel, Douglas P.
, Kanis, John A.
, Harvey, Nicholas C.
, Cooper, Cyrus
, Greenwood, Celia M. T.
, Evans, David M.
, Rivadeneira, Fernando
, Evans, Daniel
, Mellström, Dan
, Orwoll, Eric
, Richards, J. Brent
, Keller-Baruch, Julyan
, Forgetta, Vincenzo
, Bhatnagar, Sahir
, Clarke, Robert
, Ohlsson, Claes
, Nethander, Maria
, Morris, John A.
, Pineau, Joelle
, Johansson, Helena
, Durand, Audrey
in
Aged
/ Arthritis
/ association
/ Basic Medicine
/ Biology and Life Sciences
/ Biomedical research
/ Bone Density
/ Bone diseases
/ Bone mineral density
/ Calcaneus - diagnostic imaging
/ Clinical Medicine
/ Cohort Studies
/ Computer science
/ cost-effectiveness
/ Councils
/ Databases, Genetic
/ diagnosis
/ Epidemiology
/ Female
/ Fractures
/ Fractures (Injuries)
/ General & Internal Medicine
/ Genetic aspects
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Health risk assessment
/ Health sciences
/ Health screening
/ Heel - diagnostic imaging
/ Hospitals
/ Humans
/ Internal medicine
/ Klinisk medicin
/ Machine Learning
/ Male
/ management
/ Mass Screening - methods
/ Medical and Health Sciences
/ Medical Genetics and Genomics (including Gene Therapy)
/ Medical research
/ Medicin och hälsovetenskap
/ Medicine
/ Medicine and Health Sciences
/ Medicinsk genetik och genomik (Här ingår: Genterapi)
/ Medicinska och farmaceutiska grundvetenskaper
/ Metabolism
/ Middle Aged
/ Multifactorial Inheritance
/ Nutrition
/ older women
/ Orthopaedics
/ Ortopedi
/ Osteoporosis
/ Osteoporosis - genetics
/ osteoporotic fractures
/ Osteoporotic Fractures - genetics
/ Osteoporotic Fractures - prevention & control
/ Population
/ Prediction models
/ quantitative ultrasound
/ Research and Analysis Methods
/ Risk assessment
/ Risk Assessment - methods
/ Risk Factors
/ Software
/ strategies
/ uk biobank
/ Ultrasonography
/ Ultrasound
/ United Kingdom
2020
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Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
by
Forest, Marie
, Kemp, John P.
, Karlsson, Magnus
, McCloskey, Eugene V.
, Leslie, William D.
, Kiel, Douglas P.
, Kanis, John A.
, Harvey, Nicholas C.
, Cooper, Cyrus
, Greenwood, Celia M. T.
, Evans, David M.
, Rivadeneira, Fernando
, Evans, Daniel
, Mellström, Dan
, Orwoll, Eric
, Richards, J. Brent
, Keller-Baruch, Julyan
, Forgetta, Vincenzo
, Bhatnagar, Sahir
, Clarke, Robert
, Ohlsson, Claes
, Nethander, Maria
, Morris, John A.
, Pineau, Joelle
, Johansson, Helena
, Durand, Audrey
in
Aged
/ Arthritis
/ association
/ Basic Medicine
/ Biology and Life Sciences
/ Biomedical research
/ Bone Density
/ Bone diseases
/ Bone mineral density
/ Calcaneus - diagnostic imaging
/ Clinical Medicine
/ Cohort Studies
/ Computer science
/ cost-effectiveness
/ Councils
/ Databases, Genetic
/ diagnosis
/ Epidemiology
/ Female
/ Fractures
/ Fractures (Injuries)
/ General & Internal Medicine
/ Genetic aspects
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Health risk assessment
/ Health sciences
/ Health screening
/ Heel - diagnostic imaging
/ Hospitals
/ Humans
/ Internal medicine
/ Klinisk medicin
/ Machine Learning
/ Male
/ management
/ Mass Screening - methods
/ Medical and Health Sciences
/ Medical Genetics and Genomics (including Gene Therapy)
/ Medical research
/ Medicin och hälsovetenskap
/ Medicine
/ Medicine and Health Sciences
/ Medicinsk genetik och genomik (Här ingår: Genterapi)
/ Medicinska och farmaceutiska grundvetenskaper
/ Metabolism
/ Middle Aged
/ Multifactorial Inheritance
/ Nutrition
/ older women
/ Orthopaedics
/ Ortopedi
/ Osteoporosis
/ Osteoporosis - genetics
/ osteoporotic fractures
/ Osteoporotic Fractures - genetics
/ Osteoporotic Fractures - prevention & control
/ Population
/ Prediction models
/ quantitative ultrasound
/ Research and Analysis Methods
/ Risk assessment
/ Risk Assessment - methods
/ Risk Factors
/ Software
/ strategies
/ uk biobank
/ Ultrasonography
/ Ultrasound
/ United Kingdom
2020
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Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
Journal Article
Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
2020
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Overview
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.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ Calcaneus - diagnostic imaging
/ Councils
/ Female
/ Genetic Predisposition to Disease
/ Genetics
/ Genome-Wide Association Study
/ Genomes
/ Genomics
/ Humans
/ Male
/ Medical Genetics and Genomics (including Gene Therapy)
/ Medicine
/ Medicine and Health Sciences
/ Medicinsk genetik och genomik (Här ingår: Genterapi)
/ Medicinska och farmaceutiska grundvetenskaper
/ Ortopedi
/ Osteoporotic Fractures - genetics
/ Osteoporotic Fractures - prevention & control
/ Research and Analysis Methods
/ Software
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