Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study.
Aged
Bone Density
Calcaneus
/ diagnostic imaging
Cohort Studies
Databases, Genetic
Female
Genetic Predisposition to Disease
Genome-Wide Association Study
Heel
/ diagnostic imaging
Humans
Machine Learning
Male
Mass Screening
/ methods
Middle Aged
Multifactorial Inheritance
Osteoporosis
/ genetics
Osteoporotic Fractures
/ genetics
Risk Assessment
/ methods
Risk Factors
Ultrasonography
United Kingdom
Journal
PLoS medicine
ISSN: 1549-1676
Titre abrégé: PLoS Med
Pays: United States
ID NLM: 101231360
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
05
12
2019
accepted:
03
06
2020
entrez:
3
7
2020
pubmed:
3
7
2020
medline:
17
9
2020
Statut:
epublish
Résumé
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.
Sections du résumé
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.
Identifiants
pubmed: 32614825
doi: 10.1371/journal.pmed.1003152
pii: PMEDICINE-D-19-04448
pmc: PMC7331983
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1003152Subventions
Organisme : Medical Research Council
ID : MC_UP_A620_1015
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : U01 AG042140
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042124
Pays : United States
Organisme : British Heart Foundation
Pays : United Kingdom
Organisme : NCATS NIH HHS
ID : UL1 TR002369
Pays : United States
Organisme : CIHR
Pays : Canada
Organisme : NIAMS NIH HHS
ID : K01 AR062655
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG027810
Pays : United States
Organisme : Medical Research Council
ID : MC_U147585827
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : R01 AG005394
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG005407
Pays : United States
Organisme : Medical Research Council
ID : MC_U147585824
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/P020941/1
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : U01 AG042145
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR035583
Pays : United States
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : NIAMS NIH HHS
ID : RC2 AR058973
Pays : United States
Organisme : Medical Research Council
ID : G0400491
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_U147585819
Pays : United Kingdom
Organisme : NCATS NIH HHS
ID : UL1 TR000128
Pays : United States
Organisme : Medical Research Council
ID : MC_UU_12011/2
Pays : United Kingdom
Organisme : Department of Health
ID : 10/33/04
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_12011/1
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : R01 AG027576
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042139
Pays : United States
Organisme : Medical Research Council
ID : MC_UP_A620_1014
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : U01 AG042143
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR035584
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR035582
Pays : United States
Organisme : NIAMS NIH HHS
ID : U01 AR066160
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG042168
Pays : United States
Organisme : Medical Research Council
ID : MC_UU_12013/4
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : R01 AG027574
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR051124
Pays : United States
Déclaration de conflit d'intérêts
I have read the journal’s policy and the authors of this manuscript have the following competing interests: JAK reports grants from Amgen, Eli Lilly and Radius Health; consulting fees from Theramex. JAK is the architect of FRAX but has no financial interest. JBR reports investigator-initiated grants from Biogen, Eli Lilly and GlaxoSmithKline, for programs unrelated to the research presented here. JBR is an advisor to GlaxoSmithKline. DPK reports grants from Radius Health and the Dairy Council unrelated to the research presented here and consulting fees from Solarea Bio unrelated to the research presented here. CC reports personal fees (outside the submitted work) from Amgen, Danone, Eli Lilly, GSK, Kyowa Kirin, Medtronic, Merck, Nestle, Novartis, Pfizer, Roche, Servier, Shire, Takeda, UCB. NCH reports consultancy, lecture fees and honoraria (outside the submitted work) from Alliance for Better Bone Health, AMGEN, MSD, Eli Lilly, Servier, Shire, UCB, Kyowa Kirin, Consilient Healthcare, Radius Health and Internis Pharma.
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