Meta-analysis of genome-wide scans for total body BMD in children and adults reveals allelic heterogeneity and age-specific effects at the WNT16 locus.
To identify genetic loci influencing bone accrual, we performed a genome-wide association scan for total-body bone mineral density (TB-BMD) variation in 2,660 children of different ethnicities. We discovered variants in 7q31.31 associated with BMD measurements, with the lowest P = 4.1 × 10(-11) observed for rs917727 with minor allele frequency of 0.37. We sought replication for all SNPs located ± 500 kb from rs917727 in 11,052 additional individuals from five independent studies including children and adults, together with de novo genotyping of rs3801387 (in perfect linkage disequilibrium (LD) with rs917727) in 1,014 mothers of children from the discovery cohort. The top signal mapping in the surroundings of WNT16 was replicated across studies with a meta-analysis P = 2.6 × 10(-31) and an effect size explaining between 0.6%-1.8% of TB-BMD variance. Conditional analyses on this signal revealed a secondary signal for total body BMD (P = 1.42 × 10(-10)) for rs4609139 and mapping to C7orf58. We also examined the genomic region for association with skull BMD to test if the associations were independent of skeletal loading. We identified two signals influencing skull BMD variation, including rs917727 (P = 1.9 × 10(-16)) and rs7801723 (P = 8.9 × 10(-28)), also mapping to C7orf58 (r(2) = 0.50 with rs4609139). Wnt16 knockout (KO) mice with reduced total body BMD and gene expression profiles in human bone biopsies support a role of C7orf58 and WNT16 on the BMD phenotypes observed at the human population level. In summary, we detected two independent signals influencing total body and skull BMD variation in children and adults, thus demonstrating the presence of allelic heterogeneity at the WNT16 locus. One of the skull BMD signals mapping to C7orf58 is mostly driven by children, suggesting temporal determination on peak bone mass acquisition. Our life-course approach postulates that these genetic effects influencing peak bone mass accrual may impact the risk of osteoporosis later in life.
Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
Carolina
C
Medina-Gomez
John P
JP
Kemp
Karol
K
Estrada
Joel
J
Eriksson
Jeff
J
Liu
Sjur
S
Reppe
David M
DM
Evans
Denise H M
DH
Heppe
Liesbeth
L
Vandenput
Lizbeth
L
Herrera
Susan M
SM
Ring
Claudia J
CJ
Kruithof
Nicholas J
NJ
Timpson
M Carola
MC
Zillikens
Ole K
OK
Olstad
Hou-Feng
HF
Zheng
J Brent
JB
Richards
Beate
B
St Pourcain
Albert
A
Hofman
Vincent W V
VW
Jaddoe
George Davey
GD
Smith
Mattias
M
Lorentzon
Kaare M
KM
Gautvik
André G
AG
Uitterlinden
Robert
R
Brommage
Claes
C
Ohlsson
Jonathan H
JH
Tobias
Fernando
F
Rivadeneira
D000328:Adult; D000367:Age Factors; D000483:Alleles; D000818:Animals; D015519:Bone Density / Q000235:genetics* / Q000502:physiology; D002648:Child; D002675:Child, Preschool; D005260:Female; D020869:Gene Expression Profiling; D005787:Gene Frequency; D018740:Genetic Heterogeneity; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D051379:Mice; D010024:Osteoporosis / Q000235:genetics*; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors; D012886:Skull / Q000502:physiology; D051153:Wnt Proteins / Q000235:genetics*
C417262:WNT16 protein, human; D051153:Wnt Proteins