Search

Searching. Please wait…

Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture

Abstract: The extent to which low-frequency (minor allele frequency (MAF) between 1?5%) and rare (MAF#1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants1?8, as well as rare, populationspecific, coding variants9. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal553,236) and fracture (ntotal5508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n52,882 fromUK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n 53,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n526,534), and de novo replication genotyping (n 520,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD8 (rs11692564(T), MAF51.6%, replication effect size510.20 s.d., Pmeta52310214), which was also associated with a decreased risk of fracture (odds ratio50.85; P52310211; ncases598,742 and ncontrols5409,511). Using an En1cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel lowfrequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF51.2%, replication effect size5 10.41 s.d., Pmeta51310211). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

 Authorship: Zheng H.F., Forgetta V., Hsu Y.H., Estrada K., Rosello-Diez A., Leo P.J., Dahia C.L., Park-Min K.H., Tobias J.H., Kooperberg C., Kleinman A., Styrkarsdottir U., Liu C.T., Uggla C., Evans D.S., Nielson C.M., Walter K., Pettersson-Kymmer U., McCarthy S., Eriksson J., Kwan T., Jhamai M., Trajanoska K., Memari Y., Min J., Huang J., Danecek P., Wilmot B., Li R., Chou W.C., Mokry L.E., Moayyeri A., Claussnitzer M., Cheng C.H., Cheung

 Fuente: Nature. 2015, 526, 112-117

 Publisher: Nature Publishing Group

 Publication date: 01/10/2015

 No. of pages: 20

 Publication type: Article

 DOI: 10.1038/nature14878

 ISSN: 0028-0836,1476-4687

 Publication Url: https://doi.org/10.1038/nature14878

Authorship

ZHENG, HOU-FENG

FORGETTA, VINCENZO

HSU, YI-HSIANG

ESTRADA, KAROL

ROSELLO-DIEZ, ALBERTO

LEO, PAUL J.

DAHIA, CHITRA L.

PARK-MIN, KYUNG HYUN

TOBIAS, JONATHAN H.

KOOPERBERG, CHARLES

KLEINMAN, AARON

STYRKARSDOTTIR, UNNUR

LIU, CHING-TI

UGGLA, CHARLOTTA

EVANS, DANIEL S.

NIELSON, CARRIE M.

WALTER, KLAUDIA

MARIA TERESA ZARRABEITIA CIMIANO