A genome-wide scan for pleiotropy between bone mineral density and nonbone phenotypes

Maria A. Christou, Georgios Ntritsos, Georgios Markozannes, Fotis Koskeridis, Spyros N. Nikas, David Karasik, Douglas P. Kiel, Evangelos Evangelou, Evangelia E. Ntzani

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7 Scopus citations

Abstract

Osteoporosis is the most common metabolic bone disorder globally and is characterized by skeletal fragility and microarchitectural deterioration. Genetic pleiotropy occurs when a single genetic element is associated with more than one phenotype. We aimed to identify pleiotropic loci associated with bone mineral density (BMD) and nonbone phenotypes in genome-wide association studies. In the discovery stage, the NHGRI-EBI Catalog was searched for genome-wide significant associations (P value < 5 × 10−8), excluding bone-related phenotypes. SNiPA was used to identify proxies of the significantly associated single nucleotide polymorphisms (SNPs) (r2 = 1). We then assessed putative genetic associations of this set of SNPs with femoral neck (FN) and lumbar spine (LS) BMD data from the GEFOS Consortium. Pleiotropic variants were claimed at a false discovery rate < 1.4 × 10−3 for FN-BMD and < 1.5 × 10−3 for LS-BMD. Replication of these genetic markers was performed among more than 400 000 UK Biobank participants of European ancestry with available genetic and heel bone ultrasound data. In the discovery stage, 72 BMD-related pleiotropic SNPs were identified, and 12 SNPs located in 11 loci on 8 chromosomes were replicated in the UK Biobank. These SNPs were associated, in addition to BMD, with 14 different phenotypes. Most pleiotropic associations were exhibited by rs479844 (AP5B1, OVOL1 genes), which was associated with dermatological and allergic diseases, and rs4072037 (MUC1 gene), which was associated with magnesium levels and gastroenterological cancer. In conclusion, 12 BMD-related genome-wide significant SNPs showed pleiotropy with nonbone phenotypes. Pleiotropic associations can deepen the genetic understanding of bone-related diseases by identifying shared biological mechanisms with other diseases or traits.

Original languageEnglish
Article number26
JournalBone Research
Volume8
Issue number1
DOIs
StatePublished - 1 Dec 2020

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© 2020, The Author(s).

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