Epigenome-wide Association of DNA Methylation in Whole Blood With Bone Mineral Density

Abstract

Genetic and environmental determinants of skeletal phenotypes such as bone mineral density (BMD) may converge through the epigenome, providing a tool to better understand osteoporosis pathophysiology. Because the epigenetics of BMD have been largely unexplored in humans, we performed an epigenome‐wide association study (EWAS) of BMD. We undertook a large‐scale BMD EWAS using the Infinium HumanMethylation450 array to measure site‐specific DNA methylation in up to 5515 European‐descent individuals (NDiscovery = 4614, NValidation = 901). We associated methylation at multiple cytosine‐phosphate‐guanine (CpG) sites with dual‐energy X‐ray absorptiometry (DXA)‐derived femoral neck and lumbar spine BMD. We performed sex‐combined and stratified analyses, controlling for age, weight, smoking status, estimated white blood cell proportions, and random effects for relatedness and batch effects. A 5% false‐discovery rate was used to identify CpGs associated with BMD. We identified one CpG site, cg23196985, significantly associated with femoral neck BMD in 3232 females (p = 7.9 × 10−11) and 4614 females and males (p = 3.0 × 10−8). cg23196985 was not associated with femoral neck BMD in an additional sample of 474 females (p = 0.64) and 901 males and females (p = 0.60). Lack of strong consistent association signal indicates that among the tested probes, no large‐effect epigenetic changes in whole blood associated with BMD, suggesting future epigenomic studies of musculoskeletal traits measure DNA methylation in a different tissue with extended genome coverage. © 2017 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals Inc.

Distinct DNA methylation profiles in bone and blood of osteoporotic and healthy postmenopausal women

“…A recent blood EWAS of >5500 individuals identified only one BMD associated CpG methylation using the same platform as the current study. 47 The CpG was localized to the gene CES, which was not among those assessed in our study. Also their different statistical approach (no candidate CpGs) may explain why none of our blood associated CpGs were identified.…”

Mendelian Randomization Identifies CpG Methylation Sites With Mediation Effects for Genetic Influences on BMD in Peripheral Blood Monocytes

“…The GREAT analysis shows that the nearby genes of DMCs with difference >0.05 are enriched in association with a bonerelated human phenotype term, elevated alkaline phosphatase of bone origin (Figure 3). To evaluate whether our findings are consistent with previous studies, we checked the overlap of DMCs with the significant signals in three previous EWAS of OP (Delgado-Calle et al, 2013;Reppe et al, 2017;Morris et al, 2017). For each DMC identified by our study, we found the nearest signals identified in previous EWAS and calculated the distance between the DMC and the EWAS signals (Tables S5 and S6).…”

Quantification of the pace of biological aging in humans through a blood test: The DunedinPoAm DNA methylation algorithm

“…Step 3, which we report here, we distill the Pace of Aging into a measurement that can be obtained from a single blood sample. Here we focused on blood DNA methylation as an accessible molecular measurement that is sensitive to changes in physiology occurring in multiple organ systems (Birney et al, 2016;Bolund et al, 2017;Chambers et al, 2015;Chu et al, 2017;Hedman Åsa K. et al, 2017;Ma et al, 2019;Mill and Heijmans, 2013;Morris et al, 2017;Wahl et al, 2017). We used data about the Pace of Aging from age 26 to 38 years in the Dunedin Study along with whole-genome methylation data at age 38 years.…”