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Objective: Femoral neck geometric parameters (FNGPs), such as periosteal diameter (W), cross-sectional area (CSA), cortical thickness (CT), buckling ratio (BR), and section modulus (Z), are highly genetically correlated with body lean mass. However, the specific SNPs/genes shared by these phenotypes are largely unknown., Methods: To identify the specific SNPs/genes shared between FNGPs and appendicular lean mass (ALM), we performed an initial bivariate genome-wide association study (GWAS) by scanning ∼690,000 SNPs in 1,627 unrelated Han Chinese adults (802 males and 825 females) and a follow-up replicate study in 2,286 unrelated US Caucasians., Results: We identified 13 interesting SNPs that may be important for both FNGPs and ALM. Two SNPs, rs681900 located in the HK2 (hexokinase 2) gene and rs11859916 in the UMOD (uromodulin) gene, were bivariately associated with FNGPs and ALM (p = 7.58×10(-6) for ALM-BR and p = 2.93×10(-6) for ALM-W, respectively). The associations were then replicated in Caucasians, with corresponding p values of 0.024 for rs681900 and 0.047 for rs11859916. Meta-analyses yielded combined p values of 3.05×10(-6) and 2.31×10(-6) for rs681900 and rs11859916, respectively. Our findings are consistent with previous biological studies that implicated HK2 and UMOD in both FNGPs and ALM. Our study also identified a group of 11 contiguous SNPs, which spanned a region of ∼130 kb, were bivariately associated with FNGPs and ALM, with p values ranging from 3.06×10(-7) to 4.60×10(-6) for ALM-BR. The region contained two neighboring miRNA coding genes, MIR873 (MicroRNA873) and MIR876 (MicroRNA876)., Conclusion: Our study implicated HK2, UMOD, MIR873 and MIR876, as pleiotropic genes underlying variation of both FNGPs and ALM, thus suggesting their important functional roles in co-regulating both FNGPs and ALM.

Background: Overweight or obese populations may have lower risk of osteoporotic fractures and higher bone mineral density (BMD), while bone strength is determined not only by bone material but also by bone structural parameters. Thus, the influence of body weight on bone geometry was examined in Chinese overweight adults., Aim: The purpose of this study was to explore how total body lean mass (TBLM) and total body fat mass (TBFM) contribute to the variation of bone geometry at the femoral neck in Chinese overweight adults., Subjects and Methods: Bone geometric parameters including section modulus (Z), cross-sectional area (CSA), subperiosteal width (W), cortical thickness (CT) and buckling ratio (BR) were compared in 100 overweight (body mass index, BMI >/= 23) vs. 100 underweight subjects (BMI 0.055 for both sexes)., Conclusion: Bone geometry may adapt primarily to mechanical load as represented by TBLM, but TBFM seemed to have no independent effect on bone geometry in Chinese overweight subjects.

Bone mineral density (BMD) and whole‐body lean mass (WBLM) are two important phenotypes of osteoporosis and sarcopenia. Previous studies have shown that BMD and lean mass were phenotypically and genetically correlated. To identify the novel common genetic factors shared between BMD and WBLM, we performed the conditional false discovery rate (cFDR) analysis using summary data of the genome‐wide association study of femoral neck BMD (n = 53,236) and WBLM (n = 38,292) from the Genetic Factors for Osteoporosis Consortium (GEFOS). We identified eight pleiotropic Single Nucleotide Polymorphism (SNPs) (PLCL1 rs11684176 and rs2880389, JAZF1 rs198, ADAMTSL3 rs10906982, RFTN2/MARS2 rs7340470, SH3GL3 rs1896797, ST7L rs10776755, ANKRD44/SF3B1 rs11888760) significantly associated with femoral neck BMD and WBLM (ccFDR < 0.05). Bayesian fine‐mapping analysis showed that rs11888760, rs198, and rs1896797 were the possible functional variants in the ANKRD44/SF3B1, JAZF1i, and SH3GL3 loci, respectively. Functional annotation suggested that rs11888760 was likely to comprise a DNA regulatory element and linked to the expression of RFTN2 and PLCL1. PLCL1 showed differential expression in laryngeal posterior cricoarytenoid muscle between rats of 6 months and 30 months of age. Our findings, together with PLCL1's potential functional relevance to bone and skeletal muscle function, suggested that rs11888760 was the possible pleiotropic functional variants appearing to coregulate both bone and muscle metabolism through regulating the expression of PLCL1. The findings enhanced our knowledge of genetic associations between BMD and lean mass and provide a rationale for subsequent functional studies of the implicated genes in the pathophysiology of diseases, such as osteoporosis and sarcopenia. [ABSTRACT FROM AUTHOR]

Leptin, a small polypeptide hormone secreted by the adipocytes, controls body weight and gonadal function by binding to a special receptor located in the hypothalamus. Observational studies have demonstrated a controversial association between leptin and bone mineral density (BMD), and functional studies of the relationship between leptin and BMD still largely vary by different studies. Using SNPs strongly associated with leptin levels in 52,140 individuals, we conducted a two-sample Mendelian randomization study to identify whether genetically lowered leptin levels were associated with BMD by using an inverse-variance weighted method, a weighted median method, MR-Egger and Robust Adjusted Profile Score. We found that circulating leptin levels may causally decrease lumbar spine BMD (effect size = −0.45, 95% CI: −0.82, −0.083; p value = 0.016). The association estimates of circulating leptin levels on femoral neck, forearm and total body BMD were not significant. Our study suggests that genetically predicted higher circulating leptin was associated with lower LS-BMD. • We inferred the causal relationship between leptin and BMD in large samples by using summary statistics from GWAS. • We estimated the causal relationships between leptin and BMD at different skeletal sites. • Four methods of Mendelian randomization were used to examine the causal relationship between leptin and BMD. [ABSTRACT FROM AUTHOR]

Abstract Aims Clinical and epidemiological findings point to an association between type 2 diabetes (T2D) and osteoporosis. Genome-wide association studies (GWASs) have been fruitful in identifying some loci potentially associated with osteoporosis and T2D respectively. However, the total genetic variance for each of these two diseases and the shared genetic determination between them are largely unknown. The aim of this study was to identify novel genetic variants for osteoporosis and/or T2D. Methods First, using a pleiotropic conditional false discovery rate (cFDR) method, we analyzed two GWAS summary data of femoral neck bone mineral density (FN_BMD, n = 53,236) and T2D (n = 159,208) to identify novel shared genetic loci. FN_BMD is an important risk factor for osteoporosis. Next, to explore the potential functions of the identified potential pleiotropic genes, differential expression analysis was performed for them in monocytes and peripheral blood mononuclear cells (PBMCs) as these cells are relevant to the etiology of osteoporosis and/or T2D. Further, weighted gene co-expression analysis (WGCNA) was conducted to identify functional connections between novel pleiotropic genes and known osteoporosis/T2D susceptibility genes by using transcriptomic expression datasets in bone biopsies (E-MEXP-1618) and pancreatic islets (GSE50397). Finally, multi-trait fine mapping for the detected pleiotropic risk loci were conducted to identify the SNPs that have the highest probability of being causal for both FN_BMD and T2D. Results We identified 27 significant SNPs with cFDR<0.05 for FN_BMD and 61 SNPs for T2D respectively. Four loci, rs7068487 (PLEKHA1), rs10885421 (TCF7L2), rs944082 (GNG12-AS1 (WLS)) and rs2065929 (PIFO||PGCP1), were found to be potentially pleiotropic and shared between FN_BMD and T2D (ccFDR<0.05). PLEKHA1 was found differentially expressed in circulating monocytes between high and low BMD subjects, and PBMCs between diabetic and non-diabetic conditions. WGCNA showed that PLEKHA1 and TCF7L2 were interconnected with multiple osteoporosis and T2D associated genes in bone biopsy and pancreatic islets, such as JAG, EN1 and CPE. Fine mapping showed that rs11200594 was a potentially causal variant in the locus of PLEKHA1. rs11200594 is also an eQTL of PLEKHA1 in multiple tissue (e.g. peripheral blood cells, adipose and ovary) and is in strong LD with a number of functional variants. Conclusions Four potential pleiotropic loci were identified for shared genetic determination of osteoporosis and T2D. Our study highlights PLEKHA1 as an important potentially pleiotropic gene. The findings may help us gain a better understanding of the shared genetic determination between these two important disorders. Highlights • Identified potential novel variants for complex diseases by cFDR with GWAS statistics • Identified 27 potential novel variants for osteoporosis and 61 for type 2 diabetes • Identified 4 potential pleiotropic variants for osteoporosis and type 2 diabetes [ABSTRACT FROM AUTHOR]