Dissecting the Genetics of Osteoporosis using Systems Approaches

Identification of an novel genetic variant associated with osteoporosis: insights from the Taiwan Biobank Study

Purpose

The purpose of this study was to identify new independent significant SNPs associated with osteoporosis using data from the Taiwan Biobank (TWBB).

Material and Methods

The dataset was divided into discovery (60%) and replication (40%) subsets. Following data quality control, genome-wide association study (GWAS) analysis was performed, adjusting for sex, age, and the top 5 principal components, employing the Scalable and Accurate Implementation of the Generalized mixed model approach. This was followed by a meta-analysis of TWBB1 and TWBB2. The Functional Mapping and Annotation (FUMA) platform was used to identify osteoporosis-associated loci. Manhattan and quantile-quantile plots were generated using the FUMA platform to visualize the results. Independent significant SNPs were selected based on genome-wide significance (P < 5 × 10-8) and independence from each other (r2 < 0.6) within a 1 Mb window. Positional, eQTL(expression quantitative trait locus), and Chromatin interaction mapping were used to map SNPs to genes.

Results

A total of 29 084 individuals (3154 osteoporosis cases and 25 930 controls) were used for GWAS analysis (TWBB1 data), and 18 918 individuals (1917 cases and 17 001 controls) were utilized for replication studies (TWBB2 data). We identified a new independent significant SNP for osteoporosis in TWBB1, with the lead SNP rs76140829 (minor allele frequency = 0.055, P-value = 1.15 × 10-08). Replication of the association was performed in TWBB2, yielding a P-value of 6.56 × 10-3. The meta-analysis of TWBB1 and TWBB2 data demonstrated a highly significant association for SNP rs76140829 (P-value = 7.52 × 10-10). In the positional mapping of rs76140829, 6 genes (HABP2, RP11-481H12.1, RNU7-165P, RP11-139 K1.2, RP11-57H14.3, and RP11-214 N15.5) were identified through chromatin interaction mapping in mesenchymal stem cells.

Conclusions

Our GWAS analysis using the Taiwan Biobank dataset unveils rs76140829 in the VTI1A gene as a key risk variant associated with osteoporosis. This finding expands our understanding of the genetic basis of osteoporosis and highlights the potential regulatory role of this SNP in mesenchymal stem cells.

Amoli M, Fana SE, Dimai HP, Obermayer-Pietsch B, Luegger B, Rivadeneira F, Nabipour I, Larijani B, Khashayar P. Protocol for preliminary, multicenteric validation of "PoCOsteo device": A point of care tool for proteomic and genomic study of osteoporosis

One of the goals of the HORIZON 2020 project PoCOsteo was to develop a medical device, which would measure and/or quantify proteomic as well as genomic factors as present in whole blood samples collected through finger prick. After validating the tool in the clinical setting, the next step would be its clinical validation based on the existing guidelines. This article presents the protocol of a validation study to be carried out independently at two different centers (Division of Endocrinology and Diabetology at the Medical University of Graz as a clinic-based cohort, and the Endocrinology and Metabolism Research Institute at the Tehran University of Medical Sciences as a population-based cohort). It aims to assess the tool according to the Clinical & Laboratory Standards Institute guidelines, confirming if the proteomics and genomics measurements provided by the tool are accurate and reproducible compared with the existing state-of-the-art tests. This is the first time that such a detailed protocol for lab validation of a medical tool for proteomics and genomic measurement is designed based on the existing guidelines and thus could be used as a template for clinical validation of future point-of-care tools. Moreover, the multicentric cohort design will allow the study of a large number of diverse individuals, which will improve the validity and generalizability of the results for different settings.

Atp6v1h Deficiency Blocks Bone Loss in Simulated Microgravity Mice through the Fos-Jun-Src-Integrin Pathway

The microgravity conditions in outer space are widely acknowledged to induce significant bone loss. Recent studies have implicated the close relationship between Atp6v1h gene and bone loss. Despite this, the role of Atp6v1h in bone remodeling and its molecular mechanisms in microgravity have not been fully elucidated. To address this, we used a mouse tail suspension model to simulate microgravity. We categorized both wild-type and Atp6v1h knockout (Atp6v1h+/-) mice into two groups: regular feeding and tail-suspension feeding, ensuring uniform feeding conditions across all cohorts. Analysis via micro-CT scanning, hematoxylin-eosin staining, and tartrate-resistant acid phosphatase assays indicated that wild-type mice underwent bone loss under simulated microgravity. Atp6v1h+/- mice exhibited bone loss due to Atp6v1h deficiency but did not present aggravated bone loss under the same simulated microgravity. Transcriptomic sequencing revealed the upregulation of genes, such as Fos, Src, Jun, and various integrin subunits in the context of simulated microgravity and Atp6v1h knockout. Real-time quantitative polymerase chain reaction (RT-qPCR) further validated the modulation of downstream osteoclast-related genes in response to interactions with ATP6V1H overexpression cell lines. Co-immunoprecipitation indicated potential interactions between ATP6V1H and integrin beta 1, beta 3, beta 5, alpha 2b, and alpha 5. Our results indicate that Atp6v1h level influences bone loss in simulated microgravity by modulating the Fos-Jun-Src-Integrin pathway, which, in turn, affects osteoclast activity and bone resorption, with implications for osteoporosis. Therefore, modulating Atp6v1h expression could mitigate bone loss in microgravity conditions. This study elucidates the molecular mechanism of Atp6v1h's role in osteoporosis and positions it as a potential therapeutic target against environmental bone loss. These findings open new possibilities for the treatment of multifactorial osteoporosis.

Systems genetics approaches for understanding complex traits with relevance for human disease

Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.

Resveratrol promotes bone mass in ovariectomized rats and the SIRT1 rs7896005 SNP is associated with bone mass in women during perimenopause and early postmenopause

OBJECTIVE

This study aimed to examine the effects of SIRT1 agonist resveratrol on bone mass in ovariectomized (OVX) rats and the SIRT1 single-nucleotide polymorphism (SNP) rs7896005 on bone mass in women during menopause and early postmenopause.

METHODS

An animal experiment was conducted on rats that were sham-operated (SHAM), OVX or OVX and different administered doses of resveratrol. Serum markers and femur microstructure and staining were assessed. A cross-sectional study was conducted in women undergoing menopause. SIRT1 protein and SIRT1 SNP rs7896005 were evaluated.

RESULTS

OVX rats administered resveratrol, especially high doses, showed lower bone loss than OVX rats. Serum osteoprotegerin (OPG) and femur SIRT1, β-catenin and bone mineral density (BMD) were significantly increased, whereas receptor activator of NF-κB ligand (RANKL) was significantly decreased. Serum SIRT1 levels were significantly lower in women with low bone mass (p < 0.01). Women with the CA genotype of rs7896005 had lower bone mass than those with the CC genotype. The A allele showed a significant negative effect on bone loss risk (odds ratio = 3.48; p = 0.025).

CONCLUSIONS

Resveratrol stimulated SIRT1 expression and Wnt/β-catenin signaling to promote bone mass in rat femurs. Among women in perimenopause and early postmenopause, SIRT1 protected bone mass, and the A allele of SIRT1 rs7896005 was a risk factor for reduced bone mass.

Relationship between Coffee Consumption and Osteoporosis Risk Determined by the ESR1 Polymorphism rs2982573

BACKGROUND

The development of osteoporosis is partly explained by interactions between genetic and lifestyle or environmental factors.

OBJECTIVES

In the current study, we determined the relationship between coffee consumption and the risk of osteoporosis among individuals with ESR1 rs2982573 in Taiwan.

DESIGN, PARTICIPANTS AND SETTING

In this population-based cross-sectional study, we used genetic, demographic, and lifestyle data from participants recruited in Taiwan Biobank (TWB) between 2016 and 2019. We used multiple logistic regression analyses to determine the relationship between osteoporosis and variant rs2982573 genotypes (TT, TC, and CC).

MAIN OUTCOME

The primary outcome was osteoporosis.

RESULTS

Individuals with osteoporosis (n = 515) were older than those without the disease (mean age ±SE (year); 61.324±0.361 versus 53.068 ±0.130, p<0.001). There was no significant association between rs2982573 and osteoporosis (OR, 0.904; 95% CI, 0.706-1.157; p=0.422 for TC+CC when compared with the TT genotype). Coffee consumption was associated with a lower risk of osteoporosis (OR, 0.737; 95% CI, 0.592-0.918; p=0.006). The p-value for interaction between rs2982573 and coffee consumption was 0.0393. In our subgroup analyses, the adjusted ORs (95% CI) were 0.635 (0.410-0.985) in coffee drinking TC+CC individuals and 1.095 (0.809-1.482) in non-coffee drinking TC+CC individuals, respectively when compared with their TT genotype counterparts.

CONCLUSION

According to our study, participants in the TWB with the TC+CC genotype of ESR1 rs2982573 who consumed at least three cups of coffee per week were less likely to have osteoporosis.

Identification of ferroptosis-associated biomarkers for the potential diagnosis and treatment of postmenopausal osteoporosis

OBJECTIVE

Postmenopausal osteoporosis (PMOP) is one of the most commonly occurring conditions worldwide and is characterized by estrogen deficiency as well as persistent calcium loss with age. The aim of our study was to identify significant ferroptosis-associated biomarkers for PMOP.

METHODS AND MATERIALS

We obtained our training dataset from the Gene Expression Omnibus (GEO) database using GSE56815 expression profiling data. Meanwhile, we extracted ferroptosis-associated genes for further analysis. Differentially expressed ferroptosis-associated genes (DEFAGs) between OP patients and normal controls were selected using the "limma" package. We established a ferroptosis-associated gene signature using training models, specifically, random forest (RF) and support vector machine (SVM) models. It was further validated in another dataset (GSE56814) which also showed a high AUC: 0.98, indicating high diagnostic value. Using consensus clustering, the OP patient subtypes were identified. A ferroptosis associated gene (FAG)-Scoring scheme was developed by PCA. The important candidate genes associated with OP were also compared between different ferrclusters and geneclusters.

RESULTS

There were significant DEFAGs acquired, of which five (HMOX1, HAMP, LPIN1, MAP3K5, FLT3) were selected for establishing a ferroptosis-associated gene signature. Analyzed from the ROC curve, our established RF model had a higher AUC value than the SVM model (RF model AUC:1.00). Considering these results, the established RF model was chosen to be the most appropriate training model. Later, based on the expression levels of the five DEFAGs, a clinical application nomogram was established. The OP patients were divided into two subtypes (ferrcluster A, B and genecluster A, B, respectively) according to the consensus clustering method based on DEFAGs and differentially expressed genes (DEGs). Ferrcluster B and genecluster B had higher ferroptosis score than ferrcluster A and genecluster A, respectively. The expression of COL1A1 gene was significantly higher in ferrcluster B and gencluster B compared with ferrcluster A and gencluster A, respectively, while there is no statistical difference in term of VDR gene, COL1A2 genes, and PTH gene expressions between ferrcluster A and B, together with gencluster A and B.

CONCLUSIONS

On the basis of five explanatory variables (HMOX1, HAMP, LPIN1, MAP3K5 and FLT3), we developed a diagnostic ferroptosis-associated gene signature and identified two differently categorized OP subtypes that may potentially be applied for the early diagnosis and individualized treatment of PMOP. The ER gene, VDR gene, IL-6 gene, COL1A1 and COL1A2 genes, and PTH gene are important candidate gene of OP, however, more studies are still anticipated to further elucidate the relationship between these genes and ferroptosis in OP.

Systems Genetics Analysis Defines Importance Of TMEM43/LUMA For Cardiac And Metabolic Related Pathways

Broad cellular functions and diseases including muscular dystrophy, arrhythmogenic right ventricular cardiomyopathy (ARVC5) and cancer are associated with transmembrane protein43 (TMEM43/LUMA). The study aimed to investigate biological roles of TMEM43 through genetic regulation, gene pathways and gene networks, candidate interacting genes, and up- or downstream regulators. Cardiac transcriptomes from 40 strains of recombinant inbred BXD mice and two parental strains representing murine genetic reference population (GRP) were applied for genetic correlation, functional enrichment, and coexpression network analysis using systems genetics approach. The results were validated in a newly created knock-in Tmem43-S358L mutation mouse model (Tmem43^S358L) that displayed signs of cardiac dysfunction, resembling ARVC5 phenotype seen in humans. We found high Tmem43 levels among BXDs with broad variability in expression. Expression of Tmem43 highly negatively correlated with heart mass and heart rate among BXDs, whereas levels of Tmem43 highly positively correlated with plasma high-density lipoproteins (HDL). Through finding differentially expressed genes (DEGs) between Tmem43^S358L mutant and wild-type (Tmem43^WT) lines, 18 pathways (out of 42 found in BXDs GRP) that are involved in ARVC, hypertrophic cardiomyopathy, dilated cardiomyopathy, nonalcoholic fatty liver disease, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease were verified. We further constructed Tmem43-mediated gene network, in which Ctnna1, Adcy6, Gnas, Ndufs6, and Uqcrc2 were significantly altered in Tmem43^S358L mice versus Tmem43^WT controls. Our study defined the importance of Tmem43 for cardiac- and metabolism-related pathways, suggesting that cardiovascular disease-relevant risk factors may also increase risk of metabolic and neurodegenerative diseases via TMEM43-mediated pathways.

Identifying a possible new target for diagnosis and treatment of postmenopausal osteoporosis through bioinformatics and clinical sample analysis

Background

Postmenopausal osteoporosis, a common yet chronic systemic metabolic disease, has become a major public health problem due to life expectancy increasing around the world. The differentiation of mesenchymal stem cells (MSCs) into osteoblasts, and the differentiation of circulating monocyte cells into osteoclasts, play an important role in the balance of bone metabolism. However, when both undergo pathological changes, it can lead to abnormalities, resulting in osteoporosis. This study aims to explore a new biomarker for postmenopausal osteoporosis, thereby providing a new entry point for bioinformatic research into the clinical diagnosis and treatment of the disease.

Methods

Using the Gene Expression Omnibus (GEO) database, microarray analysis was conducted to identify differentially expressed genes in MSCs and monocytes in both postmenopausal osteoporosis patients and a healthy control group. The Database for Annotation, Visualization and Integrated Discovery (DAVID) database was used to analyze the function and enrichment of the selected genes, and a protein-protein interaction (PPI) network was constructed from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website and displayed in Cytoscape. To achieve the final results, module analysis of the PPI network was performed by using Molecular Complex Detection (MCODE).

Results

We identified 45 high-expression and 26 low-expression genes through the study, all of which underwent pathway enrichment analysis. This enrichment was observed in the cell cycle regulation, osteoclast differentiation, tumor necrosis factor (TNF) signaling pathway, and RNA transport. The top 10 hub genes of the PPI network were SF3B1, SRSF5, FUBP1, SRSF3, TIA1, KHSRP, LUC7L3, PNN, SRC, and ATRX. Comparing the MSCs and monocytes between the postmenopausal osteoporosis patients and the healthy control group, we noted that the expression of the above genes differed greatly.

Conclusions

Through bioinformatic analysis and clinical specimen validation, our study provides a new way for exploring the pathogenesis of postmenopausal osteoporosis. Most importantly, it suggests that the hub genes, SF3B1, SRSF5, FUBP1, KHSRP, and SRC, may become new diagnostic markers and therapeutic targets for diagnosing and treating postmenopausal osteoporosis in the future.

Systems genetics in diversity outbred mice inform BMD GWAS and identify determinants of bone strength

Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we use Diversity Outbred (DO) mice to directly address these limitations by performing a systems genetics analysis of 55 complex skeletal phenotypes. We apply a network approach to cortical bone RNA-seq data to discover 66 genes likely to be causal for human BMD GWAS associations, including the genes SERTAD4 and GLT8D2. We also perform GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a gene influencing cortical bone accrual and bone strength. In this work, we advance our understanding of the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.

Osteoporosis GWAS faces two challenges, causal gene discovery and a lack of phenotypic diversity. Here, the authors use the Diversity Outbred mouse population to inform human GWAS using networks and map genetic loci for 55 bone traits, identifying new potential bone strength genes.

Prioritization of Osteoporosis-Associated Genome-wide Association Study (GWAS) Single-Nucleotide Polymorphisms (SNPs) Using Epigenomics and Transcriptomics

Genetic risk factors for osteoporosis, a prevalent disease associated with aging, have been examined in many genome-wide association studies (GWASs). A major challenge is to prioritize transcription-regulatory GWAS-derived variants that are likely to be functional. Given the critical role of epigenetics in gene regulation, we have used an unusual epigenetics-based and transcription-based approach to identify some of the credible regulatory single-nucleotide polymorphisms (SNPs) relevant to osteoporosis from 38 reported bone mineral density (BMD) GWASs. Using Roadmap databases, we prioritized SNPs based upon their overlap with strong enhancer or promoter chromatin preferentially in osteoblasts relative to 12 heterologous cell culture types. We also required that these SNPs overlap open chromatin (Deoxyribonuclease I [DNaseI]-hypersensitive sites) and DNA sequences predicted to bind to osteoblast-relevant transcription factors in an allele-specific manner. From >50,000 GWAS-derived SNPs, we identified 14 novel and credible regulatory SNPs (Tier-1 SNPs) for osteoporosis risk. Their associated genes, BICC1, LGR4, DAAM2, NPR3, or HMGA2, are involved in osteoblastogenesis or bone homeostasis and regulate cell signaling or enhancer function. Four of these genes are preferentially expressed in osteoblasts. BICC1, LGR4, and DAAM2 play important roles in canonical Wnt signaling, a pathway critical for bone formation and repair. The transcription factors predicted to bind to the Tier-1 SNP-containing DNA sequences also have bone-related functions. We present evidence that some of the Tier-1 SNPs exert their effects on BMD risk indirectly through little-studied long noncoding RNA (lncRNA) genes, which may, in turn, control the nearby bone-related protein-encoding gene. Our study illustrates a method to identify novel BMD-related causal regulatory SNPs for future study and to prioritize candidate regulatory GWAS-derived SNPs, in general. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Micro-scale technologies propel biology and medicine

Historically, technology has been central to new discoveries in biology and progress in medicine. Among various technologies, microtechnologies, in particular, have had a prominent role in the revolution experienced by the life sciences in the last few decades, which will surely continue in the years to come. In this Perspective, we illustrate how microtechnologies, with a focus on microfluidics, have evolved in trends/waves to tackle the boundary of knowledge in the life sciences. We provide illustrative examples of technology-enabled biological breakthroughs and their current and future use in clinics. Finally, we take a closer look at the translational process to understand why the incorporation of new micro-scale technologies in medicine has been comparatively slow so far.

Mouse Genetic Reference Populations: Cellular Platforms for Integrative Systems Genetics

Interrogation of disease-relevant cellular and molecular traits exhibited by genetically diverse cell populations enables in vitro systems genetics approaches for uncovering the basic properties of cellular function and identity. Primary cells, stem cells, and organoids derived from genetically diverse mouse strains, such as Collaborative Cross and Diversity Outbred populations, offer the opportunity for parallel in vitro/in vivo screening. These panels provide genetic resolution for variant discovery and functional characterization, as well as disease modeling and in vivo validation capabilities. Here we review mouse cellular systems genetics approaches for characterizing the influence of genetic variation on signaling networks and phenotypic diversity, and we discuss approaches for data integration and cross-species validation.

The Polymorphism at PLCB4 Promoter (rs6086746) Changes the Binding Affinity of RUNX2 and Affects Osteoporosis Susceptibility: An Analysis of Bioinformatics-Based Case-Control Study and Functional Validation

PURPOSE

Genome-wide association studies have identified numerous genetic variants that are associated with osteoporosis risk; however, most of them are present in the non-coding regions of the genome and the functional mechanisms are unknown. In this study, we aimed to investigate the potential variation in runt domain transcription factor 2 (RUNX2), which is an osteoblast-specific transcription factor that normally stimulates bone formation and osteoblast differentiation, regarding variants within RUNX2 binding sites and risk of osteoporosis in postmenopausal osteoporosis (PMOP).

METHODS

We performed bioinformatics-based prediction by combining whole genome sequencing and chromatin immunoprecipitation sequencing to screen functional SNPs in the RUNX2 binding site using data from the database of Taiwan Biobank; Case-control studies with 651 postmenopausal women comprising 107 osteoporosis patients, 290 osteopenia patients, and 254 controls at Tri-Service General Hospital between 2015 and 2019 were included. The subjects were examined for bone mass density and classified into normal and those with osteopenia or osteoporosis by T-scoring with dual-energy X-ray absorptiometry. Furthermore, mRNA expression and luciferase reporter assay were used to provide additional evidence regarding the associations identified in the association analyses. Chi-square tests and logistic regression were mainly used for statistical assessment.

RESULTS

Through candidate gene approaches, 3 SNPs in the RUNX2 binding site were selected. A novel SNP rs6086746 in the PLCB4 promoter was identified to be associated with osteoporosis in Chinese populations. Patients with AA allele had higher risk of osteoporosis than those with GG+AG (adjusted OR = 6.89; 95% confidence intervals: 2.23-21.31, p = 0.001). Moreover, the AA genotype exhibited lower bone mass density (p < 0.05). Regarding mRNA expression, there were large differences in the correlation between PLCB4 and different RUNX2 alleles (Cohen's q = 0.91). Functionally, the rs6086746 A allele reduces the RUNX2 binding affinity, thus enhancing the suppression of PLCB4 expression (p < 0.05).

CONCLUSIONS

Our results provide further evidence to support the important role of the SNP rs6086746 in the etiology of osteopenia/osteoporosis, thereby enhancing the current understanding of the susceptibility to osteoporosis. We further studied the mechanism underlying osteoporosis regulation by PLCB4.

Metaanalysis Reveals Genetic Correlates of Osteoporosis Pathogenesis

OBJECTIVE

Osteoporosis is a growing healthcare burden. By identifying osteoporosis-promoting genetic variations, we can spotlight targets for new pharmacologic therapies that will improve patient outcomes. In this metaanalysis, we analyzed mesenchymal stem cell (MSC) biomarkers in patients with osteoporosis.

METHODS

We employed our Search Tag Analyze Resource for the Gene Expression Omnibus (STARGEO) platform to conduct a metaanalysis to define osteoporosis pathogenesis. We compared 15 osteoporotic and 14 healthy control MSC samples. We then analyzed the genetic signature in Ingenuity Pathway Analysis.

RESULTS

The top canonical pathways identified that were statistically significant included the serine peptidase inhibitor kazal type 1 pancreatic cancer pathway, calcium signaling, pancreatic adenocarcinoma signaling, axonal guidance signaling, and glutamate receptor signaling. Upstream regulators involved in this disease process included ESR1, dexamethasone, CTNNβ1, CREB1, and ERBB2.

CONCLUSION

Although there has been extensive research looking at the genetic basis for inflammatory arthritis, very little literature currently exists that has identified genetic pathways contributing to osteoporosis. Our study has identified several important genes involved in osteoporosis pathogenesis including ESR1, CTNNβ1, CREB1, and ERBB2. ESR1 has been shown to have numerous polymorphisms, which may play a prominent role in osteoporosis. The Wnt pathway, which includes the CTNNβ1 gene identified in our study, plays a prominent role in bone mass regulation. Wnt pathway polymorphisms can increase susceptibility to osteoporosis. Our analysis also suggests a potential mechanism for ERBB2 in osteoporosis through Semaphorin 4D (SEMA4D). Our metaanalysis identifies several genes and pathways that can be targeted to develop new anabolic drugs for osteoporosis treatment.

Genetic variability in noncoding RNAs: involvement of miRNAs and long noncoding RNAs in osteoporosis pathogenesis

The pathogenesis of osteoporosis is multifactorial and is the consequence of genetic, hormonal and lifestyle factors. Epigenetics, including noncoding RNA (ncRNA) deregulation, represents a link between susceptibility to develop the disease and environmental influences. The majority of studies investigated the expression of ncRNAs in osteoporosis patients; however, very little information is available on their genetic variability. In this review, we focus on two classes of ncRNAs: miRNAs and long noncoding RNAs (lncRNAs). We summarize recent findings on how polymorphisms in miRNAs and lncRNAs can perturb the lncRNA/miRNA/mRNA axis and may be involved in osteoporosis clinical outcome. We also provide a general overview on databases and bioinformatic tools useful for associating miRNAs and lncRNAs variability with complex genetic diseases.

Machine Learning Approaches for Fracture Risk Assessment: A Comparative Analysis of Genomic and Phenotypic Data in 5130 Older Men

The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Study (n = 5130), were analyzed. After a comprehensive genotype imputation, genetic risk score (GRS) was calculated from 1103 associated Single Nucleotide Polymorphisms for each participant. Data were normalized and split into a training set (80%) and a validation set (20%) for analysis. Random forest, gradient boosting, neural network, and logistic regression were used to develop prediction models for major osteoporotic fractures separately, with GRS, bone density, and other risk factors as predictors. In model training, the synthetic minority oversampling technique was used to account for low fracture rate, and tenfold cross-validation was employed for hyperparameters optimization. In the testing, the area under curve (AUC) and accuracy were used to assess the model performance. The McNemar test was employed to examine the accuracy difference between models. The results showed that the prediction performance of gradient boosting was the best, with AUC of 0.71 and an accuracy of 0.88, and the GRS ranked as the 7th most important variable in the model. The performance of random forest and neural network were also significantly better than that of logistic regression. This study suggested that improving fracture prediction in older men can be achieved by incorporating genetic profiling and by utilizing the gradient boosting approach. This result should not be extrapolated to women or young individuals.

Epigenetic Regulation of Skeletal Tissue Integrity and Osteoporosis Development

Bone turnover is sophisticatedly balanced by a dynamic coupling of bone formation and resorption at various rates. The orchestration of this continuous remodeling of the skeleton further affects other skeletal tissues through organ crosstalk. Chronic excessive bone resorption compromises bone mass and its porous microstructure as well as proper biomechanics. This accelerates the development of osteoporotic disorders, a leading cause of skeletal degeneration-associated disability and premature death. Bone-forming cells play important roles in maintaining bone deposit and osteoclastic resorption. A poor organelle machinery, such as mitochondrial dysfunction, endoplasmic reticulum stress, and defective autophagy, etc., dysregulates growth factor secretion, mineralization matrix production, or osteoclast-regulatory capacity in osteoblastic cells. A plethora of epigenetic pathways regulate bone formation, skeletal integrity, and the development of osteoporosis. MicroRNAs inhibit protein translation by binding the 3'-untranslated region of mRNAs or promote translation through post-transcriptional pathways. DNA methylation and post-translational modification of histones alter the chromatin structure, hindering histone enrichment in promoter regions. MicroRNA-processing enzymes and DNA as well as histone modification enzymes catalyze these modifying reactions. Gain and loss of these epigenetic modifiers in bone-forming cells affect their epigenetic landscapes, influencing bone homeostasis, microarchitectural integrity, and osteoporotic changes. This article conveys productive insights into biological roles of DNA methylation, microRNA, and histone modification and highlights their interactions during skeletal development and bone loss under physiological and pathological conditions.

A trans-eQTL network regulates osteoclast multinucleation and bone mass

Functional characterisation of cell-type-specific regulatory networks is key to establish a causal link between genetic variation and phenotype. The osteoclast offers a unique model for interrogating the contribution of co-regulated genes to in vivo phenotype as its multinucleation and resorption activities determine quantifiable skeletal traits. Here we took advantage of a trans-regulated gene network (MMnet, macrophage multinucleation network) which we found to be significantly enriched for GWAS variants associated with bone-related phenotypes. We found that the network hub gene Bcat1 and seven other co-regulated MMnet genes out of 13, regulate bone function. Specifically, global (Pik3cb^-/-, Atp8b2^+/-, Igsf8^-/-, Eml1^-/-, Appl2^-/-, Deptor^-/-) and myeloid-specific Slc40a1 knockout mice displayed abnormal bone phenotypes. We report opposing effects of MMnet genes on bone mass in mice and osteoclast multinucleation/resorption in humans with strong correlation between the two. These results identify MMnet as a functionally conserved network that regulates osteoclast multinucleation and bone mass.

Review of Secondary Causes of Osteoporotic Fractures Due to Diabetes and Spinal Cord Injury

PURPOSE OF REVIEW

The aim of this review is to gain a better understanding of osteoporotic fractures and the different mechanisms that are driven in the scenarios of bone disuse due to spinal cord injury and osteometabolic disorders due to diabetes.

RECENT FINDINGS

Despite major advances in understanding the pathogenesis, prevention, and treatment of osteoporosis, the high incidence of impaired fracture healing remains an important complication of bone loss, leading to marked impairment of the health of an individual and economic burden to the medical system. This review underlines several pathways leading to bone loss and increased risk for fractures. Specifically, we addressed the different mechanisms leading to bone loss after a spinal cord injury and diabetes. Finally, it also encompasses the changes responsible for impaired bone repair in these scenarios, which may be of great interest for future studies on therapeutic approaches to treat osteoporosis and osteoporotic fractures.

Comprehensive Analysis of the Genetic and Epigenetic Mechanisms of Osteoporosis and Bone Mineral Density

Osteoporosis is a skeletal disorder characterized by a systemic impairment of bone mineral density (BMD). Genome-wide association studies (GWAS) have identified hundreds of susceptibility loci for osteoporosis and BMD. However, the vast majority of susceptibility loci are located in non-coding regions of the genome and provide limited information about the genetic mechanisms of osteoporosis. Herein we performed a comprehensive functional analysis to investigate the genetic and epigenetic mechanisms of osteoporosis and BMD. BMD and osteoporosis are found to share many common susceptibility loci, and the corresponding susceptibility genes are significantly enriched in bone-related biological pathways. The regulatory element enrichment analysis indicated that BMD and osteoporosis susceptibility loci are significantly enriched in 5′UTR and DNase I hypersensitive sites (DHSs) of peripheral blood immune cells. By integrating GWAS and expression Quantitative Trait Locus (eQTL) data, we found that 15 protein-coding genes are regulated by the osteoporosis and BMD susceptibility loci. Our analysis provides new clues for a better understanding of the pathogenic mechanisms and offers potential therapeutic targets for osteoporosis.

Genetic Burden Contributing to Extremely Low or High Bone Mineral Density in a Senior Male Population From the Osteoporotic Fractures in Men Study (MrOS)

Worldwide, one in five men aged over 50 years will experience osteoporosis or a clinical bone fracture, with a greater fracture-related mortality rate than women. However, the genetic etiology of osteoporosis in men is still poorly understood. We aimed to identify the genetic variants and candidate genes associated with extremely low or high BMD for a better understanding of the biology underlying low bone density that may point to potential therapeutic targets for increasing bone mass. Subjects from the Osteoporotic Fractures in Men Study (MrOS) cohort were evaluated by age and BMI-adjusted total hip BMD. Those with BMD values 3 SDs away from the mean were selected and the remaining individuals whose adjusted BMD ranked at the highest or lowest 100 were included. Men with the lowest adjusted BMD (N = 98) and highest adjusted BMD (N = 110) were chosen for exome sequencing. Controls (N = 82) were men of Northern and Western European descent from the US Utah population of the 1000 Genomes Project. Fisher's exact test was performed to compare low- or high-BMD subjects with controls for single-gene associations. Additionally, sets of candidate genes causative of heritable disorders of connective tissue, including osteogenesis imperfecta (OI) and Ehlers-Danlos syndrome (EDS), were grouped for multigene and mutation burden analyses. No single-gene associations with rare variants were found for either the low BMD group (33 genes) or high BMD group (18 genes). In the group of OI genes, we detected a significant threefold increased accumulation of rare variants in low-BMD subjects compared with controls (p = 0.009). Additionally, genes associated with EDS had a twofold increased frequency in low-BMD subjects compared with controls (p = 0.03). These findings reveal a rare variant burden in OI and EDS disease genes at low BMD, which suggests a potential gene-panel approach to screen for multivariant associations in larger cohorts. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

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

Osteoporosis is mainly characterized by low bone mineral density (BMD) and is an increasingly serious public health concern. DNA methylation is a major epigenetic mechanism that may contribute to the variation in BMD and may mediate the effects of genetic and environmental factors of osteoporosis. In this study, we performed an epigenome-wide DNA methylation analysis in peripheral blood monocytes of 118 Caucasian women with extreme BMD values. Further, we developed and implemented a novel analytical framework that integrates Mendelian randomization with genetic fine mapping and colocalization to evaluate the causal relationships between DNA methylation and BMD phenotype. We identified 2,188 differentially methylated CpGs (DMCs) between the low and high BMD groups and distinguished 30 DMCs that may mediate the genetic effects on BMD. The causal relationship was further confirmed by eliminating the possibility of horizontal pleiotropy, linkage effect and reverse causality. The fine-mapping analysis determined 25 causal variants that are most likely to affect the methylation levels at these mediator DMCs. The majority of the causal methylation quantitative loci and DMCs reside within cell type-specific histone mark peaks, enhancers, promoters, promoter flanking regions and CTCF binding sites, supporting the regulatory potentials of these loci. The established causal pathways from genetic variant to BMD phenotype mediated by DNA methylation provide a gene list to aid in designing future functional studies and lead to a better understanding of the genetic and epigenetic mechanisms underlying the variation of BMD.

An eQTL in the cystathionine beta synthase gene is linked to osteoporosis in laying hens

BACKGROUND

Skeletal damage is a challenge for laying hens because the physiological adaptations required for egg laying make them susceptible to osteoporosis. Previously, we showed that genetic factors explain 40% of the variation in end of lay bone quality and we detected a quantitative trait locus (QTL) of large effect on chicken chromosome 1. The aim of this study was to combine data from the commercial founder White Leghorn population and the F2 mapping population to fine-map this QTL and understand its function in terms of gene expression and physiology.

RESULTS

Several single nucleotide polymorphisms on chromosome 1 between 104 and 110 Mb (galGal6) had highly significant associations with tibial breaking strength. The alternative genotypes of markers of large effect that flanked the region had tibial breaking strengths of 200.4 vs. 218.1 Newton (P < 0.002) and, in a subsequent founder generation, the higher breaking strength genotype was again associated with higher breaking strength. In a subsequent generation, cortical bone density and volume were increased in individuals with the better bone genotype but with significantly reduced medullary bone quality. The effects on cortical bone density were confirmed in a further generation and was accompanied by increased mineral maturity of the cortical bone as measured by infrared spectrometry and there was evidence of better collagen cross-linking in the cortical bone. Comparing the transcriptome of the tibia from individuals with good or poor bone quality genotypes indicated four differentially-expressed genes at the locus, one gene, cystathionine beta synthase (CBS), having a nine-fold higher expression in the genotype for low bone quality. The mechanism was cis-acting and although there was an amino-acid difference in the CBS protein between the genotypes, there was no difference in the activity of the enzyme. Plasma homocysteine concentration, the substrate of CBS, was higher in the poor bone quality genotype.

CONCLUSIONS

Validated markers that predict bone strength have been defined for selective breeding and a gene was identified that may suggest alternative ways to improve bone health in addition to genetic selection. The identification of how genetic variants affect different aspects of bone turnover shows potential for translational medicine.

A road map for understanding molecular and genetic determinants of osteoporosis

Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in 'systems genetics and genomics'. In this Review, we highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis. Furthermore, we summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis. The integration of multiple technologies will provide a road map to illuminate the complex pathogenesis of osteoporosis, especially from molecular functional aspects, in vivo in humans.

Identification of a key gene module associated with glucocorticoid- induced derangement in bone mineral density in patients with asthma

Derangement in bone mineral density (BMD) caused by glucocorticoid is well-known. The present study aimed to find key biological pathways associated with low BMD after glucocorticoid treatment in asthmatics using gene expression profiles of peripheral blood cells. We utilized immortalized B cells (IBCs) from 32 childhood asthmatics after multiple oral glucocorticoid bursts and peripheral blood mononuclear cells (PBMCs) from 17 adult asthmatics after a long-term use of oral glucocorticoid. We searched co-expressed gene modules significantly related with the BMD Z score in childhood asthmatics and tested if these gene modules were preserved and significantly associated with the BMD Z score in adult asthmatics as well. We identified a gene module composed of 199 genes significantly associated with low BMD in both childhood and adult asthmatics. The structure of this module was preserved across gene expression profiles. We found that the cellular metabolic pathway was significantly enriched in this module. Among 18 hub genes in this module, we postulated that 2 genes, CREBBP and EP300, contributed to low BMD following a literature review. A novel biologic pathway identified in this study highlighted a gene module and several genes as playing possible roles in the pathogenesis of glucocorticoid- induced derangement in BMD.

The Progress of CRISPR/Cas9-Mediated Gene Editing in Generating Mouse/Zebrafish Models of Human Skeletal Diseases

Genetic factors play a substantial role in the etiology of skeletal diseases, which involve 1) defects in skeletal development, including intramembranous ossification and endochondral ossification; 2) defects in skeletal metabolism, including late bone growth and bone remodeling; 3) defects in early developmental processes related to skeletal diseases, such as neural crest cell (NCC) and cilia functions; 4) disturbance of the cellular signaling pathways which potentially affect bone growth. Efficient and high-throughput genetic methods have enabled the exploration and verification of disease-causing genes and variants. Animal models including mouse and zebrafish have been extensively used in functional mechanism studies of causal genes and variants. The conventional approaches of generating mutant animal models include spontaneous mutagenesis, random integration, and targeted integration via mouse embryonic stem cells. These approaches are costly and time-consuming. Recent development and application of gene-editing tools, especially the CRISPR/Cas9 system, has significantly accelerated the process of gene-editing in diverse organisms. Here we review both mice and zebrafish models of human skeletal diseases generated by CRISPR/Cas9 system, and their contributions to deciphering the underpins of disease mechanisms.

OsteoporosAtlas: a human osteoporosis-related gene database

Background

Osteoporosis is a common, complex disease of bone with a strong heritable component, characterized by low bone mineral density, microarchitectural deterioration of bone tissue and an increased risk of fracture. Due to limited drug selection for osteoporosis and increasing morbidity, mortality of osteoporotic fractures, osteoporosis has become a major health burden in aging societies. Current researches for identifying specific loci or genes involved in osteoporosis contribute to a greater understanding of the pathogenesis of osteoporosis and the development of better diagnosis, prevention and treatment strategies. However, little is known about how most causal genes work and interact to influence osteoporosis. Therefore, it is greatly significant to collect and analyze the studies involved in osteoporosis-related genes. Unfortunately, the information about all these osteoporosis-related genes is scattered in a large amount of extensive literature. Currently, there is no specialized database for easily accessing relevant information about osteoporosis-related genes and miRNAs.

Methods

We extracted data from literature abstracts in PubMed by text-mining and manual curation. Moreover, a local MySQL database containing all the data was developed with PHP on a Windows server.

Results

OsteoporosAtlas (http://biokb.ncpsb.org/osteoporosis/), the first specialized database for easily accessing relevant information such as osteoporosis-related genes and miRNAs, was constructed and served for researchers. OsteoporosAtlas enables users to retrieve, browse and download osteoporosis-related genes and miRNAs. Gene ontology and pathway analyses were integrated into OsteoporosAtlas. It currently includes 617 human encoding genes, 131 human non-coding miRNAs, and 128 functional roles. We think that OsteoporosAtlas will be an important bioinformatics resource to facilitate a better understanding of the pathogenesis of osteoporosis and developing better diagnosis, prevention and treatment strategies.