Multiple Functional Variants at 13q14 Risk Locus for Osteoporosis Regulate RANKL Expression Through Long-Range Super-Enhancer

New insights into dairy management and the prevention and treatment of osteoporosis: The shift from single nutrient to dairy matrix effects-A review

Dairy is recognized as a good source of calcium, which is important for preventing osteoporosis. However, the relationship between milk and bone health is more complex than just calcium supplementation. It is unwise to focus solely on observing the effects of a single nutrient. Lactose, proteins, and vitamins in milk, as well as fatty acids, oligosaccharides, and exosomes, all work together with calcium to enhance its bioavailability and utilization efficiency through various mechanisms. We evaluate the roles of dairy nutrients and active ingredients in maintaining bone homeostasis from the perspective of the dairy matrix effects. Special attention is given to threshold effects, synergistic effects, and associations with the gut-bone axis. We also summarize the associations between probiotic/prebiotic milk, low-fat/high-fat milk, lactose-free milk, and fortified milk with a reduced risk of osteoporosis and discuss the potential benefits and controversies of these dairy products. Moreover, we examine the role of dairy products in increasing peak bone mass during adolescence and reducing bone loss in old age. It provides a theoretical reference for the use of dairy products in the accurate prevention and management of osteoporosis and related chronic diseases and offers personalized dietary recommendations for bone health in different populations.

Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis

The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.

The osteoporosis susceptibility SNP rs188303909 at 2q14.2 regulates EN1 expression by modulating DNA methylation and E2F6 binding

EN1 encodes a homeodomain-containing transcription factor and is a determinant of bone density and fracture. Previous powerful genome-wide association studies (GWASs) have identified multiple single-nucleotide polymorphisms (SNPs) near EN1 at 2q14.2 locus for osteoporosis, but the causal SNPs and functional mechanisms underlying these associations are poorly understood. The target genes regulated by the transcription factor EN1 are also unclear. In this study, we identified rs188303909, a functional CpG-SNP, as a causal SNP for osteoporosis at 2q14.2 through the integration of functional and epigenomic analyses. Functional experiments demonstrated that unmethylated rs188303909 acted as a strong allele-specific distal enhancer to regulate EN1 expression by modifying the binding of transcription factor E2F6, but rs188303909 methylation attenuated the active effect of E2F6 on EN1 expression. Importantly, transcription factor EN1 could differentially bind osteoporosis GWAS lead SNPs rs4869739-T and rs4355801-G to upregulate CCDC170 and COLEC10 expression, thus promoting bone formation. Our study provided a mechanistic insight into expression regulation of the osteoporosis susceptibility gene EN1, which could be a potential therapeutic target for osteoporosis precision medicine. KEY MESSAGES: CpG-SNP rs188303909 is a causal SNP at the osteoporosis susceptibility locus 2q14.2. Rs188303909 distally regulates EN1 expression by modulating DNA methylation and E2F6 binding. EN1 upregulates CCDC170 and COLEC10 expression through osteoporosis GWAS lead SNPs rs4869739 and rs4355801.

Utilizing Human Genetics to Develop Chemoprevention for Cancer-Too Good an Opportunity to be Missed

Large-scale genetic studies are reliably identifying many risk factors for disease in the general population. Several of these genetic risk factors encode potential drug targets, and genetics has already helped to introduce targeted agents for some diseases, an example being lipid-lowering drugs to reduce the incidence of cardiovascular disease. Multiple drugs have been developed to treat cancers based on somatic mutations and genomics, but in stark contrast, there seems to be a reluctance to use germline genetic data to develop drugs to prevent malignancy, despite the large numbers of people who could benefit, the potential for lowering cancer rates, and the widespread current use of non-pharmaceutical measures to reduce cancer risk factors such as tobacco, alcohol, and infectious diseases. We argue that concerted efforts for cancer prevention based on genetics, including genes influenced by common polymorphisms that modulate cancer risk, are urgently needed. There are enormous, yet underutilized, opportunities to develop novel targeted agents for chemoprevention of cancer based on human germline genetics. Such efforts are likely to require the support of a dedicated funding program by national and international agencies. See related commentary by Winham and Sherman, p. 13.

Enhancer variants on chromosome 2p14 regulating SPRED2 and ACTR2 act as a signal amplifier to protect against rheumatoid arthritis

Genome-wide association studies (GWASs) have repeatedly reported multiple non-coding single-nucleotide polymorphisms (SNPs) at 2p14 associated with rheumatoid arthritis (RA), but their functional roles in the pathological mechanisms of RA remain to be explored. In this study, we integrated a series of bioinformatics and functional experiments and identified three intronic RA SNPs (rs1876518, rs268131, and rs2576923) within active enhancers that can regulate the expression of SPRED2 directly. At the same time, SPRED2 and ACTR2 influence each other as a positive feedback signal amplifier to strengthen the protective role in RA by inhibiting the migration and invasion of rheumatoid fibroblast-like synoviocytes (FLSs). In particular, the transcription factor CEBPB preferentially binds to the rs1876518-T allele to increase the expression of SPRED2 in FLSs. Our findings decipher the molecular mechanisms behind the GWAS signals at 2p14 for RA and emphasize SPRED2 as a potential candidate gene for RA, providing a potential target and direction for precise treatment of RA.

Factors associated with bone thickness: Comparison of the cranium and humerus

Cortical bone thickness is important for the mechanical function of bone. Ontogeny, aging, sex, body size, hormone levels, diet, behavior, and genetics potentially cause variations in postcranial cortical robusticity. However, the factors associated with cranial cortical robusticity remain poorly understood. Few studies have examined cortical robusticity in both cranial and postcranial bones jointly. In the present study, we used computed tomography (CT) images to measure cortical bone thicknesses in the cranial vault and humeral diaphysis. This study clearly showed that females have a greater cranial vault thickness and greater age-related increase in cranial vault thickness than males. We found an age-related increase in the full thickness of the temporal cranial vault and the width of the humeral diaphysis, as well as an age-related decrease in the cortical thickness of the frontal cranial vault and the cortical thickness of the humeral diaphysis, suggesting that the mechanisms of bone modeling in cranial and long bones are similar. A positive correlation between cortical indices in the cranial vault and humeral diaphysis also suggested that common factors affect cortical robusticity. We also examined the association of polymorphisms in the WNT16 and TNFSF11 genes with bone thickness. However, no significant associations were observed. The present study provides fundamental knowledge about similarities and differences in the mechanisms of bone modeling between cranial and postcranial bones.

An Osteoporosis Susceptibility Allele at 11p15 Regulates SOX6 Expression by Modulating TCF4 Chromatin Binding

Osteoporosis is an age-related complex disease clinically diagnosed with bone mineral density (BMD). Although several genomewide association studies (GWASs) have discovered multiple noncoding genetic variants at 11p15 influencing osteoporosis risk, the functional mechanisms of these variants remain unknown. Through integrating bioinformatics and functional experiments, a potential functional single-nucleotide polymorphism (SNP; rs1440702) located in an enhancer element was identified and the A allele of rs1440702 acted as an allelic specificities enhancer to increase its distal target gene SOX6 (~600 Kb upstream) expression, which plays a key role in bone formation. We also validated this long-range regulation via conducting chromosome conformation capture (3C) assay. Furthermore, we demonstrated that SNP rs1440702 with a risk allele (rs1440702-A) could increase the activity of the enhancer element by altering the binding affinity of the transcription factor TCF4, resulting in the upregulation expression of SOX6 gene. Collectively, our integrated analyses revealed how the noncoding genetic variants (rs1440702) affect osteoporosis predisposition via long-range gene regulatory mechanisms and identified its target gene SOX6 for downstream biomarker and drug development. © 2022 American Society for Bone and Mineral Research (ASBMR).

Functional genomic analysis delineates regulatory mechanisms of GWAS-identified bipolar disorder risk variants

Background

Genome-wide association studies (GWASs) have identified multiple risk loci for bipolar disorder (BD). However, pinpointing functional (or causal) variants in the reported risk loci and elucidating their regulatory mechanisms remain challenging.

Methods

We first integrated chromatin immunoprecipitation sequencing (ChIP-Seq) data from human brain tissues (or neuronal cell lines) and position weight matrix (PWM) data to identify functional single-nucleotide polymorphisms (SNPs). Then, we verified the regulatory effects of these transcription factor (TF) binding–disrupting SNPs (hereafter referred to as “functional SNPs”) through a series of experiments, including reporter gene assays, allele-specific expression (ASE) analysis, TF knockdown, CRISPR/Cas9-mediated genome editing, and expression quantitative trait loci (eQTL) analysis. Finally, we overexpressed PACS1 (whose expression was most significantly associated with the identified functional SNPs rs10896081 and rs3862386) in mouse primary cortical neurons to investigate if PACS1 affects dendritic spine density.

Results

We identified 16 functional SNPs (in 9 risk loci); these functional SNPs disrupted the binding of 7 TFs, for example, CTCF and REST binding was frequently disrupted. We then identified the potential target genes whose expression in the human brain was regulated by these functional SNPs through eQTL analysis. Of note, we showed dysregulation of some target genes of the identified TF binding–disrupting SNPs in BD patients compared with controls, and overexpression of PACS1 reduced the density of dendritic spines, revealing the possible biological mechanisms of these functional SNPs in BD.

Conclusions

Our study identifies functional SNPs in some reported risk loci and sheds light on the regulatory mechanisms of BD risk variants. Further functional characterization and mechanistic studies of these functional SNPs and candidate genes will help to elucidate BD pathogenesis and develop new therapeutic approaches and drugs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01057-3.

Functional Characterization of Genetic Variant Effects on Expression

Thousands of common genetic variants in the human population have been associated with disease risk and phenotypic variation by genome-wide association studies (GWAS). However, the majority of GWAS variants fall into noncoding regions of the genome, complicating our understanding of their regulatory functions, and few molecular mechanisms of GWAS variant effects have been clearly elucidated. Here, we set out to review genetic variant effects, focusing on expression quantitative trait loci (eQTLs), including their utility in interpreting GWAS variant mechanisms. We discuss the interrelated challenges and opportunities for eQTL analysis, covering determining causal variants, elucidating molecular mechanisms of action, and understanding context variability. Addressing these questions can enable better functional characterization of disease-associated loci and provide insights into fundamental biological questions of the noncoding genetic regulatory code and its control of gene expression. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

The osteoporosis risk variant rs9820407 at 3p22.1 acts as an allele-specific enhancer to regulate CTNNB1 expression by long-range chromatin loop formation

Previous powerful genome-wide association studies (GWASs) and whole-genome sequencing have identified multiple single-nucleotide polymorphisms (SNPs) located over 69 kb upstream of CTNNB1 at 3p22.1 locus associated with osteoporosis. The CTNNB1 gene encodes β-catenin that is an integral part of adherens junctions and the primary mediator of the canonical Wnt signaling pathway. The causal variants and underlying molecular mechanisms of the osteoporosis susceptibility locus 3p22.1 remains unknown. Through comprehensive computational analyses, including expression quantitative trait locus (eQTL), high-throughput chromatin interaction (Hi-C), epigenomic and functional annotation, four enhancer SNPs (rs9820407, rs9878224, rs454690 and rs9832204) were prioritized as potential causal SNPs at 3p22.1 for osteoporosis. Rs9820407 displayed the strongest enhancer activity in dual-luciferase assays. Specifically, the minor rs9820407-A can preferentially bind transcription factor FOXC1, elevate the enhancer activity and increase CTNNB1 expression. The architectural protein CTCF was presumably involved in long-range chromatin interaction between rs9820407 and CTNNB1. Our study provided a mechanistic insight into how noncoding enhancer SNP rs9820407 distally regulates CTNNB1 expression and modulates osteoporosis risk.

Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and Animal-Modeling Techniques

The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits ("endophenotypes"), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.

Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C

Eukaryotic genomes are highly organised within the nucleus of a cell, allowing widely dispersed regulatory elements such as enhancers to interact with gene promoters through physical contacts in three-dimensional space. Recent chromosome conformation capture methodologies such as Hi-C have enabled the analysis of interacting regions of the genome providing a valuable insight into the three-dimensional organisation of the chromatin in the nucleus, including chromosome compartmentalisation and gene expression. Complicating the analysis of Hi-C data, however, is the massive amount of identified interactions, many of which do not directly drive gene function, thus hindering the identification of potentially biologically functional 3D interactions. In this review, we collate and examine the downstream analysis of Hi-C data with particular focus on methods that prioritise potentially functional interactions. We classify three groups of approaches: structural-based discovery methods, e.g. A/B compartments and topologically associated domains, detection of statistically significant chromatin interactions, and the use of epigenomic data integration to narrow down useful interaction information. Careful use of these three approaches is crucial to successfully identifying potentially functional interactions within the genome.

Combining artificial intelligence: deep learning with Hi-C data to predict the functional effects of non-coding variants

MOTIVATION

Although genome-wide association studies (GWASs) have identified thousands of variants for various traits, the causal variants and the mechanisms underlying the significant loci are largely unknown. In this study, we aim to predict non-coding variants that may functionally affect translation initiation through long-range chromatin interaction.

RESULTS

By incorporating the Hi-C data, we propose a novel and powerful deep learning model of artificial intelligence to classify interacting and non-interacting fragment pairs and predict the functional effects of sequence alteration of single nucleotide on chromatin interaction and thus on gene expression. The changes in chromatin interaction probability between the reference sequence and the altered sequence reflect the degree of functional impact for the variant. The model was effective and efficient with the classification of interacting and non-interacting fragment pairs. The predicted causal SNPs that had a larger impact on chromatin interaction were more likely to be identified by GWAS and eQTL analyses. We demonstrate that an integrative approach combining artificial intelligence-deep learning with high throughput experimental evidence of chromatin interaction leads to prioritizing the functional variants in disease- and phenotype-related loci and thus will greatly expedite uncover of the biological mechanism underlying the association identified in genomic studies.

AVAILABILITY AND IMPLEMENTATION

Source code used in data preparing and model training is available at the GitHub website (https://github.com/biocai/DeepHiC).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Genetic Variants in Transcription Factor Binding Sites in Humans: Triggered by Natural Selection and Triggers of Diseases

Variants of transcription factor binding sites (TFBSs) constitute an important part of the human genome. Current evidence demonstrates close links between nucleotides within TFBSs and gene expression. There are multiple pathways through which genomic sequences located in TFBSs regulate gene expression, and recent genome-wide association studies have shown the biological significance of TFBS variation in human phenotypes. However, numerous challenges remain in the study of TFBS polymorphisms. This article aims to cover the current state of understanding as regards the genomic features of TFBSs and TFBS variants; the mechanisms through which TFBS variants regulate gene expression; the approaches to studying the effects of nucleotide changes that create or disrupt TFBSs; the challenges faced in studies of TFBS sequence variations; the effects of natural selection on collections of TFBSs; in addition to the insights gained from the study of TFBS alleles related to gout, its associated comorbidities (increased body mass index, chronic kidney disease, diabetes, dyslipidemia, coronary artery disease, ischemic heart disease, hypertension, hyperuricemia, osteoporosis, and prostate cancer), and the treatment responses of patients.

Opportunities and Challenges in Functional Genomics Research in Osteoporosis: Report From a Workshop Held by the Causes Working Group of the Osteoporosis and Bone Research Academy of the Royal Osteoporosis Society on October 5th 2020

The discovery that sclerostin is the defective protein underlying the rare heritable bone mass disorder, sclerosteosis, ultimately led to development of anti-sclerostin antibodies as a new treatment for osteoporosis. In the era of large scale GWAS, many additional genetic signals associated with bone mass and related traits have since been reported. However, how best to interrogate these signals in order to identify the underlying gene responsible for these genetic associations, a prerequisite for identifying drug targets for further treatments, remains a challenge. The resources available for supporting functional genomics research continues to expand, exemplified by "multi-omics" database resources, with improved availability of datasets derived from bone tissues. These databases provide information about potential molecular mediators such as mRNA expression, protein expression, and DNA methylation levels, which can be interrogated to map genetic signals to specific genes based on identification of causal pathways between the genetic signal and the phenotype being studied. Functional evaluation of potential causative genes has been facilitated by characterization of the "osteocyte signature", by broad phenotyping of knockout mice with deletions of over 7,000 genes, in which more detailed skeletal phenotyping is currently being undertaken, and by development of zebrafish as a highly efficient additional in vivo model for functional studies of the skeleton. Looking to the future, this expanding repertoire of tools offers the hope of accurately defining the major genetic signals which contribute to osteoporosis. This may in turn lead to the identification of additional therapeutic targets, and ultimately new treatments for osteoporosis.

lncRNA Neat1 Stimulates Osteoclastogenesis Via Sponging miR-7

Increasing evidence uncover the essential role of long noncoding RNA (lncRNAs) in bone metabolism and the association of lncRNA with genetic risk of osteoporosis. However, whether lncRNA nuclear paraspeckle assembly transcript 1 (Neat1) is involved remains largely unknown. In the present study, we found that Neat1 is induced by osteoclastic differentiation stimuli. Knockdown of Neat1 attenuates osteoclast formation whereas overexpression of Neat1 accelerates osteoclast formation. In vivo evidence showed that enhanced Neat1 expression stimulates osteoclastogenesis and reduces bone mass in mice. Mechanically, Neat1 competitively binds with microRNA 7 (miR-7) and blocks its function for regulating protein tyrosine kinase 2 (PTK2). Intergenic SNP rs12789028 acts as allele-specific long-range enhancer for NEAT1 via chromatin interactions. We establish for the first time that Neat1 plays an essential role in osteoclast differentiation, and provide genetic mechanism underlying the association of NEAT1 locus with osteoporosis risk. These results enrich the current knowledge of NEAT1 function, and uncover the potential of NEAT1 as a therapeutic target for osteoporosis. © 2020 American Society for Bone and Mineral Research.

Analysis of the tumor necrosis factor superfamily member 11 gene polymorphism with bone mineral density and bone fracture frequency in patients with postmenopausal osteoporosis

PURPOSE

We aimed to examine the polymorphism of the promoter and exon 5 of the TNFSF11 gene and their impact on bone mineral density (BMD) and the frequency of bone fractures. TNFSF11 encodes the receptor activator of the NF-kB ligand (RANKL), a key regulator of bone metabolism and osteoporosis drug targets. BMD is an essential measure in diagnosing osteoporosis and assessing the risk of fractures. In vivo, RANKL expression research suggests that promoter TNFSF11 variants influence BMD. Moreover, exon 5 polymorphism of a linear epitope sequence for a denosumab could be related to the effectiveness of biological therapy.

PATIENTS AND METHODS

The study included 114 postmenopausal osteoporosis patients. BMD was measured in the lumbar spine and the femoral neck. Genetic analysis was performed using Sanger sequencing. Genotypes data for 263 female European population group were obtained from the 1000Genomes database.

RESULTS

We identified six promoter polymorphisms (rs9525641, rs9533155, rs9533156, rs11839112, rs28926171, rs183599708) and one silent TNFSF11 variant in exon 5 (rs9562415). Three of the sequence variants detected (rs9525641, rs9533155, rs9533156) proved to be polymorphic, whereas the others four occurred at a frequency below 2%. The statistical analysis demonstrated no significant differences between polymorphisms and BMD, and bone fractures. However, variant rs9533156 was relevant with the lumbar spine T-score (p = 0.0273), and no association with BMD was of borderline significance (p = 0.0529).

CONCLUSIONS

Variant rs9533156 may contribute to the genetic regulation of BMD in Polish postmenopausal osteoporosis, while the exon 5 sequence of the TNFSF11 gene is very conservative.

Identifying Pleiotropic SNPs Associated With Femoral Neck and Heel Bone Mineral Density

Background

Genome-wide association studies (GWASs) routinely identify loci associated with risk factors for osteoporosis. However, GWASs with relatively small sample sizes still lack sufficient power to ascertain the majority of genetic variants with small to modest effect size, which may together truly influence the phenotype. The loci identified only account for a small percentage of the heritability of osteoporosis. This study aims to identify novel genetic loci associated with DXA-derived femoral neck (FNK) bone mineral density (BMD) and quantitative ultrasound of the heel calcaneus estimated BMD (eBMD), and to detect shared/causal variants for the two traits, to assess whether the SNPs or putative causal SNPs associated with eBMD were also associated with FNK-BMD.

Methods

Novel loci associated with eBMD and FNK-BMD were identified by the genetic pleiotropic conditional false discovery rate (cFDR) method. Shared putative causal variants between eBMD and FNK-BMD and putative causal SNPs for each trait were identified by the colocalization method. Mendelian randomization analysis addresses the causal relationship between eBMD/FNK-BMD and fracture.

Results

We identified 9,500 (cFDR < 9.8E-6), 137 (cFDR < 8.9E-4) and 124 SNPs associated with eBMD, FNK-BMD, and both eBMD and FNK-BMD, respectively, with 37 genomic regions where there was a SNP that influences both eBMD and FNK-BMD. Most genomic regions only contained putative causal SNPs associated with eBMD and 3 regions contained two distinct putative causal SNPs influenced both traits, respectively. We demonstrated a causal effect of FNK-BMD/eBMD on fracture.

Conclusion

Most of SNPs or putative causal SNPs associated with FNK-BMD were also associated with eBMD. However, most of SNPs or putative causal SNPs associated with eBMD were not associated with FNK-BMD. The novel variants we identified may help to account for the additional proportion of variance of each trait and advance our understanding of the genetic mechanisms underlying osteoporotic fracture.

Functions and Clinical Significance of Super-Enhancers in Bone-Related Diseases

Super-enhancers (SEs) are a large cluster of cis-regulatory DNA elements that contain many binding motifs, which master transcription factors and cofactors bind to with high density. SEs usually regulate the expression of genes that can control the cell identity and fate, and SEs can be used to explain the patterns of the expression of cell-specific genes. Hence, it shows great potential for application in the treatment of diseases like cancer. At present, the clinical treatments for osteosarcoma, Ewing sarcoma, and other bone-related diseases remain challenging. The poor prognosis and difficult treatment of these diseases imposes heavy economic burden on patients and society. In recent years, research on SEs with respect to bone-related diseases has attracted increasing attention. In this paper, we first review the identification and functional mechanisms of SEs. Then, we integrate the findings of the emerging studies on SEs in bone-related diseases. Finally, we summarize recent strategies for targeting SEs for the treatment of bone-related diseases. This review aims to provide comprehensive insights into the roles of SEs in bone-related diseases.

Targeting complexes of super-enhancers is a promising strategy for cancer therapy

The hyperactivation and overexpression of critical oncogenes is a common occurrence in multiple types of malignant tumors. Recently, the abnormal activation mechanism of an oncogene by a super-enhancer (SE) has attracted significant attention. A series of changes (insertion, deletion, translocation and rearrangement) in the genome occurring in cancer cells may generate new SEs, leading to the overexpression of SE-driven oncogenes. SEs are composed of typical enhancers densely loaded with mediator complexes, transcription factors, and chromatin regulators, and drive the overexpression of oncogenes associated with cellular identity and disease. Cyclin-dependent kinase 7 (CDK7) and bromodomain protein 4 (BRD4) are critical mediator complexes associated with SE-mediated transcription. Clinical trials have shown that emerging small-molecule inhibitors (CDK7 and BRD4 inhibitor), targeting the SE exert a notable effect on cancer treatment. Increasing evidences has illustrated that the SE and its associated complexes play a critical role in the development of various types of cancer. The present review discusses the composition, function and regulation of SEs and their contribution to oncogenic transcription. In addition, creative therapeutic approaches that target SE, their advantages and disadvantages, as well as the problems with their clinical application are discussed. It was found that targeting SE may be used in conventional treatment and establish more access for patients with cancer.

Gene-gene and gene-lifestyle interactions of AKAP11, KCNMA1, PUM1, SPTBN1, and EPDR1 on osteoporosis risk in middle-aged adults

OBJECTIVES

Osteoporosis is associated with genetic and environmental factors. The aim of this article was to determine how the polygenic risk scores (PRS) of genetic variants that affect osteoporosis and its related signaling interact with the lifestyle of middle-aged adults.

METHODS

The study examined 8845 participants from Ansan/Ansung cohorts. Osteoporosis was defined as a T-score of bone mineral density ≤-2.5 in either the wrist or tibia; 1136 participants had osteoporosis. Genome-wide association studies of individuals 40 to 65 y of age were conducted and the best gene-gene interactions from the genetic variants related to osteoporosis were selected and explored using the generalized multifactor dimensionality reduction method. PRS for the best model (PRSBM) was calculated by weighted PRS that was divided into low, medium, and high groups.

RESULTS

The model that contributed the most influence on osteoporosis risk with gene-gene interactions included AKAP11_rs238340, KCNMA1_ rs628948, PUM1_rs7529390, SPTBN1_ rs6752877, and EPDR1_rs2722298. The risk for osteoporosis in the tibia was elevated by 1.71-fold in the high PRSBM group compared with the low PRSBM group. Energy and nutrient intake did not have any interaction with PRSBM and thus did not influence risk for osteoporosis. However, interestingly, only coffee and caffeine intake did interact with PRSBM and affected risk for osteoporosis. In patients with low coffee (<3 cup/wk) and caffeine(<60 mg/d) consumption, osteoporosis risk was higher in the high PRSBM group than the low PRSBM group by 2.27- and 2.29-fold, respectively. In the low coffee intake group, bone mineral density in the high PRSBM group was significantly higher than in the low PRSBM arm.

CONCLUSIONS

Carriers with high PRSBM increased susceptibility to osteoporosis, especially in low coffee and caffeine intake. The results can be applied to personalized nutrition for lowering the risk for osteoporosis.

Deciphering Sex-Specific Genetic Architectures Using Local Bayesian Regressions

Many complex human traits exhibit differences between sexes. While numerous factors likely contribute to this phenomenon, growing evidence from genome-wide studies suggest a partial explanation: that males and females from the same population possess differing genetic architectures. Despite this, mapping gene-by-sex (G×S) interactions remains a challenge likely because the magnitude of such an interaction is typically and exceedingly small; traditional genome-wide association techniques may be underpowered to detect such events, due partly to the burden of multiple test correction. Here, we developed a local Bayesian regression (LBR) method to estimate sex-specific SNP marker effects after fully accounting for local linkage-disequilibrium (LD) patterns. This enabled us to infer sex-specific effects and G×S interactions either at the single SNP level, or by aggregating the effects of multiple SNPs to make inferences at the level of small LD-based regions. Using simulations in which there was imperfect LD between SNPs and causal variants, we showed that aggregating sex-specific marker effects with LBR provides improved power and resolution to detect G×S interactions over traditional single-SNP-based tests. When using LBR to analyze traits from the UK Biobank, we detected a relatively large G×S interaction impacting bone mineral density within ABO, and replicated many previously detected large-magnitude G×S interactions impacting waist-to-hip ratio. We also discovered many new G×S interactions impacting such traits as height and body mass index (BMI) within regions of the genome where both male- and female-specific effects explain a small proportion of phenotypic variance (R2 < 1 × 10-4), but are enriched in known expression quantitative trait loci.

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.

Management of Osteoporosis in Survivors of Adult Cancers With Nonmetastatic Disease: ASCO Clinical Practice Guideline

PURPOSE

The aim of this work is to provide evidence-based guidance on the management of osteoporosis in survivors of adult cancer.

METHODS

ASCO convened a multidisciplinary Expert Panel to develop guideline recommendations based on a systematic review of the literature.

RESULTS

The literature search of the 2018 systematic review by the US Preventive Services Task Force in the noncancer population was used as the evidentiary base upon which the Expert Panel based many of its recommendations. A total of 61 additional studies on topics and populations not covered in the US Preventive Services Task Force review were also included. Patients with cancer with metastatic disease and cancer survival outcomes related to bone-modifying agents are not included in this guideline.

RECOMMENDATIONS

Patients with nonmetastatic cancer may be at risk for osteoporotic fractures due to baseline risks or due to the added risks that are associated with their cancer therapy. Clinicians are advised to assess fracture risk using established tools. For those patients with substantial risk of osteoporotic fracture, the clinician should obtain a bone mineral density test. The bone health of all patients may benefit from optimizing nutrition, exercise, and lifestyle. When a pharmacologic agent is indicated, bisphosphonates or denosumab at osteoporosis-indicated dosages are the preferred interventions.

The SNP of rs6854845 suppresses transcription via the DNA looping structure alteration of super-enhancer in colon cells

Single-nucleotide polymorphisms (SNPs) identified by Genome-Wide Association Studies (GWASs) have been determined to closely connect with multiple diseases. Previous studies revealed one underlying mechanism that SNPs located within the regulatory elements could affect the encoding gene expression through long-range regulation. SNP rs6854845 was suggested to be a risk of colon cancer in human population. Nevertheless, the underlying molecular mechanism for colon carcinogenesis remains largely unknown. In present study, rs6854845 with G > T mutation in situ in FHC, HCT-116 and SW-480 cells were generated by Crispr/Cas9. The nearby chromatin organization was investigated by chromatin conformation capture (3C). And the expression of coding gene regulated by super-enhancer (SE) was detected by real-time PCR. We observed a significantly different pattern of the genome organization upon rs6854845 generation in colon epithelial cells but not in colon cancer cells. Moreover, we observed the shifted enrichment of H3K4me1 and H3K27ac at the SE (chr4:75.7M-76.0 M) where rs6854845 located. Furthermore, we observed that the transcription of the gene clusters regulated by SE were affected by rs6854845 in colon cells. Overall, our results demonstrated that SNP rs6854845 located in SE could destroy the long-range chromosomal interaction between SE and target gene clusters thereby affecting the transcription of these genes.

Analysis of Transcriptional Regulation in Bone Cells

Transcription is a process by which the rate of RNA synthesis is regulated. Here we describe the techniques for carrying out promoter-reporter assays, electrophoretic mobility shift assays, chromosome conformation capture (3C) assays, chromatin immunoprecipitation assays, and CRISPR-Cas9 assay, five commonly used methods for studying and altering gene transcription.

The effect of CTCF binding sites destruction by CRISPR/Cas9 on transcription of metallothionein gene family in liver hepatocellular carcinoma

Chromatin spatial organization is essential for transcriptional modulation and stabilization. The pattern of DNA distal interplay form the multiple topological associating domains (TADs), and further assemble the functional compartmentalization with open and expression-active chromatin ("A" compartments) or closed and expression-inactive chromatin ("B" compartments) in genome, whose boundaries were defined by the high enrichment of CCCTC-binding factor (CTCF). Nevertheless, As a potential therapeutic strategy, changing the local chromatin architecture via adding or removing the CTCF binding sites in situ to regulate the transcription activity of genes within one TAD in cancer cells is poorly explored. In present study, we observed that the metallothionein (MT) family were all remarkably decreased in HCC of TCGA database, and MT genes family were located within a TAD of 1.2 Mb at 16q13 in order, and CTCF binding sites were distributed at the both sites of MT gene clusters. Furthermore, CRISPR/Cas9 was employed to destroy the CTCF binding sites at the vicinity of the MT family in human liver hepatocellular carcinoma (HCC) cell lines Huh-7 and HepG2. And the presence of up-regulated transcription of MTs were observed in Huh-7 and HepG2 cells compared to normal liver CRL-12461 cells. Moreover, the presence of the varying DNA interplay as well as H3K4me3 and H3K9me3 modification on different MT genes were observed after CTCF binding domain destruction compared to the control using chromosome conformation capture (3C) and chromatin immunoprecipitation (ChIP). Our results determined a potential way to regulate the transcription of a series of genes via changing the local genomic organization for diseases treatment.

Dissecting the Genetics of Osteoporosis using Systems Approaches

Osteoporosis is a condition characterized by low bone mineral density (BMD) and an increased risk of fracture. Traits contributing to osteoporotic fracture are highly heritable, indicating that a comprehensive understanding of bone requires a thorough understanding of the genetic basis of bone traits. Towards this goal, genome-wide association studies (GWASs) have identified over 500 loci associated with bone traits. However, few of the responsible genes have been identified, and little is known of how these genes work together to influence systems-level bone function. In this review, we describe how systems genetics approaches can be used to fill these knowledge gaps.

What's in the "fold"?

Complexity in genome architecture determines how gene expression programs are established, maintained, and modified from early developmental stages to normal adult phenotypes. Large scale and hierarchical organization of the genome impacts various aspects of cell functions, ranging from X-chromosome inactivation, stem-cell fate determination to transcription, DNA replication, and cellular repair. While chromatin loops and topologically-associated domains represent a basic structural or fundamental unit of chromatin organization, spatio-temporal organization of the genome further creates a complex network of interacting genome patterns, forming chromosomal compartments and chromosome territories. The understanding of human diseases, including cancers, auto-immune disorders, Alzheimer's, and cardiovascular diseases, relies on the associated molecular and epigenetic mechanisms. There is a growing interest in the impact of three-dimensional chromatin folding upon the genome structure and function, which gives rise to the question "What's in the fold?" and is the main focus of this review. Here we discuss the principles determining the spatial and regulatory relationships between gene regulation and three-dimensional chromatin landscapes, and how changes in chromatin-folding could influence the outcome of genome function in healthy and disease states.

VDR and TNFSF11 polymorphisms are associated with osteoporosis in Thai patients

Determining molecular markers for osteoporosis may be valuable for improving the quality of life of affected elderly patients by aiding in early detection and disease management. In the present study, the association between single nucleotide polymorphisms (SNPs) of the vitamin D receptor (VDR) and tumour necrosis factor superfamily number 11 (TNFSF11) genes and the susceptibility of developing osteoporosis was investigated in a Thai female cohort. The study group consisted of 105 Thai postmenopausal patients diagnosed with osteoporosis and 132 healthy Thai postmenopausal female volunteers. DNA extracted from blood samples was used to genotype the VDR and TNFSF11 genes using polymerase chain reaction-restriction fragment length polymorphism and sequencing analysis. For VDR, the frequencies of the genotypes TT, CT and CC for the TaqI SNP (rs731236) were 87.88, 11.36 and 0.76%, respectively, in the control group, while in the osteoporosis cohort were 92.38, 5.71 and 1.91%, respectively. For the FokI SNP (rs2228570), the frequencies of the genotypes CC, CT and TT were 31.06, 55.30 and 13.64%, respectively, in the control group, and in the osteoporosis group were 29.52, 43.81 and 26.67%, respectively. For BsmI SNP (rs1544410), the frequencies of the genotypes GG, GA and AA were 78.03, 18.94 and 3.03%, respectively, in control group, and in the osteoporosis group were 80.95, 18.10 and 0.95%, respectively. The significant risk of osteoporosis associated with the FokI SNP was determined. The odds ratio (95% confidence interval) was 2.30 (1.14-4.69; P=0.01) among patients with osteoporosis with TT as the susceptibility genotype. For TNFSF11, the frequencies of the genotypes TT, CT and CC for the -290C>T SNP (rs9525641) in the control group were 36.36, 50.76 and 12.88%, respectively, while in the osteoporosis group were 31.43, 56.19 and 12.38%, respectively. For the -643C>T SNP (rs9533156), the frequencies of the genotypes TT, CT and CC in the control group were 35.61, 48.48 and 15.91%, respectively, while in the osteoporosis group were 32.38, 55.24 and 12.38%, respectively. For the -693G>C SNP (rs9533155), the frequencies of the genotypes CC, CG, and GG in the control group were 39.39, 46.97 and 13.64%, respectively, and in the osteoporosis group were 36.19, 53.33 and 10.48%, respectively. No significant associations of the TNFSF11 SNPs with osteoporosis were determined; however, it was notable that the GCT haplotype of TNFSF11 may be a protective haplotype for osteoporosis. Therefore, it was concluded that the SNP FokI of VDR may be a potential molecular biomarker for the development of osteoporosis in Thai females.