Proteins and pathways involved in inflammation are longitudinally associated with total body bone mineral density among primarily Hispanic overweight/obese adolescents and young adults

BMD, an important marker of bone health, is regulated by a complex interaction of proteins. Plasma proteomic analyses can contribute to identification of proteins associated with changes in BMD. This may be especially informative in stages of bone accrual and peak BMD achievement (ie, adolescence and young adulthood), but existing research has focused on older adults. This analysis in the Study of Latino Adolescents at Risk for Type 2 Diabetes (SOLAR; n = 304; baseline age 8-13, 100% Hispanic) explored associations between baseline proteins (n = 653 proteins) measured with Olink plasma protein profiling and repeated annual DXA measures of BMD (average of 3.2 visits per participant). Covariate-adjusted linear mixed effect regression models were applied to estimate longitudinal protein-BMD associations using an adjusted p value cutoff (p < .00068). Identified proteins were imported into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database to determine significantly enriched protein pathways. Forty-four proteins, many of which are involved in inflammatory processes, were associated with longitudinal changes in total body BMD, including several proteins previously linked to bone health such as osteopontin (SPP1) and microfibrillar-associated protein 5 (MFAP5; both p < .00068). These 44 proteins were associated with enrichment of pathways including PI3K-Akt signaling pathway and cytokine-cytokine receptor interaction, supporting results from existing proteomics analyses in older adults. To evaluate whether protein associations were consistent into young adulthood, linear mixed effect models were repeated in a young adult cohort (n = 169; baseline age 17-22; 62.1% Hispanic) with 346 available overlapping Olink protein measures. While there were no significant overlapping longitudinal protein associations between the cohorts, these findings suggest differences in protein regulation at different ages and provide novel insight on longitudinal protein associations with BMD in overweight/obese adolescents and young adults of primarily Hispanic origin, which may inform the development of biomarkers for bone health in youth.

An updated overview of the search for biomarkers of osteoporosis based on human proteomics

Osteoporosis is a chronic metabolic disease that increases bone fragility and, leads to severe osteoporotic fractures. In recent years, the use of high-throughput omics to explore physiological and pathological biomarkers related to bone metabolism has gained popularity. In this review, we first briefly review the technical approaches of proteomics. Additionally, we summarize the relevant literature in the last decade to provide a comprehensive overview of advances in human proteomics related to osteoporosis. We describe the specific roles of various proteins related to human bone metabolism, highlighting their potential as biomarkers for risk assessment, early diagnosis and disease course monitoring in osteoporosis. Finally, we outline the main challenges currently faced by human proteomics in the field of osteoporosis and offer suggestions to address these challenges, to inspire the search for novel osteoporosis biomarkers and a foundation for their clinical translation. In conclusion, proteomics is a powerful tool for discovering osteoporosis-related biomarkers, which can not only provide risk assessment, early diagnosis and disease course monitoring, but also reveal the underlying mechanisms of disease and provide key information for personalized treatment.

The translational potential of this article

This review provides an insightful summary of recent human-based studies on osteoporosis-associated proteomics, which can aid the search for novel osteoporosis biomarkers based on human proteomics and the clinical translation of research results.

IMPC-based screening revealed that ROBO1 can regulate osteoporosis by inhibiting osteogenic differentiation

Introduction

The utilization of denosumab in treating osteoporosis highlights promising prospects for osteoporosis intervention guided by gene targets. While omics-based research into osteoporosis pathogenesis yields a plethora of potential gene targets for clinical transformation, identifying effective gene targets has posed challenges.

Methods

We first queried the omics data of osteoporosis clinical samples on PubMed, used International Mouse Phenotyping Consortium (IMPC) to screen differentially expressed genes, and conducted preliminary functional verification of candidate genes in human Saos2 cells through osteogenic differentiation and mineralization experiments. We then selected the candidate genes with the most significant effects on osteogenic differentiation and further verified the osteogenic differentiation and mineralization functions in mouse 3T3-E1 and bone marrow mesenchymal stem cells (BMSC). Finally, we used RNA-seq to explore the regulation of osteogenesis by the target gene.

Results

We identified PPP2R2A, RRBP1, HSPB6, SLC22A15, ADAMTS4, ATP8B1, CTNNB1, ROBO1, and EFR3B, which may contribute to osteoporosis. ROBO1 was the most significant regulator of osteogenesis in both human and mouse osteoblast. The inhibitory effect of Robo1 knockdown on osteogenic differentiation may be related to the activation of inflammatory signaling pathways.

Conclusion

Our study provides several novel molecular mechanisms involved in the pathogenesis of osteoporosis. ROBO1 is a potential target for osteoporosis intervention.

Navigating the Proteomic Landscape of Menopause: A Review

Background and Objectives: Proteomics encompasses the exploration of protein composition, regulation, function, and pathways. Its influence spans diverse clinical fields and holds promise in addressing various women's health conditions, including cancers, osteoporosis, and cardiovascular disorders. However, no comprehensive summary of proteomics and menopausal health exists. Our objective was to summarize proteomic profiles associated with diseases and disorders in peri- and postmenopausal women. Materials and Methods: We conducted a comprehensive search of databases including PubMed, Google Scholar, the Cochrane database, Elsevier, and ScienceDirect until 2022. A total of 253 studies were identified, and 41 studies met the inclusion criteria to identify data of interest. These included the study design, disease, and proteomics/proteins of significance, as described by the authors. Results: The 41 studies covered diverse areas, including bone disorders (10 studies), cardiovascular diseases (5 studies), oncological malignancies (10 studies), and various conditions, such as obesity, nonalcoholic liver disease, the effects of hormone replacement therapy, and neurological diseases (16 studies). The results of our study indicate that proteomic profiles correlate with heart disease in peri- and postmenopausal women, with distinct sex differences. Furthermore, proteomic profiles significantly differ between women with and without osteoporosis. Additionally, patients with breast, ovarian, and endometrial cancer exhibit notable variations in proteomic profiles compared to those without these conditions. Conclusions: Proteomics has the potential to enhance risk assessment and disease monitoring in peri- and postmenopausal women. By analyzing unique protein profiles, clinicians can identify individuals with heightened susceptibility to specific diseases or those already affected by established conditions. This review suggests that there is sufficient preliminary data related to proteomics in peri- and postmenopausal women for early identification of cardiovascular disease, osteoporosis, and cancers, disease monitoring, and tailoring individualized therapies. Rigorous validation studies involving large populations are essential before drawing definitive conclusions regarding the clinical applicability of proteomic findings.

Proteomic Biomarkers Associated with Low Bone Mineral Density: A Systematic Review

Osteoporosis is a globally relevant public health issue. Our study aimed to summarize the knowledge on the proteomic biomarkers for low bone mineral density over the last years. We conducted a systematic review following the PRISMA guidelines; the scoured databases were PubMed, Web of Sciences, Scopus, and EBSCO, from inception to 2 June 2023. A total of 610 relevant studies were identified and 33 were assessed for eligibility. Finally, 29 studies met the criteria for this systematic review. The risk of bias was evaluated using the Joanna Briggs Institute Critical Appraisal Checklist tool. From the studies selected, 154 proteins were associated with changes of bone mineral density, from which only 10 were reported in at least two articles. The protein-protein network analysis indicated potential biomarkers involved in the skeletal system, immune system process, regulation of protein metabolic process, regulation of signaling, transport, cellular component assembly, cell differentiation, hemostasis, and extracellular matrix organization. Mass spectrometry-based proteomic profiling has allowed the discovery of new biomarkers with diagnostic potential. However, it is necessary to compare and validate the potential biomarkers in different populations to determine their association with bone metabolism and evaluate their translation to the clinical management of osteoporosis.

Multiomics data integration, limitations, and prospects to reveal the metabolic activity of the coral holobiont

Since their radiation in the Middle Triassic period ∼240 million years ago, stony corals have survived past climate fluctuations and five mass extinctions. Their long-term survival underscores the inherent resilience of corals, particularly when considering the nutrient-poor marine environments in which they have thrived. However, coral bleaching has emerged as a global threat to coral survival, requiring rapid advancements in coral research to understand holobiont stress responses and allow for interventions before extensive bleaching occurs. This review encompasses the potential, as well as the limits, of multiomics data applications when applied to the coral holobiont. Synopses for how different omics tools have been applied to date and their current restrictions are discussed, in addition to ways these restrictions may be overcome, such as recruiting new technology to studies, utilizing novel bioinformatics approaches, and generally integrating omics data. Lastly, this review presents considerations for the design of holobiont multiomics studies to support lab-to-field advancements of coral stress marker monitoring systems. Although much of the bleaching mechanism has eluded investigation to date, multiomic studies have already produced key findings regarding the holobiont's stress response, and have the potential to advance the field further.

The heart-bone connection: relationships between myocardial infarction and osteoporotic fracture

Myocardial infarction (MI) and osteoporotic fracture (Fx) are two of the leading causes of mortality and morbidity worldwide. Although these traumatic injuries are treated as if they are independent, there is epidemiological evidence linking the incidence of Fx and MI, thus raising the question of whether each of these events can actively influence the risk of the other. Atherosclerotic cardiovascular disease and osteoporosis, the chronic conditions leading to MI and Fx, are known to have shared pathoetiology. Furthermore, sustained systemic inflammation after traumas such as MI and Fx has been shown to exacerbate both underlying chronic conditions. However, the effects of MI and Fx outside their own system have not been well studied. The sympathetic nervous system (SNS) and the complement system initiate a systemic response after MI that could lead to subsequent changes in bone remodeling through osteoclasts. Similarly, SNS and complement system activation following fracture could lead to heart tissue damage and exacerbate atherosclerosis. To determine whether damaging bone-heart cross talk may be important comorbidity following Fx or MI, this review details the current understanding of bone loss after MI, cardiovascular damage after Fx, and possible shared underlying mechanisms of these processes.

Proteome-wide profiling reveals dysregulated molecular features and accelerated aging in osteoporosis: A 9.8-year prospective study

The role of circulatory proteomics in osteoporosis is unclear. Proteome-wide profiling holds the potential to offer mechanistic insights into osteoporosis. Serum proteome with 413 proteins was profiled by liquid chromatography-tandem mass spectrometry (LC-MS/MS) at baseline, and the 2nd, and 3rd follow-ups (7704 person-tests) in the prospective Chinese cohorts with 9.8 follow-up years: discovery cohort (n = 1785) and internal validation cohort (n = 1630). Bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry (DXA) at follow-ups 1 through 3 at lumbar spine (LS) and femoral neck (FN). We used the Light Gradient Boosting Machine (LightGBM) to identify the osteoporosis (OP)-related proteomic features. The relationships between serum proteins and BMD in the two cohorts were estimated by linear mixed-effects model (LMM). Meta-analysis was then performed to explore the combined associations. We identified 53 proteins associated with osteoporosis using LightGBM, and a meta-analysis showed that 22 of these proteins illuminated a significant correlation with BMD (p < 0.05). The most common proteins among them were PHLD, SAMP, PEDF, HPTR, APOA1, SHBG, CO6, A2MG, CBPN, RAIN APOD, and THBG. The identified proteins were used to generate the biological age (BA) of bone. Each 1 SD-year increase in KDM-Proage was associated with higher risk of LS-OP (hazard ratio [HR], 1.25; 95% CI, 1.14-1.36, p = 4.96 × 10-06 ), and FN-OP (HR, 1.13; 95% CI, 1.02-1.23, p = 9.71 × 10-03 ). The findings uncovered that the apolipoproteins, zymoproteins, complements, and binding proteins presented new mechanistic insights into osteoporosis. Serum proteomics could be a crucial indicator for evaluating bone aging.

Discovery of novel serum biomarkers for diagnosing and predicting postmenopausal osteoporosis patients by 4D-label free protein omics

We aimed to identify protein biomarkers that could rapidly and accurately diagnose osteoporosis patients (OPs) using a highly sensitive proteomic immunoassay. Four-dimensional (4D) label-free proteomics analysis was performed to determine the differentially expressed proteins in serum collected from 10 postmenopausal osteoporosis patients and 6 non-osteoporosis patients. The ELISA method was used to select the predicted proteins for verification. Serum was taken from 36 postmenopausal osteoporosis patients and 36 healthy individuals from normal postmenopausal women. Receiver operating characteristic (ROC) curves were used to determine the diagnostic potential of this method. We validated the expression of these six proteins using ELISA. The CDH1, IGFBP2, and VWF of osteoporosis patients were significantly higher than those of the normal group. PNP was significantly lower than that in the normal group. And using ROC curve calculation, serum CDH1 had a cut-off of 3.78 ng/mL with a sensitivity of 84.4%, and PNP had a cut-off of 944.32 ng/mL with 88.9% sensitivity. These outcomes suggest that serum-level CHD1 and PNP have the potential power as effective indicators for the diagnosis of PMOP. Our results suggest that CHD1 and PNP might be associated with the pathogenesis of OP and would be helpful in diagnosing OP. Therefore, CHD1 and PNP may act as potential key markers in OP.

Research progress on the regulation of bone marrow stem cells by noncoding RNAs in adolescent idiopathic scoliosis

Adolescent idiopathic scoliosis (AIS) is a common spinal deformity in young women, but its pathogenesis remains unclear. The primary pathogenic factors contributing to its development include genetics, abnormal bone metabolism, and endocrine factors. Bone marrow stem cells (BMSCs) play a crucial role in the pathogenesis of AIS by regulating its occurrence and progression. Noncoding RNAs (ncRNAs) are also involved in the pathogenesis of AIS, and their role in regulating BMSCs in patients with AIS requires further evaluation. In this review, we discuss the relevant literature regarding the osteogenic, chondrogenic, and lipogenic differentiation of BMSCs. The corresponding mechanisms of ncRNA-mediated BMSC regulation in patients with AIS, recent advancements in AIS and ncRNA research, and the importance of ncRNA translation profiling and multiomics are highlighted.

Discovery of potential biomarkers for osteoporosis diagnosis by individual omics and multi-omics technologies

INTRODUCTION

Global aging has made osteoporosis an increasingly serious public health problem. Osteoporotic fractures seriously affect the quality of life of patients and increase disability and mortality rates. Early diagnosis is important for timely intervention. The continuous development of individual- and multi-omics methods is helpful for the exploration and discovery of biomarkers for the diagnosis of osteoporosis.

AREAS COVERED

In this review, we first introduce the epidemiological status of osteoporosis and then describe the pathogenesis of osteoporosis. Furthermore, the latest progress in individual- and multi-omics technologies for exploring biomarkers for osteoporosis diagnosis is summarized. Moreover, we clarify the advantages and disadvantages of the application of osteoporosis biomarkers obtained using the omics method. Finally, we put forward valuable views on the future research direction of diagnostic biomarkers of osteoporosis.

EXPERT OPINION

Omics methods undoubtedly provide greatly contribute to the exploration of diagnostic biomarkers of osteoporosis; however, in the future, the clinical validity and clinical utility of the obtained potential biomarkers should be thoroughly examined. In addition, the improvement and optimization of the detection methods for different types of biomarkers and standardization of the detection process guarantee the reliability and accuracy of the detection results.

Postmenopausal osteoporosis: Effect of moderate-intensity treadmill exercise on bone proteomics in ovariectomized rats

Objectives

This study aimed to identify the key proteins in the bone mass of ovariectomized (OVX) rats after a period of regular moderate-intensity treadmill exercise and to investigate their effects using tag mass spectrometry and quantitative proteomics with a view to improving the understanding and treatment of postmenopausal osteoporosis.

Methods

Sixty three-month-old female Sprague-Dawley tats of specific-pathogen-free grade were randomly and equally divided into a sham operation group, ovariectomized group (OVX) and ovariectomized combined exercise (OVX + EX) group, and the latter took moderate-intensity treadmill exercise for 17 weeks. After this period of time, body composition and bone density were measured using dual-energy x-ray absorptiometry, and serum bone metabolism indicators were measured using an enzyme immunoassay. In addition, the bone microstructure was examined using micro-computed tomography and scanning of the femur, and femur proteins were subject to proteomic analysis.

Results

Compared with the rats in the OVX group, the bone metabolism indicators in the OVX + EX group decreased significantly, femur bone density increased significantly, the number of the trabeculae increased, and continuity was higher. In the OVX + EX group, 17 proteins were significantly upregulated and 33 significantly downregulated. The main gene ontology and signaling pathways enriched by the proteins were identified as the tumor necrosis factor-mediated signaling pathways. The protein-protein interaction network identified the key proteins, and the correlation analysis of these proteins and the bone parameters found histone deacetylase 8(HDAC8) and leucine-rich transmembrane and O-methyltransferase domain containing (LRTOMT) and trimethylguanosine synthase 1(TGS1) and ankyrin repeat domain 46(ANKRD46) to be the key targets of exercise in relation to postmenopausal osteoporosis.

Conclusion

Moderate-intensity treadmill exercise significantly improved the bone mass of OVX rats, and differentially expressed proteins, such as HDAC8 and LRTOMT and TGS1 and ANKRD46, could be the target of moderate-intensity treadmill exercise.

Long-term changes in plasma proteomic profiles in premenopausal and postmenopausal Black and White women: the Atherosclerosis Risk in Communities study

OBJECTIVE

The activity, localization, and turnover of proteins within cells and plasma may contribute to physiologic changes during menopause and may influence disease occurrence. We examined cross-sectional differences and long-term changes in plasma proteins between premenopausal and naturally postmenopausal women.

METHODS

We used data from 4,508 (19% Black) women enrolled in the Atherosclerosis Risk in Communities study. SOMAscan multiplexed aptamer technology was used to measure 4,697 plasma proteins. Linear regression models were used to compare differences in proteins at baseline (1993-1995) and 18-year change in proteins from baseline to 2011-2013.

RESULTS

At baseline, 472 women reported being premenopausal and 4,036 women reported being postmenopausal, with average ages of 52.3 and 61.4 years, respectively. A greater proportion of postmenopausal women had diabetes (15 vs 9%), used hypertension (38 vs 27%) and lipid-lowering medications (10 vs 3%), and had elevated total cholesterol and waist girth. In multivariable adjusted models, 38 proteins differed significantly between premenopausal and postmenopausal women at baseline, with 29 of the proteins also showing significantly different changes between groups over the 18-year follow-up as the premenopausal women also reached menopause. These proteins were associated with various molecular/cellular functions (cellular development, growth, proliferation and maintenance), physiological system development (skeletal and muscular system development, and cardiovascular system development and function), and diseases/disorders (hematological and metabolic diseases and developmental disorders).

CONCLUSIONS

We observed significantly different changes between premenopausal and postmenopausal women in several plasma proteins that reflect many biological processes. These processes may help to understand disease development during the postmenopausal period.

Proteomics Profiling of Osteoporosis and Osteopenia Patients and Associated Network Analysis

Bone mass reduction due to an imbalance in osteogenesis and osteolysis is characterized by low bone mineral density (LBMD) and is clinically classified as osteopenia (ON) or osteoporosis (OP), which is more severe. Multiple biomarkers for diagnosing OP and its progression have been reported; however, most of these lack specificity. This cohort study aimed to investigate sensitive and specific LBMD-associated protein biomarkers in patients diagnosed with ON and OP. A label-free liquid chromatography-mass spectrometry (LC-MS) proteomics approach was used to analyze serum samples. Patients’ proteomics profiles were filtered for potential confounding effects, such as age, sex, chronic diseases, and medication. A distinctive proteomics profile between the control, ON, and OP groups (Q² = 0.7295, R² = 0.9180) was identified, and significant dysregulation in a panel of proteins (n = 20) was common among the three groups. A comparison of these proteins showed that the levels of eight proteins were upregulated in ON, compared to those in the control and the OP groups, while the levels of eleven proteins were downregulated in the ON group compared to those in the control group. Interestingly, only one protein, myosin heavy chain 14 (MYH14), showed a linear increase from the control to the ON group, with the highest abundance in the OP group. A significant separation in the proteomics profile between the ON and OP groups (Q² = 0.8760, R² = 0.991) was also noted. Furthermore, a total of twenty-six proteins were found to be dysregulated between the ON and the OP groups, with fourteen upregulated and twelve downregulated proteins in the OP, compared to that in the ON group. Most of the identified dysregulated proteins were immunoglobulins, complement proteins, cytoskeletal proteins, coagulation factors, and various enzymes. Of these identified proteins, the highest area under the curve (AUC) in the receiver operating characteristic (ROC) analysis was related to three proteins (immunoglobulin Lambda constant 1 (IGLC1), RNA binding protein (MEX3B), and fibulin 1 (FBLN1)). Multiple reaction monitoring (MRM), LC-MS, was used to validate some of the identified proteins. A network pathway analysis of the differentially abundant proteins demonstrated dysregulation of inflammatory signaling pathways in the LBMD patients, including the tumor necrosis factor (TNF), toll-like receptor (TL4), and interferon-γ (IFNG) signaling pathways. These results reveal the existence of potentially sensitive protein biomarkers that could be used in further investigations of bone health and OP progression.

Proteomic Changes of Osteoclast Differentiation in Rheumatoid and Psoriatic Arthritis Reveal Functional Differences

Background

Osteoclasts play a crucial role in the maintenance, repair, and remodeling of bones of the adult vertebral skeleton due to their bone resorption capability. Rheumatoid arthritis (RA) and psoriatic arthritis (PsA) are associated with increased activity of osteoclasts.

Objectives

Our study aimed to investigate the dynamic proteomic changes during osteoclast differentiation in healthy donors, in RA, and PsA.

Methods

Blood samples of healthy donors, RA, and PsA patients were collected, and monocytes were isolated and differentiated into osteoclasts in vitro using macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor κB ligand (RANK-L). Mass spectrometry-based proteomics was used to analyze proteins from cell lysates. The expression changes were analyzed with Gene Set Enrichment Analysis (GSEA).

Results

The analysis of the proteomic changes revealed that during the differentiation of the human osteoclasts, expression of the proteins involved in metabolic activity, secretory function, and cell polarity is increased; by contrast, signaling pathways involved in the immune functions are downregulated. Interestingly, the differences between cells of healthy donors and RA/PsA patients are most pronounced after the final steps of differentiation to osteoclasts. In addition, both in RA and PsA the differentiation is characterized by decreased metabolic activity, associated with various immune pathway activities; furthermore by accelerated cytokine production in RA.

Conclusions

Our results shed light on the characteristic proteomic changes during human osteoclast differentiation and expression differences in RA and PsA, which reveal important pathophysiological insights in both diseases.

USP25 Expression in Peripheral Blood Mononuclear Cells Is Associated With Bone Mineral Density in Women

Osteoporosis is the most common metabolic bone disease in postmenopausal women. As precursors of osteoclasts, peripheral blood mononuclear cells are accessible and considered suitable models for studying osteoporosis pathology. Ubiquitination is a crucial protein degradation system in bone metabolism. The aim of this study was to identify potential ubiquitination-related genes in PBMCs that are related to osteoporosis pathogenesis. Therefore, we performed an integrated analysis of osteoporosis-related microarray datasets. With the obtained ubiquitination-related gene set, weighted gene coexpression network analysis was performed. The results showed that genes in the turquoise module were correlated with menopause, and 48 genes were identified as hub genes. A differential expression analysis revealed 43 differentially expressed genes between pre- and postmenopausal samples. After integrating the information on differentially expressed menopause-related genes, we found that several members of the ubiquitin-specific protease (USP) family (USP1, USP7, USP9X, USP16, and USP25) were highly expressed in samples from postmenopausal female and that, USP25 expression was significantly higher in low-BMD samples than in high-BMD samples among samples from premenopausal subjects (p = 0.0013) and among all samples (p = 0.013). Finally, we verified the protein expression of USP25 in PBMCs by performing Western blot analysis, which yielded results consistent with the aforementioned results. Moreover, by assessing GTEx datasets, we found that USP25 expression was highly correlated with TRAF6 expression in whole blood (p < 0.001). We also tested the protein expression levels of TRAF6 in PBMCs and found that it was positively correlated with USP25 expression (p = 0.036). Our results reveal that the ubiquitin-specific protease family may play important roles in menopause and that USP25 is related to osteoporosis pathogenesis.

The Effect of Moderate-Intensity Treadmill Exercise on Bone Mass and the Transcription of Peripheral Blood Mononuclear Cells in Ovariectomized Rats

Objective: Using RNA-sequencing technology to screen the effect of moderate-intensity treadmill exercise on the sensitive genes that affect bone mass in the peripheral blood mononuclear cells (PBMCs) of ovariectomized (OVX) rats.

Methods: Three-month-old female Sprague-Dawley rats of Specific Pathogen Free (SPF) grade were randomly divided into the sham operation (SHAM) group, OVX group, and OVX combined exercise (OVX + EX) group. The OVX + EX group performed moderate-intensity treadmill exercise for 17 weeks. Then, the body composition and bone mineral density (BMD) were measured, and the bone microstructure of the femur was observed. PBMCs were collected from the abdominal aorta, and the differential genes were analyzed by transcriptome sequencing to further screen sensitive genes.

Results: (1) In the OVX group, the body weight and body fat content were significantly higher than in the SHAM group while the muscle content and BMD were significantly lower than the SHAM group. (2) The trabecular bone parameters in the OVX group were significantly lower than in the SHAM group, and they were significantly higher in the OVX + EX group than in the OVX group. When compared with the SHAM group, the microstructure of the distal femur trabecular in the OVX group was severely damaged, suggest that the morphological structure of trabecular bone is severely damaged, the number of trabecular bones is reduced, and the thickness becomes thinner, which lead to the widening of the trabecular bone space and the appearance of osteoporosis. The number and continuity of the trabecular bones were higher in the OVX + EX group than in the OVX group. (3) A Venn diagram showed that there were 58 common differential genes, and the differential genes were mainly enriched in the PI3K-Akt signaling pathway. Five sensitive genes were screened including CCL2, Nos3, Tgfb3, ITGb4, and LpL. The expression of CCL2, Nos3, and Tgfb3 genes was closely related to multiple bone parameters.

Conclusion: Moderate-intensity treadmill exercise may improve the body composition and bone mass of the OVX group by upregulating CCL2 and other genes of the PBMC. The PBMCs in the peripheral blood can be a useful tool for monitoring the effect of exercise on bone health in postmenopausal osteoporosis.

Immunoporosis: Role of Innate Immune Cells in Osteoporosis

Osteoporosis or porous bone disorder is the result of an imbalance in an otherwise highly balanced physiological process known as 'bone remodeling'. The immune system is intricately involved in bone physiology as well as pathologies. Inflammatory diseases are often correlated with osteoporosis. Inflammatory mediators such as reactive oxygen species (ROS), and pro-inflammatory cytokines and chemokines directly or indirectly act on the bone cells and play a role in the pathogenesis of osteoporosis. Recently, Srivastava et al. (Srivastava RK, Dar HY, Mishra PK. Immunoporosis: Immunology of Osteoporosis-Role of T Cells. Frontiers in immunology. 2018;9:657) have coined the term "immunoporosis" to emphasize the role of immune cells in the pathology of osteoporosis. Accumulated pieces of evidence suggest both innate and adaptive immune cells contribute to osteoporosis. However, innate cells are the major effectors of inflammation. They sense various triggers to inflammation such as pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), cellular stress, etc., thus producing pro-inflammatory mediators that play a critical role in the pathogenesis of osteoporosis. In this review, we have discussed the role of the innate immune cells in great detail and divided these cells into different sections in a systemic manner. In the beginning, we talked about cells of the myeloid lineage, including macrophages, monocytes, and dendritic cells. This group of cells explicitly influences the skeletal system by the action of production of pro-inflammatory cytokines and can transdifferentiate into osteoclast. Other cells of the myeloid lineage, such as neutrophils, eosinophils, and mast cells, largely impact osteoporosis via the production of pro-inflammatory cytokines. Further, we talked about the cells of the lymphoid lineage, including natural killer cells and innate lymphoid cells, which share innate-like properties and play a role in osteoporosis. In addition to various innate immune cells, we also discussed the impact of classical pro-inflammatory cytokines on osteoporosis. We also highlighted the studies regarding the impact of physiological and metabolic changes in the body, which results in chronic inflammatory conditions such as ageing, ultimately triggering osteoporosis.

GWA-based pleiotropic analysis identified potential SNPs and genes related to type 2 diabetes and obesity

Metabolic syndrome is a cluster of symptoms including excessive body fat and insulin resistance which may lead to obesity and type 2 diabetes (T2D). The physiological and pathological cross-talk between T2D and obesity is crucial and complex, meanwhile, the genetic connection between T2D and obesity is largely unknown. The purpose of this study is to identify pleiotropic SNPs and genes between these two associated conditions by applying genetic analysis incorporating pleiotropy and annotation (GPA) on two large genome-wide association studies (GWAS) data sets: a body mass index (BMI) data set containing 339,224 subjects and a T2D data set containing 110,452 subjects. In all, 5182 SNPs showed pleiotropy in both T2D and obesity. After further prioritization based on suggested local false discovery rates (FDR) by the GPA model, 2146 SNPs corresponding to 217 unique genes are significantly associated with both traits (FDR < 0.2), among which 187 are newly identified pleiotropic genes compare with original GWAS in individual traits. Subsequently, gene enrichment and pathway analyses highlighted several pleiotropic SNPs including rs849135 (FDR = 0.0002), rs2119812 (FDR = 0.0018), rs4506565 (FDR = 1.23E-08), rs1558902 (7.23E-10) and corresponding genes JAZF1, SYN2, TCF7L2, FTO which may play crucial rol5es in the etiology of both T2D and obesity. Additional evidences from expression data analysis of pleiotropic genes strongly supports that the pleiotropic genes including JAZF1 (p = 1.39E-05 and p = 2.13E-05), SYN2 (p = 5.49E-03 and p = 5.27E-04), CDKN2C (p = 1.99E-12 and p = 6.27E-11), RABGAP1 (p = 3.08E-03 and p = 7.46E-03), and UBE2E2 (p = 1.83E-04 and p = 8.22E-03) play crucial roles in both obesity and T2D pathogenesis. Pleiotropic analysis integrated with functional network identified several novel and causal SNPs and genes involved in both BMI and T2D which may be ignored in single GWAS.

Integrative Analysis of Genomics and Transcriptome Data to Identify Regulation Networks in Female Osteoporosis

Background: Osteoporosis is a highly heritable skeletal muscle disease. However, the genetic mechanisms mediating the pathogenesis of osteoporosis remain unclear. Accordingly, in this study, we aimed to clarify the transcriptional regulation and heritability underlying the onset of osteoporosis.

Methods: Transcriptome gene expression data were obtained from the Gene Expression Omnibus database. Microarray data from peripheral blood monocytes of 73 Caucasian women with high and low bone mineral density (BMD) were analyzed. Differentially expressed messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs) were identified. Differences in BMD were then attributed to several gene modules using weighted gene co-expression network analysis (WGCNA). LncRNA/mRNA regulatory networks were constructed based on the WGCNA and subjected to functional enrichment analysis.

Results: In total, 3,355 mRNAs and 999 lncRNAs were identified as differentially expressed genes between patients with high and low BMD. The WGCNA yielded three gene modules, including 26 lncRNAs and 55 mRNAs as hub genes in the blue module, 36 lncRNAs and 31 mRNAs as hub genes in the turquoise module, and 56 mRNAs and 30 lncRNAs as hub genes in the brown module. JUN and ACSL5 were subsequently identified in the modular gene network. After functional pathway enrichment, 40 lncRNAs and 16 mRNAs were found to be related to differences in BMD. All three modules were enriched in metabolic pathways. Finally, mRNA/lncRNA/pathway networks were constructed using the identified regulatory networks of lncRNAs/mRNAs and pathway enrichment relationships.

Conclusion: The mRNAs and lncRNAs identified in this WGCNA could be novel clinical targets in the diagnosis and management of osteoporosis. Our findings may help elucidate the complex interactions between transcripts and non-coding RNAs and provide novel perspectives on the regulatory mechanisms of osteoporosis.

Quantitative proteomics and reverse engineer analysis identified plasma exosome derived protein markers related to osteoporosis

Alongside an aging population, osteoporosis has become increasingly common, representing a major public health problem. Human blood provides the predominant matrix for pathological targets underlining disease mechanisms. In the present study, the protein profiles of blood plasma exosomes from patients with osteoporosis, osteopenia, and those with normal bone mass were compared. The aim of the study was to search for potential novel diagnostic/therapeutic targets for further investigation in osteoporosis. A total of 60 participants were included from the PLAGH Hip Fracture Database. Quantitative proteomics was carried out to profile the plasma exosome derived proteins from patients diagnosed with osteoporosis, osteopenia, and normal bone mass, respectively. A Parallel reaction monitoring (PRM) analysis was further carried out to validate the identified proteins. Bio-informatics analyses including GO annotation and reverse engineering of gene regulatory networks analysis were applied in annotating the biological relevance of the identified proteins. Forty-five differentially expressed proteins were identified in the discovery dataset and four of them, PSMB9, AARS, PCBP2, and VSIR were further verified in a validation set. Based on the results, an exosomal-proteins index was constructed to classify individuals with osteoporosis from those without, an AUC of 0.805 (95% CI 0.620-0.926, p < 0.001) was achieved in classification performance assessment. Additionally, a reverse engineer of the regulatory network analysis identified and predicted the proteins which may interact with the four target proteins identified, providing references for further investigations into the pathological mechanisms of osteoporosis.

Proteomic profiling analysis of postmenopausal osteoporosis and osteopenia identifies potential proteins associated with low bone mineral density

Postmenopausal osteoporosis (PMOP) is a major global public health concern and older women are more susceptible to experiencing fragility fractures. Our study investigated the associations between circulating proteins with bone mineral density (BMD) in postmenopausal women with or without low BMD (osteoporosis and osteopenia) using a tandem mass tag (TMT) labeling proteomic experiment and parallel reaction monitoring testing. Across all plasma samples, we quantitatively measured 1,092 proteins, and the OP and normal control (NC) samples were differentiated by principal component analysis and a partial least squares-discrimination analysis model based on the protein profiling data. The differentially abundant proteins between the low BMD and NC samples mostly exhibited binding, molecular function regulator, transporter and molecular transducer activity, and were involved in metabolic and cellular processes, stimulus response, biological regulation, immune system processes and so forth. TMT analysis and RRM validation indicated that the expression of protein Lysozyme C (P61626) was negatively related to BMD, while the expression of proteins Glucosidase (A0A024R592) and Protein disulfideisomerase A5 (Q14554) was positively related to BMD values. Collectively, our results suggest that postmenopausal women with low BMD have a different proteomic profile or signature. Protein alterations may play an important role in the pathogenesis of PMOP, and they may act as novel biomarkers and targets of therapeutic agents for this disease.

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.

Monocytes affect bone mineral density in pre- and postmenopausal women through ribonucleoprotein complex biogenesis by integrative bioinformatics analysis

Osteoporosis is one of the most common metabolic bone disease among pre- and postmenopausal women. As the precursors of osteoclast cells, circulating monocytes play important role in bone destruction and remodeling. The aim of study is to identify potential key genes and pathways correlated with the pathogenesis of osteoporosis. Then we construct novel estimation model closely linked to the bone mineral density (BMD) with key genes. Weighted gene co-expression network analysis (WGCNA) were conducted by collecting gene data set with 80 samples from gene expression omnibus (GEO) database. Besides, hub genes were identified by series of bioinformatics and machine learning algorithms containing protein-protein interaction (PPI) network, receiver operating characteristic curve and Pearson correlation. The direction of correlation coefficient were performed to screen for gene signatures with high BMD and low BMD. A novel BMD score system was put forward based on gene set variation analysis and logistic regression, which was validated by independent data sets. We identified six modules correlated with BMD. Finally 100 genes were identified as the high bone mineral density signatures while 130 genes were identified as low BMD signatures. Besides, we identified the significant pathway in monocytes: ribonucleoprotein complex biogenesis. What's more, our score validated it successfully.

Integrating transcriptome-wide association study and mRNA expression profiling identified candidate genes and pathways associated with osteomyelitis

Objective: Osteomyelitis (OM) is an acute or chronic inflammatory process, characterized by severe inflammation and progressive bone destruction. Limited efforts have been made to explore the genetic basis of OM.Method: The genome-wide association study data set of OM was obtained from the UK Biobank. A transcriptome-wide association study (TWAS) of OM was conducted by the FUSION tool using the gene expression reference weights of lymphocytes and blood. The OM-associated genes identified by TWAS were subjected to gene ontology (GO) enrichment analysis to explore OM-related gene sets. The TWAS results of OM were finally compared with a genome-wide mRNA expression profiling of OM to detect common genes and gene sets.Results: TWAS of OM detected 86 genes for lymphocytes and 387 genes for blood. Comparing the genes identified by TWAS and mRNA expression profiling detected eight common genes for OM, including VWF (p_TWAS = 0.0030, p_mRNA = 3.44 × 10^-9), CCDC50 (p_TWAS = 0.0130, p_mRNA = 0.0003), and TPD52 (p_TWAS = 0.0180, p_mRNA = 1 × 10^-6). GO analysis of the genes identified by TWAS detected multiple OM-associated GO terms, e.g. peroxisomal matrix (p_TWAS = 0.0082), extracellular exosome (p_TWAS = 0.0248), and monooxygenase activity (p_TWAS = 0.0040). Further comparing the GO results of TWAS and mRNA expression profiling detected one common GO term, named extracellular exosome (p_TWAS = 0.0248, p_mRNA = 0.0027).Conclusion: This integrative study of TWAS and mRNA expression profiling detected multiple candidate genes and GO terms for OM. Our results provide novel clues for understanding the pathogenesis of OM.

Proteomic studies of bone and skeletal health outcomes

Proteins are an essential part of essentially all biological processes, and there is enormous variation in protein forms and concentrations that is not reflected in DNA or RNA. Recently there have been rapid advances in the ability to measure protein sequence, modification and concentration, particularly with methods based in mass spectrometry. Global measures of proteins in tissues or in the circulation provide a broad assessment of the proteome that can be extremely useful for discovery, and targeted proteomic measures can yield specific and sensitive assessments of specific peptides and proteins. While most proteomic measures are directed at the detection of consensus peptide sequences, mass spectrometry based proteomic methods also allow a detailed examination of the peptide sequence differences that result from genetic variants and that may have important effects on protein function. In evaluating proteomic data, a number of analytical considerations are important, including an understanding of missing data, the challenge of multiple testing and replication, and the use of rapidly evolving methods in systems biology. While proteomics has not yet had a major impact in skeletal research, interesting recent research has used these approaches in the study of bone cell biology and the discovery of biomarkers of skeletal disorders. Proteomics can be expected to have an increasing influence in the study of bone biology and pathophysiology.

PPWD1 is associated with the occurrence of postmenopausal osteoporosis as determined by weighted gene co‑expression network analysis

Postmenopausal osteoporosis (PMO) is the most common type of primary osteoporosis (OP), a systemic skeletal disease. Although many factors have been revealed to contribute to the occurrence of PMO, specific biomarkers for the early diagnosis and therapy of PMO are not available. In the present study, a weighted gene co-expression network analysis (WGCNA) was performed to screen gene modules associated with menopausal status. The turquoise module was verified as the clinically significant module, and 12 genes (NUP133, PSMD12, PPWD1, RBM8A, CRNKL1, PPP2R5C, RBM22, PIK3CB, SKIV2L2, PAPOLA, SRSF1 and COPS2) were identified as ‘real’ hub genes in both the protein-protein interaction (PPI) network and co-expression network. Furthermore, gene expression analysis by microarray in blood monocytes from pre- and post-menopausal women revealed an increase in the expression of these hub genes in postmenopausal women. However, only the expression of peptidylprolyl isomerase domain and WD repeat containing 1 (PPWD1) was correlated with bone mineral density (BMD) in postmenopausal women. In the validation set, a similar expression pattern of PPWD1 was revealed. Functional enrichment analysis revealed that the fatty acid metabolism pathway was significantly abundant in the samples that exhibited a higher expression of PPWD1. Collectively, PPWD1 is indicated as a potential diagnostic biomarker for the occurrence of PMO.

Bronchoalveolar Lavage Fluid from COPD Patients Reveals More Compounds Associated with Disease than Matched Plasma

Smoking causes chronic obstructive pulmonary disease (COPD). Though recent studies identified a COPD metabolomic signature in blood, no large studies examine the metabolome in bronchoalveolar lavage (BAL) fluid, a more direct representation of lung cell metabolism. We performed untargeted liquid chromatography-mass spectrometry (LC-MS) on BAL and matched plasma from 115 subjects from the SPIROMICS cohort. Regression was performed with COPD phenotypes as the outcome and metabolites as the predictor, adjusted for clinical covariates and false discovery rate. Weighted gene co-expression network analysis (WGCNA) grouped metabolites into modules which were then associated with phenotypes. K-means clustering grouped similar subjects. We detected 7939 and 10,561 compounds in BAL and paired plasma samples, respectively. FEV₁/FVC (Forced Expiratory Volume in One Second/Forced Vital Capacity) ratio, emphysema, FEV₁ % predicted, and COPD exacerbations associated with 1230, 792, eight, and one BAL compounds, respectively. Only two plasma compounds associated with a COPD phenotype (emphysema). Three BAL co-expression modules associated with FEV₁/FVC and emphysema. K-means BAL metabolomic signature clustering identified two groups, one with more airway obstruction (34% of subjects, median FEV₁/FVC 0.67), one with less (66% of subjects, median FEV₁/FVC 0.77; p < 2 × 10^-4). Associations between metabolites and COPD phenotypes are more robustly represented in BAL compared to plasma.

Integrative analysis of transcriptome-wide association study data and mRNA expression profiles identified candidate genes and pathways associated with atrial fibrillation

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia characterized by extensive structural, contractile and electrophysiological remodeling. The genetic basis of AF remained elusive until now. Transcriptome-wide association study (TWAS) was conducted by FUSION tool using gene expression weights of 7 tissues combined with a large-scale genome-wide association study (GWAS) dataset of AF, totally involving 8180 AF cases and 28,612 controls. Significant genes identified by TWAS were then subjected to gene ontology (GO) and pathway enrichment analysis. The genome-wide mRNA gene expression profiling of AF was compared with the results of TWAS to detect common genes shared by TWAS and mRNA expression profiling of AF. TWAS detected a group of candidate genes with P_TWAS values < 0.05 across the seven tissues for AF, such as CMAH (P_TWAS = 3.15 × 10^-25 for whole blood), INCENP (P_TWAS = 1.77 × 10^-22 for artery aorta), CMAHP (P_TWAS = 4.57 × 10^-20 for artery aorta). Pathway enrichment analysis identified multiple candidate pathways, such as protein K48-linked ubiquitination (P value = 0.0124), positive regulation of leukocyte chemotaxis (P value = 0.0046) and fatty acid degradation (P value = 0.0295). Further comparing the GO results of TWAS and mRNA expression profiling, 2 common GO terms were identified, including actin binding (P_TWAS = 0.0446, P_mRNA = 7.00 × 10^-4) and extracellular matrix (P_TWAS = 0.0037, P_mRNA = 3.00 × 10^-6). We detected multiple novel candidate genes, GO terms and pathways for AF, providing novel clues for understanding the genetic mechanism of AF.

Differentially expressed proteins identified by TMT proteomics analysis in bone marrow microenvironment of osteoporotic patients

We applied tandem mass tag (TMT)-based proteomics to investigate protein changes in bone marrow microenvironment of osteoporotic patients undergoing spine fusion. Multiple bioinformatics tools were used to identify and analyze 219 differentially expressed proteins. These proteins may be associated with the pathogenesis of osteoporosis.

INTRODUCTION

Bone marrow microenvironment is indispensable for the maintenance of bone homeostasis. We speculated that alterations of some factors in the microenvironment of osteoporotic subjects might influence the homeostasis. This study aimed to investigate the changes in the expression of protein factors in the bone marrow environment of osteoporosis.

METHODS

We performed a proteomics analysis in the vertebral body-derived bone marrow supernatant fluid from 8 Chinese patients undergoing posterior lumbar interbody fusion (4 osteoporotic vs. 4 non-osteoporotic) and used micro-CT to analyze the microstructural features of spinous processes from these patients. We further performed western blotting to validate the differential expressions of some proteins.

RESULTS

There was deteriorated bone microstructure in osteoporotic patients. Based on proteomics analysis, 172 upregulated and 47 downregulated proteins were identified. These proteins had multiple biological functions associated with osteoblast differentiation, lipid metabolism, and cell migration, and formed a complex protein-protein interaction network. We identified five major regulatory mechanisms, splicing, translation, protein degradation, cytoskeletal organization, and lipid metabolism, involved in the pathogenesis of osteoporosis.

CONCLUSIONS

There are various protein factors, such as DDX5, PSMC2, CSNK1A1, PLIN1, ILK, and TPM4, differentially expressed in the bone marrow microenvironment of osteoporotic patients, providing new ideas for finding therapeutic targets for osteoporosis.

In Search of Biomarkers for Pathogenesis and Control of Leishmaniasis by Global Analyses of Leishmania-Infected Macrophages

Leishmaniasis is a vector-borne, neglected tropical disease with a worldwide distribution that can present in a variety of clinical forms, depending on the parasite species and host genetic background. The pathogenesis of this disease remains far from being elucidated because the involvement of a complex immune response orchestrated by host cells significantly affects the clinical outcome. Among these cells, macrophages are the main host cells, produce cytokines and chemokines, thereby triggering events that contribute to the mediation of the host immune response and, subsequently, to the establishment of infection or, alternatively, disease control. There has been relatively limited commercial interest in developing new pharmaceutical compounds to treat leishmaniasis. Moreover, advances in the understanding of the underlying biology of Leishmania spp. have not translated into the development of effective new chemotherapeutic compounds. As a result, biomarkers as surrogate disease endpoints present several potential advantages to be used in the identification of targets capable of facilitating therapeutic interventions considered to ameliorate disease outcome. More recently, large-scale genomic and proteomic analyses have allowed the identification and characterization of the pathways involved in the infection process in both parasites and the host, and these analyses have been shown to be more effective than studying individual molecules to elucidate disease pathogenesis. RNA-seq and proteomics are large-scale approaches that characterize genes or proteins in a given cell line, tissue, or organism to provide a global and more integrated view of the myriad biological processes that occur within a cell than focusing on an individual gene or protein. Bioinformatics provides us with the means to computationally analyze and integrate the large volumes of data generated by high-throughput sequencing approaches. The integration of genomic expression and proteomic data offers a rich multi-dimensional analysis, despite the inherent technical and statistical challenges. We propose that these types of global analyses facilitate the identification, among a large number of genes and proteins, those that hold potential as biomarkers. The present review focuses on large-scale studies that have identified and evaluated relevant biomarkers in macrophages in response to Leishmania infection.

Proteomics in plasma of ovariectomized rats and those exposed to estradiol valerate

The menopausal period, an inevitable physiological process for women, is frequently associated with physiological and psychological dysfunction attributable to substantial fluctuation and gradual decrease in female hormones induced by ovarian failure, leading to corresponding symptoms and diseases that impact multiple systems in the body to varying degrees. As prior studies have focused primarily on menopausal syndrome-related pathophysiological changes and hormone replacement therapy effects, here we approached menopausal disease incidence risk and pathogenesis through systemic plasma proteomics analysis. Female Sprague-Dawley rats were randomly divided into sham, ovariectomized, and estrogen treatment after ovariectomy groups (n=9 per group). Tandem Mass Tag quantitative proteomics analysis of their plasma identified over 900 proteins by MS. Between group fold change of >1.2 and p<0.05 (Student's t-test) identified 121 (including 36 up-regulated and 85 down-regulated), 117 (69 up-regulated and 48 down-regulated), and 109 (41 up-regulated and 68 down-regulated) differentially expressed proteins between groups, respectively. Of these, 5 (GHR, LIFR, apoA IV, RTN, and Lin28b) were verified by parallel reaction monitoring to be reliable. Further application of optimized screening criteria and performance of a series of bioinformatics analyses allowed the selection of 35 optimal differentially expressed proteins. Gene ontology annotation results suggested that the differentially expressed proteins are mainly annotated as protein binding, cell, and single organism process in terms of molecular function, cell composition, and biological process, respectively. KEGG pathway analysis indicated that the PI3-Akt pathway has the highest aggregation degree of differentially expressed proteins. Protein-protein interaction analysis noted GLUT4 as an important node protein. This research is the first to comprehensively analyze plasma protein changes, together with estrogen efficacy, in ovariectomized rats. The findings facilitate our understanding of the molecular mechanism of systemic menopausal changes and provide valuable clues for developing diagnostic biomarkers for menopausal dysfunctions and selecting clinical therapeutic strategies.

"Omics" Signatures in Peripheral Monocytes from Women with Low BMD Condition

Postmenopausal osteoporosis (PMO) is a result of increased bone resorption compared to formation. Osteoclasts are responsible for bone resorption, which are derived from circulating monocytes that undertake a journey from the blood to the bone for the process of osteoclastogenesis. In recent times, the use of high throughput technologies to explore monocytes from women with low versus high bone density has led to the identification of candidate molecules that may be deregulated in PMO. This review provides a list of molecules in monocytes relevant to bone density which have been identified by "omics" studies in the last decade or so. The molecules in monocytes that are deregulated in low BMD condition may contribute to processes such as monocyte survival, migration/chemotaxis, adhesion, transendothelial migration, and differentiation into the osteoclast lineage. Each of these processes may be crucial to the overall route of osteoclastogenesis and an increase in any/all of these processes can lead to increased bone resorption and subsequently low bone density. Whether these molecules are indeed the cause or effect is an arena currently unexplored.

Integrated proteomics and network analysis identifies protein hubs and network alterations in Alzheimer's disease

Although the genetic causes for several rare, familial forms of Alzheimer’s disease (AD) have been identified, the etiology of the sporadic form of AD remains unclear. Here, we report a systems-level study of disease-associated proteome changes in human frontal cortex of sporadic AD patients using an integrated approach that combines mass spectrometry-based quantitative proteomics, differential expression analysis, and co-expression network analysis. Our analyses of 16 human brain tissues from AD patients and age-matched controls showed organization of the cortical proteome into a network of 24 biologically meaningful modules of co-expressed proteins. Of these, 5 modules are positively correlated to AD phenotypes with hub proteins that are up-regulated in AD, and 6 modules are negatively correlated to AD phenotypes with hub proteins that are down-regulated in AD. Our study generated a molecular blueprint of altered protein networks in AD brain and uncovered the dysregulation of multiple pathways and processes in AD brain, including altered proteostasis, RNA homeostasis, immune response, neuroinflammation, synaptic transmission, vesicular transport, cell signaling, cellular metabolism, lipid homeostasis, mitochondrial dynamics and function, cytoskeleton organization, and myelin-axon interactions. Our findings provide new insights into AD pathogenesis and suggest novel candidates for future diagnostic and therapeutic development.

Proteomic profiling of NCI-60 extracellular vesicles uncovers common protein cargo and cancer type-specific biomarkers

Packed with biological information, extracellular vesicles (EVs) offer exciting promise for biomarker discovery and applications in therapeutics and non-invasive diagnostics. Currently, our understanding of EV contents is confined by the limited cells from which vesicles have been characterized utilizing the same enrichment method. Using sixty cell lines from the National Cancer Institute (NCI-60), here we provide the largest proteomic profile of EVs in a single study, identifying 6,071 proteins with 213 common to all isolates. Proteins included established EV markers, and vesicular trafficking proteins such as Rab GTPases and tetraspanins. Differentially-expressed proteins offer potential for cancer diagnosis and prognosis. Network analysis of vesicle quantity and proteomes identified EV components associated with vesicle secretion, including CD81, CD63, syntenin-1, VAMP3, Rab GTPases, and integrins. Integration of vesicle proteomes with whole-cell molecular profiles revealed similarities, suggesting EVs provide a reliable reflection of their progenitor cell content, and are therefore excellent indicators of disease.

Integrating genome-wide association study summaries and element-gene interaction datasets identified multiple associations between elements and complex diseases

Chemical elements are closely related to human health. Extensive genomic profile data of complex diseases offer us a good opportunity to systemically investigate the relationships between elements and complex diseases/traits. In this study, we applied gene set enrichment analysis (GSEA) approach to detect the associations between elements and complex diseases/traits though integrating element-gene interaction datasets and genome-wide association study (GWAS) data of complex diseases/traits. To illustrate the performance of GSEA, the element-gene interaction datasets of 24 elements were extracted from the comparative toxicogenomics database (CTD). GWAS summary datasets of 24 complex diseases or traits were downloaded from the dbGaP or GEFOS websites. We observed significant associations between 7 elements and 13 complex diseases or traits (all false discovery rate (FDR) < 0.05), including reported relationships such as aluminum vs. Alzheimer's disease (FDR = 0.042), calcium vs. bone mineral density (FDR = 0.031), magnesium vs. systemic lupus erythematosus (FDR = 0.012) as well as novel associations, such as nickel vs. hypertriglyceridemia (FDR = 0.002) and bipolar disorder (FDR = 0.027). Our study results are consistent with previous biological studies, supporting the good performance of GSEA. Our analyzing results based on GSEA framework provide novel clues for discovering causal relationships between elements and complex diseases.

Network based subcellular proteomics in monocyte membrane revealed novel candidate genes involved in osteoporosis

In this study, label-free-based quantitative subcellular proteomics integrated with network analysis highlighted several candidate genes including P4HB, ITGB1, CD36, and ACTN1 that may be involved in osteoporosis. All of them are predicted as significant membrane proteins with high confidence and enriched in bone-related biological process. The results were further verified in transcriptomic and genomic levels.

INTRODUCTION

Osteoporosis is a metabolic bone disease mainly characterized by low bone mineral density (BMD). As the precursors of osteoclasts, peripheral blood monocytes (PBMs) are supported to be important candidates for identifying genes related to osteoporosis. We performed subcellular proteomics study to identify significant membrane proteins that involved in osteoporosis.

METHODS

To investigate the association between monocytes, membrane proteins, and osteoporosis, we performed label-free quantitative subcellular proteomics in 59 male subjects with discordant BMD levels, with 30 high vs. 29 low BMD subjects. Subsequently, we performed integrated gene enrichment analysis, functional annotation, and pathway and network analysis based on multiple bioinformatics tools.

RESULTS

A total of 1070 membrane proteins were identified and quantified. By comparing the proteins' expression level, we found 36 proteins that were differentially expressed between high and low BMD groups. Protein localization prediction supported the notion that the differentially expressed proteins, P4HB (p = 0.0021), CD36 (p = 0.0104), ACTN1 (p = 0.0381), and ITGB1 (p = 0.0385), are significant membrane proteins. Functional annotation and pathway and network analysis highlighted that P4HB, ITGB1, CD36, and ACTN1 are enriched in osteoporosis-related pathways and terms including "ECM-receptor interaction," "calcium ion binding," "leukocyte transendothelial migration," and "reduction of cytosolic calcium levels." Results from transcriptomic and genomic levels provided additional supporting evidences.

CONCLUSION

Our study strongly supports the significance of the genes P4HB, ITGB1, CD36, and ACTN1 to the etiology of osteoporosis risk.

Transgelin-2: A potential oncogenic factor

Actin-binding proteins are proteins that could bind to actin or actin fibers. As a member of actin-binding proteins, Transgelin-2 is expressed in smooth muscle cells and non-smooth muscle cells, and its gene, TAGLN2, is differently expressed in all cells and tissues. The deregulation of Transgelin-2 is considered to be correlated with progression of many kinds of diseases, especially the development of malignant tumors, such as invasion, metastasis, and resistance, yet the function and mechanism of action of Transgelin-2 remain elusive. Therefore, we reviewed the basic characteristics and function of Transgelin-2 and its biological role in various types of diseases in order to provide the theoretical basis for further research and new perspectives on cancer development.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

WGCNA Application to Proteomic and Metabolomic Data Analysis

Progresses in mass spectrometric instrumentation and bioinformatics identification algorithms made over the past decades allow quantitative measurements of relative or absolute protein/metabolite amounts in cells in a high-throughput manner, which has significantly expedited the exploration into functions and dynamics of complex biological systems. However, interpretation of high-throughput data is often restricted by the limited availability of suitable computational methods and enough statistical power. While many computational methodologies have been developed in the past decades to address the issue, it becomes clear that network-focused rather than individual gene/protein-focused strategies would be more appropriate to obtain a complete picture of cellular responses. Recently, an R analytical package named as weighted gene coexpression network analysis (WGCNA) was developed and applied to high-throughput microarray or RNA-seq datasets since it provides a systems-level insights, high sensitivity to low abundance, or small fold changes genes without any information loss. The approach was also recently applied to proteomic and metabolomic data analysis. However, due to the fact that low coverage of the current proteomic and metabolomic analytical technologies, causing the format of datasets are often incomplete, the method needs to be modified so that it can be properly utilized for meaningful biologically interpretation. In this chapter, we provide a detailed introduction of the modified protocol and its tutorials for applying the WGCNA approach in analyzing proteomic and metabolomic datasets.

P4 medicine and osteoporosis: a systematic review

BACKGROUND

Osteoporosis is the most frequent bone metabolic disease. In order to improve early detection, prediction, prevention, diagnosis, and treatment of the disease, a new model of P4 medicine (personalized, predictive, preventive, and participatory medicine) could be applied. The aim of this work was to systematically review the publications of four different types of "omics" studies related to osteoporosis, in order to discover novel predictive, preventive, diagnostic, and therapeutic targets for better management of the geriatric population.

METHODS

To systematically search the PubMed database, we created specific groups of criteria for four different types of "omics" information on osteoporosis: genomic, transcriptomic, proteomic, and metabolomic. We then analyzed the intersections between them in order to find correlations and common pathways or molecules with important roles in osteoporosis, and with a potential application in disease prediction, prevention, diagnosis, or treatment.

RESULTS

Altogether, 180 publications of "omics" studies in the field of osteoporosis were found and reviewed at first selection. After introducing the inclusion and exclusion criteria (the secondary selection), 46 papers were included in the systematic review.

CONCLUSIONS

The intersection of reviewed papers identified five genes (ESR1, IBSP, CTNNB1, SOX4, and IDUA) and processes like the Wnt pathway, JAK/STAT signaling, and ERK/MAPK, which should be further validated for their predictive, diagnostic, or other clinical value in osteoporosis. Such molecular insights will enable us to fit osteoporosis into the P4 strategy and could increase the effectiveness of disease prediction and prevention, with a decrease in morbidity in the geriatric population.

Quantitative proteomics and integrative network analysis identified novel genes and pathways related to osteoporosis

Osteoporosis is mainly characterized by low bone mineral density (BMD), and can be attributed to excessive bone resorption by osteoclasts. Migration of circulating monocytes from blood to bone is important for subsequent osteoclast differentiation and bone resorption. Identification of those genes and pathways related to osteoclastogenesis and BMD will contribute to a better understanding of the pathophysiological mechanisms of osteoporosis. In this study, we applied the LC-nano-ESI-MS(E) (Liquid Chromatograph-nano-Electrospray Ionization-Mass Spectrometry) for quantitative proteomic profiling in 33 female Caucasians with discordant BMD levels, with 16 high vs. 17 low BMD subjects. Protein quantitation was accomplished by label-free measurement of total ion currents collected from MS(E) data. Comparison of protein expression in high vs. low BMD subjects showed that ITGA2B (p=0.0063) and GSN (p=0.019) were up-regulated in the high BMD group. Additionally, our protein-RNA integrative analysis showed that RHOA (p=0.00062) differentially expressed between high vs. low BMD groups. Network analysis based on multiple tools revealed two pathways: "regulation of actin cytoskeleton" (p=1.13E-5, FDR=3.34E-4) and "leukocyte transendothelial migration" (p=2.76E-4, FDR=4.71E-3) that are functionally relevant to osteoporosis. Consistently, ITGA2B, GSN and RHOA played crucial roles in these two pathways respectively. All together, our study strongly supported the contribution of the genes ITGA2B, GSN and RHOA and the two pathways to osteoporosis risk.

BIOLOGICAL SIGNIFICANCE

Mass spectrometry based quantitative proteomics study integrated with network analysis identified novel genes and pathways related to osteoporosis. The results were further verified in multiple level studies including protein-RNA integrative analysis and genome wide association studies.