scholarly journals Circulating miRNAs: A New Opportunity in Bone Fragility

Biomolecules ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 927 ◽  
Author(s):  
Simone Donati ◽  
Simone Ciuffi ◽  
Gaia Palmini ◽  
Maria Luisa Brandi

Osteoporosis, one of the leading causes of bone fractures, is characterized by low bone mass and structural deterioration of bone tissue, which are associated with a consequent increase in bone fragility and predisposition to fracture. Current screening tools are limited in estimating the proper assessment of fracture risk, highlighting the need to discover novel more suitable biomarkers. Genetic and environmental factors are both implicated in this disease. Increasing evidence suggests that epigenetics and, in particular, miRNAs, may represent a link between these factors and an increase of fracture risk. miRNAs are a class of small noncoding RNAs that negatively regulate gene expression. In the last decade, several miRNAs have been associated with the development of osteoporosis and bone fracture risk, opening up new possibilities in precision medicine. Recently, these molecules have been identified in several biological fluids, and the possible existence of a circulating miRNA (c-miRNA) signature years before the fracture occurrence is suggested. The aim of this review is to provide an overview of the c-miRNAs suggested as promising biomarkers for osteoporosis up until now, which could be helpful for early diagnosis and monitoring of treatment response, as well as fracture risk assessment, in osteoporotic patients.

2020 ◽  
Vol 27 ◽  
Author(s):  
Giulia De Riso ◽  
Sergio Cocozza

: Epigenetics is a field of biological sciences focused on the study of reversible, heritable changes in gene function not due to modifications of the genomic sequence. These changes are the result of a complex cross-talk between several molecular mechanisms, that is in turn orchestrated by genetic and environmental factors. The epigenetic profile captures the unique regulatory landscape and the exposure to environmental stimuli of an individual. It thus constitutes a valuable reservoir of information for personalized medicine, which is aimed at customizing health-care interventions based on the unique characteristics of each individual. Nowadays, the complex milieu of epigenomic marks can be studied at the genome-wide level thanks to massive, highthroughput technologies. This new experimental approach is opening up new and interesting knowledge perspectives. However, the analysis of these complex omic data requires to face important analytic issues. Artificial Intelligence, and in particular Machine Learning, are emerging as powerful resources to decipher epigenomic data. In this review, we will first describe the most used ML approaches in epigenomics. We then will recapitulate some of the recent applications of ML to epigenomic analysis. Finally, we will provide some examples of how the ML approach to epigenetic data can be useful for personalized medicine.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 294.2-294
Author(s):  
D. Ciardo ◽  
P. Pisani ◽  
F. A. Lombardi ◽  
R. Franchini ◽  
F. Conversano ◽  
...  

Background:The main consequence of osteoporosis is the occurrence of fractures due to bone fragility, with important sequelae in terms of disability and mortality. It has been already demonstrated that the information about bone mass density (BMD) alone is not sufficient to predict the risk of fragility fractures, since several fractures occur in patients with normal BMD [1].The Fragility Score is a parameter that allows to estimate skeletal fragility thanks to a trans-abdominal ultrasound scan performed with Radiofrequency Echographic Multi Spectrometry (REMS) technology. It is calculated by comparing the results of the spectral analysis of the patient’s raw ultrasound signals with reference models representative of fragile and non-fragile bones [2]. It is a dimensionless parameter, which can vary from 0 to 100, in proportion to the degree of fragility, independently from BMD.Objectives:This study aims to evaluate the effectiveness of Fragility Score, measured during a bone densitometry exam performed with REMS technology at lumbar spine, in identifying patients at risk of incident osteoporotic fractures at a follow-up period of 5 years.Methods:Caucasian women with age between 30 and 90 were scanned with spinal REMS and DXA. The incidence of osteoporotic fractures was assessed during a follow-up period of 5 years. The ability of the Fragility Score to discriminate between patients with and without incident fragility fractures was subsequently evaluated and compared with the discriminatory ability of the T-score calculated with DXA and with REMS.Results:Overall, 533 women (median age: 60 years; interquartile range [IQR]: 54-66 years) completed the follow-up (median 42 months; IQR: 35-56 months), during which 73 patients had sustained an incident fracture.Both median REMS and DXA measured T-score values were significantly lower in fractured patients than for non-fractured ones, conversely, REMS Fragility Score was significantly higher (Table 1).Table 1.Analysis of T-score values calculated with REMS and DXA and Fragility Score calculated with REMS. Median values and interquartile ranges (IQR) are reported. The p-value is derived from the Mann-Whitney test.Patients without incident fragility fracturePatients with incident fragility fracturep-valueT-score DXA[median (IQR)]-1.9 (-2.7 to -1.0)-2.6 (-3.3 to -1.7)0.0001T-score REMS[median (IQR)]-2.0 (-2.8 to -1.1)-2.7 (-3.5 to -1.9)<0.0001Fragility Score[median (IQR)]29.9 (25.7 to 36.2)53.0 (34.2 to 62.5)<0.0001By evaluating the capability to discriminate patients with/without fragility fractures, the Fragility Score obtained a value of the ROC area under the curve (AUC) of 0.80, higher than the AUC of the REMS T-score (0.66) and of the T-score DXA (0.64), and the difference was statistically significant (Figure 1).Figure 1.ROC curve comparison of Fragility Score, REMS and DXA T-score values in the classification of patients with incident fragility fractures.Furthermore, the correlation between the Fragility Score and the T-score values was low, with Pearson correlation coefficient r=-0.19 between Fragility Score and DXA T-score and -0.18 between the Fragility Score and the REMS T-score.Conclusion:The Fragility Score was found to be an effective tool for the prediction of fracture risk in a population of Caucasian women, with performances superior to those of the T-score values. Therefore, this tool presents a high potential as an effective diagnostic tool for the early identification and subsequent early treatment of bone fragility.References:[1]Diez Perez A et al. Aging Clin Exp Res 2019; 31(10):1375-1389.[2]Pisani P et al. Measurement 2017; 101:243–249.Disclosure of Interests:None declared


Author(s):  
Fjorda Koromani ◽  
Samuel Ghatan ◽  
Mandy van Hoek ◽  
M. Carola Zillikens ◽  
Edwin H. G. Oei ◽  
...  

Abstract Purpose of Review The purpose of this review is to summarize the recently published evidence concerning vertebral fracture risk in individuals with diabetes mellitus. Recent Findings Vertebral fracture risk is increased in individuals with T2DM. The presence of vertebral fractures in T2DM is associated with increased non-vertebral fracture risk and mortality. TBS could be helpful to estimate vertebral fracture risk in individuals with T2DM. An increased amount of bone marrow fat has been implicated in bone fragility in T2DM. Results from two recent studies show that both teriparatide and denosumab are effective in reducing vertebral fracture risk also in individuals with T2DM. Summary Individuals with T2DM could benefit from systematic screening in the clinic for presence of vertebral fractures.


2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jie Huang ◽  
Zhandong Sun ◽  
Wenying Yan ◽  
Yujie Zhu ◽  
Yuxin Lin ◽  
...  

Sepsis is regarded as arising from an unusual systemic response to infection but the physiopathology of sepsis remains elusive. At present, sepsis is still a fatal condition with delayed diagnosis and a poor outcome. Many biomarkers have been reported in clinical application for patients with sepsis, and claimed to improve the diagnosis and treatment. Because of the difficulty in the interpreting of clinical features of sepsis, some biomarkers do not show high sensitivity and specificity. MicroRNAs (miRNAs) are small noncoding RNAs which pair the sites in mRNAs to regulate gene expression in eukaryotes. They play a key role in inflammatory response, and have been validated to be potential sepsis biomarker recently. In the present work, we apply a miRNA regulatory network based method to identify novel microRNA biomarkers associated with the early diagnosis of sepsis. By analyzing the miRNA expression profiles and the miRNA regulatory network, we obtained novel miRNAs associated with sepsis. Pathways analysis, disease ontology analysis, and protein-protein interaction network (PIN) analysis, as well as ROC curve, were exploited to testify the reliability of the predicted miRNAs. We finally identified 8 novel miRNAs which have the potential to be sepsis biomarkers.


2019 ◽  
Vol 57 (7) ◽  
pp. 932-953 ◽  
Author(s):  
Alessandro Terrinoni ◽  
Cosimo Calabrese ◽  
Daniela Basso ◽  
Ada Aita ◽  
Sabrina Caporali ◽  
...  

Abstract A large portion of the human genome transcribes RNA sequences that do not code for any proteins. The first of these sequences was identified in 1993, and the best known noncoding RNAs are microRNA (miRNAs). It is now fully established that miRNAs regulate approximately 30% of the known genes that codify proteins. miRNAs are involved in several biological processes, like cell proliferation, differentiation, apoptosis and metastatization. These RNA products regulate gene expression at the post-transcriptional level, modulating or inhibiting protein expression by interacting with specific sequences of mRNAs. Mature miRNAs can be detected in blood plasma, serum and also in a wide variety of biological fluids. They can be found associated with proteins, lipids as well as enclosed in exosome vesicles. We know that circulating miRNAs (C-miRNAs) can regulate several key cellular processes in tissues different from the production site. C-miRNAs behave as endogenous mediators of RNA translation, and an extraordinary knowledge on their function has been obtained in the last years. They can be secreted in different tissue cells and associated with specific pathological conditions. Significant evidence indicates that the initiation and progression of several pathologies are “highlighted” by the presence of specific C-miRNAs, underlining their potential diagnostic relevance as clinical biomarkers. Here we review the current literature on the possible use of this new class of molecules as clinical biomarkers of diseases.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fumikazu Hayashi ◽  
◽  
Tetsuya Ohira ◽  
Hironori Nakano ◽  
Masanori Nagao ◽  
...  

Abstract Background It has been reported that psychological stress affects bone metabolism and increases the risk of fracture. However, the relationship between bone fractures and post-traumatic stress disorder (PTSD) is unclear. This study aimed to evaluate the effects of disaster-induced PTSD symptoms on fracture risk in older adults. Methods This study evaluated responses from 17,474 individuals aged ≥ 65 years without a history of fractures during the Great East Japan Earthquake who answered the Mental Health and Lifestyle Survey component of the Fukushima Health Management Survey conducted in 2011. The obtained data could determine the presence or absence of fractures until 2016. Age, sex, physical factors, social factors, psychological factors, and lifestyle factors were subsequently analyzed. Survival analysis was then performed to determine the relationship between the fractures and each factor. Thereafter, univariate and multivariate Cox proportional hazard models were constructed to identify fracture risk factors. Results In total, 2,097 (12.0%) fractures were observed throughout the follow-up period. Accordingly, univariate and multivariate Cox proportional hazard models showed that PTSD symptoms (total PTSD checklists scoring ≥ 44) [hazard ratio (HR): 1.26; 95% confidence interval (CI): 1.10–1.44; P = 0.001], history of cancer (HR: 1.49; 95% CI: 1.24–1.79; P < 0.001), history of stroke (HR: 1.25; 95% CI: 1.03–1.52; P = 0.023), history of heart disease (HR: 1.30; 95% CI: 1.13–1.50; P < 0.001), history of diabetes (HR: 1.23; 95% CI: 1.09–1.39; P < 0.001), current smoking (HR: 1.29; 95% CI: 1.02–1.63; P = 0.036), and high dissatisfaction with sleep or no sleep at all (HR: 1.33; 95% CI: 1.02–1.74; P = 0.035) promoted a significant increase in fracture risk independent of age and sex. Conclusions The present study indicates that disaster-induced PTSD symptoms and insomnia contribute to increased fracture risk among older adults residing in evacuation areas within the Fukushima Prefecture.


2019 ◽  
Vol 20 (5) ◽  
pp. 1836-1852 ◽  
Author(s):  
Liang Chen ◽  
Liisa Heikkinen ◽  
Changliang Wang ◽  
Yang Yang ◽  
Huiyan Sun ◽  
...  

Abstract MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via recognition of cognate sequences and interference of transcriptional, translational or epigenetic processes. Bioinformatics tools developed for miRNA study include those for miRNA prediction and discovery, structure, analysis and target prediction. We manually curated 95 review papers and ∼1000 miRNA bioinformatics tools published since 2003. We classified and ranked them based on citation number or PageRank score, and then performed network analysis and text mining (TM) to study the miRNA tools development trends. Five key trends were observed: (1) miRNA identification and target prediction have been hot spots in the past decade; (2) manual curation and TM are the main methods for collecting miRNA knowledge from literature; (3) most early tools are well maintained and widely used; (4) classic machine learning methods retain their utility; however, novel ones have begun to emerge; (5) disease-associated miRNA tools are emerging. Our analysis yields significant insight into the past development and future directions of miRNA tools.


2011 ◽  
Vol 38 (8) ◽  
pp. 1671-1679 ◽  
Author(s):  
ELISABETTA ROMAGNOLI ◽  
ROMANO DEL FIACCO ◽  
STEFANIA RUSSO ◽  
SARA PIEMONTE ◽  
FRANCESCA FIDANZA ◽  
...  

Objective.To evaluate the clinical and etiological factors of osteoporosis. We also tested the FRAX algorithm to compare the assessment of fracture risk in patients with primary or secondary osteoporosis.Methods.A prospective study carried out in a large sample of 123 men and 246 women. All subjects had a biochemical, densitometric, and radiological examination of thoracic and lumbar spine.Results.The prevalence of primary (men 52.9% vs women 50%; p = nonsignificant) and secondary (men 21.1% vs women 17.5%; p = nonsignificant) osteoporosis did not differ between the sexes. In contrast, the prevalence of primary osteoporosis was significantly higher than secondary causes (p < 0.0001) in both men and women. While women came to our attention for prevention of osteoporosis, men sought help because of clinical symptoms or disease-related complications, such as fractures. As evaluated by the FRAX tool, patients with osteopenia do not need treatment, in agreement with Italian guidelines. The estimated risk of major osteoporotic and hip fractures was significantly higher in women with secondary osteoporosis compared to men and also compared to women with primary osteoporosis.Conclusion.The prevalence of secondary osteoporosis in men is similar to that in women and it is less frequent than commonly reported. In patients with secondary osteoporosis, FRAX calculation may provide an estimate of a particularly high fracture risk in patients whose bone fragility is usually attributed to another disease.


Biosensors ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 63
Author(s):  
Elba Mauriz

The monitoring of biomarkers in body fluids provides valuable prognostic information regarding disease onset and progression. Most biosensing approaches use noninvasive screening tools and are conducted in order to improve early clinical diagnosis. However, biofouling of the sensing surface may disturb the quantification of circulating biomarkers in complex biological fluids. Thus, there is a great need for antifouling interfaces to be designed in order to reduce nonspecific adsorption and prevent inactivation of biological receptors and loss of sensitivity. To address these limitations and enable their application in clinical practice, a variety of plasmonic platforms have been recently developed for biomarker analysis in easily accessible biological fluids. This review presents an overview of the latest advances in the design of antifouling strategies for the detection of clinically relevant biomarkers on the basis of the characteristics of biological samples. The impact of nanoplasmonic biosensors as point-of-care devices has been examined for a wide range of biomarkers associated with cancer, inflammatory, infectious and neurodegenerative diseases. Clinical applications in readily obtainable biofluids such as blood, saliva, urine, tears and cerebrospinal and synovial fluids, covering almost the whole range of plasmonic applications, from surface plasmon resonance (SPR) to surface-enhanced Raman scattering (SERS), are also discussed.


2020 ◽  
Vol 7 (4) ◽  
pp. 125
Author(s):  
Yuliya Safarova (Yantsen) ◽  
Farkhad Olzhayev ◽  
Bauyrzhan Umbayev ◽  
Andrey Tsoy ◽  
Gonzalo Hortelano ◽  
...  

Osteoporosis is a progressive skeletal disease characterized by reduced bone density leading to bone fragility and an elevated risk of bone fractures. In osteoporotic conditions, decrease in bone density happens due to the augmented osteoclastic activity and the reduced number of osteoblast progenitor cells (mesenchymal stem cells, MSCs). We investigated a new method of cell therapy with membrane-engineered MSCs to restore the osteoblast progenitor pool and to inhibit osteoclastic activity in the fractured osteoporotic bones. The primary active sites of the polymer are the N-hydroxysuccinimide and bisphosphonate groups that allow the polymer to covalently bind to the MSCs’ plasma membrane, target hydroxyapatite molecules on the bone surface and inhibit osteolysis. The therapeutic utility of the membrane-engineered MSCs was investigated in female rats with induced estrogen-dependent osteoporosis and ulnar fractures. The analysis of the bone density dynamics showed a 27.4% and 21.5% increase in bone density at 4 and 24 weeks after the osteotomy of the ulna in animals that received four transplantations of polymer-modified MSCs. The results of the intravital observations were confirmed by the post-mortem analysis of histological slices of the fracture zones. Therefore, this combined approach that involves polymer and cell transplantation shows promise and warrants further bio-safety and clinical exploration.


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