This post is part of a series on bone markers standardization from the Committee on Bone Metabolism of the International Federation of Clinical Chemistry.


Bone modelling and remodeling are time- and space-dependent processes involving sequential resorption-formation cycles that occur in discrete packets identified as short-lived basic multicellular units (BMUs), described by Harold Frost in 1987 (1). They implicate the differentiation and maturation of bone marrow-derived osteoclasts and of mesenchymal stroma-derived osteoblasts. This implies that vast arrays of genes are modulated to either enhance or repress the transcription and translation of specific factors and structural proteins (2). 

Regulation of gene expression comprises a wide range of transcriptional and post-transcriptional mechanisms. Among the latter, the three main epigenetic pathways namely histone deacetylation, deoxyribonucleic acid (DNA) methylation, and micro-ribonucleic acids (mi-RNAs), the focus of the present short opinion paper, are important in cell growth, differentiation and function, including bone (3). 

Dual energy X-ray absorptiometry and Biochemical markers in osteoporosis 

Osteoporosis, stemming from a progressive silent process of bone loss, inevitably leads to increased risk of fractures. Dual energy X-ray absorptiometry (DXA), providing an overall estimate of bone mineral density (BMD) and bone mineral content (BMC), is recognized a cornerstone technology in the diagnosis and follow-up of osteoporosis, and evaluation of fracture risk. However it may take several months before radiological abnormalities before observable. Hence information on more short-term changes (weeks) in bone physiology has been sought (2). 

Bone turnover markers (BTMs) can provide such additional information particularly the N-terminal propeptide of type I procollagen (PINP) and the C-terminal cross-linked telopeptide of type-I collagen (β-CTX), respectively markers of bone formation and resorption, afford a snapshot vision of the current bone metabolic status. Moreover, these indubitably useful complementary markers can discriminate between low- and high-turnover osteoporosis; elevated circulating concentrations suggesting a high turnover provoked by a secondary cause such as metastases, and low concentrations suggesting slowed-down bone cell metabolic activity (4). Bone-turnover index (BTI), obtained by subtracting age- and sex-adjusted β-CTX Z-scores from PINP Z-scores, is also helpful in assessing the overall bone metabolic status (5). Although, on their own, BTMs are not fit for diagnosing osteoporosis or for predicting fracture risk, their prognostic value is enhanced by their inclusion into ad hoc FRAX algorithms that integrate patients’ anthropometric and behavioral characteristics (4).  

Do miRNAs improve the diagnosis bone diseases and the monitoring of their treatment? 

Precocious detection of diseases is a constant quest as it would allow early intervention and improve the outcome represents a major challenge. De Guire et al. (6) have provided an excellent review on the promises and challenges related to the use of circulating miRNAs as biomarkers for the diagnosis and follow-up of diseases. Borrowing the cardinal features of a novel biomarker from the cardiovascular field, to have a clinical utility it should be reliably measurable, add or improve information and influence the monitoring and management of patients (7)(see previously published Scientific Short: MicroRNAs as potential biomarkers: Is the future here?). Hence, in the context of osteoporosis, could recent development in the realm of miRNAs biology offer effective tools for predicting fracture risk and change the treatment strategy?  

The advantages of miRNAs are that they represent the epigenetic environment of gene expression in a particular condition, that they are accessible in different biological fluids, that they are easily and reproducibly measurable and that they are stable. Their measurement however are submitted, as other biological variables, to the potential pre-analytical, analytical and post-analytical sources of error (3). The list of miRNAs potentially useful in the diagnosis of bone diseases, either primary or secondary, is extensive and has recently been reviewed (3, 8). Of interest, in one recently reported clinical study, plasma miR-24-3p levels were higher in primary hyperparathyroid (PHPT) women who experienced osteoporotic fractures than those without fractures. Also, miR-93-5 permitted distinguishing estrogen-related from PHPT-related osteoporosis (9). As of today, miRNA-133a, involved in RANKL-mediated osteoclastogenesis, is the most promising diagnostic and therapeutic target specie associated with post-menopausal osteoporosis (10). 


miRNAs possess a definite potential in terms of signatures of specific bone diseases, but the clinical utility is still to be demonstrated, as the knowledge is embryonic. Furthermore, the way to their clinical usage is paved with several issues that need to be overcome: 1) standardization of the pre-analytical phase, 2) harmonization of the post-analytical phase, and 3) standardization of the validation stage (3).  



  1. Frost HM. Bone "mass" and the "mechanostat": a proposal. Anat Rec 1987;219(1):1-9. 
  2. Szulc P. Bone turnover: Biology and assessment tools. Best Pract Res Clin Endocrinol Metabol 2018;32(5):725-38. 
  3. Bottani M, Banfi G, Lombardi G. Perspectives on miRNAs as Epigenetic Markers in Osteoporosis and Bone Fracture Risk: A Step Forward in Personalized Diagnosis. Front Genetics 2019;10:1044. 
  4. Eastell R, Szulc P. Use of bone turnover markers in postmenopausal osteoporosis. Lancet Diabetes Endocrinol 2017;5(11):908-23. 
  5. Delvin E, Alos N, Rauch F, Marcil V, Morel S, Boisvert M, et al. Vitamin D nutritional status and bone turnover markers in childhood acute lymphoblastic leukemia survivors: A PETALE study. Clin Nutr 2019;38(2):912-9. 
  6. De Guire V, Robitaille R, Tétreault N, Guérin R, Ménard C, Bambace N, et al. Circulating miRNAs as sensitive and specific biomarkers for the diagnosis and monitoring of human diseases: promises and challenges. Clin Biochem 2013;46(10-11):846-60. 
  7. Morrow DA, de Lemos JA. Benchmarks for the assessment of novel cardiovascular biomarkers. Circulation 2007;115(8):949-52. 
  8. Bottani M, Banfi G, Lombardi G. The Clinical Potential of Circulating miRNAs as Biomarkers: Present and Future Applications for Diagnosis and Prognosis of Age-Associated Bone Diseases. Biomolecules 2020;10(4). 
  9. Verdelli C, Sansoni V, Perego S, Favero V, Vitale J, Terrasi A, et al. Circulating fractures-related microRNAs distinguish primary hyperparathyroidism-related from estrogen withdrawal-related osteoporosis in postmenopausal osteoporotic women: A pilot study. Bone 2020;137:115350. 
  10. Li Z, Zhang W, Huang Y. MiRNA-133a is involved in the regulation of postmenopausal osteoporosis through promoting osteoclast differentiation. Acta Biochim Biophys Sinica 2018;50(3):273-80.