OSTEOPOROSIS: Genetic Risk Factors in the New Therapies. Challenges for Personalized Treatments
Main Article Content
Abstract
The word osteoporosis means “porous bone” a disease that is defined as a skeletal disorder characterized by alterations in its microarchitecture making the bones more porous and less dense, leading to a decrease in bone strength, generating a greater risk of fractures.
It is a disease considered among the greatest public health problems in the elderly population worldwide, affecting women to a greater extent; around a third of women suffer from osteoporosis and one in eight men over 50 years of age.
Known as a silent disease because significant signs do not appear before fractures appear, so in most cases, people realize they have osteoporosis until they suffer a fracture. Osteoporotic fractures have various risk factors, from low physical activity, smoking, and the use of certain drugs, as well as genetic variations that have been associated with diverse types of fractures.
There is a considerable group of drugs to treat the disease, however, management is only focused on monotherapy according to the quantitative value of a phenotype (BMD) bone mineral density. It has never focused on individual pathophysiology, since it was unknown. The main treatment guidelines for osteoporosis include a bisphosphonate and it is maintained for years depending on response, in addition to lifestyle and dietary recommendations. However, a controversial aspect is the low response to treatment, which is accompanied by poor adherence to treatments.
The new drugs that have more intense and prolonged effects are expensive and are not available in most countries. Much progress has been made in terms of knowledge of the factors that contribute to the development of this and other pathologies. Diversity of variations in the genome has been implicated both in the development of the disease and in the response to pharmacological treatments.
Many of these variations in the genome and its expression represent part of the genetic factors that contribute to the development of the disease. They are now important biomarkers that allow us to better understand and develop more specific drugs or individualized schemes with those already existing. There are already various scores and indications of first guidelines on how to quantify these factors, such as the Polygenic Risk Score (PRS) or Mendelian Randomization (MR). However, there is still a need to analyze and expand the perspectives of how the factors involved interact without being specifically additive/summative, and the difficulties that this face have already been observed.
The aims of this brief review are to discuss shortly the actual drugs approved for osteoporosis by the main treatment guidelines. The advances in molecular biology studies that support the importance of genetic factors in risk and response to osteoporosis treatment.
Keywords:
Osteoporosis, Risk Factors, Classic and New Treatments, Challenges in Treatments
Article Details
How to Cite
VILLAGOMEZ-VEGA, Alejandra; NUÑO-ARANA, Ismael.
OSTEOPOROSIS: Genetic Risk Factors in the New Therapies. Challenges for Personalized Treatments.
Medical Research Archives, [S.l.], v. 13, n. 4, apr. 2025.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/6413>. Date accessed: 15 may 2025.
doi: https://doi.org/10.18103/mra.v13i4.6413.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
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3. He J, Xu S, Zhang B, et al. Gut microbiota and metabolite alterations associated with reduced bone mineral density or bone metabolic indexes in postmenopausal osteoporosis. Aging (Albany NY). 2020;12(9):8583-8604. doi:10.18632/aging.103168
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5. Muñoz M, Robinson K, Shibli-Rahhal A. Bone Health and Osteoporosis Prevention and Treatment. Clin Obstet Gynecol. 2020;63(4):770-787. doi:10.1097/ GRF.0000000000000572
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8. Garnero P. Biomarkers for osteoporosis management: utility in diagnosis, fracture risk prediction and therapy monitoring. Mol Diagn Ther. 2008;12(3):157-170. doi:10.1007/BF03256280
9. Migliorini F, Maffulli N, Spiezia F, Tingart M, Maria PG, Riccardo G. Biomarkers as therapy monitoring for postmenopausal osteoporosis: a systematic review. J Orthop Surg Res. 2021 May 18;16(1):318. doi: 10.1186/s13018-021-02474-7. PMID: 34006294; PMCID: PMC8130375.
10. Morales-Santana S, Díez-Pérez A, Olmos JM, et al. Circulating sclerostin and estradiol levels are associated with inadequate response to bisphosphonates in postmenopausal women with osteoporosis. Maturitas. 2015;82(4):402-410. doi:10.1016/j.maturitas.2015.08.007
11. Marozik P, Alekna V, Rudenko E, et al. Bone metabolism genes variation and response to bisphosphonate treatment in women with postmenopausal osteoporosis. PLoS One. 2019;14(8):e0221511. Published 2019 Aug 22. doi:10.1371/journal.pone.0221511
12. Srivastava RK, Sapra L. The Rising Era of "Immunoporosis": Role of Immune System in the Pathophysiology of Osteoporosis. J Inflamm Res. 2022;15:1667-1698. Published 2022 Mar 5. doi:10.2147/JIR.S351918
13. Chen H, Senda T, Kubo KY. The osteocyte plays multiple roles in bone remodeling and mineral homeostasis. Med Mol Morphol. 2015;48(2):61-68. doi:10.1007/s00795-015-0099-y
14. Nakashima T. Clin Calcium. 2015;25(1):21-28.
15. Siddiqui JA, Partridge NC. Physiological Bone Remodeling: Systemic Regulation and Growth Factor Involvement. Physiology (Bethesda). 2016;31(3):233-245. doi:10.1152/physiol.00061.2014
16. Weitzmann MN. Bone and the Immune System. Toxicol Pathol. 2017;45(7):911-924. doi:10.1177/0192623317735316
17. Horton JE, Raisz LG, Simmons HA, Oppenheim JJ, Mergenhagen SE. Bone resorbing activity in supernatant fluid from cultured human peripheral blood leukocytes. Science. 1972;177(4051):793-795. doi:10.1126/science.177.4051.793
18. Nakashima T, Takayanagi H. Osteoimmunology: crosstalk between the immune and bone systems. J Clin Immunol. 2009;29(5):555-567. doi:10.1007/s10875-009-9316-6
19. Srivastava RK, Dar HY, Mishra PK. Immunoporosis: Immunology of Osteoporosis-Role of T Cells. Front Immunol. 2018;9:657. Published 2018 Apr 5. doi:10.3389/fimmu.2018.00657
20. Khalid AB, Krum SA. Estrogen receptors alpha and beta in bone. Bone. 2016;87:130-135. doi:10.1016/j.bone.2016.03.016
21. Xia B, Li Y, Zhou J, Tian B, Feng L. Identification of potential pathogenic genes associated with osteoporosis. Bone Joint Res. 2017;6(12):640-648. doi:10.1302/2046-3758.612.BJR-2017-0102.R1
22. Aspray TJ, Hill TR. Osteoporosis and the Ageing Skeleton. Subcell Biochem. 2019;91:453-476. doi:10.1007/978-981-13-3681-2_16
23. Clark GR, Duncan EL. The genetics of osteoporosis. Br Med Bull. 2015;113(1):73-81. doi:10.1093/bmb/ldu042
24. Rocha-Braz MG, Ferraz-de-Souza B. Genetics of osteoporosis: searching for candidate genes for bone fragility. Arch Endocrinol Metab. 2016;60(4):391-401. doi:10.1590/2359-3997000000178
25. Zhu X, Bai W, Zheng H. Twelve years of GWAS discoveries for osteoporosis and related traits: advances, challenges and applications. Bone Res. 2021;9(1):23. Published 2021 Apr 29. doi:10.1038/s41413-021-00143-3
26. Richards JB, Kavvoura FK, Rivadeneira F, et al. Collaborative meta-analysis: associations of 150 candidate genes with osteoporosis and osteoporotic fracture. Ann Intern Med. 2009;151(8):528-537. doi:10.7326/0003-4819-151-8-200910200-00006
27. Morris JA, Kemp JP, Youlten SE, et al. An atlas of genetic influences on osteoporosis in humans and mice [published correction appears in Nat Genet. 2019 May;51(5):920. doi: 10.1038/s41588-019-0415-x.]. Nat Genet. 2019;51(2):258-266. doi:10.1038/s41588-018-0302-x
28. Riancho JA, Sañudo C, Valero C, et al. Association of the aromatase gene alleles with BMD: epidemiological and functional evidence. J Bone Miner Res. 2009;24(10):1709-1718. doi:10.1359/jbmr.090404
29. Urano T, Inoue S. Genetics of osteoporosis. Biochem Biophys Res Commun. 2014;452(2):287-293. doi:10.1016/j.bbrc.2014.07.141
30. Zupan J, Mencej-Bedrac S, Jurković-Mlakar S, Prezelj J, Marc J. Gene-gene interactions in RANK/RANKL/OPG system influence bone mineral density in postmenopausal women. J Steroid Biochem Mol Biol. 2010;118(1-2):102-106. doi:10.1016/j.jsbmb.2009.10.013
31. Moffett, S., Oakley, J., Cauley, J., Lui, L., Ensrud, K., Taylor, B., et. al.(2008). Osteoprotegerin Lys3Asn Polymorphism and the Risk of Fracture in Older Women. J Clin Endocrinol Metab., 93(5):2002–2008. doi: 10.1210/jc.2007-1019
32. Vilariño-Güell C, Miles LJ, Duncan EL, et al. PTHR1 polymorphisms influence BMD variation through effects on the growing skeleton. Calcif Tissue Int. 2007;81(4):270-278. doi:10.1007/s00223-007-9072-7
33. Xiao X, Roohani D, Wu Q. Genetic profiling of decreased bone mineral density in an independent sample of Caucasian women. Osteoporos Int. 2018;29(8):1807-1814. doi:10.1007/s00198-018-4546-1
34. Styrkarsdottir U, Halldorsson BV, Gretarsdottir S, et al. Multiple genetic loci for bone mineral density and fractures. N Engl J Med. 2008;358(22):2355-2365. doi:10.1056/NEJMoa0801197
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