Osteoporosis: now and the future
Open accessAbstract
Osteoporosis is a common disease characterised by a systemic impairment of bone mass and microarchitecture that results in fragility fractures. With an ageing population, the medical and socioeconomic effect of osteoporosis, particularly postmenopausal osteoporosis, will increase further. A detailed knowledge of bone biology with molecular insights into the communication between bone-forming osteoblasts and bone-resorbing osteoclasts and the orchestrating signalling network has led to the identification of novel therapeutic targets. Novel treatment strategies have been developed that aim to inhibit excessive bone resorption and increase bone formation. The most promising novel treatments include: denosumab, a monoclonal antibody for receptor activator of NF-κB ligand, a key osteoclast cytokine; odanacatib, a specific inhibitor of the osteoclast protease cathepsin K; and antibodies against the proteins sclerostin and dickkopf-1, two endogenous inhibitors of bone formation. This overview discusses these novel therapies and explains their underlying physiology.
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Bone ageing is a major risk factor for primary osteoporosis, an age-related disease characterised by altered bone metabolism that suppresses bone formation and promotes bone resorption, impairing bone homoeostasis.
“Bone ageing is major risk factor for primary osteoporosis, an age-related disease characterised by altered bone metabolism that suppresses bone formation and promotes bone resorption, 91 impairing bone homoeostasis.92”
From The costs and benefits of senotherapeutics for human health (2022) · cites this paper as [91]
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- Authors
- Rachner, T. D., Khosla, S., & Hofbauer, L. C.
- Affiliations
- Technische Universität Dresden (DE)
- Mayo Clinic (US)
- Center for Regenerative Therapies Dresden (DE)
- Corresponding author
- Hofbauer, Lorenz C
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 377
- Issue
- 9773
- Pages
- 1276-1287
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- PMC
- PMC3555696
- OpenAlex
- W2123346255
- Cited by
- 2,696
- References
- 93
- Citations by year
- 2026: 161 · 2025: 239 · 2024: 252 · 2023: 256 · 2022: 230 · 2021: 217 · 2020: 194 · 2019: 166 · 2018: 174 · 2017: 116 · 2016: 142 · 2015: 145 · 2014: 132 · 2013: 108 · 2012: 123
- FWCI
- 22.18
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (1875/12-1, 1875/13-1, HO 1875/8-1, Transregio-67 (B2)
- Topics
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Bone health and osteoporosis research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bone Metabolism and Diseases
- Health Sciences › Medicine › Oncology › Bone health and treatments
- Keywords
- osteoporosis, postmenopausal osteoporosis, bone fragility, bone resorption, bone formation, osteoblasts, osteoclasts, RANKL, denosumab, odanacatib, cathepsin K, sclerostin, DKK1, anti-osteoporotic therapy, bone biology, population aging
- MeSH terms
- Denosumab, Aged, Aged, 80 and over, Antibodies, Monoclonal, Biphenyl Compounds, Bone Resorption, Calcium, Diphosphonates, Female, Genetic Markers, Humans, Middle Aged, Osteoblasts, Osteoclasts, Osteoporosis, Quinazolines, Risk Factors, Vitamin D Deficiency, Absorptiometry, Photon, Bone Density, Osteoporosis, Postmenopausal, Randomized Controlled Trials as Topic, Bone Remodeling, Risk Assessment, Bone Morphogenetic Proteins, Intercellular Signaling Peptides and Proteins, Anabolic Agents, Adaptor Proteins, Signal Transducing, Bone Density Conservation Agents, Wnt Proteins, Benzodioxoles, RANK Ligand, Osteoporotic Fractures, Antibodies, Monoclonal, Humanized
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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