About this Research Topic
Bone mass and strength are determined by genetic and environmental factors. Conditions like osteoporosis, characterized by low bone mass, pose significant global health challenges, particularly among aging populations. Biomarkers play a crucial role in diagnosing and managing these conditions as they provide valuable information on bone health and turnover. Biomarkers are measurable indicators that reflect bone metabolism, such as proteins involved in bone formation and resorption, bone cell activity markers, and bone degradation products. By analyzing these biomarkers, healthcare professionals can assess bone health, predict fracture risk, and monitor treatment effectiveness. Incorporating biomarkers into clinical practice improves diagnose accuracy, enables personalized treatment strategies, and enhances bone-related condition management.
Biomarkers such as Sclerostin, Dickkopf-1 (DKK1), Osteoprotegerin (OPG), C-terminal telopeptide of type I collagen (CTX), Procollagen 1 intact N-terminal propeptide (P1NP), Osteocalcin, Fibroblast growth factor 23 (FGF23), and Bone-specific alkaline phosphatase (BALP) have been identified for bone mass regulation and other bone pathologies. These biomarkers hold promise for the development of diagnostic and therapeutic tools for various bone conditions. However, further scientific investigation is required to discover novel and essential biomarkers that control bone mass and strength. It is crucial to validate their utility in clinical practice to enhance bone-related diseases prevention, treatment, and cure. Advancing our understanding of these biomarkers can significantly contribute to the scientific knowledge and medical management of bone mass-related disorders.
Typical themes include but are not limited to:
1. Animal models: Animal models of bone diseases used to identify novel biomarkers associated with bone conditions. Comparison of genetic (or epigenetic), and proteomic profiles of control and experimental animals to identify candidate biomarkers.
2. Genomic, proteomic, and metabolic approaches: Analysis of the genetic (or epigenetic), proteomic and metabolic profiles of individuals with bone diseases to identify candidate genes and proteins associated with these conditions.
3. High-throughput platforms: Microarrays and next-generation sequencing, used to identify novel biomarkers for bone diseases by profiling the gene and protein expression levels of large numbers of individuals with these conditions.
4. Data mining: Analysis of large datasets of clinical and genetic information, to identify novel biomarkers associated with bone diseases. It may help identify new targets for drug development and personalized medicine.
5. Imaging techniques: Any advances in imaging techniques, such as magnetic resonance imaging (MRI) and computed tomography (CT) that provide valuable information about bone tissue structural and functional changes.
Biomarkers such as Sclerostin, Dickkopf-1 (DKK1), Osteoprotegerin (OPG), C-terminal telopeptide of type I collagen (CTX), Procollagen 1 intact N-terminal propeptide (P1NP), Osteocalcin, Fibroblast growth factor 23 (FGF23), and Bone-specific alkaline phosphatase (BALP) have been identified for bone mass regulation and other bone pathologies. These biomarkers hold promise for the development of diagnostic and therapeutic tools for various bone conditions. However, further scientific investigation is required to discover novel and essential biomarkers that control bone mass and strength. It is crucial to validate their utility in clinical practice to enhance bone-related diseases prevention, treatment, and cure. Advancing our understanding of these biomarkers can significantly contribute to the scientific knowledge and medical management of bone mass-related disorders.
Typical themes include but are not limited to:
1. Animal models: Animal models of bone diseases used to identify novel biomarkers associated with bone conditions. Comparison of genetic (or epigenetic), and proteomic profiles of control and experimental animals to identify candidate biomarkers.
2. Genomic, proteomic, and metabolic approaches: Analysis of the genetic (or epigenetic), proteomic and metabolic profiles of individuals with bone diseases to identify candidate genes and proteins associated with these conditions.
3. High-throughput platforms: Microarrays and next-generation sequencing, used to identify novel biomarkers for bone diseases by profiling the gene and protein expression levels of large numbers of individuals with these conditions.
4. Data mining: Analysis of large datasets of clinical and genetic information, to identify novel biomarkers associated with bone diseases. It may help identify new targets for drug development and personalized medicine.
5. Imaging techniques: Any advances in imaging techniques, such as magnetic resonance imaging (MRI) and computed tomography (CT) that provide valuable information about bone tissue structural and functional changes.
Keywords: Biomarkers, Bone mass, Bone Strength, Bone Health, Bone Physiology, Bone Pathology, Bone Diseases, Diagnostic Tools
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