Kas-İskelet Sistemi ve Hastalıklarında Güncel Genetik Özellikler
Özet
Kas-iskelet sistemi ile ilgili genetik araştırmalar sistemin gelişimi ve hastalıkları üzerine yoğunlaşmıştır. Gelişim ile ilgili genetik araştırmalar hücre dizileme tekniği, proteomik çalışmaları, tek hücre dizileme yöntemi hücre dizileme yöntemi, transkriptomik ve metabolomik yöntemleri kullanılarak yapılmakta ve kas-iskelet sisteminde etkili genlerin yapısı ve diğer gen ve proteinlerle olan etkileşimlerine odaklanmaktadır. Kas-iskelet sisteminin hastalıkları ile ilgili olan genetik araştırmalar ise kanserler, romatoid artrit, intervertebral disk bozuklukları ve osteoartrit üzerinde yoğunlaşmaktadır. Kas-iskelet sisteminin genetik arka planı ile ilgili yapılan araştırmalardaki ana hedef mutasyonların hastalıklarla olan ilişkilerini açığa çıkarmaktır. Bilinen genomik mutasyonlara ek olarak son yıllarda özellikle epigenetik mekanizmalar da araştırma konusu edilmektedir. Doğumsal defektlerin yanında yetişkinlikte de epigenetik mekanizmalar oldukça etkili olmaktadır. Diğer yandan elde edilmiş olan genetik verilen en sağlıklı şekilde değerlendirilmesinin sağlanması gerek tanı gerekse de tedavide etkili olarak kullanılması amacıyla biyoinformatik yönden de kapsamlı araştırmaların gelecekte yapılması gerekmektedir.
Genetic studies on the musculoskeletal system focus on the development and diseases of the system. These studies utilize various techniques such as cell sequencing, proteomics, single cell sequencing, transcriptomics, and metabolomics to examine the structure of genes involved in the musculoskeletal system and their interactions with other genes and proteins. The diseases studied mainly include cancers, rheumatoid arthritis, intervertebral disc disorders, and osteoarthritis. The primary objective of these studies is to uncover the connections between genetic mutations and diseases. In addition to known genomic mutations, recent research has also focused on epigenetic mechanisms. These mechanisms not only play a role in congenital defects, but also have a significant impact on adult health. Furthermore, it is crucial to conduct comprehensive bioinformatics research in the future to ensure that genetic data is evaluated accurately and effectively used for both diagnosis and treatment.
Referanslar
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Referanslar
Del Real A, Riancho-Zarrabeitia L, López-Delgado L, et al. Epigenetics of Skeletal Diseases. Current Osteoporosis Reports. 2018;16(3): 246–255. doi:10.1007/s11914-018-0435-y
Barker DJP. The origins of the developmental origins theory. Journal of Internal Medicine. 2007;261(5): 412–417. doi:10.1111/j.1365-2796.2007.01809.x
Wood CL, Stenson C, Embleton N. The Developmental Origins of Osteoporosis. Current Genomics. 2015;16(6): 411–418. doi:10.2174/1389202916666150817202217
Mikkola TM, von Bonsdorff MB, Osmond C, et al. Childhood growth predicts higher bone mass and greater bone area in early old age: findings among a subgroup of women from the Helsinki Birth Cohort Study. Osteoporosis international: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2017;28(9): 2717–2722. doi:10.1007/s00198-017-4048-6
Zhu K, Whitehouse AJO, Hart PH, et al. Maternal vitamin D status during pregnancy and bone mass in offspring at 20 years of age: a prospective cohort study. Journal of Bone and Mineral Research: The Official Journal of the American Society for Bone and Mineral Research. 2014;29(5): 1088–1095. doi:10.1002/jbmr.2138
Curtis EM, Murray R, Titcombe P, et al. Perinatal DNA Methylation at CDKN2A Is Associated With Offspring Bone Mass: Findings From the Southampton Women’s Survey. Journal of Bone and Mineral Research. 2017;32(10): 2030–2040. doi:10.1002/jbmr.3153
Gnoli M, Pedrini E, Mordenti M, et al. Skeletal dysplasias: approach to the clinical diagnosis and implication of appropriate diagnosis for knowledge and research studies in these rare diseases. Hereditary multiple Osteochondromas as example/paradigm. Italian Journal of Pediatrics. 2014;40(1): A8. doi:10.1186/1824-7288-40-S1-A8
Carter LE, Kilroy G, Gimble JM, et al. An improved method for isolation of RNA from bone. BMC biotechnology. 2012;12: 5. doi:10.1186/1472-6750-12-5
Le Bleu HK, Kamal FA, Kelly M, et al. Extraction of high-quality RNA from human articular cartilage. Analytical Biochemistry. 2017;518: 134–138. doi:10.1016/j.ab.2016.11.018
Grinstein M, Dingwall HL, Shah RR, et al. A robust method for RNA extraction and purification from a single adult mouse tendon. PeerJ. 2018;6: e4664. doi:10.7717/peerj.4664
Debnath S, Yallowitz AR, McCormick J, et al. Discovery of a periosteal stem cell mediating intramembranous bone formation. Nature. 2018;562(7725): 133–139. doi:10.1038/s41586-018-0554-8
Bueno MJ, Pérez de Castro I, Gómez de Cedrón M, et al. Genetic and epigenetic silencing of microRNA-203 enhances ABL1 and BCR-ABL1 oncogene expression. Cancer Cell. 2008;13(6): 496–506. doi:10.1016/j.ccr.2008.04.018
Chen L, Wang Q, Wang G, et al. miR-16 inhibits cell proliferation by targeting IGF1R and the Raf1-MEK1/2-ERK1/2 pathway in osteosarcoma. FEBS letters. 2013;587(9): 1366–1372. doi:10.1016/j.febslet.2013.03.007
Chen R, Wang G, Zheng Y, et al. Long non-coding RNAs in osteosarcoma. Oncotarget. 2017;8(12): 20462–20475. doi:10.18632/oncotarget.14726
Heuck CJ, Mehta J, Bhagat T, et al. Myeloma is characterized by stage-specific alterations in DNA methylation that occur early during myelomagenesis. Journal of Immunology (Baltimore, Md.: 1950). 2013;190(6): 2966–2975. doi:10.4049/jimmunol.1202493
Mithraprabhu S, Kalff A, Chow A, et al. Dysregulated Class I histone deacetylases are indicators of poor prognosis in multiple myeloma. Epigenetics. 2014;9(11): 1511–1520. doi:10.4161/15592294.2014.983367
Krum S, Miranda-Carboni G, Lillo-Osuna MA. Re-expression of estrogen receptor alpha in osteosarcomas leads to osteoblast differentiation. J Bone Miner Res. 2017;32:S16 - Google Search. [Online] https://www.google.com/search?q=Krum+S%2C+Miranda-Carboni+G%2C+Lillo-Osuna+MA.+Re-expression+of+estrogen+receptor+alpha+in+osteosarcomas+leads+to+osteoblast+differentiation.+J+Bone+Miner+Res.+2017%3B32%3AS16&sourceid=chrome&ie=UTF-8
Stephenson W, Donlin LT, Butler A, et al. Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation. Nature Communications. 2018;9(1): 791. doi:10.1038/s41467-017-02659-x
Zhang F, Wei K, Slowikowski K, et al. Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nature Immunology. 2019;20(7): 928–942. doi:10.1038/s41590-019-0378-1
Scott DL, Wolfe F, Huizinga TWJ. Rheumatoid arthritis. Lancet (London, England). 2010;376(9746): 1094–1108. doi:10.1016/S0140-6736(10)60826-4
Machado CRL, Dias FF, Resende GG, et al. Morphofunctional analysis of fibroblast-like synoviocytes in human rheumatoid arthritis and mouse collagen-induced arthritis. Advances in Rheumatology (London, England). 2023;63(1): 1. doi:10.1186/s42358-022-00281-0
Ting YT, Petersen J, Ramarathinam SH, et al. The interplay between citrullination and HLA-DRB1 polymorphism in shaping peptide binding hierarchies in rheumatoid arthritis. The Journal of Biological Chemistry. 2018;293(9): 3236–3251. doi:10.1074/jbc.RA117.001013
Raychaudhuri S. Recent advances in the genetics of rheumatoid arthritis. Current opinion in rheumatology. 2010;22(2): 109–118. doi:10.1097/BOR.0b013e328336474d
Mackie SL, Taylor JC, Martin SG, et al. A spectrum of susceptibility to rheumatoid arthritis within HLA-DRB1: stratification by autoantibody status in a large UK population. Genes and Immunity. 2012;13(2): 120–128. doi:10.1038/gene.2011.60
Ng CT, Biniecka M, Kennedy A, et al. Synovial tissue hypoxia and inflammation in vivo. Annals of the Rheumatic Diseases. 2010;69(7): 1389–1395. doi:10.1136/ard.2009.119776
Bustamante MF, Garcia-Carbonell R, Whisenant KD, et al. Fibroblast-like synoviocyte metabolism in the pathogenesis of rheumatoid arthritis. Arthritis Research & Therapy. 2017;19(1): 110. doi:10.1186/s13075-017-1303-3
Garcia-Carbonell R, Divakaruni AS, Lodi A, et al. Critical Role of Glucose Metabolism in Rheumatoid Arthritis Fibroblast-like Synoviocytes. Arthritis & Rheumatology (Hoboken, N.J.). 2016;68(7): 1614–1626. doi:10.1002/art.39608
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