OBJECTIVES: Muscular dystrophies are a clinically and genetically heterogeneous group of inherited myogenic disorders. In clinical tests for these diseases, creatine kinase (CK) is generally used as diagnostic blood-based biomarker. However, because CK levels can be altered by various other factors, such as vigorous exercise, etc., false positive is observed. Therefore, three microRNAs (miRNAs), miR-1, miR-133a, and miR-206, were previously reported as alternative biomarkers for duchenne muscular dystrophy (DMD). However, no alternative biomarkers have been established for the other muscular dystrophies. METHODS: We, therefore, evaluated whether these miR-1, miR-133a, and miR-206 can be used as powerful biomarkers using the serum from muscular dystrophy patients including DMD, myotonic dystrophy 1 (DM1), limb-girdle muscular dystrophy (LGMD), facioscapulohumeral muscular dystrophy (FSHD), becker muscular dystrophy (BMD), and distal myopathy with rimmed vacuoles (DMRV) by qualitative polymerase chain reaction (PCR) amplification assay. RESULTS: Statistical analysis indicated that all these miRNA levels in serum represented no significant differences between all muscle disorders examined in this study and controls by Bonferroni correction. However, some of these indicated significant differences without correction for testing multiple diseases (P < 0.05). The median values of miR-1 levels in the serum of patients with LGMD, FSHD, and BMD were approximately 5.5, 3.3 and 1.7 compared to that in controls, 0.68, respectively. Similarly, those of miR-133a and miR-206 levels in the serum of BMD patients were about 2.5 and 2.1 compared to those in controls, 1.03 and 1.32, respectively. CONCLUSIONS: Taken together, our data demonstrate that levels of miR-1, miR-133a, and miR-206 in serum of BMD and miR-1 in sera of LGMD and FSHD patients showed no significant differences compared with those of controls by Bonferroni correction. However, the results might need increase in sample sizes to evaluate these three miRNAs as variable biomarkers.
OBJECTIVES:Muscular dystrophies are a clinically and genetically heterogeneous group of inherited myogenic disorders. In clinical tests for these diseases, creatine kinase (CK) is generally used as diagnostic blood-based biomarker. However, because CK levels can be altered by various other factors, such as vigorous exercise, etc., false positive is observed. Therefore, three microRNAs (miRNAs), miR-1, miR-133a, and miR-206, were previously reported as alternative biomarkers for duchenne muscular dystrophy (DMD). However, no alternative biomarkers have been established for the other muscular dystrophies. METHODS: We, therefore, evaluated whether these miR-1, miR-133a, and miR-206 can be used as powerful biomarkers using the serum from muscular dystrophypatients including DMD, myotonic dystrophy 1 (DM1), limb-girdle muscular dystrophy (LGMD), facioscapulohumeral muscular dystrophy (FSHD), becker muscular dystrophy (BMD), and distal myopathy with rimmed vacuoles (DMRV) by qualitative polymerase chain reaction (PCR) amplification assay. RESULTS: Statistical analysis indicated that all these miRNA levels in serum represented no significant differences between all muscle disorders examined in this study and controls by Bonferroni correction. However, some of these indicated significant differences without correction for testing multiple diseases (P < 0.05). The median values of miR-1 levels in the serum of patients with LGMD, FSHD, and BMD were approximately 5.5, 3.3 and 1.7 compared to that in controls, 0.68, respectively. Similarly, those of miR-133a and miR-206 levels in the serum of BMDpatients were about 2.5 and 2.1 compared to those in controls, 1.03 and 1.32, respectively. CONCLUSIONS: Taken together, our data demonstrate that levels of miR-1, miR-133a, and miR-206 in serum of BMD and miR-1 in sera of LGMD and FSHDpatients showed no significant differences compared with those of controls by Bonferroni correction. However, the results might need increase in sample sizes to evaluate these three miRNAs as variable biomarkers.
Authors: J C van Deutekom; C Wijmenga; E A van Tienhoven; A M Gruter; J E Hewitt; G W Padberg; G J van Ommen; M H Hofker; R R Frants Journal: Hum Mol Genet Date: 1993-12 Impact factor: 6.150
Authors: Ning Liu; Andrew H Williams; Johanna M Maxeiner; Svetlana Bezprozvannaya; John M Shelton; James A Richardson; Rhonda Bassel-Duby; Eric N Olson Journal: J Clin Invest Date: 2012-05-01 Impact factor: 14.808
Authors: Hadi Valadi; Karin Ekström; Apostolos Bossios; Margareta Sjöstrand; James J Lee; Jan O Lötvall Journal: Nat Cell Biol Date: 2007-05-07 Impact factor: 28.824
Authors: Iris Eisenberg; Alal Eran; Ichizo Nishino; Maurizio Moggio; Costanza Lamperti; Anthony A Amato; Hart G Lidov; Peter B Kang; Kathryn N North; Stella Mitrani-Rosenbaum; Kevin M Flanigan; Lori A Neely; Duncan Whitney; Alan H Beggs; Isaac S Kohane; Louis M Kunkel Journal: Proc Natl Acad Sci U S A Date: 2007-10-17 Impact factor: 11.205
Authors: Thomas C Roberts; Caroline Godfrey; Graham McClorey; Pieter Vader; Deborah Briggs; Chris Gardiner; Yoshitsugu Aoki; Ian Sargent; Jennifer E Morgan; Matthew J A Wood Journal: Nucleic Acids Res Date: 2013-08-14 Impact factor: 16.971