Longitudinal characterization of biomarkers for spinal muscular atrophy. Bonati, U., Holiga, Š., Hellbach, N., Risterucci, C., Bergauer, T., Tang, W., Hafner, P., Thoeni, A., Bieri, O., Gerlach, I., Marquet, A., Khwaja, O., Sambataro, F., Bertolino, A., Dukart, J., Fischmann, A., Fischer, D., & Czech, C. Annals of Clinical and Translational Neurology, 4(5):292–304, April, 2017. ![Longitudinal characterization of biomarkers for spinal muscular atrophy [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Objective Recent advances in understanding Spinal Muscular Atrophy (SMA) etiopathogenesis prompted development of potent intervention strategies and raised need for sensitive outcome measures capable of assessing disease progression and response to treatment. Several biomarkers have been proposed; nevertheless, no general consensus has been reached on the most feasible ones. We observed a wide range of measures over 1 year to assess their ability to monitor the disease status and progression. Methods 18 SMA patients and 19 healthy volunteers (HV) were followed in this 52‐weeks observational study. Quantitative‐MRI (qMRI) of both thighs and clinical evaluation of motor function was performed at baseline, 6, 9 and 12 months follow‐up. Blood samples were taken in patients for molecular characterization at screening, 9 and 12 month follow‐up. Progression, responsiveness and reliability of collected indices were quantified. Correlation analysis was performed to test for potential associations. Results QMRI indices, clinical scales and molecular measures showed high to excellent reliability. Significant differences were found between qMRI of SMA patients and HV. Significant associations were revealed between multiple qMRI measures and functional clinical scales. None of the qMRI, clinical, or molecular measures was able to detect significant disease progression over 1 year. Interpretation We probed a variety of quantitative measures for SMA in a slowly‐progressing disease population over 1 year. The presented measures demonstrated potential to provide a closer link to underlying disease biology as compared to conventional functional scales. The proposed biomarker framework can guide implementation of more sensitive endpoints in future clinical trials and prove their utility in search for novel disease‐modifying therapies.
@article{bonati_longitudinal_2017,
title = {Longitudinal characterization of biomarkers for spinal muscular atrophy},
volume = {4},
issn = {2328-9503},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420809/},
doi = {10.1002/acn3.406},
abstract = {Objective
Recent advances in understanding Spinal Muscular Atrophy (SMA) etiopathogenesis prompted development of potent intervention strategies and raised need for sensitive outcome measures capable of assessing disease progression and response to treatment. Several biomarkers have been proposed; nevertheless, no general consensus has been reached on the most feasible ones. We observed a wide range of measures over 1 year to assess their ability to monitor the disease status and progression.
Methods
18 SMA patients and 19 healthy volunteers (HV) were followed in this 52‐weeks observational study. Quantitative‐MRI (qMRI) of both thighs and clinical evaluation of motor function was performed at baseline, 6, 9 and 12 months follow‐up. Blood samples were taken in patients for molecular characterization at screening, 9 and 12 month follow‐up. Progression, responsiveness and reliability of collected indices were quantified. Correlation analysis was performed to test for potential associations.
Results
QMRI indices, clinical scales and molecular measures showed high to excellent reliability. Significant differences were found between qMRI of SMA patients and HV. Significant associations were revealed between multiple qMRI measures and functional clinical scales. None of the qMRI, clinical, or molecular measures was able to detect significant disease progression over 1 year.
Interpretation
We probed a variety of quantitative measures for SMA in a slowly‐progressing disease population over 1 year. The presented measures demonstrated potential to provide a closer link to underlying disease biology as compared to conventional functional scales. The proposed biomarker framework can guide implementation of more sensitive endpoints in future clinical trials and prove their utility in search for novel disease‐modifying therapies.},
number = {5},
urldate = {2018-07-05},
journal = {Annals of Clinical and Translational Neurology},
author = {Bonati, Ulrike and Holiga, Štefan and Hellbach, Nicole and Risterucci, Céline and Bergauer, Tobias and Tang, Wakana and Hafner, Patricia and Thoeni, Alain and Bieri, Oliver and Gerlach, Irene and Marquet, Anne and Khwaja, Omar and Sambataro, Fabio and Bertolino, Alessandro and Dukart, Juergen and Fischmann, Arne and Fischer, Dirk and Czech, Christian},
month = apr,
year = {2017},
pmid = {28491897},
pmcid = {PMC5420809},
pages = {292--304},
}
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Several biomarkers have been proposed; nevertheless, no general consensus has been reached on the most feasible ones. We observed a wide range of measures over 1 year to assess their ability to monitor the disease status and progression. Methods 18 SMA patients and 19 healthy volunteers (HV) were followed in this 52‐weeks observational study. Quantitative‐MRI (qMRI) of both thighs and clinical evaluation of motor function was performed at baseline, 6, 9 and 12 months follow‐up. Blood samples were taken in patients for molecular characterization at screening, 9 and 12 month follow‐up. Progression, responsiveness and reliability of collected indices were quantified. Correlation analysis was performed to test for potential associations. Results QMRI indices, clinical scales and molecular measures showed high to excellent reliability. Significant differences were found between qMRI of SMA patients and HV. Significant associations were revealed between multiple qMRI measures and functional clinical scales. None of the qMRI, clinical, or molecular measures was able to detect significant disease progression over 1 year. Interpretation We probed a variety of quantitative measures for SMA in a slowly‐progressing disease population over 1 year. The presented measures demonstrated potential to provide a closer link to underlying disease biology as compared to conventional functional scales. The proposed biomarker framework can guide implementation of more sensitive endpoints in future clinical trials and prove their utility in search for novel disease‐modifying therapies.","number":"5","urldate":"2018-07-05","journal":"Annals of Clinical and Translational Neurology","author":[{"propositions":[],"lastnames":["Bonati"],"firstnames":["Ulrike"],"suffixes":[]},{"propositions":[],"lastnames":["Holiga"],"firstnames":["Štefan"],"suffixes":[]},{"propositions":[],"lastnames":["Hellbach"],"firstnames":["Nicole"],"suffixes":[]},{"propositions":[],"lastnames":["Risterucci"],"firstnames":["Céline"],"suffixes":[]},{"propositions":[],"lastnames":["Bergauer"],"firstnames":["Tobias"],"suffixes":[]},{"propositions":[],"lastnames":["Tang"],"firstnames":["Wakana"],"suffixes":[]},{"propositions":[],"lastnames":["Hafner"],"firstnames":["Patricia"],"suffixes":[]},{"propositions":[],"lastnames":["Thoeni"],"firstnames":["Alain"],"suffixes":[]},{"propositions":[],"lastnames":["Bieri"],"firstnames":["Oliver"],"suffixes":[]},{"propositions":[],"lastnames":["Gerlach"],"firstnames":["Irene"],"suffixes":[]},{"propositions":[],"lastnames":["Marquet"],"firstnames":["Anne"],"suffixes":[]},{"propositions":[],"lastnames":["Khwaja"],"firstnames":["Omar"],"suffixes":[]},{"propositions":[],"lastnames":["Sambataro"],"firstnames":["Fabio"],"suffixes":[]},{"propositions":[],"lastnames":["Bertolino"],"firstnames":["Alessandro"],"suffixes":[]},{"propositions":[],"lastnames":["Dukart"],"firstnames":["Juergen"],"suffixes":[]},{"propositions":[],"lastnames":["Fischmann"],"firstnames":["Arne"],"suffixes":[]},{"propositions":[],"lastnames":["Fischer"],"firstnames":["Dirk"],"suffixes":[]},{"propositions":[],"lastnames":["Czech"],"firstnames":["Christian"],"suffixes":[]}],"month":"April","year":"2017","pmid":"28491897","pmcid":"PMC5420809","pages":"292–304","bibtex":"@article{bonati_longitudinal_2017,\n\ttitle = {Longitudinal characterization of biomarkers for spinal muscular atrophy},\n\tvolume = {4},\n\tissn = {2328-9503},\n\turl = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420809/},\n\tdoi = {10.1002/acn3.406},\n\tabstract = {Objective\nRecent advances in understanding Spinal Muscular Atrophy (SMA) etiopathogenesis prompted development of potent intervention strategies and raised need for sensitive outcome measures capable of assessing disease progression and response to treatment. Several biomarkers have been proposed; nevertheless, no general consensus has been reached on the most feasible ones. We observed a wide range of measures over 1 year to assess their ability to monitor the disease status and progression.\n\nMethods\n18 SMA patients and 19 healthy volunteers (HV) were followed in this 52‐weeks observational study. Quantitative‐MRI (qMRI) of both thighs and clinical evaluation of motor function was performed at baseline, 6, 9 and 12 months follow‐up. Blood samples were taken in patients for molecular characterization at screening, 9 and 12 month follow‐up. Progression, responsiveness and reliability of collected indices were quantified. Correlation analysis was performed to test for potential associations.\n\nResults\n\nQMRI indices, clinical scales and molecular measures showed high to excellent reliability. Significant differences were found between qMRI of SMA patients and HV. Significant associations were revealed between multiple qMRI measures and functional clinical scales. None of the qMRI, clinical, or molecular measures was able to detect significant disease progression over 1 year.\n\nInterpretation\nWe probed a variety of quantitative measures for SMA in a slowly‐progressing disease population over 1 year. The presented measures demonstrated potential to provide a closer link to underlying disease biology as compared to conventional functional scales. 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