Spinal Muscular Atrophy Biomarkers

Spinal Muscular Atrophy Biomarkers

A biomarker is defined as “any substance, structure, or process that can be measured in the body or its products and influence or predict the incidence of outcome or disease.”1 Biomarkers can be used as clinical readouts to aid decision making (i.e., x-ray radiography to evaluate bone integrity) or can serve as surrogate endpoints to evaluate treatment outcomes for regulatory purposes (i.e., serum cholesterol levels for heart disease).1

The search for biomarkers in Spinal Muscular Atrophy (SMA) has proven difficult for several reasons. SMA progression can take decades and therefore requires longer durations for biomarker validation.2 SMA causes weakness and functional biomarkers measuring strength may be impractical in very young or severely debilitated patients or may be effort dependent and not reliably reproducible in all patients.2 The natural histories of rarer forms of SMA are not as well characterized making generalizability of putative markers characterized in the more common forms potentially limited.3 Finally, even patients with the same forms of SMA can have different disease features making some biomarker readouts too variable between patients with the same type to allow for meaningful comparisons.2

There is presently no consensus regarding a universally accepted “gold standard” biomarker for either clinical or regulatory use in the evaluation of SMA.4 Despite the challenges listed above, investigators have proposed several potential biomarkers for SMA in two general categories: instrumental or molecular.4

Instrumental biomarkers in SMA span the gamut from evaluation of bedside motor function to advanced radiological techniques. Two motor function tests widely used in neuromuscular disease are the six-minute walk test (6MWT) and the Motor Function Measure 32 (MFM32) test.2 The 6MWT is easy to administer, reproducible, and relatively objective,2 but 6MWT requires that a patient to be ambulatory which is not an appropriate biomarker for all patients with SMA since individuals with types 0, 1, and 2 will not be ambulatory.5-7 Similarly, the MFM32 test is similarly inappropriate for all patients with SMA because it requires a patient be able to perform tasks such as standing and transferring.2 Videotaped motor function tests and infant motor assessment scales such as the Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP-INTEND) and the Alberta Infant Motor Scale (AIMS) have shown initial promise as reliable, reproducible motor tests for younger patients with more severe forms of SMA.8 Studies in animal models9 and patients with SMA10 suggest that neurophysiological measurements such as compound motor action potential (CMAP), motor unit number estimation (MUNE), and single motor unit action potential (SMUP)11 may be useful as longitudinal biomarkers of progression in SMA. However, CMAP and MUNE do not correlate with motor function in all forms of SMA raising questions about their utility as biomarkers.4 Neuromuscular diseases associated with immobility yields bone resorption, and the earliest radiographic test suggested as a biomarker in SMA was dual-energy X-ray absorptiometry to evaluate bone density. Unfortunately, the interpretation absorptiometry abnormalities in SMA was never clear,4 and this technique appears insensitive to bone changes early in SMA.12 Recently, investigators have shown that quantitative MRI of muscle volume correlates with clinical2,13 and molecular measures2 and may be a sensitive biomarker of progression in slowly progressive forms of SMA like type 3b.14 

It was originally hoped that the genetic linkages in SMA would provide a molecular biomarker for the disease, but the genetics of SMA are complex and patients with the same variant in the causative gene (SMN1) can have very different clinical manifestations due to known (i.e., SMN2 copy number) and unknown modifying factors.15,16 Evaluations of SMN1 and SMN2 RNA and protein, logical potential biomarkers given the aforementioned genetics of SMA, have not been fruitful. The SMN gene products are difficult to measure in accessible tissues due to low expression,17 are highly variable between tissues,18 fail to differentiate SMA types,19 have age dependent expression,18 were unchanging over a prolonged observation period,2 or have failed to correlate with motor function.17 More comprehensive efforts to identify biomarkers using RNA3 and protein panels20 has yielded lists of potential candidate biomarkers that would be evaluated in combination with functional correlates, but these lists await rigorous validation before they can be used for medical decisions or clinical trials.21

References

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2. Bonati U, Holiga S, Hellbach N, et al. Longitudinal characterization of biomarkers for spinal muscular atrophy. Annals of clinical and translational neurology. 2017;4(5):292-304.

3. Kolb SJ, Coffey CS, Yankey JW, et al. Baseline results of the neuronext spinal muscular atrophy infant biomarker study. Annals of clinical and translational neurology. 2016;3(2):132-145.

4. Tiziano FD, Neri G, Brahe C. Biomarkers in rare disorders: The experience with spinal muscular atrophy. Int J Mol Sci. 2010;12(1):24-38.

5. De Sanctis R, Pane M, Coratti G, et al. Clinical phenotypes and trajectories of disease progression in type 1 spinal muscular atrophy. Neuromuscular disorders : NMD. 2018;28(1):24-28.

6. Grotto S, Cuisset JM, Marret S, et al. Type 0 spinal muscular atrophy: Further delineation of prenatal and postnatal features in 16 patients. J Neuromuscul Dis. 2016;3(4):487-495.

7. Kaufmann P, McDermott MP, Darras BT, et al. Prospective cohort study of spinal muscular atrophy types 2 and 3. Neurology. 2012;79(18):1889-1897.

8. Krosschell KJ, Bosch M, Nelson L, et al. Motor function test reliability during the neuronext spinal muscular atrophy infant biomarker study. J Neuromuscul Dis. 2018.

9. Arnold WD, Porensky PN, McGovern VL, et al. Electrophysiological biomarkers in spinal muscular atrophy: Preclinical proof of concept. Annals of clinical and translational neurology. 2014;1(1):34-44.

10. Arnold WD, Kassar D, Kissel JT. Spinal muscular atrophy: Diagnosis and management in a new therapeutic era. Muscle Nerve. 2015;51(2):157-167.

11. Kang PB, Gooch CL, McDermott MP, et al. The motor neuron response to smn1 deficiency in spinal muscular atrophy. Muscle Nerve. 2014;49(5):636-644.

12. Kinali M, Banks LM, Mercuri E, Manzur AY, Muntoni F. Bone mineral density in a paediatric spinal muscular atrophy population. Neuropediatrics. 2004;35(6):325-328.

13. Sproule DM, Punyanitya M, Shen W, et al. Muscle volume estimation by magnetic resonance imaging in spinal muscular atrophy. J Child Neurol. 2011;26(3):309-317.

14. Durmus H, Yilmaz R, Gulsen-Parman Y, et al. Muscle magnetic resonance imaging in spinal muscular atrophy type 3: Selective and progressive involvement. Muscle Nerve. 2017;55(5):651-656.

15. Tizzano EF, Finkel RS. Spinal muscular atrophy: A changing phenotype beyond the clinical trials. Neuromuscular disorders : NMD. 2017;27(10):883-889.

16. Mercuri E, Bertini E, Iannaccone ST. Childhood spinal muscular atrophy: Controversies and challenges. The Lancet Neurology. 2012;11(5):443-452.

17. Crawford TO, Paushkin SV, Kobayashi DT, et al. Evaluation of smn protein, transcript, and copy number in the biomarkers for spinal muscular atrophy (bforsma) clinical study. PLoS One. 2012;7(4):e33572.

18. Wadman RI, Stam M, Jansen MD, et al. A comparative study of smn protein and mrna in blood and fibroblasts in patients with spinal muscular atrophy and healthy controls. PLoS One. 2016;11(11):e0167087.

19. Czech C, Tang W, Bugawan T, et al. Biomarker for spinal muscular atrophy: Expression of smn in peripheral blood of sma patients and healthy controls. PLoS One. 2015;10(10):e0139950.

20. Kobayashi DT, Shi J, Stephen L, et al. Sma-map: A plasma protein panel for spinal muscular atrophy. PLoS One. 2013;8(4):e60113.

21. Bartlett A, Kolb SJ, Kingsley A, et al. Recruitment & retention program for the neuronext sma biomarker study: Super babies for sma! Contemporary clinical trials communications. 2018;11:113-119.