Background
With the expansion of newborn screening (NBS) panels in many countries, more babies are being identified with serious genetic disorders in a “pre-symptomatic” state and, hopefully, provided an opportunity for early treatment. The term “pre-symptomatic”, however, may be taken to mean different things and in some instances, this designation has created confusion and misunderstanding. Spinal muscular atrophy (SMA) is used here to highlight these issues. While “pre-symptomatic” babies with only two copies of SMN2 are generally responding well to treatment with all 3 FDA-approved drugs, approximately one-third remain delayed in the tempo of motor development, and some have mild impairments in feeding and respiratory status. The prospect for a cure in this population of patients is clearly much more muted. As such, it is important not to confuse “pre-symptomatic” with an implicit expectation that treatment initiated at that time will result in a cure.
Results
A tripartite classification is proposed:
1.Clinically silent (pre-manifest) disease describes individuals with bi-allelic SMN deletions/mutations who appear clinically normal. The parents report no symptoms, and an experienced pediatric neurologist regards the motor examination as normal.
2.Prodromal disease encompasses those individuals who have subtle symptoms and/or findings on examination that are consistent with SMA but are not definitive.
3.Symptomatic SMA is the term reserved for those individuals with definite clinical findings that are typical of SMA.
Conclusions
This new nosology encourages characterization of individuals identified genetically with SMA according to our proposed tripartite clinical classification, and also with respect to known biomarkers (SMN2 copy number, compound muscle action potential amplitude, and neurofilament levels). Such a parallel approach serves the need of clinicians in framing discussions with parents and presenting reasonable expectations when initiating treatment; and supports the research needed to better understand expected trajectories of disease in response to an intervention.