When compared with healthy controls, patients with SMA type 3 performed worse on tests that assessed executive function, language, and visuospatial abilities, suggesting that intrinsic brain pathology may exist in these patients.
After undergoing a comprehensive neuropsychological battery, results from a preliminary study showed that patients with spinal muscular atrophy (SMA) type 3 have poorer cognitive abilities than healthy controls (HCs), which may reflect the presence of intrinsic brain pathology and cognitive adaptive mechanisms following physical dysfunction.1
To understand more about the relationship between cognitive and clinical factors in adults with SMA type 3, investigators assessed a cohort of 22 patients with the neurodegenerative disorder and 22 sex-matched HCs. To assess functionality and motor ability, patients first completed Hammersmith Functional Motor Scale for SMA (HFMSE), Revised Upper Limb Module (RULM), and the 6-Minute Walk Test (6MWT). Considering that fatigue is a core clinical feature of SMA, patients were advised to stay at rest before the examination and were carefully monitored during the exam by clinicians for any signs of fatigue.
Led by Sabrina Lenzoni, MSc, graduate student, University of Padova, patients also completed a neuropsychological battery which included 13 tests in multiple cognitive domains, including executive function, language, visuospatial abilities, and memory. Patients completed testing in-clinic during their usual care appointment and controls completed cognitive testing in a quiet room in the department.
At baseline, patients with SMA had a median age of disease onset of 5.5 years (IQR, 1.5-11) and disease duration of 24 years (IQR, 19-33). Between the 2 groups, those with SMA type 3 had significantly lower performance on the Rey-Osterrieth Complex Figure Test (ROCFT), Trail Making Test B (TMT-B), Raven Progressive Matrices (RPM), and Boston Naming Test (BNT) as compared with controls.
Among those with SMA, performance on TMT-A scores correlated with the age of onset (ρ = –0.48; P = .021), while BNT performance correlated with age of onset (ρ = –0.61; P = .002), and HFMSE (ρ = –0.47; P = .02) and RULM (ρ = –0.48; P = .02) scores. Additionally, Semantic Fluency performance correlated with age of onset (ρ = –0.62; P = .026).
"It is important to note that these preliminary findings show cognitive changes in SMA type III are associated to motor functioning,” Lenzoni et al wrote. "However, they are not sufficient to establish to what extent cognitive test performance represents the clinical profile of SMA type 3 patients. Studies with larger sample are needed to understand the frequency of cognitive ‘impairments’ and what factors can mediate cognitive functions trajectories."
In men, but not women, cognitive test performance was associated with motor functioning. Specifically, Phonetic Fluency performance was associated with age of onset (ρ = –0.74; P = .0005), TMT-A was associated with age of onset (ρ = –0.60; P = .047) and disease duration (ρ = 0.67; P = .023). Additionally, BNT performance was associated with age of onset (ρ = –0.68; P = .020), HFSME (ρ = –0.68; P = .019) and RULM (ρ = –0.62; P = .03) scores. Among women, Digit Span backward performance correlated with disease duration (ρ = –0.64; P = .035) and 6MWT was associated with memory z-scores (B = –0.005; 95% CI, –0.009 to –0.001).
Although SMA diagnosis was not associated with any domain z-scores, results on linear regression models revealed that SMA diagnoses were associated with ROCFT copy (B = 0.04; 95% CI, –0.52 to 0.61) after adjusting for age and education. Similar associations were found on RPM (B = 2.10; 95% CI, 0.74-3.46) and BNT (B = 1.75; 95% CI, 0.13-3.37) scores. These findings were supported by the comparison of patients with SMA scores to the clinically normative data, which showed the greatest frequency of patients performing in the abnormal and borderline ranges in the ROCFT.