Introduction: Huntington disease (HD) is an autosomal dominant neurodegenerative disorder caused by an expanded CAG repeat in the HTT gene. Although disease onset and progression are known to vary between individuals, recent research has highlighted the role of genetic modifiers—both cis- and trans-acting—in influencing somatic instability, neuronal vulnerability, and age of onset. However, the extent to which these modifiers affect cross-sectional clinical severity and neuroimaging markers remains unclear. This study evaluates the phenotypic impact of genetic modifier categories in a large real-world HD dataset.
Methods: We analyzed a cohort of 48,536 genetically confirmed HD cases containing demographic variables, HTT CAG repeat length, motor severity (Chorea Score), functional impairment (Functional Capacity), and a quantitative neurodegeneration index (Brain Volume Loss). Genetic information included HTT (primary cause), trans-acting modifiers (e.g., MSH3, MLH1), and cis-acting somatic expansion events, classified into three categories. We compared clinical and MRI variables across categories using ANOVA and assessed correlations between CAG length, age, and severity measures using Pearson coefficients.
Results: The distribution of modifier categories was balanced (primary: 25.2%; trans-acting: 50.0%; cis-acting: 24.8%). Mean values of Chorea Score, Brain Volume Loss, and Functional Capacity were nearly identical across groups, with no statistically significant differences (p = 0.27, p = 0.48, p = 0.10, respectively). CAG repeat length was not correlated with motor severity, neurodegeneration, or functional status (all r ≈ 0; p > 0.05). Similarly, age showed no significant associations with any clinical variable. Disease stage (pre-symptomatic, early, middle, late) did not yield significant group differences.
Conclusions: Across this large real-world cohort, genetic modifier categories did not produce meaningful differences in cross-sectional clinical severity or MRI-based neurodegeneration. These findings suggest that modifier effects are subtle and likely act on longitudinal trajectories, age of onset, or progression rates rather than on isolated clinical snapshots. Longitudinal modeling is warranted to capture their true phenotypic impact.
