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Published on: June 9, 2018
Beyond the CAG triplet number: exploring potential predictors of delayed age of onset in Huntington's disease
Sonia Di Tella1, Maria RIta Lo Monaco2,3, Martina Petracca4
1Department of Psychology, Università Cattolica del Sacro Cuore, 20123, Milan, Italy.
Insights
Non-genetic factors influence Huntington's disease onset age. Factors like marital status, living environment, and education level, alongside genetics, impact disease progression and patient stratification for clinical trials.
Area of Science:
- Neurogenetics
- Neurodegenerative Diseases
Background:
- Huntington's disease (HD) is a genetic neurodegenerative disorder caused by CAG repeat expansion in the Huntingtin gene.
- While CAG repeat length influences age of onset (AOO), it explains only ~70% of variability, suggesting other factors are involved.
- Understanding non-genetic modifiers is crucial for predicting HD progression and patient stratification.
Purpose of the Study:
- To identify demographic, anamnestic, and socio-environmental factors that predict age of motor onset in Huntington's disease.
- To explore predictors of AOO beyond the well-established CAG repeat expansion in the Huntingtin gene.
Main Methods:
- Retrospective analysis of data from the ENROLL-HD global registry study (n=5053).
- Multivariate regression modeling incorporating sociodemographic, genetic, and psychobehavioral variables.
- Subgroup analyses were performed for individuals with 41 CAG repeats and those with unknown family history.
Main Results:
- Delayed onset in HD patients was associated with unknown family history, being married or widowed, living in urbanized areas, and lower educational attainment.
- Earlier onset was more frequently linked to the development of psychobehavioral symptoms.
- These findings highlight significant non-genetic influences on Huntington's disease AOO.
Conclusions:
- The study confirms that factors beyond the Huntingtin gene's CAG repeat expansion modulate Huntington's disease age of onset.
- Identifying these diverse determinants of AOO is essential for refining patient stratification in future clinical trial designs.
- These insights contribute to a more comprehensive understanding of Huntington's disease variability.
Objective:
Huntington's disease (HD) is a genetic neurodegenerative disease characterized by cognitive, motor, and psychiatric dysfunction. It is caused by an expansion of the trinucleotide repeat sequence cytosine-adenine-guanine (CAG) in the Huntingtin gene on chromosome 4. Onset typically occurs in the fourth or fifth decade, ranging from childhood to late adulthood. The CAG triplet number is generally inversely proportional to the age of onset (AOO), but the repeat number only accounts for ∼70% of the variability in AOO. Several studies demonstrated the impact of genetic modifiers on age of disease onset. In addition to genetics, we also explored the demographic, anamnestic, and socio-environmental factors that can affect AOO, to help us understand the non-genetic variability of age of onset in HD.
Methods:
We analyzed the retrospective data of the ENROLL-HD global registry study, particularly focusing on the continuum of ages, to include sociodemographic, genetic, and anamnestic psychobehavioral variables in a multivariate regression model aimed at identifying the potential predictors of age of motor onset (n = 5053). We ran the same regression model in the sample of subjects who had the same number of triplets (41 CAG, n = 593) and in the sample whose family history was absent/unknown (n = 630).
Results:
Patients with delayed onset more frequently have unknown/missing family history, are married or widowed, live in larger urbanized contexts and have a lower educational level. Individuals with earlier onset more frequently develop psychobehavioral symptoms.
Conclusions:
In the past, the HD gene was considered the epitome of genetic determinism. Our results are consistent with recent evidence that other factors might modulate its impact. These findings allow characterizing the determinants of AOO beyond the CAG expansions and provide valuable information for stratifying patients for future clinical trial designs.
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