TY - JOUR
T1 - The search for cerebral biomarkers of Huntington's disease
T2 - A review of genetic models of age at onset prediction
AU - Squitieri, F.
AU - Ciarmiello, A.
AU - Di Donato, S.
AU - Frati, L.
PY - 2006/4
Y1 - 2006/4
N2 - The mutation causing Huntington's disease is an expanded CAG trinucleotide repeat number beyond 35 in the 5′ translated region of the gene. The mutation penetrance varies widely and depends on the CAG expansion length, the low pathological triplet range (36-41) showing a very low penetrance, possibly associated with late ages at onset. No research has so far yielded biomarkers for accurately predicting either age at onset or disease progression in at risk individuals. Specific markers able to follow-up mutation carrier subjects from the pre-symptomatic stages of life are crucial for testing experimental neuroprotective preventive therapies. Nevertheless, the factor accounting for the largest percentage of age at onset variation is the expanded repeat number within the gene. Over the years, this factor has helped in setting up models for genetically predicting age at onset. Once available for practical application in clinics, such models allowed phenotype-genotype correlations that were hitherto inconceivable. In this review, we discuss how these genetic models have been applied in clinical practice and comment on their potential value in searching for cerebral biomarkers of disease onset and severity and in designing trials of therapeutic drugs.
AB - The mutation causing Huntington's disease is an expanded CAG trinucleotide repeat number beyond 35 in the 5′ translated region of the gene. The mutation penetrance varies widely and depends on the CAG expansion length, the low pathological triplet range (36-41) showing a very low penetrance, possibly associated with late ages at onset. No research has so far yielded biomarkers for accurately predicting either age at onset or disease progression in at risk individuals. Specific markers able to follow-up mutation carrier subjects from the pre-symptomatic stages of life are crucial for testing experimental neuroprotective preventive therapies. Nevertheless, the factor accounting for the largest percentage of age at onset variation is the expanded repeat number within the gene. Over the years, this factor has helped in setting up models for genetically predicting age at onset. Once available for practical application in clinics, such models allowed phenotype-genotype correlations that were hitherto inconceivable. In this review, we discuss how these genetic models have been applied in clinical practice and comment on their potential value in searching for cerebral biomarkers of disease onset and severity and in designing trials of therapeutic drugs.
KW - Age at onset
KW - Biomarkers
KW - Onset prediction models
KW - Positron emission tomography
KW - Predictive testing
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U2 - 10.1111/j.1468-1331.2006.01264.x
DO - 10.1111/j.1468-1331.2006.01264.x
M3 - Article
C2 - 16643321
AN - SCOPUS:33646022550
VL - 13
SP - 408
EP - 415
JO - European Journal of Neurology
JF - European Journal of Neurology
SN - 1351-5101
IS - 4
ER -