OBJECTIVE: Preliminary data suggested that there are three subgroups of bipolar affective disorder based on age at onset. The authors sought to replicate those findings and determine the cut-off age of each subgroup. METHOD: Admixture analysis was used to determine the best-fitting model for the observed ages at onset of 368 consecutively admitted patients. The results obtained were compared with those of the previously described model. The authors also investigated whether affected siblings are more likely to belong to the same theoretical age-at-onset subgroup as identified by admixture analysis. RESULTS: The existence of three subgroups defined by age at onset was confirmed. The mean ages estimated in this model were 17.4 years (SD=2.3), 25.1 years (SD=6.2), and 40.4 years (SD=11.3). Affected siblings were more likely to belong to the same theoretical subgroup. CONCLUSIONS: There are three age-at-onset subgroups of bipolar patients, and specific familial vulnerability factors might underlie each subgroup.
OBJECTIVE: Preliminary data suggested that there are three subgroups of bipolar affective disorder based on age at onset. The authors sought to replicate those findings and determine the cut-off age of each subgroup. METHOD: Admixture analysis was used to determine the best-fitting model for the observed ages at onset of 368 consecutively admitted patients. The results obtained were compared with those of the previously described model. The authors also investigated whether affected siblings are more likely to belong to the same theoretical age-at-onset subgroup as identified by admixture analysis. RESULTS: The existence of three subgroups defined by age at onset was confirmed. The mean ages estimated in this model were 17.4 years (SD=2.3), 25.1 years (SD=6.2), and 40.4 years (SD=11.3). Affected siblings were more likely to belong to the same theoretical subgroup. CONCLUSIONS: There are three age-at-onset subgroups of bipolarpatients, and specific familial vulnerability factors might underlie each subgroup.
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