Literature DB >> 10197826

Clinical characteristics of major depression that predict risk of depression in relatives.

K S Kendler1, C O Gardner, C A Prescott.   

Abstract

BACKGROUND: Major depression (MD) is both clinically and etiologically heterogeneous. We attempt to relate clinical and etiologic heterogeneity by determining those features of MD that reflect a high familial liability to depressive illness.
METHODS: Our sample, 3786 personally interviewed twin pairs from a population-based registry, contained 1765 people with a lifetime history of MD by DSM-III-R criteria, of whom 639 (36.2%) had affected co-twins. We examine, using Cox proportional hazard models, the clinical features of MD in affected twins that predicted the risk for MD in the co-twin. Control variables were zygosity, age at interview, and sex of the twin and co-twin.
RESULTS: The best-fitting model contained 4 significant predictors: number of episodes, duration of longest episode, recurrent thoughts of death or suicide, and level of distress or impairment. These 4 clinical features were similarly predictive of the risk for MD in the co-twins of male and female twins and predicted risk of illness more strongly in monozygotic than in dizygotic twins. Variables that did not uniquely predict risk of MD in the co-twin included age at onset and number of depressive symptoms. For number of episodes, the best-fitting model indicated an inverted U-shaped function with greatest co-twin risk for MD with 7 to 9 lifetime episodes.
CONCLUSIONS: The clinical features of MD in epidemiologic samples can be meaningfully related to the familial vulnerability to illness. Familial MD is best characterized by intermediate levels of recurrence, long duration of episodes, high levels of impairment, and recurrent thoughts of death or suicide. These clinical features probably reflect a high genetic liability to depressive illness.

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Year:  1999        PMID: 10197826     DOI: 10.1001/archpsyc.56.4.322

Source DB:  PubMed          Journal:  Arch Gen Psychiatry        ISSN: 0003-990X


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