Clinical correlates and familial aggregation of age at onset in bipolar disorder.
OBJECTIVE
To assess whether age at onset variation reflects underlying genetic heterogeneity in bipolar disorder, the authors examined the clinical and familial characteristics of age at onset in bipolar disorder subjects from families with multiple affected members.


METHODS
A total of 211 families with 1,856 subjects were ascertained through bipolar I disorder probands. All the subjects were assessed with the Diagnostic Interview for Genetic Studies and assigned diagnoses by trained clinicians using best estimate procedures. Admixture analysis with the 211 bipolar disorder probands was used to decompose the age-at-onset distribution into a mixture of theoretical normal distributions. Logistic regression with general estimating equations was then used to examine clinical correlates and familial aggregation of age at onset in all 717 bipolar disorder subjects.


RESULTS
The age-at-onset distribution consisted of a mixture of three normal distributions with means of 16.6 (SD=5.1), 26.0 (SD=1.4), and 34.7 (SD=6.6) years that comprised 79.7%, 7.2%, and 13.1% of the group, respectively. Cutoff points at ages 21 and 28 were derived from this analysis and used to define age-at-onset subgroups. Early-onset (age at onset </=21) subjects had higher risks of drug abuse, alcohol abuse, rapid cycling, and suicide attempts. Affected subjects from a family with an early-onset proband were more likely than others to have an early onset (odds ratio=4.53, 95% CI=3.09-6.64). Subjects from a family with a proband whose age at onset was <28 were also more likely to have higher risks of drug abuse (odds ratio=11.62, 95% CI=2.16-62.66).


CONCLUSIONS
Age at onset is associated with clinical heterogeneity in bipolar disorder and aggregates, possibly along with drug abuse, within families. These findings are consistent with the conclusion that age at onset reflects underlying genetic heterogeneity in bipolar disorder. Thus, age at onset may conceivably be used to identify more homogeneous groups of bipolar disorder families and thereby facilitate the mapping of bipolar disorder susceptibility genes.
Lin
Ping-I
PI
Dept. of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, 8th Floor, Baltimore, MD 21205, USA.
McInnis
Melvin G
MG
Potash
James B
JB
Willour
Virginia
V
MacKinnon
Dean F
DF
DePaulo
J Raymond
JR
Zandi
Peter P
PP
D000328:Adult; D000367:Age Factors; D017668:Age of Onset; D000704:Analysis of Variance; D001714:Bipolar Disorder / Q000175:diagnosis* / Q000453:epidemiology / Q000235:genetics*; D015897:Comorbidity; D016001:Confidence Intervals; D017831:Diagnosis, Dual (Psychiatry); D004852:Epoxy Compounds; D005190:Family; D005192:Family Health; D005260:Female; D018740:Genetic Heterogeneity; D006576:Heterocyclic Compounds, 4 or More Rings; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016011:Normal Distribution; D016017:Odds Ratio; D010375:Pedigree; D011569:Psychiatric Status Rating Scales / Q000706:statistics & numerical data; D019966:Substance-Related Disorders / Q000175:diagnosis / Q000453:epidemiology / Q000235:genetics
D004852:Epoxy Compounds; D006576:Heterocyclic Compounds, 4 or More Rings; C501551:preussomerin K