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Confirmatory test of two factors and four subtypes of bipolar disorder based on lifetime psychiatric co-morbidity

  • P. O. Monahan (a1), T. Stump (a1), W. H. Coryell (a2), J. Harezlak (a1), G. A. Marcoulides (a3), H. Liu (a1), C. M. Steeger (a4), P. B. Mitchell (a5) (a6), H. C. Wilcox (a7), L. A. Hulvershorn (a8), A. L. Glowinski (a9), Bipolar Disorder Genome Study (BiGS) Consortium, Bipolar High Risk Study Group, P. A. Iyer-Eimerbrink (a8), M. McInnis (a10) and J. I. Nurnberger (a8)...



The first aim was to use confirmatory factor analysis (CFA) to test a hypothesis that two factors (internalizing and externalizing) account for lifetime co-morbid DSM-IV diagnoses among adults with bipolar I (BPI) disorder. The second aim was to use confirmatory latent class analysis (CLCA) to test the hypothesis that four clinical subtypes are detectible: pure BPI; BPI plus internalizing disorders only; BPI plus externalizing disorders only; and BPI plus internalizing and externalizing disorders.


A cohort of 699 multiplex BPI families was studied, ascertained and assessed (1998–2003) by the National Institute of Mental Health Genetics Initiative Bipolar Consortium: 1156 with BPI disorder (504 adult probands; 594 first-degree relatives; and 58 more distant relatives) and 563 first-degree relatives without BPI. Best-estimate consensus DSM-IV diagnoses were based on structured interviews, family history and medical records. MPLUS software was used for CFA and CLCA.


The two-factor CFA model fit the data very well, and could not be improved by adding or removing paths. The four-class CLCA model fit better than exploratory LCA models or post-hoc-modified CLCA models. The two factors and four classes were associated with distinctive clinical course and severity variables, adjusted for proband gender. Co-morbidity, especially more than one internalizing and/or externalizing disorder, was associated with a more severe and complicated course of illness. The four classes demonstrated significant familial aggregation, adjusted for gender and age of relatives.


The BPI two-factor and four-cluster hypotheses demonstrated substantial confirmatory support. These models may be useful for subtyping BPI disorders, predicting course of illness and refining the phenotype in genetic studies.


Corresponding author

* Address for correspondence: P. O. Monahan, Ph.D., Department of Biostatistics, Indiana University, 410 West 10th Street, Suite 3000, Indianapolis, IN 46202-3002, USA. (Email:


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