Bipolar polygenic loading and bipolar spectrum features in major depressive disorder
Article first published online: 12 APR 2014
© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
Volume 16, Issue 6, pages 608–616, September 2014
How to Cite
Bipolar polygenic loading and bipolar spectrum features in major depressive disorder. Bipolar Disord 2014: 16: 608–616. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd., , , , , , , , , , .
- Issue published online: 28 AUG 2014
- Article first published online: 12 APR 2014
- Manuscript Accepted: 16 OCT 2013
- Manuscript Received: 10 APR 2013
- NIMH. Grant Number: 5R25MH094612
- National Institutes of Health. Grant Number: T32MH017119
- German Federal Ministry of Education and Research
- 7th framework programme
- European Union. Grant Number: HEALTH-F4-2009-242257
- European Community's Seventh Framework Programme. Grant Number: FP7/2007-2013
- National Institute of Mental Health. Grant Number: MH086026
- Genetic Association Information
- US National Institutes of Health
- bipolar disorder;
- major depressive disorder;
- polygenic score;
Family and genetic studies indicate overlapping liability for major depressive disorder and bipolar disorder. The purpose of the present study was to determine whether this shared genetic liability influences clinical presentation.
A polygenic risk score for bipolar disorder, derived from a large genome-wide association meta-analysis, was generated for each subject of European–American ancestry (n = 1,274) in the Sequential Treatment Alternatives to Relieve Depression study (STAR*D) outpatient major depressive disorder cohort. A hypothesis-driven approach was used to test for association between bipolar disorder risk score and features of depression associated with bipolar disorder in the literature. Follow-up analyses were performed in two additional cohorts.
A generalized linear mixed model including seven features hypothesized to be associated with bipolar spectrum illness was significantly associated with bipolar polygenic risk score [F = 2.07, degrees of freedom (df) = 7, p = 0.04]. Features included early onset, suicide attempt, recurrent depression, atypical depression, subclinical mania, subclinical psychosis, and severity. Post-hoc univariate analyses demonstrated that the major contributors to this omnibus association were onset of illness at age ≤ 18 years [odds ratio (OR) = 1.2, p = 0.003], history of suicide attempt (OR = 1.21, p = 0.03), and presence of at least one manic symptom (OR = 1.16, p = 0.02). The maximal variance in these traits explained by polygenic score ranged from 0.8% to 1.1%. However, analyses in two replication cohorts testing a five-feature model did not support this association.
Bipolar genetic loading appeared to be associated with bipolar-like presentation in major depressive disorder in the primary analysis. However, the results were at most inconclusive because of lack of replication. Replication efforts were challenged by different ascertainment and assessment strategies in the different cohorts. The methodological approach described here may prove useful in applying genetic data to clarify psychiatric nosology in future studies.