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Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses

Authors :
Joanna M. Biernacka
Christine W. Galardy
Kathryn M. Schak
Miguel L. Prieto
Euijung Ryu
Bruce Sutor
Alfredo B. Cuellar-Barboza
Scott Crowe
Nicole Mori
Teresa A. Rummans
Jennifer R. Geske
Marin Veldic
Manuel Fuentes
Mark A. Frye
Lisa R. Seymour
Brian A. Palmer
Susan L. McElroy
Christopher L. Sola
Simon Kung
Source :
International Journal of Bipolar Disorders
Publication Year :
2015
Publisher :
Springer Science and Business Media LLC, 2015.

Abstract

Background We aimed to establish a bipolar disorder biobank to serve as a resource for clinical and biomarker studies of disease risk and treatment response. Here, we describe the aims, design, infrastructure, and research uses of the biobank, along with demographics and clinical features of the first participants enrolled. Methods Patients were recruited for the Mayo Clinic Bipolar Biobank beginning in July 2009. The Structured Clinical Interview for DSM-IV was used to confirm bipolar diagnosis. The Bipolar Biobank Clinical Questionnaire and Participant Questionnaire were designed to collect detailed demographic and clinical data, including clinical course of illness measures that would delineate differential phenotypes for subsequent analyses. Blood specimens were obtained from participants, and various aliquots were stored for future research. Results As of September 2014, 1363 participants have been enrolled in the bipolar biobank. Among these first participants, 69.0 % had a diagnosis of bipolar disorder type I. The group was 60.2 % women and predominantly white (90.6 %), with a mean (SD) age of 42.6 (14.9) years. Clinical phenotypes of the group included history of psychosis (42.3 %), suicide attempt (32.5 %), addiction to alcohol (39.1 %), addiction to nicotine (39.8 %), obesity (42.9 %), antidepressant-induced mania (31.7 %), tardive dyskinesia (3.2 %), and history of drug-related serious rash (5.7 %). Conclusions Quantifying phenotypic patterns of illness beyond bipolar subtype can provide more detailed clinical disease characteristics for biomarker research, including genomic-risk studies. Future research can harness clinically useful biomarkers using state-of-the-art research technology to help stage disease burden and better individualize treatment selection for patients with bipolar disorder.

Details

ISSN :
21947511
Volume :
3
Database :
OpenAIRE
Journal :
International Journal of Bipolar Disorders
Accession number :
edsair.doi.dedup.....3c2715641868ce149298c8125333356f
Full Text :
https://doi.org/10.1186/s40345-015-0030-4