TY - JOUR
T1 - Development of a bipolar disorder biobank
T2 - differential phenotyping for subsequent biomarker analyses
AU - Frye, Mark A.
AU - McElroy, Susan L.
AU - Fuentes, Manuel
AU - Sutor, Bruce
AU - Schak, Kathryn M.
AU - Galardy, Christine W.
AU - Palmer, Brian A.
AU - Prieto, Miguel L.
AU - Kung, Simon
AU - Sola, Christopher L.
AU - Ryu, Euijung
AU - Veldic, Marin
AU - Geske, Jennifer
AU - Cuellar-Barboza, Alfredo
AU - Seymour, Lisa R.
AU - Mori, Nicole
AU - Crowe, Scott
AU - Rummans, Teresa A.
AU - Biernacka, Joanna M.
N1 - Publisher Copyright:
© 2015, Frye et al.
PY - 2015/12/30
Y1 - 2015/12/30
N2 - 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.
AB - 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.
KW - Biobank
KW - Bipolar disorder
KW - Phenotype
UR - http://www.scopus.com/inward/record.url?scp=84940994979&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940994979&partnerID=8YFLogxK
U2 - 10.1186/s40345-015-0030-4
DO - 10.1186/s40345-015-0030-4
M3 - Article
AN - SCOPUS:84940994979
SN - 2194-7511
VL - 3
JO - International Journal of Bipolar Disorders
JF - International Journal of Bipolar Disorders
IS - 1
M1 - 14
ER -