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

Mark A Frye, Susan L. McElroy, Manuel Fuentes, Bruce Sutor, Kathryn M. Schak, Christine W. Galardy, Brian A. Palmer, Miguel L. Prieto, Simon Kung, Christopher L. Sola, Euijung Ryu, Marin D Veldic, Jennifer Geske, Alfredo Cuellar-Barboza, Lisa R. Seymour, Nicole Mori, Scott Crowe, Teresa A. Rummans, Joanna M Biernacka

Research output: Contribution to journalArticle

22 Citations (Scopus)

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.

Original languageEnglish (US)
Article number14
JournalInternational Journal of Bipolar Disorders
Volume3
Issue number1
DOIs
StatePublished - Dec 30 2015

Fingerprint

Bipolar Disorder
Biomarkers
Demography
Phenotype
Exanthema
Nicotine
Research
Diagnostic and Statistical Manual of Mental Disorders
Psychotic Disorders
Suicide
Patient Selection
Antidepressive Agents
Alcoholism
Research Design
Obesity
Interviews
Technology
Therapeutics
Pharmaceutical Preparations
Surveys and Questionnaires

Keywords

  • Biobank
  • Bipolar disorder
  • Phenotype

ASJC Scopus subject areas

  • Biological Psychiatry
  • Psychiatry and Mental health

Cite this

Development of a bipolar disorder biobank : differential phenotyping for subsequent biomarker analyses. / Frye, Mark A; McElroy, Susan L.; Fuentes, Manuel; Sutor, Bruce; Schak, Kathryn M.; Galardy, Christine W.; Palmer, Brian A.; Prieto, Miguel L.; Kung, Simon; Sola, Christopher L.; Ryu, Euijung; Veldic, Marin D; Geske, Jennifer; Cuellar-Barboza, Alfredo; Seymour, Lisa R.; Mori, Nicole; Crowe, Scott; Rummans, Teresa A.; Biernacka, Joanna M.

In: International Journal of Bipolar Disorders, Vol. 3, No. 1, 14, 30.12.2015.

Research output: Contribution to journalArticle

Frye, MA, McElroy, SL, Fuentes, M, Sutor, B, Schak, KM, Galardy, CW, Palmer, BA, Prieto, ML, Kung, S, Sola, CL, Ryu, E, Veldic, MD, Geske, J, Cuellar-Barboza, A, Seymour, LR, Mori, N, Crowe, S, Rummans, TA & Biernacka, JM 2015, 'Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses', International Journal of Bipolar Disorders, vol. 3, no. 1, 14. https://doi.org/10.1186/s40345-015-0030-4
Frye, Mark A ; McElroy, Susan L. ; Fuentes, Manuel ; Sutor, Bruce ; Schak, Kathryn M. ; Galardy, Christine W. ; Palmer, Brian A. ; Prieto, Miguel L. ; Kung, Simon ; Sola, Christopher L. ; Ryu, Euijung ; Veldic, Marin D ; Geske, Jennifer ; Cuellar-Barboza, Alfredo ; Seymour, Lisa R. ; Mori, Nicole ; Crowe, Scott ; Rummans, Teresa A. ; Biernacka, Joanna M. / Development of a bipolar disorder biobank : differential phenotyping for subsequent biomarker analyses. In: International Journal of Bipolar Disorders. 2015 ; Vol. 3, No. 1.
@article{003f1894b9624766be94e222e5a4afb9,
title = "Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses",
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.",
keywords = "Biobank, Bipolar disorder, Phenotype",
author = "Frye, {Mark A} and McElroy, {Susan L.} and Manuel Fuentes and Bruce Sutor and Schak, {Kathryn M.} and Galardy, {Christine W.} and Palmer, {Brian A.} and Prieto, {Miguel L.} and Simon Kung and Sola, {Christopher L.} and Euijung Ryu and Veldic, {Marin D} and Jennifer Geske and Alfredo Cuellar-Barboza and Seymour, {Lisa R.} and Nicole Mori and Scott Crowe and Rummans, {Teresa A.} and Biernacka, {Joanna M}",
year = "2015",
month = "12",
day = "30",
doi = "10.1186/s40345-015-0030-4",
language = "English (US)",
volume = "3",
journal = "International Journal of Bipolar Disorders",
issn = "2194-7511",
publisher = "Springer Open",
number = "1",

}

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 D

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

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

VL - 3

JO - International Journal of Bipolar Disorders

JF - International Journal of Bipolar Disorders

SN - 2194-7511

IS - 1

M1 - 14

ER -