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

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 fi...

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Autores principales: 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, Geske, Jennifer, Cuellar-Barboza, Alfredo, Seymour, Lisa R, Mori, Nicole, Crowe, Scott, Rummans, Teresa A, Biernacka, Joanna M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478187/
https://www.ncbi.nlm.nih.gov/pubmed/26105627
http://dx.doi.org/10.1186/s40345-015-0030-4
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author 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
Geske, Jennifer
Cuellar-Barboza, Alfredo
Seymour, Lisa R
Mori, Nicole
Crowe, Scott
Rummans, Teresa A
Biernacka, Joanna M
author_facet 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
Geske, Jennifer
Cuellar-Barboza, Alfredo
Seymour, Lisa R
Mori, Nicole
Crowe, Scott
Rummans, Teresa A
Biernacka, Joanna M
author_sort Frye, Mark A
collection PubMed
description 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.
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spelling pubmed-44781872015-06-25 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 Geske, Jennifer Cuellar-Barboza, Alfredo Seymour, Lisa R Mori, Nicole Crowe, Scott Rummans, Teresa A Biernacka, Joanna M Int J Bipolar Disord Research 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. Springer Berlin Heidelberg 2015-06-24 /pmc/articles/PMC4478187/ /pubmed/26105627 http://dx.doi.org/10.1186/s40345-015-0030-4 Text en © Frye et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research
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
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
title Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses
title_full Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses
title_fullStr Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses
title_full_unstemmed Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses
title_short Development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses
title_sort development of a bipolar disorder biobank: differential phenotyping for subsequent biomarker analyses
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478187/
https://www.ncbi.nlm.nih.gov/pubmed/26105627
http://dx.doi.org/10.1186/s40345-015-0030-4
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