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The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients

Biobanks of linked clinical patient histories and biological samples are an efficient strategy to generate large cohorts for modern genetics research. Biobank recruitment varies by factors such as geographic catchment and sampling strategy, which affect biobank demographics and research utility. Her...

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Autores principales: Zawistowski, Matthew, Fritsche, Lars G., Pandit, Anita, Vanderwerff, Brett, Patil, Snehal, Schmidt, Ellen M., VandeHaar, Peter, Willer, Cristen J., Brummett, Chad M., Kheterpal, Sachin, Zhou, Xiang, Boehnke, Michael, Abecasis, Gonçalo R., Zöllner, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932985/
https://www.ncbi.nlm.nih.gov/pubmed/36819667
http://dx.doi.org/10.1016/j.xgen.2023.100257
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author Zawistowski, Matthew
Fritsche, Lars G.
Pandit, Anita
Vanderwerff, Brett
Patil, Snehal
Schmidt, Ellen M.
VandeHaar, Peter
Willer, Cristen J.
Brummett, Chad M.
Kheterpal, Sachin
Zhou, Xiang
Boehnke, Michael
Abecasis, Gonçalo R.
Zöllner, Sebastian
author_facet Zawistowski, Matthew
Fritsche, Lars G.
Pandit, Anita
Vanderwerff, Brett
Patil, Snehal
Schmidt, Ellen M.
VandeHaar, Peter
Willer, Cristen J.
Brummett, Chad M.
Kheterpal, Sachin
Zhou, Xiang
Boehnke, Michael
Abecasis, Gonçalo R.
Zöllner, Sebastian
author_sort Zawistowski, Matthew
collection PubMed
description Biobanks of linked clinical patient histories and biological samples are an efficient strategy to generate large cohorts for modern genetics research. Biobank recruitment varies by factors such as geographic catchment and sampling strategy, which affect biobank demographics and research utility. Here, we describe the Michigan Genomics Initiative (MGI), a single-health-system biobank currently consisting of >91,000 participants recruited primarily during surgical encounters at Michigan Medicine. The surgical enrollment results in a biobank enriched for many diseases and ideally suited for a disease genetics cohort. Compared with the much larger population-based UK Biobank, MGI has higher prevalence for nearly all diagnosis-code-based phenotypes and larger absolute case counts for many phenotypes. Genome-wide association study (GWAS) results replicate known findings, thereby validating the genetic and clinical data. Our results illustrate that opportunistic biobank sampling within single health systems provides a unique and complementary resource for exploring the genetics of complex diseases.
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spelling pubmed-99329852023-02-17 The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients Zawistowski, Matthew Fritsche, Lars G. Pandit, Anita Vanderwerff, Brett Patil, Snehal Schmidt, Ellen M. VandeHaar, Peter Willer, Cristen J. Brummett, Chad M. Kheterpal, Sachin Zhou, Xiang Boehnke, Michael Abecasis, Gonçalo R. Zöllner, Sebastian Cell Genom Article Biobanks of linked clinical patient histories and biological samples are an efficient strategy to generate large cohorts for modern genetics research. Biobank recruitment varies by factors such as geographic catchment and sampling strategy, which affect biobank demographics and research utility. Here, we describe the Michigan Genomics Initiative (MGI), a single-health-system biobank currently consisting of >91,000 participants recruited primarily during surgical encounters at Michigan Medicine. The surgical enrollment results in a biobank enriched for many diseases and ideally suited for a disease genetics cohort. Compared with the much larger population-based UK Biobank, MGI has higher prevalence for nearly all diagnosis-code-based phenotypes and larger absolute case counts for many phenotypes. Genome-wide association study (GWAS) results replicate known findings, thereby validating the genetic and clinical data. Our results illustrate that opportunistic biobank sampling within single health systems provides a unique and complementary resource for exploring the genetics of complex diseases. Elsevier 2023-01-31 /pmc/articles/PMC9932985/ /pubmed/36819667 http://dx.doi.org/10.1016/j.xgen.2023.100257 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Zawistowski, Matthew
Fritsche, Lars G.
Pandit, Anita
Vanderwerff, Brett
Patil, Snehal
Schmidt, Ellen M.
VandeHaar, Peter
Willer, Cristen J.
Brummett, Chad M.
Kheterpal, Sachin
Zhou, Xiang
Boehnke, Michael
Abecasis, Gonçalo R.
Zöllner, Sebastian
The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients
title The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients
title_full The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients
title_fullStr The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients
title_full_unstemmed The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients
title_short The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients
title_sort michigan genomics initiative: a biobank linking genotypes and electronic clinical records in michigan medicine patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932985/
https://www.ncbi.nlm.nih.gov/pubmed/36819667
http://dx.doi.org/10.1016/j.xgen.2023.100257
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