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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-9932985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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