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Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank
Background: UK Biobank is a large prospective study that recruited 500,000 participants aged 40 to 69 years, between 2006-2010.The study has collected (and continues to collect) extensive phenotypic and genomic data about its participants. In order to enhance further the value of the UK Biobank reso...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7739095/ https://www.ncbi.nlm.nih.gov/pubmed/33364437 http://dx.doi.org/10.12688/wellcomeopenres.16171.2 |
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author | Allen, Naomi E. Arnold, Matthew Parish, Sarah Hill, Michael Sheard, Simon Callen, Howard Fry, Daniel Moffat, Stewart Gordon, Mark Welsh, Samantha Elliott, Paul Collins, Rory |
author_facet | Allen, Naomi E. Arnold, Matthew Parish, Sarah Hill, Michael Sheard, Simon Callen, Howard Fry, Daniel Moffat, Stewart Gordon, Mark Welsh, Samantha Elliott, Paul Collins, Rory |
author_sort | Allen, Naomi E. |
collection | PubMed |
description | Background: UK Biobank is a large prospective study that recruited 500,000 participants aged 40 to 69 years, between 2006-2010.The study has collected (and continues to collect) extensive phenotypic and genomic data about its participants. In order to enhance further the value of the UK Biobank resource, a wide range of biochemistry markers were measured in all participants with an available biological sample. Here, we describe the approaches UK Biobank has taken to minimise error related to sample collection, processing, retrieval and assay measurement. Methods: During routine quality control checks, the laboratory team observed that some assay results were lower than expected for samples acquired during certain time periods. Analyses were undertaken to identify and correct for the unexpected dilution identified during sample processing, and for expected error caused by laboratory drift of assay results. Results: The vast majority (92%) of biochemistry serum assay results were assessed to be not materially affected by dilution, with an estimated difference in concentration of less than 1% (i.e. either lower or higher) than that expected if the sample were unaffected; 8.3% were estimated to be diluted by up to 10%; very few samples appeared to be diluted more than this. Biomarkers measured in urine (creatinine, microalbumin, sodium, potassium) and red blood cells (HbA1c) were not affected. In order to correct for laboratory variation over the assay period, all assay results were adjusted for date of assay, with the exception of those that had a high biological coefficient of variation or evident seasonal variability: vitamin D, lipoprotein (a), gamma glutamyltransferase, C-reactive protein and rheumatoid factor. Conclusions: Rigorous approaches related to sample collection, processing, retrieval, assay measurement and data analysis have been taken to mitigate the impact of both systematic and random variation in epidemiological analyses that use the biochemistry assay data in UK Biobank. |
format | Online Article Text |
id | pubmed-7739095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-77390952020-12-23 Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank Allen, Naomi E. Arnold, Matthew Parish, Sarah Hill, Michael Sheard, Simon Callen, Howard Fry, Daniel Moffat, Stewart Gordon, Mark Welsh, Samantha Elliott, Paul Collins, Rory Wellcome Open Res Research Article Background: UK Biobank is a large prospective study that recruited 500,000 participants aged 40 to 69 years, between 2006-2010.The study has collected (and continues to collect) extensive phenotypic and genomic data about its participants. In order to enhance further the value of the UK Biobank resource, a wide range of biochemistry markers were measured in all participants with an available biological sample. Here, we describe the approaches UK Biobank has taken to minimise error related to sample collection, processing, retrieval and assay measurement. Methods: During routine quality control checks, the laboratory team observed that some assay results were lower than expected for samples acquired during certain time periods. Analyses were undertaken to identify and correct for the unexpected dilution identified during sample processing, and for expected error caused by laboratory drift of assay results. Results: The vast majority (92%) of biochemistry serum assay results were assessed to be not materially affected by dilution, with an estimated difference in concentration of less than 1% (i.e. either lower or higher) than that expected if the sample were unaffected; 8.3% were estimated to be diluted by up to 10%; very few samples appeared to be diluted more than this. Biomarkers measured in urine (creatinine, microalbumin, sodium, potassium) and red blood cells (HbA1c) were not affected. In order to correct for laboratory variation over the assay period, all assay results were adjusted for date of assay, with the exception of those that had a high biological coefficient of variation or evident seasonal variability: vitamin D, lipoprotein (a), gamma glutamyltransferase, C-reactive protein and rheumatoid factor. Conclusions: Rigorous approaches related to sample collection, processing, retrieval, assay measurement and data analysis have been taken to mitigate the impact of both systematic and random variation in epidemiological analyses that use the biochemistry assay data in UK Biobank. F1000 Research Limited 2021-01-04 /pmc/articles/PMC7739095/ /pubmed/33364437 http://dx.doi.org/10.12688/wellcomeopenres.16171.2 Text en Copyright: © 2021 Allen NE et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Allen, Naomi E. Arnold, Matthew Parish, Sarah Hill, Michael Sheard, Simon Callen, Howard Fry, Daniel Moffat, Stewart Gordon, Mark Welsh, Samantha Elliott, Paul Collins, Rory Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank |
title | Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank |
title_full | Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank |
title_fullStr | Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank |
title_full_unstemmed | Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank |
title_short | Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank |
title_sort | approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in uk biobank |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7739095/ https://www.ncbi.nlm.nih.gov/pubmed/33364437 http://dx.doi.org/10.12688/wellcomeopenres.16171.2 |
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