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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2021
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.
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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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