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Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants
Metabolic biomarker data quantified by nuclear magnetic resonance (NMR) spectroscopy in approximately 121,000 UK Biobank participants has recently been released as a community resource, comprising absolute concentrations and ratios of 249 circulating metabolites, lipids, and lipoprotein sub-fraction...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887579/ https://www.ncbi.nlm.nih.gov/pubmed/36720882 http://dx.doi.org/10.1038/s41597-023-01949-y |
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author | Ritchie, Scott C. Surendran, Praveen Karthikeyan, Savita Lambert, Samuel A. Bolton, Thomas Pennells, Lisa Danesh, John Di Angelantonio, Emanuele Butterworth, Adam S. Inouye, Michael |
author_facet | Ritchie, Scott C. Surendran, Praveen Karthikeyan, Savita Lambert, Samuel A. Bolton, Thomas Pennells, Lisa Danesh, John Di Angelantonio, Emanuele Butterworth, Adam S. Inouye, Michael |
author_sort | Ritchie, Scott C. |
collection | PubMed |
description | Metabolic biomarker data quantified by nuclear magnetic resonance (NMR) spectroscopy in approximately 121,000 UK Biobank participants has recently been released as a community resource, comprising absolute concentrations and ratios of 249 circulating metabolites, lipids, and lipoprotein sub-fractions. Here we identify and characterise additional sources of unwanted technical variation influencing individual biomarkers in the data available to download from UK Biobank. These included sample preparation time, shipping plate well, spectrometer batch effects, drift over time within spectrometer, and outlier shipping plates. We developed a procedure for removing this unwanted technical variation, and demonstrate that it increases signal for genetic and epidemiological studies of the NMR metabolic biomarker data in UK Biobank. We subsequently developed an R package, ukbnmr, which we make available to the wider research community to enhance the utility of the UK Biobank NMR metabolic biomarker data and to facilitate rapid analysis. |
format | Online Article Text |
id | pubmed-9887579 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98875792023-01-31 Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants Ritchie, Scott C. Surendran, Praveen Karthikeyan, Savita Lambert, Samuel A. Bolton, Thomas Pennells, Lisa Danesh, John Di Angelantonio, Emanuele Butterworth, Adam S. Inouye, Michael Sci Data Analysis Metabolic biomarker data quantified by nuclear magnetic resonance (NMR) spectroscopy in approximately 121,000 UK Biobank participants has recently been released as a community resource, comprising absolute concentrations and ratios of 249 circulating metabolites, lipids, and lipoprotein sub-fractions. Here we identify and characterise additional sources of unwanted technical variation influencing individual biomarkers in the data available to download from UK Biobank. These included sample preparation time, shipping plate well, spectrometer batch effects, drift over time within spectrometer, and outlier shipping plates. We developed a procedure for removing this unwanted technical variation, and demonstrate that it increases signal for genetic and epidemiological studies of the NMR metabolic biomarker data in UK Biobank. We subsequently developed an R package, ukbnmr, which we make available to the wider research community to enhance the utility of the UK Biobank NMR metabolic biomarker data and to facilitate rapid analysis. Nature Publishing Group UK 2023-01-31 /pmc/articles/PMC9887579/ /pubmed/36720882 http://dx.doi.org/10.1038/s41597-023-01949-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Analysis Ritchie, Scott C. Surendran, Praveen Karthikeyan, Savita Lambert, Samuel A. Bolton, Thomas Pennells, Lisa Danesh, John Di Angelantonio, Emanuele Butterworth, Adam S. Inouye, Michael Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants |
title | Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants |
title_full | Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants |
title_fullStr | Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants |
title_full_unstemmed | Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants |
title_short | Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants |
title_sort | quality control and removal of technical variation of nmr metabolic biomarker data in ~120,000 uk biobank participants |
topic | Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887579/ https://www.ncbi.nlm.nih.gov/pubmed/36720882 http://dx.doi.org/10.1038/s41597-023-01949-y |
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