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A workflow for integrated processing of multi-cohort untargeted 1H NMR metabolomics data in large scale metabolic epidemiology

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NMR Preprocessing Paper - 20160720 noref.docxAccepted version7.18 MBMicrosoft WordView/Open
Title: A workflow for integrated processing of multi-cohort untargeted 1H NMR metabolomics data in large scale metabolic epidemiology
Authors: Karaman, I
Ferreira, DL
Boulange, CL
Kaluarachchi, MR
Herrington, D
Dona, AC
Castagné, R
Moayyeri, A
Lehne, B
Loh, M
De Vries, PS
Dehghan, A
Franco, O
Hofman, A
Evangelou, E
Tzoulaki, I
Elliott, P
Lindon, JC
Ebbels, TM
Item Type: Journal Article
Abstract: Large-scale metabolomics studies involving thousands of samples present multiple challenges in data analysis, particularly when an untargeted platform is used. Studies with multiple cohorts and analysis platforms exacerbate existing problems such as peak alignment and normalization. Therefore, there is a need for robust processing pipelines which can ensure reliable data for statistical analysis. The COMBI-BIO project incorporates serum from approximately 8000 individuals, in 3 cohorts, profiled by 6 assays in 2 phases using both 1H-NMR and UPLC-MS. Here we present the COMBI-BIO NMR analysis pipeline and demonstrate its fitness for purpose using representative quality control (QC) samples. NMR spectra were first aligned and normalized. After eliminating interfering signals, outliers identified using Hotelling’s T2 were removed and a cohort/phase adjustment was applied, resulting in two NMR datasets (CPMG and NOESY). Alignment of the NMR data was shown to increase the correlation-based alignment quality measure from 0.319 to 0.391 for CPMG and from 0.536 to 0.586 for NOESY, showing that the improvement was present across both large and small peaks. End-to-end quality assessment of the pipeline was achieved using Hotelling’s T2 distributions. For CPMG spectra, the interquartile range decreased from 1.425 in raw QC data to 0.679 in processed spectra, while the corresponding change for NOESY spectra was from 0.795 to 0.636 indicating an improvement in precision following processing. PCA indicated that gross phase and cohort differences were no longer present. These results illustrate that the pipeline produces robust and reproducible data, successfully addressing the methodological challenges of this large multi-faceted study.
Issue Date: 15-Sep-2016
Date of Acceptance: 1-Sep-2016
URI: http://hdl.handle.net/10044/1/40307
DOI: https://dx.doi.org/10.1021/acs.jproteome.6b00125
ISSN: 1535-3907
Publisher: American Chemical Society
Start Page: 4188
End Page: 4194
Journal / Book Title: Journal of Proteome Research
Volume: 15
Issue: 12
Copyright Statement: © 2016 American Chemical Society. This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Proteome Research, after peer review and technical editing by the publisher. To access the final edited and published work see http://dx.doi.org/10.1021/acs.jproteome.6b00125.
Sponsor/Funder: National Institute for Health Research
Commission of the European Communities
Medical Research Council (MRC)
Commission of the European Communities
Medical Research Council (MRC)
Medical Research Council (MRC)
National Institute for Health Research
European Molecular Biology Laboratory
Funder's Grant Number: NF-SI-0611-10136
305422
MC_PC_12025
312941
MR/L01632X/1
MR/L01341X/1
RTJ6219303-1
654241
Keywords: NMR
alignment
epidemiology
large scale
metabolomics
multicohort
normalization
preprocessing
quality control
Biochemistry & Molecular Biology
06 Biological Sciences
03 Chemical Sciences
Publication Status: Published
Appears in Collections:Division of Surgery
Faculty of Medicine
Epidemiology, Public Health and Primary Care



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