PMID- 28927937
OWN - NLM
STAT- MEDLINE
DCOM- 20171204
LR  - 20191210
IS  - 1873-3778 (Electronic)
IS  - 0021-9673 (Print)
IS  - 0021-9673 (Linking)
VI  - 1523
DP  - 2017 Nov 10
TI  - Evaluation of intensity drift correction strategies using MetaboDrift, a 
      normalization tool for multi-batch metabolomics data.
PG  - 265-274
LID - S0021-9673(17)31343-2 [pii]
LID - 10.1016/j.chroma.2017.09.023 [doi]
AB  - In recent years, mass spectrometry-based metabolomics has increasingly been 
      applied to large-scale epidemiological studies of human subjects. However, the 
      successful use of metabolomics in this context is subject to the challenge of 
      detecting biologically significant effects despite substantial intensity drift 
      that often occurs when data are acquired over a long period or in multiple 
      batches. Numerous computational strategies and software tools have been developed 
      to aid in correcting for intensity drift in metabolomics data, but most of these 
      techniques are implemented using command-line driven software and custom scripts 
      which are not accessible to all end users of metabolomics data. Further, it has 
      not yet become routine practice to assess the quantitative accuracy of drift 
      correction against techniques which enable true absolute quantitation such as 
      isotope dilution mass spectrometry. We developed an Excel-based tool, 
      MetaboDrift, to visually evaluate and correct for intensity drift in a 
      multi-batch liquid chromatography - mass spectrometry (LC-MS) metabolomics 
      dataset. The tool enables drift correction based on either quality control (QC) 
      samples analyzed throughout the batches or using QC-sample independent methods. 
      We applied MetaboDrift to an original set of clinical metabolomics data from a 
      mixed-meal tolerance test (MMTT). The performance of the method was evaluated for 
      multiple classes of metabolites by comparison with normalization using 
      isotope-labeled internal standards. QC sample-based intensity drift correction 
      significantly improved correlation with IS-normalized data, and resulted in 
      detection of additional metabolites with significant physiological response to 
      the MMTT. The relative merits of different QC-sample curve fitting strategies are 
      discussed in the context of batch size and drift pattern complexity. Our drift 
      correction tool offers a practical, simplified approach to drift correction and 
      batch combination in large metabolomics studies.
CI  - Copyright (c) 2017 Elsevier B.V. All rights reserved.
FAU - Thonusin, Chanisa
AU  - Thonusin C
AD  - Department of Internal Medicine, University of Michigan, 6300 Brehm Tower, 1000 
      Wall St., Ann Arbor, MI 48109, United States; Department of Molecular and 
      Integrative Physiology, University of Michigan, 6300 Brehm Tower, 1000 Wall St., 
      Ann Arbor, MI 48109, United States; Faculty of Medicine, Chiang Mai University, 
      Chiang Mai, Thailand.
FAU - IglayReger, Heidi B
AU  - IglayReger HB
AD  - Department of Internal Medicine, University of Michigan, 6300 Brehm Tower, 1000 
      Wall St., Ann Arbor, MI 48109, United States.
FAU - Soni, Tanu
AU  - Soni T
AD  - Department of Internal Medicine, University of Michigan, 6300 Brehm Tower, 1000 
      Wall St., Ann Arbor, MI 48109, United States.
FAU - Rothberg, Amy E
AU  - Rothberg AE
AD  - Department of Internal Medicine, University of Michigan, 6300 Brehm Tower, 1000 
      Wall St., Ann Arbor, MI 48109, United States.
FAU - Burant, Charles F
AU  - Burant CF
AD  - Department of Internal Medicine, University of Michigan, 6300 Brehm Tower, 1000 
      Wall St., Ann Arbor, MI 48109, United States; Department of Molecular and 
      Integrative Physiology, University of Michigan, 6300 Brehm Tower, 1000 Wall St., 
      Ann Arbor, MI 48109, United States.
FAU - Evans, Charles R
AU  - Evans CR
AD  - Department of Internal Medicine, University of Michigan, 6300 Brehm Tower, 1000 
      Wall St., Ann Arbor, MI 48109, United States. Electronic address: 
      chevans@umich.edu.
LA  - eng
GR  - U01 DK097430/DK/NIDDK NIH HHS/United States
GR  - P30 DK092926/DK/NIDDK NIH HHS/United States
GR  - P30 DK089503/DK/NIDDK NIH HHS/United States
GR  - P30 DK020572/DK/NIDDK NIH HHS/United States
GR  - U24 DK097153/DK/NIDDK NIH HHS/United States
GR  - K25 DK092558/DK/NIDDK NIH HHS/United States
GR  - R01 DK099034/DK/NIDDK NIH HHS/United States
PT  - Evaluation Study
PT  - Journal Article
DEP - 20170909
PL  - Netherlands
TA  - J Chromatogr A
JT  - Journal of chromatography. A
JID - 9318488
SB  - IM
MH  - Chromatography, Liquid
MH  - Humans
MH  - Mass Spectrometry
MH  - Metabolomics/*methods
MH  - Multiple Chronic Conditions
MH  - *Software
PMC - PMC5788449
MID - NIHMS907160
OTO - NOTNLM
OT  - Drift correction
OT  - Intensity drift
OT  - LC-MS
OT  - Meal tolerance test
OT  - Metabolomics
OT  - Normalization
EDAT- 2017/09/21 06:00
MHDA- 2017/12/05 06:00
PMCR- 2018/11/10
CRDT- 2017/09/21 06:00
PHST- 2017/04/20 00:00 [received]
PHST- 2017/09/07 00:00 [revised]
PHST- 2017/09/08 00:00 [accepted]
PHST- 2017/09/21 06:00 [pubmed]
PHST- 2017/12/05 06:00 [medline]
PHST- 2017/09/21 06:00 [entrez]
PHST- 2018/11/10 00:00 [pmc-release]
AID - S0021-9673(17)31343-2 [pii]
AID - 10.1016/j.chroma.2017.09.023 [doi]
PST - ppublish
SO  - J Chromatogr A. 2017 Nov 10;1523:265-274. doi: 10.1016/j.chroma.2017.09.023. Epub 
      2017 Sep 9.