Evidence map›Paper›PMID 34244696›Full record

ReviewNature protocols2021

Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation.

Ernesto S Nakayasu, Marina Gritsenko, Paul D Piehowski, Yuqian Gao, Daniel J Orton, Athena A Schepmoes, Thomas L Fillmore, Brigitte I Frohnert, Marian Rewers, Jeffrey P Krischer and 6 more

Abstract readReview
In one paragraph

Review in Nature protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 130 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
130citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

130 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  17. Characterization ofMicroorganisms · 2026
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70 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Ernesto S NakayasuBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA. ernesto.nakayasu@pnnl.gov.ORCID http://orcid.org/0000-0002-4056-2695
Marina GritsenkoBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.ORCID http://orcid.org/0000-0001-9992-9829
Paul D PiehowskiBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Yuqian GaoBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Daniel J OrtonBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Athena A SchepmoesBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Thomas L FillmoreBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Brigitte I FrohnertBarbara Davis Center for Diabetes, School of Medicine, University of Colorado, Aurora, CO, USA.
Marian RewersBarbara Davis Center for Diabetes, School of Medicine, University of Colorado, Aurora, CO, USA.
Jeffrey P KrischerMorsani College of Medicine, University of South Florida, Tampa, FL, USA.
Charles AnsongBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Astrid M Suchy-DiceyElson S. Floyd College of Medicine, Washington State University, Seattle, WA, USA.
Carmella Evans-MolinaCenter for Diabetes and Metabolic Diseases and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA.
Wei-Jun QianBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.ORCID http://orcid.org/0000-0002-5393-2827
Bobbie-Jo M Webb-RobertsonBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.ORCID http://orcid.org/0000-0002-4744-2397
Thomas O MetzBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA. thomas.metz@pnnl.gov.ORCID http://orcid.org/0000-0001-6049-3968

Funding

Data Coordinating Center (DCC)for the Consortium for Identification of EnvironmenUC4DK095300 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2011 to 2011
$56.0M
NIH Prior Approval Process ProfessionalUL1TR002535 · NCATS · UNIVERSITY OF COLORADO DENVER · PI SOKOL, RONALD J. · 2018 to 2022
$51.1M
Data Coordinating CenterU01DK063790 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2002 to 2006
$50.1M
NIDDK Follow-up on Subjects and Immunological Assessments in The Environmental Determinants of Diabetes In The Young Study (TEDDY) (UC4)UC4DK117483 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2017 to 2020
$30.4M
Establish a Data Coordinating Center (DCC) for the Consortium for Identification UC4DK100238 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2014 to 2014
$28.9M
The Study of Epigenetics and Infections in The Environmental Determinants of Diabetes in the Young (TEDDY)UC4DK112243 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2016 to 2016
$27.0M
Data Coordinating Center (DCC) for the Consortium for Identification of Environmental Determinants of Diabetes in the Young (TEDDY) StudyUC4DK106955 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2015 to 2015
$20.0M
Translation CoreP30DK097512 · NIDDK · INDIANA UNIVERSITY INDIANAPOLIS · PI Carmella Evans-Molina · 2015 to 2026
$17.4M
The Environmental Determinants of Diabetes in Young (TEDDY0U01DK063863 · NIDDK · HOSPITAL DISTRICT OF SOUTHWEST FINLAND · PI TOPPARI, JORMA · 2003 to 2022
$13.5M
The Environmental Triggers of Diabetes (TEDDY) in SwedenU01DK063861 · NIDDK · UNIVERSITY OF WASHINGTON · PI LERNMARK, AKE · 2003 to 2022
$13.4M
THE TEDDY STUDY - COLORADO CLINICAL CENTERU01DK063821 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI REWERS, MARIAN J · 2003 to 2022
$12.3M
The TEDDY Study: Georgia/Florida Clinical CenterU01DK063865 · NIDDK · MEDICAL COLLEGE OF GEORGIA (MCG) · PI MCINDOE, RICHARD A. · 2003 to 2022
$12.3M
BLRD VA I01 BX001733NCATS NIH HHS UL1 TR000064NCATS NIH HHS UL1 TR002535NIDDK NIH HHS P30 DK097512NIDDK NIH HHS P30 DK116073NIDDK NIH HHS R01 DK032493NIDDK NIH HHS R01 DK093954NIDDK NIH HHS R21 DK119800NIDDK NIH HHS U01 DK063790NIDDK NIH HHS U01 DK063821NIDDK NIH HHS U01 DK063829NIDDK NIH HHS U01 DK063836NIDDK NIH HHS U01 DK063861NIDDK NIH HHS U01 DK063863NIDDK NIH HHS U01 DK063865NIDDK NIH HHS U01 DK124020NIDDK NIH HHS U01 DK127786NIDDK NIH HHS UC4 DK063821NIDDK NIH HHS UC4 DK063829NIDDK NIH HHS UC4 DK063836NIDDK NIH HHS UC4 DK063861NIDDK NIH HHS UC4 DK063863NIDDK NIH HHS UC4 DK063865NIDDK NIH HHS UC4 DK095300NIDDK NIH HHS UC4 DK100238NIDDK NIH HHS UC4 DK104166NIDDK NIH HHS UC4 DK106955NIDDK NIH HHS UC4 DK112243NIDDK NIH HHS UC4 DK117483NLM NIH HHS HHSN267200700014C
6 · The paper itself

Abstract

Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.

Indexed as

BiomarkersHumansMass SpectrometryProteinsProteomicsReproducibility of ResultsBiomarkersProteins

Identifiers

PMID34244696
PMCPMC8830262

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.