Literature DB >> 12612175

Laboratory issues: use of nutritional biomarkers.

Heidi Michels Blanck1, Barbara A Bowman, Gerald R Cooper, Gary L Myers, Dayton T Miller.   

Abstract

Biomarkers of nutritional status provide alternative measures of dietary intake. Like the error and variation associated with dietary intake measures, the magnitude and impact of both biological (preanalytical) and laboratory (analytical) variability need to be considered when one is using biomarkers. When choosing a biomarker, it is important to understand how it relates to nutritional intake and the specific time frame of exposure it reflects as well as how it is affected by sampling and laboratory procedures. Biological sources of variation that arise from genetic and disease states of an individual affect biomarkers, but they are also affected by nonbiological sources of variation arising from specimen collection and storage, seasonality, time of day, contamination, stability and laboratory quality assurance. When choosing a laboratory for biomarker assessment, researchers should try to make sure random and systematic error is minimized by inclusion of certain techniques such as blinding of laboratory staff to disease status and including external pooled standards to which laboratory staff are blinded. In addition analytic quality control should be ensured by use of internal standards or certified materials over the entire range of possible values to control method accuracy. One must consider the effect of random laboratory error on measurement precision and also understand the method's limit of detection and the laboratory cutpoints. Choosing appropriate cutpoints and reducing error is extremely important in nutritional epidemiology where weak associations are frequent. As part of this review, serum lipids are included as an example of a biomarker whereby collaborative efforts have been put forth to both understand biological sources of variation and standardize laboratory results.

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Year:  2003        PMID: 12612175     DOI: 10.1093/jn/133.3.888S

Source DB:  PubMed          Journal:  J Nutr        ISSN: 0022-3166            Impact factor:   4.798


  23 in total

1.  Estimating laboratory precision of urinary albumin excretion and other urinary measures in the International Study on Macronutrients and Blood Pressure.

Authors:  Alan R Dyer; Philip Greenland; Paul Elliott; Martha L Daviglus; George Claeys; Hugo Kesteloot; Queenie Chan; Hirotsugu Ueshima; Jeremiah Stamler
Journal:  Am J Epidemiol       Date:  2004-08-01       Impact factor: 4.897

Review 2.  A Review of Cutoffs for Nutritional Biomarkers.

Authors:  Ramkripa Raghavan; Fayrouz Sakr Ashour; Regan Bailey
Journal:  Adv Nutr       Date:  2016-01-15       Impact factor: 8.701

Review 3.  [Limits and relevance of the laboratory diagnosis of malnutrition in the elderly].

Authors:  Alexander Lapin
Journal:  Wien Med Wochenschr       Date:  2006-03

4.  Opportunities and challenges in conducting systematic reviews to support the development of nutrient reference values: vitamin A as an example.

Authors:  Robert Russell; Mei Chung; Ethan M Balk; Stephanie Atkinson; Edward L Giovannucci; Stanley Ip; Alice H Lichtenstein; Susan Taylor Mayne; Gowri Raman; A Catharine Ross; Thomas A Trikalinos; Keith P West; Joseph Lau
Journal:  Am J Clin Nutr       Date:  2009-01-28       Impact factor: 7.045

Review 5.  Markers for nutrition studies: review of criteria for the evaluation of markers.

Authors:  Jan de Vries; Jean-Michel Antoine; Tomasz Burzykowski; Alessandro Chiodini; Mike Gibney; Gunter Kuhnle; Agnès Méheust; Loek Pijls; Ian Rowland
Journal:  Eur J Nutr       Date:  2013-08-17       Impact factor: 5.614

Review 6.  Challenges and Lessons Learned in Generating and Interpreting NHANES Nutritional Biomarker Data.

Authors:  Christine M Pfeiffer; David A Lacher; Rosemary L Schleicher; Clifford L Johnson; Elizabeth A Yetley
Journal:  Adv Nutr       Date:  2017-03-15       Impact factor: 8.701

7.  A conditional likelihood approach for regression analysis using biomarkers measured with batch-specific error.

Authors:  Ming Wang; W Dana Flanders; Roberd M Bostick; Qi Long
Journal:  Stat Med       Date:  2012-07-24       Impact factor: 2.373

Review 8.  Critical appraisal of biomarkers of dietary intake and nutritional status in patients undergoing dialysis.

Authors:  Juan Jesús Carrero; Joline Chen; Csaba P Kovesdy; Kamyar Kalantar-Zadeh
Journal:  Semin Dial       Date:  2014-07-10       Impact factor: 3.455

9.  Robust statistical methods for analysis of biomarkers measured with batch/experiment-specific errors.

Authors:  Qi Long; W Dana Flanders; Veronika Fedirko; Roberd M Bostick
Journal:  Stat Med       Date:  2010-02-10       Impact factor: 2.373

10.  Selected physiologic variables are weakly to moderately associated with 29 biomarkers of diet and nutrition, NHANES 2003-2006.

Authors:  Bridgette M H Haynes; Christine M Pfeiffer; Maya R Sternberg; Rosemary L Schleicher
Journal:  J Nutr       Date:  2013-04-17       Impact factor: 4.798

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