Penalized regression models to select biomarkers of environmental enteric dysfunction associated with linear growth acquisition in a Peruvian birth cohort.

Bibliographic Details
Title:	Penalized regression models to select biomarkers of environmental enteric dysfunction associated with linear growth acquisition in a Peruvian birth cohort.
Authors:	Josh M Colston, Pablo Peñataro Yori, Lawrence H Moulton, Maribel Paredes Olortegui, Peter S Kosek, Dixner Rengifo Trigoso, Mery Siguas Salas, Francesca Schiaffino, Ruthly François, Fahmina Fardus-Reid, Jonathan R Swann, Margaret N Kosek
Source:	PLoS Neglected Tropical Diseases, Vol 13, Iss 11, p e0007851 (2019)
Publisher Information:	Public Library of Science (PLoS), 2019.
Publication Year:	2019
Collection:	LCC:Arctic medicine. Tropical medicine LCC:Public aspects of medicine
Subject Terms:	Arctic medicine. Tropical medicine, RC955-962, Public aspects of medicine, RA1-1270
More Details:	Environmental enteric dysfunction (EED) is associated with chronic undernutrition. Efforts to identify minimally invasive biomarkers of EED reveal an expanding number of candidate analytes. An analytic strategy is reported to select among candidate biomarkers and systematically express the strength of each marker's association with linear growth in infancy and early childhood. 180 analytes were quantified in fecal, urine and plasma samples taken at 7, 15 and 24 months of age from 258 subjects in a birth cohort in Peru. Treating the subjects' length-for-age Z-score (LAZ-score) over a 2-month lag as the outcome, penalized linear regression models with different shrinkage methods were fitted to determine the best-fitting subset. These were then included with covariates in linear regression models to obtain estimates of each biomarker's adjusted effect on growth. Transferrin had the largest and most statistically significant adjusted effect on short-term linear growth as measured by LAZ-score-a coefficient value of 0.50 (0.24, 0.75) for each log2 increase in plasma transferrin concentration. Other biomarkers with large effect size estimates included adiponectin, arginine, growth hormone, proline and serum amyloid P-component. The selected subset explained up to 23.0% of the variability in LAZ-score. Penalized regression modeling approaches can be used to select subsets from large panels of candidate biomarkers of EED. There is a need to systematically express the strength of association of biomarkers with linear growth or other outcomes to compare results across studies.
Document Type:	article
File Description:	electronic resource
Language:	English
ISSN:	1935-2727 1935-2735
Relation:	https://doaj.org/toc/1935-2727; https://doaj.org/toc/1935-2735
DOI:	10.1371/journal.pntd.0007851
Access URL:	https://doaj.org/article/c38e346ef03a45c18b1a358383c0b8a5
Accession Number:	edsdoj.38e346ef03a45c18b1a358383c0b8a5
Database:	Directory of Open Access Journals
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More Details
ISSN:	19352727 19352735
DOI:	10.1371/journal.pntd.0007851
Published in:	PLoS Neglected Tropical Diseases
Language:	English