001     119392
005     20240228134939.0
024 7 _ |a 10.3945/jn.113.183970
|2 doi
024 7 _ |a pmid:24647390
|2 pmid
024 7 _ |a pmc:PMC3985828
|2 pmc
024 7 _ |a 0022-3166
|2 ISSN
024 7 _ |a 1541-6100
|2 ISSN
024 7 _ |a altmetric:2199375
|2 altmetric
037 _ _ |a DKFZ-2017-00146
041 _ _ |a eng
082 _ _ |a 630
100 1 _ |a Abbenhardt, Clare
|0 P:(DE-HGF)0
|b 0
|e First author
245 _ _ |a Biomarkers of one-carbon metabolism are associated with biomarkers of inflammation in women.
260 _ _ |a Bethesda, Md.
|c 2014
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1522740143_24001
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Folate-mediated one-carbon metabolism is essential for DNA synthesis, repair, and methylation. Perturbations in one-carbon metabolism have been implicated in increased risk of some cancers and may also affect inflammatory processes. We investigated these interrelated pathways to understand their relation. The objective was to explore associations between inflammation and biomarkers of nutritional status and one-carbon metabolism. In a cross-sectional study in 1976 women selected from the Women's Health Initiative Observational Study, plasma vitamin B-6 [pyridoxal-5'-phosphate (PLP)], plasma vitamin B-12, plasma folate, and RBC folate were measured as nutritional biomarkers; serum C-reactive protein (CRP) and serum amyloid A (SAA) were measured as biomarkers of inflammation; and homocysteine and cysteine were measured as integrated biomarkers of one-carbon metabolism. Student's t, chi-square, and Spearman rank correlations, along with multiple linear regressions, were used to explore relations between biomarkers; additionally, we tested stratification by folic acid fortification period and multivitamin use. With the use of univariate analysis, plasma PLP was the only nutritional biomarker that was modestly significantly correlated with serum CRP and SAA (ρ = -0.22 and -0.12, respectively; P < 0.0001). Homocysteine (μmol/L) showed significant inverse correlations with all nutritional biomarkers (ranging from ρ = -0.30 to ρ = -0.46; all P < 0.0001). With the use of multiple linear regression, plasma PLP, RBC folate, homocysteine, and cysteine were identified as independent predictors of CRP; and PLP, vitamin B-12, RBC folate, and homocysteine were identified as predictors of SAA. When stratified by folic acid fortification period, nutrition-homocysteine correlations were generally weaker in the postfortification period, whereas associations between plasma PLP and serum CRP increased. Biomarkers of inflammation are associated with PLP, RBC folate, and homocysteine in women. The connection between the pathways needs to be further investigated and causality established. The trial is registered at clinicaltrials.gov as NCT00000611.
536 _ _ |a 317 - Translational cancer research (POF3-317)
|0 G:(DE-HGF)POF3-317
|c POF3-317
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed,
650 _ 7 |a Biomarkers
|2 NLM Chemicals
650 _ 7 |a Serum Amyloid A Protein
|2 NLM Chemicals
650 _ 7 |a Homocysteine
|0 0LVT1QZ0BA
|2 NLM Chemicals
650 _ 7 |a Carbon
|0 7440-44-0
|2 NLM Chemicals
650 _ 7 |a Vitamin B 6
|0 8059-24-3
|2 NLM Chemicals
650 _ 7 |a C-Reactive Protein
|0 9007-41-4
|2 NLM Chemicals
650 _ 7 |a Folic Acid
|0 935E97BOY8
|2 NLM Chemicals
650 _ 7 |a Cysteine
|0 K848JZ4886
|2 NLM Chemicals
650 _ 7 |a Vitamin B 12
|0 P6YC3EG204
|2 NLM Chemicals
700 1 _ |a Miller, Joshua W
|b 1
700 1 _ |a Song, Xiaoling
|b 2
700 1 _ |a Brown, Elissa C
|b 3
700 1 _ |a Cheng, Ting-Yuan David
|b 4
700 1 _ |a Wener, Mark H
|b 5
700 1 _ |a Zheng, Yingye
|b 6
700 1 _ |a Toriola, Adetunji T
|b 7
700 1 _ |a Neuhouser, Marian L
|b 8
700 1 _ |a Beresford, Shirley A A
|b 9
700 1 _ |a Makar, Karen W
|b 10
700 1 _ |a Bailey, Lynn B
|b 11
700 1 _ |a Maneval, David R
|b 12
700 1 _ |a Green, Ralph
|b 13
700 1 _ |a Manson, Joann E
|b 14
700 1 _ |a Van Horn, Linda
|b 15
700 1 _ |a Ulrich, Cornelia M
|0 P:(DE-HGF)0
|b 16
|e Last author
773 _ _ |a 10.3945/jn.113.183970
|g Vol. 144, no. 5, p. 714 - 721
|0 PERI:(DE-600)1469429-3
|n 5
|p 714 - 721
|t The journal of nutrition
|v 144
|y 2014
|x 1541-6100
909 C O |p VDB
|o oai:inrepo02.dkfz.de:119392
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 0
|6 P:(DE-HGF)0
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 16
|6 P:(DE-HGF)0
913 1 _ |a DE-HGF
|l Krebsforschung
|1 G:(DE-HGF)POF3-310
|0 G:(DE-HGF)POF3-317
|2 G:(DE-HGF)POF3-300
|v Translational cancer research
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Gesundheit
914 1 _ |y 2014
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b J NUTR : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1060
|2 StatID
|b Current Contents - Agriculture, Biology and Environmental Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
920 1 _ |0 I:(DE-He78)G110-20160331
|k G110
|l Präventive Onkologie
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)G110-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21