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Biomarkers for personalizing omega-3 fatty acid dosing.

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Biomarkers for personalizing omega-3 fatty acid dosing.

Auteurs : Yan Jiang [États-Unis] ; Zora Djuric [États-Unis] ; Ananda Sen [États-Unis] ; Jianwei Ren [États-Unis] ; Dmitry Kuklev [États-Unis] ; Ian Waters [États-Unis] ; Lili Zhao [États-Unis] ; Charis L. Uhlson [États-Unis] ; Yu H. Hong [États-Unis] ; Robert C. Murphy [États-Unis] ; Daniel P. Normolle [États-Unis] ; William L. Smith [États-Unis] ; Dean E. Brenner [États-Unis]

Source :

Cancer prevention research (Philadelphia, Pa.) [ 1940-6215 ] ; 2014.

RBID : pubmed:25139294

Descripteurs français

KwdFr :
- Acides gras (), Acides gras omega-3 (métabolisme), Animaux, Chromatographie gazeuse-spectrométrie de masse, Côlon (métabolisme), Dinoprostone (urine), Huiles de poisson, Hydroquinones (), Inflammation, Lipides (), Marqueurs biologiques tumoraux (analyse), Modèles théoriques, Mâle, Phospholipides (), Poids du corps, Rats, Rats de lignée F344, Spectrométrie de masse en tandem, Température, Éicosanoïdes (métabolisme).
MESH :
- analyse : Marqueurs biologiques tumoraux.
- métabolisme : Acides gras omega-3, Côlon, Éicosanoïdes.
- Acides gras, Animaux, Chromatographie gazeuse-spectrométrie de masse, Dinoprostone, Huiles de poisson, Hydroquinones, Inflammation, Lipides, Modèles théoriques, Mâle, Phospholipides, Poids du corps, Rats, Rats de lignée F344, Spectrométrie de masse en tandem, Température.

English descriptors

KwdEn :
- Animals, Biomarkers, Tumor (analysis), Body Weight, Colon (metabolism), Dinoprostone (urine), Eicosanoids (metabolism), Fatty Acids (chemistry), Fatty Acids, Omega-3 (metabolism), Fish Oils, Gas Chromatography-Mass Spectrometry, Hydroquinones (chemistry), Inflammation, Lipids (chemistry), Male, Models, Theoretical, Phospholipids (chemistry), Rats, Rats, Inbred F344, Tandem Mass Spectrometry, Temperature.
MESH :
- chemical , analysis : Biomarkers, Tumor.
- chemical , chemistry : Fatty Acids, Hydroquinones, Lipids, Phospholipids.
- metabolism : Colon, Eicosanoids, Fatty Acids, Omega-3.
- chemical , urine : Dinoprostone.
- Animals, Body Weight, Fish Oils, Gas Chromatography-Mass Spectrometry, Inflammation, Male, Models, Theoretical, Rats, Rats, Inbred F344, Tandem Mass Spectrometry, Temperature.

Abstract

Prostaglandin E2 (PGE2) has been linked to a higher risk of colorectal cancer. PGE2 in colon tissue can be reduced by increasing dietary eicosapentaenoic acid (EPA). The dose-dependent relationships between dietary EPA, serum EPA:arachidonate (AA) ratio, urinary PGE2 metabolites, and colonic eicosanoids were evaluated to develop biomarkers for prediction of colonic PGE2. Male rats were fed diets containing EPA:ω6 fatty acid ratios of 0, 0.1, 0.2, 0.4, or 0.6 for 5 weeks. Increasing the dietary EPA:ω6 fatty acid ratio increased EPA:AA ratios in serum and in the proximal, transverse, and distal colon (P < 0.001). The urinary PGE2 metabolite was reduced (P = 0.006). EPA-rich diets reduced colonic tissue PGE2 concentrations by 58% to 66% and increased PGE3 by 19- to 28-fold. Other AA-derived eicosanoids were reduced by 35% to 83%. The changes were not linear, with the largest changes in eicosanoids observed with the lower doses. A mathematical model predicts colonic tissue eicosanoids from the EPA:AA ratio in serum and the EPA dose. Every 10% increase in serum EPA:AA was associated with a 2% decrease in the (geometric) mean of PGE2 in the distal colon. These mathematical relationships can now be applied to individualized EPA dosing in clinical trials.

DOI: 10.1158/1940-6207.CAPR-14-0134
PubMed: 25139294

Affiliations:

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term>
<term>Biomarkers, Tumor (analysis)</term>
<term>Body Weight</term>
<term>Colon (metabolism)</term>
<term>Dinoprostone (urine)</term>
<term>Eicosanoids (metabolism)</term>
<term>Fatty Acids (chemistry)</term>
<term>Fatty Acids, Omega-3 (metabolism)</term>
<term>Fish Oils</term>
<term>Gas Chromatography-Mass Spectrometry</term>
<term>Hydroquinones (chemistry)</term>
<term>Inflammation</term>
<term>Lipids (chemistry)</term>
<term>Male</term>
<term>Models, Theoretical</term>
<term>Phospholipids (chemistry)</term>
<term>Rats</term>
<term>Rats, Inbred F344</term>
<term>Tandem Mass Spectrometry</term>
<term>Temperature</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Acides gras ()</term>
<term>Acides gras omega-3 (métabolisme)</term>
<term>Animaux</term>
<term>Chromatographie gazeuse-spectrométrie de masse</term>
<term>Côlon (métabolisme)</term>
<term>Dinoprostone (urine)</term>
<term>Huiles de poisson</term>
<term>Hydroquinones ()</term>
<term>Inflammation</term>
<term>Lipides ()</term>
<term>Marqueurs biologiques tumoraux (analyse)</term>
<term>Modèles théoriques</term>
<term>Mâle</term>
<term>Phospholipides ()</term>
<term>Poids du corps</term>
<term>Rats</term>
<term>Rats de lignée F344</term>
<term>Spectrométrie de masse en tandem</term>
<term>Température</term>
<term>Éicosanoïdes (métabolisme)</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Biomarkers, Tumor</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Fatty Acids</term>
<term>Hydroquinones</term>
<term>Lipids</term>
<term>Phospholipids</term>
</keywords>
<keywords scheme="MESH" qualifier="analyse" xml:lang="fr"><term>Marqueurs biologiques tumoraux</term>
</keywords>
<keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Colon</term>
<term>Eicosanoids</term>
<term>Fatty Acids, Omega-3</term>
</keywords>
<keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Acides gras omega-3</term>
<term>Côlon</term>
<term>Éicosanoïdes</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="urine" xml:lang="en"><term>Dinoprostone</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Animals</term>
<term>Body Weight</term>
<term>Fish Oils</term>
<term>Gas Chromatography-Mass Spectrometry</term>
<term>Inflammation</term>
<term>Male</term>
<term>Models, Theoretical</term>
<term>Rats</term>
<term>Rats, Inbred F344</term>
<term>Tandem Mass Spectrometry</term>
<term>Temperature</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Acides gras</term>
<term>Animaux</term>
<term>Chromatographie gazeuse-spectrométrie de masse</term>
<term>Dinoprostone</term>
<term>Huiles de poisson</term>
<term>Hydroquinones</term>
<term>Inflammation</term>
<term>Lipides</term>
<term>Modèles théoriques</term>
<term>Mâle</term>
<term>Phospholipides</term>
<term>Poids du corps</term>
<term>Rats</term>
<term>Rats de lignée F344</term>
<term>Spectrométrie de masse en tandem</term>
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<front><div type="abstract" xml:lang="en">Prostaglandin E2 (PGE2) has been linked to a higher risk of colorectal cancer. PGE2 in colon tissue can be reduced by increasing dietary eicosapentaenoic acid (EPA). The dose-dependent relationships between dietary EPA, serum EPA:arachidonate (AA) ratio, urinary PGE2 metabolites, and colonic eicosanoids were evaluated to develop biomarkers for prediction of colonic PGE2. Male rats were fed diets containing EPA:ω6 fatty acid ratios of 0, 0.1, 0.2, 0.4, or 0.6 for 5 weeks. Increasing the dietary EPA:ω6 fatty acid ratio increased EPA:AA ratios in serum and in the proximal, transverse, and distal colon (P < 0.001). The urinary PGE2 metabolite was reduced (P = 0.006). EPA-rich diets reduced colonic tissue PGE2 concentrations by 58% to 66% and increased PGE3 by 19- to 28-fold. Other AA-derived eicosanoids were reduced by 35% to 83%. The changes were not linear, with the largest changes in eicosanoids observed with the lower doses. A mathematical model predicts colonic tissue eicosanoids from the EPA:AA ratio in serum and the EPA dose. Every 10% increase in serum EPA:AA was associated with a 2% decrease in the (geometric) mean of PGE2 in the distal colon. These mathematical relationships can now be applied to individualized EPA dosing in clinical trials.</div>
</front>
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</JournalIssue>
<Title>Cancer prevention research (Philadelphia, Pa.)</Title>
<ISOAbbreviation>Cancer Prev Res (Phila)</ISOAbbreviation>
</Journal>
<ArticleTitle>Biomarkers for personalizing omega-3 fatty acid dosing.</ArticleTitle>
<Pagination><MedlinePgn>1011-22</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1158/1940-6207.CAPR-14-0134</ELocationID>
<Abstract><AbstractText>Prostaglandin E2 (PGE2) has been linked to a higher risk of colorectal cancer. PGE2 in colon tissue can be reduced by increasing dietary eicosapentaenoic acid (EPA). The dose-dependent relationships between dietary EPA, serum EPA:arachidonate (AA) ratio, urinary PGE2 metabolites, and colonic eicosanoids were evaluated to develop biomarkers for prediction of colonic PGE2. Male rats were fed diets containing EPA:ω6 fatty acid ratios of 0, 0.1, 0.2, 0.4, or 0.6 for 5 weeks. Increasing the dietary EPA:ω6 fatty acid ratio increased EPA:AA ratios in serum and in the proximal, transverse, and distal colon (P < 0.001). The urinary PGE2 metabolite was reduced (P = 0.006). EPA-rich diets reduced colonic tissue PGE2 concentrations by 58% to 66% and increased PGE3 by 19- to 28-fold. Other AA-derived eicosanoids were reduced by 35% to 83%. The changes were not linear, with the largest changes in eicosanoids observed with the lower doses. A mathematical model predicts colonic tissue eicosanoids from the EPA:AA ratio in serum and the EPA dose. Every 10% increase in serum EPA:AA was associated with a 2% decrease in the (geometric) mean of PGE2 in the distal colon. These mathematical relationships can now be applied to individualized EPA dosing in clinical trials.</AbstractText>
<CopyrightInformation>©2014 American Association for Cancer Research.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Jiang</LastName>
<ForeName>Yan</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Djuric</LastName>
<ForeName>Zora</ForeName>
<Initials>Z</Initials>
<AffiliationInfo><Affiliation>Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Sen</LastName>
<ForeName>Ananda</ForeName>
<Initials>A</Initials>
<AffiliationInfo><Affiliation>Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ren</LastName>
<ForeName>Jianwei</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Kuklev</LastName>
<ForeName>Dmitry</ForeName>
<Initials>D</Initials>
<AffiliationInfo><Affiliation>Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Waters</LastName>
<ForeName>Ian</ForeName>
<Initials>I</Initials>
<AffiliationInfo><Affiliation>Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhao</LastName>
<ForeName>Lili</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Uhlson</LastName>
<ForeName>Charis L</ForeName>
<Initials>CL</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology, University of Colorado Denver, Aurora, Colorado.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hong</LastName>
<ForeName>Yu H</ForeName>
<Initials>YH</Initials>
<AffiliationInfo><Affiliation>Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Murphy</LastName>
<ForeName>Robert C</ForeName>
<Initials>RC</Initials>
<AffiliationInfo><Affiliation>Department of Pharmacology, University of Colorado Denver, Aurora, Colorado.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Normolle</LastName>
<ForeName>Daniel P</ForeName>
<Initials>DP</Initials>
<AffiliationInfo><Affiliation>Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Smith</LastName>
<ForeName>William L</ForeName>
<Initials>WL</Initials>
<AffiliationInfo><Affiliation>Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, Michigan.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Brenner</LastName>
<ForeName>Dean E</ForeName>
<Initials>DE</Initials>
<AffiliationInfo><Affiliation>Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan. Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan. VA Medical Center, Ann Arbor, Michigan. dbrenner@med.umich.edu.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><GrantID>P30 CA046592</GrantID>
<Acronym>CA</Acronym>
<Agency>NCI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>U54 HL117798</GrantID>
<Acronym>HL</Acronym>
<Agency>NHLBI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>GM068848</GrantID>
<Acronym>GM</Acronym>
<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>P50 CA130810</GrantID>
<Acronym>CA</Acronym>
<Agency>NCI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>HL117798</GrantID>
<Acronym>HL</Acronym>
<Agency>NHLBI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>P30 DK020572</GrantID>
<Acronym>DK</Acronym>
<Agency>NIDDK NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>M01 RR000042</GrantID>
<Acronym>RR</Acronym>
<Agency>NCRR NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>AT002782</GrantID>
<Acronym>AT</Acronym>
<Agency>NCCIH NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>P50 AT002782</GrantID>
<Acronym>AT</Acronym>
<Agency>NCCIH NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>CA130810</GrantID>
<Acronym>CA</Acronym>
<Agency>NCI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>R01 GM068848</GrantID>
<Acronym>GM</Acronym>
<Agency>NIGMS NIH HHS</Agency>
<Country>United States</Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType>
<PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2014</Year>
<Month>08</Month>
<Day>19</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>Cancer Prev Res (Phila)</MedlineTA>
<NlmUniqueID>101479409</NlmUniqueID>
<ISSNLinking>1940-6215</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList><Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D014408">Biomarkers, Tumor</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D015777">Eicosanoids</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D005227">Fatty Acids</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D015525">Fatty Acids, Omega-3</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D005395">Fish Oils</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D006873">Hydroquinones</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D008055">Lipids</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>0</RegistryNumber>
<NameOfSubstance UI="D010743">Phospholipids</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>C12674942B</RegistryNumber>
<NameOfSubstance UI="C018855">2-tert-butylhydroquinone</NameOfSubstance>
</Chemical>
<Chemical><RegistryNumber>K7Q1JQR04M</RegistryNumber>
<NameOfSubstance UI="D015232">Dinoprostone</NameOfSubstance>
</Chemical>
</ChemicalList>
<CitationSubset>IM</CitationSubset>
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</CommentsCorrectionsList>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D014408" MajorTopicYN="N">Biomarkers, Tumor</DescriptorName>
<QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D001835" MajorTopicYN="N">Body Weight</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D003106" MajorTopicYN="N">Colon</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015232" MajorTopicYN="N">Dinoprostone</DescriptorName>
<QualifierName UI="Q000652" MajorTopicYN="N">urine</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015777" MajorTopicYN="N">Eicosanoids</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005227" MajorTopicYN="N">Fatty Acids</DescriptorName>
<QualifierName UI="Q000737" MajorTopicYN="N">chemistry</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015525" MajorTopicYN="N">Fatty Acids, Omega-3</DescriptorName>
<QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005395" MajorTopicYN="N">Fish Oils</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008401" MajorTopicYN="N">Gas Chromatography-Mass Spectrometry</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006873" MajorTopicYN="N">Hydroquinones</DescriptorName>
<QualifierName UI="Q000737" MajorTopicYN="N">chemistry</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007249" MajorTopicYN="N">Inflammation</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008055" MajorTopicYN="N">Lipids</DescriptorName>
<QualifierName UI="Q000737" MajorTopicYN="N">chemistry</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008962" MajorTopicYN="N">Models, Theoretical</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D010743" MajorTopicYN="N">Phospholipids</DescriptorName>
<QualifierName UI="Q000737" MajorTopicYN="N">chemistry</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D051381" MajorTopicYN="N">Rats</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011916" MajorTopicYN="N">Rats, Inbred F344</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D053719" MajorTopicYN="N">Tandem Mass Spectrometry</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D013696" MajorTopicYN="N">Temperature</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<OtherID Source="NLM">NIHMS622397</OtherID>
<OtherID Source="NLM">PMC4185239</OtherID>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2014</Year>
<Month>8</Month>
<Day>21</Day>
<Hour>6</Hour>
<Minute>0</Minute>
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<PubMedPubDate PubStatus="pubmed"><Year>2014</Year>
<Month>8</Month>
<Day>21</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2015</Year>
<Month>6</Month>
<Day>26</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">25139294</ArticleId>
<ArticleId IdType="pii">1940-6207.CAPR-14-0134</ArticleId>
<ArticleId IdType="doi">10.1158/1940-6207.CAPR-14-0134</ArticleId>
<ArticleId IdType="pmc">PMC4185239</ArticleId>
<ArticleId IdType="mid">NIHMS622397</ArticleId>
</ArticleIdList>
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<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Colorado</li>
<li>Michigan</li>
<li>Pennsylvanie</li>
</region>
</list>
<tree><country name="États-Unis"><region name="Michigan"><name sortKey="Jiang, Yan" sort="Jiang, Yan" uniqKey="Jiang Y" first="Yan" last="Jiang">Yan Jiang</name>
</region>
<name sortKey="Brenner, Dean E" sort="Brenner, Dean E" uniqKey="Brenner D" first="Dean E" last="Brenner">Dean E. Brenner</name>
<name sortKey="Djuric, Zora" sort="Djuric, Zora" uniqKey="Djuric Z" first="Zora" last="Djuric">Zora Djuric</name>
<name sortKey="Hong, Yu H" sort="Hong, Yu H" uniqKey="Hong Y" first="Yu H" last="Hong">Yu H. Hong</name>
<name sortKey="Kuklev, Dmitry" sort="Kuklev, Dmitry" uniqKey="Kuklev D" first="Dmitry" last="Kuklev">Dmitry Kuklev</name>
<name sortKey="Murphy, Robert C" sort="Murphy, Robert C" uniqKey="Murphy R" first="Robert C" last="Murphy">Robert C. Murphy</name>
<name sortKey="Normolle, Daniel P" sort="Normolle, Daniel P" uniqKey="Normolle D" first="Daniel P" last="Normolle">Daniel P. Normolle</name>
<name sortKey="Ren, Jianwei" sort="Ren, Jianwei" uniqKey="Ren J" first="Jianwei" last="Ren">Jianwei Ren</name>
<name sortKey="Sen, Ananda" sort="Sen, Ananda" uniqKey="Sen A" first="Ananda" last="Sen">Ananda Sen</name>
<name sortKey="Smith, William L" sort="Smith, William L" uniqKey="Smith W" first="William L" last="Smith">William L. Smith</name>
<name sortKey="Uhlson, Charis L" sort="Uhlson, Charis L" uniqKey="Uhlson C" first="Charis L" last="Uhlson">Charis L. Uhlson</name>
<name sortKey="Waters, Ian" sort="Waters, Ian" uniqKey="Waters I" first="Ian" last="Waters">Ian Waters</name>
<name sortKey="Zhao, Lili" sort="Zhao, Lili" uniqKey="Zhao L" first="Lili" last="Zhao">Lili Zhao</name>
</country>
</tree>
</affiliations>
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   |étape=   Checkpoint
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   |clé=     pubmed:25139294
   |texte=   Biomarkers for personalizing omega-3 fatty acid dosing.
}}

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HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/RBID.i   -Sk "pubmed:25139294" \
       | HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd   \
       | NlmPubMed2Wicri -a PittsburghV1

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Data generation: Fri Jun 18 17:37:45 2021. Site generation: Fri Jun 18 18:15:47 2021

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Serveur d'exploration sur Pittsburgh

Biomarkers for personalizing omega-3 fatty acid dosing.

Biomarkers for personalizing omega-3 fatty acid dosing.

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