Carrying minor allele of FADS1 and haplotype of FADS1 and FADS2 increased the risk of metabolic syndrome and moderate but ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

Sunmin Park, Da Sol Kim, Suna Kang

ABSTRACT

PURPOSE: Delta-5-desaturase (fatty acid desaturase-1, FADS1) and delta-6 desaturase (fatty acid desaturase-2, FADS2), rate-limiting enzymes in the biosynthesis of long-chain polyunsaturated fatty acids, may be associated with the risk of metabolic syndrome (MetS). We investigated how FADS1 rs174547 and FADS2 rs2845573 variants modify the prevalence of MetS and whether the risk is modulated by interactions with dietary fat. METHODS: Genetic, anthropometric, biochemical, and dietary data were collected from the Ansan/Ansung (8842 adults) and City-Rural (5512 adults) cohorts in Korea. The association between FADS1 rs174547(C/T) and FADS2 rs2845573(C/T) variants and MetS was analyzed, as was the interaction of genotypes and fatty acid intake and the risk of MetS after adjusting for MetS-related confounders. RESULTS: Carriers of FADS1 rs174547 and FADS2 rs2845573 minor alleles had lower serum HDL-cholesterol and glucose levels and higher triglyceride levels than those with major alleles. Ansan/Ansung cohort individuals with FADS1 minor alleles or haplotypes of FADS1 and FADS2 minor alleles had increased risk of MetS, including lower serum HDL-cholesterol and triglyceride levels and blood pressure after adjusting for MetS-related confounders. The City-Rural cohort showed similar results. Total fat intake showed interactions with FADS1 and haplotype variants on MetS risk: MetS frequency was reduced in people consuming moderate fat diets as compared to low fat diets in FADS1 and haplotype of FADS1 and FADS2 major alleles. CONCLUSION: Korean carriers of the FADS1 rs174547 and FADS2 rs2845573 minor alleles have a greater susceptibility to MetS and moderate fat intake protected against the risk of MetS in carriers of the FADS1 major alleles. More... »

PAGES

831-842

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00394-018-1719-9

DOI

http://dx.doi.org/10.1007/s00394-018-1719-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104124865

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29779171


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Hoseo University", 
          "id": "https://www.grid.ac/institutes/grid.412238.e", 
          "name": [
            "Department of Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, 336-795, Asan-Si, ChungNam-Do, South Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Park", 
        "givenName": "Sunmin", 
        "id": "sg:person.01060641224.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01060641224.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hoseo University", 
          "id": "https://www.grid.ac/institutes/grid.412238.e", 
          "name": [
            "Department of Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, 336-795, Asan-Si, ChungNam-Do, South Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kim", 
        "givenName": "Da Sol", 
        "id": "sg:person.0645711632.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645711632.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hoseo University", 
          "id": "https://www.grid.ac/institutes/grid.412238.e", 
          "name": [
            "Department of Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, 336-795, Asan-Si, ChungNam-Do, South Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kang", 
        "givenName": "Suna", 
        "id": "sg:person.0714025032.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0714025032.51"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.ymgme.2011.02.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002891724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00041433-200302000-00004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012950081"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00041433-200302000-00004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012950081"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mnfr.201500594", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015932798"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00394-015-1127-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019856189", 
          "https://doi.org/10.1007/s00394-015-1127-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0007114511003230", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020268280"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.clnu.2015.09.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020452427"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.ejcn.1601466", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021877686", 
          "https://doi.org/10.1038/sj.ejcn.1601466"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.ejcn.1601466", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021877686", 
          "https://doi.org/10.1038/sj.ejcn.1601466"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.nutr.24.121803.063211", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024311825"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.nut.2014.05.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024410167"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.269", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028890774", 
          "https://doi.org/10.1038/ng.269"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1194/jlr.p032276", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029981411"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1301/00296640260085831", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030381884"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.clnu.2009.11.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032414951"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12986-016-0096-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032892881", 
          "https://doi.org/10.1186/s12986-016-0096-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3945/an.114.007039", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034357605"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.metabol.2009.10.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038429606"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/bti741", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040127778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pgen.1000282", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041945577"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.ejcn.1602657", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042466608", 
          "https://doi.org/10.1038/sj.ejcn.1602657"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pgen.1000338", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044272556"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1194/jlr.p023721", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044404717"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0007114508992564", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044419467"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0007114508992564", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044419467"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/09637486.2016.1252318", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044551645"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pgen.1002193", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049908791"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.3858/emm.2010.42.4.033", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051166619", 
          "https://doi.org/10.3858/emm.2010.42.4.033"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.3858/emm.2010.42.4.033", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051166619", 
          "https://doi.org/10.3858/emm.2010.42.4.033"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3945/jn.114.192708", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052910434"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3945/ajcn.115.121244", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071753689"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4103/0975-3583.70911", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072243647"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077498724", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077514279", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078546345", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-03", 
    "datePublishedReg": "2019-03-01", 
    "description": "PURPOSE: Delta-5-desaturase (fatty acid desaturase-1, FADS1) and delta-6 desaturase (fatty acid desaturase-2, FADS2), rate-limiting enzymes in the biosynthesis of long-chain polyunsaturated fatty acids, may be associated with the risk of metabolic syndrome (MetS). We investigated how FADS1 rs174547 and FADS2 rs2845573 variants modify the prevalence of MetS and whether the risk is modulated by interactions with dietary fat.\nMETHODS: Genetic, anthropometric, biochemical, and dietary data were collected from the Ansan/Ansung (8842 adults) and City-Rural (5512 adults) cohorts in Korea. The association between FADS1 rs174547(C/T) and FADS2 rs2845573(C/T) variants and MetS was analyzed, as was the interaction of genotypes and fatty acid intake and the risk of MetS after adjusting for MetS-related confounders.\nRESULTS: Carriers of FADS1 rs174547 and FADS2 rs2845573 minor alleles had lower serum HDL-cholesterol and glucose levels and higher triglyceride levels than those with major alleles. Ansan/Ansung cohort individuals with FADS1 minor alleles or haplotypes of FADS1 and FADS2 minor alleles had increased risk of MetS, including lower serum HDL-cholesterol and triglyceride levels and blood pressure after adjusting for MetS-related confounders. The City-Rural cohort showed similar results. Total fat intake showed interactions with FADS1 and haplotype variants on MetS risk: MetS frequency was reduced in people consuming moderate fat diets as compared to low fat diets in FADS1 and haplotype of FADS1 and FADS2 major alleles.\nCONCLUSION: Korean carriers of the FADS1 rs174547 and FADS2 rs2845573 minor alleles have a greater susceptibility to MetS and moderate fat intake protected against the risk of MetS in carriers of the FADS1 major alleles.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00394-018-1719-9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7503497", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1294989", 
        "issn": [
          "1436-6207", 
          "1435-1293"
        ], 
        "name": "European Journal of Nutrition", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "58"
      }
    ], 
    "name": "Carrying minor allele of FADS1 and haplotype of FADS1 and FADS2 increased the risk of metabolic syndrome and moderate but not low fat diets lowered the risk in two Korean cohorts", 
    "pagination": "831-842", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "8a5a4a099e5ce61d633f042f3493dbba08312ad160828286251bc01d44898a6b"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "29779171"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100888704"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00394-018-1719-9"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1104124865"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00394-018-1719-9", 
      "https://app.dimensions.ai/details/publication/pub.1104124865"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:27", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000370_0000000370/records_46737_00000002.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs00394-018-1719-9"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00394-018-1719-9'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00394-018-1719-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00394-018-1719-9'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00394-018-1719-9'


 

This table displays all metadata directly associated to this object as RDF triples.

181 TRIPLES      21 PREDICATES      60 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00394-018-1719-9 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author N72b7f1702bc641d0ac8939f761d4525e
4 schema:citation sg:pub.10.1007/s00394-015-1127-3
5 sg:pub.10.1038/ng.269
6 sg:pub.10.1038/sj.ejcn.1601466
7 sg:pub.10.1038/sj.ejcn.1602657
8 sg:pub.10.1186/s12986-016-0096-8
9 sg:pub.10.3858/emm.2010.42.4.033
10 https://app.dimensions.ai/details/publication/pub.1077498724
11 https://app.dimensions.ai/details/publication/pub.1077514279
12 https://app.dimensions.ai/details/publication/pub.1078546345
13 https://doi.org/10.1002/mnfr.201500594
14 https://doi.org/10.1016/j.clnu.2009.11.005
15 https://doi.org/10.1016/j.clnu.2015.09.010
16 https://doi.org/10.1016/j.metabol.2009.10.022
17 https://doi.org/10.1016/j.nut.2014.05.011
18 https://doi.org/10.1016/j.ymgme.2011.02.012
19 https://doi.org/10.1017/s0007114508992564
20 https://doi.org/10.1017/s0007114511003230
21 https://doi.org/10.1080/09637486.2016.1252318
22 https://doi.org/10.1093/bioinformatics/bti741
23 https://doi.org/10.1097/00041433-200302000-00004
24 https://doi.org/10.1146/annurev.nutr.24.121803.063211
25 https://doi.org/10.1194/jlr.p023721
26 https://doi.org/10.1194/jlr.p032276
27 https://doi.org/10.1301/00296640260085831
28 https://doi.org/10.1371/journal.pgen.1000282
29 https://doi.org/10.1371/journal.pgen.1000338
30 https://doi.org/10.1371/journal.pgen.1002193
31 https://doi.org/10.3945/ajcn.115.121244
32 https://doi.org/10.3945/an.114.007039
33 https://doi.org/10.3945/jn.114.192708
34 https://doi.org/10.4103/0975-3583.70911
35 schema:datePublished 2019-03
36 schema:datePublishedReg 2019-03-01
37 schema:description PURPOSE: Delta-5-desaturase (fatty acid desaturase-1, FADS1) and delta-6 desaturase (fatty acid desaturase-2, FADS2), rate-limiting enzymes in the biosynthesis of long-chain polyunsaturated fatty acids, may be associated with the risk of metabolic syndrome (MetS). We investigated how FADS1 rs174547 and FADS2 rs2845573 variants modify the prevalence of MetS and whether the risk is modulated by interactions with dietary fat. METHODS: Genetic, anthropometric, biochemical, and dietary data were collected from the Ansan/Ansung (8842 adults) and City-Rural (5512 adults) cohorts in Korea. The association between FADS1 rs174547(C/T) and FADS2 rs2845573(C/T) variants and MetS was analyzed, as was the interaction of genotypes and fatty acid intake and the risk of MetS after adjusting for MetS-related confounders. RESULTS: Carriers of FADS1 rs174547 and FADS2 rs2845573 minor alleles had lower serum HDL-cholesterol and glucose levels and higher triglyceride levels than those with major alleles. Ansan/Ansung cohort individuals with FADS1 minor alleles or haplotypes of FADS1 and FADS2 minor alleles had increased risk of MetS, including lower serum HDL-cholesterol and triglyceride levels and blood pressure after adjusting for MetS-related confounders. The City-Rural cohort showed similar results. Total fat intake showed interactions with FADS1 and haplotype variants on MetS risk: MetS frequency was reduced in people consuming moderate fat diets as compared to low fat diets in FADS1 and haplotype of FADS1 and FADS2 major alleles. CONCLUSION: Korean carriers of the FADS1 rs174547 and FADS2 rs2845573 minor alleles have a greater susceptibility to MetS and moderate fat intake protected against the risk of MetS in carriers of the FADS1 major alleles.
38 schema:genre research_article
39 schema:inLanguage en
40 schema:isAccessibleForFree false
41 schema:isPartOf N1fa329ff5d154e84857a291fdac6308b
42 Na14cf2964936475f93c88660609320f8
43 sg:journal.1294989
44 schema:name Carrying minor allele of FADS1 and haplotype of FADS1 and FADS2 increased the risk of metabolic syndrome and moderate but not low fat diets lowered the risk in two Korean cohorts
45 schema:pagination 831-842
46 schema:productId N77c7a0d24e224dd393d33f64e535fac5
47 N9b1093161bac425bab536aeab823bb7c
48 Na564bf5800fb4c6fbde4504a89da1e3b
49 Naab0efe432434461a9d76cd94164e42d
50 Nb965a32fc8be4dd8a8117cd7c8cf0d42
51 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104124865
52 https://doi.org/10.1007/s00394-018-1719-9
53 schema:sdDatePublished 2019-04-11T13:27
54 schema:sdLicense https://scigraph.springernature.com/explorer/license/
55 schema:sdPublisher N15ad05462b38404a936af5889ad5181c
56 schema:url https://link.springer.com/10.1007%2Fs00394-018-1719-9
57 sgo:license sg:explorer/license/
58 sgo:sdDataset articles
59 rdf:type schema:ScholarlyArticle
60 N15ad05462b38404a936af5889ad5181c schema:name Springer Nature - SN SciGraph project
61 rdf:type schema:Organization
62 N1fa329ff5d154e84857a291fdac6308b schema:issueNumber 2
63 rdf:type schema:PublicationIssue
64 N38eb9f6ca1dc4d05953e1ed16199b1f9 rdf:first sg:person.0645711632.00
65 rdf:rest Nd2d2ecd7df074d8cb9dc36845e684cee
66 N72b7f1702bc641d0ac8939f761d4525e rdf:first sg:person.01060641224.70
67 rdf:rest N38eb9f6ca1dc4d05953e1ed16199b1f9
68 N77c7a0d24e224dd393d33f64e535fac5 schema:name doi
69 schema:value 10.1007/s00394-018-1719-9
70 rdf:type schema:PropertyValue
71 N9b1093161bac425bab536aeab823bb7c schema:name readcube_id
72 schema:value 8a5a4a099e5ce61d633f042f3493dbba08312ad160828286251bc01d44898a6b
73 rdf:type schema:PropertyValue
74 Na14cf2964936475f93c88660609320f8 schema:volumeNumber 58
75 rdf:type schema:PublicationVolume
76 Na564bf5800fb4c6fbde4504a89da1e3b schema:name pubmed_id
77 schema:value 29779171
78 rdf:type schema:PropertyValue
79 Naab0efe432434461a9d76cd94164e42d schema:name dimensions_id
80 schema:value pub.1104124865
81 rdf:type schema:PropertyValue
82 Nb965a32fc8be4dd8a8117cd7c8cf0d42 schema:name nlm_unique_id
83 schema:value 100888704
84 rdf:type schema:PropertyValue
85 Nd2d2ecd7df074d8cb9dc36845e684cee rdf:first sg:person.0714025032.51
86 rdf:rest rdf:nil
87 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
88 schema:name Medical and Health Sciences
89 rdf:type schema:DefinedTerm
90 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
91 schema:name Clinical Sciences
92 rdf:type schema:DefinedTerm
93 sg:grant.7503497 http://pending.schema.org/fundedItem sg:pub.10.1007/s00394-018-1719-9
94 rdf:type schema:MonetaryGrant
95 sg:journal.1294989 schema:issn 1435-1293
96 1436-6207
97 schema:name European Journal of Nutrition
98 rdf:type schema:Periodical
99 sg:person.01060641224.70 schema:affiliation https://www.grid.ac/institutes/grid.412238.e
100 schema:familyName Park
101 schema:givenName Sunmin
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01060641224.70
103 rdf:type schema:Person
104 sg:person.0645711632.00 schema:affiliation https://www.grid.ac/institutes/grid.412238.e
105 schema:familyName Kim
106 schema:givenName Da Sol
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645711632.00
108 rdf:type schema:Person
109 sg:person.0714025032.51 schema:affiliation https://www.grid.ac/institutes/grid.412238.e
110 schema:familyName Kang
111 schema:givenName Suna
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0714025032.51
113 rdf:type schema:Person
114 sg:pub.10.1007/s00394-015-1127-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019856189
115 https://doi.org/10.1007/s00394-015-1127-3
116 rdf:type schema:CreativeWork
117 sg:pub.10.1038/ng.269 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028890774
118 https://doi.org/10.1038/ng.269
119 rdf:type schema:CreativeWork
120 sg:pub.10.1038/sj.ejcn.1601466 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021877686
121 https://doi.org/10.1038/sj.ejcn.1601466
122 rdf:type schema:CreativeWork
123 sg:pub.10.1038/sj.ejcn.1602657 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042466608
124 https://doi.org/10.1038/sj.ejcn.1602657
125 rdf:type schema:CreativeWork
126 sg:pub.10.1186/s12986-016-0096-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032892881
127 https://doi.org/10.1186/s12986-016-0096-8
128 rdf:type schema:CreativeWork
129 sg:pub.10.3858/emm.2010.42.4.033 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051166619
130 https://doi.org/10.3858/emm.2010.42.4.033
131 rdf:type schema:CreativeWork
132 https://app.dimensions.ai/details/publication/pub.1077498724 schema:CreativeWork
133 https://app.dimensions.ai/details/publication/pub.1077514279 schema:CreativeWork
134 https://app.dimensions.ai/details/publication/pub.1078546345 schema:CreativeWork
135 https://doi.org/10.1002/mnfr.201500594 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015932798
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.clnu.2009.11.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032414951
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.clnu.2015.09.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020452427
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.metabol.2009.10.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038429606
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.nut.2014.05.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024410167
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.ymgme.2011.02.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002891724
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1017/s0007114508992564 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044419467
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1017/s0007114511003230 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020268280
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1080/09637486.2016.1252318 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044551645
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1093/bioinformatics/bti741 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040127778
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1097/00041433-200302000-00004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012950081
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1146/annurev.nutr.24.121803.063211 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024311825
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1194/jlr.p023721 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044404717
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1194/jlr.p032276 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029981411
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1301/00296640260085831 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030381884
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1371/journal.pgen.1000282 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041945577
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1371/journal.pgen.1000338 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044272556
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1371/journal.pgen.1002193 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049908791
170 rdf:type schema:CreativeWork
171 https://doi.org/10.3945/ajcn.115.121244 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071753689
172 rdf:type schema:CreativeWork
173 https://doi.org/10.3945/an.114.007039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034357605
174 rdf:type schema:CreativeWork
175 https://doi.org/10.3945/jn.114.192708 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052910434
176 rdf:type schema:CreativeWork
177 https://doi.org/10.4103/0975-3583.70911 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072243647
178 rdf:type schema:CreativeWork
179 https://www.grid.ac/institutes/grid.412238.e schema:alternateName Hoseo University
180 schema:name Department of Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, 336-795, Asan-Si, ChungNam-Do, South Korea
181 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...