Effects of familial hypercholesterolemia-associated genes on the phenotype of premature myocardial infarction. View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Chongyou Lee, Yuxia Cui, Junxian Song, Sufang Li, Feng Zhang, Manyan Wu, Long Li, Dan Hu, Hong Chen

ABSTRACT

BACKGROUND: The incidence of premature myocardial infarction (PMI) has gradually increased in recent years. Genetics plays a central role in the development of PMI. Familial hypercholesterolemia (FH) is one of the most common genetic disorders of cholesterol metabolism leading to PMI. OBJECTIVE: This study investigated the relationship between FH-associated genes and the phenotype of PMI to clarify the genetic spectrum of PMI diseases. METHOD: This study enrolled PMI patients (n = 225) and detected the mutations in their FH-associated genes (LDLR, APOB, PCSK9, LDLRAP1) by Sanger sequencing. At the same time, patients free of PMI (non-FH patients, n = 56) were enrolled as control, and a logistic regression analysis was used to identify risk factors associated with PMI. The diagnosis of FH was confirmed using "2018 Chinese expert consensus of FH screening and diagnosis" before the prevalence and clinical features of FH were analyzed. RESULTS: Pathogenic mutations in LDLR, APOB, PCSK9 and LDLRAP1 genes were found in 17 of 225 subjects (7.6%), and all mutations were loss of function (LOF) and heterozygous. The genotype-phenotype relationship of patients carrying FH-associated mutations showed high heterogeneity. The logistic regression analysis showed that the smoking history, obesity and the family history of premature CHD were independent risk factors of PMI. In this study, a total of 19 patients (8.4%) were diagnosed as FH, and the proportion of smoking subjects in FH patients was higher than that in non-FH patients. CONCLUSIONS: FH-associated gene mutations were present in about 7.6% of Chinese patients with PMI. In addition to genetic factors, smoking history, lifestyle and other environmental factors may play a synergistic role in determining the phenotype of PMI. TRIAL REGISTRATION: Essential gene mutation of cholesterol metabolism in patients with premature myocardial infarction. ChiCTR-OCH-12002349.Registered 26 December 2014, http://www.chictr.org.cn/showproj.aspx?proj=7201 . More... »

PAGES

95

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12944-019-1042-3

DOI

http://dx.doi.org/10.1186/s12944-019-1042-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113355642

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30971288


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/2008/0604", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Genetics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lee", 
        "givenName": "Chongyou", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cui", 
        "givenName": "Yuxia", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Song", 
        "givenName": "Junxian", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Sufang", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Feng", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wu", 
        "givenName": "Manyan", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Long", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hu", 
        "givenName": "Dan", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Peking University People's Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411634.5", 
          "name": [
            "Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China. chenhongbj@medmail.com.cn.", 
            "Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China. chenhongbj@medmail.com.cn.", 
            "Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China. chenhongbj@medmail.com.cn."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chen", 
        "givenName": "Hong", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.atherosclerosis.2016.03.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008016428"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/heartjnl-2012-302976", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010827778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3126/njh.v10i1.9740", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012425135"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3126/njh.v10i1.9740", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012425135"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3109/07853890.2015.1042908", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014134984"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/md.0000000000002677", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021421928"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/md.0000000000002677", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021421928"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.0000155611.41961.bb", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021517900"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.atherosclerosis.2006.12.035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025997633"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.atherosclerosis.2006.12.035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025997633"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/ehu274", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032889506"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.atherosclerosis.2016.12.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038643228"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.atv.18.2.309", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042094258"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jamainternmed.2013.6075", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051207403"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacl.2017.02.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084083824"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11033-017-4112-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090363911", 
          "https://doi.org/10.1007/s11033-017-4112-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11033-017-4112-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090363911", 
          "https://doi.org/10.1007/s11033-017-4112-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hrtlng.2018.03.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103173505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hrtlng.2018.03.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103173505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12944-018-0900-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1108056554", 
          "https://doi.org/10.1186/s12944-018-0900-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12944-018-0900-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1108056554", 
          "https://doi.org/10.1186/s12944-018-0900-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.118.035658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110968988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.118.035658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110968988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.118.035658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110968988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.118.035658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110968988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.118.035658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110968988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.118.035658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110968988"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/01.npr.0000552677.31028.57", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111219028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/clc.23154", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111396401"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/clc.23154", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111396401"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/clc.23154", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111396401"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/clc.23154", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111396401"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/mol.0000000000000580", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111442586"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/mol.0000000000000580", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111442586"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12913-019-3872-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111507906", 
          "https://doi.org/10.1186/s12913-019-3872-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12913-019-3872-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1111507906", 
          "https://doi.org/10.1186/s12913-019-3872-0"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "BACKGROUND: The incidence of premature myocardial infarction (PMI) has gradually increased in recent years. Genetics plays a central role in the development of PMI. Familial hypercholesterolemia (FH) is one of the most common genetic disorders of cholesterol metabolism leading to PMI.\nOBJECTIVE: This study investigated the relationship between FH-associated genes and the phenotype of PMI to clarify the genetic spectrum of PMI diseases.\nMETHOD: This study enrolled PMI patients (n\u2009=\u2009225) and detected the mutations in their FH-associated genes (LDLR, APOB, PCSK9, LDLRAP1) by Sanger sequencing. At the same time, patients free of PMI (non-FH patients, n\u2009=\u200956) were enrolled as control, and a logistic regression analysis was used to identify risk factors associated with PMI. The diagnosis of FH was confirmed using \"2018 Chinese expert consensus of FH screening and diagnosis\" before the prevalence and clinical features of FH were analyzed.\nRESULTS: Pathogenic mutations in LDLR, APOB, PCSK9 and LDLRAP1 genes were found in 17 of 225 subjects (7.6%), and all mutations were loss of function (LOF) and heterozygous. The genotype-phenotype relationship of patients carrying FH-associated mutations showed high heterogeneity. The logistic regression analysis showed that the smoking history, obesity and the family history of premature CHD were independent risk factors of PMI. In this study, a total of 19 patients (8.4%) were diagnosed as FH, and the proportion of smoking subjects in FH patients was higher than that in non-FH patients.\nCONCLUSIONS: FH-associated gene mutations were present in about 7.6% of Chinese patients with PMI. In addition to genetic factors, smoking history, lifestyle and other environmental factors may play a synergistic role in determining the phenotype of PMI.\nTRIAL REGISTRATION: Essential gene mutation of cholesterol metabolism in patients with premature myocardial infarction. ChiCTR-OCH-12002349.Registered 26 December 2014, http://www.chictr.org.cn/showproj.aspx?proj=7201 .", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s12944-019-1042-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1031029", 
        "issn": [
          "1476-511X"
        ], 
        "name": "Lipids in Health and Disease", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "18"
      }
    ], 
    "name": "Effects of familial hypercholesterolemia-associated genes on the phenotype of premature myocardial infarction.", 
    "pagination": "95", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12944-019-1042-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113355642"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101147696"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30971288"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12944-019-1042-3", 
      "https://app.dimensions.ai/details/publication/pub.1113355642"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-15T09:18", 
    "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/v90/0000000376_0000000376/records_56173_00000006.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://lipidworld.biomedcentral.com/articles/10.1186/s12944-019-1042-3"
  }
]
 

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.10.1186/s12944-019-1042-3'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12944-019-1042-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12944-019-1042-3'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12944-019-1042-3'


 

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

179 TRIPLES      21 PREDICATES      48 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12944-019-1042-3 schema:about anzsrc-for:06
2 anzsrc-for:0604
3 schema:author Nee46c94c94c440bd8efcc3af2b9a1e7e
4 schema:citation sg:pub.10.1007/s11033-017-4112-5
5 sg:pub.10.1186/s12913-019-3872-0
6 sg:pub.10.1186/s12944-018-0900-8
7 https://doi.org/10.1001/jamainternmed.2013.6075
8 https://doi.org/10.1002/clc.23154
9 https://doi.org/10.1016/j.atherosclerosis.2006.12.035
10 https://doi.org/10.1016/j.atherosclerosis.2016.03.009
11 https://doi.org/10.1016/j.atherosclerosis.2016.12.021
12 https://doi.org/10.1016/j.hrtlng.2018.03.002
13 https://doi.org/10.1016/j.jacl.2017.02.007
14 https://doi.org/10.1093/eurheartj/ehu274
15 https://doi.org/10.1097/01.npr.0000552677.31028.57
16 https://doi.org/10.1097/md.0000000000002677
17 https://doi.org/10.1097/mol.0000000000000580
18 https://doi.org/10.1136/heartjnl-2012-302976
19 https://doi.org/10.1161/01.atv.18.2.309
20 https://doi.org/10.1161/01.cir.0000155611.41961.bb
21 https://doi.org/10.1161/circulationaha.118.035658
22 https://doi.org/10.3109/07853890.2015.1042908
23 https://doi.org/10.3126/njh.v10i1.9740
24 schema:datePublished 2019-12
25 schema:datePublishedReg 2019-12-01
26 schema:description BACKGROUND: The incidence of premature myocardial infarction (PMI) has gradually increased in recent years. Genetics plays a central role in the development of PMI. Familial hypercholesterolemia (FH) is one of the most common genetic disorders of cholesterol metabolism leading to PMI. OBJECTIVE: This study investigated the relationship between FH-associated genes and the phenotype of PMI to clarify the genetic spectrum of PMI diseases. METHOD: This study enrolled PMI patients (n = 225) and detected the mutations in their FH-associated genes (LDLR, APOB, PCSK9, LDLRAP1) by Sanger sequencing. At the same time, patients free of PMI (non-FH patients, n = 56) were enrolled as control, and a logistic regression analysis was used to identify risk factors associated with PMI. The diagnosis of FH was confirmed using "2018 Chinese expert consensus of FH screening and diagnosis" before the prevalence and clinical features of FH were analyzed. RESULTS: Pathogenic mutations in LDLR, APOB, PCSK9 and LDLRAP1 genes were found in 17 of 225 subjects (7.6%), and all mutations were loss of function (LOF) and heterozygous. The genotype-phenotype relationship of patients carrying FH-associated mutations showed high heterogeneity. The logistic regression analysis showed that the smoking history, obesity and the family history of premature CHD were independent risk factors of PMI. In this study, a total of 19 patients (8.4%) were diagnosed as FH, and the proportion of smoking subjects in FH patients was higher than that in non-FH patients. CONCLUSIONS: FH-associated gene mutations were present in about 7.6% of Chinese patients with PMI. In addition to genetic factors, smoking history, lifestyle and other environmental factors may play a synergistic role in determining the phenotype of PMI. TRIAL REGISTRATION: Essential gene mutation of cholesterol metabolism in patients with premature myocardial infarction. ChiCTR-OCH-12002349.Registered 26 December 2014, http://www.chictr.org.cn/showproj.aspx?proj=7201 .
27 schema:genre research_article
28 schema:inLanguage en
29 schema:isAccessibleForFree true
30 schema:isPartOf N293a9396052a4e8483edac51fc7fe8a9
31 Nc53d6c1a5d514b18aa5d157a8535f1bc
32 sg:journal.1031029
33 schema:name Effects of familial hypercholesterolemia-associated genes on the phenotype of premature myocardial infarction.
34 schema:pagination 95
35 schema:productId N395d579a2fdb4752840e5d10120fba32
36 N5099f1ea32174990a75d0011f6446c3f
37 N9d26d23ccba24e4ab0df0e00fb6f8381
38 Neb78efeb8ac34f5090982f53f5690d79
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113355642
40 https://doi.org/10.1186/s12944-019-1042-3
41 schema:sdDatePublished 2019-04-15T09:18
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher N92a4c94a51eb4c05a5f0753e1ddef981
44 schema:url https://lipidworld.biomedcentral.com/articles/10.1186/s12944-019-1042-3
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N040dd28a7d3a4522a0b86908be960bfa schema:affiliation https://www.grid.ac/institutes/grid.411634.5
49 schema:familyName Chen
50 schema:givenName Hong
51 rdf:type schema:Person
52 N1eef1cde735e42549186a72ae40c29b1 schema:affiliation https://www.grid.ac/institutes/grid.411634.5
53 schema:familyName Wu
54 schema:givenName Manyan
55 rdf:type schema:Person
56 N293a9396052a4e8483edac51fc7fe8a9 schema:volumeNumber 18
57 rdf:type schema:PublicationVolume
58 N29f85085edf245f1a4968d0d85f2aa4f schema:affiliation https://www.grid.ac/institutes/grid.411634.5
59 schema:familyName Cui
60 schema:givenName Yuxia
61 rdf:type schema:Person
62 N395d579a2fdb4752840e5d10120fba32 schema:name nlm_unique_id
63 schema:value 101147696
64 rdf:type schema:PropertyValue
65 N4021b85d5c97454588215f49f5743e4f rdf:first Nd8cf8c6e3eda460abcab38be3d09d9d0
66 rdf:rest N858600bd5b6b4f0589d7b3d1207c260b
67 N4838df010ab24eb49358e3ae8c713b31 rdf:first Nf3b2bb5b262142e383fd17af815b8ef6
68 rdf:rest N4021b85d5c97454588215f49f5743e4f
69 N4d300b17126d4ade9e0cf88cf98077b0 rdf:first N040dd28a7d3a4522a0b86908be960bfa
70 rdf:rest rdf:nil
71 N5099f1ea32174990a75d0011f6446c3f schema:name pubmed_id
72 schema:value 30971288
73 rdf:type schema:PropertyValue
74 N5aa03608976d472a8da752b892e268dc schema:affiliation https://www.grid.ac/institutes/grid.411634.5
75 schema:familyName Song
76 schema:givenName Junxian
77 rdf:type schema:Person
78 N5d325d29bc4c43f9afaffc0a865a63aa rdf:first N7142dbca4746462096c9de824e0cc3d3
79 rdf:rest Ne531f67adccc497492a4d3bcfe14db2e
80 N6bf48b9c865e4209896a3d7fea4eb275 schema:affiliation https://www.grid.ac/institutes/grid.411634.5
81 schema:familyName Hu
82 schema:givenName Dan
83 rdf:type schema:Person
84 N7142dbca4746462096c9de824e0cc3d3 schema:affiliation https://www.grid.ac/institutes/grid.411634.5
85 schema:familyName Li
86 schema:givenName Long
87 rdf:type schema:Person
88 N764cc36f293845eab5aafa8bb67bd444 rdf:first N5aa03608976d472a8da752b892e268dc
89 rdf:rest N4838df010ab24eb49358e3ae8c713b31
90 N81fde82f7428442996c499e90fbc234e schema:affiliation https://www.grid.ac/institutes/grid.411634.5
91 schema:familyName Lee
92 schema:givenName Chongyou
93 rdf:type schema:Person
94 N858600bd5b6b4f0589d7b3d1207c260b rdf:first N1eef1cde735e42549186a72ae40c29b1
95 rdf:rest N5d325d29bc4c43f9afaffc0a865a63aa
96 N92a4c94a51eb4c05a5f0753e1ddef981 schema:name Springer Nature - SN SciGraph project
97 rdf:type schema:Organization
98 N9d26d23ccba24e4ab0df0e00fb6f8381 schema:name doi
99 schema:value 10.1186/s12944-019-1042-3
100 rdf:type schema:PropertyValue
101 Na78744f2d9b04886a790399229d23caa rdf:first N29f85085edf245f1a4968d0d85f2aa4f
102 rdf:rest N764cc36f293845eab5aafa8bb67bd444
103 Nc53d6c1a5d514b18aa5d157a8535f1bc schema:issueNumber 1
104 rdf:type schema:PublicationIssue
105 Nd8cf8c6e3eda460abcab38be3d09d9d0 schema:affiliation https://www.grid.ac/institutes/grid.411634.5
106 schema:familyName Zhang
107 schema:givenName Feng
108 rdf:type schema:Person
109 Ne531f67adccc497492a4d3bcfe14db2e rdf:first N6bf48b9c865e4209896a3d7fea4eb275
110 rdf:rest N4d300b17126d4ade9e0cf88cf98077b0
111 Neb78efeb8ac34f5090982f53f5690d79 schema:name dimensions_id
112 schema:value pub.1113355642
113 rdf:type schema:PropertyValue
114 Nee46c94c94c440bd8efcc3af2b9a1e7e rdf:first N81fde82f7428442996c499e90fbc234e
115 rdf:rest Na78744f2d9b04886a790399229d23caa
116 Nf3b2bb5b262142e383fd17af815b8ef6 schema:affiliation https://www.grid.ac/institutes/grid.411634.5
117 schema:familyName Li
118 schema:givenName Sufang
119 rdf:type schema:Person
120 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
121 schema:name Biological Sciences
122 rdf:type schema:DefinedTerm
123 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
124 schema:name Genetics
125 rdf:type schema:DefinedTerm
126 sg:journal.1031029 schema:issn 1476-511X
127 schema:name Lipids in Health and Disease
128 rdf:type schema:Periodical
129 sg:pub.10.1007/s11033-017-4112-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090363911
130 https://doi.org/10.1007/s11033-017-4112-5
131 rdf:type schema:CreativeWork
132 sg:pub.10.1186/s12913-019-3872-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111507906
133 https://doi.org/10.1186/s12913-019-3872-0
134 rdf:type schema:CreativeWork
135 sg:pub.10.1186/s12944-018-0900-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1108056554
136 https://doi.org/10.1186/s12944-018-0900-8
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1001/jamainternmed.2013.6075 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051207403
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1002/clc.23154 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111396401
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/j.atherosclerosis.2006.12.035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025997633
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/j.atherosclerosis.2016.03.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008016428
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1016/j.atherosclerosis.2016.12.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038643228
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1016/j.hrtlng.2018.03.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103173505
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1016/j.jacl.2017.02.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084083824
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1093/eurheartj/ehu274 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032889506
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1097/01.npr.0000552677.31028.57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111219028
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1097/md.0000000000002677 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021421928
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1097/mol.0000000000000580 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111442586
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1136/heartjnl-2012-302976 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010827778
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1161/01.atv.18.2.309 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042094258
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1161/01.cir.0000155611.41961.bb schema:sameAs https://app.dimensions.ai/details/publication/pub.1021517900
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1161/circulationaha.118.035658 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110968988
167 rdf:type schema:CreativeWork
168 https://doi.org/10.3109/07853890.2015.1042908 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014134984
169 rdf:type schema:CreativeWork
170 https://doi.org/10.3126/njh.v10i1.9740 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012425135
171 rdf:type schema:CreativeWork
172 https://www.grid.ac/institutes/grid.411634.5 schema:alternateName Peking University People's Hospital
173 schema:name Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China.
174 Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing, China. chenhongbj@medmail.com.cn.
175 Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China.
176 Center for Cardiovascular Translational Research, Peking University People's Hospital, Beijing, China. chenhongbj@medmail.com.cn.
177 Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China.
178 Department of Cardiology, Peking University People's Hospital, Xizhimen South Rd. No.11, Xicheng district, Beijing, 100044, China. chenhongbj@medmail.com.cn.
179 rdf:type schema:Organization
 




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


...