Others titles

  • Entres Pubmed
  • Pubmed Research Papers
  • MEDLINE/PubMed Data
  • MEDLINE/PubMed Baseline
  • MEDLINE/PubMed XML

Keywords

  • Pubmed Journals
  • NCBI Pubmed
  • Medline Search
  • Pubmed Citation
  • Medline Articles
  • MESH Terminology

MEDLINE PubMed Journal Citation Database

This dataset contains NLM’s database of citations and abstracts in the fields of medicine, nursing, dentistry, veterinary medicine, health care systems, and preclinical sciences.

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Description

MEDLINE is the U.S. National Library of Medicine® (NLM) premier bibliographic database that contains more than 23 million references to journal articles in life sciences with a concentration on biomedicine. A distinctive feature of MEDLINE is that the records are indexed with NLM Medical Subject Headings (MeSH®)

The subject scope of MEDLINE is biomedicine and health, broadly defined to encompass those areas of the life sciences, behavioral sciences, chemical sciences, and bioengineering needed by health professionals and others engaged in basic research and clinical care, public health, health policy development, or related educational activities. MEDLINE also covers life sciences vital to biomedical practitioners, researchers, and educators, including aspects of biology, environmental science, marine biology, plant and animal science as well as biophysics and chemistry. Publishers submit journals to an NIH-chartered advisory committee, the Literature Selection Technical Review Committee (LSTRC), which reviews and recommends journals for MEDLINE. The LSTRC considers the quality of the scientific content of a journal, including originality and the importance of the content for the MEDLINE global audience, using the guidelines found on the NLM Fact Sheet MEDLINE Journal Selection.

MEDLINE is the primary component of PubMed®, part of the Entrez series of databases provided by the NLM National Center for Biotechnology Information (NCBI). In addition to MEDLINE citations, PubMed also contains:
– In-process citations that provide a record for an article before it is indexed with MeSH® and added to MEDLINE or converted to out-of-scope status.
– Citations that precede the date that a journal was selected for MEDLINE indexing.
– Some OLDMEDLINE citations that have not yet been updated with current vocabulary and converted to MEDLINE status.
– Citations to articles that are out-of-scope (e.g., covering plate tectonics or astrophysics) from certain MEDLINE journals, primarily general science and general chemistry journals, for which the life sciences articles are indexed with MeSH for MEDLINE.
– Citations to some additional life science journals that submit full-text articles to PMC® (PubMed Central®) and receive a qualitative review by NLM.
– Citations for the majority of books and book chapters available on the NCBI Bookshelf.

MedlineCitation Status attribute

1. In-Data-Review
Records submitted to NLM electronically by publishers are added to PubMed at NLM and given in In-Data-Review status. Records in this status have undergone review at the journal issue level; i.e., the journal title, date of publication and volume/issue elements (referred to as the source data) are checked. They are not yet MEDLINE records because they have not undergone complete quality review and MeSH indexing; thus they should not be identified as MEDLINE records.

2. In-Process
Records in this status have undergone a citation level review; i.e., the author names, article title, and pagination are checked. All In-Data-Review records that entered the workflow via publisher electronic submission are redistributed again in In-Process status whether or not they were revised as a result of the second citation level review, and are not identified in any way as having been revised or not having been revised. Records created via NLM current other data entry mechanism, scanning/optical character recognition (OCR), are distributed for the first time in In-Process status after their creation. They are not yet MEDLINE records because they have not undergone complete quality review and MeSH indexing; thus they should not be identified as MEDLINE records. Most in-process records are eventually indexed with MeSH Headings and are elevated to completed MEDLINE status. However, some are determined to be out of scope (e.g., articles on plate tectonics or astrophysics from certain MEDLINE journals, primarily general science and chemistry journals, for which the life sciences articles are indexed for MEDLINE) and are not elevated to MEDLINE status; instead they become PubMed-not-Medline final status records. In rare cases the records are deleted and do not become PubMed-not-MEDLINE records.

3. MEDLINE
In-process records undergo rigorous quality assurance routines before they are elevated to MEDLINE status or to PubMed-not-MEDLINE status. Records in MEDLINE status are the only ‘true’ MEDLINE records .

4. OLDMEDLINE
A small percentage of the records in the OLDMEDLINE subset are in MedlineCitation Status = OLDMEDLINE. The criterion for records to be in OLDMEDLINE status is that all the original MeSH Headings have not yet been mapped to current MeSH. NLM exports both new and revised OLDMEDLINE records on an irregular and infrequent basis.

5. PubMed-not-MEDLINE
Records in this status are from journals included in MEDLINE and have undergone quality review but are not assigned MeSH headings because the cited item is not in scope for MEDLINE either by topic or by date of publication, or from non-MEDLINE journals and have undergone quality review.

6. Publisher
Records in Publisher status are not distributed via bulk download. At this time approximately 98% of PubMed’s content is distributed via bulk download. At any given time, there are between 400,000 to 500,000 additional records in Publisher MedlineCitation Status in PubMed. These are citations to author manuscripts of articles published by NIH-funded researchers and citations to books in the NCBI Bookshelf etc.

Citation Subset
The values and their definitions for Citation Subset are as follows. Note that several are closed subsets no longer being assigned.
AIM = citations from Abridged Index Medicus journals, a list of about 120 core clinical, English language journals.
B = citations from non-Index Medicus journals in the field of biotechnology (not currently used).
C = citations from non-Index Medicus journals in the field of communication disorders (not currently used).
D = citations from dental journals.
E = citations in the field of bioethics (includes records from the former BIOETHICS database).
F = older citations from one journal prior to its selection for Index Medicus; used to augment the database for NLM International MEDLARS Centers (not currently used).
H = citations from non-Index Medicus journals in the field of health administration (includes records from the former HealthSTAR database).
IM = citations from Index Medicus journals.
J = citations in the field of population information (not currently used; on records from the former POPLINE® database).
K = citations from non-Index Medicus journals relating to consumer health.
N = citations from nursing journals.
OM = pre-1966 citations from the older print indices of the Cumulated Index Medicus (CIM) and the Current List of Medical Literature (CLML).
Q = citations in the field of the history of medicine (includes records from the former HISTLINE® database).
QIS = citations from non-Index Medicus journals in the field of the history of medicine. (For NLM use effective in late 2006 because they require special handling at NLM; not a subset of Q; some journals previously designated as Q are now QIS.)
QO is subset of Q – indicates older history of medicine journal citations that were created before the former HISTLINE file was converted to a MEDLINE-like format. (For NLM use because they require special handling at NLM.)
R = citations from non-Index Medicus journals in the field of population and reproduction (not currently used).
S = citations in the field of space life sciences (includes records from the former SPACELINE™ database).
T = citations from non-Index Medicus journals in the field of health technology assessment (includes records from the former HealthSTAR database).
X = citations in the field of AIDS/HIV (includes records from the former AIDSLINE® database).

About this Dataset

Data Info

Date Created

1971

Last Modified

2020-09-25

Version

2020-09-25

Update Frequency

Daily

Temporal Coverage

1946 to 2018

Spatial Coverage

World

Source

John Snow Labs; National Library of Medicine (NLM);

Source License URL

Source License Requirements

N/A

Source Citation

N/A

Keywords

Pubmed Journals, NCBI Pubmed, Medline Search, Pubmed Citation, Medline Articles, MESH Terminology

Other Titles

Entres Pubmed, Pubmed Research Papers, MEDLINE/PubMed Data, MEDLINE/PubMed Baseline, MEDLINE/PubMed XML

Data Fields

Name Description Type Constraints
PubMed_IDThe PubMed unique identifier, is a 1 to 8-digit accession number with no leading zeros.integerrequired : 1 level : Nominal
PubMed_VersionUsed to accommodate the model of publishing known as "versioning"integerrequired : 1 level : Interval
Citation_StatusIndicates the stage of a citation.stringrequired : 1 enum : Array
Citation_OwnerIndicates the The party responsible for creating and validating the citation. Each citation has only one MedlineCitation Ownerstringrequired : 1 enum : Array
Citation_VersionIDUsed with “versioned” citationsstring-
Citation_Version_DateUsed with “versioned” citationsdate-
Citation_Indexing_MethodIndexing method used for citationstring-
Citation_Record_Completed_DateDate processing of the record ends i.e., MeSH Headings have been added, quality assurance validations are completed, and the completed record subsequently is distributed to PubMed.date-
Citation_Record_Revised_DateMay reside on records with Status = MEDLINE, OLDMEDLINE, and PubMed-not-MEDLINE. It identifies the date a change is made to a record in one of those statuses, either as a result of individual or global maintenance.date-
Citation_Other_SourceIDidentifies a.) the organization responsible for the information on the citation or the document where the information originated, and b.) a unique number for that citation or document.string-
Citation_Other_Abstract_TextIndicates the abstract created by a collaborating partner or other entitystring-
Citation_Other_Abstract_Text_TypeType of Other Abstractstring-
Citation_Other_Abstract_Text_LanguageIndicate on behalf of publishers that there are additional abstracts available at the publishers' Web sites or elsewhere.string-
Citation_Other_Abstract_Text_Copyright_InfoIndicate copyright statement provided by the publisher of the journalstring-
Citation_Mesh_Headings_ListNLM controlled vocabulary, Medical Subject Headings (MeSH®), is used to characterize the content of the articles represented by MEDLINE citationsstring-
Citation_Chemical_Drug_ListContains one or more chemicals or drugs,which are displayed as registry number and name of substance.string-
Citation_Protocol_Disease_ListIndicates Protocol Class 2 Supplementary Concept Record (SCR) terms and Disease Class 3 SCR termsstring-
Citation_Keywords_ListContains controlled terms that describe the content of the article.string-
Citation_Number_Of_ReferencesContains the number of bibliographic references listed in the article.integerlevel : Ratio
Citation_Subsetidentifies the subset for which MEDLINE records from certain journal lists or records on specialized topics were created. Some of these values are found on extremely small numbers of records.string-
Citation_Comments_CorrectionsThese data pertain to and contain citations to associated journal publications, e.g., comments, errata, retractions, or cited references, and enable outside links between the record at hand to its associated citation(s).string-
Citation_Gene_Symbol_ListContains the "symbol" or abbreviated form of gene names as reported in the literature.string-
Citation_Personal_Name_Subject_ListUsed for citations that contain a biographical note or obituary, or are entirely about the life or work of an individual or individuals.string-
Citation_Space_Flight_MissionContains the space flight mission name and/or number when results of research conducted in space are covered in a publication.string-
Citation_Investigator_ListContain personal names of individuals (e.g., collaborators and investigators) who are not authors of a paper but rather are listed in the paper as members of a collective/corporate group that is an author of the paper.string-
Citation_General_NoteContains supplemental or descriptive information related to the document cited in the MEDLINE record. It is a 'catchall' for various types of information included by NLM collaborating producers or by NLM.string-
Citation_Conflict_Of_Interest_StatementConflict of interest statementstring-
Journal_ISSNISSN (International Standard Serial Number) is always an eight-character value that uniquely identifies the cited journal. It is nine characters long in the hyphenated form: XXXX-XXXX.string-
Journal_ISSN_TypeIndicates which of the ISSNs assigned to the journal is recorded in the citation.stringenum : Array
Journal_TitleThe full journal titlestringrequired : 1
Journal_Title_ISO_AbbreviationISO Abbreviations are constructed at NLM to assist NCBI in linking from GenBank to PubMed. ISO Abbreviations created after 2007 are identical to the NLM title abbreviations.string-
Journal_Cited_MediumIndicates whether a citation is processed/indexed at NLM from the online or the print version of the journal.stringenum : Array
Journal_Volume_IssueThe volume number and the issue (part or supplement) of the journal in which the article was published.string-
Journal_Published_DateContains the full date on which the issue of the journal was publishedstring-
Journal_Published_CountryContains the place of publication of the journal.string-
Journal_Title_Standard_AbbreviationContains the standard abbreviation for the title of the journal in which an article appeared.string-
Journal_NLM_IDIt may appear as seven, eight or nine charcaters and is the preferred element to use when looking for the serial record for the journal in which the article was published.stringrequired : 1
Journal_ISSN_LinkingContains the ISSN designated by the ISSN Network to enable co-location or linking among the different media versions of a continuing resourcestring-
Article_TitleContains the entire title of the journal article.It is always in English; those titles originally published in a non-English language and translated are enclosed in square brackets.string-
Article_AuthorsContains the Personal and collective (corporate) author names published with the article.It includes author's lastname, forename, suffix, collective (corporate) names and affliation informationstring-
Article_LanguageContains the The language in which an article was published.stringrequired : 1
Article_Publish_ModelIdentify the medium/media in which the cited article is published.stringrequired : 1 enum : Array
Article_Abstract_TextEnglish-language abstracts taken directly from the published article. Abstracts in records may be truncated.string-
Article_Abstract_Text_Copyright_InfoContains a copyright statement provided by the publisher of the journal and appears only on records supplied electronically to NLM by the publisher.string-
Article_Publication_TypesIt identifies the type of article indexed for MEDLINE; it characterizes the nature of the information or the manner in which it is conveyed as well as the type of research support received (e.g., Review, Letter, Retracted Publication, Clinical Conference, Research Support, N.I.H., Extramural).stringrequired : 1
Article_PaginationIndicates the inclusive pages for the article cited.string-
Article_ELocationIDProvides an electronic location for items which lack standard page numbers. The element houses Digital Object Identifiers (DOIs) or Publisher Item Identifiers (PIIs) that are provided by publishers for new citations submitted to NLM for inclusion in MEDLINE/PubMed.string-
Article_DataBank_ListContains information pertaining to the registration of several types of data: 1) molecular sequence data; 2) clinical trial numbers; 3) gene expression/molecular abundance data; 4) PubChem identifiers; 5)Two general research databanks, the Dryad Digital Repository and figshare; and 6) BioProject identifiers.string-
Article_Grant_ListContains following information 1) research grant or contract number 2) grant acronym 3) institute acronym followed by the agency's hierarchical structure from lower to higher entity or agency name 4) country of the granting agencystring-
Article_Vernacular_TitleUsed for articles published in non-English languages and contains the original, untranslated title.string-
Article_Electronic_Published_DateContains the date the publisher made an electronic version of the articledate-
PubMed_HistoryChanges in the pubmed records, along with the status and the dates when it was changedstring-
PubMed_Publication_StatusPublication status of the recordstring-
PubMed_ArticleID_ListList of article ids and typesstring-

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PubMed IDPubMed VersionCitation StatusCitation OwnerCitation VersionIDCitation Version DateCitation Indexing MethodCitation Record Completed DateCitation Record Revised DateCitation Other SourceIDCitation Other Abstract TextCitation Other Abstract Text TypeCitation Other Abstract Text LanguageCitation Other Abstract Text Copyright InfoCitation Mesh Headings ListCitation Chemical Drug ListCitation Protocol Disease ListCitation Keywords ListCitation Number Of ReferencesCitation SubsetCitation Comments CorrectionsCitation Gene Symbol ListCitation Personal Name Subject ListCitation Space Flight MissionCitation Investigator ListCitation General NoteCitation Conflict Of Interest StatementJournal ISSNJournal ISSN TypeJournal TitleJournal Title ISO AbbreviationJournal Cited MediumJournal Volume IssueJournal Published DateJournal Published CountryJournal Title Standard AbbreviationJournal NLM IDJournal ISSN LinkingArticle TitleArticle AuthorsArticle LanguageArticle Publish ModelArticle Abstract TextArticle Abstract Text Copyright InfoArticle Publication TypesArticle PaginationArticle ELocationIDArticle DataBank ListArticle Grant ListArticle Vernacular TitleArticle Electronic Published DatePubMed HistoryPubMed Publication StatusPubMed ArticleID List
305253441PublisherNLM2018-12-11Owner:NOTNLM MajorTopic Generalized arterial calcification;MajorTopic infant;MajorTopic treatment;MajorTopic magnesium;MajorTopic etidronate1308-5735ElectronicJournal of clinical research in pediatric endocrinologyJ Clin Res Pediatr EndocrinolInternet;2018-12-11TurkeyJ Clin Res Pediatr Endocrinol101519456Magnesium and anti-phosphate treatment with bisphosphonates for Generalised Arterial Calcification of Infancy: a case reportDursun Fatma Department of Pediatric Endocrinology, Umraniye Training and Research Hospital, Istanbul, Turkey;Atasoy Öztürk Tülay Department of Radiology, Umraniye Training and Research Hospital, Istanbul, Turkey;Güven Serçin Department of Pediatric Nephrology, Umraniye Training and Research Hospital, Istanbul, Turkey;Kırmızıbekmez Heves Department of Pediatric Endocrinology, Umraniye Training and Research Hospital, Istanbul, Turkey;Seymen Karabulut Gülcan Department of Pediatric Endocrinology, Umraniye Training and Research Hospital, Istanbul, Turkey;Kalın Sevinç Department of Radiology, Umraniye Training and Research Hospital, Istanbul, Turkey;Sözeri Betül Department of Pediatric Rheumatology, SBU. Umraniye Training and Research Hospital, Istanbul, TurkeyengPrint-ElectronicGeneralized arterial calcification of infancy (GACI) is a rare autosomal- recessive disorder characterized by calcification of the internal elastic lamina, fibrotic myointimal proliferation of muscular arteries, and resultant arterial stenosis. Treatment with bisphosphonates has been proposed as a means of reducing arterial calcifications in GACI patients, although there is no formalized treatment approach. The case reported here is a patient with severe GACI diagnosed at 3 months of age who had no response to bisphosphonate treatment, but clinically improved after the initiation of magnesium and anti-phosphate (calcium carbonate) treatments. In patients unresponsive to bisphosphonate, magnesium and anti-phosphate treatment can be attempted.D016428 Journal Articledoi 10.4274/jcrpe.0204pubmed 2018-12-12 6:0;medline 2018-12-12 6:0;entrez 2018-12-12 6:0aheadofprintpubmed 30525344;doi 10.4274/jcrpe.0204
305253441PublisherNLM2018-12-17Owner:NOTNLM MajorTopic Generalized arterial calcification;MajorTopic infant;MajorTopic treatment;MajorTopic magnesium;MajorTopic etidronate1308-5735ElectronicJournal of clinical research in pediatric endocrinologyJ Clin Res Pediatr EndocrinolInternet;2018-Dec-11TurkeyJ Clin Res Pediatr Endocrinol101519456Magnesium and anti-phosphate treatment with bisphosphonates for Generalised Arterial Calcification of Infancy: a case reportDursun Fatma Department of Pediatric Endocrinology, Umraniye Training and Research Hospital, Istanbul, Turkey;Atasoy Öztürk Tülay Department of Radiology, Umraniye Training and Research Hospital, Istanbul, Turkey;Güven Serçin Department of Pediatric Nephrology, Umraniye Training and Research Hospital, Istanbul, Turkey;Kırmızıbekmez Heves Department of Pediatric Endocrinology, Umraniye Training and Research Hospital, Istanbul, Turkey;Seymen Karabulut Gülcan Department of Pediatric Endocrinology, Umraniye Training and Research Hospital, Istanbul, Turkey;Kalın Sevinç Department of Radiology, Umraniye Training and Research Hospital, Istanbul, Turkey;Sözeri Betül Department of Pediatric Rheumatology, SBU. Umraniye Training and Research Hospital, Istanbul, TurkeyengPrint-ElectronicGeneralized arterial calcification of infancy (GACI) is a rare autosomal- recessive disorder characterized by calcification of the internal elastic lamina, fibrotic myointimal proliferation of muscular arteries, and resultant arterial stenosis. Treatment with bisphosphonates has been proposed as a means of reducing arterial calcifications in GACI patients, although there is no formalized treatment approach. The case reported here is a patient with severe GACI diagnosed at 3 months of age who had no response to bisphosphonate treatment, but clinically improved after the initiation of magnesium and anti-phosphate (calcium carbonate) treatments. In patients unresponsive to bisphosphonate, magnesium and anti-phosphate treatment can be attempted.D016428 Journal Articledoi 10.4274/jcrpe.0204pubmed 2018-12-12 6:0;medline 2018-12-12 6:0;entrez 2018-12-12 6:0aheadofprintpubmed 30525344;doi 10.4274/jcrpe.0204
305253451PublisherNLM2018-12-171308-5263ElectronicTurkish journal of haematology : official journal of Turkish Society of HaematologyTurk J HaematolInternet;2018-Dec-11TurkeyTurk J Haematol96060651300-7777WITHDRAWN: Fok1 and Col1A1 Gene Polymorphisms and Development of Treatment-Related Bone Complications in Children with Acute Lymphoblastic Leukemia: focus on molecular changeMungmunpuntipantip Rujittika 26 Medical Center, Bangkok Thailand;Wiwanitkit Viroj Honorary professor, dr DY Patil University, Pune, India; visiting professor, Hainan Medical University, ChinaengPrint-ElectronicAhead of Print article withdrawn by Editor.D016428 Journal Articledoi 10.4274/tjh.2018.0424pubmed 2018-12-12 6:0;medline 2018-12-12 6:0;entrez 2018-12-12 6:0aheadofprintpubmed 30525345;doi 10.4274/tjh.2018.0424
305253451PublisherNLM2018-12-111308-5263ElectronicTurkish journal of haematology : official journal of Turkish Society of HaematologyTurk J HaematolInternet;2018-12-11TurkeyTurk J Haematol96060651300-7777WITHDRAWN: Fok1 and Col1A1 Gene Polymorphisms and Development of Treatment-Related Bone Complications in Children with Acute Lymphoblastic Leukemia: focus on molecular changeMungmunpuntipantip Rujittika 26 Medical Center, Bangkok Thailand;Wiwanitkit Viroj Honorary professor, dr DY Patil University, Pune, India; visiting professor, Hainan Medical University, ChinaengPrint-ElectronicAhead of Print article withdrawn by Editor.D016428 Journal Articledoi 10.4274/tjh.2018.0424pubmed 2018-12-12 6:0;medline 2018-12-12 6:0;entrez 2018-12-12 6:0aheadofprintpubmed 30525345;doi 10.4274/tjh.2018.0424
305253461PubMed-not-MEDLINENLM2018-12-171559-3908ElectronicEmergency medicine practiceEmerg Med PractInternet20;Suppl 122018-Dec-01United StatesEmerg Med Pract1008890971524-1971Points & Pearls: Influenza: diagnosis and management in the emergency departmentGiwa Al Assistant Professor of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY;Ogedegbe Chinwe Associate Professor of Emergency Medicine, Seton Hall School of Medicine, Nutley, NJ; Associate Professor of Emergency Medicine, Rutgers-New Jersey Medical School, Newark, NJ;Murphy Charles G. Department of Emergency Medicine, Metrowest Medical Center, Framingham, MA;Gupta Nachi Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY;Nusbaum Jeffrey EMS Fellow, University of Pittsburgh Medical Center, Pittsburgh, PAengElectronicEmergency clinicians must be aware of the current diagnostic and therapeutic recommendations for influenza and the available resources to guide management. This comprehensive review outlines the classification of influenza viruses, influenza pathophysiology, the identification of high-risk patients, and the importance of vaccination. Seasonal variations of influenza are discussed, as well as the rationale for limiting testing during periods of high prevalence. Differences between strains of influenza are discussed, as well as the challenges in achieving optimal vaccine effectiveness. Recommendations for use of the currently available oral, intranasal, and intravenous antiviral treatments are provided, as well as utilizing shared decision-making with patients regarding risks and benefits of treatment. [Points & Pearls is a digest of Emergency Medicine Practice]D016428 Journal Article1-2received 2018-11-01;accepted 2018-11-12;pubmed 2018-12-12 6:0;medline 2018-12-12 6:1;entrez 2018-12-12 6:0epublishpubmed 30525346;pii 591
305253461PubMed-not-MEDLINENLM2018-12-111559-3908ElectronicEmergency medicine practiceEmerg Med PractInternet20;Suppl 122018-12-01United StatesEmerg Med Pract1008890971524-1971Points & Pearls: Influenza: diagnosis and management in the emergency departmentGiwa Al Assistant Professor of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY;Ogedegbe Chinwe Associate Professor of Emergency Medicine, Seton Hall School of Medicine, Nutley, NJ; Associate Professor of Emergency Medicine, Rutgers-New Jersey Medical School, Newark, NJ;Murphy Charles G. Department of Emergency Medicine, Metrowest Medical Center, Framingham, MA;Gupta Nachi Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY;Nusbaum Jeffrey EMS Fellow, University of Pittsburgh Medical Center, Pittsburgh, PAengElectronicEmergency clinicians must be aware of the current diagnostic and therapeutic recommendations for influenza and the available resources to guide management. This comprehensive review outlines the classification of influenza viruses, influenza pathophysiology, the identification of high-risk patients, and the importance of vaccination. Seasonal variations of influenza are discussed, as well as the rationale for limiting testing during periods of high prevalence. Differences between strains of influenza are discussed, as well as the challenges in achieving optimal vaccine effectiveness. Recommendations for use of the currently available oral, intranasal, and intravenous antiviral treatments are provided, as well as utilizing shared decision-making with patients regarding risks and benefits of treatment. [Points & Pearls is a digest of Emergency Medicine Practice]D016428 Journal Article1-2received 2018-11-01;accepted 2018-11-12;pubmed 2018-12-12 6:0;medline 2018-12-12 6:0;entrez 2018-12-12 6:0epublishpubmed 30525346;pii 591
305253471PubMed-not-MEDLINENLM2018-12-15Owner:NOTNLM MajorTopic lipoproteins;MajorTopic Mendelian randomization analysis;MajorTopic metabolomicsRefType:Cites Int J Epidemiol. 2013 Feb;42(1):111-27 22507743 ;RefType:Cites N Engl J Med. 2016 Dec;375(22):2144-2153 27959767 ;RefType:Cites Circ Res. 2017 May 12;120(10):1537-1539 28495986 ;RefType:Cites J Am Coll Cardiol. 2013 Nov 12;62(20):1906-8 24055740 ;RefType:Cites Circ Cardiovasc Genet. 2015 Feb;8(1):192-206 25691689 ;RefType:Cites Circ Cardiovasc Genet. 2017 Dec;10(6):null 29237679 ;RefType:Cites N Engl J Med. 2017 Apr 20;376(16):1527-1539 28304242 ;RefType:Cites JAMA Cardiol. 2016 Sep 1;1(6):692-9 27487401 ;RefType:Cites Int J Epidemiol. 2013 Feb;42(1):97-110 22507742 ;RefType:Cites Nat Commun. 2016 Mar 23;7:11122 27005778 ;RefType:Cites N Engl J Med. 2017 Jul 20;377(3):211-221 28538136 ;RefType:Cites Arterioscler Thromb Vasc Biol. 2018 Jul;38(7):1644-1655 29880491 ;RefType:Cites Am J Epidemiol. 2017 Nov 1;186(9):1084-1096 29106475 ;RefType:Cites Lancet. 2017 Nov 25;390(10110):2360-2371 28941948 ;RefType:Cites Arterioscler Thromb Vasc Biol. 2017 Jan;37(1):43-48 27856457 ;RefType:Cites J Am Coll Cardiol. 2016 Mar 15;67(10):1211-1213 26965543 ;RefType:Cites Eur Heart J. 2018 Jul 14;39(27):2540-2545 29020411 ;RefType:Cites Nat Rev Cardiol. 2017 Nov;14(11):635-636 28980665 ;RefType:Cites Lancet. 2014 Aug 16;384(9943):607-617 25131980 ;RefType:Cites Nat Genet. 2012 Jan 29;44(3):269-76 22286219 ;RefType:Cites Eur Heart J. 2018 Jul 14;39(27):2546-2550 29236976 ;RefType:Cites J Am Heart Assoc. 2015 Nov 19;4(11):null 26586732 ;RefType:Cites J Am Heart Assoc. 2017 Jul 21;6(7):null 28733430 ;RefType:Cites Am J Cardiol. 2018 Feb 1;121(3):308-314 29221604 ;RefType:Cites N Engl J Med. 2015 Apr 16;372(16):1489-99 25773378 ;RefType:Cites J Am Coll Cardiol. 2016 Mar 15;67(10):1200-1210 26965542 ;RefType:Cites J Am Heart Assoc. 2017 Dec 9;6(12):null 29223956 ;RefType:Cites Lancet. 2015 Jan 24;385(9965):351-61 25262344 ;RefType:Cites Proc Natl Acad Sci U S A. 2013 Jan 29;110(5):1917-22 23277558 ;RefType:Cites Diabetes Care. 2016 May;39(5):833-46 27208380 ;RefType:Cites Lancet. 2014 Aug 16;384(9943):626-635 25131982 ;RefType:Cites N Engl J Med. 2006 Mar 23;354(12):1264-72 16554528 ;RefType:Cites Arterioscler Thromb Vasc Biol. 2005 Aug;25(8):1678-83 15879301 ;RefType:Cites Lancet. 2002 Nov 23;360(9346):1623-30 12457784 ;RefType:Cites N Engl J Med. 2015 Apr 16;372(16):1500-9 25773607 ;RefType:Cites Lancet. 2012 Aug 11;380(9841):581-90 22607822 ;RefType:Cites Circulation. 2015 Mar 3;131(9):774-85 25573147 ;RefType:Cites Int J Epidemiol. 2011 Dec;40(6):1652-66 22158673 ;RefType:Cites J Am Coll Cardiol. 2010 Jun 22;55(25):2833-42 20579540 ;RefType:Cites J Am Coll Cardiol. 2018 Feb 13;71(6):620-632 29420958 ;RefType:Cites Atherosclerosis. 2018 Feb;269:159-165 29366988 ;RefType:Cites N Engl J Med. 2017 May 4;376(18):1713-1722 28304224 ;RefType:Cites Lancet. 2016 Nov 19;388(10059):2532-2561 27616593 ;RefType:Cites Nat Genet. 2009 Jan;41(1):35-46 19060910 ;RefType:Cites Lancet Diabetes Endocrinol. 2017 Feb;5(2):97-105 27908689 ;RefType:Cites Circulation. 2013 Jan 22;127(3):340-8 23258601 ;RefType:Cites Eur J Heart Fail. 2018 Apr;20(4):663-673 29226610 ;RefType:Cites Int J Epidemiol. 2003 Feb;32(1):1-22 12689998 ;RefType:Cites Cell Syst. 2015 Oct 28;1(4):293-301 27136058 1524-4539ElectronicCirculationCirculationInternet138;222018-11-27United StatesCirculation1477630009-7322Metabolomic Consequences of Genetic Inhibition of PCSK9 Compared With Statin TreatmentSliz Eeva Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Kettunen Johannes Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Holmes Michael Medical Research Council Population Health Research Unit, University of Oxford, United Kingdom;Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;National Institute for Health Research, Oxford Biomedical Research Centre,Oxford University Hospital, United Kingdom;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Williams Clare MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;Homerton College, University of Cambridge, United Kingdom;Boachie Charles Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Wang Qin Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;Männikkö Minna Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Sebert Sylvain Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, United Kingdom;Walters Robin Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lin Kuang Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Millwood Lona Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Clarke Robert Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Li Liming Chinese Academy of Medical Sciences, Beijing, China;Department of Global Health, School of Public Health, Peking University, Beijing, China;Rankin N Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Welsh Paul Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Delles Christian Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Jukema J Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Cardiology, Leiden University Medical Center, The Netherlands;Trompet Stella Department of Cardiology, Leiden University Medical Center, The Netherlands;Department of Internal Medicine, Section of Gerontologyand Geriatrics, Leiden University Medical Center, The Netherlands;Ford Ian Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Perola Markus National Institute for Health and Welfare, Helsinki, Finland;Institute for Molecular Medicine Finland, University of Helsinki;University of Tartu, Estonian Genome Center, Estonia;Salomaa Veikko National Institute for Health and Welfare, Helsinki, Finland;Järvelin Marjo-Riitta Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, United Kingdom;Unit of Primary Care, Oulu University Hospital, Oulu, Finland;Chen Zhengming Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lawlor Debbie Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Ala-Korpela Mika Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio;Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia;Danesh John MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Wellcome Trust Sanger Institute, Hinxton, United Kingdom;Smith George Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Sattar Naveed Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Butterworth Adam MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Würtz Peter Diabetes and Obesity Research Program, University of Helsinki, Finland;Nightingale Health Ltd, Helsinki, FinlandengPrintBACKGROUND Both statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors lower blood low-density lipoprotein cholesterol levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these 2 lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects ofgenetic inhibition of PCSK9, acting as a naturally occurring trial.;METHODS Two hundred twenty-eight circulating metabolic measureswere quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5359 individuals (2659 on treatment) in the PROSPER (Prospective Study of Pravastatin in the Elderly at Risk) trial at 6 months postrandomization. The corresponding metabolic measures wereanalyzed in 8 population cohorts (N=72 185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors.;RESULTS Scaled to an equivalent lowering of low-density lipoproteincholesterol, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of very-low-density lipoprotein cholesterol compared with statin therapy (54% versus 77% reduction, relative tothe lowering effect on low-density lipoprotein cholesterol; P=2×10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA), whereas statin treatment weakly lowered GlycA levels.;CONCLUSIONS Genetic inhibition of PCSK9 had similar metabolic effectsto statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on very-low-density lipoprotein lipids compared with statins for an equivalent lowering of low-density lipoprotein cholesterol, which potentially translate into smaller reductions in cardiovascular disease risk.© 2018 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.D016428 Journal Article2499–2512 Wellcome Trust United Kingdom;268834 European Research Council International;MC_UU_12013/1 Medical Research Council United Kingdom;MC_UU_12013/5 Medical Research Council United Kingdomreceived 2018-03-20;accepted 2018-06-22;pmc-release 2019-11-27;pubmed 2018-12-12 6:0;medline 2018-12-12 6:1;entrez 2018-12-12 6:0ppublishpubmed 30525347;doi 10.1161/CIRCULATIONAHA.118.034942;pmc PMC6254781;mid EMS79324
305253471PubMed-not-MEDLINENLM2018-12-14Owner:NOTNLM MajorTopic lipoproteins;MajorTopic Mendelian randomization analysis;MajorTopic metabolomicsRefType:Cites Int J Epidemiol. 2013 Feb;42(1):111-27 22507743 ;RefType:Cites N Engl J Med. 2016 Dec;375(22):2144-2153 27959767 ;RefType:Cites Circ Res. 2017 May 12;120(10):1537-1539 28495986 ;RefType:Cites J Am Coll Cardiol. 2013 Nov 12;62(20):1906-8 24055740 ;RefType:Cites Circ Cardiovasc Genet. 2015 Feb;8(1):192-206 25691689 ;RefType:Cites Circ Cardiovasc Genet. 2017 Dec;10(6):null 29237679 ;RefType:Cites N Engl J Med. 2017 Apr 20;376(16):1527-1539 28304242 ;RefType:Cites JAMA Cardiol. 2016 Sep 1;1(6):692-9 27487401 ;RefType:Cites Int J Epidemiol. 2013 Feb;42(1):97-110 22507742 ;RefType:Cites Nat Commun. 2016 Mar 23;7:11122 27005778 ;RefType:Cites N Engl J Med. 2017 Jul 20;377(3):211-221 28538136 ;RefType:Cites Arterioscler Thromb Vasc Biol. 2018 Jul;38(7):1644-1655 29880491 ;RefType:Cites Am J Epidemiol. 2017 Nov 1;186(9):1084-1096 29106475 ;RefType:Cites Lancet. 2017 Nov 25;390(10110):2360-2371 28941948 ;RefType:Cites Arterioscler Thromb Vasc Biol. 2017 Jan;37(1):43-48 27856457 ;RefType:Cites J Am Coll Cardiol. 2016 Mar 15;67(10):1211-1213 26965543 ;RefType:Cites Eur Heart J. 2018 Jul 14;39(27):2540-2545 29020411 ;RefType:Cites Nat Rev Cardiol. 2017 Nov;14(11):635-636 28980665 ;RefType:Cites Lancet. 2014 Aug 16;384(9943):607-617 25131980 ;RefType:Cites Nat Genet. 2012 Jan 29;44(3):269-76 22286219 ;RefType:Cites Eur Heart J. 2018 Jul 14;39(27):2546-2550 29236976 ;RefType:Cites J Am Heart Assoc. 2015 Nov 19;4(11):null 26586732 ;RefType:Cites J Am Heart Assoc. 2017 Jul 21;6(7):null 28733430 ;RefType:Cites Am J Cardiol. 2018 Feb 1;121(3):308-314 29221604 ;RefType:Cites N Engl J Med. 2015 Apr 16;372(16):1489-99 25773378 ;RefType:Cites J Am Coll Cardiol. 2016 Mar 15;67(10):1200-1210 26965542 ;RefType:Cites J Am Heart Assoc. 2017 Dec 9;6(12):null 29223956 ;RefType:Cites Lancet. 2015 Jan 24;385(9965):351-61 25262344 ;RefType:Cites Proc Natl Acad Sci U S A. 2013 Jan 29;110(5):1917-22 23277558 ;RefType:Cites Diabetes Care. 2016 May;39(5):833-46 27208380 ;RefType:Cites Lancet. 2014 Aug 16;384(9943):626-635 25131982 ;RefType:Cites N Engl J Med. 2006 Mar 23;354(12):1264-72 16554528 ;RefType:Cites Arterioscler Thromb Vasc Biol. 2005 Aug;25(8):1678-83 15879301 ;RefType:Cites Lancet. 2002 Nov 23;360(9346):1623-30 12457784 ;RefType:Cites N Engl J Med. 2015 Apr 16;372(16):1500-9 25773607 ;RefType:Cites Lancet. 2012 Aug 11;380(9841):581-90 22607822 ;RefType:Cites Circulation. 2015 Mar 3;131(9):774-85 25573147 ;RefType:Cites Int J Epidemiol. 2011 Dec;40(6):1652-66 22158673 ;RefType:Cites J Am Coll Cardiol. 2010 Jun 22;55(25):2833-42 20579540 ;RefType:Cites J Am Coll Cardiol. 2018 Feb 13;71(6):620-632 29420958 ;RefType:Cites Atherosclerosis. 2018 Feb;269:159-165 29366988 ;RefType:Cites N Engl J Med. 2017 May 4;376(18):1713-1722 28304224 ;RefType:Cites Lancet. 2016 Nov 19;388(10059):2532-2561 27616593 ;RefType:Cites Nat Genet. 2009 Jan;41(1):35-46 19060910 ;RefType:Cites Lancet Diabetes Endocrinol. 2017 Feb;5(2):97-105 27908689 ;RefType:Cites Circulation. 2013 Jan 22;127(3):340-8 23258601 ;RefType:Cites Eur J Heart Fail. 2018 Apr;20(4):663-673 29226610 ;RefType:Cites Int J Epidemiol. 2003 Feb;32(1):1-22 12689998 ;RefType:Cites Cell Syst. 2015 Oct 28;1(4):293-301 27136058 1524-4539ElectronicCirculationCirculationInternet138;222018-11-27United StatesCirculation1477630009-7322Metabolomic Consequences of Genetic Inhibition of PCSK9 Compared With Statin TreatmentSliz Eeva Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Kettunen Johannes Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Holmes Michael Medical Research Council Population Health Research Unit, University of Oxford, United Kingdom;Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;National Institute for Health Research, Oxford Biomedical Research Centre,Oxford University Hospital, United Kingdom;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Williams Clare MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;Homerton College, University of Cambridge, United Kingdom;Boachie Charles Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Wang Qin Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;Männikkö Minna Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Sebert Sylvain Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, United Kingdom;Walters Robin Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lin Kuang Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Millwood Lona Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Clarke Robert Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Li Liming Chinese Academy of Medical Sciences, Beijing, China;Department of Global Health, School of Public Health, Peking University, Beijing, China;Rankin N Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Welsh Paul Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Delles Christian Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Jukema J Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Cardiology, Leiden University Medical Center, The Netherlands;Trompet Stella Department of Cardiology, Leiden University Medical Center, The Netherlands;Department of Internal Medicine, Section of Gerontologyand Geriatrics, Leiden University Medical Center, The Netherlands;Ford Ian Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Perola Markus National Institute for Health and Welfare, Helsinki, Finland;Institute for Molecular Medicine Finland, University of Helsinki;University of Tartu, Estonian Genome Center, Estonia;Salomaa Veikko National Institute for Health and Welfare, Helsinki, Finland;Järvelin Marjo-Riitta Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, United Kingdom;Unit of Primary Care, Oulu University Hospital, Oulu, Finland;Chen Zhengming Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lawlor Debbie Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Ala-Korpela Mika Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio;Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia;Danesh John MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Wellcome Trust Sanger Institute, Hinxton, United Kingdom;Smith George Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Sattar Naveed Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Butterworth Adam MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Würtz Peter Diabetes and Obesity Research Program, University of Helsinki, Finland;Nightingale Health Ltd, Helsinki, FinlandengPrintBACKGROUND Both statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors lower blood low-density lipoprotein cholesterol levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these 2 lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects ofgenetic inhibition of PCSK9, acting as a naturally occurring trial.;METHODS Two hundred twenty-eight circulating metabolic measureswere quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5359 individuals (2659 on treatment) in the PROSPER (Prospective Study of Pravastatin in the Elderly at Risk) trial at 6 months postrandomization. The corresponding metabolic measures wereanalyzed in 8 population cohorts (N=72 185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors.;RESULTS Scaled to an equivalent lowering of low-density lipoproteincholesterol, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of very-low-density lipoprotein cholesterol compared with statin therapy (54% versus 77% reduction, relative tothe lowering effect on low-density lipoprotein cholesterol; P=2×10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA), whereas statin treatment weakly lowered GlycA levels.;CONCLUSIONS Genetic inhibition of PCSK9 had similar metabolic effectsto statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on very-low-density lipoprotein lipids compared with statins for an equivalent lowering of low-density lipoprotein cholesterol, which potentially translate into smaller reductions in cardiovascular disease risk.© 2018 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.D016428 Journal Article2499–2512received 2018-03-20;accepted 2018-06-22;pmc-release 2019-11-27;pubmed 2018-12-12 6:0;medline 2018-12-12 6:1;entrez 2018-12-12 6:0ppublishpubmed 30525347;doi 10.1161/CIRCULATIONAHA.118.034942;pmc PMC6254781;mid EMS79324
305253471PubMed-not-MEDLINENLM2018-12-11Owner:NOTNLM MajorTopic lipoproteins;MajorTopic Mendelian randomization analysis;MajorTopic metabolomics1524-4539ElectronicCirculationCirculationInternet138;222018-11-27United StatesCirculation1477630009-7322Metabolomic Consequences of Genetic Inhibition of PCSK9 Compared With Statin TreatmentSliz Eeva Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Kettunen Johannes Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Holmes Michael Medical Research Council Population Health Research Unit, University of Oxford, United Kingdom;Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;National Institute for Health Research, Oxford Biomedical Research Centre,Oxford University Hospital, United Kingdom;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Williams Clare MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;Homerton College, University of Cambridge, United Kingdom;Boachie Charles Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Wang Qin Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;Männikkö Minna Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Sebert Sylvain Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, United Kingdom;Walters Robin Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lin Kuang Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Millwood Lona Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Clarke Robert Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Li Liming Chinese Academy of Medical Sciences, Beijing, China;Department of Global Health, School of Public Health, Peking University, Beijing, China;Rankin N Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Welsh Paul Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Delles Christian Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Jukema J Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Cardiology, Leiden University Medical Center, The Netherlands;Trompet Stella Department of Cardiology, Leiden University Medical Center, The Netherlands;Department of Internal Medicine, Section of Gerontologyand Geriatrics, Leiden University Medical Center, The Netherlands;Ford Ian Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Perola Markus National Institute for Health and Welfare, Helsinki, Finland;Institute for Molecular Medicine Finland, University of Helsinki;University of Tartu, Estonian Genome Center, Estonia;Salomaa Veikko National Institute for Health and Welfare, Helsinki, Finland;Järvelin Marjo-Riitta Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, United Kingdom;Unit of Primary Care, Oulu University Hospital, Oulu, Finland;Chen Zhengming Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lawlor Debbie Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Ala-Korpela Mika Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio;Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia;Danesh John MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Wellcome Trust Sanger Institute, Hinxton, United Kingdom;Smith George Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Sattar Naveed Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Butterworth Adam MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Würtz Peter Diabetes and Obesity Research Program, University of Helsinki, Finland;Nightingale Health Ltd, Helsinki, FinlandengPrintBACKGROUND Both statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors lower blood low-density lipoprotein cholesterol levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these 2 lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects ofgenetic inhibition of PCSK9, acting as a naturally occurring trial.;METHODS Two hundred twenty-eight circulating metabolic measureswere quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5359 individuals (2659 on treatment) in the PROSPER (Prospective Study of Pravastatin in the Elderly at Risk) trial at 6 months postrandomization. The corresponding metabolic measures wereanalyzed in 8 population cohorts (N=72 185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors.;RESULTS Scaled to an equivalent lowering of low-density lipoproteincholesterol, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of very-low-density lipoprotein cholesterol compared with statin therapy (54% versus 77% reduction, relative tothe lowering effect on low-density lipoprotein cholesterol; P=2×10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA), whereas statin treatment weakly lowered GlycA levels.;CONCLUSIONS Genetic inhibition of PCSK9 had similar metabolic effectsto statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on very-low-density lipoprotein lipids compared with statins for an equivalent lowering of low-density lipoprotein cholesterol, which potentially translate into smaller reductions in cardiovascular disease risk.© 2018 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.D016428 Journal Article2499–2512received 2018-03-20;accepted 2018-06-22;pubmed 2018-12-12 6:0;medline 2018-12-12 6:0;entrez 2018-12-12 6:0ppublishpubmed 30525347;doi 10.1161/CIRCULATIONAHA.118.034942
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Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Kettunen Johannes Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Holmes Michael Medical Research Council Population Health Research Unit, University of Oxford, United Kingdom;Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;National Institute for Health Research, Oxford Biomedical Research Centre,Oxford University Hospital, United Kingdom;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Williams Clare MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;Homerton College, University of Cambridge, United Kingdom;Boachie Charles Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Wang Qin Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;Männikkö Minna Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Sebert Sylvain Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, United Kingdom;Walters Robin Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lin Kuang Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Millwood Lona Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Clarke Robert Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Li Liming Chinese Academy of Medical Sciences, Beijing, China;Department of Global Health, School of Public Health, Peking University, Beijing, China;Rankin N Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Welsh Paul Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Delles Christian Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Jukema J Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Department of Cardiology, Leiden University Medical Center, The Netherlands;Trompet Stella Department of Cardiology, Leiden University Medical Center, The Netherlands;Department of Internal Medicine, Section of Gerontologyand Geriatrics, Leiden University Medical Center, The Netherlands;Ford Ian Robertson Centre for Biostatistics, University of Glasgow, UnitedKingdom;Perola Markus National Institute for Health and Welfare, Helsinki, Finland;Institute for Molecular Medicine Finland, University of Helsinki;University of Tartu, Estonian Genome Center, Estonia;Salomaa Veikko National Institute for Health and Welfare, Helsinki, Finland;Järvelin Marjo-Riitta Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, United Kingdom;Unit of Primary Care, Oulu University Hospital, Oulu, Finland;Chen Zhengming Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom;Lawlor Debbie Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Ala-Korpela Mika Center for Life Course Health Research, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Computational Medicine, Faculty of Medicine, University of Oulu,Finland. Biocenter Oulu, Oulu, Finland;Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne,Victoria, Australia;NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio;Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia;Danesh John MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Wellcome Trust Sanger Institute, Hinxton, United Kingdom;Smith George Medical Research Council Integrative Epidemiology Unit, University of Bristol,United Kingdom;Population Health Science, Bristol Medical School, University of Bristol,United Kingdom;Sattar Naveed Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom;Butterworth Adam MRC/BHF Cardiovascular Epidemiology Unit, Department ofPublic Health and Primary Care, University of Cambridge, United Kingdom;National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, United Kingdom;Würtz Peter Diabetes and Obesity Research Program, University of Helsinki, Finland;Nightingale Health Ltd, Helsinki, FinlandengPrintBACKGROUND Both statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors lower blood low-density lipoprotein cholesterol levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these 2 lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects ofgenetic inhibition of PCSK9, acting as a naturally occurring trial.;METHODS Two hundred twenty-eight circulating metabolic measureswere quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5359 individuals (2659 on treatment) in the PROSPER (Prospective Study of Pravastatin in the Elderly at Risk) trial at 6 months postrandomization. The corresponding metabolic measures wereanalyzed in 8 population cohorts (N=72 185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors.;RESULTS Scaled to an equivalent lowering of low-density lipoproteincholesterol, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of very-low-density lipoprotein cholesterol compared with statin therapy (54% versus 77% reduction, relative tothe lowering effect on low-density lipoprotein cholesterol; P=2×10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA), whereas statin treatment weakly lowered GlycA levels.;CONCLUSIONS Genetic inhibition of PCSK9 had similar metabolic effectsto statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on very-low-density lipoprotein lipids compared with statins for an equivalent lowering of low-density lipoprotein cholesterol, which potentially translate into smaller reductions in cardiovascular disease risk.© 2018 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.D016428 Journal Article2499–2512 Wellcome Trust United Kingdom;268834 European Research Council International;MC_UU_12013/1 Medical Research Council United Kingdom;MC_UU_12013/5 Medical Research Council United Kingdomreceived 2018-03-20;accepted 2018-06-22;pmc-release 2019-11-27;pubmed 2018-12-12 6:0;medline 2018-12-12 6:1;entrez 2018-12-12 6:0ppublishpubmed 30525347;doi 10.1161/CIRCULATIONAHA.118.034942;pmc PMC6254781;mid EMS79324