Evidence mapPaperPMID 27768686Full record

SynthesisPLoS genetics2016

Effect of Insulin Resistance on Monounsaturated Fatty Acid Levels: A Multi-cohort Non-targeted Metabolomics and Mendelian Randomization Study.

Christoph Nowak, Samira Salihovic, Andrea Ganna, Stefan Brandmaier, Taru Tukiainen, Corey D Broeckling, Patrik K Magnusson, Jessica E Prenni, Rui Wang-Sattler, Annette Peters and 12 more

Erratum issuedOpen access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PLoS genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Metabolites as regulators of insulin sensitivity and metabolism.Nature reviews. Molecular cell biology · 2018
    Review
  10. Article
  11. Precision medicine in diabetes: an opportunity for clinical translation.Annals of the New York Academy of Sciences · 2018
    Review
  12. Article
  13. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors at 7 institutions in 5 countries.

Christoph NowakDepartment of Medical Sciences and Science for Life Laboratory, Molecular Epidemiology Unit, Uppsala University, Uppsala, Sweden.ORCID http://orcid.org/0000-0003-2071-5866
Samira SalihovicDepartment of Medical Sciences and Science for Life Laboratory, Molecular Epidemiology Unit, Uppsala University, Uppsala, Sweden.ORCID http://orcid.org/0000-0001-5752-4196
Andrea GannaAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America.
Stefan BrandmaierResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, München-Neuherberg, Germany.
Taru TukiainenInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.ORCID http://orcid.org/0000-0002-5404-8398
Corey D BroecklingProteomics and Metabolomics Facility, Colorado State University, Fort Collins, Colorado, United States of America.
Patrik K MagnussonDepartment of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-7315-7899
Jessica E PrenniProteomics and Metabolomics Facility, Colorado State University, Fort Collins, Colorado, United States of America.
Rui Wang-SattlerResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, München-Neuherberg, Germany.
Annette PetersInstitute of Epidemiology II, Helmholtz Zentrum München, München-Neuherberg, Germany.
Konstantin StrauchInstitute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Thomas MeitingerInstitute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany.
Vilmantas GiedraitisDepartment of Public Health and Caring Sciences, Geriatrics, Uppsala University, Uppsala, Sweden.
Johan ÄrnlövSchool of Health and Social Studies, Dalarna University, Falun, Sweden.
Christian BerneDepartment of Medical Sciences, Clinical Diabetology and Metabolism, Uppsala University, Uppsala, Sweden.
Christian GiegerResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, München-Neuherberg, Germany.
Samuli RipattiInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Lars LindDepartment of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.
Nancy L PedersenDepartment of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-8057-3543
Johan SundströmDepartment of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.
Erik IngelssonDepartment of Medical Sciences and Science for Life Laboratory, Molecular Epidemiology Unit, Uppsala University, Uppsala, Sweden.
Tove FallDepartment of Medical Sciences and Science for Life Laboratory, Molecular Epidemiology Unit, Uppsala University, Uppsala, Sweden.ORCID http://orcid.org/0000-0003-2071-5866
Uppsala University · SEHelmholtz Zentrum München · DEColorado State University · USKarolinska Institutet · SEUniversity of Helsinki · FIBroad Institute · USDalarna University · SE

Funding

Beyond GWAS of insulin resistance: An integrated approach to translate genetic association to functionR01DK106236 · NIDDK · STANFORD UNIVERSITY · PI KNOWLES, JOSHUA WILEY · 2016 to 2020
$2.4M
NIDDK NIH HHS R01 DK106236
6 · The paper itself

Abstract

Insulin resistance (IR) and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR) analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or β-cell responsiveness (disposition index) during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613) followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330), we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining "gold standard" measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development.

Indexed as

AdultAgedAged, 80 and overBile Acids and SaltsCaffeineDiabetes Mellitus, Type 2Fatty Acids, MonounsaturatedGlucoseGlucose Tolerance TestGlycerophospholipidsHumansInsulinInsulin ResistanceInsulin SecretionMaleMetabolic Networks and PathwaysBile Acids and SaltsCaffeineFatty Acids, MonounsaturatedGlucoseGlycerophospholipidsInsulinTyrosine

Identifiers

PMID27768686
PMCPMC5074591
OpenAlexW2535392050

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.