Evidence map›Paper›PMID 24905067›Full record

SynthesisThe Journal of clinical endocrinology and metabolism2014

Multiple metabolic genetic risk scores and type 2 diabetes risk in three racial/ethnic groups.

Yann C Klimentidis, Nathan E Wineinger, Ana I Vazquez, Gustavo de Los Campos

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in The Journal of clinical endocrinology and metabolism, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Article
  12. Observational
  13. Article
  14. Article
  15. Review
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Yann C KlimentidisMel and Enid Zuckerman College of Public Health (Y.C.K.), Division of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona 85724; Scripps Translational Science Institute (N.E.W.), La Jolla, California 92037; and Section on Statistical Genetics (A.I.V., G.d.l.C.), Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama 35294.
Nathan E Wineinger
Ana I Vazquez
Gustavo de Los Campos
University of Alabama at Birmingham · USScripps Research Institute · USUniversity of Arizona · US

Funding

Scripps Translational Science InstituteUL1TR001114 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2013 to 2017
$24.0M
Statistical Tools for Whole-Genome Prediction of Complex Traits and DiseasesR01GM101219 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LOS CAMPOS, GUSTAVO · 2012 to 2017
$1.6M
Factors Affecting Prediction Accuracy of Complex Human Traits and DiseasesR01GM099992 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LOS CAMPOS, GUSTAVO · 2012 to 2015
$1.0M
Whole-Genome Prediction of Type-2 Diabetes Susceptibility in Various PopulationsK01DK095032 · NIDDK · UNIVERSITY OF ARIZONA · PI KLIMENTIDIS, YANN CHARLES · 2012 to 2014
$440k
NCATS NIH HHS UL1 TR001114NCATS NIH HHS UL1TR001114NIDDK NIH HHS K01 DK095032NIDDK NIH HHS K01DK095032NIGMS NIH HHS R01 GM099992NIGMS NIH HHS R01GM099992NIGMS NIH HHS R01 GM101219NIGMS NIH HHS R01GM101219
6 · The paper itself

Abstract

unlabelledCONTEXT/RATIONALE: Meta-analyses of genome-wide association studies have identified many single-nucleotide polymorphisms associated with various metabolic and cardiovascular traits, offering us the opportunity to learn about and capitalize on the links between cardiometabolic traits and type 2 diabetes (T2D).

designIn multiple datasets comprising over 30 000 individuals and 3 ethnic/racial groups, we calculated 17 genetic risk scores (GRSs) for glycemic, anthropometric, lipid, hemodynamic, and other traits, based on the results of recent trait-specific meta-analyses of genome-wide association studies, and examined associations with T2D risk. Using a training-testing procedure, we evaluated whether additional GRSs could contribute to risk prediction.

resultsIn European Americans, we find that GRSs for T2D, fasting glucose, fasting insulin, and body mass index are associated with T2D risk. In African Americans, GRSs for T2D, fasting insulin, and waist-to-hip ratio are associated with T2D. In Hispanic Americans, GRSs for T2D and body mass index are associated with T2D. We observed a trend among European Americans suggesting that genetic risk for hyperlipidemia is inversely associated with T2D risk. The use of additional GRSs resulted in only small changes in prediction accuracy in multiple independent validation datasets.

conclusionsThe analysis of multiple GRSs can shed light on T2D etiology and how it varies across ethnic/racial groups. Our findings using multiple GRSs are consistent with what is known about the differences in T2D pathogenesis across racial/ethnic groups. However, further work is needed to understand the putative inverse correlation of genetic risk for hyperlipidemia and T2D risk and to develop ethnic-specific GRSs.

Indexed as

Genome-Wide Association StudyBlack or African AmericanDiabetes Mellitus, Type 2EthnicityGenetic TestingHispanic or LatinoHumansRisk FactorsWhite People

Identifiers

PMID24905067
PMCPMC4154088
OpenAlexW2020384330

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.