Evidence map›Paper›PMID 22498248›Full record

ReviewBest practice & research. Clinical endocrinology & metabolism2012

Is genetic testing useful to predict type 2 diabetes?

Jason L Vassy, James B Meigs

Open access · greenAbstract readReview
In one paragraph

Review in Best practice & research. Clinical endocrinology & metabolism, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

35 citing papers in PubMed, 59 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Review
  5. Type 2 Diabetes Subtyping via Phenotype and Genotype Co-Learning.Studies in health technology and informatics · 2025
    Article
  6. Article
  7. TCF7L2 and FTO Polymorphisms Are Associated with Type 2 Diabetes Mellitus Risk in Kuwait.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2024
    Article
  8. Article
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  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
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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

2 authors at 1 institution in 1 country.

Jason L VassyGeneral Medicine Division, Massachusetts General Hospital, Boston, 02114, USA. jvassy@partners.org
James B Meigs
Harvard University · US

Funding

Common Genetic Variation and Quantitative Diabetes TraitsR01DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2008 to 2014
$5.0M
Epidemiology of Precursors to Type 2 DiabetesK24DK080140 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2007 to 2016
$1.9M
NIDDK NIH HHS K24 DK080140NIDDK NIH HHS L30 DK089597NIDDK NIH HHS R01 DK078616PHS HHS T32 HP12706
6 · The paper itself

Abstract

The early identification of individuals at risk for type 2 diabetes (T2D) enables prevention. Recent genome-wide association studies (GWAS) have added at least 40 genetic variants to the list of already well characterized T2D risk predictors, including family history, obesity, and elevated fasting plasma glucose levels. Although these variants can significantly predict T2D alone and as a part of genotype risk scores, they do not yet offer clinical discrimination beyond that achieved with common clinical measurements. Future progress on at least two research fronts may improve the predictive performance of genotype information. First, expanded GWAS efforts in non-European populations will allow targeted sequencing of risk loci and the identification of true causal variants. Second, studies with longer prediction time horizons may demonstrate that genotype information performs better than clinical risk predictors over a longer period of the life course. At present, however, genetic testing cannot be recommended for clinical T2D risk prediction in adults.

Indexed as

Genetic TestingAge FactorsBiomarkersDiabetes Mellitus, Type 2Family HealthGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideRisk FactorsTranscription Factor 7-Like 2 ProteinWhite PeopleBiomarkersTCF7L2 protein, humanTranscription Factor 7-Like 2 Protein

Identifiers

PMID22498248
PMCPMC4070012
OpenAlexW1978979824

What OpenQuestion holds

Textmetadata
LicenceTDM
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.