Evidence map›Paper›PMID 28283684›Full record

ReviewDiabetologia2017

Pharmacogenetics in type 2 diabetes: precision medicine or discovery tool?

Jose C Florez

Open access · hybridAbstract readReview
PubMed Publisher
In one paragraph

Review in Diabetologia, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
7.4field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 62 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Observational
  6. Review
  7. Article
  8. Predicting diagnostic gene biomarkers associated with immune infiltration in patients with diabetes.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas · 2026
    Article
  9. Review
  10. Article
  11. Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023
    Review
  12. Review
  13. Association of GLP1R Polymorphisms With the Incretin Response.The Journal of clinical endocrinology and metabolism · 2022
    Article
  14. Review
  15. Effects of theJournal of diabetes and metabolic disorders · 2022
    Article
  16. Article
  17. Review
  18. Review
  19. Review
  20. Review
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

1 author at 1 institution in 1 country.

Jose C FlorezDiabetes Unit, Massachusetts General Hospital, Boston, MA, USA. jcflorez@partners.org.
Broad Institute · US

Funding

Proposal for the AMP T2D-GENES Data Coordination Center and Web PortalU01DK105554 · NIDDK · BROAD INSTITUTE, INC. · PI FLOREZ, JOSE CARLOS · 2015 to 2019
$16.8M
Fine-mapping and Characterization of Metabolic Loci in the DPP Outcomes StudyR01DK072041 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI FLOREZ, JOSE CARLOS · 2005 to 2017
$7.6M
Equipment Supplement for Discovery of Pharmacogenomic Biomarkers for OATP1B1 and OATP1B3R01GM117163 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FLOREZ, JOSE CARLOS, HEDDERSON, MONIQUE MARIE · 2015 to 2023
$5.5M
Integrative genomic, epigenetic and functional studies in diabetic kidney diseaseR01DK105154 · NIDDK · BROAD INSTITUTE, INC. · PI FLOREZ, JOSE CARLOS, HIRSCHHORN, JOEL N · 2016 to 2019
$3.0M
Mentoring Investigators on the Clinical Translation of Genetic Discoveries in Type 2 DiabetesK24DK110550 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI FLOREZ, JOSE CARLOS · 2016 to 2020
$812k
NIDDK NIH HHS K24 DK110550NIDDK NIH HHS R01 DK072041NIDDK NIH HHS R01 DK105154NIDDK NIH HHS U01 DK105554NIGMS NIH HHS R01 GM117163
6 · The paper itself

Abstract

In recent years, technological and analytical advances have led to an explosion in the discovery of genetic loci associated with type 2 diabetes. However, their ability to improve prediction of disease outcomes beyond standard clinical risk factors has been limited. On the other hand, genetic effects on drug response may be stronger than those commonly seen for disease incidence. Pharmacogenetic findings may aid in identifying new drug targets, elucidate pathophysiology, unravel disease heterogeneity, help prioritise specific genes in regions of genetic association, and contribute to personalised or precision treatment. In diabetes, precedent for the successful application of pharmacogenetic concepts exists in its monogenic subtypes, such as MODY or neonatal diabetes. Whether similar insights will emerge for the much more common entity of type 2 diabetes remains to be seen. As genetic approaches advance, the progressive deployment of candidate gene, large-scale genotyping and genome-wide association studies has begun to produce suggestive results that may transform clinical practice. However, many barriers to the translation of diabetes pharmacogenetic discoveries to the clinic still remain. This perspective offers a contemporary overview of the field with a focus on sulfonylureas and metformin, identifies the major uses of pharmacogenetics, and highlights potential limitations and future directions.

Indexed as

Diabetes Mellitus, Type 2Genome-Wide Association StudyHumansHypoglycemic AgentsMetforminPharmacogeneticsPolymorphism, Single NucleotidePrecision MedicineHypoglycemic AgentsMetforminGenome-wide association studiesMetforminPharmacogeneticsReviewSingle nucleotide polymorphismsSulfonylureasTCF7L2Type 2 diabetes

Identifiers

PMID28283684
OpenAlexW2884403234

What OpenQuestion holds

Texttitle and abstract
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.