Evidence map›Paper›PMID 35953726›Full record

ReviewDiabetologia2022

Phenotypic and genetic classification of diabetes.

Aaron J Deutsch, Emma Ahlqvist, Miriam S Udler

Abstract readReview
In one paragraph

Review in Diabetologia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

65 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
  3. Trial
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Genetic basis of Asian diabetes.Journal of diabetes investigation · 2026
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Reuniting diabetes through the islet coordinate framework.The lancet. Diabetes & endocrinology · 2026
    Article
  17. Article
  18. Review
  19. Review
  20. Review

5 more citing papers are in PubMed but not listed here.

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

3 authors.

Aaron J DeutschDiabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0001-6750-5335
Emma AhlqvistGenomics, Diabetes and Endocrinology, Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund University, Malmö, Sweden. emma.ahlqvist@med.lu.se.ORCID 0000-0002-6513-2384
Miriam S UdlerDiabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. mudler@mgh.harvard.edu.ORCID 0000-0003-3824-9162

Funding

TRAINING PROGRAM IN ENDOCRINOLOGY AND DIABETEST32DK007028 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Karen K Miller · 1986 to 2026
$18.5M
Clinical Implications of Genetically Defined Diabetes Subtypes and Application to Electronic Health Medical Record SystemsK23DK114551 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI UDLER, MIRIAM SARGON · 2017 to 2021
$1000k
Extension of Type 2 Diabetes Genetic Clustering to Populations of non-European AncestryR03DK131249 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI UDLER, MIRIAM SARGON · 2022 to 2023
$252k
NIDDK NIH HHS K23 DK114551NIDDK NIH HHS R03 DK131249NIDDK NIH HHS T32 DK007028
6 · The paper itself

Abstract

The historical subclassification of diabetes into predominantly types 1 and 2 is well appreciated to inadequately capture the heterogeneity seen in patient presentations, disease course, response to therapy and disease complications. This review summarises proposed data-driven approaches to further refine diabetes subtypes using clinical phenotypes and/or genetic information. We highlight the benefits as well as the limitations of these subclassification schemas, including practical barriers to their implementation that would need to be overcome before incorporation into clinical practice.

Indexed as

Diabetes Mellitus, Type 2HumansPhenotypePrecision MedicineCluster analysisDisease subtypesGeneticsMODYPersonalised medicinePolygenic scorePrecision medicineReviewType 1 diabetesType 2 diabetes

Identifiers

PMID35953726
PMCPMC9522707

What OpenQuestion 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 OpenQuestion graph.