Cited by 140Diabetes Management and ResearchDiabetes and associated disordersDiabetes, Cardiovascular Risks, and Lipoproteins

A novel diabetes typology: towards precision diabetology from pathogenesis to treatment

Open access
Herder, Christian, Roden, Michael·2022·Diabetologia

Abstract

The current classification of diabetes, based on hyperglycaemia, islet-directed antibodies and some insufficiently defined clinical features, does not reflect differences in aetiological mechanisms and in the clinical course of people with diabetes. This review discusses evidence from recent studies addressing the complexity of diabetes by proposing novel subgroups (subtypes) of diabetes. The most widely replicated and validated approach identified, in addition to severe autoimmune diabetes, four subgroups designated severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes and mild age-related diabetes subgroups. These subgroups display distinct patterns of clinical features, disease progression and onset of comorbidities and complications, with severe insulin-resistant diabetes showing the highest risk for cardiovascular, kidney and fatty liver diseases. While it has been suggested that people in these subgroups would benefit from stratified treatments, RCTs are required to assess the clinical utility of any reclassification effort. Several methodological and practical issues also need further study: the statistical approach used to define subgroups and derive recommendations for diabetes care; the stability of subgroups over time; the optimal dataset (e.g. phenotypic vs genotypic) for reclassification; the transethnic generalisability of findings; and the applicability in clinical routine care. Despite these open questions, the concept of a new classification of diabetes has already allowed researchers to gain more insight into the colourful picture of diabetes and has stimulated progress in this field so that precision diabetology may become reality in the future.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s00125-021-05625-x

Cites

69 of 69 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Different subtypes/endotypes/clusters of T2D are associated with different risks of disease progression, with particularly high risk for MASLD/MASH progression in individuals with severe insulin resistance.

    “Different subtypes/endotypes/clusters of T2D are associated with different risks of disease progression, 58,59 with particularly high risk for MASLD/MASH progression in those individuals with severe insulin resistance.”

    From EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD). (2024) · cites this paper as [59]

    In “Diabetes subgroups” (Table 1; page not supplied), the paper reports that T2D subgroups differ in complication risk and that the severe insulin-resistant subgroup has the highest NAFLD prevalence and fibrosis score. “Genetic predisposition” links this subgroup to possible NAFLD progression to fibrosis. It does not establish a particularly high risk of MASLD/MASH progression specifically; its progression discussion is narrower and qualified. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [70]Mahajan A Taliun D Thurner M Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps Nat Genet 2018 50 11 1505 1513 10.1038/s41588-018-0241-6 30297969 PMC6287706 · DOI · Paper page

Cited by

Sorted by citations

Authors
Herder, C., & Roden, M.
Affiliations
Düsseldorf University Hospital (DE)
Corresponding author
  • Herder, Christian
  • Roden, Michael
Venue
Diabetologia
Published
2022-01-04
Volume
65
Issue
11
Pages
1770-1781
ISSN
  • 0012-186X (ISSN-L)
  • 1432-0428
OpenAlex
W4206342425
Cited by
140
References
69
Citations by year
2026: 21 · 2025: 37 · 2024: 34 · 2023: 33 · 2022: 15
FWCI
4.24
Type
journal article
Language
en
Open access
Locations
  • Diabetologia (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion, cc-by)
Funders
  • German Center for Diabetes Research
  • German Federal Ministry of Education and Research
  • German Federal Ministry of Health
  • Ministry of Culture and Science of the State of North Rhine-Westphalia
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Keywords
diabetes classification, diabetes subtypes, autoimmune diabetes, insulin-deficient diabetes, obesity-related diabetes, age-related diabetes, pathogenesis, diabetes complications, cardiovascular risk, diabetic nephropathy, hepatic steatosis, treatment stratification
MeSH terms
Diabetes Mellitus, Type 1, Humans, Hyperglycemia, Insulin Resistance, Comorbidity, Insulins

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review