Evidence map›Paper›PMID 30377832›Full record

ReviewCurrent diabetes reports2018

Genetics of Monogenic Diabetes: Present Clinical Challenges.

Shivani Misra, Katharine R Owen

Abstract readReview
In one paragraph

Review in Current diabetes reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–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

33 citing papers in PubMed.

  1. Trial
  2. Genes · 2026
    Article
  3. Review
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  12. Review
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  17. Genome Editing and Human Pluripotent Stem Cell Technologies for in vitro Monogenic Diabetes Modeling.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022
    Review
  18. Article
  19. Review
  20. Congenital hyperinsulinism: 2 case reports with different rare variants in ABCC8.Annals of pediatric endocrinology & metabolism · 2021
    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

2 authors.

Shivani MisraDiabetes, Endocrinology & Metabolism, Imperial College London, Ground Floor Medical School, St Mary's Campus, Norfolk Place, London, W2 1PG, UK. smisra@imperial.ac.uk.
Katharine R OwenOxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, OX3 7LJ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewMonogenic forms of diabetes have specific treatments that differ from the standard care provided for type 1 and type 2 diabetes, making the appropriate diagnosis essential. In this review, we discuss current clinical challenges that remain, including improving case-finding strategies, particularly those that have transethnic applicability, and understanding the interpretation of genetic variants as pathogenic, with clinically meaningful impacts. RECENT

findingsBiomarker approaches to the stratification for genetic testing now appear to be most effective in identifying cases of monogenic diabetes, and use of genetic risk scores may also prove useful. However, applicability in all ethnic groups is lacking. Challenges remain in the classification of genes as diabetes-causing and the interpretation of genetic variants at the clinical interface. Since the discovery that genetic defects can cause neonatal or young-onset diabetes, multiple causal genes have been identified and there have been many advances in strategies to detect genetic forms of diabetes and their treatments. Approaches learnt from monogenic diabetes are now being translated to polygenic diabetes.

Indexed as

Genetic Predisposition to DiseaseBiomarkersDiabetes MellitusEthnicityGenetic TestingHumansMutationBiomarkersGenetic testingHNF1AMODYMonogenic diabetesNeonatal diabetes

Identifiers

PMID30377832
PMCPMC6209016

What OpenQuestion holds

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Registered trials

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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.