Evidence map›Paper›PMID 28509690›Full record

ReviewCurrent opinion in endocrinology, diabetes, and obesity2017

Genetics and its potential to improve type 1 diabetes care.

Stephen S Rich

Abstract readReview
In one paragraph

Review in Current opinion in endocrinology, diabetes, and obesity, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Genetics of diabetes.World journal of diabetes · 2023
    Review
  6. Article
  7. Review
  8. Type 1 diabetes: genes associated with disease development.Central-European journal of immunology · 2020
    Review
  9. Review
  10. Prediction and prevention of type 1 diabetes in children.Clinical pediatric endocrinology : case reports and clinical investigations : official journal of the Japanese Society for Pediatric Endocrinology · 2019
    Article
  11. 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.

Stephen S RichCenter for Public Health Genomics and Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA.
University of Virginia · US

Funding

Type 1 Diabetes Genetics ConsortiumU01DK062418 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI RICH, STEPHEN S. · 2002 to 2007
$59.8M
NIDDK NIH HHS U01 DK062418Wellcome Trust
6 · The paper itself

Abstract

purpose of reviewThe genetic basis of type 1 diabetes (T1D) is being characterized through DNA sequence variation and cell type specificity. This review discusses the current understanding of the genes and variants implicated in risk of T1D and how genetic information can be used in prediction, intervention and components of clinical care. RECENT

findingsFine mapping and functional studies has provided resolution of the heritable basis of T1D risk, incorporating novel insights on the dominant role of human leukocyte antigen (HLA) genes as well as the lesser impact of non-HLA genes. Evaluation of T1D-associated single nucleotide polymorphisms (SNPs), there is enrichment of genetic effects restricted to specific immune cell types (CD4 and CD8 T cells, CD19 B cells and CD34 stem cells), suggesting pathways to improved prediction. In addition, T1D-associated SNPs have been used to generate genetic risk scores (GRS) as a tool to distinguish T1D from type 2 diabetes (T2D) and to provide prediagnostic data to target those for autoimmunity screening (e.g. islet autoantibodies) as a prelude for continuous monitoring and entry into intervention trials. SUMMARY: Genetic susceptibility accounts for nearly one-half of the risk for T1D. Although the T1D-associated SNPs in white populations account for nearly 90% of the genetic risk, with high sensitivity and specificity, the low prevalence of T1D makes the T1D GRS of limited utility. However, identifying those with highest genetic risk may permit early and targeted immune monitoring to diagnose T1D months prior to clinical onset.

Indexed as

Molecular Diagnostic TechniquesPrecision MedicineQuality ImprovementDiabetes Mellitus, Type 1Disease ProgressionGenetic Predisposition to DiseaseGenetic TestingHumansPolymorphism, Single NucleotideRisk Factors

Identifiers

PMID28509690
PMCPMC6107086
OpenAlexW2615881070

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.