Evidence map›Paper›PMID 27189761›Full record

ReviewCurrent diabetes reports2016

Genetics of Type 2 Diabetes: the Power of Isolated Populations.

Mette Korre Andersen, Casper-Emil Tingskov Pedersen, Ida Moltke, Torben Hansen, Anders Albrechtsen, Niels Grarup

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current diabetes reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. AnHGG advances · 2022
    Article
  3. Article
  4. DNA Methylation and Type 2 Diabetes: Novel Biomarkers for Risk Assessment?International journal of molecular sciences · 2021
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2019
    Review
  11. Article
  12. Review
  13. Birth weight and type 2 diabetes: A meta-analysis.Experimental and therapeutic medicine · 2017
    Article
  14. Review
  15. 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

6 authors.

Mette Korre AndersenThe Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark.
Casper-Emil Tingskov PedersenThe Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
Ida MoltkeThe Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
Torben HansenThe Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark.
Anders AlbrechtsenThe Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
Niels GrarupThe Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2100, Copenhagen, Denmark. niels.grarup@sund.ku.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes (T2D) affects millions of people worldwide. Improving the understanding of the underlying mechanisms and ultimately improving the treatment strategies are, thus, of great interest. To achieve this, identification of genetic variation predisposing to T2D is important. A large number of variants have been identified in large outbred populations, mainly from Europe and Asia. However, to elucidate additional variation, isolated populations have a number of advantageous properties, including increased amounts of linkage disequilibrium, and increased probability for presence of high frequency disease-associated variants due to genetic drift. Collectively, this increases the statistical power to detect association signals in isolated populations compared to large outbred populations. In this review, we elaborate on why isolated populations are a powerful resource for the identification of complex disease variants and describe their contributions to the understanding of the genetics of T2D.

Indexed as

Diabetes Mellitus, Type 2Genetic VariationGenome-Wide Association StudyHumansLinkage DisequilibriumRisk FactorsGenetic driftGenome-wide association studyIsolated populationsLinkage disequilibriumStatistical powerType 2 diabetes

Identifiers

What OpenQuestion holds

Textmetadata
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.