Evidence map›Paper›PMID 32537749›Full record

ArticleGenetic epidemiology2020

Validating the doubly weighted genetic risk score for the prediction of type 2 diabetes in the Lifelines and Estonian Biobank cohorts.

Katri Pärna, Harold Snieder, Kristi Läll, Krista Fischer, Ilja Nolte

Open access · hybridAbstract read
In one paragraph

Article in Genetic epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

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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

5 authors at 2 institutions in 2 countries.

Katri PärnaDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.ORCID 0000-0002-0013-6077
Harold SniederDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Kristi LällInstitute of Genomics, University of Tartu, Tartu, Estonia.
Krista FischerInstitute of Genomics, University of Tartu, Tartu, Estonia.
Ilja NolteDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
University Medical Center Groningen · NLUniversity of Tartu · EE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As many cases of type 2 diabetes (T2D) are likely to remain undiagnosed, better tools for early detection of high-risk individuals are needed to prevent or postpone the disease. We investigated the value of the doubly weighted genetic risk score (dwGRS) for the prediction of incident T2D in the Lifelines and Estonian Biobank (EstBB) cohorts. The dwGRS uses an additional weight for each single nucleotide polymorphism in the risk score, to correct for "Winner's curse" bias in the effect size estimates. The traditional (single-weighted genetic risk score; swGRS) and dwGRS were calculated for participants in Lifelines (n = 12,018) and EstBB (n = 34,129). The dwGRS was found to have stronger association with incident T2D (hazard ratio [HR] = 1.26 [95% confidence interval: 1.10-1.43] and HR = 1.35 [1.28-1.42]) compared to the swGRS (HR = 1.21 [1.07-1.38] and HR = 1.25 [1.19-1.32]) in Lifelines and EstBB, respectively. Comparing the 5-year predicted risks from the models with and without the dwGRS, the continuous net reclassification index was 0.140 (0.034-0.243; p = .009 Lifelines), and 0.257 (0.194-0.319; p < 2 × 10

Indexed as

Biological Specimen BanksGenetic Predisposition to DiseaseAdolescentAdultAgedAged, 80 and overCohort StudiesDiabetes Mellitus, Type 2EstoniaFemaleHumansIncidenceMaleMiddle AgedModels, GeneticPolymorphism, Single Nucleotidegenetic risk scoreincidencepersonalized predictiontype 2 diabetes

Identifiers

PMID32537749
PMCPMC7496366
OpenAlexW3035387029

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.